DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Ren-Kou; Qafoku, Nikolla; Van Ranst, Eric
2016-01-25
This review paper attempts to summarize the progress made in research efforts conducted over the last years to study the surface chemical properties of the tropical and subtropical soils, usually called variable charge soils, and the way they response to different management practices. The paper is composed of an introductory section that provides a brief discussion on the surface chemical properties of these soils, and five other review sections. The focus of these sections is on the evolution of surface chemical properties during the development of the variable charge properties (second section), interactions between oppositely charged particles and the resultingmore » effects on the soil properties and especially on soil acidity (third section), the surface effects of low molecular weight organic acids sorbed to mineral surfaces and the chemical behavior of aluminum (fourth section), and the crop straw derived biochar induced changes of the surface chemical properties of these soils (fifth section). A discussion on the effect of climate change variables on the properties of the variable charge soils is included at the end of this review paper (sixth section).« less
NASA Astrophysics Data System (ADS)
Vanwalleghem, T.; Román, A.; Giraldez, J. V.
2016-12-01
There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.
NASA Technical Reports Server (NTRS)
Brunet, Y.; Vauclin, M.
1985-01-01
The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.
Field-scale apparent soil electrical conductivity
USDA-ARS?s Scientific Manuscript database
Soils are notoriously spatially heterogeneous and many soil properties (e.g., salinity, water content, trace element concentration, etc.) are temporally variable, making soil a complex media. Spatial variability of soil properties has a profound influence on agricultural and environmental processes ...
Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies
NASA Technical Reports Server (NTRS)
Sullivan, Dana; Shaw, Joey; Rickman, Doug
2005-01-01
Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.
Soil properties discriminating Araucaria forests with different disturbance levels.
Bertini, Simone Cristina Braga; Azevedo, Lucas Carvalho Basilio; Stromberger, Mary E; Cardoso, Elke Jurandy Bran Nogueira
2015-04-01
Soil biological, chemical, and physical properties can be important for monitoring soil quality under one of the most spectacular vegetation formation on Atlantic Forest Biome, the Araucaria Forest. Our aim was to identify a set of soil variables capable of discriminating between disturbed, reforested, and native Araucaria forest soils such that these variables could be used to monitor forest recovery and maintenance. Soil samples were collected at dry and rainy season under the three forest types in two state parks at São Paulo State, Brazil. Soil biological, chemical, and physical properties were evaluated to verify their potential to differentiate the forest types, and discriminant analysis was performed to identify the variables that most contribute to the differentiation. Most of physical and chemical variables were sensitive to forest disturbance level, but few biological variables were significantly different when comparing native, reforested, and disturbed forests. Despite more than 20 years following reforestation, the reforested soils were chemically and biologically distinct from native and disturbed forest soils, mainly because of the greater acidity and Al3+ content of reforested soil. Disturbed soils, in contrast, were coarser in texture and contained greater concentrations of extractable P. Although biological properties are generally highly sensitive to disturbance and amelioration efforts, the most important soil variables to discriminate forest types in both seasons included Al3+, Mg2+, P, and sand, and only one microbial attribute: the NO2- oxidizers. Therefore, these five variables were the best candidates, of the variables we employed, for monitoring Araucaria forest disturbance and recovery.
REGIONAL SOIL WATER RETENTION IN THE CONTIGUOUS US: SOURCES OF VARIABILITY AND VOLCANIC SOIL EFFECTS
Water retention of mineral soil is often well predicted using algorithms (pedotransfer functions) with basic soil properties but the spatial variability of these properties has not been well characterized. A further source of uncertainty is that water retention by volcanic soils...
Thomas, Matthew A.; Mirus, Benjamin B.; Collins, Brian D.; Lu, Ning; Godt, Jonathan W.
2018-01-01
Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.
Exploring the spatial variability of soil properties in an Alfisol Catena
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.
Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less
NASA Astrophysics Data System (ADS)
Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.
2017-12-01
There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.
NASA Astrophysics Data System (ADS)
Fan, Linfeng; Lehmann, Peter; Or, Dani
2015-04-01
Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.
A Brief History of the use of Electromagnetic Induction Techniques in Soil Survey
NASA Astrophysics Data System (ADS)
Brevik, Eric C.; Doolittle, James
2017-04-01
Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools and increased the amount and types of data that can be gathered with a single pass. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales. The future should witness a greater use of multiple-frequency and multiple-coil EMI sensors and integration with other sensors to assess the spatial variability of soil properties. Data analysis will be improved with advanced processing and presentation systems and more sophisticated geostatistical modeling algorithms will be developed and used to interpolate EMI data, improve the resolution of subsurface features, and assess soil properties.
NASA Astrophysics Data System (ADS)
Zhao, Yongcun; Xu, Xianghua; Darilek, Jeremy Landon; Huang, Biao; Sun, Weixia; Shi, Xuezheng
2009-05-01
Topsoil samples (0-20 cm) ( n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.
The History of Electromagnetic Induction Techniques in Soil Survey
NASA Astrophysics Data System (ADS)
Brevik, Eric C.; Doolittle, Jim
2014-05-01
Electromagnetic induction (EMI) has been used to characterize the spatial variability of soil properties since the late 1970s. Initially used to assess soil salinity, the use of EMI in soil studies has expanded to include: mapping soil types; characterizing soil water content and flow patterns; assessing variations in soil texture, compaction, organic matter content, and pH; and determining the depth to subsurface horizons, stratigraphic layers or bedrock, among other uses. In all cases the soil property being investigated must influence soil apparent electrical conductivity (ECa) either directly or indirectly for EMI techniques to be effective. An increasing number and diversity of EMI sensors have been developed in response to users' needs and the availability of allied technologies, which have greatly improved the functionality of these tools. EMI investigations provide several benefits for soil studies. The large amount of georeferenced data that can be rapidly and inexpensively collected with EMI provides more complete characterization of the spatial variations in soil properties than traditional sampling techniques. In addition, compared to traditional soil survey methods, EMI can more effectively characterize diffuse soil boundaries and identify included areas of dissimilar soils within mapped soil units, giving soil scientists greater confidence when collecting spatial soil information. EMI techniques do have limitations; results are site-specific and can vary depending on the complex interactions among multiple and variable soil properties. Despite this, EMI techniques are increasingly being used to investigate the spatial variability of soil properties at field and landscape scales.
Othman, Rashidi; Hasni, Shah Irani; Baharuddin, Zainul Mukrim; Hashim, Khairusy Syakirin Has-Yun; Mahamod, Lukman Hakim
2017-10-01
Slope failure has become a major concern in Malaysia due to the rapid development and urbanisation in the country. It poses severe threats to any highway construction industry, residential areas, natural resources and tourism activities. The extent of damages that resulted from this catastrophe can be lessened if a long-term early warning system to predict landslide prone areas is implemented. Thus, this study aims to characterise the relationship between Oxisols properties and soil colour variables to be manipulated as key indicators to forecast shallow slope failure. The concentration of each soil property in slope soil was evaluated from two different localities that consist of 120 soil samples from stable and unstable slopes located along the North-South Highway (PLUS) and East-West Highway (LPT). Analysis of variance established highly significant difference (P < 0.0001) between the locations, the total organic carbon (TOC), soil pH, cation exchange capacity (CEC), soil texture, soil chromaticity and all combinations of interactions. The overall CIELAB analysis leads to the conclusion that the CIELAB variables lightness L*, c* (Chroma) and h* (Hue) provide the most information about soil colour and other related soil properties. With regard to the relationship between colour variables and soil properties, the analysis detected that soil texture, organic carbon, iron oxide and aluminium concentration were the key factors that strongly correlate with soil colour variables at the studied area. Indicators that could be used to predict shallow slope failure were high value of L*(62), low values of c* (20) and h* (66), low concentration of iron (53 mg kg -1 ) and aluminium oxide (37 mg kg -1 ), low soil TOC (0.5%), low CEC (3.6 cmol/kg), slightly acidic soil pH (4.9), high amount of sand fraction (68%) and low amount of clay fraction (20%).
Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli
2017-10-01
Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1 yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.
2012-04-01
Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.
Spatial variability of soil properties and soil erodibility in the Alqueva reservoir watershed
NASA Astrophysics Data System (ADS)
Ferreira, V.; Panagopoulos, T.; Andrade, R.; Guerrero, C.; Loures, L.
2015-04-01
The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this end, three areas representative of different land uses (agroforestry grassland, lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while the K factor increased with intensive cultivation. The HJ-Biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. The K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.
Spatial variability of soil properties and soil erodibility in the Alqueva dam watershed, Portugal
NASA Astrophysics Data System (ADS)
Ferreira, V.; Panagopoulos, T.; Andrade, R.; Guerrero, C.; Loures, L.
2015-01-01
The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this, three areas representative of different land uses (agroforestry grassland, Lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while K factor increased with intensive cultivation. The HJ-biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.
The Use of Electromagnetic Induction Techniques for Soil Mapping
NASA Astrophysics Data System (ADS)
Brevik, Eric C.; Doolittle, Jim
2015-04-01
Soils have high natural spatial variability. This has been recognized for a long time, and many methods of mapping that spatial variability have been investigated. One technique that has received considerable attention over the last ~30 years is electromagnetic induction (EMI). Particularly when coupled with modern GPS and GIS systems, EMI techniques have allowed the rapid and relatively inexpensive collection of large spatially-related data sets that can be correlated to soil properties that either directly or indirectly influence electrical conductance in the soil. Soil electrical conductivity is directly controlled by soil water content, soluble salt content, clay content and mineralogy, and temperature. A wide range of indirect controls have been identified, such as soil organic matter content and bulk density; both influence water relationships in the soil. EMI techniques work best in areas where there are large changes in one soil property that influences soil electrical conductance, and don't work as well when soil properties that influence electrical conductance are largely homogenous. This presentation will present examples of situations where EMI techniques were successful as well as a couple of examples of situations where EMI was not so useful in mapping the spatial variability of soil properties. Reasons for both the successes and failures will be discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane
2007-01-01
The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less
NASA Astrophysics Data System (ADS)
Bang, Jisu
Field-scale characterization of soil spatial variability using remote sensing technology has potential for achieving the successful implementation of site-specific management (SSM). The objectives of this study were to: (i) examine the spatial relationships between apparent soil electrical conductivity (EC a) and soil chemical and physical properties to determine if EC a could be useful to characterize soil properties related to crop productivity in the Coastal Plain and Piedmont of North Carolina; (ii) evaluate the effects of in-situ soil moisture variation on ECa mapping as a basis for characterization of soil spatial variability and as a data layer in cluster analysis as a means of delineating sampling zones; (iii) evaluate clustering approaches using different variable sets for management zone delineation to characterize spatial variability in soil nutrient levels and crop yields. Studies were conducted in two fields in the Piedmont and three fields in the Coastal Plain of North Carolina. Spatial measurements of ECa via electromagnetic induction (EMI) were compared with soil chemical parameters (extractable P, K, and micronutrients; pH, cation exchange capacity [CEC], humic matter or soil organic matter; and physical parameters (percentage sand, silt, and clay; and plant-available water [PAW] content; bulk density; cone index; saturated hydraulic conductivity [Ksat] in one of the coastal plain fields) using correlation analysis across fields. We also collected ECa measurements in one coastal plain field on four days with significantly different naturally occurring soil moisture conditions measured in five increments to 0.75 m using profiling time-domain reflectometry probes to evaluate the temporal variability of ECa associated with changes in in-situ soil moisture content. Nonhierarchical k-means cluster analysis using sensor-based field attributes including vertical ECa, near-infrared (NIR) radiance of bare-soil from an aerial color infrared (CIR) image, elevation, slope, and their combinations was performed to delineate management zones. The strengths and signs of the correlations between ECa and measured soil properties varied among fields. Few strong direct correlations were found between ECa and the soil chemical and physical properties studied (r2 < 0.50), but correlations improved considerably when zone mean ECa and zone means of selected soil properties among ECa zones were compared. The results suggested that field-scale ECa survey is not able to directly predict soil nutrient levels at any specific location, but could delimit distinct zones of soil condition among which soil nutrient levels differ, providing an effective basis for soil sampling on a zone basis. (Abstract shortened by UMI.)
NASA Astrophysics Data System (ADS)
Becker, R.; Gebremichael, M.; Marker, M.
2015-12-01
Soil moisture is one of the main input variables for hydrological models. However due to the high spatial and temporal variability of soil properties it is often difficult to obtain accurate soil information at the required resolution. The new satellite SMAP promises to deliver soil moisture information at higher resolutions and could therefore improve the results of hydrological models. Nevertheless it still has to be investigated how precisely the SMAP soil moisture data can be used to delineate rainfall-runoff generation processes and if SMAP imagery can significantly improve the results of surface runoff models. Important parameters to understand the spatiotemporal distribution of soil humidity are infiltration and hydraulic conductivities apart from soil texture and macrostructure. During the SMAPVEX15-field campaign data on hydraulic conductivity and infiltration rates is collected in the Walnut Gulch Experimental Watershed (WGEW) in Southeastern Arizona in order to analyze the spatiotemporal variability of soil hydraulic properties. A Compact Constant Head Permeameter is used for in situ measurements of saturated hydraulic conductivity within the soil layers and a Hood Infiltrometer is used to determine infiltration rates at the undisturbed soil surface. Sampling sites were adjacent to the USDA-ARS meteorological and soil moisture measuring sites in the WGEW to take advantage of the long-term database of soil and climate data. Furthermore a sample plot of 3x3km was selected, where the spatial variability of soil hydraulic properties within a SMAP footprint was investigated. The results of the ground measurement based analysis are then compared with the remote sensing data derived from SMAP and aircraft-based microwave data to determine how well these spatiotemporal variations are captured by the remotely sensed data with the final goal of evaluating the use of future satellite soil moisture products for the improvement of rainfall runoff models. The results reveal several interesting features on the spatiotemporal variability of soil moisture at multiple scales, and the capabilities and limitations of remote sensing derived products in reproducing them.
State-Space Estimation of Soil Organic Carbon Stock
NASA Astrophysics Data System (ADS)
Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.
2014-04-01
Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.
NASA Astrophysics Data System (ADS)
Mansuy, N. R.; Paré, D.; Thiffault, E.
2015-12-01
Large-scale mapping of soil properties is increasingly important for environmental resource management. Whileforested areas play critical environmental roles at local and global scales, forest soil maps are typically at lowresolution.The objective of this study was to generate continuous national maps of selected soil variables (C, N andsoil texture) for the Canadian managed forest landbase at 250 m resolution. We produced these maps using thekNN method with a training dataset of 538 ground-plots fromthe National Forest Inventory (NFI) across Canada,and 18 environmental predictor variables. The best predictor variables were selected (7 topographic and 5 climaticvariables) using the Least Absolute Shrinkage and Selection Operator method. On average, for all soil variables,topographic predictors explained 37% of the total variance versus 64% for the climatic predictors. Therelative root mean square error (RMSE%) calculated with the leave-one-out cross-validation method gave valuesranging between 22% and 99%, depending on the soil variables tested. RMSE values b 40% can be considered agood imputation in light of the low density of points used in this study. The study demonstrates strong capabilitiesfor mapping forest soil properties at 250m resolution, compared with the current Soil Landscape of CanadaSystem, which is largely oriented towards the agricultural landbase. The methodology used here can potentiallycontribute to the national and international need for spatially explicit soil information in resource managementscience.
Bodner, G; Scholl, P; Loiskandl, W; Kaul, H-P
2013-08-01
Structural porosity is a decisive property for soil productivity and soil environmental functions. Hydraulic properties in the structural range vary over time in response to management and environmental influences. Although this is widely recognized, there are few field studies that determine dominant driving forces underlying hydraulic property dynamics. During a three year field experiment we measured temporal variability of soil hydraulic properties by tension infiltrometry. Soil properties were characterized by hydraulic conductivity, effective macroporosity and Kosugi's lognormal pore size distribution model. Management related influences comprised three soil cover treatment (mustard and rye vs. fallow) and an initial mechanical soil disturbance with a rotary harrow. Environmental driving forces were derived from meteorological and soil moisture data. Soil hydraulic parameters varied over time by around one order of magnitude. The coefficient of variation of soil hydraulic conductivity K(h) decreased from 69.5% at saturation to 42.1% in the more unsaturated range (- 10 cm pressure head). A slight increase in the Kosugi parameter showing pore heterogeneity was observed under the rye cover crop, reflecting an enhanced structural porosity. The other hydraulic parameters were not significantly influenced by the soil cover treatments. Seedbed preparation with a rotary harrow resulted in a fourfold increase in macroporosity and hydraulic conductivity next to saturation, and homogenized the pore radius distribution. Re-consolidation after mechanical loosening lasted over 18 months until the soil returned to its initial state. The post-tillage trend of soil settlement could be approximated by an exponential decay function. Among environmental factors, wetting-drying cycles were identified as dominant driving force explaining short term hydraulic property changes within the season (r 2 = 0.43 to 0.59). Our results suggested that beside considering average management induced changes in soil properties (e.g. cover crop introduction), a dynamic approach to hydrological modeling is required to capture over-seasonal (tillage driven) and short term (environmental driven) variability in hydraulic parameters.
USDA-ARS?s Scientific Manuscript database
Soil properties are thought to affect annual plant productivity in rangelands, and thus soil variables that are consistently correlated with variation in plant biomass may be general indicators of rangeland health. Here we measured several soil properties (e.g. aggregate stability, organic carbon, ...
Predictor variable resolution governs modeled soil types
USDA-ARS?s Scientific Manuscript database
Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...
Farm-scale variation of soil quality indices and association with edaphic properties
USDA-ARS?s Scientific Manuscript database
Soil organisms are indicators of dynamic soil quality because their community structure and population density are sensitive to management changes. However, edaphic properties can also affect soil organisms and high spatial variability can confound their utility for soil evaluation. In the present...
Simulating maize yield and biomass with spatial variability of soil field capacity
USDA-ARS?s Scientific Manuscript database
Spatial variability in field soil water and other properties is a challenge for system modelers who use only representative values for model inputs, rather than their distributions. In this study, we compared simulation results from a calibrated model with spatial variability of soil field capacity ...
Timber Harvesting Effects on Spatial Variability of Southeastern U.S. Piedmont Soil Properties
J.N. Shaw; Emily A. Carter
2002-01-01
Site-specific forestry requires detailed characterization of the spatial distribution of forest soil properties and the magnitude of harvesting impacts in order to prescribe appropriate management schemes. Furthermore, evaluation of the effects of timber harvesting on soil properties conducted on a landscape scale improves the interpretive value of soil survey data....
Bodner, G.; Scholl, P.; Loiskandl, W.; Kaul, H.-P.
2013-01-01
Structural porosity is a decisive property for soil productivity and soil environmental functions. Hydraulic properties in the structural range vary over time in response to management and environmental influences. Although this is widely recognized, there are few field studies that determine dominant driving forces underlying hydraulic property dynamics. During a three year field experiment we measured temporal variability of soil hydraulic properties by tension infiltrometry. Soil properties were characterized by hydraulic conductivity, effective macroporosity and Kosugi's lognormal pore size distribution model. Management related influences comprised three soil cover treatment (mustard and rye vs. fallow) and an initial mechanical soil disturbance with a rotary harrow. Environmental driving forces were derived from meteorological and soil moisture data. Soil hydraulic parameters varied over time by around one order of magnitude. The coefficient of variation of soil hydraulic conductivity K(h) decreased from 69.5% at saturation to 42.1% in the more unsaturated range (− 10 cm pressure head). A slight increase in the Kosugi parameter showing pore heterogeneity was observed under the rye cover crop, reflecting an enhanced structural porosity. The other hydraulic parameters were not significantly influenced by the soil cover treatments. Seedbed preparation with a rotary harrow resulted in a fourfold increase in macroporosity and hydraulic conductivity next to saturation, and homogenized the pore radius distribution. Re-consolidation after mechanical loosening lasted over 18 months until the soil returned to its initial state. The post-tillage trend of soil settlement could be approximated by an exponential decay function. Among environmental factors, wetting-drying cycles were identified as dominant driving force explaining short term hydraulic property changes within the season (r2 = 0.43 to 0.59). Our results suggested that beside considering average management induced changes in soil properties (e.g. cover crop introduction), a dynamic approach to hydrological modeling is required to capture over-seasonal (tillage driven) and short term (environmental driven) variability in hydraulic parameters. PMID:24748683
On the role of "internal variability" on soil erosion assessment
NASA Astrophysics Data System (ADS)
Kim, Jongho; Ivanov, Valeriy; Fatichi, Simone
2017-04-01
Empirical data demonstrate that soil loss is highly non-unique with respect to meteorological or even runoff forcing and its frequency distributions exhibit heavy tails. However, all current erosion assessments do not describe the large associated uncertainties of temporal erosion variability and make unjustified assumptions by relying on central tendencies. Thus, the predictive skill of prognostic models and reliability of national-scale assessments have been repeatedly questioned. In this study, we attempt to reveal that the high variability in soil losses can be attributed to two sources: (1) 'external variability' referring to the uncertainties originating at macro-scale, such as climate, topography, and land use, which has been extensively studied; (2) 'geomorphic internal variability' referring to the micro-scale variations of pedologic properties (e.g., surface erodibility in soils with multi-sized particles), hydrologic properties (e.g., soil structure and degree of saturation), and hydraulic properties (e.g., surface roughness and surface topography). Using data and a physical hydraulic, hydrologic, and erosion and sediment transport model, we show that the geomorphic internal variability summarized by spatio-temporal variability in surface erodibility properties is a considerable source of uncertainty in erosion estimates and represents an overlooked but vital element of geomorphic response. The conclusion is that predictive frameworks of soil erosion should embed stochastic components together with deterministic assessments, if they do not want to largely underestimate uncertainty. Acknowledgement: This study was supported by the Basic Science Research Program of the National Research Foundation of Korea funded by the Ministry of Education (2016R1D1A1B03931886).
Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol
NASA Astrophysics Data System (ADS)
Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva
2013-04-01
Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.
Li, Tao; Hao, Xinmei; Kang, Shaozhong
2016-01-01
There is a growing interest in precision viticulture with the development of global positioning system and geographical information system technologies. Limited information is available on spatial variation of bud behavior and its possible association with soil properties. The objective of this study was to investigate spatial variability of bud burst percentage and its association with soil properties based on 2-year experiments at a vineyard of arid northwest China. Geostatistical approach was used to describe the spatial variation in bud burst percentage within the vineyard. Partial least square regressions (PLSRs) of bud burst percentage with soil properties were used to evaluate the contribution of soil properties to overall spatial variability in bud burst percentage for the high, medium and low bud burst percentage groups. Within the vineyard, the coefficient of variation (CV) of bud burst percentage was 20% and 15% for 2012 and 2013 respectively. Bud burst percentage within the vineyard showed moderate spatial variability, and the overall spatial pattern of bud burst percentage was similar between the two years. Soil properties alone explained 31% and 37% of the total spatial variation respectively for the low group of 2012 and 2013, and 16% and 24% for the high group of 2012 and 2013 respectively. For the low group, the fraction of variations explained by soil properties was found similar between the two years, while there was substantial difference for the high group. The findings are expected to lay a good foundation for developing remedy measures in the areas with low bud burst percentage, thus in turn improving the overall grape yield and quality. PMID:27798692
Sample sizes to control error estimates in determining soil bulk density in California forest soils
Youzhi Han; Jianwei Zhang; Kim G. Mattson; Weidong Zhang; Thomas A. Weber
2016-01-01
Characterizing forest soil properties with high variability is challenging, sometimes requiring large numbers of soil samples. Soil bulk density is a standard variable needed along with element concentrations to calculate nutrient pools. This study aimed to determine the optimal sample size, the number of observation (n), for predicting the soil bulk density with a...
Effects of spatial variability of soil hydraulic properties on water dynamics
NASA Astrophysics Data System (ADS)
Gumiere, Silvio Jose; Caron, Jean; Périard, Yann; Lafond, Jonathan
2013-04-01
Soil hydraulic properties may present spatial variability and dependence at the scale of watersheds or fields even in man-made single soil structures, such as cranberry fields. The saturated hydraulic conductivity (Ksat) and soil moisture curves were measured at two depths for three cranberry fields (about 2 ha) at three different sites near Québec city, Canada. Two of the three studied fields indicate strong spatial dependence for Ksat values and soil moisture curves both in horizontal and vertical directions. In the summer of 2012, the three fields were equipped with 55 tensiometers installed at a depth of 0.10 m in a regular grid. About 20 mm of irrigation water were applied uniformly by aspersion to the fields, raising soil water content to near saturation condition. Soil water tension was measured once every hour during seven days. Geostatistical techniques such as co-kriging and cross-correlograms estimations were used to investigate the spatial dependence between variables. The results show that soil tension varied faster in high Ksat zones than in low Ksatones in the cranberry fields. These results indicate that soil water dynamic is strongly affected by the variability of saturated soil hydraulic conductivity, even in a supposed homogenous anthropogenic soil. This information may have a strong impact in irrigation management and subsurface drainage efficiency as well as other water conservation issues. Future work will involve 3D numerical modeling of the field water dynamics with HYDRUS software. The anticipated outcome will provide valuable information for the understanding of the effect of spatial variability of soil hydraulic properties on soil water dynamics and its relationship with crop production and water conservation.
Factors to consider in developing variable rate seeding prescriptions
USDA-ARS?s Scientific Manuscript database
Soil hydraulic properties influence many of the ecological functions of soil. The objectives of this study were to determine the influence of topsoil thickness on soil hydraulic properties for grain and perennial grass production systems. The experiment was carried out at the Soil Productivity Asses...
NASA Astrophysics Data System (ADS)
Bodner, G.; Loiskandl, W.; Kaul, H.-P.
2009-04-01
Soil structure is a dynamic property subject to numerous natural and human influences. It is recognized as fundamental for sustainable functioning of soil. Therefore knowledge of management impacts on the sensitive structural states of soil is decisive in order to avoid soil degradation. The stabilization of the soil's (macro)pore system and eventually the improvement of its infiltrability are essential to avoid runoff and soil erosion, particularly in view of an increasing probability of intense rainfall events. However structure-related soil properties generally have a high natural spatiotemporal variability that interacts with the potential influence of agricultural land use. This complicates a clear determination of management vs. environmental effects and requires adequate measurement methods, allowing a sufficient spatiotemporal resolution to estimate the impact of the targeted management factors within the natural dynamics of soil structure. A common method to assess structure-related soil hydraulic properties is tension infiltrometry. A major advantage of tension infiltrometer measurements is that no or only minimum soil disturbance is necessary and several structure-controlled water transmission properties can readily be derived. The method is more time- and cost-efficient compared to laboratory measurements of soil hydraulic properties, thus enabling more replications. Furthermore in situ measurements of hydraulic properties generally allow a more accurate reproduction of field soil water dynamics. The present study analyses the impact of two common agricultural management options on structure related hydraulic properties based on tension infiltrometer measurements. Its focus is the identification of the role of management within the natural spatiotemporal variability, particularly in respect to seasonal temporal dynamics. Two management approaches are analysed, (i) cover cropping as a "plant-based" agro-environmental measure, and (ii) tillage with different intensities including conventional tillage with a mouldboard plough, reduced tillage with a chisel plough and no-tillage. The results showed that the plant-based management measure of cover cropping had only minor influence on near-saturated hydraulic conductivity (kh) and flow weighted mean pore radius (λm). Substantial over-winter changes were found with a significant increase in kh and a reduction in the pore radius. A spatial trend in soil texture along the cover cropped slope resulted in a higher kh at lower pressure heads at the summit with higher fractions of coarse particles, while kh tended to be highest at the toeslope towards saturation. Cover crop management accounted for a maximum of 9.7% of the total variability in kh, with a decreasing impact towards the unsaturated range. A substantial difference to bare soil in the cover cropped treatments could be identified in relation to a stabilization of macro-pores over winter. The different tillage treatments had a substantial impact on near-saturated kh and pore radius. Although conventional tillage showed the highest values in kh and λm, settling of the soil after the ploughing event tended to reduce differences over time compared to the other tillage methods. The long-term no-tillage (10 years) however had the lowest values of kh at all measurement dates. The high contents of silt and fine sand probably resulted in soil densification that was not counterbalanced sufficiently by biological structure forming agents. The study could show that soil structure related hydraulic properties are subject to a substantial seasonal variability. A comprehensive assessment of agricultural measures such as tillage or cover cropping requires an estimate of these temporal dynamics and their interaction with the management strategies. Particularly for plant-based management measures such as cover cropping, which represent a less intense intervention in the structural states of the soil compared to tillage, this was evident, as the main mechanism revealed for this measure was structure stabilization over time. While spatial variability is mostly controlled in designed experiments, the role of temporal variability is often underestimated. From our study we concluded that (i) a proper understanding of processes involved in management effects on soil structure must take into consideration the dynamic nature of the respective soil properties, (ii) experimental planning for studies regarding management impacts on soil structure should allow an estimation of temporal variability, and (iii) for this purpose tension infiltrometry provides an efficient measurement tool to assess structure related soil hydraulic properties.
Fractal behavior of soil water storage at multiple depths
NASA Astrophysics Data System (ADS)
Ji, Wenjun; Lin, Mi; Biswas, Asim; Si, Bing C.; Chau, Henry W.; Cresswell, Hamish P.
2016-08-01
Spatiotemporal behavior of soil water is essential to understand the science of hydrodynamics. Data intensive measurement of surface soil water using remote sensing has established that the spatial variability of soil water can be described using the principle of self-similarity (scaling properties) or fractal theory. This information can be used in determining land management practices provided the surface scaling properties are kept at deep layers. The current study examined the scaling properties of sub-surface soil water and their relationship to surface soil water, thereby serving as supporting information for plant root and vadose zone models. Soil water storage (SWS) down to 1.4 m depth at seven equal intervals was measured along a transect of 576 m for 5 years in Saskatchewan. The surface SWS showed multifractal nature only during the wet period (from snowmelt until mid- to late June) indicating the need for multiple scaling indices in transferring soil water variability information over multiple scales. However, with increasing depth, the SWS became monofractal in nature indicating the need for a single scaling index to upscale/downscale soil water variability information. In contrast, all soil layers during the dry period (from late June to the end of the growing season in early November) were monofractal in nature, probably resulting from the high evapotranspirative demand of the growing vegetation that surpassed other effects. This strong similarity between the scaling properties at the surface layer and deep layers provides the possibility of inferring about the whole profile soil water dynamics using the scaling properties of the easy-to-measure surface SWS data.
Spatial and temporal variability of soil temperature, moisture and surface soil properties
NASA Technical Reports Server (NTRS)
Hajek, B. F.; Dane, J. H.
1993-01-01
The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.
Near Surface Investigation of Agricultural Soils using a Multi-Frequency Electromagnetic Sensor
NASA Astrophysics Data System (ADS)
Sadatcharam, K.; Unc, A.; Krishnapillai, M.; Cheema, M.; Galagedara, L.
2017-12-01
Electromagnetic induction (EMI) sensors have been used as precision agricultural tools over decades. They are being used to measure spatiotemporal variability of soil properties and soil stratification in the sense of apparent electrical conductivity (ECa). We mapped the ECa variability by horizontal coplanar (HCP) and by vertical coplanar (VCP) orientation of a multi-frequency EMI sensor and identified its interrelation with physical properties of soil. A broadband, multi-frequency handheld EMI sensor (GEM-2) was used on a loamy sand soil cultivated with silage-corn in western Newfoundland, Canada. Log and line spaced, three frequency ranges (weak, low, and high), based on the factory calibration were tested using HCP and VCP orientation to produce spatiotemporal data of ECa. In parallel, we acquired data on soil moisture content, texture and bulk density. We then assessed the statistical significance of the relationship between ECa and soil physical properties. The test site had three areas of distinct soil properties corresponding to the elevation, in particular. The same spatial variability was also identified by ECa mapping at different frequencies and the two modes of coil orientations. Data analysis suggested that the high range frequency (38 kHz (log-spaced) and 49 kHz (line-spaced)) for both HCP and VCP orientations produced accurate ECa maps, better than the weak and low range frequencies tested. Furthermore, results revealed that the combined effects of soil texture, moisture content and bulk density affect ECameasurements as obtained by both frequencies and two coil orientations. Keywords: Apparent electrical conductivity, Electromagnetic induction, Horizontal coplanar, Soil properties, Vertical coplanar
Acoustic Determination of Near-Surface Soil Properties
2008-12-01
requiring geostatistical analysis, while nearby others are spatially independent. In studies involving many different soil properties and chemistry ...Am 116(6), p. 3354-3369. Kravchenko, N., C.W. Boast, D.G. Bullock, 1991. Fractal analysis of soil spatial variability. Agronomy Journal 91
Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes
NASA Astrophysics Data System (ADS)
Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.
2017-12-01
Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation differences amplify the soil moisture variability of semi-arid landscapes.
NASA Astrophysics Data System (ADS)
Gomez, Jose Alfonso; Auxiliadora Soriano, Maria; Montes-Borrego, Miguel; Navas, Juan Antonio; Landa, Blanca B.
2014-05-01
One of the objectives of organic agriculture is to maintain and improve soil quality, while simultaneously producing an adequate yield. A key element in organic olive production is soil management, which properly implemented can optimize the use of rainfall water enhancing infiltration rates and controlling competition for soil water by weeds. There are different soil management strategies: eg. weed mowing (M), green manure with surface tillage in spring (T), or combination with animal grazing among the trees (G). That variability in soil management combined with the large variability in soil types on which organic olive trees are grown in Southern Spain, difficult the evaluation of the impact of different soil management on soil properties, and yield as well as its interpretation in terms of improvement of soil quality. This communications presents the results and analysis of soil physical, chemical and biological properties on 58 soils in Southern Spain during 2005 and 2006, and analyzed and evaluated in different studies since them. Those 58 soils were sampled in 46 certified commercial organic olive orchards with four soil types as well as 12 undisturbed areas with natural vegetation near the olive orchards. The four soil types considered were Eutric Regosol (RGeu, n= 16), Eutric Cambisol (CMeu, n=16), Calcaric Regosol (RGca, n=13 soils sampled) and Calcic Cambisol (CMcc), and the soil management systems (SMS) include were 10 light tillage (LT), 16 sheep grazing (G), 10 tillage (T), 10 mechanical mowing (M), and 12 undisturbed areas covered by natural vegetation (NV-C and NV-S). Our results indicate that soil management had a significant effect on olive yield as well as on key soil properties. Among these soil properties are physical ones, such as infiltration rate or bulk density, chemical ones, especially organic carbon concentration, and biological ones such as soil microbial respiration and bacterial community composition. Superimpose to that soil management induced variability, there was a strong interaction with soil type and climate conditions. There was also a relatively high variability within the same soil management and soil type class, indicating farm to farm variability in conditions and history of soil management. Based on this dataset two different approaches were taken to: A) evaluate the risk of soil degradation based on a limited set of soil properties, B) assess the effect of changes in SMS on soil biodiversity by using terminal restriction profiles (TRFs) derived from T-RFLP analysis of amplified 16S rDNA as. The results indicates the potential of both approaches to assess the risk of soil degradation (A) and the impact on soil biodiversity (B) upon appropriate benchmarking to characterize the interaction between soil management and soil type References Álvarez, S., Soriano, M.A., Landa, B.B., and Gómez, J.A. 2007. Soil properties in organic olive orchards compared with that in natural areas in a mountainous landscape in southern Spain. Soil Use Manage 23:404-416. Gómez, J.A., Álvarez, S., and Soriano, M.A. 2009. Development of a soil degradation assessment tool for organic olive groves in southern Spain. Catena 79:9-17. Landa, B.B., Montes-Borrego, M., Aranda, S., Soriano, M.A., Gómez, J.A., and Navas-Cortés, J.A. 2013. Soil factors involved in the diversity and structure of soil bacterial communities in commercial organic olive orchards in Southern Spain. Environmental Microbiology Reports (accepted) Soriano, M.A., Álvarez, S., Landa, B.B., and Gómez, J.A. 2013. Soil properties in organic olive orchards following different weed management in a rolling landscape of Andalusia, Spain. Renew Agr Food Syst (in press), doi:10.1017/S1742170512000361.
Effects of biochar produced from different feedstocks on soil properties and sunflower growth
NASA Astrophysics Data System (ADS)
Alburquerque, J. A.; Calero, J. M.; Villar, R.; Barrón, V.; Torrent, J.; del Campillo, M. C.; Gallardo, A.
2012-04-01
The use of biochar obtained from biomass pyrolysis as a soil amendment has potential benefits, such as reduction in gas emissions, increase in soil carbon sequestration and improvements in soil fertility and crop yield. These constitute a great incentive for the implementation of biochar-based strategies, which could contribute to improvement of the sustainability of agricultural systems. However, to date, the results of research studies show great variability as a result of differences in both the raw materials and the pyrolysis conditions used to produce biochar, as well as in the experimental setting (crop, soil type, pedo-climatic conditions, etc.). The aim of this study was to evaluate the effects of five types of biochar produced from representative agricultural and forestry wastes (olive husk, almond shell, wheat straw, pine woodchips and olive tree prunings), and applied to soil at different rates, on soil properties and sunflower (Helianthus annuus L.) growth. The biochars had a high organic matter content, alkaline pH, variable soluble salt content and non-phytotoxic properties. The addition of biochar to soil increased pH, electrical conductivity and water retention capacity, and decreased soil bulk density compared to control (unamended soil). However, these effects differed depending on biochar type. In contrast, no consistent effects on sunflower growth variables were observed due to the addition of biochar: increases were observed in some variables (plant dry weight, leaf area and height), but these increases were, in general, not statistically significant when compared to the unamended soil. This can be explained by the nature of biochar, being rich in carbon but relatively poor in nutrients. In summary, our results indicate that biochar is capable of improving soil properties which can impact positively on soil-plant water relations, without negative effects on sunflower growth, and therefore it is suitable for use as a long-term carbon sink in agricultural soils, with both agricultural and environmental benefits.
Tahmasbian, Iman; Safari Sinegani, Ali Akbar; Nguyen, Thi Thu Nhan; Che, Rongxiao; Phan, Thuc D; Hosseini Bai, Shahla
2017-12-01
Ethylenediaminetetraacetic acid (EDTA) used with electrokinetic (EK) to remediate heavy metal-polluted soils is a toxic chelate for soil microorganisms. Therefore, this study aimed to evaluate the effects of alternative organic chelates to EDTA on improving the microbial properties of a heavy metal-polluted soil subjected to EK. Cow manure extract (CME), poultry manure extract (PME) and EDTA were applied to a lead (Pb) and zinc (Zn)-polluted calcareous soil which were subjected to two electric intensities (1.1 and 3.3 v/cm). Soil carbon pools, microbial activity, microbial abundance (e.g., fungal, actinomycetes and bacterial abundances) and diethylenetriaminepentaacetic acid (DTPA)-extractable Pb and Zn (available forms) were assessed in both cathodic and anodic soils. Applying the EK to soil decreased all the microbial variables in the cathodic and anodic soils in the absence or presence of chelates. Both CME and PME applied with two electric intensities decreased the negative effect of EK on soil microbial variables. The lowest values of soil microbial variables were observed when EK was combined with EDTA. The following order was observed in values of soil microbial variables after treating with EK and chelates: EK + CME or EK + PME > EK > EK + EDTA. The CME and PME could increase the concentrations of available Pb and Zn, although the increase was less than that of EDTA. Overall, despite increasing soil available Pb and Zn, the combination of EK with manures (CME or PME) mitigated the negative effects of using EK on soil microbial properties. This study suggested that the synthetic chelates such as EDTA could be replaced with manures to alleviate the environmental risks of EK application.
Time-dependent effect of composted tannery sludge on the chemical and microbial properties of soil.
de Sousa, Ricardo Silva; Santos, Vilma Maria; de Melo, Wanderley Jose; Nunes, Luis Alfredo Pinheiro Leal; van den Brink, Paul J; Araújo, Ademir Sérgio Ferreira
2017-12-01
Composting has been suggested as an efficient method for tannery sludge recycling before its application to the soil. However, the application of composted tannery sludge (CTS) should be monitored to evaluate its effect on the chemical and microbial properties of soil. This study evaluated the time-dependent effect of CTS on the chemical and microbial properties of soil. CTS was applied at 0, 2.5, 5, 10, and 20 Mg ha -1 and the soil chemical and microbial properties were evaluated at 0, 45, 75, 150, and 180 days. Increased CTS rates increased the levels of Ca, Cr, and Mg. While Soil pH, organic C, and P increased with the CTS rates initially, this effect decreased over time. Soil microbial biomass, respiration, metabolic quotient, and dehydrogenase increased with the application of CTS, but decreased over time. Analysis of the Principal Response Curve showed a significant effect of CTS rate on the chemical and microbial properties of the soil over time. The weight of each variable indicated that all soil properties, except β-glucosidase, dehydrogenase and microbial quotient, increased due to the CTS application. However, the highest weights were found for Cr, pH, Ca, P, phosphatase and total organic C. The application of CTS in the soil changed the chemical and microbial properties over time, indicating Cr, pH, Ca, phosphatase, and soil respiration as the more responsive chemical and microbial variables by CTS application.
Poggio, Laura; Gimona, Alessandro
2017-02-01
Soil is very important for many land functions. To achieve sustainability it is important to understand how soils vary over space in the landscape. Remote sensing data can be instrumental in mapping and spatial modelling of soil properties, resources and their variability. The aims of this study were to compare satellite sensors (MODIS, Landsat, Sentinel-1 and Sentinel-2) with varying spatial, temporal and spectral resolutions for Digital Soil Mapping (DSM) of a set of soil properties in Scotland, evaluate the potential benefits of adding Sentinel-1 data to DSM models, select the most suited mix of sensors for DSM to map the considered set of soil properties and validate the results of topsoil (2D) and whole profile (3D) models. The results showed that the use of a mixture of sensors proved more effective to model and map soil properties than single sensors. The use of radar Sentinel-1 data proved useful for all soil properties, improving the prediction capability of models with only optical bands. The use of MODIS time series provided stronger relationships than the use of temporal snapshots. The results showed good validation statistics with a RMSE below 20% of the range for all considered soil properties. The RMSE improved from previous studies including only MODIS sensor and using a coarser prediction grid. The performance of the models was similar to previous studies at regional, national or continental scale. A mix of optical and radar data proved useful to map soil properties along the profile. The produced maps of soil properties describing both lateral and vertical variability, with associated uncertainty, are important for further modelling and management of soil resources and ecosystem services. Coupled with further data the soil properties maps could be used to assess soil functions and therefore conditions and suitability of soils for a range of purposes. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Bönecke, Eric; Lück, Erika; Gründling, Ralf; Rühlmann, Jörg; Franko, Uwe
2016-04-01
Today, the knowledge of within-field variability is essential for numerous purposes, including practical issues, such as precision and sustainable soil management. Therefore, process-oriented soil models have been applied for a considerable time to answer question of spatial soil nutrient and water dynamics, although, they can only be as consistent as their variation and resolution of soil input data. Traditional approaches, describe distribution of soil types, soil texture or other soil properties for greater soil units through generalised point information, e.g. from classical soil survey maps. Those simplifications are known to be afflicted with large uncertainties. Varying soil, crop or yield conditions are detected even within such homogenised soil units. However, recent advances of non-invasive soil survey and on-the-go monitoring techniques, made it possible to obtain vertical and horizontal dense information (3D) about various soil properties, particularly soil texture distribution which serves as an essential soil key variable affecting various other soil properties. Thus, in this study we based our simulations on detailed 3D soil type distribution (STD) maps (4x4 m) to adjacently built-up sufficient informative soil profiles including various soil physical and chemical properties. Our estimates of spatial STD are based on high-resolution lateral and vertical changes of electrical resistivity (ER), detected by a relatively new multi-sensor on-the-go ER monitoring device. We performed an algorithm including fuzzy-c-mean (FCM) logic and traditional soil classification to estimate STD from those inverted and layer-wise available ER data. STD is then used as key input parameter for our carbon, nitrogen and water transport model. We identified Pedological horizon depths and inferred hydrological soil variables (field capacity, permanent wilting point) from pedotransferfunctions (PTF) for each horizon. Furthermore, the spatial distribution of soil organic carbon (SOC), as essential input variable, was predicted by measured soil samples and associated to STD of the upper 30 cm. The comprehensive and high-resolution (4x4 m) soil profile information (up to 2 m soil depth) were then used to initialise a soil process model (Carbon and Nitrogen Dynamics - CANDY) for soil functional modelling (daily steps of matter fluxes, soil temperature and water balances). Our study was conducted on a practical field (~32,000 m²) of an agricultural farm in Central Germany with Chernozem soils under arid conditions (average rainfall < 550 mm). This soil region is known to have differences in soil structure mainly occurring within the subsoil, since topsoil conditions are described as homogenous. The modelled soil functions considered local climate information and practical farming activities. Results show, as expected, distinguished functional variability, both on spatial and temporal resolution for subsoil evident structures, e.g. visible differences for available water capacity within 0-100 cm but homogenous conditions for the topsoil.
Moody, John A.; Nyman, Peter
2013-01-01
Wildfire affects hillslope erosion through increased surface runoff and increased sediment availability, both of which contribute to large post-fire erosion events. Relations between soil detachment rate, soil depth, flow and root properties, and fire impacts are poorly understood and not represented explicitly in commonly used post-fire erosion models. Detachment rates were measured on intact soil cores using a modified tilting flume. The cores were mounted flush with the flume-bed and a measurement was made on the surface of the core. The core was extruded upward, cut off, and another measurement was repeated at a different depth below the original surface of the core. Intact cores were collected from one site burned by the 2010 Fourmile Canyon (FMC) fire in Colorado and from one site burned by the 2010 Pozo fire in California. Each site contained contrasting vegetation and soil types. Additional soil samples were collected alongside the intact cores and were analyzed in the laboratory for soil properties (organic matter, bulk density, particle-size distribution) and for root properties (root density and root-length density). Particle-size distribution and root properties were different between sites, but sites were similar in terms of bulk density and organic matter. Soil detachment rates had similar relations with non-uniform shear stress and non-uniform unit stream power. Detachment rates within single sampling units displayed a relatively weak and inconsistent relation to flow variables. When averaged across all clusters, the detachment rate displayed a linear relation to shear stress, but variability in soil properties meant that the shear stress accounted for only a small proportion of the overall variability in detachment rates (R2 = 0.23; R2 is the coefficient of determination). Detachment rate was related to root-length density in some clusters (R2 values up to 0.91) and unrelated in others (R2 values 2 value improved and the range of exponents became narrower by applying a multivariate regression model where boundary shear stress and root-length density were included as explanatory variables. This suggests that an erodibility parameter which incorporates the effects of both flow and root properties on detachment could improve the representation of sediment availability after wildfire.
Landsat thematic mapper (TM) soil variability analysis over Webster County, Iowa
NASA Technical Reports Server (NTRS)
Thompson, D. R.; Henderson, K. E.; Pitts, D. E.
1984-01-01
Thematic mapper simulator (TMS) data acquired June 7, June 23, and July 31, 1982, and Landsat thematic mapper (TM) data acquired August 2, September 3, and October 21, 1982, over Webster County, Iowa, were examined for within-field soil effects on corn and soybean spectral signatures. It was found that patterns displayed on various computer-generated map products were in close agreement with the detailed soil survey of the area. The difference in spectral values appears to be due to a combination of subtle soil properties and crop growth patterns resulting from the different soil properties. Bands 4 (0.76-.90 micron), 5 (1.55-1.75 micron), and 7 (2.08-2.35 micron) were found to be responding to the within-field soil variability even with increasing ground cover. While these results are preliminary, they do indicate that the soil influence on the vegetation is being detected by TM and should provide improved information relating to crop and soil properties.
Venteris, E.R.; McCarty, G.W.; Ritchie, J.C.; Gish, T.
2004-01-01
Controlled studies to investigate the interaction between crop growth, soil properties, hydrology, and management practices are common in agronomy. These sites (much as with real world farmland) often have complex management histories and topographic variability that must be considered. In 1993 an interdisiplinary study was started for a 20-ha site in Beltsville, MD. Soil cores (271) were collected in 1999 in a 30-m grid (with 5-m nesting) and analyzed as part of the site characterization. Soil organic carbon (SOC) and 137Cesium (137Cs) were measured. Analysis of aerial photography from 1992 and of farm management records revealed that part of the site had been maintained as a swine pasture and the other portion as cropped land. Soil properties, particularly soil redistribution and SOC, show large differences in mean values between the two areas. Mass C is 0.8 kg m -2 greater in the pasture area than in the cropped portion. The pasture area is primarily a deposition site, whereas the crop area is dominated by erosion. Management influence is suggested, but topographic variability confounds interpretation. Soil organic carbon is spatially structured, with a regionalized variable of 120 m. 137Cs activity lacks spatial structure, suggesting disturbance of the profile by animal activity and past structures such as swine shelters and roads. Neither SOC nor 137Cs were strongly correlated to terrain parameters, crop yields, or a seasonal soil moisture index predicted from crop yields. SOC and 137Cs were weakly correlated (r2 ???0.2, F-test P-value 0.001), suggesting that soil transport controls, in part, SOC distribution. The study illustrates the importance of past site history when interpreting the landscape distribution of soil properties, especially those strongly influenced by human activity. Confounding variables, complex soil hydrology, and incomplete documentation of land use history make definitive interpretations of the processes behind the spatial distributions difficult. Such complexity may limit the accuracy of scaling approaches to mapping SOC and soil redistribution.
Baptiste Dafflon; Rusen Oktem; John Peterson; Craig Ulrich; Anh Phuong Tran; Vladimir Romanovsky; Susan Hubbard
2017-05-10
The dataset contains measurements obtained through electrical resistivity tomography (ERT) to monitor soil properties, pole-mounted optical cameras to monitor vegetation dynamics, point probes to measure soil temperature, and periodic manual measurements of thaw layer thickness, snow thickness and soil dielectric permittivity.
USDA-ARS?s Scientific Manuscript database
Soil hydraulic properties, which control surface fluxes and storage of water and chemicals in the soil profile, vary in space and time. Spatial variability above the measurement scale (e.g., soil area of 0.07 m2 or support volume of 14 L) must be upscaled appropriately to determine “effective” hydr...
NASA Astrophysics Data System (ADS)
Rodrigo Panosso, Alan; Milori, Débora M. B. P.; Marques Júnior, José; Martin-Neto, Ladislau; La Scala, Newton, Jr.
2010-05-01
Soil management causes changes in soil physical, chemical, and biological properties that consequently affect its CO2 emission. In this work we studied soil respiration (FCO2) in areas with sugarcane production in southern Brazil under two different sugarcane management systems: green (G), consisting of mechanized harvesting that produces a large amount of crop residues left on the soil surface, and slash-and-burn (SB), in which the residues are burned before manual harvest, leaving no residues on the soil surface. The study was conducted after the harvest period in two side-by-side grids installed in adjacent areas, having 20 measurement points each. The objective of this work was to determinate whether soil physical and chemical properties within each plot were useful in order to explain the spatial variability of FCO2, supposedly influence by each management system. Most of the soil physical properties studied showed no significant differences between management systems, but on the other hand most of the chemical properties differed significantly when SB and G areas were compared. Total FCO2 was 31% higher in the SB plot (729 g CO2 m-2) when compared to the G plot (557 g CO2 m-2) throughout the 70-day period after harvest studied. This seems to be related to the sensitivity of FCO2 to precipitation events, as respiration in this plot increased significantly with increases in soil moisture. Despite temporal variability showed to be positively related to soil moisture, inside each management system there was a negative correlation (p<0.01) between the spatial changes of FCO2 and soil moisture (MS), R= -0.56 and -0.59 for G and SB respectively. There was no spatial correlation between FCO2 and soil organic matter in each management system, however, the humification index (Hum) of organic matter was negatively linear correlated with FCO2 in SB (R= -0.53, p<0.05) while positively linear correlated in G area (R=0.42, p<0.10). The multiple regression model analysis applied in each management system indicates that 63% of the FCO2 spatial variability in G managed could be explained by the model: FCO2(G)= 4.11978 -0.07672MS + 0.0045Hum +1.5352K -0.04474FWP, where K and FWP are potassium content and free water porosity in G area, respectively. On the other hand, 75% of FCO2 spatial variability in SB managed plot was accounted by the model: FCO2(SB) = 10.66774 -0.08624MS -0.02904Hum -2.42548K. Therefore, soil moisture, humification index of organic matter and potassium level were the main properties able to explain the spatial variability of FCO2 in both sugarcane management systems. This result indicates that changes in sugarcane management systems could result in changes on the soil chemical properties, mostly, especially humification index of organic matter. It seems that in conversion from slash-and-burn to green harvest system, free water porosity turns to be an important aspect in order to explain part of FCO2 spatial variability in green managed system.
What are the most crucial soil factors for predicting the distribution of alpine plant species?
NASA Astrophysics Data System (ADS)
Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.
2017-12-01
Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil pH remains one of the most important soil factor for predicting plant species distributions, closely followed by water, organic and inorganic carbon related properties. Finally, we were able to extract three main categories of important soil properties for plant species distributions: grain size distribution, acidity and water in the soil.
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2013-08-01
Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.
Vidic, N.; Pavich, M.; Lobnik, F.
1991-01-01
Alpine glaciations, climatic changes and tectonic movements have created a Quaternary sequence of gravely carbonate sediments in the upper Sava River Valley, Slovenia, Yugoslavia. The names for terraces, assigned in this model, Gu??nz, Mindel, Riss and Wu??rm in order of decreasing age, are used as morphostratigraphic terms. Soil chronosequence on the terraces was examined to evaluate which soil properties are time dependent and can be used to help constrain the ages of glaciofluvial sedimentation. Soil thickness, thickness of Bt horizons, amount and continuity of clay coatings and amount of Fe and Me concretions increase with soil age. The main source of variability consists of solutions of carbonate, leaching of basic cations and acidification of soils, which are time dependent and increase with the age of soils. The second source of variability is the content of organic matter, which is less time dependent, but varies more within soil profiles. Textural changes are significant, presented by solution of carbonate pebbles and sand, and formation is silt loam matrix, which with age becomes finer, with clay loam or clayey texture. The oldest, Gu??nz, terrace shows slight deviation from general progressive trends of changes of soil properties with time. The hypothesis of single versus multiple depositional periods of deposition was tested with one-way analysis of variance (ANOVA) on a staggered, nested hierarchical sampling design on a terrace of largest extent and greatest gravel volume, the Wu??rm terrace. The variability of soil properties is generally higher within subareas than between areas of the terrace, except for the soil thickness. Observed differences in soil thickness between the areas of the terrace could be due to multiple periods of gravel deposition, or to the initial differences of texture of the deposits. ?? 1991.
Relationship between sugarcane rust severity and soil properties in louisiana.
Johnson, Richard M; Grisham, Michael P; Richard, Edward P
2007-06-01
ABSTRACT The extent of spatial and temporal variability of sugarcane rust (Puccinia melanocephala) infestation was related to variation in soil properties in five commercial fields of sugarcane (interspecific hybrids of Saccharum spp., cv. LCP 85-384) in southern Louisiana. Sugarcane fields were grid-soil sampled at several intensities and rust ratings were collected at each point over 6 to 7 weeks. Soil properties exhibited significant variability (coefficients of variation = 9 to 70.1%) and were spatially correlated in 39 of 40 cases with a range of spatial correlation varying from 39 to 201 m. Rust ratings were spatially correlated in 32 of 33 cases, with a range varying from 29 to 241 m. Rust ratings were correlated with several soil properties, most notably soil phosphorus (r = 0.40 to 0.81) and soil sulfur (r = 0.36 to 0.68). Multiple linear regression analysis resulted in coefficients of determination that ranged from 0.22 to 0.73, and discriminant analysis further improved the overall predictive ability of rust models. Finally, contour plots of soil properties and rust levels clearly suggested a link between these two parameters. These combined data suggest that sugarcane growers that apply fertilizer in excess of plant requirements will increase the incidence and severity of rust infestations in their fields.
Christina E. Stringer; Carl C. Trettin; Stan Zarnoch
2016-01-01
Mangroves are well-known for their numerous ecosystem services, including sequestering a significant carbon stock, with soils accounting for the largest pool. The soil carbon pool is dependent on the carbon content and bulk density. Our objective was to assess the spatial variability of mangrove soil physical and chemical properties within the Zambezi River Delta and...
Properties and variability of soil and trench fill at an arid waste-burial site
Andraski, Brian J.
1996-01-01
Arid sites commonly are assumed to be ideal for long-term isolation of wastes. Information on properties and variability of desert soils is limited, however, and little is known about how the natural site environment is altered by installation of a waste facility. During fall construction of two test trenches next to the waste facility on the Amargosa Desert near Beatty, NV, samples were collected to: (i) characterize physical and hydraulic properties of native soil (upper 5 m) and trench fill, (ii) determine effects of trench construction on selected properties and vertical variability of these properties, and (iii) develop conceptual models of vertical variation within the soil profile and trench fill. Water retention was measured to air dryness (ψ = 2 × 106 cm water suction). The 15 300-cm pressure-plate data were omitted from the analysis because water-activity measurements showed the actual suction values were significantly less than the expected 15 300-cm value (avg. difference = 8550 ± 2460 cm water). Trench construction significantly altered properties and variability of the natural site environment. For example, water content ranged from 0.029 to 0.041 m3 m-3 for fill vs. 0.030 to 0.095 m3 m-3 for soil; saturated hydraulic conductivity was ≈ 10-4 cm s-1 for fill vs. 10-2 to ≈ 10-4 cm s-1 for soil. Statistical analyses showed that the native soil may be represented by three major horizontal components and the fill by a single component. Under initial conditions, calculated liquid conductivity (Kl) plus isothermal vapor conductivity (Kv) for the upper two soil layers and the trench fill was ≈ 10-13 cm s-1, and Kl was ≤ Kv. For the deeper (2–5 m) soil, total conductivity was ≈ 10-10 cm s-1, and Kl was >Kv. This study quantitatively describes hydraulic characteristics of a site using data measured across a water-content range that is representative of arid conditions, but is seldom studied.
NASA Astrophysics Data System (ADS)
Volk, Elazar; Iden, Sascha C.; Furman, Alex; Durner, Wolfgang; Rosenzweig, Ravid
2016-08-01
Understanding the influence of attached microbial biomass on water flow in variably saturated soils is crucial for many engineered flow systems. So far, the investigation of the effects of microbial biomass has been mainly limited to water-saturated systems. We have assessed the influence of biofilms on the soil hydraulic properties under variably saturated conditions. A sandy soil was incubated with Pseudomonas Putida and the hydraulic properties of the incubated soil were determined by a combination of methods. Our results show a stronger soil water retention in the inoculated soil as compared to the control. The increase in volumetric water content reaches approximately 0.015 cm3 cm-3 but is only moderately correlated with the carbon deficit, a proxy for biofilm quantity, and less with the cell viable counts. The presence of biofilm reduced the saturated hydraulic conductivity of the soil by up to one order of magnitude. Under unsaturated conditions, the hydraulic conductivity was only reduced by a factor of four. This means that relative water conductance in biofilm-affected soils is higher compared to the clean soil at low water contents, and that the unsaturated hydraulic conductivity curve of biofilm-affected soil cannot be predicted by simply scaling the saturated hydraulic conductivity. A flexible parameterization of the soil hydraulic functions accounting for capillary and noncapillary flow was needed to adequately describe the observed properties over the entire wetness range. More research is needed to address the exact flow mechanisms in biofilm-affected, unsaturated soil and how they are related to effective system properties.
NASA Astrophysics Data System (ADS)
Ding, R.; Cruz, L.; Whitney, J.; Telenko, D.; Oware, E. K.
2017-12-01
There is the growing need for the development of efficient irrigation management practices due to increasing irrigation water scarcity as a result of growing population and changing climate. Soil texture primarily controls the water-holding capacity of soils, which determines the amount of irrigation water that will be available to the plant. However, while there are significant variabilities in the textural properties of the soil across a field, conventional irrigation practices ignore the underlying variability in the soil properties, resulting in over- or under-irrigation. Over-irrigation leaches plant nutrients beyond the root-zone leading to fertilizer, energy, and water wastages with dire environmental consequences. Under-irrigation, in contrast, causes water stress of the plant, thereby reducing plant quality and yield. The goal of this project is to leverage soil textural map of a field to create water management zones (MZs) to guide site-specific precision irrigation. There is increasing application of electromagnetic induction methods to rapidly and inexpensively map spatially continuous soil properties in terms of the apparent electrical conductivity (ECa) of the soil. ECa is a measure of the bulk soil properties, including soil texture, moisture, salinity, and cation exchange capacity, making an ECa map a pseudo-soil map. Data for the project were collected from a farm site at Eden, NY. The objective is to leverage high-resolution ECa map to predict spatially dense soil textural properties from limited measurements of soil texture. Thus, after performing ECa mapping, we conducted particle-size analysis of soil samples to determine the textural properties of soils at selected locations across the field. We cokriged the high-resolution ECa measurements with the sparse soil textural data to estimate a soil texture map for the field. We conducted irrigation experiments at selected locations to calibrate representative water-holding capacities of each estimated soil textural unit. Estimated soil units with similar water-holding characteristics were merged to create sub-field water MZs to guide precision irrigation of each MZ, instructed by each MZ's calibrated water-holding properties.
Ross, Donald S.; Bailiey, Scott W; Briggs, Russell D; Curry, Johanna; Fernandez, Ivan J.; Fredriksen, Guinevere; Goodale, Christine L.; Hazlett, Paul W.; Heine, Paul R; Johnson, Chris E.; Larson, John T; Lawrence, Gregory B.; Kolka, Randy K; Ouimet, Rock; Pare, D; Richter, Daniel D.; Shirmer, Charles D; Warby, Richard A.F.
2015-01-01
Long-term forest soil monitoring and research often requires a comparison of laboratory data generated at different times and in different laboratories. Quantifying the uncertainty associated with these analyses is necessary to assess temporal changes in soil properties. Forest soil chemical properties, and methods to measure these properties, often differ from agronomic and horticultural soils. Soil proficiency programs do not generally include forest soil samples that are highly acidic, high in extractable Al, low in extractable Ca and often high in carbon. To determine the uncertainty associated with specific analytical methods for forest soils, we collected and distributed samples from two soil horizons (Oa and Bs) to 15 laboratories in the eastern United States and Canada. Soil properties measured included total organic carbon and nitrogen, pH and exchangeable cations. Overall, results were consistent despite some differences in methodology. We calculated the median absolute deviation (MAD) for each measurement and considered the acceptable range to be the median 6 2.5 3 MAD. Variability among laboratories was usually as low as the typical variability within a laboratory. A few areas of concern include a lack of consistency in the measurement and expression of results on a dry weight basis, relatively high variability in the C/N ratio in the Bs horizon, challenges associated with determining exchangeable cations at concentrations near the lower reporting range of some laboratories and the operationally defined nature of aluminum extractability. Recommendations include a continuation of reference forest soil exchange programs to quantify the uncertainty associated with these analyses in conjunction with ongoing efforts to review and standardize laboratory methods.
NASA Astrophysics Data System (ADS)
Shepard, C.; Holleran, M.; Lybrand, R. A.; Rasmussen, C.
2014-12-01
Understanding critical zone evolution and function requires an accurate assessment of local soil properties. Two-dimensional (2D) digital soil mapping provides a general assessment of soil characteristics across a sampled landscape, but lacks the ability to predict soil properties with depth. The utilization of mass-preserving spline functions enable the extrapolation of soil properties with depth, extending predictive functions to three-dimensions (3D). The present study was completed in the Marshall Gulch (MG) catchment, located in the Santa Catalina Mountains, 30 km northwest of Tucson, Arizona, as part of the Santa Catalina-Jemez Mountains Critical Zone Observatory. Twenty-four soil pits were excavated and described following standard procedures. Mass-preserving splines were used to extrapolate mass carbon (kg C m-2); percent clay, silt, and sand (%); sodium mass flux (kg Na m-2); and pH for 24 sampled soil pits in 1-cm depth increments. Saturated volumetric water content (θs) and volumetric water content at 10 kPa (θ10) were predicted using ROSETTA and established empirical relationships. The described profiles were all sampled to differing depths; to compensate for the unevenness of the profile descriptions, the soil depths were standardized from 0.0 to 1.0 and then split into five equal standard depth sections. A logit-transformation was used to normalize the target variables. Step-wise regressions were calculated using available environmental covariates to predict the properties of each variable across the catchment in each depth section, and interpolated model residuals added back to the predicted layers to generate the final soil maps. Logit-transformed R2 for the predictive functions varied widely, ranging from 0.20 to 0.79, with logit-transformed RMSE ranging from 0.15 to 2.77. The MG catchment was further classified into clusters with similar properties based on the environmental covariates, and representative depth functions for each target variable in each cluster calculated. Mass-preserving splines combined with stepwise regressions are an effective tool for predicting soil physical, chemical, and hydrological properties with depth, enhancing our understanding of the critical zone.
Towards soil property retrieval from space: Proof of concept using in situ observations
NASA Astrophysics Data System (ADS)
Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph
2014-05-01
Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.
NASA Astrophysics Data System (ADS)
Chandler, D. G.; Seyfried, M. S.
2016-12-01
This study explores the impacts of fire and plant community succession on soil water repellency (SWR) and infiltration properties to improve understanding the long term impacts of prescribed fire on SWR and infiltration properties in sagebrush-steppe ecosystem. The objectives of this study were: 1) To explore the temporal effects of prescribed burning in sagebrush dominated landscape; 2) To investigate spatial variability of soil hydrologic properties; 3) To determine the relationship among soil organic fraction, soil hydrophobicity and infiltration properties. Fieldwork was conducted in paired catchments with three dominant vegetation cover communities: Low sage, big mountain sage and aspen. Detailed, heavily replicated analyses were conducted for unsaturated hydraulic conductivity, sorptivity water drop penetration time and static soil-water-air contact angle. The results show that the severity and presence of surface soil water repellency were considerably reduced six years after fire and that hydraulic conductivity increased significantly in each vegetation cover compared to pre-burn condition. Comparisons among soil hydrological properties shows that hydraulic conductivity is not strongly related to SWR, and that sorptivity is negatively correlated with SWR. The spatial variance of hydraulic properties within the burned high sage and low sage, in particularly, spatial variability of hydraulic conductivity is basically controlled by soil texture and sorptivity is affected by soil wettability. The average water repellency in Low Sage area was significantly different with Big Sage and Aspen as the gap of organic content between Low Sage and other vegetation area. The result of contact angle measurement and organic content analysis shows a strong positive correlation between SWR and organic matter.
Joint Multifractal Analysis of penetration resistance variability in an olive orchard.
NASA Astrophysics Data System (ADS)
Lopez-Herrera, Juan; Herrero-Tejedor, Tomas; Saa-Requejo, Antonio; Villeta, Maria; Tarquis, Ana M.
2016-04-01
Spatial variability of soil properties is relevant for identifying those zones with physical degradation. We used descriptive statistics and multifractal analysis for characterizing the spatial patterns of soil penetrometer resistance (PR) distributions and compare them at different soil depths and soil water content to investigate the tillage effect in soil compactation. The study was conducted on an Inceptisol dedicated to olive orchard for the last 70 years. Two parallel transects of 64 m were selected as different soil management plots, conventional tillage (CT) and no tillage (NT). Penetrometer resistance readings were carried out at 50 cm intervals within the first 20 cm of soil depth (López de Herrera et al., 2015a). Two way ANOVA highlighted that tillage system, soil depth and their interaction are statistically significant to explain the variance of PR data. The comparison of CT and NT results at different depths showed that there are significant differences deeper than 10 cm but not in the first two soil layers. The scaling properties of each PR profile was characterized by τ(q) function, calculated in the range of moment orders (q) between -5 and +5 taken at 0.5 lag increments. Several parameters were calculated from this to establish different comparisons (López de Herrera et al., 2015b). While the multifractal analysis characterizes the distribution of a single variable along its spatial support, the joint multifractal analysis can be used to characterize the joint distribution of two or more variables along a common spatial support (Kravchenko et al., 2000; Zeleke and Si, 2004). This type of analysis was performed to study the scaling properties of the joint distribution of PR at different depths. The results showed that this type of analysis added valuable information to describe the spatial arrangement of depth-dependent penetrometer data sets in all the soil layers. References Kravchenko AN, Bullock DG, Boast CW (2000) Joint multifractal analysis of crop yield and terrain slope. Agro. j. 92: 1279-1290. López de Herrera, J., Tomas Herrero Tejedor, Antonio Saa-Requejo and Ana M. Tarquis (2015a) Influence of tillage in soil penetration resistance variability in an olive orchard. Geophysical Research Abstracts, 17, EGU2015-15425. López de Herrera, J., Tomás Herrero Tejedor, Antonio Saa-Requejo, A.M. Tarquis. Influence of tillage in soil penetration resistance variability in an olive orchard. Soil Research, accepted, 2015b. doi: SR15046 Zeleke TB, Si BC (2004) Scaling properties of topographic indices and crop yield: Multifractal and joint multifractal approaches. Agro. j. 96: 1082-1090.
USDA-ARS?s Scientific Manuscript database
Soil properties are thought to affect rangeland ecosystem functioning (e.g. primary productivity, hydrology), and thus soil variables that are consistently correlated with key ecosystem functions may be general indicators of rangeland health. We summarize results from several studies in mixed-grass...
Soil fertility assessment in the 3 PG model using site index in the southeastern United States
Santosh Subedi; Thomas R. Fox
2016-01-01
Soil fertility is one of the most important, yet least understood aspects of forest ecosystems. Study of soil fertility in forest ecosystems is complicated by the complex relationship between soil properties and stand productivity and immense variability in properties and characteristics of soils within relatively small geographic areas. Furthermore, the deep rooting...
NASA Astrophysics Data System (ADS)
Zhang, Changshun; Xie, Gaodi; Fan, Shaohui; Zhen, Lin
2010-04-01
Biodiversity maintenance and soil improvement are key sustainable forestry objectives. Research on the effects of bamboo forest management on plant diversity and soil properties are therefore necessary in bamboo-growing regions, such as southeastern China’s Shunchang County, that have not been studied from this perspective. We analyzed the effects of different Phyllostachys pubescens proportions in managed forests on vegetation structure and soil properties using pure Cunninghamia lanceolata forests as a contrast, and analyzed the relation between understory plants and environmental variables (i.e., topography, stand and soil characteristics) by canonical correspondence analysis (CCA). The forest with 80% P. pubescens and 20% hardwoods (such as Phoebe bournei, Jatropha curcas, Schima superba) maintained the highest plant diversity and best soil properties, with significantly higher plant diversity than the C. lanceolata forest, and better soil physicochemical and biological properties. The distribution of understory plants is highly related to environmental factors. Silvicultural disturbance strongly influenced the ability of different bamboo forests to maintain biodiversity and soil quality under extensive management, and the forest responses to management were consistent with the intermediate-disturbance hypothesis (i.e., diversity and soil properties were best at intermediate disturbance levels). Our results suggest that biodiversity maintenance and soil improvement are important management goals for sustainable bamboo management. To achieve those objectives, managers should balance the inputs and outputs of nutrients and protect understory plants by using appropriate fertilizer (e.g., organic fertilizer), adjusting stand structure, modifying utilization model and the harvest time, and controlling the intensity of culms and shoots harvests.
NASA Astrophysics Data System (ADS)
Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.
2015-12-01
Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.
USDA-ARS?s Scientific Manuscript database
Background/Question/Methods: Soils matter for restoration. Or do they? This paper takes a process-based approach to this question, using a combination of published literature, pedotransfer functions, and several datasets where a range of relatively static and dynamic soil properties were measured on...
Romero-Freire, A; Martin Peinado, F J; van Gestel, C A M
2015-05-30
Soil contamination with lead is a worldwide problem. Pb can cause adverse effects, but its mobility and availability in the terrestrial environment are strongly controlled by soil properties. The present study investigated the influence of different soil properties on the solubility of lead in laboratory spiked soils, and its toxicity in three bioassays, including Lactuca sativa root elongation and Vibrio fischeri illumination tests applied to aqueous extracts and basal soil respiration assays. Final aim was to compare soil-dependent toxicity with guideline values. The L. sativa bioassay proved to be more sensitive to Pb toxicity than the V. fischeri and soil respiration tests. Toxicity was significantly correlated with soil properties, with soil pH, carbonate and organic carbon content being the most important factors. Therefore, these variables should be considered when defining guideline values. Copyright © 2015 Elsevier B.V. All rights reserved.
Pardo, Arturo; Emilio Pardo, J; de Juan, J Arturo; Zied, Diego Cunha
2010-12-01
The aim of this research was to show the mathematical data obtained through the correlations found between the physical and chemical characteristics of casing layers and the final mushrooms' properties. For this purpose, 8 casing layers were used: soil, soil + peat moss, soil + black peat, soil + composted pine bark, soil + coconut fibre pith, soil + wood fibre, soil + composted vine shoots and, finally, the casing of La Rioja subjected to the ruffling practice. The conclusion that interplays in the fructification process with only the physical and chemical characteristics of casing are complicated was drawn. The mathematical data obtained in earliness could be explained in non-ruffled cultivation. The variability observed for the mushroom weight and the mushroom diameter variables could be explained in both ruffled and non-ruffled cultivations. Finally, the properties of the final quality of mushrooms were established by regression analysis.
NASA Astrophysics Data System (ADS)
Gopp, N. V.; Nechaeva, T. V.; Savenkov, O. A.; Smirnova, N. V.; Smirnov, V. V.
2017-01-01
The relationships between the morphometric parameters (MPs) of topography calculated on the basis of digital elevation model (ASTER GDEM, 30 m) and the properties of the plow layer of agrogray soils on a slope were analyzed. The contribution of MPs to the spatial variability of the soil moisture reached 42%; to the content of physical clay (<0.01 mm particles), 59%; to the humus content, 46%; to the total nitrogen content, 31%; to the content of nitrate nitrogen, 28%; to the content of mobile phosphorus, 40%; to the content of exchangeable potassium, 45%; to the content of exchangeable calcium, 67%; to the content of exchangeable magnesium, 40%; and to the soil pH, 42%. A comparative analysis of the plow layer within the eluvial and transitional parts of the slope was performed with the use of geomorphometric methods and digital soil mapping. The regression analysis showed statistically significant correlations between the properties of the plow layer and the MPs describing surface runoff, geometric forms of surface, and the soil temperature regime.
Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama
Barthold, F.K.; Stallard, R.F.; Elsenbeer, H.
2008-01-01
Soils play a crucial role in biogeochemical cycles as spatially distributed sources and sinks of nutrients. Any spatial patterns depend on soil forming processes, our understanding of which is still limited, especially in regards to tropical rainforests. The objective of our study was to investigate the effects of landscape properties, with an emphasis on the geometry of the land surface, on the spatial heterogeneity of soil chemical properties, and to test the suitability of soil-landscape modeling as an appropriate technique to predict the spatial variability of exchangeable K and Mg in a humid tropical forest in Panama. We used a design-based, stratified sampling scheme to collect soil samples at 108 sites on Barro Colorado Island, Panama. Stratifying variables are lithology, vegetation and topography. Topographic variables were generated from high-resolution digital elevation models with a grid size of 5 m. We took samples from five depths down to 1 m, and analyzed for total and exchangeable K and Mg. We used simple explorative data analysis techniques to elucidate the importance of lithology for soil total and exchangeable K and Mg. Classification and Regression Trees (CART) were adopted to investigate importance of topography, lithology and vegetation for the spatial distribution of exchangeable K and Mg and with the intention to develop models that regionalize the point observations using digital terrain data as explanatory variables. Our results suggest that topography and vegetation do not control the spatial distribution of the selected soil chemical properties at a landscape scale and lithology is important to some degree. Exchangeable K is distributed equally across the study area indicating that other than landscape processes, e.g. biogeochemical processes, are responsible for its spatial distribution. Lithology contributes to the spatial variation of exchangeable Mg but controlling variables could not be detected. The spatial variation of soil total K and Mg is mainly influenced by lithology. ?? 2007 Elsevier B.V. All rights reserved.
Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing
NASA Astrophysics Data System (ADS)
Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.
2018-05-01
In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.
Assessment of site variability from analysis of cone penetration test data.
DOT National Transportation Integrated Search
2015-01-01
Soil property values for use in geotechnical design are often estimated from a limited number of in situ or laboratory tests. The : uncertainty involved in estimating soil properties from a limited number of tests can be addressed by quantifying the ...
Harvest traffic monitoring and soil physical response in a pine plantation
Emily A. Carter; Timothy P. McDonald; John L. Torbert
2000-01-01
Mechanized forest harvest operations induce changes in soil physical properties, which have the potential to impact soil sustainability and forest productivity. The assessment of soil compaction and its spatial variability has been determined previously through the identification and tabulation of visual soil disturbance classes and soil physical changes associated...
Predicting surface vibration from underground railways through inhomogeneous soil
NASA Astrophysics Data System (ADS)
Jones, Simon; Hunt, Hugh
2012-04-01
Noise and vibration from underground railways is a major source of disturbance to inhabitants near subways. To help designers meet noise and vibration limits, numerical models are used to understand vibration propagation from these underground railways. However, the models commonly assume the ground is homogeneous and neglect to include local variability in the soil properties. Such simplifying assumptions add a level of uncertainty to the predictions which is not well understood. The goal of the current paper is to quantify the effect of soil inhomogeneity on surface vibration. The thin-layer method (TLM) is suggested as an efficient and accurate means of simulating vibration from underground railways in arbitrarily layered half-spaces. Stochastic variability of the soil's elastic modulus is introduced using a K-L expansion; the modulus is assumed to have a log-normal distribution and a modified exponential covariance kernel. The effect of horizontal soil variability is investigated by comparing the stochastic results for soils varied only in the vertical direction to soils with 2D variability. Results suggest that local soil inhomogeneity can significantly affect surface velocity predictions; 90 percent confidence intervals showing 8 dB averages and peak values up to 12 dB are computed. This is a significant source of uncertainty and should be considered when using predictions from models assuming homogeneous soil properties. Furthermore, the effect of horizontal variability of the elastic modulus on the confidence interval appears to be negligible. This suggests that only vertical variation needs to be taken into account when modelling ground vibration from underground railways.
Esperón-Rodríguez, Manuel; Baumgartner, John B.; Beaumont, Linda J.
2017-01-01
Background Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent. Methods This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only. Results The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables. Conclusions Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants. PMID:28652933
NASA Astrophysics Data System (ADS)
Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo
2017-04-01
Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.
NASA Astrophysics Data System (ADS)
Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team
2003-04-01
Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, inter-annual and spatial variability of soil respiration as affected by water availability, temperature and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g. leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical non-linear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and inter-site variability of soil respiration with a mean absolute error of 0.82 µmol m-2 s-1. The parameterised model exhibits the following principal properties: 1) At a relative amount of upper-layer soil water of 16% of field capacity half-maximal soil respiration rates are reached. 2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. 3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly time-scale we employed the approach by Raich et al. (2002, Global Change Biol. 8, 800-812) that used monthly precipitation and air temperature to globally predict soil respiration (T&P-model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the inter-site variability, regardless whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly time scale we developed a simple T&P&LAI-model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time-step model and explained 50 % of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index.
Loescher, Henry; Ayres, Edward; Duffy, Paul; Luo, Hongyan; Brunke, Max
2014-01-01
Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (Ts) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure Ts to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than Ts at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our continental-scale understanding of soil behavior. PMID:24465377
DOT National Transportation Integrated Search
2016-04-01
While structural engineering deals with mostly homogeneous manmade materials : (e.g., concrete and steel), geotechnical engineering typically involves highly varied : natural materials (e.g., soil and rock). As a result, high variance of the resistan...
Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel
2017-09-11
Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.
NASA Astrophysics Data System (ADS)
Tavernier, Emma; Verdoodt, Ann; Cornelis, Wim; Delbecque, Nele; Tiebergijn, Lynn; Seynnaeve, Marleen; Gabriels, Donald
2015-04-01
The 'Heuvelland' region with a surface area of 94 km² is situated in the Province of West Flanders, Belgium, bordering with France. The region comprises a number of hills ("heuvel") on which a fast growing 'wine culture' is developing. Both professional as well as non-professional wine makers together cultivate about 19 ha of vineyards, and are still expanding. Grapes cultivated include Chardonnay, Pinot gris and Pinot noir among others. The small-scale, strongly dispersed vineyards are located in different landscape positions of variable aspect. The objective of our preliminary study was to assess the between-field and within-field variation in physico-chemical soil properties of these vineyards with the aim to better characterise the terroir(s) in Heuvelland and provide guidelines for soil management. Fourteen vineyards from five different wineries were selected for detailed soil sampling. Twenty-five sampling sites were chosen according to the topography, soil map units and observed variability in grape growth. The soil was sampled using 15 cm depth increments up to a depth of 60 cm or a shallower lithic contact. Composite samples of 5 sampling locations along the contour lines were taken per within-field zone. Besides the texture, pH, organic carbon, total nitrogen, available phosphorous and exchangeable base cations (Ca, Mg, K), also some micronutrients (Fe, B, Cu, Mn) were determined using standard laboratory procedures. The soils developed on Quaternary niveo-eolian sandy loam and loamy sediments of variable thickness covering marine sandy and clayey sediments of the Tertiary. Where the Tertiary clayey sediments occur at shallow depth, they can strongly influence the internal drainage. At higher positions in the landscape, iron-rich sandstone layers are found at shallow depth. Fragments of this iron-rich sandstone can also be found at lower positions (colluvial material). This iron sandstone is claimed to contribute to the unique character of this wine growing region. According to the soil map of Belgium (scale 1:20,000), the soils are characterized by variable depth, texture, internal drainage and profile development. As such, the 23 vineyards in Heuvelland are found on 21 different soil types; of which 12 different soil types are included within our sampling strategy. Our sampling furthermore revealed an even greater variability in physico-chemical soil properties than reflected by the soil map. This leads to a 'tentative' conclusion that Heuvelland cannot be considered as one natural terroir as such and that the wine growers can potentially improve their production by adapting their management to local soil properties using the improved knowledge on the vineyard soils.
Estimation of effective hydrologic properties of soils from observations of vegetation density
NASA Technical Reports Server (NTRS)
Tellers, T. E.; Eagleson, P. S.
1980-01-01
A one-dimensional model of the annual water balance is reviewed. Improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate soil system, is verified through comparisons with observed data. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides verification of the soil-selection procedure. This method of parameterization of the land surface is useful with global circulation models, enabling them to account for both the nonlinearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.
USDA-ARS?s Scientific Manuscript database
Directed soil sampling based on geospatial measurements of apparent soil electrical conductivity (ECa) is a potential means of characterizing the spatial variability of any soil property that influences ECa including soil salinity, water content, texture, bulk density, organic matter, and cation exc...
Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael
2017-01-01
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.
NASA Astrophysics Data System (ADS)
Drouin, Ariane; Michaud, Aubert; Sylvain, Jean-Daniel; N'Dayegamiye, Adrien; Gasser, Marc-Olivier; Nolin, Michel; Perron, Isabelle; Grenon, Lucie; Beaudin, Isabelle; Desjardins, Jacques; Côté, Noémi
2013-04-01
This project aims at developing and validating an operational integrated management and localized approach at field scale using remote sensing data. It is realized in order to support the competitiveness of agricultural businesses, to ensure soil productivity in the long term and prevent diffuse contamination of surface waters. Our intention is to help agrienvironmental advisors and farmers in the consideration of spatial variability of soil properties in the management of fields. The proposed approach of soil properties recognition is based on the combination of elevation data and multispectral satellite imagery (Landsat) within statistical models. The method is based on the use of the largest possible number of satellite images to cover the widest range of soil moisture variability. Several spectral indices are calculated for each image (normalized brightness index, soil color index, organic matter index, etc.). The assignation of soils is based on a calibration procedure making use of the spatial soil database available in Canada. It includes soil profile point data associated to a database containing the information collected in the field. Three soil properties are predicted and mapped: A horizon texture, B horizon texture and drainage class. All the spectral indices, elevation data and soil data are combined in a discriminant analysis that produces discriminant functions. These are then used to produce maps of soil properties. In addition, from mapping soil properties, management zones are delineated within the field. The delineation of management zones with relatively similar soil properties is created to enable farmers to manage their fertilizers by taking greater account of their soils. This localized or precision management aims to adjust the application of fertilizer according to the real needs of soils and to reduce costs for farmers and the exports of nutrients to the stream. Mapping of soil properties will be validated in three agricultural regions in Quebec through an experimental field protocol (spatial sampling by management zones). Soils will be sampled, but crop yields under different nitrogen rates will also be assessed. Specifically, in each of the management areas defined, five different doses of nitrogen were applied (0, 50, 100, 150, 200 kg N / ha) on corn fields. In fall, the corn is harvested to assess differences in yields between the management areas and also in terms of doses of nitrogen. Ultimately, on the basis of well-established management areas, showing contrasting soil properties, the farmer will be able to ensure optimal correction of soil acidity, nitrogen fertilization, richness of soil in P and K, and improve soil drainage and physical properties. Environmentally, the principles of integrated and localized management carries significant benefits, particularly in terms of reduction of diffuse nutrient pollution.
Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands
NASA Astrophysics Data System (ADS)
Anne, Naveen J. P.; Abd-Elrahman, Amr H.; Lewis, David B.; Hewitt, Nicole A.
2014-12-01
Developing spectral models of soil properties is an important frontier in remote sensing and soil science. Several studies have focused on modeling soil properties such as total pools of soil organic matter and carbon in bare soils. We extended this effort to model soil parameters in areas densely covered with coastal vegetation. Moreover, we investigated soil properties indicative of soil functions such as nutrient and organic matter turnover and storage. These properties include the partitioning of mineral and organic soil between particulate (>53 μm) and fine size classes, and the partitioning of soil carbon and nitrogen pools between stable and labile fractions. Soil samples were obtained from Avicennia germinans mangrove forest and Juncus roemerianus salt marsh plots on the west coast of central Florida. Spectra corresponding to field plot locations from Hyperion hyperspectral image were extracted and analyzed. The spectral information was regressed against the soil variables to determine the best single bands and optimal band combinations for the simple ratio (SR) and normalized difference index (NDI) indices. The regression analysis yielded levels of correlation for soil variables with R2 values ranging from 0.21 to 0.47 for best individual bands, 0.28 to 0.81 for two-band indices, and 0.53 to 0.96 for partial least-squares (PLS) regressions for the Hyperion image data. Spectral models using Hyperion data adequately (RPD > 1.4) predicted particulate organic matter (POM), silt + clay, labile carbon (C), and labile nitrogen (N) (where RPD = ratio of standard deviation to root mean square error of cross-validation [RMSECV]). The SR (0.53 μm, 2.11 μm) model of labile N with R2 = 0.81, RMSECV= 0.28, and RPD = 1.94 produced the best results in this study. Our results provide optimism that remote-sensing spectral models can successfully predict soil properties indicative of ecosystem nutrient and organic matter turnover and storage, and do so in areas with dense canopy cover.
Soil property effects on wind erosion of organic soils
NASA Astrophysics Data System (ADS)
Zobeck, Ted M.; Baddock, Matthew; Scott Van Pelt, R.; Tatarko, John; Acosta-Martinez, Veronica
2013-09-01
Histosols (also known as organic soils, mucks, or peats) are soils that are dominated by organic matter (OM > 20%) in half or more of the upper 80 cm. Forty two states have a total of 21 million ha of Histosols in the United States. These soils, when intensively cropped, are subject to wind erosion resulting in loss of crop productivity and degradation of soil, air, and water quality. Estimating wind erosion on Histosols has been determined by USDA-Natural Resources Conservation Service (NRCS) as a critical need for the Wind Erosion Prediction System (WEPS) model. WEPS has been developed to simulate wind erosion on agricultural land in the US, including soils with organic soil material surfaces. However, additional field measurements are needed to understand how soil properties vary among organic soils and to calibrate and validate estimates of wind erosion of organic soils using WEPS. Soil properties and sediment flux were measured in six soils with high organic contents located in Michigan and Florida, USA. Soil properties observed included organic matter content, particle density, dry mechanical stability, dry clod stability, wind erodible material, and geometric mean diameter of the surface aggregate distribution. A field portable wind tunnel was used to generate suspended sediment and dust from agricultural surfaces for soils ranging from 17% to 67% organic matter. The soils were tilled and rolled to provide a consolidated, friable surface. Dust emissions and saltation were measured using an isokinetic vertical slot sampler aspirated by a regulated suction source. Suspended dust was sampled using a Grimm optical particle size analyzer. Particle density of the saltation-sized material (>106 μm) was inversely related to OM content and varied from 2.41 g cm-3 for the soil with the lowest OM content to 1.61 g cm-3 for the soil with highest OM content. Wind erodible material and the geometric mean diameter of the surface soil were inversely related to dry clod stability. The effect of soil properties on sediment flux varied among flux types. Saltation flux was adequately predicted with simple linear regression models. Dry mechanical stability was the best single soil property linearly related to saltation flux. Simple linear models with soil properties as independent variables were not well correlated with PM10E values (mass flux). A second order polynomial equation with OM as the independent variable was found to be most highly correlated with PM10E values. These results demonstrate that variations in sediment and dust emissions can be linked to soil properties using simple models based on one or more soil properties to estimate saltation mass flux and PM10E values from organic and organic-rich soils.
S-World: A high resolution global soil database for simulation modelling (Invited)
NASA Astrophysics Data System (ADS)
Stoorvogel, J. J.
2013-12-01
There is an increasing call for high resolution soil information at the global level. A good example for such a call is the Global Gridded Crop Model Intercomparison carried out within AgMIP. While local studies can make use of surveying techniques to collect additional techniques this is practically impossible at the global level. It is therefore important to rely on legacy data like the Harmonized World Soil Database. Several efforts do exist that aim at the development of global gridded soil property databases. These estimates of the variation of soil properties can be used to assess e.g., global soil carbon stocks. However, they do not allow for simulation runs with e.g., crop growth simulation models as these models require a description of the entire pedon rather than a few soil properties. This study provides the required quantitative description of pedons at a 1 km resolution for simulation modelling. It uses the Harmonized World Soil Database (HWSD) for the spatial distribution of soil types, the ISRIC-WISE soil profile database to derive information on soil properties per soil type, and a range of co-variables on topography, climate, and land cover to further disaggregate the available data. The methodology aims to take stock of these available data. The soil database is developed in five main steps. Step 1: All 148 soil types are ordered on the basis of their expected topographic position using e.g., drainage, salinization, and pedogenesis. Using the topographic ordering and combining the HWSD with a digital elevation model allows for the spatial disaggregation of the composite soil units. This results in a new soil map with homogeneous soil units. Step 2: The ranges of major soil properties for the topsoil and subsoil of each of the 148 soil types are derived from the ISRIC-WISE soil profile database. Step 3: A model of soil formation is developed that focuses on the basic conceptual question where we are within the range of a particular soil property at a particular location given a specific soil type. The soil properties are predicted for each grid cell based on the soil type, the corresponding ranges of soil properties, and the co-variables. Step 4: Standard depth profiles are developed for each of the soil types using the diagnostic criteria of the soil types and soil profile information from the ISRIC-WISE database. The standard soil profiles are combined with the the predicted values for the topsoil and subsoil yielding unique soil profiles at each location. Step 5: In a final step, additional soil properties are added to the database using averages for the soil types and pedo-transfer functions. The methodology, denominated S-World (Soils of the World), results in readily available global maps with quantitative pedon data for modelling purposes. It forms the basis for the Global Gridded Crop Model Intercomparison carried out within AgMIP.
Effects of golf course management on subsurface soil properties in Iowa
NASA Astrophysics Data System (ADS)
Streeter, Matthew T.; Schilling, Keith E.
2018-05-01
Currently, in the USA and especially in the Midwest region, urban expansion is developing turfgrass landscapes surrounding commercial sites, homes, and recreational areas on soils that have been agriculturally managed for decades. Often, golf courses are at the forefront of conversations concerning anthropogenic environmental impacts as they account for some of the most intensively managed soils in the world. Iowa golf courses provide an ideal location to evaluate whether golf course management is affecting the quality of soils at depth. Our study evaluated how soil properties relating to soil health and resiliency varied with depth at golf courses across Iowa and interpreted relationships of these properties to current golf course management, previous land use, and inherent soil properties. Systematic variation in soil properties including sand content, NO3, and soil organic matter (SOM) were observed with depth at six Iowa golf courses among three landform regions. Variability in sand content was identified between the 20 and 50 cm depth classes at all courses, where sand content decreased by as much as 37 %. Highest concentrations of SOM and NO3 were found in the shallowest soils, whereas total C and P variability was not related to golf course management. Sand content and NO3 were found to be directly related to golf course management, particularly at shallow depths. The effects of golf course management dissipated with depth and deeper soil variations were primarily due to natural geologic conditions. The two abovementioned soil properties were very noticeably altered by golf course management and may directly impact crop productivity, soil health, and water quality, and while NO3 may be altered relatively quickly in soil through natural processes, particle size of the soil may not be altered without extensive mitigation. Iowa golf courses continue to be developed in areas of land use change from historically native prairies and more recently agriculture to urban landscapes. As soils are continually altered by human impacts, it is imperative that we monitor the changes, both physical and chemical, in order to establish management practices that maintain environmental sustainability and productivity.
Environmental and management impacts on temporal variability of soil hydraulic properties
NASA Astrophysics Data System (ADS)
Bodner, G.; Scholl, P.; Loiskandl, W.; Kaul, H.-P.
2012-04-01
Soil hydraulic properties underlie temporal changes caused by different natural and management factors. Rainfall intensity, wet-dry cycles, freeze-thaw cycles, tillage and plant effects are potential drivers of the temporal variability. For agricultural purposes it is important to determine the possibility of targeted influence via management. In no-till systems e.g. root induced soil loosening (biopores) is essential to counteract natural soil densification by settling. The present work studies two years of temporal evolution of soil hydraulic properties in a no-till crop rotation (durum wheat-field pea) with two cover crops (mustard and rye) having different root systems (taproot vs. fibrous roots) as well as a bare soil control. Soil hydraulic properties such as near-saturated hydraulic conductivity, flow weighted pore radius, pore number and macroporosity are derived from measurements using a tension infiltrometer. The temporal dynamics are then analysed in terms of potential driving forces. Our results revealed significant temporal changes of hydraulic conductivity. When approaching saturation, spatial variability tended to dominate over the temporal evolution. Changes in near-saturated hydraulic conductivity were mainly a result of changing pore number, while the flow weighted mean pore radius showed less temporal dynamic in the no-till system. Macroporosity in the measured range of 0 to -10 cm pressure head ranged from 1.99e-4 to 8.96e-6 m3m-3. The different plant coverage revealed only minor influences on the observed system dynamics. Mustard increased slightly the flow weighted mean pore radius, being 0.090 mm in mustard compared to 0.085 mm in bare soil and 0.084 mm in rye. Still pore radius changes were of minor importance for the overall temporal dynamics. Rainfall was detected as major driving force of the temporal evolution of structural soil hydraulic properties at the site. Soil hydraulic conductivity in the slightly unsaturated range (-7 cm to -10 cm) showed a similar time course as a moving average of rainfall. Drying induced a decrease in conductivity while wetting of the soil resulted in higher conductivity values. Approaching saturation however, the drying phase showed a different behaviour with increasing values of hydraulic conductivity. This may be explained probably by formation of cracks acting as large macropores. We concluded that aggregate coalescence as a function of capillary forces and soil rheologic properties (cf. Or et al., 2002) are a main predictor of temporal dynamics of near saturated soil hydraulic properties while different plant covers only had a minor effect on the observed system dynamics. Or, D., Ghezzehei, T.A. 2002. Modeling post-tillage soil structural dynamics. a review. Soil Till Res. 64, 41-59.
Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale
USDA-ARS?s Scientific Manuscript database
Soil water patterns vary significantly due to precipitation, soil properties, topographic features, and land use. We used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water across a 37-ha field of the Washington State University Cook Agronomy Farm near...
Soil variability in engineering applications
NASA Astrophysics Data System (ADS)
Vessia, Giovanna
2014-05-01
Natural geomaterials, as soils and rocks, show spatial variability and heterogeneity of physical and mechanical properties. They can be measured by in field and laboratory testing. The heterogeneity concerns different values of litho-technical parameters pertaining similar lithological units placed close to each other. On the contrary, the variability is inherent to the formation and evolution processes experienced by each geological units (homogeneous geomaterials on average) and captured as a spatial structure of fluctuation of physical property values about their mean trend, e.g. the unit weight, the hydraulic permeability, the friction angle, the cohesion, among others. The preceding spatial variations shall be managed by engineering models to accomplish reliable designing of structures and infrastructures. Materon (1962) introduced the Geostatistics as the most comprehensive tool to manage spatial correlation of parameter measures used in a wide range of earth science applications. In the field of the engineering geology, Vanmarcke (1977) developed the first pioneering attempts to describe and manage the inherent variability in geomaterials although Terzaghi (1943) already highlighted that spatial fluctuations of physical and mechanical parameters used in geotechnical designing cannot be neglected. A few years later, Mandelbrot (1983) and Turcotte (1986) interpreted the internal arrangement of geomaterial according to Fractal Theory. In the same years, Vanmarcke (1983) proposed the Random Field Theory providing mathematical tools to deal with inherent variability of each geological units or stratigraphic succession that can be resembled as one material. In this approach, measurement fluctuations of physical parameters are interpreted through the spatial variability structure consisting in the correlation function and the scale of fluctuation. Fenton and Griffiths (1992) combined random field simulation with the finite element method to produce the Random Finite Element Method (RFEM). This method has been used to investigate the random behavior of soils in the context of a variety of classical geotechnical problems. Afterward, some following studies collected the worldwide variability values of many technical parameters of soils (Phoon and Kulhawy 1999a) and their spatial correlation functions (Phoon and Kulhawy 1999b). In Italy, Cherubini et al. (2007) calculated the spatial variability structure of sandy and clayey soils from the standard cone penetration test readings. The large extent of the worldwide measured spatial variability of soils and rocks heavily affects the reliability of geotechnical designing as well as other uncertainties introduced by testing devices and engineering models. So far, several methods have been provided to deal with the preceding sources of uncertainties in engineering designing models (e.g. First Order Reliability Method, Second Order Reliability Method, Response Surface Method, High Dimensional Model Representation, etc.). Nowadays, the efforts in this field have been focusing on (1) measuring spatial variability of different rocks and soils and (2) developing numerical models that take into account the spatial variability as additional physical variable. References Cherubini C., Vessia G. and Pula W. 2007. Statistical soil characterization of Italian sites for reliability analyses. Proc. 2nd Int. Workshop. on Characterization and Engineering Properties of Natural Soils, 3-4: 2681-2706. Griffiths D.V. and Fenton G.A. 1993. Seepage beneath water retaining structures founded on spatially random soil, Géotechnique, 43(6): 577-587. Mandelbrot B.B. 1983. The Fractal Geometry of Nature. San Francisco: W H Freeman. Matheron G. 1962. Traité de Géostatistique appliquée. Tome 1, Editions Technip, Paris, 334 p. Phoon K.K. and Kulhawy F.H. 1999a. Characterization of geotechnical variability. Can Geotech J, 36(4): 612-624. Phoon K.K. and Kulhawy F.H. 1999b. Evaluation of geotechnical property variability. Can Geotech J, 36(4): 625-639. Terzaghi K. 1943. Theoretical Soil Mechanics. New York: John Wiley and Sons. Turcotte D.L. 1986. Fractals and fragmentation. J Geophys Res, 91: 1921-1926. Vanmarcke E.H. 1977. Probabilistic modeling of soil profiles. J Geotech Eng Div, ASCE, 103: 1227-1246. Vanmarcke E.H. 1983. Random fields: analysis and synthesis. MIT Press, Cambridge.
A global data set of soil particle size properties
NASA Technical Reports Server (NTRS)
Webb, Robert S.; Rosenzweig, Cynthia E.; Levine, Elissa R.
1991-01-01
A standardized global data set of soil horizon thicknesses and textures (particle size distributions) was compiled. This data set will be used by the improved ground hydrology parameterization designed for the Goddard Institute for Space Studies General Circulation Model (GISS GCM) Model 3. The data set specifies the top and bottom depths and the percent abundance of sand, silt, and clay of individual soil horizons in each of the 106 soil types cataloged for nine continental divisions. When combined with the World Soil Data File, the result is a global data set of variations in physical properties throughout the soil profile. These properties are important in the determination of water storage in individual soil horizons and exchange of water with the lower atmosphere. The incorporation of this data set into the GISS GCM should improve model performance by including more realistic variability in land-surface properties.
Assessment of physical and chemical indicators of sandy soil quality for sustainable crop production
NASA Astrophysics Data System (ADS)
Lipiec, Jerzy; Usowicz, Boguslaw
2017-04-01
Sandy soils are used in agriculture in many regions of the world. The share of sandy soils in Poland is about 55%. The aim of this study was to assess spatial variability of soil physical and chemical properties affecting soil quality and crop yields in the scale of field (40 x 600 m) during three years of different weather conditions. The experimental field was located on the post glacial and acidified sandy deposits of low productivity (Szaniawy, Podlasie Region, Poland). Physical soil quality indicators included: content of sand, silt, clay and water, bulk density and those chemical: organic carbon, cation exchange capacity, acidity (pH). Measurements of the most soil properties were done at spring and summer each year in topsoil and subsoil layer in 150 points. Crop yields were evaluated in places close to measuring points of the soil properties. Basic statistics including mean, standard deviation, skewness, kurtosis minimal, maximal and correlations between the soil properties and crop yields were calculated. Analysis of spatial dependence and distribution for each property was performed using geostatistical methods. Mathematical functions were fitted to the experimentally derived semivariograms that were used for mapping the soil properties and crop yield by kriging. The results showed that the largest variations had clay content (CV 67%) and the lowest: sand content (5%). The crop yield was most negatively correlated with sand content and most positively with soil water content and cation exchange capacity. In general the exponential semivariogram models fairly good matched to empirical data. The range of semivariogram models of the measured indicators varied from 14 m to 250 m indicate high and moderate spatial variability. The values of the nugget-to-sill+nugget ratios showed that most of the soil properties and crop yields exhibited strong and moderate spatial dependency. The kriging maps allowed identification of low yielding sub-field areas that correspond with low soil organic carbon and cation exchange capacity and high content of sand. These areas are considered as management zones to improve crop productivity and soil properties responsible for soil quality and functions. We conclude that soil organic carbon, cation exchange capacity and pH should be included as indicators of soil quality in sandy soils. The study was funded by HORIZON 2020, European Commission, Programme H2020-SFS-2015-2: Soil Care for profitable and sustainable crop production in Europe, project No. 677407 (SoilCare, 2016-2021).
Fu, Qing-Long; Weng, Nanyan; Fujii, Manabu; Zhou, Dong-Mei
2018-03-01
Global warming has obtained increasing attentions due to its multiple impacts on agro-ecosystem. However, limited efforts had been devoted to reveal the temporal variability of metal speciation and phytotoxicity of heavy metal-polluted soils affected by elevated temperature under the global warming scenario. In this study, effects of elevated temperature (15 °C, 25 °C, and 35 °C) on the physicochemical properties, microbial metabolic activities, and phytotoxicity of three Cu-polluted soils were investigated by a laboratory incubation study. Soil physicochemical properties were observed to be significantly altered by elevated temperature with the degree of temperature effect varying in soil types and incubation time. The Biolog and enzymatic tests demonstrated that soil microbial activities were mainly controlled and decreased with increasing incubation temperature. Moreover, plant assays confirmed that the phytotoxicity and Cu uptake by wheat roots were highly dependent on soil types but less affected by incubation temperature. Overall, the findings in this study have highlighted the importance of soil types to better understand the temperature-dependent alternation of soil properties, Cu speciation and bioavailability, as well as phytotoxicity of Cu-polluted soils under global warming scenario. The present study also suggests the necessary of investigating effects of soil types on the transport and accumulation of toxic elements in soil-crop systems under global warming scenario. Copyright © 2017 Elsevier Ltd. All rights reserved.
Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale
NASA Astrophysics Data System (ADS)
Ibrahim, Hesham M.; Huggins, David R.
2011-07-01
SummarySpatio-temporal patterns of soil water are major determinants of crop yield potential in dryland agriculture and can serve as the basis for delineating precision management zones. Soil water patterns can vary significantly due to differences in seasonal precipitation, soil properties and topographic features. In this study we used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water at the Washington State University Cook Agronomy Farm (CAF) near Pullman, WA. During the period 1999-2006, the CAF was divided into three roughly equal blocks (A, B, and C), and soil water at 0.3 m intervals to a depth of 1.5 m measured gravimetrically at approximately one third of the 369 geo-referenced points on the 37-ha watershed. These data were combined with terrain attributes, soil bulk density and apparent soil conductivity (EC a). The first EOF generated from the three blocks explained 73-76% of the soil water variability. Field patterns of soil water based on EOF interpolation varied between wet and dry conditions during spring and fall seasons. Under wet conditions, elevation and wetness index were the dominant factors regulating the spatial patterns of soil water. As soil dries out during summer and fall, soil properties (EC a and bulk density) become more important in explaining the spatial patterns of soil water. The EOFs generated from block B, which represents average topographic and soil properties, provided better estimates of soil water over the entire watershed with larger Nash-Sutcliffe Coefficient of Efficiency (NSCE) values, especially when the first two EOFs were retained. Including more than the first two EOFs did not significantly increase the NSCE of soil water estimate. The EOF interpolation method to estimate soil water variability worked slightly better during spring than during fall, with average NSCE values of 0.23 and 0.20, respectively. The predictable patterns of stored soil water in the spring could serve as the basis for delineating precision management zones as yield potential is largely driven by water availability. The EOF-based method has the advantage of estimating the soil water variability based on soil water data from several measurement times, whereas in regression methods only soil water measurement at a single time are used. The EOF-based method can also be used to estimate soil water at any time other than measurement times, assuming the average soil water of the watershed is known at that time.
Wei, Hui; Chen, Xiaomei; Xiao, Guoliang; Guenet, Bertrand; Vicca, Sara; Shen, Weijun
2015-12-16
Soil temperature and moisture are widely-recognized controlling factors on heterotrophic soil respiration (Rh), although they often explain only a portion of Rh variability. How other soil physicochemical and microbial properties may contribute to Rh variability has been less studied. We conducted field measurements on Rh half-monthly and associated soil properties monthly for two years in four subtropical forests of southern China to assess influences of carbon availability and microbial properties on Rh. Rh in coniferous forest was significantly lower than that in the other three broadleaf species-dominated forests and exhibited obvious seasonal variations in the four forests (P < 0.05). Temperature was the primary factor influencing the seasonal variability of Rh while moisture was not in these humid subtropical forests. The quantity and decomposability of dissolved organic carbon (DOC) were significantly important to Rh variations, but the effect of DOC content on Rh was confounded with temperature, as revealed by partial mantel test. Microbial biomass carbon (MBC) was significantly related to Rh variations across forests during the warm season (P = 0.043). Our results suggest that DOC and MBC may be important when predicting Rh under some conditions, and highlight the complexity by mutual effects of them with environmental factors on Rh variations.
NASA Astrophysics Data System (ADS)
Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.
2016-02-01
The effects of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The null-space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of predictive uncertainty (due to soil property (parametric) uncertainty) and the inter-annual climate variability due to year to year differences in CESM climate forcings. After calibrating to measured borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant predictive uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Inter-annual climate variability in projected soil moisture content and Stefan number are small. A volume- and time-integrated Stefan number decreases significantly, indicating a shift in subsurface energy utilization in the future climate (latent heat of phase change becomes more important than heat conduction). Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we quantify the relative magnitude of soil property uncertainty to another source of permafrost uncertainty, structural climate model uncertainty. We show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.
NASA Technical Reports Server (NTRS)
Tellers, T. E.
1980-01-01
An existing one-dimensional model of the annual water balance is reviewed. Slight improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate-soil system, is verified through comparisons with observed data and is employed in the annual water balance of watersheds in Clinton, Ma., and Santa Paula, Ca., to estimate effective areal average soil properties. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides excellent verification of the soil-selection procedure. This method of parameterization of the land surface should be useful with present global circulation models, enabling them to account for both the non-linearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.
New Mexico Tech landmine, UXO, IED detection sensor test facility: measurements in real field soils
NASA Astrophysics Data System (ADS)
Hendrickx, Jan M. H.; Alkov, Nicole; Hong, Sung-ho; Van Dam, Remke L.; Kleissl, Jan; Shannon, Heather; Meason, John; Borchers, Brian; Harmon, Russell S.
2006-05-01
Modeling studies and experimental work have demonstrated that the dynamic behavior of soil physical properties has a significant effect on most sensors for the detection of buried land mines. An outdoor test site has been constructed allowing full control over soil water content and continuous monitoring of important soil properties and environmental conditions. Time domain reflectometry sensors and thermistors measure soil water1 content and temperature, respectively, at different depths above and below the land mines as well as in homogeneous soil away from the land mines. During the two-year operation of the test-site, the soils have evolved to reflect real field soil conditions. This paper compares visual observations as well as ground-penetrating radar and thermal infrared measurements at this site taken immediately after construction in early 2004 with measurements from early 2006. The visual observations reveal that the 2006 soil surfaces exhibit a much higher spatial variability due to the development of mini-reliefs, "loose" and "connected" soil crusts, cracks in clay soils, and vegetation. Evidence is presented that the increased variability of soil surface characteristics leads to a higher natural spatial variability of soil surface temperatures and, thus, to a lower probability to detect landmines using thermal imagery. No evidence was found that the soil surface changes affect the GPR signatures of landmines under the soil conditions encountered in this study. The New Mexico Tech outdoor Landmine Detection Sensor Test Facility is easily accessible and anyone interested is welcome to use it for sensor testing.
NASA Astrophysics Data System (ADS)
Recio Vázquez, Lorena; Almendros, Gonzalo; Knicker, Heike; López-Martín, María; Carral, Pilar; Álvarez, Ana
2014-05-01
In Mediterranean areas, the loss of soil physical quality is of particular concern due to the vulnerability of these ecosystems in relation to unfavourable climatic conditions, which usually lead to soil degradation processes and severe decline of its functionality. As a result, increasing scientific attention is being paid on the exploration of soil properties which could be readily used as quality indicators, including organic matter which, in fact, represents a key factor in the maintenance of soil physical status. In this line, the present research tackles the assessment of the quality of several soils from central Spain with the purpose of identifying the physical properties most closely correlated with the organic matter, considering not only the quantity but also the quality of the different C-forms. The studied attributes consist of a series of physical properties determined in field and laboratory conditions-total porosity, aggregate stability, available water capacity, air provision, water infiltration rate and soil hydric saturation-.The bulk organic matter was characterised by solid-state 13C NMR spectroscopy and the major organic fractions (lipids, free particulate organic matter, fulvic acids, humic acids and humin) were quantified using standard procedures. The humic acids were also analysed by visible and infrared spectroscopies. The use of multidimensional scaling to classify physical properties in conjunction with molecular descriptors of soil organic matter, suggested significant correlations between the two set of variables, which were confirmed with simple and canonical regression models. The results pointed to two well-defined groups of physical attributes in the studied soils: (i) those associated with organic matter of predominantly aromatic character (water infiltration descriptors), and (ii) soil physical variables related to organic matter with marked aliphatic character, high preservation of the lignin signature and comparatively low degree of humification (properties involved in the maintenance of physical support, water storage and air provision functions). From the practical viewpoint, the results support the idea that the detailed structural study of the different soil C-forms is useful for accurately monitoring soil physical status. The quantification of total soil organic carbon ought to be complemented with qualitative analyses of the organic matter, at least at the spectroscopic level, which can be used for the early diagnosis of possible degradation processes. Moreover, in already degraded soils, the knowledge of the sources of variability for each physical property provides valuable information for the restoration of these ecosystems by adapting inputs of organic matter with specific features (aliphatic nature, oxidation degree, humification stage, etc.) to particular soil degradation problems (i.e. soil compaction, waterlogging, water erosion, etc.).
Biochemical processes in sagebrush ecosystems: Interactions with terrain
NASA Technical Reports Server (NTRS)
Matson, P. (Principal Investigator); Reiners, W.; Strong, L.
1985-01-01
The objectives of a biogeochemical study of sagebrush ecosystems in Wyoming and their interactions with terrain are as follows: to describe the vegetational pattern on the landscape and elucidate controlling variables, to measure the soil properties and chemical cycling properties associated with the vegetation units, to associate soil properties with vegetation properties as measured on the ground, to develop remote sensing capabilities for vegetation and surface characteristics of the sagebrush landscape, to develop a system of sensing snow cover and indexing seasonal soil to moisture; and to develop relationships between temporal Thematic Mapper (TM) data and vegetation phenological state.
Bending, Gary D; Lincoln, Suzanne D; Edmondson, Rodney N
2006-01-01
The extent of within field variability in the degradation rate of the pesticides isoproturon, azoxystrobin and diflufenican, and the role of intrinsic soil factors and technical errors in contributing to the variability, was investigated in sites on sandy-loam and clay-loam. At each site, 40 topsoil samples were taken from a 160 x 60 m area, and pesticides applied in the laboratory. Time to 25% dissipation (DT25) ranged between 13 and 61 weeks for diflufenican, 5.6 and 17.2 weeks for azoxystrobin, and 0.3 and 12.5 weeks for isoproturon. Variability in DT25 was higher in the sandy-loam in which there was also greatest variability in soil chemical and microbial properties. Technical error associated with pesticide extraction, analysis and lack of model fit during derivation of DT25 accounted for between 5.3 and 25.8% of the variability for isoproturon and azoxystrobin, but could account for almost all the variability for diflufenican. Azoxystrobin DT25, sorption and pH were significantly correlated.
Horizontal and vertical variability of soil properties in a trace element contaminated area
NASA Astrophysics Data System (ADS)
Burgos, Pilar; Madejón, Engracia; Pérez-de-Mora, Alfredo; Cabrera, Francisco
2008-02-01
The spatial distribution of some soil chemical properties and trace element contents of a plot affected by the Aznalcóllar mine spill were investigated using statistical and geostatistical methods to assess the extent of soil contamination. Total and EDTA-extractable soil trace element concentrations and total S content showed great variability and high coefficients of variation in the three examined depths. Soil in the plot was found to be significantly contaminated by As, Cd, Cu, Pb and Zn within a wide range of pH. Total trace element concentrations at all depths (0-60 cm) were much higher than background values of non-affected soil, indicating that despite the clean-up operations, the concentration of trace elements in the experimental plot was still high. The spatial distribution of the different variables was estimated by kriging to design contour maps. These maps allowed the identification of specific zones with high metal concentrations and low pH values corresponding to spots of residual sludge. Moreover, kriged maps showed distinct spatial distribution and hence different behaviour for the elements considered. This information may be applied to optimise remediation strategies in highly and moderately contaminated areas.
Environmental stochasticity controls soil erosion variability
Kim, Jongho; Ivanov, Valeriy Y.; Fatichi, Simone
2016-01-01
Understanding soil erosion by water is essential for a range of research areas but the predictive skill of prognostic models has been repeatedly questioned because of scale limitations of empirical data and the high variability of soil loss across space and time scales. Improved understanding of the underlying processes and their interactions are needed to infer scaling properties of soil loss and better inform predictive methods. This study uses data from multiple environments to highlight temporal-scale dependency of soil loss: erosion variability decreases at larger scales but the reduction rate varies with environment. The reduction of variability of the geomorphic response is attributed to a ‘compensation effect’: temporal alternation of events that exhibit either source-limited or transport-limited regimes. The rate of reduction is related to environment stochasticity and a novel index is derived to reflect the level of variability of intra- and inter-event hydrometeorologic conditions. A higher stochasticity index implies a larger reduction of soil loss variability (enhanced predictability at the aggregated temporal scales) with respect to the mean hydrologic forcing, offering a promising indicator for estimating the degree of uncertainty of erosion assessments. PMID:26925542
Ulrich, Werner; Piwczyński, Marcin; Zaplata, Markus Klemens; Winter, Susanne; Schaaf, Wolfgang; Fischer, Anton
2014-07-01
During early plant succession, the phylogenetic structure of a community changes in response to important environmental filters and emerging species interactions. We traced the development of temperate-zone plant communities during the first 7 years of primary succession on catchment soils to explore patterns of initial species assembly. We found pronounced small-scale differences in the phylogenetic composition of neighbouring plant assemblages and a large-scale trend towards phylogenetic evenness. This small-scale variability appears to be mediated by soil properties, particularly carbonate content. Therefore, abiotic environmental conditions might counteract or even supersede the effects of interspecific competition among closely related species, which are usually predicted to exhibit patterns of phylogenetic evenness. We conclude that theories on phylogenetic community composition need to incorporate effects of small-scale variability of environmental factors.
NASA Astrophysics Data System (ADS)
Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan
2003-12-01
Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 μmol m-2 s-1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.
Does Timing Matter? Temporal Stability of Soil-Magnetic Climate Proxies
NASA Astrophysics Data System (ADS)
Geiss, C. E.
2013-12-01
Numerous studies have shown that the rock-magnetic properties of soils can serve as valuable proxies of continental climates. Many studies average the magnetic properties of several closely spaced sites to reconstruct regional climate signals, but little is known about the temporal variability of soil-magnetic properties. We analyzed the magnetic properties of five, closely spaced (within 20 m from each other) soil profiles that were sampled over a period of five years between 2002 and 2006. The soil profiles are well-developed and display strong magnetic enhancement. According to land records, agricultural influence was minimal as the site had never been plowed and solely been used as pasture. Detailed soil descriptions and measurements of magnetic susceptibility (χ), anhysteretic and isothermal remanent magnetization (ARM, IRM), as well as coercivity parameters show that all studied profiles have very similar horizination and magnetic properties are virtually unchanged from year to year. The only differences between the soil profiles are the position and strength of redoximorphic features. These nanocrystalline iron-oxide deposits have little influence on the magnetic properties of the soils and the timing of soil sampling for magnetic analyses is not a critical factor when sampling for climatic reconstructions.
NASA Astrophysics Data System (ADS)
Pérez, Luis D.; Cumbrera, Ramiro; Mato, Juan; Millán, Humberto; Tarquis, Ana M.
2015-04-01
Spatial variability of soil properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns (Brouder et al., 2001; Millán et al., 2012). The objective of the present work was to quantify the spatial structure of soil penetrometer resistance (PR) collected from a transect data consisted of 221 points equidistant. In each sampling, readings were obtained from 0 cm till 70 cm of depth, with an interval of 5 cm (Pérez, 2012). The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years (Pérez et al., 2010). Recently, scaling approach has been applied on the determination of the scaling data properties (Tarquis et al., 2008; Millán et al., 2012; Pérez, 2012). We focus in the Hurst analysis to characterize the data variability for each depth. Previously a detrended analysis was conducted in order to better study de intrinsic variability of the series. The Hurst exponent (H) for each depth was estimated showing a characteristic pattern and differentiating PR evolution in depth. References Brouder, S., Hofmann, B., Reetz, H.F., 2001. Evaluating spatial variability of soil parameters for input management. Better Crops 85, 8-11. Millán, H; AM Tarquís, Luís D. Pérez, Juan Mato, Mario González-Posada, 2012. Spatial variability patterns of some Vertisol properties at a field scale using standardized data. Soil and Tillage Research, 120, 76-84. Pérez, Luís D. 2012. Influencia de la maquinaria agrícola sobre la variabilidad espacial de la compactación del suelo. Aplicación de la metodología geoestadística-fractal. PhD thesis, UPM (In Spanish). Pérez, Luís D., Humberto Millán, Mario González-Posada 2010. Spatial complexity of soil plow layer penetrometer resistance as influenced by sugarcane harvesting: A prefractal approach. Soil and Tillage Research, 110(1), 77-86. Tarquis, A.M., N. Bird, M.C. Cartagena, A. Whitmore and Y. Pachepsky, 2008. Multiscale entropy-based analyses of soil transect data. Vadose Zone Journal, 7(2), 563-569.
USDA-ARS?s Scientific Manuscript database
Indices derived from remotely-sensed imagery are commonly used to predict soil properties with digital soil mapping (DSM) techniques. The use of images from single dates or a small number of dates is most common for DSM; however, selection of the appropriate images is complicated by temporal variabi...
Maru, Ali; Haruna, Osumanu Ahmed; Charles Primus, Walter
2015-01-01
The excessive use of nitrogen (N) fertilizers in sustaining high rice yields due to N dynamics in tropical acid soils not only is economically unsustainable but also causes environmental pollution. The objective of this study was to coapply biochar and urea to improve soil chemical properties and productivity of rice. Biochar (5 t ha−1) and different rates of urea (100%, 75%, 50%, 25%, and 0% of recommended N application) were evaluated in both pot and field trials. Selected soil chemical properties, rice plants growth variables, nutrient use efficiency, and yield were determined using standard procedures. Coapplication of biochar with 100% and 75% urea recommendation rates significantly increased nutrients availability (especially P and K) and their use efficiency in both pot and field trials. These treatments also significantly increased rice growth variables and grain yield. Coapplication of biochar and urea application at 75% of the recommended rate can be used to improve soil chemical properties and productivity and reduce urea use by 25%. PMID:26273698
Spatial and temporal variability of soil hydraulic properties of topsoil affected by soil erosion
NASA Astrophysics Data System (ADS)
Nikodem, Antonin; Kodesova, Radka; Jaksik, Ondrej; Jirku, Veronika; Klement, Ales; Fer, Miroslav
2014-05-01
This study is focused on the comparison of soil hydraulic properties of topsoil that is affected by erosion processes. In order to include variable morphological and soil properties along the slope three sites - Brumovice, Vidim and Sedlčany were selected. Two transects (A, B) and five sampling sites along each one were chosen. Soil samples were taken in Brumovice after the tillage and sowing of winter wheat in October 2010 and after the wheat harvest in August 2011. At locality Vidim and Sedlčany samples were collected in May and August 2012. Soil hydraulic properties were studied in the laboratory on the undisturbed 100-cm3 soil samples placed in Tempe cells using the multi-step outflow test. Soil water retention data points were obtained by calculating water balance in the soil sample at each pressure head step of the experiment. The single-porosity model in HYDRUS-1D was applied to analyze the multi-step outflow and to obtain the parameters of soil hydraulic properties using the numerical inversion. The saturated hydraulic conductivities (Ks) and unsaturated hydraulic conductivities (Kw) for the pressure head of -2 cm of topsoil were also measured after the harvest using Guelph permeameter and Minidisk tensiometer, respectively. In general soil water retention curves measured before and after vegetation period apparently differed, which indicated soil material consolidation and soil-porous system rearrangement. Soil water retention curves obtained on the soil samples and hydraulic conductivities measured in the field reflected the position at the elevation transect and the effect of erosion/accumulation processes on soil structure and consequently on the soil hydraulic properties. The highest Ks values in Brumovice were obtained at the steepest parts of the elevation transects, that have been the most eroded. The Ks values at the bottom parts decreased due to the sedimentation of eroded soil particles. The change of the Kw values along transects didn't show similar trends. However, the variability of values within both transects was low. Higher values were obtained in transect B, where the soil was more affected by erosion. The highest values of Ks as well as the value of Kw were also obtained in the steepest part of transect A in Vidim. This trend was not observed in transect B. The results corresponded with measured retention curves. Two different trends were shown in Sedlčany. While the highest values of Ks and Kw were found in the upper part of transect A, in the case of transect B the highest values were measured at the bottom of transect. Differences observed at both localities were caused by the different terrain attributes of both transects and extent of soil erosion. Acknowledgement: Authors acknowledge the financial support of the Ministry of Agriculture of the Czech Republic (QJ1230319).
How to feed environmental studies with soil information to address SDG 'Zero hunger'
NASA Astrophysics Data System (ADS)
Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven
2017-04-01
As pledged by UN Sustainable Development Goal (SDG) 2, there should be zero hunger, food security, improved food nutrition and sustainable agriculture by 2030. Environmental studies are essential to reach SDG 2. Soils play a crucial role, especially in addressing 'Zero hunger'. This study aims to discuss the connection between the supply and demand of soil data for environmental studies and how this connection can be improved illustrating different methods. As many studies are resource constrained, the options to collect new soil data are limited. Therefore, it is essential to use existing soil information, auxiliary data and collected field data efficiently. Existing soil data are criticised in literature as i) being dominantly qualitative, ii) being often outdated, iii) being not spatially exhaustive, iv) being only available at general scales, v) being inconsistent, and vi) lacking quality assessments. Additional field data can help to overcome some of these problems. Outdated maps can, for example, be improved by collecting additional soil data in areas where changes in soil properties are expected. Existing soil data can also provide insight in the expected soil variability and, as such, these data can be used for the design of sampling schemes. Existing soil data are also crucial input for studies on digital soil mapping because they give information on parent material and the relative age of soils. Digital soil mapping is commonly applied as an efficient method to quantitatively predict the spatial variation of soil properties. However, the efficiency of digital soil mapping may increase if we look at functional soil properties (e.g. nutrient availability, available water capacity) for the soil profile that vary in a two-dimensional space rather than at basic soil properties of individual soil layers (e.g. texture, organic matter content, nitrogen content) that vary in a three-dimensional space. Digital soil mapping techniques are based on statistical relations between soil properties and environmental variables. However, in some cases a more mechanistic approach, based on pedological knowledge, might be more convincing to predict soil properties. This study showed that the soil science community is able to provide the required soil information for environmental studies. However, there is not a single solution that provides the required soil data. Case studies are needed to prove that certain methods meet the data requirements, whereafter these case studies function as a lighthouse to other studies. We illustrate data availability and methodological innovations for a case study in Kenya, where the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) aims to contribute to SDG 2.
NASA Astrophysics Data System (ADS)
Nyckowiak, Jedrzej; Lesny, Jacek; Haas, Edwin; Juszczak, Radoslaw; Kiese, Ralf; Butterbach-Bahl, Klaus; Olejnik, Janusz
2014-05-01
Modeling of nitrous oxide emissions from soil is very complex. Many different biological and chemical processes take place in soils which determine the amount of emitted nitrous oxide. Additionaly, biogeochemical models contain many detailed factors which may determine fluxes and other simulated variables. We used the LandscapeDNDC model in order to simulate N2O emissions, crop yields and soil physical properties from mineral cultivated soils in Poland. Nitrous oxide emissions from soils were modeled for fields with winter wheat, winter rye, spring barley, triticale, potatoes and alfalfa crops. Simulations were carried out for the plots of the Brody arable experimental station of Poznan University of Life Science in western Poland and covered the period 2003 - 2012. The model accuracy and its efficiency was determined by comparing simulations result with measurements of nitrous oxide emissions (measured with static chambers) from about 40 field campaigns. N2O emissions are strongly dependent on temperature and soil water content, hence we compared also simulated soil temperature at 10cm depth and soil water content at the same depth with the daily measured values of these driving variables. We compared also simulated yield quantities for each individual experimental plots with yield quantities which were measured in the period 2003-2012. We conclude that the LandscapeDNDC model is capable to simulate soil N2O emissions, crop yields and physical properties of soil with satisfactorily good accuracy and efficiency.
NASA Astrophysics Data System (ADS)
Bekele, Dawit N.; Naidu, Ravi; Chadalavada, Sreenivasulu
2014-05-01
A comprehensive field study was conducted at a site contaminated with chlorinated solvents, mainly trichloroethylene (TCE), to investigate the influence of subsurface soil moisture and temperature on vapour intrusion (VI) into built structures. Existing approaches to predict the risk of VI intrusion into buildings assume homogeneous or discrete layers in the vadose zone through which TCE migrates from an underlying source zone. In reality, the subsurface of the majority of contaminated sites will be subject to significant variations in moisture and temperature. Detailed site-specific data were measured contemporaneously to evaluate the impact of spatial and temporal variability of subsurface soil properties on VI exposure assessment. The results revealed that indoor air vapour concentrations would be affected by spatial and temporal variability of subsurface soil moisture and temperature. The monthly monitoring of soil-gas concentrations over a period of one year at a depth of 3 m across the study site demonstrated significant variation in TCE vapour concentrations, which ranged from 480 to 629,308 μg/m3. Soil-gas wells at 1 m depth exhibited high seasonal variability in TCE vapour concentrations with a coefficient of variation 1.02 in comparison with values of 0.88 and 0.74 in 2 m and 3 m wells, respectively. Contour plots of the soil-gas TCE plume during wet and dry seasons showed that the plume moved across the site, hence locations of soil-gas monitoring wells for human risk assessment is a site specific decision. Subsurface soil-gas vapour plume characterisation at the study site demonstrates that assessment for VI is greatly influenced by subsurface soil properties such as temperature and moisture that fluctuate with the seasons of the year.
NASA Astrophysics Data System (ADS)
Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven
2015-04-01
In the past, soil surveying techniques were mainly developed for qualitative regional land use analysis (RLUA) like land evaluation and land use planning. Conventional soil survey techniques usually describe soil types according to a soil classification scheme (e.g. Soil Taxonomy and World Reference Base). These soil surveys met the requirements of qualitative land evaluation and land use planning. However, during the last decades there is an increased need for quantitative RLUA resulting in an increased demand for quantitative soil data. The rapid developments in computing technology and the availability of auxiliary information (e.g. remote sensing and digital elevation models) allowed for the development of new soil surveying techniques like digital soil mapping. These new soil surveying techniques aim to produce continuous maps of quantitative functional soil properties. However, RLUA nowadays requires soil data that include a description of the spatial variability of the entire pedon in which correlations between soil properties are retained. Current surveying techniques do not fully fulfil these requirements resulting in a gap between the supply and demand of soil data in RLUA. The gap is caused by the fact that legacy soil data are collected for different purposes and inherently have different assumptions on e.g., soil variability. In this study, some of these assumptions are tested and verified using primary soil data collected during a recent field survey in Machakos and Makueni County (Kenya). Subsequently an ongoing RLUA, the Global Yield Gap Atlas (GYGA) project, is taken as a case study to evaluate the effect of different sources of soil data on the results of the RLUA. The results of the study show that various assumptions underlying the soil survey hamper the quality requirements of soil data for the specific objectives of the RLUA. To give a few examples: mapping soil properties individually ignores correlations between them, soil properties differed significantly between natural and agricultural land, discrete soil mapping units described by a representative soil profile showed internal variability. None of the legacy datasets fitted the requirements of the RLUA. However, resources to collect additional primary soil data are limited. Evaluating legacy data allows us to identify the soil data that we need to collect. Legacy data lack information on e.g. soil management and effective rooting depth, while these data are often required for RLUA. This results in the use of assumptions, estimations and simplifications in a RLUA. The choice of legacy data has a profound effect on the results of a RLUA. The GYGA case study shows for example that different sources of soil input data can lead to differences in simulated water-limited maize yields of up to 3 ton/ha.
Romero-Freire, A; Peinado, F J Martín; Ortiz, M Díez; van Gestel, C A M
2015-10-01
This study aimed at assessing the influence of soil properties on the uptake and toxicity effects of arsenic in the earthworm Eisenia andrei exposed for 4 weeks to seven natural soils spiked with different arsenic concentrations. Water-soluble soil concentrations (AsW) and internal As concentrations in the earthworms (AsE) were greatly different between soils. These two variables were highly correlated and were key factors in earthworm toxicity response. AsW was explained by some soil properties, such as the pH, calcium carbonate content, ionic strength, texture or oxide forms. Toxicity showed a clear variation between soils, in some cases without achieving 50 % adverse effect at the highest As concentration added (600 mg kg(-1)). Nevertheless, soil properties did not show, in general, a high relation with studied toxicity endpoints, although the high correlation with AsW could greatly reduce indirectly As bioavailability and toxicity risk for earthworms. Obtained results suggest that soil properties should be part of the criteria to establishing thresholds for contaminated soils because they will be key in controlling As availability and thus result in different degrees of toxicity.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Halvorson, J.J.; Smith, J.L.; Bolton, H. Jr.
1995-09-01
Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations ofmore » these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.« less
Soils, peatlands, and biomonitoring
James Doolittle
2009-01-01
Soils are three-dimensional (3D) natural bodies conSlStmg of unconsolidated mineral and organic materials that form a continuous blanket over most of the earth's land sUlface. At all sca les of measurements, soils are exceedingly complex and variable in biological, chemical, physical, mineralogical, and electromagnetic properties....
Growing concern over climate and management induced changes to soil nutrient status has prompted interest in understanding the spatial distribution of forest soil properties. Recent advancements in remotely sensed geospatial technologies are providing an increasing array of data...
NASA Astrophysics Data System (ADS)
Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.
2017-12-01
Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.
NASA Astrophysics Data System (ADS)
Romzaikina, Olga; Vasenev, Viacheslav; Khakimova, Rita
2017-04-01
On-going urbanization stresses a necessity for structural and aesthetically organized urban landscapes to improve citizen's life quality. Urban soils and vegetation are the main components of urban ecosystems. Urban greenery regulates the climate, controls and air quality and supports biodiversity in urban areas. Soils play a key role in supporting urban greenery. However, soils of urban parks also perform other important environmental functions. Urban soils are influenced by a variety of environmental and anthropogenic factors and, in the result, are highly heterogeneous and dynamic. Reconstructions of green zones and urban parks, usually occurring in cities, alter soil properties. Analyzing spatial variability and dynamics of soil properties is important to support decision-making in landscaping. Therefore, the research aimed to analyze the spatial distribution of the key soil properties (acidity, soil organic carbon (SOC) and nutrient contents) in the urban park before and after reconstruction to support decision-making in selecting ornamental plants for landscaping. The research was conducted in the urban park named after Artyom Borovik in Moscow before (2012) and after (2014) the reconstruction. Urban soil's properties maps for both periods were created by interpolation of the field data. The observed urban soils included recreazems, urbanozems and constuctozems. Before the reconstruction soils were sampled using the uniform design (the net with 100 m side and key plots with 50m size). After the reconstructions the additional samples were collected at locations, where the land cover and functional zones changed in a result of the reconstruction.We sample from the depths 0-30, 30-50 and 50-100 cm. The following soil properties were measured: pH, SOC, K2O and P2O5. The maps of the analyzed properties were developed using open QGIS2.4 software by IDW. The vegetation in the park was examined using the scale of the visual assessment. The results of the visual assessment were processed using QGIS2.4 and the maps of the vegetation condition were created. High spatial variability was shown for observed soil properties with the highest variance reported for nutrient concentrations. High heterogeneity in P2O5 and K2O was obtained both in topsoil and subsoil, before and after reconstruction. We showed that average concentrations of P2O5 and K2O were correspondingly above and below legal threshold taken for the Moscow city. In result of the reconstruction the pH has changed from slightly acid and acidic to neutral and slightly alkaline. The topsoil SOC content has increased in the result of reconstruction but still was below threshold, recommended by municipal regulations. The potassium content and acidity were the main factors, influencing the vegetation condition. The 'weakened' condition of wood vegetation was reported with the lowest values obtained for the Pinus sylvestris, Thuja occidentals and, Sorbus aucuparia. References have developed for planting vegetation. The spatial heterogeneity and high dynamics of urban soils constraints the quantitative assessment of their properties and functions and the use of this information in landscaping. The successful experience of digital soil mapping techniques in urban park allowed solving this problem and highlighted the importance of soil data for creating urban green infrastructure.
Gregory B. Lawrence; Ivan J. Fernandez; Daniel D. Richter; Donald S. Ross; Paul W. Hazlett; Scott W. Bailey; Rock Ouimet; Richard A. F. Warby; Arthur H. Johnson; Henry Lin; James M. Kaste; Andrew G. Lapenis; Timothy J. Sullivan
2013-01-01
Environmental change is monitored in North America through repeated measurements of weather, stream and river flow, air and water quality, and most recently, soil properties. Some skepticism remains, however, about whether repeated soil sampling can effectively distinguish between temporal and spatial variability, and efforts to document soil change in forest...
Selection harvests in Amazonian rainforests: long-term impacts on soil properties
K.L. McNabb; M.S. Miller; B.G. Lockaby; B.J. Stokes; R.G. Clawson; John A. Stanturf; J.N.M. Silva
1997-01-01
Surface soil properties were compared among disturbance classes associated with a single-tree selection harvest study installed in 1979 in the Brazilian Amazon. Response variables included pH, total N, total organic C, extractable P, exchangeable K, Ca, Mg, and bulk density. In general, concentrations of all elements displayed residual effects 16 years after harvests...
NASA Astrophysics Data System (ADS)
Mahalder, B.; Schwartz, J. S.; Palomino, A.; Papanicolaou, T.
2016-12-01
Cohesive soil erodibility and threshold shear stress for stream bed and bank are dependent on both soil physical and geochemical properties in association with the channel vegetative conditions. These properties can be spatially variable therefore making critical shear stress measurement in cohesive soil challenging and leads to a need for a more comprehensive understanding of the erosional processes in streams. Several in-situ and flume-type test devices for estimating critical shear stress have been introduced by different researchers; however reported shear stress estimates per device vary widely in orders of magnitude. Advantages and disadvantages exist between these devices. Development of in-situ test devices leave the bed and/or bank material relatively undisturbed and can capture the variable nature of field soil conditions. However, laboratory flumes provide a means to control environmental conditions that can be quantify and tested. This study was conducted to observe differences in critical shear stress using jet tester and a well-controlled conduit flume. Soil samples were collected from the jet test locations and tested in a pressurized flume following standard operational procedure to calculate the critical shear stress. The results were compared using statistical data analysis (mean-separation ANOVA procedure) to identify possible differences. In addition to the device comparison, the mini jet device was used to measure critical shear stress across geologically diverse regions of Tennessee, USA. Statistical correlation between critical shear stress and the soil physical, and geochemical properties were completed identifying that geological origin plays a significant role in critical shear stress prediction for cohesive soils. Finally, the critical shear stress prediction equations using the jet test data were examined with possible suggestions to modify based on the flume test results.
NASA Astrophysics Data System (ADS)
Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo
2014-05-01
Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.
Carminati, Andrea; Vetterlein, Doris
2013-01-01
Background It is known that the soil near roots, the so-called rhizosphere, has physical and chemical properties different from those of the bulk soil. Rhizosphere properties are the result of several processes: root and soil shrinking/swelling during drying/wetting cycles, soil compaction by root growth, mucilage exuded by root caps, interaction of mucilage with soil particles, mucilage shrinking/swelling and mucilage biodegradation. These processes may lead to variable rhizosphere properties, i.e. the presence of air-filled gaps between soil and roots; water repellence in the rhizosphere caused by drying of mucilage around the soil particles; or water accumulation in the rhizosphere due to the high water-holding capacity of mucilage. The resulting properties are not constant in time but they change as a function of soil condition, root growth rate and mucilage age. Scope We consider such a variability as an expression of rhizosphere plasticity, which may be a strategy for plants to control which part of the root system will have a facilitated access to water and which roots will be disconnected from the soil, for instance by air-filled gaps or by rhizosphere hydrophobicity. To describe such a dualism, we suggest classifying rhizosphere into two categories: class A refers to a rhizosphere covered with hydrated mucilage that optimally connects roots to soil and facilitates water uptake from dry soils. Class B refers to the case of air-filled gaps and/or hydrophobic rhizosphere, which isolate roots from the soil and may limit water uptake from the soil as well water loss to the soil. The main function of roots covered by class B will be long-distance transport of water. Outlook This concept has implications for soil and plant water relations at the plant scale. Root water uptake in dry conditions is expected to shift to regions covered with rhizosphere class A. On the other hand, hydraulic lift may be limited in regions covered with rhizosphere class B. New experimental methods need to be developed and applied to different plant species and soil types, in order to understand whether such dualism in rhizosphere properties is an important mechanism for efficient utilization of scarce resources and drought tolerance. PMID:23235697
The past, present, and future of soils and human health studies
NASA Astrophysics Data System (ADS)
Brevik, E. C.; Sauer, T. J.
2015-01-01
The idea that human health is tied to the soil is not a new one. As far back as circa 1400 BC the Bible depicts Moses as understanding that fertile soil was essential to the well-being of his people. In 400 BC the Greek philosopher Hippocrates provided a list of things that should be considered in a proper medical evaluation, including the properties of the local ground. By the late 1700s and early 1800s, American farmers had recognized that soil properties had some connection to human health. In the modern world, we recognize that soils have a distinct influence on human health. We recognize that soils influence (1) food availability and quality (food security), (2) human contact with various chemicals, and (3) human contact with various pathogens. Soils and human health studies include investigations into nutrient supply through the food chain and routes of exposure to chemicals and pathogens. However, making strong, scientific connections between soils and human health can be difficult. There are multiple variables to consider in the soil environment, meaning traditional scientific studies that seek to isolate and manipulate a single variable often do not provide meaningful data. The complete study of soils and human health also involves many different specialties such as soil scientists, toxicologists, medical professionals, anthropologists, etc. These groups do not traditionally work together on research projects, and do not always effectively communicate with one another. Climate change and how it will affect the soil environment/ecosystem going into the future is another variable affecting the relationship between soils and health. Future successes in soils and human health research will require effectively addressing difficult issues such as these.
NASA Astrophysics Data System (ADS)
Cumming, William Frank Preston
Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.
Technical Note: Orientation of cracks and hydrology in a shrink-swell soil
USDA-ARS?s Scientific Manuscript database
Crack orientations are an important soil physical property that affects water flow, particularly in vertic soils. However, the spatial and temporal variability of crack orientations across different land uses and gilgai features is not well-documented and addressed in hydrology models. Thus there is...
Estimation of effective soil hydraulic properties at field scale via ground albedo neutron sensing
NASA Astrophysics Data System (ADS)
Rivera Villarreyes, C. A.; Baroni, G.; Oswald, S. E.
2012-04-01
Upscaling of soil hydraulic parameters is a big challenge in hydrological research, especially in model applications of water and solute transport processes. In this contest, numerous attempts have been made to optimize soil hydraulic properties using observations of state variables such as soil moisture. However, in most of the cases the observations are limited at the point-scale and then transferred to the model scale. In this way inherent small-scale soil heterogeneities and non-linearity of dominate processes introduce sources of error that can produce significant misinterpretation of hydrological scenarios and unrealistic predictions. On the other hand, remote-sensed soil moisture over large areas is also a new promising approach to derive effective soil hydraulic properties over its observation footprint, but it is still limited to the soil surface. In this study we present a new methodology to derive soil moisture at the intermediate scale between point-scale observations and estimations at the remote-sensed scale. The data are then used for the estimation of effective soil hydraulic parameters. In particular, ground albedo neutron sensing (GANS) was used to derive non-invasive soil water content in a footprint of ca. 600 m diameter and a depth of few decimeters. This approach is based on the crucial role of hydrogen compared to other landscape materials as neutron moderator. As natural neutron measured aboveground depends on soil water content, the vertical footprint of the GANS method, i.e. its penetration depth, does also. Firstly, this study was designed to evaluate the dynamics of GANS vertical footprint and derive a mathematical model for its prediction. To test GANS-soil moisture and its penetration depth, it was accompanied by other soil moisture measurements (FDR) located at 5, 20 and 40 cm depths over the GANS horizontal footprint in a sunflower field (Brandenburg, Germany). Secondly, a HYDRUS-1D model was set up with monitored values of crop height and meteorological variables as input during a four-month period. Parameter estimation (PEST) software was coupled to HYDRUS-1D in order to calibrate soil hydraulic properties based on soil water content data. Thirdly, effective soil hydraulic properties were derived from GANS-soil moisture. Our observations show the potential of GANS to compensate the lack of information at the intermediate scale, soil water content estimation and effective soil properties. Despite measurement volumes, GANS-derived soil water content compared quantitatively to FDRs at several depths. For one-hour estimations, root mean square error was estimated as 0.019, 0.029 and 0.036 m3/m3 for 5 cm, 20 cm and 40 cm depths, respectively. In the context of soil hydraulic properties, this first application of GANS method succeed and its estimations were comparable to those derived by other approaches.
Visible-near infrared spectroscopy as a tool to improve mapping of soil properties
NASA Astrophysics Data System (ADS)
Evgrafova, Alevtina; Kühnel, Anna; Bogner, Christina; Haase, Ina; Shibistova, Olga; Guggenberger, Georg; Tananaev, Nikita; Sauheitl, Leopold; Spielvogel, Sandra
2017-04-01
Spectroscopic measurements, which are non-destructive, precise and rapid, can be used to predict soil properties and help estimate the spatial variability of soil properties at the pedon scale. These estimations are required for quantifying soil properties with higher precision, identifying the changes in soil properties and ecosystem response to climate change as well as increasing the estimation accuracy of soil-related models. Our objectives were to (i) predict soil properties for nested samples (n = 296) using the laboratory-based visible-near infrared (vis-NIR) spectra of air-dried (<2 mm) soil samples and values of measured soil properties for gridded samples (n = 174) as calibration and validation sets; (ii) estimate the precision and predictive accuracy of an empirical spectral model using (a) our own spectral library and (b) the global spectral library; (iii) support the global spectral library with obtained vis-NIR spectral data on permafrost-affected soils. The soil samples were collected from three permafrost-affected soil profiles underlain by permafrost at various depths between 23 cm to 57.5 cm below the surface (Cryosols) and one soil profile with no presence of permafrost within the upper 100 cm layer (Cambisol) in order to characterize the spatial distribution and variability of soil properties. The gridded soil samples (n = 174) were collected using an 80 cm wide grid with a mesh size of 10 cm on both axes. In addition, 300 nested soil samples were collected using a grid of 12 cm by 12 cm (25 samples per grid) from a hole of 1 cm in a diameter with a distance from the next sample of 1 cm. Due to a small amount of available soil material (< 1.5 g), 296 nested soil samples were analyzed only using vis-NIR spectroscopy. The air-dried mineral gridded soil samples (n = 174) were sieved through a 2-mm sieve and ground with an agate mortar prior to the elemental analysis. The soil organic carbon and total nitrogen concentrations (in %) were determined using a dry combustion method on the Vario EL cube analyzer (Elementar Analysensysteme GmbH, Germany). Inorganic C was removed from the mineral soil samples with pH values higher than 7 prior to the elemental analysis using the volatilization method (HCl, 6 hours). The pH of soil samples was measured in 0.01 M CaCl2 using a 1:2 soil:solution ratio. However, for soil sample with a high in organic matter content, a 1:10 ratio was applied. We also measured oxalate and dithionite extracted iron, aluminum and manganese oxides and hydroxides using inductively coupled plasma optical emission spectroscopy (Varian Vista MPX ICP-OES, Agilent Technologies, USA). We predicted the above-mentioned soil properties for all nested samples using partial least squares regression, which was performed using R program. We can conclude that vis-NIR spectroscopy can be used effectively in order to describe, estimate and further map the spatial patterns of soil properties using geostatistical methods. This research could also help to improve the global soil spectral library taking into account that only few previous applications of vis-NIR spectroscopy were conducted on permafrost-affected soils of Northern Siberia. Keywords: Visible-near infrared spectroscopy, vis-NIR, permafrost-affected soils, Siberia, partial least squares regression.
Ebel, Brian A.; Rengers, Francis K.; Tucker, Gregory E.
2016-01-01
Hydrologic response to extreme rainfall in disturbed landscapes is poorly understood because of the paucity of measurements. A unique opportunity presented itself when extreme rainfall in September 2013 fell on a headwater catchment (i.e., <1 ha) in Colorado, USA that had previously been burned by a wildfire in 2010. We compared measurements of soil-hydraulic properties, soil saturation from subsurface sensors, and estimated peak runoff during the extreme rainfall with numerical simulations of runoff generation and subsurface hydrologic response during this event. The simulations were used to explore differences in runoff generation between the wildfire-affected headwater catchment, a simulated unburned case, and for uniform versus spatially variable parameterizations of soil-hydraulic properties that affect infiltration and runoff generation in burned landscapes. Despite 3 years of elapsed time since the 2010 wildfire, observations and simulations pointed to substantial surface runoff generation in the wildfire-affected headwater catchment by the infiltration-excess mechanism while no surface runoff was generated in the unburned case. The surface runoff generation was the result of incomplete recovery of soil-hydraulic properties in the burned area, suggesting recovery takes longer than 3 years. Moreover, spatially variable soil-hydraulic property parameterizations produced longer duration but lower peak-flow infiltration-excess runoff, compared to uniform parameterization, which may have important hillslope sediment export and geomorphologic implications during long duration, extreme rainfall. The majority of the simulated surface runoff in the spatially variable cases came from connected near-channel contributing areas, which was a substantially smaller contributing area than the uniform simulations.
NASA Astrophysics Data System (ADS)
Chouaib, Wafa; Caldwell, Peter V.; Alila, Younes
2018-04-01
This paper advances the physical understanding of the flow duration curve (FDC) regional variation. It provides a process-based analysis of the interaction between climate and landscape properties to explain disparities in FDC shapes. We used (i) long term measured flow and precipitation data over 73 catchments from the eastern US. (ii) We calibrated the Sacramento model (SAC-SMA) to simulate soil moisture and flow components FDCs. The catchments classification based on storm characteristics pointed to the effect of catchments landscape properties on the precipitation variability and consequently on the FDC shapes. The landscape properties effect was pronounce such that low value of the slope of FDC (SFDC)-hinting at limited flow variability-were present in regions of high precipitation variability. Whereas, in regions with low precipitation variability the SFDCs were of larger values. The topographic index distribution, at the catchment scale, indicated that saturation excess overland flow mitigated the flow variability under conditions of low elevations with large soil moisture storage capacity and high infiltration rates. The SFDCs increased due to the predominant subsurface stormflow in catchments at high elevations with limited soil moisture storage capacity and low infiltration rates. Our analyses also highlighted the major role of soil infiltration rates on the FDC despite the impact of the predominant runoff generation mechanism and catchment elevation. In conditions of slow infiltration rates in soils of large moisture storage capacity (at low elevations) and predominant saturation excess, the SFDCs were of larger values. On the other hand, the SFDCs decreased in catchments of prevalent subsurface stormflow and poorly drained soils of small soil moisture storage capacity. The analysis of the flow components FDCs demonstrated that the interflow contribution to the response was the higher in catchments with large value of slope of the FDC. The surface flow FDC was the most affected by the precipitation as it tracked the precipitation duration curve (PDC). In catchments with low SFDCs, this became less applicable as surface flow FDC diverged from PDC at the upper tail (> 40% of the flow percentile). The interflow and baseflow FDCs illustrated most the filtering effect on the precipitation. The process understanding we achieved in this study is key for flow simulation and assessment in addition to future works focusing on process-based FDC predictions.
Welp, Gerhard; Thiel, Michael
2017-01-01
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources. PMID:28114334
Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography
NASA Astrophysics Data System (ADS)
Jarecke, K. M.; Wondzell, S. M.; Bladon, K. D.
2016-12-01
Hillslope ecohydrological processes, including subsurface water flow and plant water uptake, are strongly influenced by soil moisture. However, the factors controlling spatial and temporal variability of soil moisture in steep, mountainous terrain are poorly understood. We asked: How do topography and soils interact to control the spatial and temporal variability of soil moisture in steep, Douglas-fir dominated hillslopes in the western Cascades? We will present a preliminary analysis of bimonthly soil moisture variability from July-November 2016 at 0-30 and 0-60 cm depth across spatially extensive convergent and divergent topographic positions in Watershed 1 of the H.J. Andrews Experimental Forest in central Oregon. Soil moisture monitoring locations were selected following a 5 m LIDAR analysis of topographic position, aspect, and slope. Topographic position index (TPI) was calculated as the difference in elevation to the mean elevation within a 30 m radius. Convergent (negative TPI values) and divergent (positive TPI values) monitoring locations were established along northwest to northeast-facing aspects and within 25-55 degree slopes. We hypothesized that topographic position (convergent vs. divergent), as well as soil physical properties (e.g., texture, bulk density), control variation in hillslope soil moisture at the sub-watershed scale. In addition, we expected the relative importance of hillslope topography to the spatial variability in soil moisture to differ seasonally. By comparing the spatiotemporal variability of hillslope soil moisture across topographic positions, our research provides a foundation for additional understanding of subsurface flow processes and plant-available soil-water in forests with steep, highly dissected terrain.
Siqueira, Glécio Machado; Dafonte, Jorge Dafonte; Valcárcel Armesto, Montserrat; Silva, Ênio Farias França e
2014-01-01
The apparent soil electrical conductivity (ECa) was continuously recorded in three successive dates using electromagnetic induction in horizontal (ECa-H) and vertical (ECa-V) dipole modes at a 6 ha plot located in Northwestern Spain. One of the ECa data sets was used to devise an optimized sampling scheme consisting of 40 points. Soil was sampled at the 0.0–0.3 m depth, in these 40 points, and analyzed for sand, silt, and clay content; gravimetric water content; and electrical conductivity of saturated soil paste. Coefficients of correlation between ECa and gravimetric soil water content (0.685 for ECa-V and 0.649 for ECa-H) were higher than those between ECa and clay content (ranging from 0.197 to 0.495, when different ECa recording dates were taken into account). Ordinary and universal kriging have been used to assess the patterns of spatial variability of the ECa data sets recorded at successive dates and the analyzed soil properties. Ordinary and universal cokriging methods have improved the estimation of gravimetric soil water content using the data of ECa as secondary variable with respect to the use of ordinary kriging. PMID:25614893
Siqueira, Glécio Machado; Dafonte, Jorge Dafonte; Valcárcel Armesto, Montserrat; França e Silva, Ênio Farias
2014-01-01
The apparent soil electrical conductivity (ECa) was continuously recorded in three successive dates using electromagnetic induction in horizontal (ECa-H) and vertical (ECa-V) dipole modes at a 6 ha plot located in Northwestern Spain. One of the ECa data sets was used to devise an optimized sampling scheme consisting of 40 points. Soil was sampled at the 0.0-0.3 m depth, in these 40 points, and analyzed for sand, silt, and clay content; gravimetric water content; and electrical conductivity of saturated soil paste. Coefficients of correlation between ECa and gravimetric soil water content (0.685 for ECa-V and 0.649 for ECa-H) were higher than those between ECa and clay content (ranging from 0.197 to 0.495, when different ECa recording dates were taken into account). Ordinary and universal kriging have been used to assess the patterns of spatial variability of the ECa data sets recorded at successive dates and the analyzed soil properties. Ordinary and universal cokriging methods have improved the estimation of gravimetric soil water content using the data of ECa as secondary variable with respect to the use of ordinary kriging.
Loizeau, Vincent; Ciffroy, Philippe; Roustan, Yelva; Musson-Genon, Luc
2014-09-15
Semi-volatile organic compounds (SVOCs) are subject to Long-Range Atmospheric Transport because of transport-deposition-reemission successive processes. Several experimental data available in the literature suggest that soil is a non-negligible contributor of SVOCs to atmosphere. Then coupling soil and atmosphere in integrated coupled models and simulating reemission processes can be essential for estimating atmospheric concentration of several pollutants. However, the sources of uncertainty and variability are multiple (soil properties, meteorological conditions, chemical-specific parameters) and can significantly influence the determination of reemissions. In order to identify the key parameters in reemission modeling and their effect on global modeling uncertainty, we conducted a sensitivity analysis targeted on the 'reemission' output variable. Different parameters were tested, including soil properties, partition coefficients and meteorological conditions. We performed EFAST sensitivity analysis for four chemicals (benzo-a-pyrene, hexachlorobenzene, PCB-28 and lindane) and different spatial scenari (regional and continental scales). Partition coefficients between air, solid and water phases are influent, depending on the precision of data and global behavior of the chemical. Reemissions showed a lower variability to soil parameters (soil organic matter and water contents at field capacity and wilting point). A mapping of these parameters at a regional scale is sufficient to correctly estimate reemissions when compared to other sources of uncertainty. Copyright © 2014 Elsevier B.V. All rights reserved.
Strategies for soil-based precision agriculture in cotton
NASA Astrophysics Data System (ADS)
Neely, Haly L.; Morgan, Cristine L. S.; Stanislav, Scott; Rouze, Gregory; Shi, Yeyin; Thomasson, J. Alex; Valasek, John; Olsenholler, Jeff
2016-05-01
The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.
Spatial variability of specific surface area of arable soils in Poland
NASA Astrophysics Data System (ADS)
Sokolowski, S.; Sokolowska, Z.; Usowicz, B.
2012-04-01
Evaluation of soil spatial variability is an important issue in agrophysics and in environmental research. Knowledge of spatial variability of physico-chemical properties enables a better understanding of several processes that take place in soils. In particular, it is well known that mineralogical, organic, as well as particle-size compositions of soils vary in a wide range. Specific surface area of soils is one of the most significant characteristics of soils. It can be not only related to the type of soil, mainly to the content of clay, but also largely determines several physical and chemical properties of soils and is often used as a controlling factor in numerous biological processes. Knowledge of the specific surface area is necessary in calculating certain basic soil characteristics, such as the dielectric permeability of soil, water retention curve, water transport in the soil, cation exchange capacity and pesticide adsorption. The aim of the present study is two-fold. First, we carry out recognition of soil total specific surface area patterns in the territory of Poland and perform the investigation of features of its spatial variability. Next, semivariograms and fractal analysis are used to characterize and compare the spatial variability of soil specific surface area in two soil horizons (A and B). Specific surface area of about 1000 samples was determined by analyzing water vapor adsorption isotherms via the BET method. The collected data of the values of specific surface area of mineral soil representatives for the territory of Poland were then used to describe its spatial variability by employing geostatistical techniques and fractal theory. Using the data calculated for some selected points within the entire territory and along selected directions, the values of semivariance were determined. The slope of the regression line of the log-log plot of semi-variance versus the distance was used to estimate the fractal dimension, D. Specific surface area in A and B horizons was space-dependent, with the range of spatial dependence of about 2.5°. Variogram surfaces showed anisotropy of the specific surface area in both horizons with a trend toward the W to E directions. The smallest fractal dimensions were obtained for W to E directions and the highest values - for S to N directions. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.
NASA Astrophysics Data System (ADS)
Fan, Linfeng; Lehmann, Peter; Or, Dani
2016-03-01
Spatial variations in soil properties affect key hydrological processes, yet their role in soil mechanical response to hydro-mechanical loading is rarely considered. This study aims to fill this gap by systematically quantifying effects of spatial variations in soil type and initial water content on rapid rainfall-induced shallow landslide predictions at the hillslope- and catchment-scales. We employed a physically-based landslide triggering model that considers mechanical interactions among soil columns governed by strength thresholds. At the hillslope scale, we found that the emergence of weak regions induced by spatial variations of soil type and initial water content resulted in early triggering of landslides with smaller volumes of released mass relative to a homogeneous slope. At the catchment scale, initial water content was linked to a topographic wetness index, whereas soil type varied deterministically with soil depth considering spatially correlated stochastic components. Results indicate that a strong spatial organization of initial water content delays landslide triggering, whereas spatially linked soil type with soil depth promoted landslide initiation. Increasing the standard deviation and correlation length of the stochastic component of soil type increases landslide volume and hastens onset of landslides. The study illustrates that for similar external boundary conditions and mean soil properties, landslide characteristics vary significantly with soil variability, hence it must be considered for improved landslide model predictions.
NASA Astrophysics Data System (ADS)
Bogunović, Igor; Pereira, Paulo; Šeput, Miranda
2016-04-01
Soil organic carbon (SOC), pH, available phosphorus (P), and potassium (K) are some of the most important factors to soil fertility. These soil parameters are highly variable in space and time, with implications to crop production. The aim of this work is study the spatial variability of SOC, pH, P and K in an organic farm located in river Rasa valley (Croatia). A regular grid (100 x 100 m) was designed and 182 samples were collected on Silty Clay Loam soil. P, K and SOC showed moderate heterogeneity with coefficient of variation (CV) of 21.6%, 32.8% and 51.9%, respectively. Soil pH record low spatial variability with CV of 1.5%. Soil pH, P and SOC did not follow normal distribution. Only after a Box-Cox transformation, data respected the normality requirements. Directional exponential models were the best fitted and used to describe spatial autocorrelation. Soil pH, P and SOC showed strong spatial dependence with nugget to sill ratio with 13.78%, 0.00% and 20.29%, respectively. Only K recorded moderate spatial dependence. Semivariogram ranges indicate that future sampling interval could be 150 - 200 m in order to reduce sampling costs. Fourteen different interpolation models for mapping soil properties were tested. The method with lowest Root Mean Square Error was the most appropriated to map the variable. The results showed that radial basis function models (Spline with Tension and Completely Regularized Spline) for P and K were the best predictors, while Thin Plate Spline and inverse distance weighting models were the least accurate. The best interpolator for pH and SOC was the local polynomial with the power of 1, while the least accurate were Thin Plate Spline. According to soil nutrient maps investigated area record very rich supply with K while P supply was insufficient on largest part of area. Soil pH maps showed mostly neutral reaction while individual parts of alkaline soil indicate the possibility of penetration of seawater and salt accumulation in the soil profile. Future research should focus on spatial patterns on soil pH, electrical conductivity and sodium adsorption ratio. Keywords: geostatistics, semivariogram, interpolation models, soil chemical properties
Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.
2003-01-01
Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.
Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.
2008-01-01
Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.
NASA Astrophysics Data System (ADS)
Yazdanpanah, Najme; Mahmoodabadi, Majid
2010-05-01
Soil salinity and sodicity are escalating problems worldwide, especially in Iran since 90 percent of the country is located in arid and semi-arid. Reclamation of sodic soils involves replacement of exchangeable Na by Ca. While some researches have been undertaken in the controllable laboratory conditions using soil column with emphasis on soil properties, the properties of effluent as a measure of soil reclamation remain unstudied. In addition, little attention has been paid to the temporal variability of effluent quality. The objective of this study was to investigate the effect of different amendments consist of gypsum, manure, pistachio residue, and their combination for ameliorating a calcareous saline sodic soil. Temporal variability of effluent properties during reclamation period was studied, as well. A laboratory experiment was conducted to evaluate the effect of different amendments using soil columns. The amendment treatments were: control, manure, pistachio residue, gypsum powder (equivalent of gypsum requirement), manure+gypsum and pistachio residue+gypsum, which were applied once in the beginning of the experiment. The study was performed in 120 days period and totally four irrigation treatments were supplied to each column. After irrigations, the effluent samples were collected every day at the bottom of the soil columns and were analyzed. The results show that for all treatments, cations (e.g. Ca, Mg, Na and K) in the outflow decreased with time, exponentially. Manure treatment resulted in highest rate of Ca, Mg, Na leaching from soil solution, in spite of the control which had the lowest rate. In addition, pistachio residue had the most effect on K leaching. Manure treatment showed the most EC and SAR in the leachate, while gypsum application leads to the least rate of them. The findings of this research reveal different rates of cations leaching from soil profile, which is important in environmental issues. Keywords: Saline sodic soil, Reclamation, Organic Matter, Gypsum, Leachate.
USDA-ARS?s Scientific Manuscript database
Use of electromagnetic induction (EMI) instruments has increased as a tool to map soils because it provides a means of locating suitable sampling sites that provide the basis for mapping the spatial variability of various soil properties either directly or indirectly measured with EMI, including sa...
Spatial variation of peat soil properties in the oil-producing region of northeastern Sakhalin
NASA Astrophysics Data System (ADS)
Lipatov, D. N.; Shcheglov, A. I.; Manakhov, D. V.; Zavgorodnyaya, Yu. A.; Rozanova, M. S.; Brekhov, P. T.
2017-07-01
Morphology and properties of medium-deep oligotrophic peat, oligotrophic peat gley, pyrogenic oligotrophic peat gley, and peat gley soils on subshrub-cotton grass-sphagnum bogs and in swampy larch forests of northeastern Sakhalin have been studied. Variation in the thickness and reserves of litters in the studied bog and forest biogeocenoses has been analyzed. The profile distribution and spatial variability of moisture, density, ash, and pHKCl in separate groups of peat soils have been described. The content and spatial variability of petroleum hydrocarbons have been considered in relation to the accumulation of natural bitumoids by peat soils and the technogenic pressing in the oil-producing region. Variation of each parameter at different distances (10, 50, and 1000 m) has been estimated using a hierarchical sampling scheme. The spatial conjugation of soil parameters has been studied by factor analysis using the principal components method and Spearman correlation coefficients. Regression equations have been proposed to describe relationships of ash content with soil density and content of petroleum hydrocarbons in peat horizons.
Anaka, Alison; Wickstrom, Mark; Siciliano, Steven Douglas
2008-03-01
Industrial and human activities in the Arctic regions may pose a risk to terrestrial Arctic ecosystem functions. One of the most common terrestrial toxicological end points, primary productivity, typically is assessed using a plant phytotoxicity test. Because of cryoturbation, a soil mixing process common in polar regions, we hypothesized that phytotoxicity test results in Arctic soils would be highly variable compared to other terrestrial ecosystems. The variability associated with phytotoxicity tests was evaluated using Environment Canada's standardized plant toxicity test in three cryoturbated soils from Canada's Arctic exposed to a reference toxicant, boric acid. Northern wheatgrass (Elymus lanceolatus) not only was more sensitive to toxicants in Arctic soils, its response to toxicants was more variable compared to that in temperate soils. The phytotoxicity of boric acid in cryosols was much greater than commonly reported in other soils, with a boric acid concentration of less than 150 microg/g soil needed to inhibit root and shoot growth by 20%. Large variability also was found in the phytotoxicity test results, with coefficients of variation for 10 samples ranging from 160 to 79%. The increased toxicity of boric acid in cryosols and variability in test response was not explained by soil properties. Based on our admittedly limited data set of three different Arctic soils, we recommend that more than 30 samples be taken from each control and potentially impacted area to accurately assess contaminant effects at sites in northern Canada. Such intensive sampling will insure that false-negative results for toxicant impacts in Arctic soils are minimized.
Spatiotemporal predictions of soil properties and states in variably saturated landscapes
NASA Astrophysics Data System (ADS)
Franz, Trenton E.; Loecke, Terrance D.; Burgin, Amy J.; Zhou, Yuzhen; Le, Tri; Moscicki, David
2017-07-01
Understanding greenhouse gas (GHG) fluxes from landscapes with variably saturated soil conditions is challenging given the highly dynamic nature of GHG fluxes in both space and time, dubbed hot spots, and hot moments. On one hand, our ability to directly monitor these processes is limited by sparse in situ and surface chamber observational networks. On the other hand, remote sensing approaches provide spatial data sets but are limited by infrequent imaging over time. We use a robust statistical framework to merge sparse sensor network observations with reconnaissance style hydrogeophysical mapping at a well-characterized site in Ohio. We find that combining time-lapse electromagnetic induction surveys with empirical orthogonal functions provides additional environmental covariates related to soil properties and states at high spatial resolutions ( 5 m). A cross-validation experiment using eight different spatial interpolation methods versus 120 in situ soil cores indicated an 30% reduction in root-mean-square error for soil properties (clay weight percent and total soil carbon weight percent) using hydrogeophysical derived environmental covariates with regression kriging. In addition, the hydrogeophysical derived environmental covariates were found to be good predictors of soil states (soil temperature, soil water content, and soil oxygen). The presented framework allows for temporal gap filling of individual sensor data sets as well as provides flexible geometric interpolation to complex areas/volumes. We anticipate that the framework, with its flexible temporal and spatial monitoring options, will be useful in designing future monitoring networks as well as support the next generation of hyper-resolution hydrologic and biogeochemical models.
Sorption-desorption of fipronil in some soils, as influenced by ionic strength, pH and temperature.
Singh, Anand; Srivastava, Anjana; Srivastava, Prakash C
2016-08-01
The sorption-desorpion of fipronil insecticide is influenced by soil properties and variables such as pH, ionic strength, temperature, etc. A better understanding of soil properties and these variables in sorption-desorption processes by quantification of fipronil using liquid chromatography may help to optimise suitable soil management to reduce contamination of surface and groundwaters. In the present investigation, the sorption-desorption of fipronil was studied in some soils at varying concentrations, ionic strengths, temperatures and pH values, and IR specta of fipronil sorbed onto soils were studied. The sorption of fipronil onto soils conformed to the Freundlich isotherm model. The sorption-desorption of fipronil varied with ionic strength in each of the soils. Sorption decreased but desorption increased with temperature. Sorption did not change with increasing pH, but for desorption there was no correlation. The cumulative desorption of fipronil from soil was significantly and inversely related to soil organic carbon content. IR spectra of sorbed fipronil showed the involvement of amino, nitrile, sulfone, chloro and fluoro groups and the pyrazole nucleus of the fipronil molecule. The sorption of fipronil onto soils appeared to be a physical process with the involvement of hydrogen bonding. An increase in soil organic carbon may help to reduce desorption of fipronil. High-temperature regimes are more conducive to the desorption. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.
Using Remote Sensing Data to Evaluate Surface Soil Properties in Alabama Ultisols
NASA Technical Reports Server (NTRS)
Sullivan, Dana G.; Shaw, Joey N.; Rickman, Doug; Mask, Paul L.; Luvall, Jeff
2005-01-01
Evaluation of surface soil properties via remote sensing could facilitate soil survey mapping, erosion prediction and allocation of agrochemicals for precision management. The objective of this study was to evaluate the relationship between soil spectral signature and surface soil properties in conventionally managed row crop systems. High-resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil organic carbon, particle size distribution, and citrate dithionite extractable iron content. Surface roughness, soil water content, and crusting were also measured during sampling. Two methods of analysis were evaluated: 1) multiple linear regression using common spectral band ratios, and 2) partial least squares regression. Our data show that thermal infrared spectra are highly, linearly related to soil organic carbon, sand and clay content. Soil organic carbon content was the most difficult to quantify in these highly weathered systems, where soil organic carbon was generally less than 1.2%. Estimates of sand and clay content were best using partial least squares regression at the Valley site, explaining 42-59% of the variability. In the Coastal Plain, sandy surfaces prone to crusting limited estimates of sand and clay content via partial least squares and regression with common band ratios. Estimates of iron oxide content were a function of mineralogy and best accomplished using specific band ratios, with regression explaining 36-65% of the variability at the Valley and Coastal Plain sites, respectively.
Correlations and spatial variability of soil physical properties in harvested piedmont forests
Emily A. Carter; J.N. Shaw
2002-01-01
Soil response to timber harvest trafficking was similar for eroded soils in two locations of the Piedmont of Alabama. Pre-harvest and post-harvest data indicated compaction to be present to a depth of 40 cm as indicated by cone index measurements, with the most significant changes occurring in the upper 20 cm. The degree of spatial dependence differed among soil...
J.M. Warren; F.C. Meinzer; J.R. Brooks; J.-C. Domec; R. Coulombe
2006-01-01
We incorporated soil/plant biophysical properties into a simple model to predict seasonal trajectories of hydraulic redistribution (HR). We measured soil water content, water potential root conductivity, and climate across multiple years in two old-growth coniferous forests. The HR variability within sites (0 to 0.5 mm/d) was linked to spatial patterns of roots, soil...
Multivariate control of plant species richness and community biomass in blackland prairie
Weiher, E.; Forbes, S.; Schauwecker, T.; Grace, J.B.
2004-01-01
Recent studies have shown that patterns of plant species richness and community biomass are best understood in a multivariate context. The objective of this study was to develop and evaluate a multivariate hypothesis about how herbaceous biomass and richness relate to gradients in soil conditions and woody plant cover in blackland prairies. Structural equation modeling was used to investigate how soil characteristics and shade by scattered Juniperus virginiana trees relate to standing biomass and species richness in 99 0.25 m2 quadrats collected in eastern Mississippi, USA. Analysis proceeded in two stages. In the first stage, we evaluated the hypothesis that correlations among soil parameters could be represented by two underlying (latent) soil factors, mineral content and organic content. In the second stage, we evaluated the hypothesis that richness and biomass were related to (1) soil properties, (2) tree canopy extent, and (3) each other (i.e. reciprocal effects between richness and biomass). With some modification to the details of the original model, it was found that soil properties could be represented as two latent variables. In the overall model, 51% and 53% of the observed variation in richness and biomass were explained. The order of importance for variables explaining variations in richness was (1) soil organic content, (2) soil mineral content, (3) community biomass, and (4) tree canopy extent. The order of importance for variables explaining biomass was (1) tree canopy and (2) soil organic content, with neither soil mineral content nor species richness explaining significant variation in biomass. Based on these findings, we conclude that variations in richness are uniquely related to both variations in soil conditions and variations in herbaceous biomass. We further conclude that there is no evidence in these data for effects of species richness on biomass.
Li, Yue; Liu, Yinghui; Wu, Shanmei; Niu, Lei; Tian, Yuqiang
2015-01-01
The role of soil microbial variables in shaping the temporal variability of soil respiration has been well acknowledged but is poorly understood, particularly under elevated nitrogen (N) deposition conditions. We measured soil respiration along with soil microbial properties during the early, middle, and late growing seasons in temperate grassland plots that had been treated with N additions of 0, 2, 4, 8, 16, or 32 g N m−2 yr−1 for 10 years. Representing the averages over three observation periods, total (Rs) and heterotrophic (Rh) respiration were highest with 4 g N m−2 yr−1, but autotrophic respiration (Ra) was highest with 8 to 16 g N m−2 yr−1. Also, the responses of Rh and Ra were unsynchronized considering the periods separately. N addition had no significant impact on the temperature sensitivity (Q10) for Rs but inhibited the Q10 for Rh. Significant interactions between observation period and N level occurred in soil respiration components, and the temporal variations in soil respiration components were mostly associated with changes in microbial biomass carbon (MBC) and phospholipid fatty acids (PLFAs). Further observation on soil organic carbon and root biomass is needed to reveal the long-term effect of N deposition on soil C sequestration. PMID:26678303
Spatial prediction of near surface soil water retention functions using hydrogeophysics
NASA Astrophysics Data System (ADS)
Gibson, J. P.; Franz, T. E.
2017-12-01
The hydrological community often turns to widely available spatial datasets such as SSURGO to characterize the spatial variability of soil across a landscape of interest. This has served as a reasonable first approximation when lacking localized soil data. However, previous work has shown that information loss within land surface models primarily stems from parameterization. Localized soil sampling is both expensive and time intense, and thus a need exists in connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with larger spatial datasets. In this work, we utilize 2 geophysical techniques; cosmic ray neutron probe and electromagnetic induction, to identify temporally stable soil moisture patterns. This is achieved by measuring numerous times over a range of wet to dry field conditions in order to apply an empirical orthogonal function. We then present measured water retention functions of shallow cores extracted within each temporally stable zone. Lastly, we use soil moisture patterns as a covariate to predict soil hydraulic properties in areas without measurement and validate using a leave-one-out cross validation analysis. Using these approaches to better constrain soil hydraulic property variability, we speculate that further research can better estimate hydrologic fluxes in areas of interest.
Can APEX Represent In-Field Spatial Variability and Simulate Its Effects On Crop Yields?
USDA-ARS?s Scientific Manuscript database
Precision agriculture, from variable rate nitrogen application to precision irrigation, promises improved management of resources by considering the spatial variability of topography and soil properties. Hydrologic models need to simulate the effects of this variability if they are to inform about t...
Investigating local controls on soil moisture temporal stability using an inverse modeling approach
NASA Astrophysics Data System (ADS)
Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry
2013-04-01
A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).
Zhang, Houxi; Zhuang, Shunyao; Qian, Haiyan; Wang, Feng; Ji, Haibao
2015-01-01
Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production. PMID:25789615
NASA Astrophysics Data System (ADS)
Fois, Laura; Montaldo, Nicola
2017-04-01
Soil moisture plays a key role in water and energy exchanges between soil, vegetation and atmosphere. For water resources planning and managementthesoil moistureneeds to be accurately and spatially monitored, specially where the risk of desertification is high, such as Mediterranean basins. In this sense active remote sensors are very attractive for soil moisture monitoring. But Mediterranean basinsaretypicallycharacterized by strong topography and high spatial variability of physiographic properties, and only high spatial resolution sensorsare potentially able to monitor the strong soil moisture spatial variability.In this regard the Envisat ASAR (Advanced Synthetic Aperture Radar) sensor offers the attractive opportunity ofsoil moisture mapping at fine spatial and temporal resolutions(up to 30 m, every 30 days). We test the ASAR sensor for soil moisture estimate in an interesting Sardinian case study, the Mulargia basin withan area of about 70 sq.km. The position of the Sardinia island in the center of the western Mediterranean Sea basin, its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. The Mulargia basin is a typical Mediterranean basinin water-limited conditions, and is an experimental basin from 2003. For soil moisture mapping23 satellite ASAR imagery at single and dual polarization were acquired for the 2003-2004period.Satellite observationsmay bevalidated through spatially distributed soil moisture ground-truth data, collected over the whole basin using the TDR technique and the gravimetric method, in days with available radar images. The results show that ASAR sensor observations can be successfully used for soil moisture mapping at different seasons, both wet and dry, but an accurate calibration with field data is necessary. We detect a strong relationship between the soil moisture spatial variability and the physiographic properties of the basin, such as soil water storage capacity, deep and texture of soils, type and density of vegetation, and topographic parameters. Finally we demonstrate that the high resolution ASAR imagery are an attractive tool for estimating surface soil moisture at basin scale, offering a unique opportunity for monitoring the soil moisture spatial variability in typical Mediterranean basins.
Forest thinning and soil respiration in a ponderosa pine plantation in the Sierra Nevada.
Tang, Jianwu; Qi, Ye; Xu, Ming; Misson, Laurent; Goldstein, Allen H
2005-01-01
Soil respiration is controlled by soil temperature, soil water, fine roots, microbial activity, and soil physical and chemical properties. Forest thinning changes soil temperature, soil water content, and root density and activity, and thus changes soil respiration. We measured soil respiration monthly and soil temperature and volumetric soil water continuously in a young ponderosa pine (Pinus ponderosa Dougl. ex P. Laws. & C. Laws.) plantation in the Sierra Nevada Mountains in California from June 1998 to May 2000 (before a thinning that removed 30% of the biomass), and from May to December 2001 (after thinning). Thinning increased the spatial homogeneity of soil temperature and respiration. We conducted a multivariate analysis with two independent variables of soil temperature and water and a categorical variable representing the thinning event to simulate soil respiration and assess the effect of thinning. Thinning did not change the sensitivity of soil respiration to temperature or to water, but decreased total soil respiration by 13% at a given temperature and water content. This decrease in soil respiration was likely associated with the decrease in root density after thinning. With a model driven by continuous soil temperature and water time series, we estimated that total soil respiration was 948, 949 and 831 g C m(-2) year(-1) in the years 1999, 2000 and 2001, respectively. Although thinning reduced soil respiration at a given temperature and water content, because of natural climate variability and the thinning effect on soil temperature and water, actual cumulative soil respiration showed no clear trend following thinning. We conclude that the effect of forest thinning on soil respiration is the combined result of a decrease in root respiration, an increase in soil organic matter, and changes in soil temperature and water due to both thinning and interannual climate variability.
Topography effect on soil organic carbon pool in Mediterranean natural areas (Southern Spain)
NASA Astrophysics Data System (ADS)
Parras-Alcántara, Luis; Lozan-García, Beatriz; Galán-Espejo, Arantxa
2014-05-01
Soils are important reservoirs of carbon, in fact, the primary terrestrial pool of organic carbon (OC) that accounts more than 75% of the Earth's terrestrial OC are the soils. In addition, soils have the ability to store carbon for a long time, playing a crucial role in the overall carbon cycle. In Spanish soils, climate, use and management are very influential in the carbon variability, mainly in the soils in Mediterranean dry climate, characterized by its low OC content, weak structure and readily degradable. Generally, the capacity to soil carbon store depends on abiotic factors such as the climate and mineralogical composition, but also depends on soil use and management. The principal factors that affect to forest soils carbon concentration and stock are: climate, landscape, landscape position, slope, latitude, chemical properties, texture and aggregation, anthropogenic factors, natural disturbance - wind, fire, drought, insects and diseases…etc. The soil organic matter (SOM), given by the total organic carbon content (TOC) is one of the main indicators of soil quality. Several studies have been carried out to estimate differences in SOC in relation to soil properties, land uses and climate. Although the impact of topographic aspect on soil properties is widely recognized, relatively few studies have been conducted to examine the role of aspect on SOC content globally. Studies indicate some variations in soil properties related to topographic. Topographic aspect induces local variation in temperature and precipitation solar radiation and relative humidity, which along with chemical and physical composition of the substrate, are the main regulators of decomposition rates of SOM. The spatial variation of soil properties is significantly influenced by some environmental factors such as topographic aspect that induced microclimate differences, topographic (landscape) positions, parent materials, and vegetation communities. Many attempts have been made to quantify the relationships between topographical parameters and soil properties. Researchers suggested some promising indicators such as pH, organic matter, exchangeable cations, total exchangeable basis, ratio of primary to secondary minerals, free oxides, carbonates and physical properties such as, particle size distribution, moisture content, color, bulk density and depth to specific horizon. If we considered SOC and TN how indicators of soil quality it is necessary to explain the relationship between the soil properties and topographic position, furthermore, is necessary establish indicator of the soil quality. In this regard, the stratification ratio (SR) is the most used. Soil development in this region is genetically complicated by three important soil forming factors: relief, fragility of this environment and absence of good vegetation (erosion by water) and the use and management (CT). Very little literature is published on soil variability and its relationship with topographic positions within such fragile environment. There are few reports on stratification of the SOC, TN and C:N ratio as affected by topography in natural areas. In this context, the objectives of this study were; assess the SOC in the soils, its vertical distribution in the profile and analyze the accumulation and SR of SOC along a topographic gradient and their relationship to soil depth in arid Mediterranean climate in Spain.
One perspective on spatial variability in geologic mapping
Markewich, H.W.; Cooper, S.C.
1991-01-01
This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Farrington, Stephen P.
Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance ismore » directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.« less
NASA Technical Reports Server (NTRS)
Famiglietti, J. S.; Wood, Eric F.
1993-01-01
A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.
Fire and fire-suppression impacts on forest-soil carbon [Chapter 13
Deborah Page-Dumroese; Martin F. Jurgensen; Alan E. Harvey
2003-01-01
The potential of forest soils to sequester carbon (C) depends on many biotic and abiotic variables, such as: forest type, stand age and structure, root activity and turnover, temperature and moisture conditions, and soil physical, chemical, and biological properties (Birdsey and Lewis, Chapter 2; Johnson and Kern, Chapter 4; Pregitzer, Chapter 6; Morris and Paul,...
NASA Astrophysics Data System (ADS)
Sahabiev, I. A.; Ryazanov, S. S.; Kolcova, T. G.; Grigoryan, B. R.
2018-03-01
The three most common techniques to interpolate soil properties at a field scale—ordinary kriging (OK), regression kriging with multiple linear regression drift model (RK + MLR), and regression kriging with principal component regression drift model (RK + PCR)—were examined. The results of the performed study were compiled into an algorithm of choosing the most appropriate soil mapping technique. Relief attributes were used as the auxiliary variables. When spatial dependence of a target variable was strong, the OK method showed more accurate interpolation results, and the inclusion of the auxiliary data resulted in an insignificant improvement in prediction accuracy. According to the algorithm, the RK + PCR method effectively eliminates multicollinearity of explanatory variables. However, if the number of predictors is less than ten, the probability of multicollinearity is reduced, and application of the PCR becomes irrational. In that case, the multiple linear regression should be used instead.
NASA Astrophysics Data System (ADS)
Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.
2003-12-01
The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.
Statistical-physical model of the hydraulic conductivity
NASA Astrophysics Data System (ADS)
Usowicz, B.; Marczewski, W.; Usowicz, J. B.; Lukowski, M. I.
2012-04-01
The water content in unsaturated subsurface soil layer is determined by processes of exchanging mass and energy between media of soil and atmosphere, and particular members of layered media. Generally they are non-homogeneous on different scales, considering soil porosity, soil texture including presence of vegetation elements in the root zone, and canopy above the surface, and varying biomass density of plants above the surface in clusters. That heterogeneity determines statistically effective values of particular physical properties. This work considers mainly those properties which determine the hydraulic conductivity of soil. This property is necessary for characterizing physically water transfer in the root zone and access of nutrient matter for plants, but it also the water capacity on the field scale. The temporal variability of forcing conditions and evolutionarily changing vegetation causes substantial effects of impact on the water capacity in large scales, bringing the evolution of water conditions in the entire area, spanning a possible temporal state in the range between floods and droughts. The dynamic of this evolution of water conditions is highly determined by vegetation but is hardly predictable in evaluations. Hydrological models require feeding with input data determining hydraulic properties of the porous soil which are proposed in this paper by means of the statistical-physical model of the water hydraulic conductivity. The statistical-physical model was determined for soils being typical in Euroregion Bug, Eastern Poland. The model is calibrated on the base of direct measurements in the field scales, and enables determining typical characteristics of water retention by the retention curves bounding the hydraulic conductivity to the state of water saturation of the soil. The values of the hydraulic conductivity in two reference states are used for calibrating the model. One is close to full saturation, and another is for low water content far from saturation, in a particular case of the soil type. Effects of calibrating a soil depends on assumed ranges of soil properties engaged to recognizing the soil type. Among those properties, the key role is for the bulk density, the porosity and its dependence on the specific area of the soil. The aim of this work is to provide such variables of auxiliary data to SMOS, which would bring a relation of the soil moisture to the water capacity, under retrieving SM from SMOS L1C data. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.
Shu, Qiaosheng; Liu, Zuoxin; Si, Bingcheng
2008-01-01
Understanding the correlation between soil hydraulic parameters and soil physical properties is a prerequisite for the prediction of soil hydraulic properties from soil physical properties. The objective of this study was to examine the scale- and location-dependent correlation between two water retention parameters (alpha and n) in the van Genuchten (1980) function and soil physical properties (sand content, bulk density [Bd], and organic carbon content) using wavelet techniques. Soil samples were collected from a transect from Fuxin, China. Soil water retention curves were measured, and the van Genuchten parameters were obtained through curve fitting. Wavelet coherency analysis was used to elucidate the location- and scale-dependent relationships between these parameters and soil physical properties. Results showed that the wavelet coherence between alpha and sand content was significantly different from red noise at small scales (8-20 m) and from a distance of 30 to 470 m. Their wavelet phase spectrum was predominantly out of phase, indicating negative correlation between these two variables. The strong negative correlation between alpha and Bd existed mainly at medium scales (30-80 m). However, parameter n had a strong positive correlation only with Bd at scales between 20 and 80 m. Neither of the two retention parameters had significant wavelet coherency with organic carbon content. These results suggested that location-dependent scale analyses are necessary to improve the performance for soil water retention characteristic predictions.
NASA Astrophysics Data System (ADS)
Machado Siqueira, Glécio; Soares da Silva, Jucicleia; Farías França e Silva, Ênio; Lado, Marcos; Paz-González, Antonio; Vidal-Vázquez, Eva
2017-04-01
The lowlands coastal region of the state of Pernambuco, Northeast of Brazil, was formerly covered by humid Atlantic forest (Mata Atlântica) and then has been increasingly devoted to Sugar cane production. Because the water table is near to the soil surface salinity can occur in this area. The objective of this study was to assess the scale dependence of parameters associated to soil salinity and ions responsible for salination using multifractal analysis. The field work was conducted at an experimental field located in the Goiania municipality, Pernambuco, Brazil. This site is located 10 km east from the Atlantic coast. The field has been devoted to monoculture of sugarcane (Saccharum of?cinarum sp.) since 25 years. The climate of the region is tropical, with average annual temperature of 24°C and 1800 mm of precipitation per year. Soil was sampled every 3 m at 128 locations across a 384 m transect at a depth of 0-20 cm. The soil samples were analysed for pH, electrical conductivity (EC), Na+, K+, Ca2+, Mg2+, Cl- and SO4-2; also sodium adsorption ratio (SAR) was calculated. The spatial distributions of all the studied variables associated to soil salinity exhibited multifractal behaviour. Although all the variables studied exhibited a very strong power law scaling, different degrees of multifractality, assessed by differences in the amplitude and several selected parameters of the generalized dimension and singularity spectrum curves, have been appreciated. The multifractal approach gives a good description of the patterns of spatial variability of properties and ions describing soil salinity, and allows discriminating differences between them.
Some aspects of interrelations between fungi and other biota in forest soil.
Krivtsov, Vladimir; Griffiths, Bryan S; Salmond, Ross; Liddell, Keith; Garside, Adam; Bezginova, Tanya; Thompson, Jacqueline A; Staines, Harry J; Watling, Roy; Palfreyman, John W
2004-08-01
Interrelations of fungal mycelium with other soil biota are of paramount importance in forestry and soil ecology. Here we present the results of statistical analysis of a comprehensive data set collected in the first (and the only) British fungus sanctuary over a period of four months. The variables studied included a number of soil properties, bacteria, protozoan flagellates, ciliates and amoebae, microbial and plant feeding nematodes, various microarthropods, and two fungal biomarkers--glomalin and ergosterol. One way ANOVA showed that the dynamics of the microbiota studied was influenced by seasonal changes. Superimposed on these changes, however, was variability due to biological interactions and habitat characteristics. Two fungal biomarkers, ergosterol and glomalin, were differently influenced by other biota and abiotic variables. The results indicate that the dynamics of soil fungi is influenced not only by soil microarthropods, but also by those found in forest litter. The overall outcome, therefore, is likely to be very complex and will depend upon specific conditions of any particular ecosystem.
Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander
2008-01-01
The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759
de Santiago-Martín, Ana; Vaquero-Perea, Cristina; Valverde-Asenjo, Inmaculada; Quintana Nieto, Jose R; González-Huecas, Concepción; Lafuente, Antonio L; Vázquez de la Cueva, Antonio
2016-05-01
Abandonment of vineyards after uprooting has dramatically increased in last decades in Mediterranean countries, often followed by vegetation expansion processes. Inadequate management strategies can have negative consequences on soil quality. We studied how the age and type of vegetation cover and several environmental characteristics (lithology, soil properties, vineyard slope and so on) after vineyard uprooting and abandonment contribute to the variation patterns in total, HAc (acetic acid-method, HAc) and EDTA-extractable (ethylenediaminetetraacetic acid-method) concentrations of Cd, Cu, Pb and Zn in soils. We sampled 141 points from vineyards and abandoned vineyard Mediterranean soils recolonized by natural vegetation in recent decades. The contribution of several environmental variables (e.g. age and type of vegetation cover, lithology, soil properties and vineyard slope) to the total and extractable concentrations of metals was evaluated by canonical ordination based on redundancy analysis, considering the interaction between both environmental and response variables. The ranges of total metal contents were: 0.01-0.15 (Cd), 2.6-34 (Cu), 6.6-30 (Pb), and 29-92mgkg(-1) (Zn). Cadmium (11-100%) had the highest relative extractability with both extractants, and Zn and Pb the lowest. The total and EDTA-extractable of Cd, Pb and Zn were positively related to the age of abandonment, to the presence of Agrostis castellana and Retama sphaerocarpa, and to the contents of Fe-oxides, clay and organic matter (OM). A different pattern was noted for Cu, positively related to vineyard soils. Soil properties successfully explained HAc-extractable Cd, Cu, Pb and Zn but the age and type of vegetation cover lost significance. Clay content was negatively related to HAc-extractable Cu and Pb; and OM was positively related to HAc-Cd and Zn. In conclusion, the time elapsed after vineyard uprooting, and subsequent land abandonment, affects the soil content and availability of metals, and this impact depended on the colonizing plant species and soil properties. Copyright © 2016 Elsevier B.V. All rights reserved.
Zornoza, R; Guerrero, C; Mataix-Solera, J; Scow, K M; Arcenegui, V; Mataix-Beneyto, J
2008-07-01
The potential of near infrared (NIR) reflectance spectroscopy to predict various physical, chemical and biochemical properties in Mediterranean soils from SE Spain was evaluated. Soil samples (n=393) were obtained by sampling thirteen locations during three years (2003-2005 period). These samples had a wide range of soil characteristics due to variations in land use, vegetation cover and specific climatic conditions. Biochemical properties also included microbial biomarkers based on phospholipid fatty acids (PLFA). Partial least squares (PLS) regression with cross validation was used to establish relationships between the NIR spectra and the reference data from physical, chemical and biochemical analyses. Based on the values of coefficient of determination (r(2)) and the ratio of standard deviation of validation set to root mean square error of cross validation (RPD), predicted results were evaluated as excellent (r(2)>0.90 and RPD>3) for soil organic carbon, Kjeldahl nitrogen, soil moisture, cation exchange capacity, microbial biomass carbon, basal soil respiration, acid phosphatase activity, β-glucosidase activity and PLFA biomarkers for total bacteria, Gram positive bacteria, actinomycetes, vesicular-arbuscular mycorrhizal fungi and total PLFA biomass. Good predictions (0.81
Huang, Haobo; Ouyang, Wei; Wu, Haotian; Liu, Hongbin; Andrea, Critto
2017-02-01
Analyses of the spatial-temporal distribution of diffuse pollution in agricultural regions are essential to the sustained management of water resources. Although nutrients, such as phosphorus fertilizers, can promote crop growth while improving soil fertility, excessive nutrient inputs can produce diffuse pollution, which may results in water quality degradation. The objective of this paper is to employ the SWAT (Soil and Water Assessment Tool) to estimate diffuse P effects on temporal and spatial distributions for a typical agricultural watershed and to identify the conjunct and independent influences of long-term land use and soil properties variation on diffuse P. With the validated model, the four-period simulation results (from 1979 to 2009) indicate that land use changes from agricultural development increased diffuse P yields. However, regarding updated soil properties, no significant differences of P yield were found between 1979 and 2009, demonstrating that impact of the cropland expansion were naturalized with soil property variations. An F-test was employed to assess the essentiality of all of the variables examined during the simulation period, and the test results indicated that diffuse P loading was more sensitive to soil properties than to land use. Before the P pollution control project about the land use optimization planning, it is more effective to distinguish the impacts of land use and soil properties. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Roberts, B. J.; Chelsky, A.; Bernhard, A. E.; Giblin, A. E.
2017-12-01
Salt marshes are important sites for retention and transformation of carbon and nutrients. Much of our current marsh biogeochemistry knowledge is based on sampling at times and in locations that are convenient, most often vegetated marsh platforms during low tide. Wetland loss rates are high in many coastal regions including Louisiana which has the highest loss rates in the US. This loss not only reduces total marsh area but also changes the relative allocation of subhabitats in the remaining marsh. Climate and other anthropogenic changes lead to further changes including inundation patterns, redox conditions, salinity regimes, and shifts in vegetation patterns across marsh landscapes. We present results from a series of studies examining biogeochemical rates, microbial communities, and soil properties along multiple edge to interior transects within Spartina alterniflora across the Louisiana coast; between expanding patches of Avicennia germinans and adjacent S. alterniflora marshes; in soils associated with the four most common Louisiana salt marsh plants species; and across six different marsh subhabitats. Spartina alterniflora marsh biogeochemistry and microbial populations display high spatial variability related to variability in soil properties which appear to be, at least in part, regulated by differences in elevation, hydrology, and redox conditions. Differences in rates between soils associated with different vegetation types were also related to soil properties with S. alterniflora soils often yielding the lowest rates. Biogeochemical process rates vary significantly across marsh subhabitats with individual process rates differing in their hotspot habitat(s) across the marsh. Distinct spatial patterns may influence the roles that marshes play in retaining and transforming nutrients in coastal regions and highlight the importance of incorporating spatial sampling when scaling up plot level measurements to landscape or regional scales.
Gu, Sen; Gruau, Gérard; Dupas, Rémi; Rumpel, Cornélia; Crème, Alexandra; Fovet, Ophélie; Gascuel-Odoux, Chantal; Jeanneau, Laurent; Humbert, Guillaume; Petitjean, Patrice
2017-11-15
In agricultural landscapes, establishment of vegetated buffer zones in riparian wetlands (RWs) is promoted to decrease phosphorus (P) emissions because RWs can trap particulate P from upslope fields. However, long-term accumulation of P risks the release of dissolved P, since the unstable hydrological conditions in these zones may mobilize accumulated particulate P by transforming it into a mobile dissolved P species. This study evaluates how hydroclimate variability, topography and soil properties interact and influence this mobilization, using a three-year dataset of molybdate-reactive dissolved P (MRDP) and total dissolved P (TDP) concentrations in soil water from two RWs located in an agricultural catchment in western France (Kervidy-Naizin), along with stream P concentrations. Two main drivers of seasonal dissolved P release were identified: i) soil rewetting during water-table rise after dry periods and ii) reductive dissolution of soil Fe (hydr)oxides during prolonged water saturation periods. These mechanisms were shown to vary greatly in space (according to topography) and time (according to intra- and interannual hydroclimate variability). The concentration and speciation of the released dissolved P also varied spatially depending on soil chemistry and local topography. Comparison of sites revealed a similar correlation between soil P speciation (percentage of organic P ranging from 35-70%) and the concentration and speciation of the released P (MRDP from <0.10 to 0.40mgl -1 ; percentage of MRDP in TDP from 25-70%). These differences propagated to stream water, suggesting that the two RWs investigated were the main sources of dissolved P to streams. RWs can be critical areas due to their ability to biogeochemically transform the accumulated P in these zones into highly mobile and highly bioavailable dissolved P forms. Hydroclimate variability, local topography and soil chemistry must be considered to decrease the risk of remobilizing legacy soil P when establishing riparian buffer zones in agricultural landscapes. Copyright © 2017 Elsevier B.V. All rights reserved.
STOCHASTIC SIMULATION OF FIELD-SCALE PESTICIDE TRANSPORT USING OPUS AND GLEAMS
Incorporating variability in soil and chemical properties into root zone leaching models should provide a better representation of pollutant distribution in natural field conditions. Our objective was to determine if a more mechanistic rate-based model (Opus) would predict soil w...
NASA Astrophysics Data System (ADS)
Bogunović, Igor; Trevisani, Sebastiano; Pereira, Paulo; Šeput, Miranda
2017-04-01
Climate change is expected to have an important influence on the crop production in agricultural regions. Soil carbon represents an important soil property that contributes to mitigate the negative influence of climate change on intensive cropped areas. Based on 5063 soil samples sampled from soil top layer (0-30 cm) we studied the spatial distribution of total carbon (TC) and soil organic carbon (SOC) content in various soil types (Anthrosols, Cambisols, Chernozems, Fluvisols, Gleysols, Luvisols) in Baranja region, Croatia. TC concentrations ranged from 2.10 to 66.15 mg/kg (with a mean of 16.31 mg/kg). SOC concentrations ranged from 1.86 to 58.00 mg/kg (with a mean of 13.35 mg/kg). TC and SOC showed moderate heterogeneity with coefficient of variation (CV) of 51.3% and 33.8%, respectively. Average concentrations of soil TC vary in function of soil types in the following decreasing order: Anthrosols (20.9 mg/kg) > Gleysols (19.3 mg/kg) > Fluvisols (15.6 mg/kg) > Chernozems (14.2 mg/kg) > Luvisols (12.6 mg/kg) > Cambisols (11.1 mg/kg), while SOC concentrations follow next order: Gleysols (15.4 mg/kg) > Fluvisols (13.2 mg/kg) = Anthrosols (13.2 mg/kg) > Chernozems (12.6 mg/kg) > Luvisols (11.4 mg/kg) > Cambisols (10.5 mg/kg). Performed geostatistical analysis of TC and SOC; both the experimental variograms as well as the interpolated maps reveal quite different spatial patterns of the two studied soil properties. The analysis of the spatial variability and of the spatial patterns of the produced maps show that SOC is likely influenced by antrophic processes. Spatial variability of SOC indicates soil health deterioration on an important significant portion of the studied area; this suggests the need for future adoption of environmentally friendly soil management in the Baranja region. Regional maps of TC and SOC provide quantitative information for regional planning and environmental monitoring and protection purposes.
Šimůnek, Jirka; Nimmo, John R.
2005-01-01
A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time‐variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field.
A Comparison of Selected Statistical Techniques to Model Soil Cation Exchange Capacity
NASA Astrophysics Data System (ADS)
Khaledian, Yones; Brevik, Eric C.; Pereira, Paulo; Cerdà, Artemi; Fattah, Mohammed A.; Tazikeh, Hossein
2017-04-01
Cation exchange capacity (CEC) measures the soil's ability to hold positively charged ions and is an important indicator of soil quality (Khaledian et al., 2016). However, other soil properties are more commonly determined and reported, such as texture, pH, organic matter and biology. We attempted to predict CEC using different advanced statistical methods including monotone analysis of variance (MONANOVA), artificial neural networks (ANNs), principal components regressions (PCR), and particle swarm optimization (PSO) in order to compare the utility of these approaches and identify the best predictor. We analyzed 170 soil samples from four different nations (USA, Spain, Iran and Iraq) under three land uses (agriculture, pasture, and forest). Seventy percent of the samples (120 samples) were selected as the calibration set and the remaining 50 samples (30%) were used as the prediction set. The results indicated that the MONANOVA (R2= 0.82 and Root Mean Squared Error (RMSE) =6.32) and ANNs (R2= 0.82 and RMSE=5.53) were the best models to estimate CEC, PSO (R2= 0.80 and RMSE=5.54) and PCR (R2= 0.70 and RMSE=6.48) also worked well and the overall results were very similar to each other. Clay (positively correlated) and sand (negatively correlated) were the most influential variables for predicting CEC for the entire data set, while the most influential variables for the various countries and land uses were different and CEC was affected by different variables in different situations. Although the MANOVA and ANNs provided good predictions of the entire dataset, PSO gives a formula to estimate soil CEC using commonly tested soil properties. Therefore, PSO shows promise as a technique to estimate soil CEC. Establishing effective pedotransfer functions to predict CEC would be productive where there are limitations of time and money, and other commonly analyzed soil properties are available. References Khaledian, Y., Kiani, F., Ebrahimi, S., Brevik, E.C., Aitkenhead-Peterson, J. 2016. Assessment and monitoring of soil degradation during land use change using multivariate analysis. Land Degradation and Development. doi: 10.1002/ldr.2541.
Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils
NASA Technical Reports Server (NTRS)
Eagleson, Peter S.; Jasinski, Michael F.
1988-01-01
The estimation of the spatially variable surface moisture and heat fluxes of natural, semivegetated landscapes is difficult due to the highly random nature of the vegetation (e.g., plant species, density, and stress) and the soil (e.g., moisture content, and soil hydraulic conductivity). The solution to that problem lies, in part, in the use of satellite remotely sensed data, and in the preparation of those data in terms of the physical properties of the plant and soil. The work was focused on the development and testing of a stochastic geometric canopy-soil reflectance model, which can be applied to the physically-based interpretation of LANDSAT images. The model conceptualizes the landscape as a stochastic surface with bulk plant and soil reflective properties. The model is particularly suited for regional scale investigations where the quantification of the bulk landscape properties, such as fractional vegetation cover, is important on a pixel by pixel basis. A summary of the theoretical analysis and the preliminary testing of the model with actual aerial radiometric data is provided.
NASA Astrophysics Data System (ADS)
Usowicz, Boguslaw; Marczewski, Wojciech; Usowicz, Jerzy B.; Łukowski, Mateusz; Lipiec, Jerzy; Stankiewicz, Krystyna
2013-04-01
Radiometric observations with SMOS rely on the Radiation Transfer Equations (RTE) determining the Brightness Temperature (BT) in two linear polarization components (H, V) satisfying Fresnel principle of propagation in horizontally layered target media on the ground. RTE involve variables which bound the equations expressed in Electro-Magnetic (EM) terms of the intensity BT to the physical reality expressed by non-EM variables (Soil Moisture (SM), vegetation indexes, fractional coverage with many different properties, and the boundary conditions like optical thickness, layer definitions, roughness, etc.) bridging the EM domain to other physical aspects by means of the so called tau-omega methods. This method enables joining variety of different valuable models, including specific empirical estimation of physical properties in relation to the volumetric water content. The equations of RTE are in fact expressed by propagation, reflection and losses or attenuation existing on a considered propagation path. The electromagnetic propagation is expressed in the propagation constant. For target media on the ground the dielectric constant is a decisive part for effects of propagation. Therefore, despite of many various physical parameters involved, one must effectively and dominantly rely on the dielectric constant meant as a complex variable. The real part of the dielectric constant represents effect of apparent shortening the propagation path and the refraction, while the imaginary part is responsible for the attenuation or losses. This work engages statistical-physical modeling of soil properties considering the media as a mixture of solid grains, and gas or liquid filling of pores and contact bridges between compounds treated statistically. The method of this modeling provides an opportunity of characterizing the porosity by general statistical means, and is applicable to various physical properties (thermal, electrical conductivity and dielectric properties) which depend on composition of compounds. The method was developed beyond the SMOS method, but they meet just in RTE, at the dielectric constant. The dielectric constant is observed or measured (retrieved) by SMOS, regardless other properties like the soil porosity and without a direct relation to thermal properties of soils. Relations between thermal properties of soil to the water content are very consistent. Therefore, we took a concept of introducing effects of the soil porosity, and thermal properties of soils into the representation of the dielectric constant in complex measures, and thus gaining new abilities for capturing effects of the porosity by the method of SMOS observations. Currently we are able presenting few effects of relations between thermal properties and the soil moisture content, on examples from wetlands Biebrza and Polesie in Poland, and only search for correlations between SM from SMOS to the moisture content known from the ground. The correlations are poor for SMOS L2 data processed with the version of retrievals using the model of Dobson (501), but we expect more correlation for the version using the model of Mironov (551). If the supposition is confirmed, then we may gain encouragement to employing the statistical-physical modeling of the dielectric constant and thermal properties for the purposes of using this model in RTE and tau-omega method. Treating the soil porosity for a target of research directly is not enough strongly motivated like the use of effects on SM observable in SMOS.
Effect of climate on the storage and turnover of carbon in soils
NASA Technical Reports Server (NTRS)
Trumbore, Susan; Chadwick, Oliver; Amundson, Ronald; Brasher, Benny
1994-01-01
Climate is, in many instances, the dominant variable controlling the storage of carbon in soils. It has proven difficult, however, to determine how soil properties influenced by climate, such as soil temperature and soil moisture, actually operate to determine the rates of accumulation and decomposition of soil organic matter. Our approach has been to apply a relatively new tool, the comparison of C-14 in soil organic matter from pre- and post-bomb soils, to quantify carbon turnover rates along climosequences. This report details the progress made toward this end by work under this contract.
Response to elevated CO2 in the temperate C3 grass Festuca arundinaceae across a wide range of soils
Nord, Eric A.; Jaramillo, Raúl E.; Lynch, Jonathan P.
2015-01-01
Soils vary widely in mineral nutrient availability and physical characteristics, but the influence of this variability on plant responses to elevated CO2 remains poorly understood. As a first approximation of the effect of global soil variability on plant growth response to CO2, we evaluated the effect of CO2 on tall fescue (Festuca arundinacea) grown in soils representing 10 of the 12 global soil orders plus a high-fertility control. Plants were grown in small pots in continuously stirred reactor tanks in a greenhouse. Elevated CO2 (800 ppm) increased plant biomass in the high-fertility control and in two of the more fertile soils. Elevated CO2 had variable effects on foliar mineral concentration—nitrogen was not altered by elevated CO2, and phosphorus and potassium were only affected by CO2 in a small number of soils. While leaf photosynthesis was stimulated by elevated CO2 in six soils, canopy photosynthesis was not stimulated. Four principle components were identified; the first was associated with foliar minerals and soil clay, and the second with soil acidity and foliar manganese concentration. The third principle component was associated with gas exchange, and the fourth with plant biomass and soil minerals. Soils in which tall fescue did not respond to elevated CO2 account for 83% of global land area. These results show that variation in soil physical and chemical properties have important implications for plant responses to global change, and highlight the need to consider soil variability in models of vegetation response to global change. PMID:25774160
Unsaturated flow processes in structurally-variable pathways in wildfire-affected soils and ash
NASA Astrophysics Data System (ADS)
Ebel, B. A.
2016-12-01
Prediction of flash flood and debris flow generation in wildfire-affected soils and ash hinges on understanding unsaturated flow processes. Water resources issues, such as groundwater recharge, also rely on our ability to quantify subsurface flow. Soil-hydraulic property data provide insight into unsaturated flow processes and timescales. A literature review and synthesis of existing data from the literature for wildfire-affected soils, including ash and unburned soils, facilitated calculating metrics and timescales of hydrologic response related to infiltration and surface runoff generation. Sorptivity (S) and the Green-Ampt wetting front parameter (Ψf) were significantly lower in burned soils compared to unburned soils, while field-saturated hydraulic conductivity (Kfs) was not significantly different. The magnitude and duration of the influence of capillarity was substantially reduced in burned soils, leading to faster ponding times in response to rainfall. Ash had large values of S and Kfs compared to unburned and burned soils but intermediate values of Ψf, suggesting that ash has long ponding times in response to rainfall. The ratio of S2/Kfs was nearly constant ( 100 mm) for unburned soils, but was more variable in burned soils. Post-wildfire changes in this ratio suggested that unburned soils had a balance between gravity and capillarity contributions to infiltration, which may depend on soil organic matter, while burning shifted infiltration more towards gravity contributions by reducing S. Taken together, the changes in post-wildfire soil-hydraulic properties increased the propensity for surface runoff generation and may have enhanced subsurface preferential flow through pathways altered by wildfire.
Cunha, Cleyton Saialy Medeiros; da Silva, Ygor Jacques Agra Bezerra; Escobar, Maria Eugenia Ortiz; do Nascimento, Clístenes Williams Araújo
2018-02-22
The Itataia uranium-phosphate deposit is the largest uranium reserve in Brazil. Rare earth elements (REEs) are commonly associated with phosphate deposits; however, there are no studies on the concentrations of REEs in soils of the Itataia deposit region. Thus, the objective of the research was to evaluate the concentration and spatial variability of REEs in topsoils of Itataia phosphate deposit region. In addition, the influence of soil properties on the geochemistry of REEs was investigated. Results showed that relatively high mean concentrations (mg kg -1 ) of heavy REEs (Gd 6.01; Tb 1.25; Ho 1.15; Er 4.05; Tm 0.64; Yb 4.61; Lu 0.65) were found in surface soils samples. Soil properties showed weak influence on the geochemical behavior of REEs in soils, except for the clay content. On the other hand, parent material characteristics, such as P and U, had strong influence on REEs concentrations. Spatial distribution patterns of REEs in soils are clearly associated with P and U contents. Therefore, geochemical surveys aiming at the delineation of ore-bearing zones in the region can benefit from our data. The results of this work reinforce the perspective for co-mining of P, U and REEs in this important P-U reserve.
Effect of suction-dependent soil deformability on landslide susceptibility maps
NASA Astrophysics Data System (ADS)
Lizarraga, Jose J.; Buscarnera, Giuseppe; Frattini, Paolo; Crosta, Giovanni B.
2016-04-01
This contribution presents a physically-based, spatially-distributed model for shallow landslides promoted by rainfall infiltration. The model features a set of Factor of Safety values aimed to capture different failure mechanisms, namely frictional slips with limited mobility and flowslide events associated with the liquefaction of the considered soils. Indices of failure associated with these two modes of instability have been derived from unsaturated soil stability principles. In particular, the propensity to wetting-induced collapse of unsaturated soils is quantified through the introduction of a rigid-plastic model with suction-dependent yielding and strength properties. The model is combined with an analytical approach (TRIGRS) to track the spatio-temporal evolution of soil suction in slopes subjected to transient infiltration. The model has been tested to reply the triggering of shallow landslides in pyroclastic deposits in Sarno (1998, Campania Region, Southern Italy). It is shown that suction-dependent mechanical properties, such as soil deformability, have important effects on the predicted landslide susceptibility scenarios, resulting on computed unstable zones that may encompass a wide range of slope inclinations, saturation levels, and depths. Such preliminary results suggest that the proposed methodology offers an alternative mechanistic interpretation to the variability in behavior of rainfall-induced landslides. Differently to standard methods the explanation to this variability is based on suction-dependent soil behavior characteristics.
Woodward, Andrea
1998-01-01
Relationships among environmental variables and occurrence of tree species were investigated at Hurricane Ridge in Olympic National Park, Washington, USA. A transect consisting of three plots was established down one north-and one south-facing slope in stands representing the typical elevational sequence of tree species. Tree species included subalpine fir (Abies lasiocarpa), Douglas-fir (Pseudotsuga menziesii), mountain hemlock (Tsuga mertensiana), and Pacific silver fir (Abies amabilis). Air and soil temperature, precipitation, and soil moisture were measured during three growing seasons. Snowmelt patterns, soil carbon and moisture release curves were also determined. The plots represented a wide range in soil water potential, a major determinant of tree species distribution (range of minimum values = -1.1 to -8.0 MPa for Pacific silver fir and Douglas-fir plots, respectively). Precipitation intercepted at plots depended on topographic location, storm direction and storm type. Differences in soil moisture among plots was related to soil properties, while annual differences at each plot were most often related to early season precipitation. Changes in climate due to a doubling of atmospheric CO2 will likely shift tree species distributions within, but not among aspects. Change will be buffered by innate tolerance of adult trees and the inertia of soil properties.
Human land-use and soil change
Wills, Skye A.; Williams, Candiss O.; Duniway, Michael C.; Veenstra, Jessica; Seybold, Cathy; Pressley, DeAnn
2017-01-01
Soil change refers to the alteration of soil and soil properties over time in one location, as opposed to soil variability across space. Although soils change with pedogensis, this chapter focuses on human caused soil change. Soil change can occur with human use and management over long or short time periods and small or large scales. While change can be negative or positive; often soil change is observed when short-term or narrow goals overshadow the other soil’s ecosystem services. Many soils have been changed in their chemical, physical or biological properties through agricultural activities, including cultivation, tillage, weeding, terracing, subsoiling, deep plowing, manure and fertilizer addition, liming, draining, and irrigation. Assessing soil change depends upon the ecosystem services and soil functions being evaluated. The interaction of soil properties with the type and intensity of management and disturbance determines the changes that will be observed. Tillage of cropland disrupts aggregates and decreases soil organic carbon content which can lead to decreased infiltration, increased erosion, and reduced biological function. Improved agricultural management systems can increase soil functions including crop productivity and sustainability. Forest management is most intensive during harvesting and seedling establishment. Most active management in forests causes disturbance of the soil surface which may include loss of forest floor organic materials, increases in bulk density, and increased risk of erosion. In grazing lands, pasture management often includes periods of biological, chemical and physical disturbance in addition to the grazing management imposed on rangelands. Grazing animals have both direct and indirect impacts on soil change. Hoof action can lead to the disturbance of biological crusts and other surface features impairing the soil’s physical, biological and hydrological function. There are clear feedbacks between vegetative systems and soil properties; when vegetation is altered because of grazing or other disturbances, soil property changes often follow. Some soils are very sensitive to management and disturbance and can undergo rapid change: cropping led to massive gully formation in the southeastern USA, exposure of acid-sulfate soils led to irreversible changes in soil minerology and thawing of cold soils has created thermokarst features. These soil changes alter soil properties and functions and may impact soil ecosystem services far into the future.
Durán, Jorge; Delgado-Baquerizo, Manuel; Dougill, Andrew J; Guuroh, Reginald T; Linstädter, Anja; Thomas, Andrew D; Maestre, Fernando T
2018-05-01
The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation modelling was clearly higher for the spatial variability of N- than for C- and P-related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change. © 2018 by the Ecological Society of America.
Spatial relationships among cereal yields and selected soil physical and chemical properties.
Lipiec, Jerzy; Usowicz, Bogusław
2018-08-15
Sandy soils occupy large area in Poland (about 50%) and in the world. This study aimed at determining spatial relationships of cereal yields and the selected soil physical and chemical properties in three study years (2001-2003) on low productive sandy Podzol soil (Podlasie, Poland). The yields and soil properties in plough and subsoil layers were determined at 72-150 points. The test crops were: wheat, wheat and barley mixture and oats. To explore the spatial relationship between cereal yields and each soil property spatial statistics was used. The best fitting models were adjusted to empirical semivariance and cross-semivariance, which were used to draw maps using kriging. Majority of the soil properties and crop yields exhibited low and medium variability (coefficient of variation 5-70%). The effective ranges of the spatial dependence (the distance at which data are autocorrelated) for yields and all soil properties were 24.3-58.5m and 10.5-373m, respectively. Nugget to sill ratios showed that crop yields and soil properties were strongly spatially dependent except bulk density. Majority of the pairs in cross-semivariograms exhibited strong spatial interdependence. The ranges of the spatial dependence varied in plough layer between 54.6m for yield×pH up to 2433m for yield×silt content. Corresponding ranges in subsoil were 24.8m for crop yield×clay content in 2003 and 1404m for yield×bulk density. Kriging maps allowed separating sub-field area with the lowest yield and soil cation exchange capacity, organic carbon content and pH. This area had lighter color on the aerial photograph due to high content of the sand and low content of soil organic carbon. The results will help farmers at identifying sub-field areas for applying localized management practices to improve these soil properties and further spatial studies in larger scale. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics
NASA Technical Reports Server (NTRS)
Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)
2002-01-01
Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.
NASA Astrophysics Data System (ADS)
McGuire, K. J.; Bailey, S. W.; Ross, D. S.
2017-12-01
Heterogeneity in biophysical properties within catchments challenges how we quantify and characterize biogeochemical processes and interpret catchment outputs. Interactions between the spatiotemporal variability of hydrological states and fluxes and soil development can spatially structure catchments, leading to a framework for understanding patterns in biogeochemical processes. In an upland, glaciated landscape at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, we are embracing the structure and organization of soils to understand the spatial relations between runoff production zones, distinct soil-biogeochemical environments, and solute retention and release. This presentation will use observations from the HBEF to demonstrate that a soil-landscape framework is essential in understanding the spatial and temporal variability of biogeochemical processes in this catchment. Specific examples will include how laterally developed soils reveal the location of active runoff production zones and lead to gradients in primary mineral dissolution and the distribution of weathering products along hillslopes. Soil development patterns also highlight potential carbon and nitrogen cycling hotspots, differentiate acidic conditions, and affect the regulation of surface water quality. Overall, this work demonstrates the importance of understanding the landscape-level structural organization of soils in characterizing the variation and extent of biogeochemical processes that occur in catchments.
NASA Astrophysics Data System (ADS)
Aparicio, Virginia; Costa, José; Domenech, Marisa; Castro Franco, Mauricio
2013-04-01
Predicting how solutes move through the unsaturated zone is essential to determine the potential risk of groundwater contamination (Costa et al., 1994). The estimation of the spatial variability of solute transport parameters, such as velocity and dispersion, enables a more accurate understanding of transport processes. Apparent electrical conductivity (ECa) has been used to characterize the spatial behavior of soil properties. The objective of this study was to characterize the spatial variability of soil transport parameters at field scale using ECa measurements. ECa measurements of 42 ha (Tres Arroyos) and 50 ha (Balcarce) farms were collected for the top 0-30 cm (ECa(s)) soil using the Veris® 3100. ECa maps were generated using geostatistical interpolation techniques. From these maps, three general areas were delineated, named high, medium, and low ECa zones. At each zone, three sub samples were collected. Soil samples were taken at 0-30 cm. Clay content and organic matter (OM) was analyzed. The transport assay was performed in the laboratory using undisturbed soil columns, under controlled conditions of T ° (22 ° C).Br- determinations were performed with a specific Br- electrode. The breakthrough curves were fitted using the model CXTFIT 2.1 (Toride et al., 1999) to estimate the transport parameters Velocity (V) and Dispersion (D). In this study we found no statistical significant differences for V and D between treatments. Also, there were no differences in V and D between sites. The average V and D value was 9.3 cm h-1 and 357.5 cm2 h-2, respectively. Despite finding statistically significant differences between treatments for the other measured physical and chemical properties, in our work it was not possible to detect the spatial variability of solute transport parameters.
NASA Astrophysics Data System (ADS)
Badagliacca, Giuseppe; Petrovičová, Beatrix; Zumbo, Antonino; Romeo, Maurizio; Gullì, Tommaso; Martire, Luigi; Monti, Michele; Gelsomino, Antonio
2017-04-01
Soil incorporation of digestate represents a common practice to dispose the solid residues from biogas producing plants. Although the digestate constitutes a residual biomass rich in partially decomposed organic matter and nutrients, whose content is often highly variable and unbalanced, its potential fertilizer value can vary considerably depending on the recipient soil properties. The aim of the work was to assess short-term changes in the fertility status of two contrasting agricultural soils in Southern Italy (Calabria), olive grove on a clay acid soil (Typic Hapludalfs) and citrus grove on a sandy loam slightly calcareous soil (Typic Xerofluvents), respectively located along the Tyrrhenian or the Ionian coast. An amount of 30 t ha-1 digestate was incorporated into the soil by ploughing. Unamended tilled soil was used as control. The following soil physical, chemical and biochemical variables were monitored during the experimental period: aggregate stability, pH, electrical conductivity, organic C, total N, Olsen-P, N-NH4+, N-NO3-, microbial biomass carbon (MBC), microbial biomass nitrogen (MBN) and the mineralization quotient (qM). Moreover, in the olive grove soil CO2 emissions have been continuously measured at field scale for 5 months after digestate incorporation. Digestate application in both site exerted a significant positive effect on soil aggregate stability with a greater increase in clay than in sandy loam soil. Over the experimental period, digestate considerably affected the nutrient availability, namely Olsen-P, N-NH4+, N-NO3-, along with the electrical conductivity. The soil type increased significantly the soil N-NH4+ content, which was always higher in the olive than in citrus grove soil. N-NO3- content was markedly increased soon after the organic amendment, followed by a seasonal decline more evident in the sandy loam soil. Moreover, soil properties as CaCO3 content and the pH selectively affected the Olsen-P dynamics. No appreciable variation was recorded in total C and N pools. Interestingly, amendment with digestate altered the soil microbial community size in both soils as MBC and MBN were increased, although the response was more evident in the clay soil (olive) than in the sandy loam (citrus) one. The considerably higher qM observed in the clay soil suggests that the C mineralization was selectively stimulated in this soil. This finding was confirmed by the increase of CO2 emissions. As a whole our results show that digestate application selectively stimulated soil C dynamics and determined an unbalanced nutrient release, strongly depending on the soil physical-chemical properties. The use of digestate can therefore represent an interesting strategy for managing the soil fertility in Mediterranean agroecosystem soils, provided that digestate and recipient soil properties are carefully taken into account.
Soils of Agricultural Terraces with Retaining Walls in the Mountains of Dagestan
NASA Astrophysics Data System (ADS)
Borisov, A. V.; Korobov, D. S.; Idrisov, I. A.; Kalinin, P. I.
2018-01-01
Soil-archeological studies of agricultural terraces with retaining walls in the area of construction of the Gotsatlinskaya Hydroelectric Power Station in Khunzakh district of the Republic of Dagestan have been performed. The morphogenetic and chemical properties of the anthropogenic soils (Anthrosols) in different parts of the terrace complex are analyzed. It is argued that slope terracing in the mountains ensures the development of thicker soil profiles with pronounced genetic horizons. The soils of agricultural terraces store important information of the paleoenvironmental history and land use. A characteristic feature of the Anthrosols of agricultural terraces is a relatively even distribution of gravelly material of up to 5 cm in diameter in the plow layer. The soils of terraces are characterized by the high variability in their properties within the entire terrace complex and within the particular terraces.
He, Jinhong; Tedersoo, Leho; Hu, Ang; Han, Conghai; He, Dan; Wei, Hui; Jiao, Min; Anslan, Sten; Nie, Yanxia; Jia, Yongxia; Zhang, Gengxin; Yu, Guirui; Liu, Shirong; Shen, Weijun
2017-07-01
Whether and how seasonality of environmental variables impacts the spatial variability of soil fungal communities remain poorly understood. We assessed soil fungal diversity and community composition of five Chinese zonal forests along a latitudinal gradient spanning 23°N to 42°N in three seasons to address these questions. We found that soil fungal diversity increased linearly or parabolically with latitude. The seasonal variations in fungal diversity were more distinguishable in three temperate deciduous forests than in two subtropical evergreen forests. Soil fungal diversity was mainly correlated with edaphic factors such as pH and nutrient contents. Both latitude and its interactions with season also imposed significant impacts on soil fungal community composition (FCC), but the effects of latitude were stronger than those of season. Vegetational properties such as plant diversity and forest age were the dominant factors affecting FCC in the subtropical evergreen forests while edaphic properties were the dominant ones in the temperate deciduous forests. Our results indicate that latitudinal variation patterns of soil fungal diversity and FCC may differ among seasons. The stronger effect of latitude relative to that of season suggests a more important influence by the spatial than temporal heterogeneity in shaping soil fungal communities across zonal forests. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Rebollo, Francisco J.; Jesús Moral García, Francisco
2016-04-01
Soil apparent electrical conductivity (ECa) is one of the simplest, least expensive soil measurements that integrates many soil properties affecting crop productivity, including, for instance, soil texture, water content, and cation exchange capacity. The ECa measurements obtained with a 3100 Veris sensor, operating in both shallow (0-30 cm), ECs, and deep (0-90 cm), ECd, mode, can be used as an additional and essential information to be included in a probabilistic model, the Rasch model, with the aim of quantifying the overall soil fertililty potential in an agricultural field. This quantification should integrate the main soil physical and chemical properties, with different units. In this work, the formulation of the Rasch model integrates 11 soil properties (clay, silt and sand content, organic matter -OM-, pH, total nitrogen -TN-, available phosphorus -AP- and potassium -AK-, cation exchange capacity -CEC-, ECd, and ECs) measured at 70 locations in a field. The main outputs of the model include a ranking of all soil samples according to their relative fertility potential and the unexpected behaviours of some soil samples and properties. In the case study, the considered soil variables fit the model reasonably, having an important influence on soil fertility, except pH, probably due to its homogeneity in the field. Moreover, ECd, ECs are the most influential properties on soil fertility and, on the other hand, AP and AK the less influential properties. The use of the Rasch model to estimate soil fertility potential (always in a relative way, taking into account the characteristics of the studied soil) constitutes a new application of great practical importance, enabling to rationally determine locations in a field where high soil fertility potential exists and establishing those soil samples or properties which have any anomaly; this information can be necessary to conduct site-specific treatments, leading to a more cost-effective and sustainable field management. Furthermore, from the measures of soil fertility potential at sampled locations, estimates can be computed using, for instance, a geostatistical algorithm, and these estimates can be utilized to map soil fertility potential and delineate with a rational basis the management zones in the field. Keywords: Rasch model; soil management; soil electrical conductivity; probabilistic algorithm.
Williams, Alwyn; Jordan, Nicholas R; Smith, Richard G; Hunter, Mitchell C; Kammerer, Melanie; Kane, Daniel A; Koide, Roger T; Davis, Adam S
2018-05-31
Climate models predict increasing weather variability, with negative consequences for crop production. Conservation agriculture (CA) may enhance climate resilience by generating certain soil improvements. However, the rate at which these improvements accrue is unclear, and some evidence suggests CA can lower yields relative to conventional systems unless all three CA elements are implemented: reduced tillage, sustained soil cover, and crop rotational diversity. These cost-benefit issues are important considerations for potential adopters of CA. Given that CA can be implemented across a wide variety of regions and cropping systems, more detailed and mechanistic understanding is required on whether and how regionally-adapted CA can improve soil properties while minimizing potential negative crop yield impacts. Across four US states, we assessed short-term impacts of regionally-adapted CA systems on soil properties and explored linkages with maize and soybean yield stability. Structural equation modeling revealed increases in soil organic matter generated by cover cropping increased soil cation exchange capacity, which improved soybean yield stability. Cover cropping also enhanced maize minimum yield potential. Our results demonstrate individual CA elements can deliver rapid improvements in soil properties associated with crop yield stability, suggesting that regionally-adapted CA may play an important role in developing high-yielding, climate-resilient agricultural systems.
What is the effect of local controls on the temporal stability of soil water contents?
NASA Astrophysics Data System (ADS)
Martinez, G.; Pachepsky, Y. A.; Vereecken, H.; Vanderlinden, K.; Hardelauf, H.; Herbst, M.
2012-04-01
Temporal stability of soil water content (TS SWC) reflects the spatio-temporal organization of SWC. Factors and their interactions that control this organization, are not completely understood and have not been quantified yet. It is understood that these factors should be classified into groups of local and non-local controls. This work is a first attempt to evaluate the effects of soil properties at a certain location as local controls Time series of SWC were generated by running water flow simulations with the HYDRUS6 code. Bare and grassed sandy loam, loam and clay soils were represented by sets of 100 independent soil columns. Within each set, values of saturated hydraulic conductivity (Ks) were generated randomly assuming for the standard deviation of the scaling factor of ln Ks a value ranging from 0.1 to 1.0. Weather conditions were the same for all of the soil columns. SWC at depths of 0.05 and 0.60 m, and the average water content of the top 1 m were analyzed. The temporal stability was characterized by calculating the mean relative differences (MRD) of soil water content. MRD distributions from simulations, developed from the log-normal distribution of Ks, agreed well with the experimental studies found in the literature. Generally, Ks was the leading variable to define the MRD rank for a specific location. Higher MRD corresponded to the lowest values of Ks when a single textural class was considered. Higher MRD were found in the finer texture when mixtures of textural classes were considered and similar values of Ks were compared. The relationships between the spread of the MRD distributions and the scaling factor of ln Ks were nonlinear. Variation in MRD was higher in coarser textures than in finer ones and more variability was seen in the topsoil than in the subsoil. Established vegetation decreased variability of MRD in the root zone and increased variability below. The dependence of MRD on Ks opens the possibility of using SWC sensor networks to relate variations of MRD of measured SWC time series to spatial variations of Ks. TS of SWC can provide information on Ks variability at ungauged watersheds if the effect of non-local controls of SWC on TS is not significant. Using the spatiotemporal statistics to convert the information about the temporal variability of soil moisture into information about the spatial variability of soil hydraulic properties presents an interesting avenue for further exploration.
Spatial variability of soil hydraulics and remotely sensed soil parameters
NASA Technical Reports Server (NTRS)
Lascano, R. J.; Van Bavel, C. H. M.
1982-01-01
The development of methods to correctly interpret remotely sensed information about soil moisture and soil temperature requires an understanding of water and energy flow in soil, because the signals originate from the surface, or from a shallow surface layer, but reflect processes in the entire profile. One formidable difficulty in this application of soil physics is the spatial heterogeneity of natural soils. Earlier work has suggested that the heterogeneity of soil hydraulic properties may be described by the frequency distribution of a single scale factor. The sensitivity of hydraulic and energetic processes to the variation of this scale factor is explored with a suitable numerical model. It is believed that such an analysis can help in deciding how accurately and extensively basic physical properties of field soils need to be known in order to interpret thermal or radar waveband signals. It appears that the saturated hydraulic conductivity needs to be known only to its order of magnitude, and that the required accuracy of the soil water retention function is about 0.02 volume fraction. Furthermore, the results may be helpful in deciding how the total scene or view field, as perceived through a sensor, is composed from the actual mosaic of transient soil properties, such as surface temperature or surface soil moisture. However, the latter proposition presupposes a random distribution of permanent properties, a condition that may not be met in many instances, and no solution of the problem is apparent.
NASA Astrophysics Data System (ADS)
Benitez Buelga, Javier; Rodriguez-Sinobas, Leonor; Sanchez, Raul; Gil, Maria; Tarquis, Ana M.
2014-05-01
Soils can be seen as the result of spatial variation operating over several scales. This observation points to 'variability' as a key soil attribute that should be studied. Soil variability has often been considered to be composed of 'functional' (explained) variations plus random fluctuations or noise. However, the distinction between these two components is scale dependent because increasing the scale of observation almost always reveals structure in the noise. Geostatistical methods and, more recently, multifractal/wavelet techniques have been used to characterize scaling and heterogeneity of soil properties among others coming from complexity science. Multifractal formalism, first proposed by Mandelbrot (1982), is suitable for variables with self-similar distribution on a spatial domain (Kravchenko et al., 2002). Multifractal analysis can provide insight into spatial variability of crop or soil parameters (Vereecken et al., 2007). This technique has been used to characterize the scaling property of a variable measured along a transect as a mass distribution of a statistical measure on a spatial domain of the studied field (Zeleke and Si, 2004). To do this, it divides the transect into a number of self-similar segments. It identifies the differences among the subsets by using a wide range of statistical moments. Wavelets were developed in the 1980s for signal processing, and later introduced to soil science by Lark and Webster (1999). The wavelet transform decomposes a series; whether this be a time series (Whitcher, 1998; Percival and Walden, 2000), or as in our case a series of measurements made along a transect; into components (wavelet coefficients) which describe local variation in the series at different scale (or frequency) intervals, giving up only some resolution in space (Lark et al., 2003, 2004). Wavelet coefficients can be used to estimate scale specific components of variation and correlation. This allows us to see which scales contribute most to signal variation, or to see at which scales signals are most correlated. This can give us an insight into the dominant processes An alternative to both of the above methods has been described recently. Relative entropy and increments in relative entropy has been applied in soil images (Bird et al., 2006) and in soil transect data (Tarquis et al., 2008) to study scale effects localized in scale and provide the information that is complementary to the information about scale dependencies found across a range of scales. We will use them in this work to describe the spatial scaling properties of a set of field water content data measured in an extension of a corn field, in a plot of 500 m2 and an spatial resolution of 25 cm. These measurements are based on an optics cable (BruggSteal) buried on a ziz-zag deployment at 30cm depth. References Bird, N., M.C. Díaz, A. Saa, and A.M. Tarquis. 2006. A review of fractal and multifractal analysis of soil pore-scale images. J. Hydrol. 322:211-219. Kravchenko, A.N., R. Omonode, G.A. Bollero, and D.G. Bullock. 2002. Quantitative mapping of soil drainage classes using topographical data and soil electrical conductivity. Soil Sci. Soc. Am. J. 66:235-243. Lark, R.M., A.E. Milne, T.M. Addiscott, K.W.T. Goulding, C.P. Webster, and S. O'Flaherty. 2004. Scale- and location-dependent correlation of nitrous oxide emissions with soil properties: An analysis using wavelets. Eur. J. Soil Sci. 55:611-627. Lark, R.M., S.R. Kaffka, and D.L. Corwin. 2003. Multiresolution analysis of data on electrical conductivity of soil using wavelets. J. Hydrol. 272:276-290. Lark, R. M. and Webster, R. 1999. Analysis and elucidation of soil variation using wavelets. European J. of Soil Science, 50(2): 185-206. Mandelbrot, B.B. 1982. The fractal geometry of nature. W.H. Freeman, New York. Percival, D.B., and A.T. Walden. 2000. Wavelet methods for time series analysis. Cambridge Univ. Press, Cambridge, UK. Tarquis, A.M., N.R. Bird, A.P. Whitmore, M.C. Cartagena, and Y. Pachepsky. 2008. Multiscale analysis of soil transect data. Vadose Zone J. 7: 563-569. Vereecken, H., R. Kasteel, J. Vanderborght, and T. Harter. 2007. Upscaling hydraulic properties and soil water flow processes in heterogeneous soils: A review. Vadose Zone J. 6:1-28. Whitcher, B.J. 1998. Assessing nonstationary time series using wavelets. Ph.D. diss. Univ. of Washington, Seattle (Diss. Abstr. 9907961). Zeleke, T.B., and B.C. Si. 2004. Scaling properties of topographic indices and crop yield: Multifractal and joint multifractal approaches. Agron J., 96:1082-1090.
NASA Astrophysics Data System (ADS)
Heckman, K. A.; Gallo, A.; Hatten, J. A.; Swanston, C.; McKnight, D. M.; Strahm, B. D.; Sanclements, M.
2017-12-01
Soil carbon stocks have become recognized as increasingly important in the context of climate change and global C cycle modeling. As modelers seek to identify key parameters affecting the size and stability of belowground C stocks, attention has been drawn to the mineral matrix and the soil physiochemical factors influenced by it. Though clay content has often been utilized as a convenient and key explanatory variable for soil C dynamics, its utility has recently come under scrutiny as new paradigms of soil organic matter stabilization have been developed. We utilized soil cores from a range of National Ecological Observatory Network (NEON) experimental plots to examine the influence of physicochemical parameters on soil C stocks and turnover, and their relative importance in comparison to climatic variables. Soils were cored at NEON sites, sampled by genetic horizon, and density separated into light fractions (particulate organics neither occluded within aggregates nor associated with mineral surfaces), occluded fractions (particulate organics occluded within aggregates), and heavy fractions (organics associated with mineral surfaces). Bulk soils and density fractions were measured for % C and radiocarbon abundance (as a measure of C stability). Carbon and radiocarbon abundances were examined among fractions and in the context of climatic variables (temperature, precipitation, elevation) and soil physiochemical variables (% clay and pH). No direct relationships between temperature and soil C or radiocarbon abundances were found. As a whole, soil radiocarbon abundance in density fractions decreased in the order of light>heavy>occluded, highlighting the importance of both surface sorption and aggregation to the preservation of organics. Radiocarbon abundance was correlated with pH, with variance also grouping by dominate vegetation type. Soil order was also identified as an important proxy variable for C and radiocarbon abundance. Preliminary results suggest that both integrative proxies as well as physicochemical properties may be needed to account for variation in soil C abundance and stability at the continental scale.
NASA Astrophysics Data System (ADS)
Robinet, Jérémy; von Hebel, Christian; van der Kruk, Jan; Govers, Gerard; Vanderborght, Jan
2016-04-01
As highlighted by many authors, classical or geophysical techniques for measuring soil moisture such as destructive soil sampling, neutron probes or Time Domain Reflectometry (TDR) have some major drawbacks. Among other things, they provide point scale information, are often intrusive and time-consuming. ElectroMagnetic Induction (EMI) instruments are often cited as a promising alternative hydrogeophysical methods providing more efficiently soil moisture measurements ranging from hillslope to catchment scale. The overall objective of our research project is to investigate whether a combination of geophysical techniques at various scales can be used to study the impact of land use change on temporal and spatial variations of soil moisture and soil properties. In our work, apparent electrical conductivity (ECa) patterns are obtained with an EM multiconfiguration system. Depth profiles of ECa were subsequently inferred through a calibration-inversion procedure based on TDR data. The obtained spatial patterns of these profiles were linked to soil profile and soil water content distributions. Two catchments with contrasting land use (agriculture vs. natural forest) were selected in a subtropical region in the south of Brazil. On selected slopes within the catchments, combined EMI and TDR measurements were carried out simultaneously, under different atmospheric and soil moisture conditions. Ground-truth data for soil properties were obtained through soil sampling and auger profiles. The comparison of these data provided information about the potential of the EMI technique to deliver qualitative and quantitative information about the variability of soil moisture and soil properties.
Rethinking Soils: an under-investigated commons?
NASA Astrophysics Data System (ADS)
Short, Chrisopher; Mills, Jane; Ingram, Julie
2015-04-01
In a number of global contexts there is a re-awakening of interest in soils in both increasing the resilience of complex social-ecological systems (SES) and as a result of the threats to them, as shown by the UN International Year of Soils in 2015. Consequently the management of soils and their wider role within property regimes and natural resource management might need to be reassessed. At the heart of this is the rise in awareness regarding the connectedness of SES, and in frameworks such as the Ecosystem Approach and the identification and analysis of Ecosystem Services. Whilst not new to some, it has widened the understanding among many, that soils have a valuable role to play in complex SES because they are a slow variable crucial to underlying structure of the SES. The conventional approach that soils are linked to the ecosystem services category of provisioning services (production of food, timber and fibre) remains valid. Not surprisingly this link is strong within natural resource management and property rights regimes but soils remain at risk for a range of threats, for example soil erosion and compaction, salinization, sealing, desertification, loss of organic matter and biodiversity and contamination. However, soils are increasingly seen as a slow variable that can lead to increased resilience within a SES and have a profound importance to human life through a range of regulating services including water quality and purification, water flow and attenuation and , pest and disease control. Given the long-standing importance of soil as a natural resource there are also accompanying legal systems, property regimes, societal values, knowledge, custom and traditions. However, in the light of the wider understanding soil functions are these social frameworks appropriate and fit for purpose or would a shared resource of commons approach be more appropriate. To some extent this examination would also extend to the presence of soils within the cultural services category of ecosystem services. As a result of the increasing evidence regarding soil threats, there is concern that the knowledge relating to soils is fragmented and incomplete. This is particular true regarding the complexity and functioning of soil systems and their interaction with human activities and the effectiveness of governance arrangements to promote resilience in the management of soils. Therefore discussions concerning soils needs to be taken from an interdisciplinary perspectives that embraces both natural and social sciences. This paper will seek to examine soils from a multi-scale governance/complex commons perspective. It will also consider how a commons perspective might be useful in reducing soil threats and in the development of effective prevention, remediation and restoration measures. This often requires a change in thinking about soil, perhaps considering it as a 'slow variable', able to drive long-term change or as a 'cultural asset' and 'knowledge resource'.
NASA Astrophysics Data System (ADS)
Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin
2018-05-01
Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.
NASA Astrophysics Data System (ADS)
Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen
2016-04-01
Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.
Rahmatpour, Samaneh; Shirvani, Mehran; Mosaddeghi, Mohammad R; Bazarganipour, Mehdi
2017-05-15
The rapid production and application of silver nanoparticles (AgNPs) have led to significant release of AgNPs into the terrestrial environments. Once released into the soil, AgNPs could enter into different interactions with soil particles which play key roles in controlling the fate and transport of these nanoparticles. In spite of that, experimental studies on the retention of AgNPs in soils are very scarce. Hence, the key objective of this research was to find out the retention behavior of AgNPs and Ag(I) ions in a range of calcareous soils. A second objective was to determine the extent to which the physico-chemical properties of the soils influence the Ag retention parameters. To this end, isothermal batch experiments were used to determine the retention of Poly(vinylpyrrolidinone)-capped AgNPs (PVP-AgNPs) and Ag(I) ions by nine calcareous soils with a diversity of physico-chemical properties. The results revealed that the retention data for both PVP-AgNPs and Ag(I) ions were well described by the classical Freundlich and Langmuir isothermal equations. The retention of PVP-AgNPs and Ag(I) ions was positively correlated to clay and organic carbon (OC) contents as well as electrical conductivity (EC), pH, and cation exchange capacity (CEC) of the soils. Due to multicolinearity among the soil properties, principal component analysis (PCA) was used to group the soil properties which affect the retention of PVP-AgNPs and Ag(I) ions. Accordingly, we identified two groups of soil properties controlling retention of PVP-AgNPs and Ag(I) ions in the calcareous soils. The first group comprised soil solid phase parameters like clay, OC, and CEC, which generally control hetero-aggregation and adsorption reactions and the second group included soil solution variables such as EC and pH as well as Cl - and Ca 2+ concentrations, which are supposed to mainly affect homo-aggregation and precipitation reactions. Copyright © 2017. Published by Elsevier Ltd.
Tuttle, M.L.; Severson, R.C.; Dean, W.E.; Klusman, R.W.
1986-01-01
Geochemical baselines for native soils and biogeochemical baselines for plants in the Piceance basin provide data that can be used to assess geochemical and biogeochemical effects of oil-shale development, monitor changes in the geochemical and biogeochemical environment during development, and assess the degree of success of rehabilitation of native materials after development. Baseline values for 52 properties in native soils, 15 properties in big sagebrush, and 13 properties in western wheatgrass were established. Our Study revealed statistically significant regional variations of the following properties across the basin: in soil&-aluminum, cobalt, copper, iron, manganese, sodium, nickel, phosphorus, lead, scandium, titanium, vanadium, zinc, organic and total carbon, pH, clay, dolomite, sodium feldspar, and DTPA-extractable calcium, cadmium, iron, potassium, manganese, nickel, phosphorus, yttrium, and zinc; in big sagebrush-barium, calcium, copper, magnesium, molybdenum, sodium, strontium, zinc, and ash; and in western wheatgrass-boron, barium, calcium, magnesium, manganese, molybdenum, strontium, zinc, and ash. These variations show up as north-south trends across the basin, or they reflect differences in elevation, hydrology, and soil parent material. Baseline values for properties that do not have statistically significant regional variations can be represented by geometric means and deviations calculated from all values within the basin. Chemical and mineralogical analyses of soil and chemical analyses of western wheatgrass samples from Colorado State University's experimental revegetation plot at Anvil Points provide data useful in assessing potential effects on soil and plant properties when largescale revegetation operations begin. The concentrations of certain properties are related to the presence of topsoil over spent shale in the lysimeters. In soils, calcium, fluorine, lithium, magnesium, sodium, phosphorus, strontium, carbonate and total carbon, and DTPA-extractable boron, copper, iron, magnesium, and nickel have lower concentrations in topsoil than in the spent oil shale; whereas, silicon, titanium, ytterbium, clay, quartz, and DTPA-extractable potassium have greater concentrations in the topsoil than in the spent oil shale. In western wheatgrass, molybdenum has a lower concentration in grasses growing on the topsoil than in grasses on the spent oil shale; whereas, barium, calcium, manganese, strontium, zinc, and ash have greater concentrations in grasses growing on the topsoil than on the spent oil shale. When compared to baseline values, soils in the revegetation plot are significantly higher in concentrations of lead, zinc, organic and total carbon, and DTP A-extractable cadmium, iron, manganese, nickel, phosphorus, and zinc. Whereas, western wheatgrass grown within the revegetation plot has concentrations which fall within the baseline values established in the regional study. The equations used in predicting concentrations of elements in plants from native and altered sites are cumbersome because of the large number of variables required to adequately predict expected concentrations and are of limited use because many explained only a small proportion of the total variation.
The soil water regime of stony soils in a mountain catchment
NASA Astrophysics Data System (ADS)
Hlaváčiková, Hana; Danko, Michal; Holko, Ladislav; Hlavčo, Jozef; Novák, Viliam
2016-04-01
Investigation of processes related to runoff generation is an important topic in catchment hydrology. Observations are usually carried out in small catchments or on hillslopes. Many of such catchments are located in mountain or forested areas. From many studies it is evident that soil conditions and soil characteristics are one of the crucial factors in runoff generation. Mountainous or forest soils have usually high rock fragments content. Nevertheless, the influence of soil stoniness on water flow was not sufficiently studied up to now at catchment and hillslope scales due to flow formation complexity or problems with stony soil properties measurement (installing measuring devices, interpretation of measured data). Results of this work can be divided in two groups: (1) hydrophysical properties of stony soils measurements, and (2) water flow dynamic modelling in stony soils. Properties of stony soils were measured in the Jalovecky creek catchment, the Western Tatra Mts., Slovakia. Altitude of particular study sites varies from 780 to1500 m a.s.l. We measured and analyzed the stoniness of reference soil profiles, as well as retention properties of stony soils (fine soil fraction and rock fragments separately) and hydraulic conductivities of surface and subsurface soil layers. The methodology for determination of the effective hydrophysical properties of a stony soil (later used in modelling) was proposed using results from measurements, calculation, and numerical Darcy experiments. Modelling results show that the presence of rock fragments with low water retention in a stony soil with moderate or high stoniness can cause the soil water storage decrease by 16-31% in compared to the soil without rock fragments. In addition, decreased stony soil retention capacity resulted in faster outflow increase at the bottom of the soil profile during non-ponding infiltration. Furthermore, the presence of rock fragments can increase maximum outflow value. It is not possible to simply extrapolate the results from a soil profile to larger catchment scale because spatial variability of soil properties and unknown bedrock properties. Moreover, water outflow from the soil profile is a complex problem in which several factors co-operate. However, this points out that the presence of rock fragments in moderate or highly stony soils can play a significant role in catchment runoff generation under certain circumstances.
Infiltration Variability in Agricultural Soil Aggregates Caused by Air Slaking
NASA Astrophysics Data System (ADS)
Korenkova, L.; Urik, M.
2018-04-01
This article reports on variation in infiltration rates of soil aggregates as a result of phenomenon known as air slaking. Air slaking is caused by the compression and subsequent escape of air captured inside soil aggregates during water saturation. Although it has been generally assumed that it occurs mostly when dry aggregates are rapidly wetted, the measurements used for this paper have proved that it takes place even if the wetting is gradual, not just immediate. It is a phenomenon that contributes to an infiltration variability of soils. In measuring the course of water flow through the soil, several small aggregates of five agricultural soils were exposed to distilled water at zero tension in order to characterize their hydraulic properties. Infiltration curves obtained for these aggregates demonstrate the effect of entrapped air on the increase and decrease of infiltration rates. The measurements were performed under various moisture conditions of the A-horizon aggregates using a simple device.
Physical soil quality indicators for monitoring British soils
NASA Astrophysics Data System (ADS)
Corstanje, Ron; Mercer, Theresa G.; Rickson, Jane R.; Deeks, Lynda K.; Newell-Price, Paul; Holman, Ian; Kechavarsi, Cedric; Waine, Toby W.
2017-09-01
Soil condition or quality determines its ability to deliver a range of functions that support ecosystem services, human health and wellbeing. The increasing policy imperative to implement successful soil monitoring programmes has resulted in the demand for reliable soil quality indicators (SQIs) for physical, biological and chemical soil properties. The selection of these indicators needs to ensure that they are sensitive and responsive to pressure and change, e.g. they change across space and time in relation to natural perturbations and land management practices. Using a logical sieve approach based on key policy-related soil functions, this research assessed whether physical soil properties can be used to indicate the quality of British soils in terms of their capacity to deliver ecosystem goods and services. The resultant prioritised list of physical SQIs was tested for robustness, spatial and temporal variability, and expected rate of change using statistical analysis and modelling. Seven SQIs were prioritised: soil packing density, soil water retention characteristics, aggregate stability, rate of soil erosion, depth of soil, soil structure (assessed by visual soil evaluation) and soil sealing. These all have direct relevance to current and likely future soil and environmental policy and are appropriate for implementation in soil monitoring programmes.
NASA Astrophysics Data System (ADS)
Akin, Muge K.
2016-04-01
The term of ground improvement states to the modification of the engineering properties of soils. Jet-grouting is one of the grouting methods among various ground improvement techniques. During jet-grouting, different textures of columns can be obtained depending on the characteristics of surrounding subsoil as well as the adopted jet-grouting system for each site is variable. In addition to textural properties, strength and index parameters of jet-grout columns are highly affected by the adjacent soil. In this study, the physical and mechanical properties of jet-grout columns constructed at two different sites in silty and sandy soil conditions were determined by laboratory tests. A number of statistical relationships between physical and mechanical properties of soilcrete were established in this study in order to investigate the dependency of numerous variables. The relationship between qu and γd is more reliable for sandy soilcrete than that of silty columns considering the determination coefficients. Positive linear relationships between Vp and γd with significantly high determination coefficients were obtained for the jet-grout columns in silt and sand. The regression analyses indicate that the P-wave velocity is a very dominant parameter for the estimation of physical and mechanical properties of jet-grout columns and should be involved during the quality control of soilcrete material despite the intensive use of uniaxial compressive strength test. Besides, it is concluded that the dry unit weight of jet-grout column is a good indicator of the efficiency of employed operational parameters during jet-grouting.
imVisIR - a new tool for high resolution soil characterisation
NASA Astrophysics Data System (ADS)
Steffens, Markus; Buddenbaum, Henning
2014-05-01
The physical and chemical heterogeneities of soils are the source of a vast functional diversity of soil properties in a multitude of spatial domains. But many studies do not consider the spatial variability of soil types, diagnostic horizons and properties. These lateral and vertical heterogeneities of soils or soil horizons are mostly neglected due to the limitations in the available soil data and missing techniques to gather the information. We present an imaging technique that enables the spatially accurate, high resolution assessment (63×63 µm2 per pixel) of complete soil profiles consisting of mineral and organic horizons. We used a stainless steel box (100×100×300 mm3) to sample various soil types and a hyperspectral camera to record the bidirectional reflectance of the large undisturbed soil samples in the visible and near infrared (Vis-NIR) part of the electromagnetic spectrum (400-1000 nm in 160 spectral bands). Various statistical, geostatistical and image processing tools were used to 1) assess the spatial variability of the soil profile as a whole; 2) classify diagnostic horizons; 3) extrapolate elemental concentrations of small sampling areas to the complete image and calculate high resolution chemometric maps of up to five elements (C, N, Al, Fe, Mn); and 4) derive maps of the chemical composition of soil organic matter. Imaging Vis-NIR (imVisIR) has the potential to significantly improve soil classification, assessment of elemental budgets and balances and the understanding of soil forming processes and mechanisms. It will help to identify areas of interest for techniques working on smaller scales and enable the upscaling and referencing of this information to the complete pedon.
Gremer, Jennifer; Bradford, John B.; Munson, Seth M.; Duniway, Michael C.
2015-01-01
Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20 to 56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40 to 60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.
Gremer, Jennifer R; Bradford, John B; Munson, Seth M; Duniway, Michael C
2015-11-01
Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
Pedotransfer Functions in Earth System Science: Challenges and Perspectives
NASA Astrophysics Data System (ADS)
Van Looy, Kris; Bouma, Johan; Herbst, Michael; Koestel, John; Minasny, Budiman; Mishra, Umakant; Montzka, Carsten; Nemes, Attila; Pachepsky, Yakov A.; Padarian, José; Schaap, Marcel G.; Tóth, Brigitta; Verhoef, Anne; Vanderborght, Jan; van der Ploeg, Martine J.; Weihermüller, Lutz; Zacharias, Steffen; Zhang, Yonggen; Vereecken, Harry
2017-12-01
Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.
Uncertainty in predicting soil hydraulic properties at the hillslope scale with indirect methods
NASA Astrophysics Data System (ADS)
Chirico, G. B.; Medina, H.; Romano, N.
2007-02-01
SummarySeveral hydrological applications require the characterisation of the soil hydraulic properties at large spatial scales. Pedotransfer functions (PTFs) are being developed as simplified methods to estimate soil hydraulic properties as an alternative to direct measurements, which are unfeasible for most practical circumstances. The objective of this study is to quantify the uncertainty in PTFs spatial predictions at the hillslope scale as related to the sampling density, due to: (i) the error in estimated soil physico-chemical properties and (ii) PTF model error. The analysis is carried out on a 2-km-long experimental hillslope in South Italy. The method adopted is based on a stochastic generation of patterns of soil variables using sequential Gaussian simulation, conditioned to the observed sample data. The following PTFs are applied: Vereecken's PTF [Vereecken, H., Diels, J., van Orshoven, J., Feyen, J., Bouma, J., 1992. Functional evaluation of pedotransfer functions for the estimation of soil hydraulic properties. Soil Sci. Soc. Am. J. 56, 1371-1378] and HYPRES PTF [Wösten, J.H.M., Lilly, A., Nemes, A., Le Bas, C., 1999. Development and use of a database of hydraulic properties of European soils. Geoderma 90, 169-185]. The two PTFs estimate reliably the soil water retention characteristic even for a relatively coarse sampling resolution, with prediction uncertainties comparable to the uncertainties in direct laboratory or field measurements. The uncertainty of soil water retention prediction due to the model error is as much as or more significant than the uncertainty associated with the estimated input, even for a relatively coarse sampling resolution. Prediction uncertainties are much more important when PTF are applied to estimate the saturated hydraulic conductivity. In this case model error dominates the overall prediction uncertainties, making negligible the effect of the input error.
Modeling the Impact of Soil Conditions on Global Water Balance
NASA Astrophysics Data System (ADS)
Wang, P. L.; Feddema, J. J.
2016-12-01
The amount of water the soil can hold for plant use, defined as soil water-holding capacity (WHC), has a large influence on the water cycle and climatic variables. Although soil properties vary widely worldwide, many climate modeling applications assume WHC to be spatially invariant. This study explores how a more realistic soil WHC estimate affects the global water balance relative to commonly assumed soil properties. We use a modified Thornthwaite water balance model combined with a newly developed soil WHC and soil thickness data at a 30 arc second resolution. The soil WHC data was obtained by integrating WHCs to a depth of 2 m and modified by the soil thickness data on a grid-by-grid basis, and then resampling to the 0.5 degree climatology data. We observed that down scaling soils data before modifying soil depths greatly increases global soil WHCs. This new dataset is compared to WHC information with a fixed 2-m soil depth, and a constant 150-mm soil WHC. Results indicate higher soil WHC results in increased soil moisture, decreased moisture surplus and deficits, and increased actual evapotranspiration (AE), and vice-versa. However, due to high variability in soil characteristics across climate gradients, this generalization does not hold true for regionally averaged outcomes. Compared to using a constant 150-mm WHC, more realistic soil WHC increases global averaged AE 1%, and decreases deficit 2% and surplus 3%. Most change is observed in areas with pronounced wet and dry seasons; using a constant 2-m soil depth doubles the differences. Regionally, Europe was most affected: AE increases 4%, and the deficit and surplus decrease 20% and 12%. Australia shows that regionally averaged results are not equivocal for moisture surplus and deficit; deficit decreases 0.4%, while surplus decreases 9%. This research highlights the importance of soil condition for climate modeling and how a better representation of soil moisture conditions affects global water balance modeling.
The use of crop rotation for mapping soil organic content in farmland
NASA Astrophysics Data System (ADS)
Yang, Lin; Song, Min; Zhu, A.-Xing; Qin, Chengzhi
2017-04-01
Most of the current digital soil mapping uses natural environmental covariates. However, human activities have significantly impacted the development of soil properties since half a century, and therefore become an important factor affecting soil spatial variability. Many researches have done field experiments to show how soil properties are impacted and changed by human activities, however, spatial variation data of human activities as environmental covariates have been rarely used in digital soil mapping. In this paper, we took crop rotation as an example of agricultural activities, and explored its effectiveness in characterizing and mapping the spatial variability of soil. The cultivated area of Xuanzhou city and Langxi County in Anhui Province was chosen as the study area. Three main crop rotations,including double-rice, wheat-rice,and oilseed rape-cotton were observed through field investigation in 2010. The spatial distribution of the three crop rotations in the study area was obtained by multi-phase remote sensing image interpretation using a supervised classification method. One-way analysis of variance (ANOVA) for topsoil organic content in the three crop rotation groups was performed. Factor importance of seven natural environmental covariates, crop rotation, Land use and NDVI were generated by variable importance criterion of Random Forest. Different combinations of environmental covariates were selected according to the importance rankings of environmental covariates for predicting SOC using Random Forest and Soil Landscape Inference Model (SOLIM). A cross validation was generated to evaluated the mapping accuracies. The results showed that there were siginificant differences of topsoil organic content among the three crop rotation groups. The crop rotation is more important than parent material, land use or NDVI according to the importance ranking calculated by Random Forest. In addition, crop rotation improved the mapping accuracy, especially for the flat clutivated area. This study demonstrates the usefulness of human activities in digital soil mapping and thus indicates the necessity for human activity factors in digital soil mapping studies.
[Interrelationships between soil fauna and soil environmental factors in China: research advance].
Wang, Yi; Wei, Wei; Yang, Xing-zhong; Chen, Li-ding; Yang, Lei
2010-09-01
Soil fauna has close relations with various environmental factors in soil ecosystem. To explore the interrelationships between soil fauna and soil environmental factors is of vital importance to deep understand the dynamics of soil ecosystem and to assess the functioning of the ecosystem. The environmental factors affecting soil fauna can be classified as soil properties and soil external environment. The former contains soil basic physical and chemical properties, soil moisture, and soil pollution. The latter includes vegetation, land use type, landform, and climate, etc. From these aspects, this paper summarized the published literatures in China on the interrelationships between soil fauna and soil environmental factors. It was considered that several problems were existed in related studies, e.g., fewer researches were made in integrating soil fauna's bio-indicator function, research methods were needed to be improved, and the studies on the multi-environmental factors and their large scale spatial-temporal variability were in deficiency. Corresponding suggestions were proposed, i.e., more work should be done according to the practical needs, advanced experiences from abroad should be referenced, and comprehensive studies on multi-environmental factors and long-term monitoring should be conducted on large scale areas.
Estimating Soil Cation Exchange Capacity from Soil Physical and Chemical Properties
NASA Astrophysics Data System (ADS)
Bateni, S. M.; Emamgholizadeh, S.; Shahsavani, D.
2014-12-01
The soil Cation Exchange Capacity (CEC) is an important soil characteristic that has many applications in soil science and environmental studies. For example, CEC influences soil fertility by controlling the exchange of ions in the soil. Measurement of CEC is costly and difficult. Consequently, several studies attempted to obtain CEC from readily measurable soil physical and chemical properties such as soil pH, organic matter, soil texture, bulk density, and particle size distribution. These studies have often used multiple regression or artificial neural network models. Regression-based models cannot capture the intricate relationship between CEC and soil physical and chemical attributes and provide inaccurate CEC estimates. Although neural network models perform better than regression methods, they act like a black-box and cannot generate an explicit expression for retrieval of CEC from soil properties. In a departure with regression and neural network models, this study uses Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) to estimate CEC from easily measurable soil variables such as clay, pH, and OM. CEC estimates from GEP and MARS are compared with measurements at two field sites in Iran. Results show that GEP and MARS can estimate CEC accurately. Also, the MARS model performs slightly better than GEP. Finally, a sensitivity test indicates that organic matter and pH have respectively the least and the most significant impact on CEC.
NASA Astrophysics Data System (ADS)
Verdoodt, Ann; Baert, Geert; Van Ranst, Eric
2014-05-01
Central African soil resources are characterised by a large variability, ranging from stony, shallow or sandy soils with poor life-sustaining capabilities to highly weathered soils that recycle and support large amounts of biomass. Socio-economic drivers within this largely rural region foster inappropriate land use and management, threaten soil quality and finally culminate into a declining soil productivity and increasing food insecurity. For the development of sustainable land use strategies targeting development planning and natural hazard mitigation, decision makers often rely on legacy soil maps and soil profile databases. Recent development cooperation financed projects led to the design of soil information systems for Rwanda, D.R. Congo, and (ongoing) Burundi. A major challenge is to exploit these existing soil databases and convert them into soil inference systems through an optimal combination of digital soil mapping techniques, land evaluation tools, and biogeochemical models. This presentation aims at (1) highlighting some key characteristics of typical Central African soils, (2) assessing the positional, geographic and semantic quality of the soil information systems, and (3) revealing its potential impacts on the use of these datasets for thematic mapping of soil ecosystem services (e.g. organic carbon storage, pH buffering capacity). Soil map quality is assessed considering positional and semantic quality, as well as geographic completeness. Descriptive statistics, decision tree classification and linear regression techniques are used to mine the soil profile databases. Geo-matching as well as class-matching approaches are considered when developing thematic maps. Variability in inherent as well as dynamic soil properties within the soil taxonomic units is highlighted. It is hypothesized that within-unit variation in soil properties highly affects the use and interpretation of thematic maps for ecosystem services mapping. Results will mainly be based on analyses done in Rwanda, but can be complemented with ongoing research results or prospects for Burundi.
Bielská, Lucie; Hovorková, Ivana; Kuta, Jan; Machát, Jiří; Hofman, Jakub
2017-01-01
Artificial soil (AS) is used in soil ecotoxicology as a test medium or reference matrix. AS is prepared according to standard OECD/ISO protocols and components of local sources are usually used by laboratories. This may result in significant inter-laboratory variations in AS properties and, consequently, in the fate and bioavailability of tested chemicals. In order to reveal the extent and sources of variations, the batch equilibrium method was applied to measure the sorption of 2 model compounds (phenanthrene and cadmium) to 21 artificial soils from different laboratories. The distribution coefficients (K d ) of phenanthrene and cadmium varied over one order of magnitude: from 5.3 to 61.5L/kg for phenanthrene and from 17.9 to 190L/kg for cadmium. Variations in phenanthrene sorption could not be reliably explained by measured soil properties; not even by the total organic carbon (TOC) content which was expected. Cadmium logK d values significantly correlated with cation exchange capacity (CEC), pH H2O and pH KCl , with Pearson correlation coefficients of 0.62, 0.80, and 0.79, respectively. CEC and pH H2O together were able to explain 72% of cadmium logK d variability in the following model: logK d =0.29pH H2O +0.0032 CEC -0.53. Similarly, 66% of cadmium logK d variability could be explained by CEC and pH KCl in the model: logKd=0.27pH KCl +0.0028 CEC -0.23. Variable cadmium sorption in differing ASs could be partially treated with these models. However, considering the unpredictable variability of phenanthrene sorption, a more reliable solution for reducing the variability of ASs from different laboratories would be better harmonization of AS preparation and composition. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Martini, Edoardo; Werban, Ulrike; Zacharias, Steffen; Pohle, Marco; Dietrich, Peter; Wollschläger, Ute
2017-01-01
Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.
Attribution of soil information associated with modeling background clutter
NASA Astrophysics Data System (ADS)
Mason, George; Melloh, Rae
2006-05-01
This paper examines the attribution of data fields required to generate high resolution soil profiles for support of Computational Test Bed (CTB) used for countermine research. The countermine computational test bed is designed to realistically simulate the geo-environment to support the evaluation of sensors used to locate unexploded ordnance. The goal of the CTB is to derive expected moisture, chemical compounds, and measure heat migration over time, from which we expect to optimize sensor performance. Several tests areas were considered for the collection of soils data to populate the CTB. Collection of bulk soil properties has inherent spatial resolution limits. Novel techniques are therefore required to populate a high resolution model. This paper presents correlations between spatial variability in texture as related to hydraulic permeability and heat transfer properties of the soil. The extracted physical properties are used to exercise models providing a signature of subsurface media and support the simulation of detection by various sensors of buried and surface ordnance.
NASA Technical Reports Server (NTRS)
Colwell, R. N. (Principal Investigator); Wall, S. L.; Beck, L. H.; Degloria, S. D.; Ritter, P. R.; Thomas, R. W.; Travlos, A. J.; Fakhoury, E.
1984-01-01
Materials and methods used to characterize selected soil properties and agricultural crops in San Joaquin County, California are described. Results show that: (1) the location and widths of TM bands are suitable for detecting differences in selected soil properties; (2) the number of TM spectral bands allows the quantification of soil spectral curve form and magnitude; and (3) the spatial and geometric quality of TM data allows for the discrimination and quantification of within field variability of soil properties. The design of the LANDSAT based multiple crop acreage estimation experiment for the Idaho Department of Water Resources is described including the use of U.C. Berkeley's Survey Modeling Planning Model. Progress made on Peditor software development on MIDAS, and cooperative computing using local and remote systems is reported as well as development of MIDAS microcomputer systems.
Cotton NDVI response to applied N at different soil EC levels
USDA-ARS?s Scientific Manuscript database
Many fields in the southeastern Coastal Plain are highly variable in soil physical properties and are irregular in shape. These two conditions may make it difficult to determine the ‘best’ area in the field to place nitrogen (N) -rich strips for normalized difference vegetative index (NDVI) -based s...
NASA Astrophysics Data System (ADS)
Xu, Yiming; Smith, Scot E.; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P.
2017-01-01
Soil prediction models based on spectral indices from some multispectral images are too coarse to characterize spatial pattern of soil properties in small and heterogeneous agricultural lands. Image pan-sharpening has seldom been utilized in Digital Soil Mapping research before. This research aimed to analyze the effects of pan-sharpened (PAN) remote sensing spectral indices on soil prediction models in smallholder farm settings. This research fused the panchromatic band and multispectral (MS) bands of WorldView-2, GeoEye-1, and Landsat 8 images in a village in Southern India by Brovey, Gram-Schmidt and Intensity-Hue-Saturation methods. Random Forest was utilized to develop soil total nitrogen (TN) and soil exchangeable potassium (Kex) prediction models by incorporating multiple spectral indices from the PAN and MS images. Overall, our results showed that PAN remote sensing spectral indices have similar spectral characteristics with soil TN and Kex as MS remote sensing spectral indices. There is no soil prediction model incorporating the specific type of pan-sharpened spectral indices always had the strongest prediction capability of soil TN and Kex. The incorporation of pan-sharpened remote sensing spectral data not only increased the spatial resolution of the soil prediction maps, but also enhanced the prediction accuracy of soil prediction models. Small farms with limited footprint, fragmented ownership and diverse crop cycle should benefit greatly from the pan-sharpened high spatial resolution imagery for soil property mapping. Our results show that multiple high and medium resolution images can be used to map soil properties suggesting the possibility of an improvement in the maps' update frequency. Additionally, the results should benefit the large agricultural community through the reduction of routine soil sampling cost and improved prediction accuracy.
NASA Astrophysics Data System (ADS)
Altdorff, Daniel; Bechtold, Michel; van der Kruk, Jan; Tiemeyer, Bärbel; von Hebel, Christian; Huisman, Johan Alexander
2014-05-01
Peatlands represent a huge storage of soil organic carbon (SOC), and there is considerable interest to assess the total amount of carbon stored in these ecosystems. However, reliable field-scale information about peat properties, particularly SOC content and bulk density (BD) necessary to estimate C stocks, remains difficult to obtain. A potential way to acquire information on these properties and its spatial variation is the non-invasive mapping of easily recordable physical variables that correlate with peat properties, such as bulk electrical conductivity (ECa) measured with electromagnetic induction (EMI). However, ECa depends on a range of soil properties, including BD, soil and water chemistry, and water content, and thus results often show complex and site-specific relationships. Therefore, a reliable prediction of SOC and BD from ECa data is not necessarily given. In this study, we aim to explore the usefulness of Multiple Linear Regression (MLR) models to predict the peat soil properties SOC and BD from multi-offset EMI and high-resolution DEM data. The quality of the MLR models is assessed by cross-validation. We use data from a medium-scale disturbed peat relict (approximately 35ha) in Northern Germany. The potential explanatory variables considered in MLR were: EMI data of six different integral depths (approximately 0.25, 0.5, 0.6, 0.9, 1, and 1.80 m), their vertical heterogeneity, as well as several topographical variables extracted from the DEM. Ground truth information for SOC, BD content and peat layer thickness was obtained from 34 soil cores of 1 m depth. Each core was divided into several 5 to 20 cm thick layers so that integral information of the upper 0.25, 0.5, and 1 m as well as from the total peat layer was obtained. For cross-validation of results, we clustered the 34 soil cores into 4 classes using K-means clustering and selected 8 cores for validation from the clusters with a probability that depended on the size of the cluster. With the remaining 26 samples, we performed a stepwise MLR and generated separate models for each depth and soil property. Preliminary results indicate reliable model predictions for SOC and BD (R² = 0.83- 0.95). The RMSE values of the validation ranged between 3.5 and 7.2 vol. % for SOC and 0.13 and 0.37 g/cm³ for BD for the independent samples. This equates roughly the quality of SOC predictions obtained by field application of vis-NIR (visible-near infrared) presented in literature for a similar peatland setting. However, the EMI approach offers the potential to derive information from deeper depths and allows non-invasive mapping of BD variability, which is not possible with vis-NIR. Therefore, this new approach potentially provides a more useful tool for total carbon stock assessment in peatlands.
Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode
NASA Astrophysics Data System (ADS)
Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna
2016-07-01
Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.
Maxwell, Toby M; Silva, Lucas C R; Horwath, William R
2018-05-01
This study was designed to address a major source of uncertainty pertaining to coupled carbon-water cycles in montane forest ecosystems. The Sierra Nevada of California was used as a model system to investigate connections between the physiological performance of trees and landscape patterns of forest carbon and water use. The intrinsic water-use efficiency (iWUE)-an index of CO 2 fixed per unit of potential water lost via transpiration-of nine dominant species was determined in replicated transects along an ∼1,500-m elevation gradient, spanning a broad range of climatic conditions and soils derived from three different parent materials. Stable isotope ratios of carbon and oxygen measured at the leaf level were combined with field-based and remotely sensed metrics of stand productivity, revealing that variation in iWUE depends primarily on leaf traits (∼24% of the variability), followed by stand productivity (∼16% of the variability), climatic regime (∼13% of the variability), and soil development (∼12% of the variability). Significant interactions between species composition and soil properties proved useful to predict changes in forest carbon-water relations. On the basis of observed shifts in tree species composition, ongoing since the 1950s and intensified in recent years, an increase in water loss through transpiration (ranging from 10 to 60% depending on parent material) is now expected in mixed conifer forests throughout the region. Copyright © 2018 the Author(s). Published by PNAS.
Genesis and properties of wetland soils by VIS-NIR-SWIR as a technique for environmental monitoring.
Demattê, José Alexandre Melo; Horák-Terra, Ingrid; Beirigo, Raphael Moreira; Terra, Fabrício da Silva; Marques, Karina Patrícia Prazeres; Fongaro, Caio Troula; Silva, Alexandre Christófaro; Vidal-Torrado, Pablo
2017-07-15
Wetlands are important ecosystems characterized by redoximorphic environments producing typical soil forming processes and organic carbon accumulation. Assessments and management of these areas are dependent on knowledge about soil characteristics and variability. By reflectance spectroscopy, information about soils can be obtained since their spectral behaviors are directly related to their chemical, physical, and mineralogical properties reflecting the pedogenetic processes and environment conditions. Our aims were: (a) to characterize the main soil classes of wetlands regarding their spectral behaviors in VIS-NIR-SWIR (350-2500 nm) and relate them to pedogenesis and environmental conditions, (b) to determine spectral ranges (bands) with greater expression of the main soil properties, (c) to identify spectral variations and similarities between hydromorphic soils from wetlands and other soils under different moisture conditions, and (d) to propose spectral models to quantify some chemical and physical soil properties used as environmental quality indicators. Nine soil profiles from the Pantanal region (Mato Grosso State, Brazil) and one from the Serra do Espinhaço Meridional (Minas Gerais State, Brazil) were investigated. Spectral morphology interpretation allowed identifying horizon differences regarding shape, absorption features and reflectance intensity. Some pedogenetic processes of wetland soils related to organic carbon accumulation and oxide iron variation were identified by spectra. Principal Component Analysis allowed discriminating soils from wetland and outside this area (oxidic environment). Quantification of organic carbon was possible with R 2 of 0.90 and low error. Quantification of clay content was masked by soils with organic carbon content over 2% where it was not possible to quantify with high R 2 and low error both properties when dataset has soil samples with high organic carbon content. By reflectance spectroscopy, important characteristics of wetland soils can be identified and used to distinguish from soils of different environments at low costs, reduced time, and with environmental quality. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mukherjee, A; Lal, R; Zimmerman, A R
2014-07-15
Short and long-term impacts of biochar on soil properties under field conditions are poorly understood. In addition, there is a lack of field reports of the impacts of biochar on soil physical properties, gaseous emissions and C stability, particularly in comparison with other amendments. Thus, three amendments - biochar produced from oak at 650°C, humic acid (HA) and water treatment residual - (WTR) were added to a scalped silty-loam soil @ 0.5% (w/w) in triplicated plots under soybean. Over the 4-month active growing season, all amendments significantly increased soil pH, but the effect of biochar was the greatest. Biochar significantly increased soil-C by 7%, increased sub-nanopore surface area by 15% and reduced soil bulk density by 13% compared to control. However, only WTR amendment significantly increased soil nanopore surface area by 23% relative to the control. While total cumulative CH4 and CO2 emissions were not significantly affected by any amendment, cumulative N2O emission was significantly decreased in the biochar-amended soil (by 92%) compared to control over the growing period. Considering both the total gas emissions and the C removed from the atmosphere as crop growth and C added to the soil, WTR and HA resulted in net soil C losses and biochar as a soil C gain. However, all amendments reduced the global warming potential (GWP) of the soil and biochar addition even produced a net negative GWP effect. The short observation period, low application rate and high intra-treatment variation resulted in fewer significant effects of the amendments on the physicochemical properties of the soils than one might expect indicating further possible experimentation altering these variables. However, there was clear evidence of amendment-soil interaction processes affecting both soil properties and gaseous emissions, particularly for biochar, that might lead to greater changes with additional field emplacement time. Copyright © 2014 Elsevier B.V. All rights reserved.
Soil erodibility variability in laboratory and field rainfall simulations
NASA Astrophysics Data System (ADS)
Szabó, Boglárka; Szabó, Judit; Jakab, Gergely; Centeri, Csaba; Szalai, Zoltán
2017-04-01
Rainfall simulation experiments are the most common way to observe and to model the soil erosion processes in in situ and ex situ circumstances. During modelling soil erosion, one of the most important factors are the annual soil loss and the soil erodibility which represent the effect of soil properties on soil loss and the soil resistance against water erosion. The amount of runoff and soil loss can differ in case of the same soil type, while it's characteristics determine the soil erodibility factor. This leads to uncertainties regarding soil erodibility. Soil loss and soil erodibility were examined with the investigation of the same soil under laboratory and field conditions with rainfall simulators. The comparative measurement was carried out in a laboratory on 0,5 m2, and in the field (Shower Power-02) on 6 m2 plot size where the applied slope angles were 5% and 12% with 30 and 90 mm/h rainfall intensity. The main idea was to examine and compare the soil erodibility and its variability coming from the same soil, but different rainfall simulator type. The applied model was the USLE, nomograph and other equations which concern single rainfall events. The given results show differences between the field and laboratory experiments and between the different calculations. Concerning for the whole rainfall events runoff and soil loss, were significantly higher at the laboratory experiments, which affected the soil erodibility values too. The given differences can originate from the plot size. The main research questions are that: How should we handle the soil erodibility factors and its significant variability? What is the best solution for soil erodibility determination?
NASA Astrophysics Data System (ADS)
Cai, Yue; Tang, Zhiyao; Xiong, Gaoming; Xie, Zongqiang; Liu, Zongguang; Feng, Xiaojuan
2017-09-01
Mineral protection is known as an important mechanism stabilizing soil organic carbon (SOC). However, the composition, sources, and variations of mineral-protected SOC remain poorly constrained. To fill this knowledge gap, we used hydrofluoric acid to demineralize soil matrix and compared the sources and distribution of mineral-protected lipids (ML) versus hydrolyzable lipids (HL) of four typical Chinese shrubland soils. ML was found to represent a sizable fraction (9-32%) of total aliphatic lipids (including
VARIABLE CHARGE SOILS: MINERALOGY AND CHEMISTRY
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van Ranst, Eric; Qafoku, Nikolla; Noble, Andrew
2016-09-19
Soils rich in particles with amphoteric surface properties in the Oxisols, Ultisols, Alfisols, Spodosols and Andisols orders (1) are considered to be variable charge soils (2) (Table 1). The term “variable charge” is used to describe organic and inorganic soil constituents with reactive surface groups whose charge varies with pH and ionic concentration and composition of the soil solution. Such groups are the surface carboxyl, phenolic and amino functional groups of organic materials in soils, and surface hydroxyl groups of Fe and Al oxides, allophane and imogolite. The hydroxyl surface groups are also present on edges of some phyllosilicate mineralsmore » such as kaolinite, mica, and hydroxyl-interlayered vermiculite. The variable charge is developed on the surface groups as a result of adsorption or desorption of ions that are constituents of the solid phase, i.e., H+, and the adsorption or desorption of solid-unlike ions that are not constituents of the solid phase. Highly weathered soils and subsoils (e.g., Oxisols and some Ultisols, Alfisols and Andisols) may undergo isoelectric weathering and reach a “zero net charge” stage during their development. They usually have a slightly acidic to acidic soil solution pH, which is close to either the point of zero net charge (PZNC) (3) or the point of zero salt effect (PZSE) (3). They are characterized by high abundances of minerals with a point of zero net proton charge (PZNPC) (3) at neutral and slightly basic pHs; the most important being Fe and Al oxides and allophane. Under acidic conditions, the surfaces of these minerals are net positively charged. In contrast, the surfaces of permanent charge phyllosilicates are negatively charged regardless of ambient conditions. Variable charge soils therefore, are heterogeneous charge systems.« less
1100 years of human impact on woodland and soils in Kjarardalur, West Iceland
NASA Astrophysics Data System (ADS)
Gísladóttir, Guðrún; Erlendsson, Egill; Lal, Rattan
2013-04-01
Prior to the Norse settlement of Iceland around AD 874 climate was the principal control of ecosystem variability. Since then, drastic changes have been imposed on the island's ecosystem through human activities. Unsustainable land use has reduced vegetation coverage, altered floral composition and accelerated soil erosion, especially in conjunction with harsh climate. Healthy ecosystem, soil and vegetation, is not only an important resource to meet human demands but also a prominent sink of atmospheric CO2. In contrast, soil erosion and land degradation are major sources of atmospheric CO2. This study discusses the impact of human activities and climate change on vegetation, soil erosion, and soil organic carbon (SOC) in West Iceland. Analyses conducted include pollen in Histosols, soil properties, soil accumulation rates and SOC in Histosols and Andosols. Our data demonstrate a pre-settlement landscape that was not entirely stable, where relatively small differences in climate may have caused subtle changes to the terrestrial environment. However, the early colonists and subsequent occupants altered the environment significantly. The magnitude of alteration was spatially variable depending on land management. The vegetation and soil data demonstrate a swift transformation of environmental conditions across AD 874. The most profound impacts include reduction in birch woodland and concurrent decline of important habitat for fragile understory, which facilitated soil exposure and reduced soil quality. After about 300 years, land degradation-anticipated management towards enhanced sustainability was probably adopted at one of the farming properties in the study area, allowing for soil recovery after a period of drastic decline. At other properties unsustainable land use continued to degrade the terrestrial ecosystem. The late-Medieval climatic change and introduction of the Little-Ice age exerted added strain on the environments over the entire area, resulting in further soil degradation. The property where sustainable land use had been adopted preserved woodland cover and maintained greater soil quality than elsewhere in the valley, where thresholds of ecosystem resilience were crossed. Unsustainable land use over 1100 years caused vegetation denudation that accelerated soil erosion, with attendant redistribution of soil over the landscape, and decline in its quality. Vegetated areas became important sinks for wind-transported soils, as evidenced by increase in deposition rate and higher bulk density. This led to an increase in susceptibility to soil erosion, and decline in SOC content. Despite decrease in SOC content, the high sedimentation rate and elevated bulk weight resulted in higher SOC sequestration at these sites, even though soil quality declined. The potential soil C sequestration in adjacent sparsely or devegetated soils were highly impaired and along with soil mass losses these areas became sources of anthropogenic CO2.
NASA Astrophysics Data System (ADS)
Stumpf, Felix; Schönbrodt-Stitt, Sarah; Schmidt, Karsten; Behrens, Thorsten; Scholten, Thomas
2013-04-01
The Three Gorges Dam at the Yangtze River in Central China outlines a prominent example of human-induced environmental impacts. Throughout one year the water table at the main river fluctuates about 30m due to impoundment and drainage activities. The dynamic water table implicates a range of georisks such as soil erosion, mass movements, sediment transport and diffuse matter inputs into the reservoir. Within the framework of the joint Sino-German project YANGTZE GEO, the subproject "Soil Erosion" deals with soil erosion risks and sediment transport pathways into the reservoir. The study site is a small catchment (4.8 km²) in Badong, approximately 100 km upstream the dam. It is characterized by scattered plots of agricultural landuse and resettlements in a largely wooded, steep sloping and mountainous area. Our research is focused on data acquisition and processing to develop a process-oriented erosion model. Hereby, area-covering knowledge of specific soil properties in the catchment is an intrinsic input parameter. This will be acquired by means of digital soil mapping (DSM). Thereby, soil properties are estimated by covariates. The functions are calibrated by soil property samples. The DSM approach is based on an appropriate sample design, which reflects the heterogeneity of the catchment, regarding the covariates with influence on the relevant soil properties. In this approach the covariates, processed by a digital terrain analysis, are outlined by the slope, altitude, profile curvature, plane curvature, and the aspect. For the development of the sample design, we chose the Conditioned Latin Hypercube Sampling (cLHS) procedure (Minasny and McBratney, 2006). It provides an efficient method of sampling variables from their multivariate distribution. Thereby, a sample size n from multiple variables is drawn such that for each variable the sample is marginally maximally stratified. The method ensures the maximal stratification by two features: First, number of strata equals the sample size n and secondly, the probability of falling in each of the strata is n-¹ (McKay et al., 1979). We extended the classical cLHS with extremes (Schmidt et al., 2012) approach by incorporating legacy data of previous field campaigns. Instead of identifying precise sample locations by CLHS, we demarcate the multivariate attribute space of the samples based on the histogram borders of each stratum. This widens the spatial scope of the actual CLHS sample locations and allows the incorporation of legacy data lying within that scope. Furthermore, this approach provides an extended potential regarding the accessibility of sample sites in the field.
Soil internal drainage: temporal stability and spatial variability in succession bean-black oat
NASA Astrophysics Data System (ADS)
Salvador, M. M. S.; Libardi, P. L.; Moreira, N. B.; Sousa, H. H. F.; Neiverth, C. A.
2012-04-01
There are a variety of studies considering the soil water content, but those who consider the flow of water, which are translated by deep drainage and capillary rise are scarce, especially those who assess their spatio-temporal variability, due to its laborious obtaining. Large areas have been considered homogeneous, but show considerable spatial variability inherent in the soil, causing the appearance of zones of distinct physical properties. In deep, sandy soils where the groundwater level is far below the root zone of interference, internal drainage is one of the factors limiting the supply of water to the soil surface, and possibly one of the biggest factors that determines what kinds satisfactory development of plants present in a given landscape. The forms of relief may also be indicators of changes in soil properties, because this variability is caused by small changes that affect the slope of the pedogenetic processes and the transport and storage of water in the soil profile, i.e., the different trajectories of water flow in different forms of the landscape, is the cause of variability. The objectives of this research were: i) evaluate the spatial and temporal stability of internal soil water drainage in a place near and another distant from the root system in a bean-black-oat succession and ii) verify their spatial variability in relation to relief. With the hydraulic conductivity obtained by the instantaneous profile method and the total potential gradient obtained from the difference in readings of tensiometers installed at depths of 0.35 and 0.45 and 0.75 and 0.85 m in 60 sampling points totaling 1680 and 1200 observations during the cultivation of beans and oats, respectively, was obtained so the internal drainage / capillary rise through the Darcy-Buckingham equation. To evaluate the temporal stability the method used was the relative difference and Spearman correlation test and the spatial variability was analyzed as geostatistical methodology. During the period when the water flow in soil is higher, there is strong temporal stability in the depth of 0.40 m, which is the opposite for the periods of drying. The lowest relative difference and standard deviation for the internal drainage obtained during the cultivation of beans and depth of 0.40 m confirm the hypothesis that the research carried out during periods of soil water recharge have less variability than those in the drying period. Temporal stability was due to the topographic position of selected points, since the points chosen for the depth of 0.40 m in both growing seasons, are located on the lower portion of the relief, and the nominees for the depth of 0,80 m, the highest portion. There were differences in the spatial pattern of water flow in the soil along the crop succession, i.e. the seasonal demand for water by plants and evaporation from the soil at the time of drying, changed their distribution model with internal drainage phases and stages capillary rise.
NASA Astrophysics Data System (ADS)
Kumar, R.; Samaniego, L. E.; Livneh, B.
2013-12-01
Knowledge of soil hydraulic properties such as porosity and saturated hydraulic conductivity is required to accurately model the dynamics of near-surface hydrological processes (e.g. evapotranspiration and root-zone soil moisture dynamics) and provide reliable estimates of regional water and energy budgets. Soil hydraulic properties are commonly derived from pedo-transfer functions using soil textural information recorded during surveys, such as the fractions of sand and clay, bulk density, and organic matter content. Typically large scale land-surface models are parameterized using a relatively coarse soil map with little or no information on parametric sub-grid variability. In this study we analyze the impact of sub-grid soil variability on simulated hydrological fluxes over the Mississippi River Basin (≈3,240,000 km2) at multiple spatio-temporal resolutions. A set of numerical experiments were conducted with the distributed mesoscale hydrologic model (mHM) using two soil datasets: (a) the Digital General Soil Map of the United States or STATSGO2 (1:250 000) and (b) the recently collated Harmonized World Soil Database based on the FAO-UNESCO Soil Map of the World (1:5 000 000). mHM was parameterized with the multi-scale regionalization technique that derives distributed soil hydraulic properties via pedo-transfer functions and regional coefficients. Within the experimental framework, the 3-hourly model simulations were conducted at four spatial resolutions ranging from 0.125° to 1°, using meteorological datasets from the NLDAS-2 project for the time period 1980-2012. Preliminary results indicate that the model was able to capture observed streamflow behavior reasonably well with both soil datasets, in the major sub-basins (i.e. the Missouri, the Upper Mississippi, the Ohio, the Red, and the Arkansas). However, the spatio-temporal patterns of simulated water fluxes and states (e.g. soil moisture, evapotranspiration) from both simulations, showed marked differences; particularly at a shorter time scale (hours to days) in regions with coarse texture sandy soils. Furthermore, the partitioning of total runoff into near-surface interflows and baseflow components was also significantly different between the two simulations. Simulations with the coarser soil map produced comparatively higher baseflows. At longer time scales (months to seasons) where climatic factors plays a major role, the integrated fluxes and states from both sets of model simulations match fairly closely, despite the apparent discrepancy in the partitioning of total runoff.
Sebastian, Derek J; Nissen, Scott J; Westra, Phil; Shaner, Dale L; Butters, Greg
2017-02-01
Kochia (Kochia scoparia L.) is a highly competitive, non-native weed found throughout the western United States. Flumioxazin and indaziflam are two broad-spectrum pre-emergence herbicides that can control kochia in a variety of crop and non-crop situations; however, under dry conditions, these herbicides sometimes fail to control this important weed. There is very little information describing the effect of soil properties and soil moisture on the efficacy of these herbicides. Soil organic matter (SOM) explained the highest proportion of variability in predicting the herbicide dose required for 80% kochia growth reduction (GR 80 ) for flumioxazin and indaziflam (R 2 = 0.72 and 0.79 respectively). SOM had a greater impact on flumioxazin phytotoxicity compared to indaziflam. Flumioxazin and indaziflam kochia phytotoxicity was greatly reduced at soil water potentials below -200 kPa. Kochia can germinate at soil moisture potentials below the moisture required for flumioxazin and indaziflam activation, which means that kochia control is greatly influenced by the complex interaction between soil physical properties and soil moisture. This research can be used to gain a better understanding of how and why some weeds, like kochia, are so difficult to manage even with herbicides that normally provide excellent control. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.
Magnetic minerals in soils across the forest-prairie ecotone in NW Minnesota
NASA Astrophysics Data System (ADS)
Maxbauer, D.; Feinberg, J. M.; Fox, D. L.; Nater, E. A.
2016-12-01
Soil pedogenesis results in a complex assemblage of iron oxide minerals that can be disentangled successfully using sensitive magnetic techniques to better delineate specific soil processes. Here, we evaluate the variability in soil processes within forest, prairie, and transitional soils along an 11 km transect of anthropogenically unaltered soils that span the forest-to-prairie ecotone in NW Minnesota. All soils in this study developed on relatively uniform topography, similar glacial till parent material, under a uniform climate, and presumably over similar time intervals. The forest-to-prairie transition zone in this region is controlled by naturally occurring fires, affording the opportunity to evaluate differences in soil processes related to vegetation (forest versus prairie) and burning (prairie and transitional soils). Results suggest that the pedeogenic fraction of magnetite/maghemite in soils is similar in all specimens and is independent of soil type, vegetation, and any effects of burning. Magnetically enhanced horizons have 45% of remanence held by a low-coercivity pedogenic component (likely magnetite/maghemite) regardless of vegetation cover and soil type. Enhancement ratios for magnetic susceptibility and low-field remanences, often used as indicators of pedogenic magnetic minerals, are more variable but remain statistically equivalent across the transect. These results support the hypothesis that pedogenic magnetic minerals in soils mostly reflect ambient climatic conditions regardless of the variability in soil processes related to vegetation and soil type. The non-pedogenic magnetic mineral assemblage shows clear distinctions between the forest, prairie, and transitional soils in hysteresis properties (remanence and coercivity ratios; Mr/Ms and Bc/Bcr, respectively), suggesting that variable processes in these settings influence the local magnetic mineral assemblage, and that it may be possible to use magnetic minerals in paleosols to constrain these processes. This work highlights the importance of isolating the magnetic behavior of pedogenic and non-pedogenic minerals in environmental magnetism studies in order to provide the most rigorous interpretation of past environmental conditions.
Impact of alpine meadow degradation on soil hydraulic properties over the Qinghai-Tibetan Plateau
NASA Astrophysics Data System (ADS)
Zeng, Chen; Zhang, Fan
2015-04-01
Alpine meadow is one of widespread vegetation types of the Qinghai-Tibetan Plateau. It is undergoing degradation under the background of global climate change, human activities and overgrazing. Soil moisture is important to alpine meadow ecology for its water and energy transfer processes, therefore soil hydraulic properties become key parameters for local eco-hydrological processes studies. However, little research focus on the changes and it's mechanisms of soil hydraulic properties during the degradation processes. In this study, soil basic and hydraulic properties at 0-10 cm and 40-50 cm soil layer depths under different degraded alpine meadow were analyzed. Pearson correlations were adopted to study the relationships among the investigated factors and principal component analysis was performed to identify the dominant factor. Results show that with increasing degree of degradation, soil sand content increased while soil saturated hydraulic conductivity (Ks) as well as soil clay content, soil porosity decreased in the 0-10 cm soil layers, and organic matter and root gravimetric density decreased in both the 0-10 cm and 40-50 cm soil layers. For soil unsaturated hydraulic conductivity, it reduced more slowly with decreasing pressure head under degraded conditions than non-degraded conditions. However, soil moisture showed no significant changes with increasing degradation. Soil Ks was significantly correlated (P = 0.01) with bulk density, soil porosity, soil organic matter and root gravimetric density. Among these, soil porosity is the dominant factor explaining about 90% of the variability in total infiltration flow. Under non-degraded conditions, the infiltration flow principally depended on the presence of macropores. With increasing degree of degradation, soil macropores quickly changed to mesopores or micropores. The proportion of total infiltration flow through macropores and mesopores significantly decreased with the most substantial decrease observed for the macropores in the 0-10 cm soil layer. The substantial decrease of macropores caused a cut in soil moisture and hydraulic conductivity.
SoilGrids1km — Global Soil Information Based on Automated Mapping
Hengl, Tomislav; de Jesus, Jorge Mendes; MacMillan, Robert A.; Batjes, Niels H.; Heuvelink, Gerard B. M.; Ribeiro, Eloi; Samuel-Rosa, Alessandro; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Gonzalez, Maria Ruiperez
2014-01-01
Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license. PMID:25171179
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2012-12-01
Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil moisture remained in contrast to the measurements very responsive to precipitation with high soil moisture after precipitation events. This behavior indicates that the soil properties might have changed due to the formation of a surface crust or seal towards the end of the growing season. Spatial soil moisture patterns were investigated using a grid resolution of 150 meter. Spatial autocorrelation was computed on a daily basis using patterns of soil texture as well as transpiration and precipitation indices as co-variables. Spatial patterns of surface soil moisture are mostly determined by the structure of the soil properties (soil type) during winter, early growing season and after harvest of all crops. Later in the growing season, after establishment of a closed canopy the dependence of the soil moisture patterns on soil texture patterns becomes smaller and diminishes quickly after precipitation events, due to differences of the transpiration rate of the different crops. When changing the spatial scale of the analysis, the highest autocorrelation values can be found on a grid cell size between 450 and 1200 meters. Thus, small scale variability of transpiration induced by the land use pattern almost averages out, leaving the larger scale structure of soil properties to explain the soil moisture patterns.
NASA Astrophysics Data System (ADS)
Looker, N. T.; Kolka, R.; Asbjornsen, H.; Munoz-Villers, L.; Colin, P. O.; Gómez Aguilar, L. R.; Ward, A. B.
2017-12-01
Soil physical properties, such as bulk density (ρb) and penetrability (P), may vary in response to anthropogenic disturbance and are relatively easy to measure. These variables are thus often used as proxies for soil characteristics that more directly govern process rates but are logistically challenging to sample in situ (e.g., hydraulic conductivity). We evaluated within- and among-site variability in the physical condition of the upper soil throughout eight first-order catchments in the volcanic landscape of central Veracruz, Mexico, through nested sampling of ρb, P, and ground cover characteristics. The study catchments spanned a land-use intensity gradient, ranging in dominant cover type from sugarcane to mature cloud forest, with pasture and coffee agroforest as intermediate cover types. Catchments were compared using data collected in forest inventory plots and at points distributed along the topographic position index. Analysis of this hierarchical dataset led to a ranking of catchments in terms of soil physical condition and, importantly, revealed the bias introduced by ignoring the within-catchment variability in response metrics. These results will help optimize soil sampling effort in landscapes with complex topography and land-use/cover distributions.
NASA Astrophysics Data System (ADS)
Quijano, Laura; Chaparro, Marcos A. E.; Marié, Débora C.; Gaspar, Leticia; Navas, Ana
2014-09-01
The main sources of magnetic minerals in soils unaffected by anthropogenic pollution are iron oxides and hydroxides derived from parent materials through soil formation processes. Soil magnetic minerals can be used as indicators of environmental factors including soil forming processes, degree of pedogenesis, weathering processes and biological activities. In this study measurements of magnetic susceptibility are used to detect the presence and the concentration of soil magnetic minerals in topsoil and bulk samples in a small cultivated field, which forms a hydrological unit that can be considered to be representative of the rainfed agroecosystems of Mediterranean mountain environments. Additional magnetic studies such as isothermal remanent magnetization (IRM), anhysteretic remanent magnetization (ARM) and thermomagnetic measurements are used to identify and characterize the magnetic mineralogy of soil minerals. The objectives were to analyse the spatial variability of the magnetic parameters to assess whether topographic factors, soil redistribution processes, and soil properties such as soil texture, organic matter and carbonate contents analysed in this study, are related to the spatial distribution pattern of magnetic properties. The medians of mass specific magnetic susceptibility at low frequency (χlf) were 36.0 and 31.1 × 10-8 m3 kg-1 in bulk and topsoil samples respectively. High correlation coefficients were found between the χlf in topsoil and bulk core samples (r = 0.951, p < 0.01). In addition, volumetric magnetic susceptibility was measured in situ in the field (κis) and values varied from 13.3 to 64.0 × 10-5 SI. High correlation coefficients were found between χlf in topsoil measured in the laboratory and volumetric magnetic susceptibility field measurements (r = 0.894, p < 0.01). The results obtained from magnetic studies such as IRM, ARM and thermomagnetic measurements show the presence of magnetite, which is the predominant magnetic carrier, and hematite. The predominance of superparamagnetic minerals in upper soil layers suggests enrichment in pedogenic minerals. The finer soil particles, the organic matter content and the magnetic susceptibility values are statistically correlated and their spatial variability is related to similar physical processes. Runoff redistributes soil components including magnetic minerals and exports fine particles out the field. This research contributed to further knowledge on the application of soil magnetic properties to derive useful information on soil processes in Mediterranean cultivated soils.
NASA Astrophysics Data System (ADS)
Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.
2016-05-01
Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.
Influence of tillage in soil penetration resistance variability in an olive orchard
NASA Astrophysics Data System (ADS)
López de Herrera, Juan; Herrero Tejedor, Tomas; Saa-Requejo, Antonio; Tarquis, Ana M.
2015-04-01
Soil attributes usually present a high degree of spatial variation due to a combination of physical, chemical, biological or climatic processes operating at different scales. The quantification and interpretation of such variability is a key issue for site-specific soil management (Brouder et al., 2001). The usual geostatistical approach studies soil variability by means of the semi-variograms. However, recently a multiscaling approach has been applied on the determination of the scaling data properties (Kravechenko et al., 1999; Caniego et al., 2005; Tarquis et al., 2008). This work focus in the multifractal analysis as a way to characterize the variability of field data in a case study of soil penetrometer resistance (SPR) in two olive orchards, one applying tillage for 20 years and the other one non. The field measurements and soil data were obtained at the village of Puebla de Almenara (Cuenca, Spain) (39o 47'42.37'N, 2o 49'29.23'W) with 869 m of elevation approximately. The characteristic of the soil at the surface is classified as clay loam texture according to Guidelines for soil description of FAO. The soil consists of clays and red silts with some clusters of limestone's and sands. Two transect data were collected from 128 points between the squared of the olive tree, tillage and no tillage area, for SPR readings with a sampling interval of 50 cm. In each sampling, readings were obtained from 0 cm till 20 cm of depth, with an interval of 5 cm. The multifractal spectrum for each area and depth was estimated showing a characteristic pattern and differentiating both treatments. References Brouder, S., Hofmann, B., Reetz, H.F., 2001. Evaluating spatial variability of soil parameters for input management. Better Crops 85, 8-11. Kravchenko, A.N., Boast, C.W., Bullock, D.G., 1999. Multifractal analysis of soil spatial variability. Agron. J. 91, 1033-1041. Caniego, F.J., R. Espejo, M.A. Martín, F. San José, 2005. Multifractal scaling of soil spatial variability. Ecological Modelling, 182, 291-303. Tarquis, A.M., N. Bird, M.C. Cartagena, A. Whitmore and Y. Pachepsky, 2008. Multiscale entropy-based analyses of soil transect data. Vadose Zone Journal, 7(2), 563-569.
Evaluation of Deterministic Models for Near Surface Soil Moisture Prediction
1988-05-01
soil hydrological properties (max of 3) ’ . 30. mean length of segment (hWen) 31. cmax of each layer ( cmax I (k,j), k= kno, j=1,jno) 32. porosity of...kelvin Variable name: tac Subroutines: ’bevapor’ Description: air temperature in celsius • * Variable name: tak Subroutines: ’bevapor’ Description: air...3 C - 1 *’ C GET-TABLE-VALUES assign 9865 to i9930 goto 9930 9865 cloud-yn takc-ta tac-( tak -273.15) ea-6. 108*rh*exp( (ac*tac)/ ( tak -bc)) alphi
Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils
NASA Technical Reports Server (NTRS)
Eagleson, Peter S.; Jasinski, Michael F.
1988-01-01
This work focuses on the characterization of natural, spatially variable, semivegetated landscapes using a linear, stochastic, canopy-soil reflectance model. A first application of the model was the investigation of the effects of subpixel and regional variability of scenes on the shape and structure of red-infrared scattergrams. Additionally, the model was used to investigate the inverse problem, the estimation of subpixel vegetation cover, given only the scattergrams of simulated satellite scale multispectral scenes. The major aspects of that work, including recent field investigations, are summarized.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van Looy, Kris; Bouma, Johan; Herbst, Michael
Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less
Van Looy, Kris; Bouma, Johan; Herbst, Michael; ...
2017-12-28
Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less
Spatial and temporal variability of soil moisture on the field with and without plants*
NASA Astrophysics Data System (ADS)
Usowicz, B.; Marczewski, W.; Usowicz, J. B.
2012-04-01
Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil moisture runs in particular objects and of precipitation distribution shows clearly that rainfall has an effect on the soil moisture. The amount of precipitation water that increased the soil moisture depended on the strength of the rainfall, on the hydrological properties of the soil (primarily the soil density), the status of the plant cover, and surface runoff. Basing on the precipitation distribution and on the soil moisture runs, an attempt was made at finding a temporal and spatial relationship between those variables, employing for the purpose the geostatistical methods which permit time and space to be included in the analysis. The geostatistical parameters determined showed the temporal dependence of moisture distribution in the soil profile, with the autocorrelation radius increasing with increasing depth in the profile. The highest values of the radius were observed in the plots with plant cover below the arable horizon, and the lowest in the arable horizon on the barley and fallow plots. The fractal dimensions showed a clear decrease in values with increasing depth in the plots with plant cover, while in the bare plots they were relatively constant within the soil profile under study. Therefore, they indicated that the temporal distribution of soil moisture within the soil profile in the bare field was more random in character than in the plots with plants. The results obtained and the analyses indicate that the moisture in the soil profile, its variability and determination, are significantly affected by the type and condition of plant canopy. The differentiation in moisture content between the plots studied resulted from different precipitation interception and different intensity of water uptake by the roots. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO-3275.
Cone-penetrometer exploration of sinkholes: Stratigraphy and soil properties
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bloomberg, D.; Upchurch, S.B.; Hayden, M.L.
1988-10-01
Four sinkholes with varying surficial expressions were subjected to detailed stratigraphic and soil analysis by means of Standard Penetration Tests (SPT) and Electric Friction Cone Penetration Tests (CPT) in order to evaluate applications of CPT to sinkhole investigations. Although widely used, SPT data are of limited value and difficult to apply to sinkhole mapping. CPT is sensitive to minor lithologic variability and is superior to SPT as a cost-effective technique for determining geotechnical properties of sinkholes. The effectiveness of CPT data results from the force measurements made along the sleeve of the cone. The friction ratio (ratio of sleeve tomore » tip resistance) is a good indicator of soil stratigraphy and properties. By smoothing the friction-ratio data, general stratigraphy and changes in soil properties are easily identified. Stratigraphy of the sinks has been complicated by intense weathering, karstification and marine transgressions. The resulting deposits include five stratigraphic units. 1 and 2 represent Plio-Pleistocene marine sediments with Unit 2 being the zone of soil clay accumulation. 3 and 4 are horizons residual from Miocene strata and indicate an episode of karstification prior to deposition of Units 1 and 2. CPT provides sufficient information for recognition of sinkhole stratigraphy and geotechnical properties. When coupled with laboratory soil analysis, CPT provides unique information about sinkhole geometry and dynamics. In contrast, SPT indicates general, inconclusive trends.« less
Flinn, Kathryn M; Marks, P L
2007-03-01
Temperate deciduous forests across much of Europe and eastern North America reflect legacies of past land use, particularly in the diversity and composition of plant communities. Intense disturbances, such as clearing forests for agriculture, may cause persistent environmental changes that continue to shape vegetation patterns as landscapes recover. We assessed the long-term consequences of agriculture for environmental conditions in central New York forests, including tree community structure and composition, soil physical and chemical properties, and light availability. To isolate the effects of agriculture, we compared 20 adjacent pairs of forests that were never cleared for agriculture (primary forests) and forests that established 85-100 years ago on plowed fields (secondary forests). Tree communities in primary and secondary forests had similar stem density, though secondary forests had 14% greater basal area. Species composition differed dramatically between the two forest types, with primary forests dominated by Acer saccharum and Fagus grandifolia and secondary forests by Acer rubrum and Pinus strobus. Primary and secondary forests showed no consistent differences in soil physical properties or in the principal gradient of soil fertility associated with soil pH. Within stands, however, soil water content and pH were more variable in primary forests. Secondary forest soils had 15% less organic matter, 16% less total carbon, and 29% less extractable phosphorus in the top 10 cm than adjacent primary stands, though the ranges of the forest types mostly overlapped. Understory light availability in primary and secondary forests was similar. These results suggest that, within 100 years, post-agricultural stands have recovered conditions comparable to less disturbed forests in many attributes, including tree size and number, soil physical properties, soil chemical properties associated with pH, and understory light availability. The principal legacies of agriculture that remain in these forests are the reduced levels of soil organic matter, carbon, and phosphorus; the spatial homogenization of soil properties; and the altered species composition of the vegetation.
Edaphic controls on soil organic carbon stocks in restored grasslands
DOE Office of Scientific and Technical Information (OSTI.GOV)
O'Brien, Sarah L.; Jastrow, Julie D.; Grimley, David A.
Cultivation of undisturbed soils dramatically depletes organic carbon stocks at shallow depths, releasing a substantial quantity of stored carbon to the atmosphere. Restoration of native ecosystems can help degraded soils rebuild a portion of the depleted soil organic matter. However, the rate and magnitude of soil carbon accrual can be highly variable from site to site. Thus, a better understanding of the mechanisms controlling soil organic carbon stocks is necessary to improve predictions of soil carbon recovery. We measured soil organic carbon stocks and a suite of edaphic factors in the upper 10 cm of a series of restored tallgrassmore » prairies representing a range of drainage conditions. Our findings suggest that factors related to soil organic matter stabilization mechanisms (texture, polyvalent cations) were key predictors of soil organic carbon, along with variables that influence plant and microbial biomass (available phosphorus, pH) and soil moisture. Exchangeable soil calcium was the strongest single predictor, explaining 74% of the variation in soil organic carbon, followed by clay content,which explained 52% of the variation. Our results demonstrate that the cumulative effects of even relatively small differences in these edaphic properties can have a large impact on soil carbon stocks when integrated over several decades.« less
NASA Astrophysics Data System (ADS)
Marzouk, E. R.; Chenery, S. R.; Young, S. D.
2013-12-01
The Rookhope catchment of Weardale, England, has a diverse legacy of contaminated soils due to extensive lead mining activity over four centuries. We measured the isotopically exchangeable content of Pb, Cd and Zn (E-values) in a large representative subset of the catchment soils (n = 246) using stable isotope dilution. All three metals displayed a wide range of %E-values (c. 1-100%) but relative lability followed the sequence Cd > Pb > Zn. A refinement of the stable isotope dilution approach also enabled detection of non-reactive metal contained within suspended sub-micron (<0.22 μm) colloidal particles (SCP-metal). For most soils, the presence of non-labile SCP-metal caused only minor over-estimation of E-values (<2%) but the effect was greater for soils with particularly large humus or carbonate contents. Approximately 80%, 53% and 66% of the variability in Zn, Cd and Pb %E-values (respectively) could be explained by pH, loss on ignition and total metal content. E-values were affected by the presence of ore minerals at high metal contents leading to an inconsistent trend in the relationship between %E-value and soil metal concentration. Metal solubility, in the soil suspensions used to measure E-values, was predicted using the WHAM geochemical speciation model (versions VI and VII). The use of total and isotopically exchangeable metal as alternative input variables was compared; the latter provided significantly better predictions of solubility, especially in the case of Zn. Lead solubility was less well predicted by either version of WHAM, with over-prediction at low pH and under-prediction at high soil pH values. Quantify the isotopically exchangeable fractions of Zn, Cd and Pb (E-values), and assess their local and regional variability, using multi-element stable isotope dilution, in a diverse range of soil ecosystems within the catchment of an old Pb/Zn mining area. Assess the controlling influences of soil properties on metal lability and develop predictive algorithms for metal lability in the contaminated catchment based on simple soil properties (such as pH, organic matter (LOI), and total metal content). Examine the incidence of non-isotopically-exchangeable metal held within suspended colloidal particles (SCP-metal) in filtered soil solutions (<0.22 μm) by comparing E-values from isotopic abundance in solutions equilibrated with soil and in a resin phase equilibrated with the separated solution. Assess the ability of a geochemical speciation model, WHAM(VII), to predict metal solubility using isotopically exchangeable metal as an input variable.
NASA Astrophysics Data System (ADS)
DeLonge, M. S.; Basche, A.; Gonzalez, J.
2016-12-01
Due to the vast extent of grazing lands, value of grassland ecosystems, and environmental impacts of the agricultural sector, it is becoming increasingly important to understand to what extent managed grazing can be part of healthy agroecosystems. For example, grazing systems can degrade soils, pollute water, and result in substantial direct and indirect animal emissions. On the other hand, well-managed grasslands can store more carbon, support more biodiversity, and require fewer inputs than croplands or other land uses. Systems analyses are needed to evaluate how much grazing management (e.g., altering stocking rate intensity or regime, integrating versus separating crops and livestock, adopting silvopasture techniques) can affect agroecosystem properties and farm viability. As a result of climate change and likely increases to rainfall variability, the effects of grazing systems on soil water properties are particularly important. The primary goal of this study is to use meta-analytic techniques to better understand how changes to grazing systems affect soil water properties, focusing on soil water infiltration rates. Another goal is to conduct a literature survey to assess how similar changes to grazing have influenced other ecosystem services (e.g., soil carbon, farm profitability) and to identify gaps in knowledge. To date, our meta-analysis includes over 100 paired comparisons (>30 studies) related to grazing. The analysis is a subset of a broader study of agroecological practices that to date includes >350 paired observations. Preliminary results point to significant variability, but suggest that integrating livestock into croplands decreases infiltration (12%), whereas other changings to grazing (decreasing stocking rates, moving from continuous to rotational grazing, or converting to a silvopasture system) can improve infiltration (by an average of 223% including all practices). Findings also suggest that removing livestock tends to increase infiltration rates over time. In cases where infiltration rates are negatively affected by grazing, soil conservation practices such as planting perennials or rotating crops) might mitigate those effects. However, the magnitude of these effects may depend on variables such as time since management change and rainfall regime.
NASA Technical Reports Server (NTRS)
Mitchell, J. K.; Carrier, W. D., III; Houston, W. N.; Scott, R. F.; Bromwell, L. G.; Durgunoglu, H. T.; Hovland, H. J.; Treadwell, D. D.; Costes, N. C.
1972-01-01
Preliminary results are presented of an investigation of the physical and mechanical properties of lunar soil on the Descartes slopes, and the Cayley Plains in the vicinity of the LM for Apollo 16. The soil mechanics data were derived form (1) crew commentary and debriefings, (2) television, (3) lunar surface photography, (4) performance data and observations of interactions between soil and lunar roving vehicle, (5) drive-tube and deep drill samples, (6) sample characteristics, and (7) measurements using the SRP. The general characteristics, stratigraphy and variability are described along with the core samples, penetrometer test results, density, porosity and strength.
NASA Astrophysics Data System (ADS)
De Baets, S. L.; Meersmans, J.; Vanacker, V.; Quine, T. A.; van oost, K.
2013-12-01
This research focuses on understanding the impact of human activities on C dynamics in a mountainous and semi-arid environment. Despite the low C status of drylands, soil organic carbon (SOC) is the largest C pool in these systems and hence possess a large restoration capacity. Still, regional estimates of SOC stocks and insights in their determining factors are lacking. This study therefore aims 1) to interpret the variability of soil organic carbon in relation to key soil, topographical and land use variables and 2) to quantify the effects of land regeneration following abandonment on SOC stocks. Soil profiles were taken in the Sierra de los Filabres (SE Spain) in different land units along geomorphic and degradation gradients. SOC contents were modelled using recovery period, soil and topographical variables. Sample depth, topographical position, altitude, recovery period and stone content are identified as the main factors for predicting SOC concentrations. SOC stocks in 1 m depth of soil vary between 3.16 and 76.44 t ha-1. Recovery period (years since abandonment), topographical position and altitude were used to predict and map SOC stocks in the top 0.2 m. The results show that C accumulates fast during the first 10-50 years following abandonment, whereafter the stocks evolve towards a steady state level. The erosion zones in the study area demonstrate a higher potential to increase their SOC stocks when abandoned. Deposition zones have higher SOC stocks, although their C accumulation rate is lower compared to erosion dominated landscapes in the first 10-50 years following abandonment. Therefore, full understanding of the C sequestration potential of land use change in areas of complex topography requires knowledge of spatial variability in soil properties and in particular SOC.
An annual model of SSM/I radiobrightness for dry soil
NASA Technical Reports Server (NTRS)
Liou, Yuei-An; England, A. W.
1992-01-01
An annual model is presented of the temperature structure within a homogeneous, dry soil halfspace that is subject to both diurnal and annual insolation, radiant heating from the atmosphere, sensible heat exchange with the atmosphere, and radiant cooling. The thermal constitutive properties of the soil are assumed to be constant so that the heat flow equation can be solved analytically. For computational economy, a variable time interval Laplace transform method is developed to predict the temperature.
NASA Astrophysics Data System (ADS)
De Caires, Sunshine A.; Wuddivira, Mark N.; Bekele, Isaac
2014-10-01
Cocoa remains in the same field for decades, resulting in plantations dominated with aging trees growing on variable and depleted soils. We determined the spatio-temporal variability of key soil properties in a (5.81 ha) field from the International Cocoa Genebank, Trinidad using geophysical methods. Multi-year (2008-2009) measurements of apparent electrical conductivity at 0-0.75 m (shallow) and 0.75-1.5 m (deep) were conducted. Apparent electrical conductivity at deep and shallow gave the strongest linear correlation with clay-silt content (R = 0.67 and R = 0.78, respectively) and soil solution electrical conductivity (R = 0.76 and R = 0.60, respectively). Spearman rank correlation coefficients ranged between 0.89-0.97 and 0.81- 0.95 for apparent electrical conductivity at deep and shallow, respectively, signifying a strong linear dependence between measurement days. Thus, in the humid tropics, cocoa fields with thick organic litter layer and relatively dense understory cover, experience minimal fluctuations in transient properties of soil water and temperature at the topsoil resulting in similarly stable apparent electrical conductivity at shallow and deep. Therefore, apparent electrical conductivity at shallow, which covers the depth where cocoa feeder roots concentrate, can be used as a fertility indicator and to develop soil zones for efficient application of inputs and management of cocoa fields.
Spatial Variability and Stocks of Soil Organic Carbon in the Gobi Desert of Northwestern China
Zhang, Pingping; Shao, Ming'an
2014-01-01
Soil organic carbon (SOC) plays an important role in improving soil properties and the C global cycle. Limited attention, though, has been given to assessing the spatial patterns and stocks of SOC in desert ecosystems. In this study, we quantitatively evaluated the spatial variability of SOC and its influencing factors and estimated SOC storage in a region (40 km2) of the Gobi desert. SOC exhibited a log-normal depth distribution with means of 1.6, 1.5, 1.4, and 1.4 g kg−1 for the 0–10, 10–20, 20–30, and 30–40 cm layers, respectively, and was moderately variable according to the coefficients of variation (37–42%). Variability of SOC increased as the sampling area expanded and could be well parameterized as a power function of the sampling area. Significant correlations were detected between SOC and soil physical properties, i.e. stone, sand, silt, and clay contents and soil bulk density. The relatively coarse fractions, i.e. sand, silt, and stone contents, had the largest effects on SOC variability. Experimental semivariograms of SOC were best fitted by exponential models. Nugget-to-sill ratios indicated a strong spatial dependence for SOC concentrations at all depths in the study area. The surface layer (0–10 cm) had the largest spatial dependency compared with the other layers. The mapping revealed a decreasing trend of SOC concentrations from south to north across this region of the Gobi desert, with higher levels close to an oasis and lower levels surrounded by mountains and near the desert. SOC density to depths of 20 and 40 cm for this 40 km2 area was estimated at 0.42 and 0.68 kg C m−2, respectively. This study provides an important contribution to understanding the role of the Gobi desert in the global carbon cycle. PMID:24733073
NASA Astrophysics Data System (ADS)
Carles Brangarí, Albert; Sanchez-Vila, Xavier; Freixa, Anna; Romaní, Anna M.; Fernàndez-Garcia, Daniel
2017-04-01
The distribution, amount, and characteristics of biofilms and its components govern the capacity of soils to let water through, to transport solutes, and the reactions occurring. Therefore, unraveling the relationship between microbial dynamics and the hydraulic properties of soils is of concern for the management of natural systems and many technological applications. However, the increased complexity of both the microbial communities and the geochemical processes entailed by them causes that the phenomenon of bioclogging remains poorly understood. This highlights the need for a better understanding of the microbial components such as live and dead bacteria and extracellular polymeric substances (EPS), as well as of their spatial distribution. This work tries to shed some light on these issues, providing experimental data and a new mechanistic model that predicts the variably saturated hydraulic properties of bio-amended soils based on these data. We first present a long-term laboratory infiltration experiment that aims at studying the temporal variation of selected biogeochemical parameters along the infiltration path. The setup consists of a 120-cm-high soil tank instrumented with an array of sensors plus soil and liquid samplers. Sensors measured a wide range of parameters in continuous, such as volumetric water content, electrical conductivity, temperature, water pressure, soil suction, dissolved oxygen, and pH. Samples were kept for chemical and biological analyses. Results indicate that: i) biofilm is present at all depths, denoting the potential for deep bioclogging, ii) the redox conditions profile shows different stages, indicating that the community was adapted to changing redox conditions, iii) bacterial activity, richness and diversity also exhibit zonation with depth, and iv) the hydraulic properties of the soil experienced significant changes as biofilm proliferated. Based on experimental evidences, we propose a tool to predict changes in the hydraulic properties of bio-amended variably saturated soils. The new mechanistic model provides analytical equations for the water retention curve and the relative permeability. The approach consists in assuming that the porous media behaves as an ensemble of capillary tubes, which may be obtained from the experimental saturation profile. This premise is extended by considering the existence of biofilm bodies composed of bacteria and EPS. These compounds display a channeled geometry that reshapes the pore space at the pore-scale following specific geometrical patterns and changes its volume with suction. The hydraulic properties of the bio-amended soil can then be derived from the integrate contribution of the two biofilm compounds separately. Model can successfully reproduce displacements of the soil-water retention curve towards higher saturations and permeability reductions of distinct orders of magnitude.
Variability in soil CO2 efflux across distinct urban land cover types
NASA Astrophysics Data System (ADS)
Weissert, Lena F.; Salmond, Jennifer A.; Schwendenmann, Luitgard
2015-04-01
As a main source of greenhouse gases urban areas play an important role in the global carbon cycle. To assess the potential role of urban vegetation in mitigating carbon emissions we need information on the magnitude of biogenic CO2 emissions and its driving factors. We examined how urban land use types (urban forest, parklands, sportsfields) vary in their soil CO2 efflux. We measured soil CO2 efflux and its isotopic signature, soil temperature and soil moisture over a complete growing season in Auckland, New Zealand. Soil physical and chemical properties and vegetation characteristics were also measured. Mean soil CO2 efflux ranged from 4.15 to 12 μmol m-2 s-1. We did not find significant differences in soil CO2 efflux among land cover types due to high spatial variability in soil CO2 efflux among plots. Soil (soil carbon and nitrogen density, texture, soil carbon:nitrogen ratio) and vegetation characteristics (basal area, litter carbon density, grass biomass) were not significantly correlated with soil CO2 efflux. We found a distinct seasonal pattern with significantly higher soil CO2 efflux in autumn (Apr/May) and spring (Oct). In urban forests and sportsfields over 80% of the temporal variation was explained by soil temperature and soil water content. The δ13C signature of CO2 respired from parklands and sportsfields (-20 permil - -25 permil) were more positive compared to forest plots (-29 permil) indicating that parkland and sportsfields had a considerable proportion of C4 grasses. Despite the large intra-urban variability, our results compare to values reported from other, often climatically different cities, supporting the hypothesis of homogenization across urban areas as a result of human management practices.
On the distribution of scaling hydraulic parameters in a spatially anisotropic banana field
NASA Astrophysics Data System (ADS)
Regalado, Carlos M.
2005-06-01
When modeling soil hydraulic properties at field scale it is desirable to approximate the variability in a given area by means of some scaling transformations which relate spatially variable local hydraulic properties to global reference characteristics. Seventy soil cores were sampled within a drip irrigated banana plantation greenhouse on a 14×5 array of 2.5 m×5 m rectangles at 15 cm depth, to represent the field scale variability of flow related properties. Saturated hydraulic conductivity and water retention characteristics were measured in these 70 soil cores. van Genuchten water retention curves (WRC) with optimized m ( m≠1-1/ n) were fitted to the WR data and a general Mualem-van Genuchten model was used to predict hydraulic conductivity functions for each soil core. A scaling law, of the form ν=ανi*, was fitted to soil hydraulic data, such that the original hydraulic parameters νi were scaled down to a reference curve with parameters νi*. An analytical expression, in terms of Beta functions, for the average suction value, hc, necessary to apply the above scaling method, was obtained. A robust optimization procedure with fast convergence to the global minimum is used to find the optimum hc, such that dispersion is minimized in the scaled data set. Via the Box-Cox transformation P(τ)=(αiτ-1)/τ, Box-Cox normality plots showed that scaling factors for the suction ( αh) and hydraulic conductivity ( αk) were approximately log-normally distributed (i.e. τ=0), as it would be expected for such dynamic properties involving flow. By contrast static soil related properties as αθ were found closely Gaussian, although a power τ=3/4 was best for approaching normality. Application of four different normality tests (Anderson-Darling, Shapiro-Wilk, Kolmogorov-Smirnov and χ2 goodness-of-fit tests) rendered some contradictory results among them, thus suggesting that this widely extended practice is not recommended for providing a suitable probability density function for the scaling parameters, αi. Some indications for the origin of these disagreements, in terms of population size and test constraints, are pointed out. Visual inspection of normal probability plots can also lead to erroneous results. The scaling parameters αθ and αK show a sinusoidal spatial variation coincident with the underlying alignment of banana plants on the field. Such anisotropic distribution is explained in terms of porosity variations due to processes promoting soil degradation as surface desiccation and soil compaction, induced by tillage and localized irrigation of banana plants, and it is quantified by means of cross-correlograms.
Zampella, Mariavittoria; Adamo, Paola
2010-01-01
A study on variable charge soils (volcanic Italian and podzolic Scottish soils) was performed to investigate the influence of soil properties on the chemical composition of soil solution. Zinc speciation, bioavailability and toxicity in the soil solution were examined. The soils were spiked with increasing amounts of Zn (0, 100, 200, 400 and 1000 mg/kg) and the soil solutions were extracted using rhizon soil moisture samplers. The pH, total organic carbon (TOC), base cations, anions, total Zn and free Zn2+ in soil solution were analysed. A rapid bioassay with the luminescent bacterium Escherichia coli HB101 pUCD607 was performed to assess Zn toxicity. The influence of soil type and Zn treatments on the chemical composition of soil solution and on Zn toxicity was considered and discussed. Different trends of total and free Zn concentrations, base cations desorption and luminescence of E. coli HB101 pUCD607 were observed. The soil solution extracted from the volcanic soils had very low total and free Zn concentrations and showed specific Zn2+/Ca2+ exchange. The soil solution from the podzolic soil had much higher total and free Zn concentrations and showed no evidence of specific Zn2+/Ca2+ exchange. In comparison with the subalkaline volcanic soils, the acidic podzol showed enhanced levels of toxic free Zn2+ and consequently stronger effects on E. coli viability.
Integration of Hydrogeophysical Datasets for Improved Water Resource Management in Irrigated Systems
NASA Astrophysics Data System (ADS)
Finkenbiner, C. E.; Franz, T. E.; Heeren, D.; Gibson, J. P.; Russell, M. V.
2016-12-01
With an average irrigation water use efficiency of approximately 45% in the United States, improvements in water management can be made within agricultural systems. Advancements in precision irrigation technologies allow application rates and times to vary within a field. Current limitations in applying these technologies are often attributed to the quantification of soil spatial variability. This work aims to increase our understanding of soil hydrologic fluxes at intermediate spatial scales. Field capacity and wilting point values for a field near Sutherland, NE were downloaded from the USDA SSURGO database. Stationary and roving cosmic-ray neutron probes (CRNP) (sensor measurement volume of 300 m radius sphere and 30 cm vertical soil depth) were combined in order to characterize the spatial and temporal patterns of soil moisture at the site. We used a data merging technique to produce a statistical daily soil moisture product at a range of key spatial scales in support of current irrigation technologies: the individual sprinkler ( 102 m2) for variable rate irrigation, the individual wedge ( 103 m2) for variable speed irrigation, and the quarter section (0.82 km2) for uniform rate irrigation. The results show our CRNP "observed" field capacity was higher compared to the SSURGO products. The measured hydraulic properties from sixty-two soil cores collected from the field correlate well with our "observed" CRNP values. We hypothesize that our results, when provided to irrigators, will decrease water losses due to runoff and deep percolation as sprinkler managers can better estimate irrigation application depths and times in relation to soil moisture depletion below field capacity and above maximum allowable depletion. The incorporation of the CRNP into current irrigation practices has the potential to greatly increase agricultural water use efficiency. Moreover, the defined soil hydraulic properties at various spatial scales offers additional valuable datasets for the land surface modeling community.
NASA Astrophysics Data System (ADS)
Qu, W.; Bogena, H. R.; Huisman, J. A.; Martinez, G.; Pachepsky, Y. A.; Vereecken, H.
2013-12-01
Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and temporal stability presents substantial interest. The objective of this work was to assess the effect of soil hydraulic parameters on the temporal stability. The inverse modeling based on large observed time series SWC with in-situ sensor network was used to estimate the van Genuchten-Mualem (VGM) soil hydraulic parameters in a small grassland catchment located in western Germany. For the inverse modeling, the shuffled complex evaluation (SCE) optimization algorithm was coupled with the HYDRUS 1D code. We considered two cases: without and with prior information about the correlation between VGM parameters. The temporal stability of observed SWC was well pronounced at all observation depths. Both the spatial variability of SWC and the robustness of temporal stability increased with depth. Calibrated models both with and without prior information provided reasonable correspondence between simulated and measured time series of SWC. Furthermore, we found a linear relationship between the mean relative difference (MRD) of SWC and the saturated SWC (θs). Also, the logarithm of saturated hydraulic conductivity (Ks), the VGM parameter n and logarithm of α were strongly correlated with the MRD of saturation degree for the prior information case, but no correlation was found for the non-prior information case except at the 50cm depth. Based on these results we propose that establishing relationships between temporal stability and spatial variability of soil properties presents a promising research avenue for a better understanding of the controls on soil moisture variability. Correlation between Mean Relative Difference of soil water content (or saturation degree) and inversely estimated soil hydraulic parameters (log10(Ks), log10(α), n, and θs) at 5-cm, 20-cm and 50-cm depths. Solid circles represent parameters estimated by using prior information; open circles represent parameters estimated without using prior information.
Soil fertility and plant diversity enhance microbial performance in metal-polluted soils.
Stefanowicz, Anna M; Kapusta, Paweł; Szarek-Łukaszewska, Grażyna; Grodzińska, Krystyna; Niklińska, Maria; Vogt, Rolf D
2012-11-15
This study examined the effects of soil physicochemical properties (including heavy metal pollution) and vegetation parameters on soil basal respiration, microbial biomass, and the activity and functional richness of culturable soil bacteria and fungi. In a zinc and lead mining area (S Poland), 49 sites were selected to represent all common plant communities and comprise the area's diverse soil types. Numerous variables describing habitat properties were reduced by PCA to 7 independent factors, mainly representing subsoil type (metal-rich mining waste vs. sand), soil fertility (exchangeable Ca, Mg and K, total C and N, organic C), plant species richness, phosphorus content, water-soluble heavy metals (Zn, Cd and Pb), clay content and plant functional diversity (based on graminoids, legumes and non-leguminous forbs). Multiple regression analysis including these factors explained much of the variation in most microbial parameters; in the case of microbial respiration and biomass, it was 86% and 71%, respectively. The activity of soil microbes was positively affected mainly by soil fertility and, apparently, by the presence of mining waste in the subsoil. The mining waste contained vast amounts of trace metals (total Zn, Cd and Pb), but it promoted microbial performance due to its inherently high content of macronutrients (total Ca, Mg, K and C). Plant species richness had a relatively strong positive effect on all microbial parameters, except for the fungal component. In contrast, plant functional diversity was practically negligible in its effect on microbes. Other explanatory variables had only a minor positive effect (clay content) or no significant influence (phosphorus content) on microbial communities. The main conclusion from this study is that high nutrient availability and plant species richness positively affected the soil microbes and that this apparently counteracted the toxic effects of metal contamination. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Mikheeva, Irina
2017-04-01
Identification of tendencies of soil's transformations is very important for adequate ecological and economical assessment of degradation of soils. But monitoring of conditions of soils, and other natural objects, bring up a number of important methodological questions, including the probabilistic and statistical analysis of the accumulated legacy data and their use for verification of quantitative estimates of natural processes. Owing to considerable natural variability there is a problem of a reliable assessment of contemporary soil evolution under the influence of environmental management and climate changes. When studying dynamics of soil quality it is necessary to consider soil as open complex system with parameters which significantly vary in space. The analysis of probabilistic distributions of attributes of studied system is informative for the characteristic of holistic state and behavior of the system. Therefore earlier we had offered the method of evaluation of alterations of soils by analysis of changes of pdf of their properties and their statistical entropy. The executed analysis of dynamics of pdf showed that often opposite tendencies to decrease and to increase of property can be shown at the same time. However to give an adequate quantitative evaluation of changes of soil properties it is necessary to characterize them in general. We proposed that it is reasonable to name processes of modern changes in soil properties concerning their start meaning by the term "divergence" and investigate it quantitatively. For this purpose we suggested to use value of information divergence which is defined as a measure of distinctions of pdf in compared objects or in various time. As the measure of dissimilarity, divergence should satisfy come conditions, the most important is scale-invariance property. Information divergence was used by us for evaluation of distinctions of soils according heterogeneity of factors of soil formation and with course of natural and anthropogenous processes. This characteristic allowed to allocate the most changed and vulnerable kinds and layers of soils, and also to range natural changes and anthropogenous impacts in size of their influence on properties of the soil. Case study was conducted on considerable part of the Priirtyshskaya plain in South of Western Siberia. Climate here is sharply continental and droughty. Soils were formed from ancient lake and alluvial deposits. It determined their mainly easy particle size distribution and spatial diversity of the texture. It is possible to judge rates and extent of manifestation of processes of degradation on alteration of properties of the main types of soils here: chestnut soils and Haplic Chernozems.
NASA Astrophysics Data System (ADS)
Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry
2017-07-01
Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.
NASA Astrophysics Data System (ADS)
Oktem, R.; Wainwright, H. M.; Curtis, J. B.; Dafflon, B.; Peterson, J.; Ulrich, C.; Hubbard, S. S.; Torn, M. S.
2016-12-01
Predicting carbon cycling in Arctic requires quantifying tightly coupled surface and subsurface processes including permafrost, hydrology, vegetation and soil biogeochemistry. The challenge has been a lack of means to remotely sense key ecosystem properties in high resolution and over large areas. A particular challenge has been characterizing soil properties that are known to be highly heterogeneous. In this study, we exploit tightly-coupled above/belowground ecosystem functioning (e.g., the correlations among soil moisture, vegetation and carbon fluxes) to estimate subsurface and other key properties over large areas. To test this concept, we have installed a ground-based remote sensing platform - a track-mounted tram system - along a 70 m transect in the ice-wedge polygonal tundra near Barrow, Alaska. The tram carries a suite of near-surface remote sensing sensors, including sonic depth, thermal IR, NDVI and multispectral sensors. Joint analysis with multiple ground-based measurements (soil temperature, active layer soil moisture, and carbon fluxes) was performed to quantify correlations and the dynamics of above/belowground processes at unprecedented resolution, both temporally and spatially. We analyzed the datasets with particular focus on correlating key subsurface and ecosystem properties with surface properties that can be measured by satellite/airborne remote sensing over a large area. Our results provided several new insights about system behavior and also opens the door for new characterization approaches. We documented that: (1) soil temperature (at >5 cm depth; critical for permafrost thaw) was decoupled from soil surface temperature and was influenced strongly by soil moisture, (2) NDVI and greenness index were highly correlated with both soil moisture and gross primary productivity (based on chamber flux data), and (3) surface deformation (which can be measured by InSAR) was a good proxy for thaw depth dynamics at non-inundated locations.
Li, Wanlu; Xu, Binbin; Song, Qiujin; Liu, Xingmei; Xu, Jianming; Brookes, Philip C
2014-02-15
Chinese agricultural soils and crops are suffering from increasing damage from heavy metals, which are introduced from various pollution sources including agriculture, traffic, mining and especially the flourishing private metal recycling industry. In this study, 219 pairs of rice grain and corresponding soil samples were collected from Wenling in Zhejiang Province to identify the spatial relationship and pollution hotspots of Cd, Cu, Ni and Zn in the soil-rice system. The mean soil concentrations of heavy metals were 0.316 mg kg(-1) for Cd, 47.3 mg kg(-1) for Cu, 31.7 mg kg(-1) for Ni and 131 mg kg(-1) for Zn, and the metal concentrations in rice grain were 0.132 mg kg(-1) for Cd, 2.46 mg kg(-1) for Cu, 0.223 mg kg(-1) for Ni and 17.4 mg kg(-1) for Zn. The coefficient of variability (CV) of soil Cd, Cu and rice Cd were 147%, 146% and 180%, respectively, indicating an extensive variability. While the CVs of other metals ranged from 23.4% to 84.3% with a moderate variability. Kriging interpolation procedure and the Local Moran's I index detected the locations of pollution hotspots of these four metals. Cd and Cu had a very similar spatial pattern, with contamination hotspots located simultaneously in the northwestern part of the study area, and there were obvious hotspots for soil Zn in the north area, while in the northeast for soil Ni. The existence of hotspots may be due to industrialization and other anthropogenic activities. An Enrichment Index (EI) was employed to measure the uptake of heavy metals by rice. The results indicated that the accumulation and availability of heavy metals in the soil-rice system may be influenced by both soil heavy metal concentrations and soil physico-chemical properties. Cross-correlograms quantitatively illustrated that EIs were significantly correlated with soil properties. Soil pH and organic matter were the most important factors controlling the uptake of heavy metals by rice. As results, positive measures should be taken into account to control soil pollution and to curtail metal contamination to the food chain in the areas of Wenling, which were the most polluted by toxic metals. Copyright © 2013 Elsevier B.V. All rights reserved.
Soil Sampling Techniques For Alabama Grain Fields
NASA Technical Reports Server (NTRS)
Thompson, A. N.; Shaw, J. N.; Mask, P. L.; Touchton, J. T.; Rickman, D.
2003-01-01
Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.
NASA Astrophysics Data System (ADS)
Chitu, Zenaida; Bogaard, Thom; Adler, Mary-Jeanne; Steele-Dunne, Susan; Hrachowitz, Markus; Busuioc, Aristita; Sandric, Ionut; Istrate, Alexandru
2014-05-01
Like in many parts of the world, landslides represent in Romania recurrent phenomena that produce numerous damages to the infrastructure every few years. The high frequency of landslide events over the world has resulted to the development of many early warning systems that are based on the definition of rainfall thresholds triggering landslides. In Romania in particular, recent studies exploring the temporal occurrence of landslides have revealed that rainfall represents the most important triggering factor for landslides. The presence of low permeability soils and gentle slope degrees in the Ialomita Subcarpathians of Romania makes that cumulated precipitation over variable time interval and the hydraulic response of the soil plays a key role in landslides triggering. In order to identify the slope responses to rainfall events in this particular area we investigate the variability of soil moisture and its relationship to landslide events in three Subcarpathians catchments (Cricovul Dulce, Bizididel and Vulcana) by combining in situ measurements, satellite-based radiometry and hydrological modelling. For the current study, hourly soil moisture measurements from six soil moisture monitoring stations that are fitted with volumetric soil moisture sensors, temperature soil sensors and rain gauges sensors are used. Pedotransfer functions will be applied in order to infer hydraulic soil properties from soil texture sampled from 50 soil profiles. The information about spatial and temporal variability of soil moisture content will be completed with the Level 2 soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. A time series analysis of soil moisture is planned to be integrated to landslide and rainfall time series in order to determine a preliminary rainfall threshold triggering landslides in Ialomita Subcarpathians.
L.M. Egerton-Warburton; R.C. Graham; K.R. Hubbert
2003-01-01
We documented the spatial distribution, abundance and molecular diversity of mycorrhizal hyphae and physical and chemical properties of soil-weathered bedrock in a chaparral community that experiences seasonal drought. Because plants in this community were known to rely on bedrock-stored water during the summer, the data were used to evaluate the potential role of...
Reliability Coupled Sensitivity Based Design Approach for Gravity Retaining Walls
NASA Astrophysics Data System (ADS)
Guha Ray, A.; Baidya, D. K.
2012-09-01
Sensitivity analysis involving different random variables and different potential failure modes of a gravity retaining wall focuses on the fact that high sensitivity of a particular variable on a particular mode of failure does not necessarily imply a remarkable contribution to the overall failure probability. The present paper aims at identifying a probabilistic risk factor ( R f ) for each random variable based on the combined effects of failure probability ( P f ) of each mode of failure of a gravity retaining wall and sensitivity of each of the random variables on these failure modes. P f is calculated by Monte Carlo simulation and sensitivity analysis of each random variable is carried out by F-test analysis. The structure, redesigned by modifying the original random variables with the risk factors, is safe against all the variations of random variables. It is observed that R f for friction angle of backfill soil ( φ 1 ) increases and cohesion of foundation soil ( c 2 ) decreases with an increase of variation of φ 1 , while R f for unit weights ( γ 1 and γ 2 ) for both soil and friction angle of foundation soil ( φ 2 ) remains almost constant for variation of soil properties. The results compared well with some of the existing deterministic and probabilistic methods and found to be cost-effective. It is seen that if variation of φ 1 remains within 5 %, significant reduction in cross-sectional area can be achieved. But if the variation is more than 7-8 %, the structure needs to be modified. Finally design guidelines for different wall dimensions, based on the present approach, are proposed.
USDA-ARS?s Scientific Manuscript database
To maximize profitability, cotton (GossypiumhirsutumL.) producers must attempt to control the quality of the crop while maximizing yield. The objective of this research was to measure the intrinsic variability present in cotton fiber yield and quality. The 0.5-ha experimental site was located in a...
Linking the climatic and geochemical controls on global soil carbon cycling
NASA Astrophysics Data System (ADS)
Doetterl, Sebastian; Stevens, Antoine; Six, Johan; Merckx, Roel; Van Oost, Kristof; Casanova Pinto, Manuel; Casanova-Katny, Angélica; Muñoz, Cristina; Boudin, Mathieu; Zagal Venegas, Erick; Boeckx, Pascal
2015-04-01
Climatic and geochemical parameters are regarded as the primary controls for soil organic carbon (SOC) storage and turnover. However, due to the difference in scale between climate and geochemical-related soil research, the interaction of these key factors for SOC dynamics have rarely been assessed. Across a large geochemical and climatic transect in similar biomes in Chile and the Antarctic Peninsula we show how abiotic geochemical soil features describing soil mineralogy and weathering pose a direct control on SOC stocks, concentration and turnover and are central to explaining soil C dynamics at larger scales. Precipitation and temperature had an only indirect control by regulating geochemistry. Soils with high SOC content have low specific potential CO2 respiration rates, but a large fraction of SOC that is stabilized via organo-mineral interactions. The opposite was observed for soils with low SOC content. The observed differences for topsoil SOC stocks along this transect of similar biomes but differing geo-climatic site conditions are of the same magnitude as differences observed for topsoil SOC stocks across all major global biomes. Using precipitation and a set of abiotic geochemical parameters describing soil mineralogy and weathering status led to predictions of high accuracy (R2 0.53-0.94) for different C response variables. Partial correlation analyses revealed that the strength of the correlation between climatic predictors and SOC response variables decreased by 51 - 83% when controlling for geochemical predictors. In contrast, controlling for climatic variables did not result in a strong decrease in the strength of the correlations of between most geochemical variables and SOC response variables. In summary, geochemical parameters describing soil mineralogy and weathering were found to be essential for accurate predictions of SOC stocks and potential CO2 respiration, while climatic factors were of minor importance as a direct control, but are important through governing soil weathering and geochemistry. In conclusion, we pledge for a stronger implementation of geochemical soil properties to predict SOC stocks on a global scale. Understanding the effects of climate (temperature and precipitation) change on SOC dynamics also requires good understanding of the relationship between climate and soil geochemistry.
Stochastic analysis of multiphase flow in porous media: II. Numerical simulations
NASA Astrophysics Data System (ADS)
Abin, A.; Kalurachchi, J. J.; Kemblowski, M. W.; Chang, C.-M.
1996-08-01
The first paper (Chang et al., 1995b) of this two-part series described the stochastic analysis using spectral/perturbation approach to analyze steady state two-phase (water and oil) flow in a, liquid-unsaturated, three fluid-phase porous medium. In this paper, the results between the numerical simulations and closed-form expressions obtained using the perturbation approach are compared. We present the solution to the one-dimensional, steady-state oil and water flow equations. The stochastic input processes are the spatially correlated logk where k is the intrinsic permeability and the soil retention parameter, α. These solutions are subsequently used in the numerical simulations to estimate the statistical properties of the key output processes. The comparison between the results of the perturbation analysis and numerical simulations showed a good agreement between the two methods over a wide range of logk variability with three different combinations of input stochastic processes of logk and soil parameter α. The results clearly demonstrated the importance of considering the spatial variability of key subsurface properties under a variety of physical scenarios. The variability of both capillary pressure and saturation is affected by the type of input stochastic process used to represent the spatial variability. The results also demonstrated the applicability of perturbation theory in predicting the system variability and defining effective fluid properties through the ergodic assumption.
NASA Astrophysics Data System (ADS)
Osborn, B.; Chapple, W.; Ewers, B. E.; Williams, D. G.
2014-12-01
The interaction between soil conditions and climate variability plays a central role in the ecohydrological functions of montane conifer forests. Although soil moisture availability to trees is largely dependent on climate, the depth and texture of soil exerts a key secondary influence. Multiple Pleistocene glacial events have shaped the landscape of the central Rocky Mountains creating a patchwork of soils differing in age and textural classification. This mosaic of soil conditions impacts hydrological properties, and montane conifer forests potentially respond to climate variability quite differently depending on the age of glacial till and soil development. We hypothesized that the age of glacial till and associated soil textural changes exert strong control on growth and photosynthetic gas exchange of lodgepole pine. We examined physiological and growth responses of lodgepole pine to interannual variation in maximum annual snow water equivalence (SWEmax) of montane snowpack and growing season air temperature (Tair) and vapor pressure deficit (VPD) across a chronosequence of Pleistocene glacial tills ranging in age from 700k to 12k years. Soil textural differences across the glacial tills illustrate the varying degrees of weathering with the most well developed soils with highest clay content on the oldest till surfaces. We show that sensitivity of growth and carbon isotope discrimination, an integrated measure of canopy gas exchange properties, to interannual variation SWEmax , Tair and VPD is greatest on young till surfaces, whereas trees on old glacial tills with well-developed soils are mostly insensitive to these interannual climate fluctuations. Tree-ring widths were most sensitive to changes in SWEmax on young glacial tills (p < 0.01), and less sensitive on the oldest till (p < 0.05). Tair correlates strongly with δ13C values on the oldest and youngest tills sites, but shows no significant relationship on the middle aged glacial till. It is clear that growth and photosynthetic gas exchange parameters are sensitive to glacial till surfaces, which is evident by the different responses to SWEmax and Tair across sites.
NASA Astrophysics Data System (ADS)
Gorji, Taha; Sertel, Elif; Tanik, Aysegul
2017-12-01
Soil management is an essential concern in protecting soil properties, in enhancing appropriate soil quality for plant growth and agricultural productivity, and in preventing soil erosion. Soil scientists and decision makers require accurate and well-distributed spatially continuous soil data across a region for risk assessment and for effectively monitoring and managing soils. Recently, spatial interpolation approaches have been utilized in various disciplines including soil sciences for analysing, predicting and mapping distribution and surface modelling of environmental factors such as soil properties. The study area selected in this research is Tuz Lake Basin in Turkey bearing ecological and economic importance. Fertile soil plays a significant role in agricultural activities, which is one of the main industries having great impact on economy of the region. Loss of trees and bushes due to intense agricultural activities in some parts of the basin lead to soil erosion. Besides, soil salinization due to both human-induced activities and natural factors has exacerbated its condition regarding agricultural land development. This study aims to compare capability of Local Polynomial Interpolation (LPI) and Radial Basis Functions (RBF) as two interpolation methods for mapping spatial pattern of soil properties including organic matter, phosphorus, lime and boron. Both LPI and RBF methods demonstrated promising results for predicting lime, organic matter, phosphorous and boron. Soil samples collected in the field were used for interpolation analysis in which approximately 80% of data was used for interpolation modelling whereas the remaining for validation of the predicted results. Relationship between validation points and their corresponding estimated values in the same location is examined by conducting linear regression analysis. Eight prediction maps generated from two different interpolation methods for soil organic matter, phosphorus, lime and boron parameters were examined based on R2 and RMSE values. The outcomes indicate that RBF performance in predicting lime, organic matter and boron put forth better results than LPI. However, LPI shows better results for predicting phosphorus.
Spatial correlation of shear-wave velocity in the San Francisco Bay Area sediments
Thompson, E.M.; Baise, L.G.; Kayen, R.E.
2007-01-01
Ground motions recorded within sedimentary basins are variable over short distances. One important cause of the variability is that local soil properties are variable at all scales. Regional hazard maps developed for predicting site effects are generally derived from maps of surficial geology; however, recent studies have shown that mapped geologic units do not correlate well with the average shear-wave velocity of the upper 30 m, Vs(30). We model the horizontal variability of near-surface soil shear-wave velocity in the San Francisco Bay Area to estimate values in unsampled locations in order to account for site effects in a continuous manner. Previous geostatistical studies of soil properties have shown horizontal correlations at the scale of meters to tens of meters while the vertical correlations are on the order of centimeters. In this paper we analyze shear-wave velocity data over regional distances and find that surface shear-wave velocity is correlated at horizontal distances up to 4 km based on data from seismic cone penetration tests and the spectral analysis of surface waves. We propose a method to map site effects by using geostatistical methods based on the shear-wave velocity correlation structure within a sedimentary basin. If used in conjunction with densely spaced shear-wave velocity profiles in regions of high seismic risk, geostatistical methods can produce reliable continuous maps of site effects. ?? 2006 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing
2017-04-01
A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM) ''hot spots'', it is generally admitted that the variability of the surface temperature is explained by the soil moisture trough its control on the evaporation. This work suggests that the impact of the soil moisture on the temperature through its impact on the thermal inertia can be as important as its direct impact on the evaporation. Contrarily to the evaporation related soil-moisture temperature negative feedback, the thermal inertia soil-moisture related feedback newly identified by this work is a positive feedback which limits the cooling when the soil moisture increases. These results suggest that uncertainties in the representation of the soil and snow thermal properties can be responsible of significant biases in numerical simulations and emphasize the need to carefully document and evaluate these quantities in the Land Surface Modules implemented in the climate models.
NASA Astrophysics Data System (ADS)
Gil, Eshel; Guy, Levy; Oshri, Rinot; Michael, Borisover; Uri, Yermiyahu; Leah, Tsror; Hanan, Eizenberg; Tal, Svoray; Alex, Furman; Yael, Mishael; Yosef, Steinberger
2017-04-01
The link among between soil health, soil conservation, and food security, resilience, and function under a wide range of agricultural uses and different environmental systems, is at the heart of many ecofriendly research studies worldwide. We consider the health of soil as a function of its ability to provide ecosystem services, including agricultural production (provisional services); regulating natural cycles (regulation services) and as a habitat for plants (support services). Soil health is affected by a wide range of soil properties (biotic and abiotic) that maintain complex interactions among themselves. The decline in soil health includes degradation in its physical properties (e.g., deterioration of soil structure, compaction and sealing, water-repellency, soil erosion by water and wind), chemical properties (e.g., salinization, depletion of nutrients and organic matter content, accumulation of pollutants and reduction of the soils' ion exchange capacity) and biological properties (e.g., vulnerable populations of microflora, microfauna, and mesofauna, leading to a breach of ecological balance and biodiversity and, as a result, destruction of beneficial populations and pathogen outbreaks). Numerous studies show that agricultural practices have a major impact on soil functioning. Substituting longstanding tillage with no-till cropping and the amalgamation of cover crops in crop rotations were found to improve soil properties. Such changes contributed to the enhancement of the agronomical performance of the soil. On the other hand, these practices may result in lessened effectiveness of controlling perennial weeds. The evaluation of soil-health status in the Mediterranean region is very limited. Moreover, existing approaches for evaluation that have been used (such as the Cornell and Hany tests) do not give sufficient weight to important agronomic processes, such as soil erosion, salinization, sodification, spread of weeds in the fields (in particular, weeds that are difficult to control), soil-borne diseases, and pesticide fixation and release. We, a group of more than ten Israeli scientists, have recently started a multidisciplinary study aimed at developing and consolidating a multiparameter soil-health index to characterize the health of agricultural soils in Mediterranean regions. Such an index will enable us to quantitatively evaluate the contribution of different cultivation managements and reclamation activities. In order to achieve our goal, a three steps approach was adopted: 1) acquiring a multivariate component database (about 42 variables) that will be quantified in the laboratory and in the fields in two soil types of the most important agricultural region of Israel, at three different soil usage: orchard, field crops and "native" as a reference. The acquired biological, physical, and chemical variables comprise basic quantitative values in the soil health of agricultural land; (2) developing a multivariate soil-health index based on a multivariate correlation, in addition to conducting meetings with farmers and panel discussions with other scientists in the field. The whole study angled to evaluate the relative contribution of each of the biotic and abiotic parameters in order to develop a model related to soil health; and (3) to validate the efficiency of the developed index for characterizing and assessing soil-health state at the various agricultural regions in Israel where conservation and reclamation activities took place. We are open to extend our study to other areas with a Mediterranean climate and look forward to establishing cooperative activities with other research groups.
Fortuna, Ann-Marie; Honeycutt, C Wayne; Vandemark, George; Griffin, Timothy S; Larkin, Robert P; He, Zhongqi; Wienhold, Brian J; Sistani, Karamat R; Albrecht, Stephan L; Woodbury, Bryan L; Torbert, Henry A; Powell, J Mark; Hubbard, Robert K; Eigenberg, Roger A; Wright, Robert J; Alldredge, J Richard; Harsh, James B
2012-01-01
Soil biotic and abiotic factors strongly influence nitrogen (N) availability and increases in nitrification rates associated with the application of manure. In this study, we examine the effects of edaphic properties and a dairy (Bos taurus) slurry amendment on N availability, nitrification rates and nitrifier communities. Soils of variable texture and clay mineralogy were collected from six USDA-ARS research sites and incubated for 28 d with and without dairy slurry applied at a rate of ~300 kg N ha(-1). Periodically, subsamples were removed for analyses of 2 M KCl extractable N and nitrification potential, as well as gene copy numbers of ammonia-oxidizing bacteria (AOB) and archaea (AOA). Spearman coefficients for nitrification potentials and AOB copy number were positively correlated with total soil C, total soil N, cation exchange capacity, and clay mineralogy in treatments with and without slurry application. Our data show that the quantity and type of clay minerals present in a soil affect nitrifier populations, nitrification rates, and the release of inorganic N. Nitrogen mineralization, nitrification potentials, and edaphic properties were positively correlated with AOB gene copy numbers. On average, AOA gene copy numbers were an order of magnitude lower than those of AOB across the six soils and did not increase with slurry application. Our research suggests that the two nitrifier communities overlap but have different optimum environmental conditions for growth and activity that are partly determined by the interaction of manure-derived ammonium with soil properties. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Pérez-Fernández, María A; Vera-Tomé, Feliciano; Blanco-Rodríguez, María P; Lozano, Juan C
2014-06-01
The evolution of vegetation structure following mine rehabilitation is rather scarce in the literature. The concentration of long-lived radionuclides of the (238)U series might have harmful effects on living organisms. We studied soil properties and the natural vegetation occurring along a gradient in Los Ratones, an area rehabilitated after uranium mining located in Cáceres, Spain. Soil and vegetation were sampled seasonally and physical and chemical properties of soil were analysed, including natural isotopes of (238)U, (230)Th, (226)Ra and (210)Pb. Species richness, diversity, evenness and plant cover were estimated and correlated in relation to soil physical and chemical variables. The location of the sampling sites along a gradient had a strong explanatory effect on the herbaceous species, as well as the presence of shrubs and trees. Seasonal effects of the four natural isotopes were observed in species richness, species diversity and plant cover; these effects were directly related to the pH values in the soil, this being the soil property that most influences the plant distribution. Vegetation in the studied area resembles that of the surroundings, thus proving that the rehabilitation carried out in Los Ratones mine was successful in terms of understorey cover recovery.
Global Soil Respiration: Interaction with Environmental Variables and Response to Climate Change
NASA Astrophysics Data System (ADS)
Jian, J.; Steele, M.
2016-12-01
Background, methods, objectivesTerrestrial ecosystems take up around 1.7 Pg C per year; however, the role of terrestrial ecosystems as a carbon sink may change to carbon source by 2050, as a result of positive feedback of soil respiration response to global warming. Nevertheless, limited evidence shows that soil carbon is decreasing and the role of terrestrial ecosystems is changing under warming. One possibility is the positive feedback may slow due to the acclimation of soil respiration as a result of decreasing temperature sensitivity (Q10) with warming. To verify and quantify the uncertainty in soil carbon cycling and feedbacks to climate change, we assembled soil respiration observations from 1961 to 2014 from 724 publications into a monthly global soil respiration database (MSRDB), which included 13482 soil respiration measurements together with 38 other ancillary measurements from 538 sites. Using this database we examined macroscale variation in the relationship between soil respiration and air temperature, precipitation, leaf area index and soil properties. We also quantified global soil respiration, the sources of uncertainty, and its feedback to warming based on climate region-oriented models with variant Q10function. Results and ConclusionsOur results showed substantial heterogeneity in the relationship between soil respiration and environmental factors across different climate regions. For example, soil respiration was strongly related to vegetation (via leaf area index) in colder regions, but not in tropical region. Only in tropical and arid regions did soil properties explain any variation in soil respiration. Global annual mean soil respiration from 1961 to 2014 was estimated to be 72.41 Pg C yr-1 based on monthly global soil respiration database, 25 Pg lower than estimated based on yearly soil respiration database. By using the variable Q10 models, we estimated that global soil respiration increased at a rate of 0.03 Pg C yr-1 from 1961 to 2014, smaller than previous studies ( 0.1 Pg C yr-1). The substantial variations in these relationships suggest that regional scales is important for understanding and prediction of global carbon cycling and how it response to climate change.
Improved Saturated Hydraulic Conductivity Pedotransfer Functions Using Machine Learning Methods
NASA Astrophysics Data System (ADS)
Araya, S. N.; Ghezzehei, T. A.
2017-12-01
Saturated hydraulic conductivity (Ks) is one of the fundamental hydraulic properties of soils. Its measurement, however, is cumbersome and instead pedotransfer functions (PTFs) are often used to estimate it. Despite a lot of progress over the years, generic PTFs that estimate hydraulic conductivity generally don't have a good performance. We develop significantly improved PTFs by applying state of the art machine learning techniques coupled with high-performance computing on a large database of over 20,000 soils—USKSAT and the Florida Soil Characterization databases. We compared the performance of four machine learning algorithms (k-nearest neighbors, gradient boosted model, support vector machine, and relevance vector machine) and evaluated the relative importance of several soil properties in explaining Ks. An attempt is also made to better account for soil structural properties; we evaluated the importance of variables derived from transformations of soil water retention characteristics and other soil properties. The gradient boosted models gave the best performance with root mean square errors less than 0.7 and mean errors in the order of 0.01 on a log scale of Ks [cm/h]. The effective particle size, D10, was found to be the single most important predictor. Other important predictors included percent clay, bulk density, organic carbon percent, coefficient of uniformity and values derived from water retention characteristics. Model performances were consistently better for Ks values greater than 10 cm/h. This study maximizes the extraction of information from a large database to develop generic machine learning based PTFs to estimate Ks. The study also evaluates the importance of various soil properties and their transformations in explaining Ks.
NASA Astrophysics Data System (ADS)
Hernández, Zulimar; Pérez Trujillo, Juan Pedro; Hernández-Hernández, Sergio Alexander; Almendros, Gonzalo; Sanz, Jesús
2014-05-01
From a practical viewpoint, the most interesting possibilities of applying infrared (IR) spectroscopy to soil studies lie on processing IR spectra of whole soil (WS) samples [1] in order to forecast functional descriptors at high organizational levels of the soil system, such as soil C resilience. Currently, there is a discussion on whether the resistance to biodegradation of soil organic matter (SOM) depends on its molecular composition or on environmental interactions between SOM and mineral components, such could be the case with physical encapsulation of particulate SOM or organo-mineral derivatives, e.g., those formed with amorphous oxides [2]. A set of about 200 dependent variables from WS and isolated, ash free, humic acids (HA) [3] was obtained in 30 volcanic ash soils from Tenerife Island (Spain). Soil biogeochemical properties such as SOM, allophane (Alo + 1 /2 Feo), total mineralization coefficient (TMC) or aggregate stability were determined in WS. In addition, structural information on SOM was obtained from the isolated HA fractions by visible spectroscopy and analytical pyrolysis (Py-GC/MS). Aiming to explore the potential of partial least squares regression (PLS) in forecasting soil dependent variables, exclusively using the information extracted from WS and HA IR spectral profiles, data were processed by using ParLeS [4] and Unscrambler programs. Data pre-treatments should be carefully chosen: the most significant PLS models from IR spectra of HA were obtained after second derivative pre-treatment, which prevented effects of intrinsically broadband spectral profiles typical in macromolecular heterogeneous material such as HA. Conversely, when using IR spectra of WS, the best forecasting models were obtained using linear baseline correction and maximum normalization pre-treatment. With WS spectra, the most successful prediction models were obtained for SOM, magnetite, allophane, aggregate stability, clay and total aromatic compounds, whereas the PLS-model for TMC was of little significance. On the other hand, the best successful prediction models using HA spectra were for SOM, TMC, allophane content and soil fungal pigments. In these particular volcanic ash soils, with large concentration of short-range minerals, the use of WS spectra, compared to the use of HA spectra, led to predict higher number of dependent variables. This is interpreted as the fact that the information of mineral constituents may help to explain soil emergent properties (e.g., SOM resilience or hydrophysical properties). The above results coincide with previous research [2] based on classification of soil properties by multidimensional scaling, where it was demonstrated that formation of stable organomineral complexes between HA and allophane coincide with large amounts of SOM and low TMC values. [1] Viscarra Rossel, R.A., Walvoort, D.J.J., McBratney, A.B., Janik, L.J. & Skjemstad, J.O. 2006. Geoderma 131, 59-75. [2] Hernández, Z., Almendros, G. 2012. Soil Biology & Biochemistry 44, 130-142. [3] Hernández, Z. 2009. Functional study of soil organic matter in vineyards from Tenerife Island (Spain). PhD. University of Alcalá, Alcalá de Henares, Madrid. [4] Viscarra-Rossel, R.A. 2008. Chemometrics & Intelligent Laboratory Systems 90, 72-83.
NASA Astrophysics Data System (ADS)
Doerr, Stefan; Santin, Cristina; Reardon, James; Mataix-Solera, Jorge; Stoof, Cathelijne; Bryant, Rob; Miesel, Jessica; Badia, David
2017-04-01
Heat transfer from the combustion of ground fuels and soil organic matter during vegetation fires can cause substantial changes to the physical, chemical and biological characteristics of soils. Numerous studies have investigated the effects of wildfires and prescribed burns on soil properties based either on field samples or using laboratory experiments. Critical thresholds for changes in soil properties, however, have been determined largely based on laboratory heating experimentation. These experimental approaches have been criticized for being inadequate for reflecting the actual heating patterns soil experienced in vegetation fires, which remain poorly understood. To address this research gap, this study reviews existing and evaluates new field data on key soil heating parameters determined during wildfires and prescribed burns from a wide range of environments. The results highlight the high spatial and temporal variability in soil heating patters not only between, but also within fires. Most wildfires and prescribed burns are associated with heat pulses that are much shorter than those typically applied in laboratory studies, which can lead to erroneous conclusions when results from laboratory studies are used to predict fire impacts on soils in the field.
Pardini, Giovanni; Gispert, Maria; Dunjó, Gemma
2004-07-26
Abandonment of terraced soils and increased brushland cover has increased wildfire occurrence to almost an annual rate in the Cap de Creus Peninsula, NE Pyrenees Range, Province of Girona, Spain. A wildfire occurred in August 2000 and affected an area of 6760 ha of shrubs and cork trees, whereas still cultivated plots were only slightly affected. Five stations of erosion measurements, corresponding to five different environments (from present cultivation to late abandonment) were destroyed by the passage of fire, and were promptly replaced to allow to monitoring post-fire effects on soil erosion. Selected soil properties were determined monthly before the fire and during 6 months after the fire at a monthly rate. Runoff and sediment yield together with dissolved organic carbon (DOC) in runoff water and organic carbon losses in eroded sediments (EOC) were evaluated throughout 2000. The last stage of abandonment, stands of cork trees, had the highest soil stability. Nevertheless, evidence of unfavourable soil conditions was detected at the shrub stage, when Cistus monspeliensis cover was the dominant opportunistic plant. This stage was considered to be a critical threshold leading either to degradation or regeneration processes according to fire frequency. A drastic change in soil properties, erosion and nutrient depletion occurred after the fire in all the environments. Statistics enabled to state that environments differed significantly in main soil properties. By statistically comparing the measured variables between the environments before and after the fire, DOC was found to be the soil parameter showing the highest significance between environments. Absolute values of erosion were low with respect to other Mediterranean environments although the shallow nature of these soils might deserve special attention because of a comparatively higher risk of degradation. Copyright 2004 Elsevier B.V.
Rangeland degradation in savannas of South Africa: spatial patterns of soil and vegetation
NASA Astrophysics Data System (ADS)
Sandhage-Hofmann, Alexandra; Löffler, Jörg; du Preez, Chris; Kotzé, Elmarie; Weijers, Stef; Wundram, Dirk; Zacharias, Maximilan; Amelung, Wulf
2017-04-01
Extensive bush encroachment by Acacia mellifera and associated woody species at semi-arid and arid sites are the most notable forms of rangeland degradation in savannas of South Africa. Concerns are growing over the threat of suppression and loss of nutritious perennial grass species. Grazing and different rangeland management systems (communal and freehold) are considered to be of major importance for degradation, but the process of encroachment is not restricted to communal land. A vegetation change is mostly accompanied by changes in soil properties, where soils in savanna systems can profit from woody species due to litter fall, root distribution, shadow and animal resting time. Savannas are very heterogeneous systems with high spatial variation of patches with wood, herbaceous species and bare ground. We hypothesized that the spatial patterns of soil properties in South Africás rangelands are controlled by present or past vegetation, modulated by the tenure systems with higher rangeland degradation in communal areas. To test this, we sampled soils at communal and commercial land in the Kuruman area of South Africa with the following design: three farms per tenure system, 6 randomly chosen plots (100x100m) per farm, and 25 soil samples (0-10 cm) per plot, each in a 5x5m sampling area. At every sampling point, information of overlying vegetation was recorded (species or bare soil, canopy size, height). For each sampling area, if present, trees/ shrubs were sampled and their ages estimated through the counting of annual growth rings. For each plot, high resolution UAV aerial photos were taken to evaluate the extent of bush encroachment. Analyses involved main physical and chemical soil parameters and isotopic analyses. The results of a rough aerial image classification (grass, woody species, bare ground) revealed significant differences between the tenure systems with higher coverage of bare ground and shrubs at communal farms, and higher grass cover at commercial farms. The tenure systems had no differences in main texture classes of the soils, but significant differences in the composition of the sand fraction, with higher levels of fine sand and lower levels of coarse sand in communal farms. The chemical soil properties showed a high variability both within and between the farms, with much higher variability within communal than commercial farms. Additionally, concentrations of nitrogen, carbon, calcium and pH were significant higher in communal farms. Isotopic analyses in soils showed significant differences for 15N with higher levels in commercial farms. Different photosynthetic pathways are responsible for differences found in 13C values, with higher levels (-16-18‰) in C4-grassland and lower values (-22-26‰) in soils under Acacia (C3). We found relationships between soil properties and species or bare ground, where differences in texture likely interact with both, vegetation cover and soil properties.
Yu, Shen; Ehrenfeld, Joan G.
2010-01-01
Background and Aims Understanding the role of different components of hydrology in structuring wetland communities is not well developed. A sequence of adjacent wetlands located on a catenary sequence of soils and receiving the same sources and qualities of water is used to examine specifically the role of water-table median position and variability in affecting plant and microbial community composition and soil properties. Methods Two replicates of three types of wetland found adjacent to each other along a hydrological gradient in the New Jersey Pinelands (USA) were studied. Plant-community and water-table data were obtained within a 100-m2 plot in each community (pine swamp, maple swamp and Atlantic-white-cedar swamp). Monthly soil samples from each plot were analysed for soil moisture, organic matter, extractable nitrogen fractions, N mineralization rate and microbial community composition. Multivariate ordination methods were used to compare patterns among sites within and between data sets. Key Results The maple and pine wetlands were more similar to each other in plant community composition, soil properties and microbial community composition than either was to the cedar swamps. However, maple and pine wetlands differed from each other in water-table descriptors as much as they differed from the cedar swamps. All microbial communities were dominated by Gram-positive bacteria despite hydrologic differences among the sites. Water-table variability was as important as water-table level in affecting microbial communities. Conclusions Water tables affect wetland communities through both median level and variability. Differentiation of both plant and microbial communities are not simple transforms of differences in water-table position, even when other hydrologic factors are kept constant. Rather, soil genesis, a result of both water-table position and geologic history, appears to be the main factor affecting plant and microbial community similarities. PMID:19643908
Martínez-Murillo, J F; Hueso-González, P; Ruiz-Sinoga, J D
2017-10-01
Soil mapping has been considered as an important factor in the widening of Soil Science and giving response to many different environmental questions. Geostatistical techniques, through kriging and co-kriging techniques, have made possible to improve the understanding of eco-geomorphologic variables, e.g., soil moisture. This study is focused on mapping of topsoil moisture using geostatistical techniques under different Mediterranean climatic conditions (humid, dry and semiarid) in three small watersheds and considering topography and soil properties as key factors. A Digital Elevation Model (DEM) with a resolution of 1×1m was derived from a topographical survey as well as soils were sampled to analyzed soil properties controlling topsoil moisture, which was measured during 4-years. Afterwards, some topography attributes were derived from the DEM, the soil properties analyzed in laboratory, and the topsoil moisture was modeled for the entire watersheds applying three geostatistical techniques: i) ordinary kriging; ii) co-kriging considering as co-variate topography attributes; and iii) co-kriging ta considering as co-variates topography attributes and gravel content. The results indicated topsoil moisture was more accurately mapped in the dry and semiarid watersheds when co-kriging procedure was performed. The study is a contribution to improve the efficiency and accuracy of studies about the Mediterranean eco-geomorphologic system and soil hydrology in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.
Assessing the legacy effects of historic charcoal production in Brandenburg, Germany
NASA Astrophysics Data System (ADS)
Schneider, Anna; Hirsch, Florian; Raab, Alexandra; Bonhage, Alexander; Raab, Thomas
2017-04-01
Charcoal produced in kilns or hearths was an important source of energy in many regions of Europe and Northern America until the 19th century, and charcoal production in hearths is still common in many other regions of the world. The remains of charcoal hearths are therefore a widespread legacy of historic land use in forest areas. Soils on charcoal hearth sites are characterized by a technogenic layer rich in charcoal and ash on top of the soil profile, and by a pyrogenic modification of substrates below the former hearth. The aims of our study are to examine how these alterations to the natural soil profiles affect the soil water regime and other soil physical properties, and to assess the relevance of these effects on the landscape scale. We present first results of a mapping of hearth site occurrence in forest areas in the state of Brandenburg, Germany, and of a characterization of the infiltration behaviour on hearth sites as compared with undisturbed forest soils. Results of mapping small-scale relief features from LIDAR-based digital elevation models show that charcoal hearths occur in a high density in many large forest areas throughout Brandenburg. In the areas studied so far, up to almost 3% of the soil surface were found to be affected by the remains of historic hearths. First analyses of soil physical properties indicate differences in the infiltration characteristics of hearth site soils and undisturbed forest soils: Hood infiltrometer measurements show a very high spatial variability of hydraulic conductivity for hearth site soils, and water-drop-penetration-time tests reflect extremely high hydrophobicity of the technogenic layer on the sites. Results of dye tracer experiment show considerably strong preferential flow and therefore a higher spatial variability of soil wetness below the hearth remains. Overall, our first results therefore indicate that the legacy effects of historic charcoal production might significantly affect overall site conditions in forest areas with a high density of charcoal hearth remains.
NASA Astrophysics Data System (ADS)
Koestel, J. K.; Norgaard, T.; Luong, N. M.; Vendelboe, A. L.; Moldrup, P.; Jarvis, N. J.; Lamandé, M.; Iversen, B. V.; Wollesen de Jonge, L.
2013-02-01
It is known that solute transport through soil is heterogeneous at all spatial scales. However, little data are available to allow quantification of these heterogeneities at the field scale or larger. In this study, we investigated the spatial patterns of soil properties, hydrologic state variables, and tracer breakthrough curves (BTCs) at the field scale for the inert solute transport under a steady-state irrigation rate which produced near-saturated conditions. Sixty-five undisturbed soil columns approximately 20 cm in height and diameter were sampled from the loamy topsoil of an agricultural field site in Silstrup (Denmark) at a sampling distance of approximately 15 m (with a few exceptions), covering an area of approximately 1 ha (60 m × 165 m). For 64 of the 65 investigated soil columns, we observed BTC shapes indicating a strong preferential transport. The strength of preferential transport was positively correlated with the bulk density and the degree of water saturation. The latter suggests that preferential macropore transport was the dominating transport process. Increased bulk densities were presumably related with a decrease in near-saturated hydraulic conductivities and as a consequence to larger water saturation and the activation of larger macropores. Our study provides further evidence that it should be possible to estimate solute transport properties from soil properties such as soil texture or bulk density. We also demonstrated that estimation approaches established for the column scale have to be upscaled when applied to the field scale or larger.
Substantial soil organic carbon retention along floodplains of mountain streams
NASA Astrophysics Data System (ADS)
Sutfin, Nicholas A.; Wohl, Ellen
2017-07-01
Small, snowmelt-dominated mountain streams have the potential to store substantial organic carbon in floodplain sediment because of high inputs of particulate organic matter, relatively lower temperatures compared with lowland regions, and potential for increased moisture conditions. This work (i) quantifies mean soil organic carbon (OC) content along 24 study reaches in the Colorado Rocky Mountains using 660 soil samples, (ii) identifies potential controls of OC content based on soil properties and spatial position with respect to the channel, and (iii) and examines soil properties and OC across various floodplain geomorphic features in the study area. Stepwise multiple linear regression (adjusted r2 = 0.48, p < 0.001) indicates that percentage of silt and clay, sample depth, percent sand, distance from the channel, and relative elevation from the channel are significant predictors of OC content in the study area. Principle component analysis indicates limited separation between geomorphic floodplain features based on predictors of OC content. A lack of significant differences among floodplain features suggests that the systematic random sampling employed in this study can capture the variability of OC across floodplains in the study area. Mean floodplain OC (6.3 ± 0.3%) is more variable but on average greater than values in uplands (1.5 ± 0.08% to 2.2 ± 0.14%) of the Colorado Front Range and higher than published values from floodplains in other regions, particularly those of larger rivers.
NASA Astrophysics Data System (ADS)
Gray, H. J.; Tucker, G. E.; Mahan, S.
2017-12-01
Luminescence is a property of matter that can be used to obtain depositional ages from fine sand. Luminescence generates due to exposure to background ionizing radiation and is removed by sunlight exposure in a process known as bleaching. There is evidence to suggest that luminescence can also serve as a sediment tracer in fluvial and hillslope environments. For hillslope environments, it has been suggested that the magnitude of luminescence as a function of soil depth is related to the strength of soil mixing. Hillslope soils with a greater extent of mixing will have previously surficial sand grains moved to greater depths in a soil column. These previously surface-exposed grains will contain a lower luminescence than those which have never seen the surface. To attempt to connect luminescence profiles with soil mixing rate, here defined as the soil vertical diffusivity, I conduct numerical modelling of particles in hillslope soils coupled with equations describing the physics of luminescence. I use recently published equations describing the trajectories of particles under both exponential and uniform soil velocity soils profiles and modify them to include soil diffusivity. Results from the model demonstrates a strong connection between soil diffusivity and luminescence. Both the depth profiles of luminescence and the total percent of surface exposed grains will change drastically based on the magnitude of the diffusivity. This suggests that luminescence could potentially be used to infer the magnitude of soil diffusivity. However, I test other variables such as the soil production rate, e-folding length of soil velocity, background dose rate, and soil thickness, and I find these other variables can also affect the relationship between luminescence and diffusivity. This suggests that these other variables may need to be constrained prior to any inferences of soil diffusivity from luminescence measurements. Further field testing of the model in areas where the soil vertical diffusivity and other parameters are independently known will provide a test of this potential new method.
Spatial Distribution of Soil Fauna In Long Term No Tillage
NASA Astrophysics Data System (ADS)
Corbo, J. Z. F.; Vieira, S. R.; Siqueira, G. M.
2012-04-01
The soil is a complex system constituted by living beings, organic and mineral particles, whose components define their physical, chemical and biological properties. Soil fauna plays an important role in soil and may reflect and interfere in its functionality. These organisms' populations may be influenced by management practices, fertilization, liming and porosity, among others. Such changes may reduce the composition and distribution of soil fauna community. Thus, this study aimed to determine the spatial variability of soil fauna in consolidated no-tillage system. The experimental area is located at Instituto Agronômico in Campinas (São Paulo, Brazil). The sampling was conducted in a Rhodic Eutrudox, under no tillage system and 302 points distributed in a 3.2 hectare area in a regular grid of 10.00 m x 10.00 m were sampled. The soil fauna was sampled with "Pitfall Traps" method and traps remained in the area for seven days. Data were analyzed using descriptive statistics to determine the main statistical moments (mean variance, coefficient of variation, standard deviation, skewness and kurtosis). Geostatistical tools were used to determine the spatial variability of the attributes using the experimental semivariogram. For the biodiversity analysis, Shannon and Pielou indexes and richness were calculated for each sample. Geostatistics has proven to be a great tool for mapping the spatial variability of groups from the soil epigeal fauna. The family Formicidae proved to be the most abundant and dominant in the study area. The parameters of descriptive statistics showed that all attributes studied showed lognormal frequency distribution for groups from the epigeal soil fauna. The exponential model was the most suited for the obtained data, for both groups of epigeal soil fauna (Acari, Araneae, Coleoptera, Formicidae and Coleoptera larva), and the other biodiversity indexes. The sampling scheme (10.00 m x 10.00 m) was not sufficient to detect the spatial variability for all groups of soil epigeal fauna found in this study.
Intra-basin variability of snowmelt water balance calculations in a subarctic catchment
NASA Astrophysics Data System (ADS)
McCartney, Stephen E.; Carey, Sean K.; Pomeroy, John W.
2006-03-01
The intra-basin variability of snowmelt and melt-water runoff hydrology in an 8 km2 subarctic alpine tundra catchment was examined for the 2003 melt period. The catchment, Granger Creek, is within the Wolf Creek Research Basin, Yukon, which is typical of mountain subarctic landscapes in northwestern Canada. The study catchment was segmented into nine internally uniform zones termed hydrological response units (HRUs) based on their similar hydrological, physiographic, vegetation and soil properties. Snow accumulation exhibited significant variability among the HRUs, with greatest snow water equivalent in areas of tall shrub vegetation. Melt began first on southerly exposures and at lower elevations, yet average melt rates for the study period varied little among HRUs with the exception of those with steep aspects. In HRUs with capping organic soils, melt water first infiltrated this surface horizon, satisfying its storage capacity, and then percolated into the frozen mineral substrate. Infiltration and percolation into frozen mineral soils was restricted where melt occurred rapidly and organic soils were thin; in this case, melt-water delivery rates exceeded the frozen mineral soil infiltration rate, resulting in high runoff rates. In contrast, where there were slower melt rates and thick organic soils, infiltration was unlimited and runoff was suppressed. The snow water equivalent had a large impact on runoff volume, as soil storage capacity was quickly surpassed in areas of deep snow, diverting the bulk of melt water laterally to the drainage network. A spatially distributed water balance indicated that the snowmelt freshet was primarily controlled by areas with tall shrub vegetation that accumulate large quantities of snow and by alpine areas with no capping organic soils. The intra-basin water balance variability has important implications for modelling freshet in hydrological models.
Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar
NASA Astrophysics Data System (ADS)
Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.
2013-12-01
Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial scales up 20, curvature explains 40% of soil thickness variance among soils <3 m deep, while soils >3 m deep show no clear relation to curvature. To further demonstration our geomorphic segmentation approach, we apply it to DEM domains where diffusion processes are less dominant than in our primary study area. Classified landform map derived from fine scale terrestrial lidar. Color classes depict hydrogeomorphic process domains in zero order watersheds.
Harp, Dylan R.; Atchley, Adam L.; Painter, Scott L.; ...
2016-02-11
Here, the effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21more » $$^{st}$$ century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.« less
Harp, D. R.; Atchley, A. L.; Painter, S. L.; ...
2015-06-29
The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows formore » the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. As a result, by comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.« less
NASA Astrophysics Data System (ADS)
Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.
2015-06-01
The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.
NASA Astrophysics Data System (ADS)
Zeng, C.; Zhang, F.
2014-12-01
Alpine meadow is one of widespread vegetation types of the Qinghai-Tibetan Plateau. However, alpine meadow ecosystem is undergoing degradation in recent years. The degradation of alpine meadow can changes soil physical and chemical properties as well as it's spatial variability. However, little research has been done that address the spatial patterns of soil properties under different degradation degrees of alpine meadow of the Qinghai-Tibetan Plateau although these changes were important to water and heat study and modelling of land surface. 296 soil surface (0-10 cm) samples were collected using grid sampling design from three different degraded alpine meadow regions (1 km2). Then soil water content (SWC) and organic carbon content (OCC) were measured. Classical statistical and geostatistical methods were employed to study the spatial heterogeneities of SWC and OCC under different degradation degrees (Non-degraded ND, moderately degraded MD, extremely degraded ED) of alpine meadow. Results show that both SWC and OCC of alpine meadow were normally distributed with the exception of SWC under ED. On average, both SWC and OCC of alpine meadow decreased in the order that ND > MD > ED. For nugget ratios, SWC and OCC of alpine meadow showed increasing spatial dependence tendency from ND to ED. For the range of spatial variation, both SWC and OCC of alpine meadow showed increasing tendency in distance with the increasing degree of degradation. In all, the degradation of alpine meadow has significant impact on spatial heterogeneities of SWC and OCC of alpine meadow. With increasing of alpine meadow degradation, soil water condition and nutrient condition become worse, and their distributions in spatial become unevenly.
Do we really use rainfall observations consistent with reality in hydrological modelling?
NASA Astrophysics Data System (ADS)
Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves
2017-04-01
Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.
Soil Erosion as a stochastic process
NASA Astrophysics Data System (ADS)
Casper, Markus C.
2015-04-01
The main tools to provide estimations concerning risk and amount of erosion are different types of soil erosion models: on the one hand, there are empirically based model concepts on the other hand there are more physically based or process based models. However, both types of models have substantial weak points. All empirical model concepts are only capable of providing rough estimates over larger temporal and spatial scales, they do not account for many driving factors that are in the scope of scenario related analysis. In addition, the physically based models contain important empirical parts and hence, the demand for universality and transferability is not given. As a common feature, we find, that all models rely on parameters and input variables, which are to certain, extend spatially and temporally averaged. A central question is whether the apparent heterogeneity of soil properties or the random nature of driving forces needs to be better considered in our modelling concepts. Traditionally, researchers have attempted to remove spatial and temporal variability through homogenization. However, homogenization has been achieved through physical manipulation of the system, or by statistical averaging procedures. The price for obtaining this homogenized (average) model concepts of soils and soil related processes has often been a failure to recognize the profound importance of heterogeneity in many of the properties and processes that we study. Especially soil infiltrability and the resistance (also called "critical shear stress" or "critical stream power") are the most important empirical factors of physically based erosion models. The erosion resistance is theoretically a substrate specific parameter, but in reality, the threshold where soil erosion begins is determined experimentally. The soil infiltrability is often calculated with empirical relationships (e.g. based on grain size distribution). Consequently, to better fit reality, this value needs to be corrected experimentally. To overcome this disadvantage of our actual models, soil erosion models are needed that are able to use stochastic directly variables and parameter distributions. There are only some minor approaches in this direction. The most advanced is the model "STOSEM" proposed by Sidorchuk in 2005. In this model, only a small part of the soil erosion processes is described, the aggregate detachment and the aggregate transport by flowing water. The concept is highly simplified, for example, many parameters are temporally invariant. Nevertheless, the main problem is that our existing measurements and experiments are not geared to provide stochastic parameters (e.g. as probability density functions); in the best case they deliver a statistical validation of the mean values. Again, we get effective parameters, spatially and temporally averaged. There is an urgent need for laboratory and field experiments on overland flow structure, raindrop effects and erosion rate, which deliver information on spatial and temporal structure of soil and surface properties and processes.
Predicting radiocaesium sorption characteristics with soil chemical properties for Japanese soils.
Uematsu, Shinichiro; Smolders, Erik; Sweeck, Lieve; Wannijn, Jean; Van Hees, May; Vandenhove, Hildegarde
2015-08-15
The high variability of the soil-to-plant transfer factor of radiocaesium (RCs) compels a detailed analysis of the radiocaesium interception potential (RIP) of soil, which is one of the specific factors ruling the RCs transfer. The range of the RIP values for agricultural soils in the Fukushima accident affected area has not yet been fully surveyed. Here, the RIP and other major soil chemical properties were characterised for 51 representative topsoils collected in the vicinity of the Fukushima contaminated area. The RIP ranged a factor of 50 among the soils and RIP values were lower for Andosols compared to other soils, suggesting a role of soil mineralogy. Correlation analysis revealed that the RIP was most strongly and negatively correlated to soil organic matter content and oxalate extractable aluminium. The RIP correlated weakly but positively to soil clay content. The slope of the correlation between RIP and clay content showed that the RIP per unit clay was only 4.8 mmol g(-1) clay, about threefold lower than that for clays of European soils, suggesting more amorphous minerals and less micaceous minerals in the clay fraction of Japanese soils. The negative correlation between RIP and soil organic matter may indicate that organic matter can mask highly selective sorption sites to RCs. Multiple regression analysis with soil organic matter and cation exchange capacity explained the soil RIP (R(2)=0.64), allowing us to map soil RIP based on existing soil map information. Copyright © 2015 Elsevier B.V. All rights reserved.
Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods
NASA Astrophysics Data System (ADS)
Shi, Fang; Peng, Xiang; Liu, Huan; Hu, Yafei; Liu, Zheng; Li, Eric
2018-03-01
Underground pipelines are subject to severe distress from the surrounding expansive soil. To investigate the structural response of water mains to varying soil movements, field data, including pipe wall strains in situ soil water content, soil pressure and temperature, was collected. The research on monitoring data analysis has been reported, but the relationship between soil properties and pipe deformation has not been well-interpreted. To characterize the relationship between soil property and pipe deformation, this paper presents a super learning based approach combining feature selection algorithms to predict the water mains structural behavior in different soil environments. Furthermore, automatic variable selection method, e.i. recursive feature elimination algorithm, were used to identify the critical predictors contributing to the pipe deformations. To investigate the adaptability of super learning to different predictive models, this research employed super learning based methods to three different datasets. The predictive performance was evaluated by R-squared, root-mean-square error and mean absolute error. Based on the prediction performance evaluation, the superiority of super learning was validated and demonstrated by predicting three types of pipe deformations accurately. In addition, a comprehensive understand of the water mains working environments becomes possible.
Modelling soil properties in a crop field located in Croatia
NASA Astrophysics Data System (ADS)
Bogunovic, Igor; Pereira, Paulo; Millan, Mesic; Percin, Aleksandra; Zgorelec, Zeljka
2016-04-01
Development of tillage activities had negative effects on soil quality as destruction of soil horizons, compacting and aggregates destruction, increasing soil erosion and loss of organic matter. For a better management in order to mitigate the effects of intensive soil management in land degradation it is fundamental to map the spatial distribution of soil properties (Brevik et al., 2016). The understanding the distribution of the variables in space is very important for a sustainable management, in order to identify areas that need a potential intervention and decrease the economic losses (Galiati et al., 2016). The objective of this work is study the spatial distribution of some topsoil properties as clay, fine silt, coarse silt, fine sand, coarse sand, penetration resistance, moisture and organic matter in a crop field located in Croatia. A grid with 275x25 (625 m2) was designed and a total of 48 samples were collected. Previous to data modelling, data normality was checked using the Shapiro wilk-test. As in previous cases (Pereira et al., 2015), data did not followed the normal distribution, even after a logarithmic (Log), square-root, and box cox transformation. Thus, for modeling proposes, we used the log transformed data, since was the closest to the normality. In order to identify groups among the variables we applied a principal component analysis (PCA), based on the correlation matrix. On average clay content was 15.47% (±3.23), fine silt 24.24% (±4.08), coarse silt 35.34% (±3.12), fine sand 20.93% (±4.68), coarse sand 4.02% (±1.69), penetration resistance 0.66 MPa (±0.28), organic matter 1.51% (±0.25) and soil moisture 32.04% (±3.27). The results showed that the PCA identified three factors explained at least one of the variables. The first factor had high positive loadings in soil clay, fine silt and organic matter and a high negative loading in fine sand. The second factor had high positive loadings in coarse sand and moisture and a high negative loading in coarse silt. Finally, the factor 3 had a positive loading in penetration resistance. The loadings of these three factors were mapped using ordinary kriging method. The analysis of incremental spatial correlation identified that the highest spatial correlation in the factor 1 was identified at 41.87 m, in factor 2 at 75.61 m and factor 3 at 143.9 m. In the case of factor 2, the maximum peak of spatial autocorrelation was significant at a p<0.05. This showed that the variable has a random distribution, as confirmed with the Moran's I spatial correlation analysis. In relation to the other factors the maximum peaks were significantly clustered at a p<0.001. These results suggested that the each factor has a different spatial pattern and the studied soil properties explained by each factor had a different spatial distribution. References Breivik, E., Baumgarten, A., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Jordán, A. Soil mapping, classification, and modelling: history and future directions. Geoderma, 264, Part B, 256-274. Galiati, A., Gristina, L., Crescimanno, Barone, E., Novara, A. (2016) Towards more efficient incentives for agri-environment measures in degraded and eroded vineyards. Land Degradation and Development, DOI: 10.1002/ldr.2389 Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2015) Modelling the impacts of wildfire on ash thickness in a short-term period, Land Degradation and Development, 26, 180-192.
N2O fluxes at the soil-atmosphere interface in various ecosystems and the global N2O budget
NASA Technical Reports Server (NTRS)
Banin, Amos
1987-01-01
The overall purpose of this research task is to study the effects of soil properties and ecosystem variables on N2O exchanges at the soil-atmosphere interface, and to assess their effects on the globle N2O budget. Experimental procedures are implemented in various sites to measure the source/sink relations of N2O at the soil-atmosphere interface over prolonged periods of time as part of the research of biogeochemical cycling in terrestrial ecosystems. A data-base for establishing quantitative correlations between N2O fluxes and soil and environmental parameters that are of potential use for remote sensing, is being developed.
NASA Astrophysics Data System (ADS)
Barrere, Mathieu; Domine, Florent; Decharme, Bertrand; Morin, Samuel; Vionnet, Vincent; Lafaysse, Matthieu
2017-09-01
Climate change projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.
Drivers of small scale variability in soil-atmosphere fluxes of CH4, N2O and CO2 in a forest soil
NASA Astrophysics Data System (ADS)
Maier, Martin; Nicolai, Clara; Wheeler, Denis; Lang, Friedeike; Paulus, Sinikka
2016-04-01
Soil-atmosphere fluxes of CH4, N2O and CO2 can vary on different spatial scales, on large scales between ecosystems but also within apparently homogenous sites. While CO2 and CH4 consumption is rather evenly distibuted in well aerated soils, the production of N2O and CH4 seems to occur at hot spots that can be associated with anoxic or suboxic conditions. Small-scale variability in soil properties is well-known from field soil assesment, affecting also soil aeration and thus theoretically, greenhouse gas fluxes. In many cases different plant species are associated with different soil conditions and vegetation mapping should therefor combined with soil mapping. Our research objective was explaining the small scale variability of greenhouse gas fluxes in an apparently homogeneous 50 years old Scots Pine stand in a former riparian flood plain.We combined greenhouse gas measurements and soil physical lab measurments with field soil assessment and vegetation mapping. Measurements were conducted with at 60 points at a plot of 30 X 30 m at the Hartheim monitoring site (SW Germany). For greenhouse gas measurements a non-steady state chamber system and laser analyser, and a photoacoustic analyser were used. Our study shows that the well aerated site was a substantial sink for atmospheric CH4 (-2.4 nmol/m² s) and also a for N2O (-0.4 nmol/m² s), but less pronounced, whereas CO2 production was a magnitude larger (2.6 μmol/m² s). The spatial variability of the CH4 consumption of the soils could be explained by the variability of the soil gas diffusivity (measured in situ + using soil cores). Deviations of this clear trend were only observed at points where decomposing woody debris was directly under the litter layer. Soil texture ranged from gravel, coarse sand, fine sand to pure silt, with coarser texture having higher soil gas diffusivity. Changes in texture were rather abrupt at some positions or gradual at other positions, and were well reflected in the vegetation structure. On patches of gravel and coarse sand there was hardly any ground vegatation, and a shrublayer was found only at silty patches Our results indicate that a stratification and regionalisation approach based on vegetation structure and soil texture represents a promising tool for the adjustment of sampling designs for soil gas flux measurement. Acknowledgement This research was financially supported by the project DFG (MA 5826/2-1).
Palanivell, Perumal; Ahmed, Osumanu Haruna; Ab Majid, Nik Muhamad; Jalloh, Mohamadu Boyie; Susilawati, Kasim
2015-01-01
High cation exchange capacity and organic matter content of crude humic substances from compost could be exploited to reduce ammonia loss from urea and to as well improve rice growth and soil chemical properties for efficient nutrients utilization in lowland rice cultivation. Close-dynamic air flow system was used to determine the effects of crude humic substances on ammonia volatilization. A pot experiment was conducted to determine the effects of crude humic substances on rice plant growth, nutrients uptake, nutrients recovery, and soil chemical properties using an acid soil mixed with three rates of crude humic substances (20, 40, and 60 g pot(-1)). Standard procedures were used to evaluate rice plant dry matter production, nutrients uptake, nutrients recovery, and soil chemical properties. Application of crude humic substances increased ammonia volatilization. However, the lowest rate of crude humic substances (20 g pot(-1)) significantly improved total dry matter, nutrients uptake, nutrients recovery, and soil nutrients availability compared with crude humic substances (40 and 60 g pot(-1)) and the normal fertilization. Apart from improving growth of rice plants, crude humic substances can be used to ameliorate acid soils in rice cultivation. The findings of this study are being validated in our ongoing field trials.
Palanivell, Perumal; Ahmed, Osumanu Haruna; Ab Majid, Nik Muhamad; Jalloh, Mohamadu Boyie; Susilawati, Kasim
2015-01-01
High cation exchange capacity and organic matter content of crude humic substances from compost could be exploited to reduce ammonia loss from urea and to as well improve rice growth and soil chemical properties for efficient nutrients utilization in lowland rice cultivation. Close-dynamic air flow system was used to determine the effects of crude humic substances on ammonia volatilization. A pot experiment was conducted to determine the effects of crude humic substances on rice plant growth, nutrients uptake, nutrients recovery, and soil chemical properties using an acid soil mixed with three rates of crude humic substances (20, 40, and 60 g pot−1). Standard procedures were used to evaluate rice plant dry matter production, nutrients uptake, nutrients recovery, and soil chemical properties. Application of crude humic substances increased ammonia volatilization. However, the lowest rate of crude humic substances (20 g pot−1) significantly improved total dry matter, nutrients uptake, nutrients recovery, and soil nutrients availability compared with crude humic substances (40 and 60 g pot−1) and the normal fertilization. Apart from improving growth of rice plants, crude humic substances can be used to ameliorate acid soils in rice cultivation. The findings of this study are being validated in our ongoing field trials. PMID:25977938
Soil recovery across a chronosequence of restored wetlands in the Florida Everglades
NASA Astrophysics Data System (ADS)
Wang, Qibing; Li, Yuncong; Zhang, Min
2015-12-01
The restoration project in the Hole-in-the-Donut of Everglades National Park in Florida, USA is to reestablish native wetlands by complete removal of the invasive plants and the associated soil. However, there is little information available about changes in properties of the newly formed Marl soils in restored wetlands. In this study, we measured soil physicochemical properties, soil enzymatic activities, and stable isotopes of carbon (δ13C) in plants and soil organic carbon (SOC) in an undisturbed natural wetland (UNW) and three wetlands restored respectively in 1989, 1996 and 1999 (WR89, WR96 and WR99). The older restored wetlands (WR89 and WR96) are characterized by greater SOC and mineral nitrogen. The values of soil dehydrogenase and phosphatase activities in the four wetlands follow the order: UNW > WR89 > WR96 > WR99, and are consistent with changes in vegetation coverage. The principal component analysis shows that dehydrogenase and phosphatase activities are the vital variables contributing to the soil of UNW. The similar δ13C values of SOC and plants in the restored wetlands suggest the formation of SOC during restoration is mainly derived from the associated plants. These results indicate that the newly restored soils develop toward the soil in the UNW with time since restoration.
Soil recovery across a chronosequence of restored wetlands in the Florida Everglades.
Wang, Qibing; Li, Yuncong; Zhang, Min
2015-12-01
The restoration project in the Hole-in-the-Donut of Everglades National Park in Florida, USA is to reestablish native wetlands by complete removal of the invasive plants and the associated soil. However, there is little information available about changes in properties of the newly formed Marl soils in restored wetlands. In this study, we measured soil physicochemical properties, soil enzymatic activities, and stable isotopes of carbon (δ(13)C) in plants and soil organic carbon (SOC) in an undisturbed natural wetland (UNW) and three wetlands restored respectively in 1989, 1996 and 1999 (WR89, WR96 and WR99). The older restored wetlands (WR89 and WR96) are characterized by greater SOC and mineral nitrogen. The values of soil dehydrogenase and phosphatase activities in the four wetlands follow the order: UNW > WR89 > WR96 > WR99, and are consistent with changes in vegetation coverage. The principal component analysis shows that dehydrogenase and phosphatase activities are the vital variables contributing to the soil of UNW. The similar δ(13)C values of SOC and plants in the restored wetlands suggest the formation of SOC during restoration is mainly derived from the associated plants. These results indicate that the newly restored soils develop toward the soil in the UNW with time since restoration.
NASA Astrophysics Data System (ADS)
Ferré, Chiara; Comolli, Roberto
2015-04-01
The study area is located in an abandoned meander of the Oglio river (southern Lombardy, Italy), with young soils of alluvial origin (Calcaric Fluvisols). During 2002, in an area covering 20 hectares, a tree plant for wood production was realized (oak, hornbeam, ash, alder, and walnut; poplar only in the first part of the growth cycle). Objective of the study was to verify the existence of correlations between tree growth and soil characteristics. In 2004, the soil was sampled at 126 points, according to a regular grid, taking the surface soil horizon (Ap). The collected soil samples were analyzed in laboratory, measuring pH in H2O and KCl, texture, total carbonates, soil organic C (SOC), available P (Olsen), and exchangeable K. The pH in H2O varies between 7.7 and 8.1; the pH in KCl varies between 7.2 and 7.7; the more frequent particle-size classes are loam and sandy loam; SOC varies between 0.4 and 1.1%; total carbonates from 23 to 45%; exchangeable K between 0.01 and 0.25 cmol(+) kg-1; available P between 1.2 and 16.8 mg kg-1. At a distance of 12 years, in 2014, diameters at breast height of all the trees (2513 in total) were measured and their height was estimated on the basis of empirical equations obtained for each species, in order to calculate the tree volume. Spatial variability of soil properties was evaluated and mapped using multivariate geostatistical techniques. The analyses revealed the presence of different scales of spatial variation: micro-scale, short range scale (about 80 m for texture) and long range scale (about 220 m for texture). The spatial pattern of most soil properties (mainly texture and total carbonates) was probably associated with fluvial depositional processes. To evaluate soil-plant relationships, soil characteristics were collocated into the plant data set by estimating specific soil properties at each individual tree location. Soil spatial variability was reflected by the differences in plant growth. Statistical analysis of the collected data highlighted a number of statistically significant correlations between tree growth and soil features: clay content and total carbonates were almost always negatively correlated with tree growth; sand content, pH in KCl, available P and exchangeable K were almost always positively correlated; SOC content was negatively correlated, but only for oak.
VARIABLE RATE APPLICATION OF SOIL HERBICIDES IN ARABLE CROPS: FROM THEORY TO PRACTICE.
Heijting, S; Kempenaar, C
2014-01-01
Soil herbicides are applied around crop emergence and kill germinating weeds in the surface layer of the soil. These herbicides play an important role in the chemical management of weeds in major arable crops. From an environmental point of view there is a clear need for smarter application of these chemicals. This paper presents research done in The Netherlands on Variable Rate Application (VRA) of soil herbicides by taking into account spatial variation of the soil. Herbicides adsorbed to soil parameters such as clay or organic matter are not available for herbicidal activity. Decision Support Rules (DSR) describe the relation between the soil parameter and herbicide dosage needed for effectively controlling weeds. Research methods such as greenhouse trials, models and on farm research to develop DSR are discussed and results are presented. Another important ingredient for VRA of soil herbicides is an accurate soil map of the field. Sampling and subsequent interpolation is costly. Soil scans measuring a proxy that is subsequently translated into soil properties such as clay fraction and soil organic matter content offer a quicker way to achieve such maps but validation is needed. DSR is applied to the soil map to get the variable dosage map. The farmer combines this map with the routing, spray volume and spray boom width in the Farm Management Information System (FMIS), resulting in a task file. This task file can subsequently be read by the board computer resulting in a VRA spray map. Reduction in soil herbicide depends on the DSR, the spatial variation and pattern of the soil, the spatial configuration of the routing and the technical advances of the spray equipment. Recently, within the framework the Programma Precisie Landbouw, first steps were made to test and implement this in practice. Currently, theory and practice of VRA of soil herbicides is developed within the research program IJKakker in close cooperation with pioneering farmers in The Netherlands.
NASA Astrophysics Data System (ADS)
Marinho, M. D.; Paz-Gonzalez, A.; Dafonte, J. D.; Armesto, M. V.; Raposo, J. R.
2012-12-01
Spatial characterization of the variability of soil properties is a central point in site-specific agricultural management and precision agriculture. Geospatial measures of geophysical attributes are useful not only to rapidly characterize the spatial variability of soil properties but also for soil sampling optimization. This work reports partial results obtained at an experimental parcel under pasture located at Castro de Ribeira do Lea (Lugo/ Galicia/ Spain). An ECa automated survey was conducted in September 2011 employing an EM-38 DD (Geonics Ltd.) installed in a nonmetallic car, according to parallel lines spaced 10m one from each other and oriented at the east-west direction. The ECa values were recorded every second with a field computer and the locations were geo-referenced using a GPS. The entire survey was carried out in 1hour and 45 minutes and corrections due to differences in temperature were made. A total of 9.581 ECa registers were retained, configuring a sampling intensity of approximately 1 register per 1.5 m2. Employing the software ESAP 2.35 and the computational tool ESAP-RSSD, eighty positions were selected at the field to extract disturbed and undisturbed soil samples at two depths: 0.0-0.2m, 0.2-0.4m. Ten physical attributes (clay, silt, total sand, coarse sand and fine sand contents, soil bulk density, particle density, total porosity, soil water content, percentage of gravels) and 17 chemical attributes (soil organic matter-SOM, pH, P, K, Ca, Mg, Al, H+Al, Sum of bases-S, Cation exchange capacity-CEC, Base saturation-V%, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) were determined. The relationship between the geophysical variables and the soil attributes was performed using statistical and spatial analysis. There were significant correlations (p<0.01) between the geophysical variables and the textural attributes clay, silt, total sand and coarse sand contents. The biggest correlation (0.5623) was between ECa-V (vertical component) and clay content. Also, significant correlations (p<0.05) were found between the ECa-V and soil bulk density, total porosity, percentage of gravels and soil water content. Considering the chemical attributes, significant correlations (p< 0.01) were found between ECa-V and SOM and Cd, and between ECa-H (horizontal component) and SOM and Fe. Other significant correlations (p<0.05) were found between ECa-V and 6 soil chemical attributes: P, Ca, S, Fe, Ni and Pb. The biggest correlation was between ECa-V and SOM (-0.5942). In resume, clay content, SOM, Cd and Fe are the soil attributes better correlated with the observed variation of the ECa at the field. Additional analysis should be performed to compare the spatial patterns of these soil attributes and the ECa as a tool to proper define management zones in the area.
Chang, Yanping; Bu, Xiangpan; Niu, Weibo; Xiu, Yu; Wang, Huafang
2013-01-01
Relatively little information is available regarding the variability of microbial communities inhabiting deeper soil layers. We investigated the distribution of soil microbial communities down to 1.2 m in 5-year-old Robinia pseudoacacia 'Idaho' soil by 454 sequencing of the 16S RNA gene. The average number of sequences per sample was 12,802. The Shannon and Chao 1 indices revealed various relative microbial abundances and even distribution of microbial diversity for all evaluated sample depths. The predicted diversity in the topsoil exceeded that of the corresponding subsoil. The changes in the relative abundance of the major soil bacterial phyla showed decreasing, increasing, or no consistent trends with respect to sampling depth. Despite their novelty, members of the new candidate phyla OD1 and TM7 were widespread. Environmental variables affecting the bacterial community within the environment appeared to differ from those reported previously, especially the lack of detectable effect from pH. Overall, we found that the overall relative abundance fluctuated with the physical and chemical properties of the soil, root system, and sampling depth. Such information may facilitate forest soil management.
Effects of the chemical environment on the spectroscopic properties of clays: Applications for Mars
NASA Technical Reports Server (NTRS)
Bishop, Janice L.; Pieters, Carle M.
1992-01-01
Laboratory studies of Mars soil analogs pose unique problems, since soils interact readily with their environment and exhibit variable characteristics depending on the environment. We have performed a series of experiments focusing on the spectral properties of clays and how they vary as a function of composition and environment, including examination of fundamental as well as overtone absorptions, that occur in the mid- and near-IR, respectively. Smectite clays have been selected in our laboratory experiments as a primary surface analog for Mars because of their compatibility with results of the Viking biology experiments, their stability under current martian conditions, and their compatibility with reflectance spectra of Mars. We prepared a number of monoionic montmorillonites in order to examine the influence of cations on the water molecules in the clay interlayer region. Moessbauer spectra of several montmorillonites with variable amounts of interlayer iron confirm the presence of ferrihydrite.
NASA Astrophysics Data System (ADS)
Baker, I. T.; Prihodko, L.; Vivoni, E. R.; Denning, A. S.
2017-12-01
Arid and semiarid regions represent a large fraction of global land, with attendant importance of surface energy and trace gas flux to global totals. These regions are characterized by strong seasonality, especially in precipitation, that defines the level of ecosystem stress. Individual plants have been observed to respond non-linearly to increasing soil moisture stress, where plant function is generally maintained as soils dry down to a threshold at which rapid closure of stomates occurs. Incorporating this nonlinear mechanism into landscape-scale models can result in unrealistic binary "on-off" behavior that is especially problematic in arid landscapes. Subsequently, models have `relaxed' their simulation of soil moisture stress on evapotranspiration (ET). Unfortunately, these relaxations are not physically based, but are imposed upon model physics as a means to force a more realistic response. Previously, we have introduced a new method to represent soil moisture regulation of ET, whereby the landscape is partitioned into `BINS' of soil moisture wetness, each associated with a fractional area of the landscape or grid cell. A physically- and observationally-based nonlinear soil moisture stress function is applied, but when convolved with the relative area distribution represented by wetness BINS the system has the emergent property of `smoothing' the landscape-scale response without the need for non-physical impositions on model physics. In this research we confront BINS simulations of Bowen ratio, soil moisture variability and trace gas flux with soil moisture and eddy covariance observations taken at the Jornada LTER dryland site in southern New Mexico. We calculate the mean annual wetting cycle and associated variability about the mean state and evaluate model performance against this variability and time series of land surface fluxes from the highly instrumented Tromble Weir watershed. The BINS simulations capture the relatively rapid reaction to wetting events and more prolonged response to drying cycles, as opposed to binary behavior in the control.
NASA Astrophysics Data System (ADS)
Gil, Juan; Priego-Navas, Mercedes; Zavala, Lorena M.; Jordán, Antonio
2013-04-01
Generally, literature shows that the high variability of rainfall-induced soil erosion is related to climatic differences, relief, soil properties and land use. Very different runoff rates and soil loss values have been reported in Mediterranean cropped soils depending on soil management practices, but also in soils under natural vegetation types. OBJECTIVES The aim of this research is to study the relationships between soil erosion risk, soil use and soil properties in three typical Mediterranean areas from southern Spain: olive groves under conventional tillage, minimum tillage and no-till practices, and soils under natural vegetation. METHODS Rainfall simulation experiments have been carried out in order to assess the relationship between soil erosion risk, land use, soil management and soil properties in olive-cropped soils under different types of management and soils under natural vegetation type from Mediterranean areas in southern Spain RESULTS Results show that mean runoff rates decrease from 35% in olive grove soils under conventional tillage to 25% in olive (Olea europaea) grove soils with minimum tillage or no-till practices, and slightly over 22% in soils under natural vegetation. Moreover, considering the different vegetation types, runoff rates vary in a wide range, although runoff rates from soils under holm oak (Quercus rotundifolia), 25.70%, and marginal olive groves , 25.31%, are not significantly different. Results from soils under natural vegetation show that the properties and nature of the organic residues play a role in runoff characteristics, as runoff rates above 50% were observed in less than 10% of the rainfall simulations performed on soils with a organic layer. In contrast, more than half of runoff rates from bare soils reached or surpassed 50%. Quantitatively, average values for runoff water losses increase up to 2.5 times in unprotected soils. This is a key issue in the study area, where mean annual rainfall is above 600 mm. Regarding soil properties, the analysis shows that organic matter from soils under minimum tillage or no-till is strongly related with runoff, the amount of sediments in runoff and soil loss. In soils from olive groves, the amount of sediments in runoff was significantly related to soil pH. Moreover, for olive-cropped soils under conventional tillage, soil loss is strongly related with clayey texture, which is characteristic of these soils. Concerning this, the relationship between soil loss and coarse sand contents is highly significant, and shows that medium-sized soil particles are most prone to detachment and transport by runoff. Thus, the average content of these fractions in soils under conventional management is more than two times that from olive groves under minimal or no tillage, which are more coarsely textured. In fine-textured soils, hydraulic conductivity is reduced, thus increasing soil erosion risk. In addition, in sandy and silty soils with low clay content, infiltration rates are high even when soil sealing is observed. At the scale of this experiment, runoff generation and soil erosion risk decrease significantly in areas under natural vegetation, with lower clay contents
NASA Astrophysics Data System (ADS)
Naylor, S.; Gustin, A. R.; Ellett, K. M.
2012-12-01
Weather stations that collect reliable, sustained meteorological data sets are becoming more widely distributed because of advances in both instrumentation and data server technology. However, sites collecting soil moisture and soil temperature data remain sparse with even fewer locations where complete meteorological data are collected in conjunction with soil data. Thanks to the advent of sensors that collect continuous in-situ thermal properties data for soils, we have gone a step further and incorporated thermal properties measurements as part of hydrologic instrument arrays in central and northern Indiana. The coupled approach provides insights into the variability of soil thermal conductivity and diffusivity attributable to geologic and climatological controls for various hydrogeologic settings. These data are collected to facilitate the optimization of ground-source heat pumps (GSHPs) in the glaciated Midwest by establishing publicly available data that can be used to parameterize system design models. A network of six monitoring sites was developed in Indiana. Sensors that determine thermal conductivity and diffusivity using radial differential temperature measurements around a heating wire were installed at 1.2 meters below ground surface— a typical depth for horizontal GSHP systems. Each site also includes standard meteorological sensors for calculating reference evapotranspiration following the methods by the Food and Agriculture Organization (FAO) of the United Nations. Vadose zone instrumentation includes time domain reflectometry soil-moisture and temperature sensors installed at 0.3-meter depth intervals down to a 1.8-meter depth, in addition to matric potential sensors at 0.15, 0.3, 0.6, and 1.2 meters. Cores collected at 0.3-meter intervals were analyzed in a laboratory for grain size distribution, bulk density, thermal conductivity, and thermal diffusivity. Our work includes developing methods for calibrating thermal properties sensors based on known standards and comparing measurements from transient line heat source devices. Transform equations have been developed to correct in-situ measurements of thermal conductivity and comparing these results with soil moisture data indicates that thermal conductivity can increase by as much as 25 percent during wetting front propagation. Thermal dryout curves have also been modeled based on laboratory conductivity data collected from core samples to verify field measurements, and alternatively, temperature profile data are used to calibrate near-surface temperature gradient models. We compare data collected across various spatial scales to assess the potential for upscaling near-surface thermal regimes based on available soils data. A long-term goal of the monitoring effort is to establish continuous data sets that determine the effect of climate variability on soil thermal properties such that expected ranges in thermal conductivity can be used to determine optimal ground-coupling loop lengths for GSHP systems.
Beyond clay: Towards an improved set of variables for predicting soil organic matter content
Rasmussen, Craig; Heckman, Katherine; Wieder, William R.; Keiluweit, Marco; Lawrence, Corey R.; Berhe, Asmeret Asefaw; Blankinship, Joseph C.; Crow, Susan E.; Druhan, Jennifer; Hicks Pries, Caitlin E.; Marin-Spiotta, Erika; Plante, Alain F.; Schadel, Christina; Schmiel, Joshua P.; Sierra, Carlos A.; Thompson, Aaron; Wagai, Rota
2018-01-01
Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO2 to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.
Synthesis of soil-hydraulic properties and infiltration timescales in wildfire-affected soils
Ebel, Brian A.; Moody, John A.
2017-01-01
We collected soil-hydraulic property data from the literature for wildfire-affected soils, ash, and unburned soils. These data were used to calculate metrics and timescales of hydrologic response related to infiltration and surface runoff generation. Sorptivity (S) and wetting front potential (Ψf) were significantly different (lower) in burned soils compared with unburned soils, whereas field-saturated hydraulic conductivity (Kfs) was not significantly different. The magnitude and duration of the influence of capillarity during infiltration was greatly reduced in burned soils, causing faster ponding times in response to rainfall. Ash had large values of S and Kfs but moderate values of Ψf, compared with unburned and burned soils, indicating ash has long ponding times in response to rainfall. The ratio of S2/Kfs was nearly constant (~100 mm) for unburned soils but more variable in burned soils, suggesting that unburned soils have a balance between gravity and capillarity contributions to infiltration that may depend on soil organic matter, whereas in burned soils the gravity contribution to infiltration is greater. Changes in S and Kfs in burned soils act synergistically to reduce infiltration and accelerate and amplify surface runoff generation. Synthesis of these findings identifies three key areas for future research. First, short timescales of capillary influences on infiltration indicate the need for better measurements of infiltration at times less than 1 min to accurately characterize S in burned soils. Second, using parameter values, such as Ψf, from unburned areas could produce substantial errors in hydrologic modeling when used without adjustment for wildfire effects, causing parameter compensation and resulting underestimation of Kfs. Third, more thorough measurement campaigns that capture soil-structural changes, organic matter impacts, quantitative water repellency trends, and soil-water content along with soil-hydraulic properties could drive the development of better techniques for numerically simulating infiltration in burned areas.
Gillison, Andrew N; Asner, Gregory P; Fernandes, Erick C M; Mafalacusser, Jacinto; Banze, Aurélio; Izidine, Samira; da Fonseca, Ambrósio R; Pacate, Hermenegildo
2016-07-15
Sustainable biodiversity and land management require a cost-effective means of forecasting landscape response to environmental change. Conventional species-based, regional biodiversity assessments are rarely adequate for policy planning and decision making. We show how new ground and remotely-sensed survey methods can be coordinated to help elucidate and predict relationships between biodiversity, land use and soil properties along complex biophysical gradients that typify many similar landscapes worldwide. In the lower Zambezi valley, Mozambique we used environmental, gradient-directed transects (gradsects) to sample vascular plant species, plant functional types, vegetation structure, soil properties and land-use characteristics. Soil fertility indices were derived using novel multidimensional scaling of soil properties. To facilitate spatial analysis, we applied a probabilistic remote sensing approach, analyzing Landsat 7 satellite imagery to map photosynthetically active and inactive vegetation and bare soil along each gradsect. Despite the relatively low sample number, we found highly significant correlations between single and combined sets of specific plant, soil and remotely sensed variables that permitted testable spatial projections of biodiversity and soil fertility across the regional land-use mosaic. This integrative and rapid approach provides a low-cost, high-return and readily transferable methodology that permits the ready identification of testable biodiversity indicators for adaptive management of biodiversity and potential agricultural productivity. Copyright © 2016 Elsevier Ltd. All rights reserved.
A probabilistic approach to modeling erosion for spatially-varied conditions
William J. Elliot; Peter R. Robichaud; C. D. Pannkuk
2001-01-01
In the years following a major forest disturbance, such as fire, the erosion rate is greatly influenced by variability in weather, in soil properties, and in spatial distribution. This paper presents a method to incorporate these variabilities into the erosion rate predicted by the Water Erosion Prediction Project model. It appears that it is not necessary to describe...
Mathur, Manish; Sundaramoorthy, S
2012-01-01
Synergism and antagonism impact of different plant metabolites present in crude fruit extract of Tribulus terrestris 'the herbal Viagra' have been studied. Variability in plant composition, biomass and metabolites concentration in different modules was significantly contributed by spatial factor. However the edhaphic parameters also changes with both spatial and temporal factors significantly. Fruit is the officinal part and the fruit production significantly related with soil nitrogen (P<0.01), whereas the soil nitrogen and pH also influenced the alkaloid content in fruit (P<0.05). The linear relation between fruit protein and fruit alkaloid (P<0.01) also observed and the relationship in between different soil parameters were established. Bioassay work confirmed its aphrodisiac properties, and site III is suggested for maximum biomass and high concentration of different metabolites.
NASA Astrophysics Data System (ADS)
Scott, C. P.; Lohman, R. B.
2015-12-01
InSAR-based studies of the seismic cycle have focused primarily on the interferometric phase observations, which place constraints on the amount of uplift or subsidence of the ground surface. Recently, coseismic InSAR coherence has also been used to rapidly identify urban damage, surface ruptures, cracking, and soil liquefaction. Here we demonstrate that time-variable correlation and amplitude data contain additional information about surficial processes and material properties that may affect ground deformation and seismic hazard. In the use of correlation for hazard response, distinguishing the coseismic signal from other changes in surface properties associated with variations in soil moisture content, vegetation and snow cover, and wind is critical. Building SAR-based catalogues of ground properties will therefore improve the reliability of rapid response and aid in the designing of future SAR missions to better map surface ruptures, off-fault deformation, and coseismic damage. In this project, we characterize the seasonal variations in the soil moisture content in the Northern Chilean Coastal Cordillera and Southern California. The extreme climate of the Atacama Desert characterized by hyperaridity and coastal fog during the non-summer months creates an ideal landscape for exploring surface properties. We produce interferograms using L-band ALOS data (λ = 23.6 cm) that span 46 days to three years and have perpendicular baselines less than 1500 m. We observe a strong seasonal dependence on correlation that extends to the maximum elevation of the fog penetration. Interferograms with only austral summer acquisitions are more correlated than interferograms with one or both acquisitions in the autumn, winter or spring, even when the summer interferograms span multiple years. We propose that the seasonal dependence is due to small changes in the radar path length caused by variable soil moisture content in the very shallow subsurface. We further consider local variations in correlation surrounding aeolian dunes, quebradas or ravines, cities, and salars. We extend our work to include the Owens Valley and Death Valley in California.
Chicken manure enhanced yield and quality of field-grown kale and collard greens.
Antonious, George F; Turley, Eric T; Hill, Regina R; Snyder, John C
2014-01-01
Organic matter and nutrients in municipal sewage sludge (SS) and chicken manure (CM) could be recycled and used for land farming to enhance fertility and physical properties of soils. Three soil management practices were used at Kentucky State University Research Farm, Franklin County, to study the impact of soil amendments on kale (Brassica oleracea cv. Winterbar) and collard (Brassica oleracea cv. Top Bunch) yields and quality. The three soil management practices were: (i) SS mixed with native soil at 15 t acre(-1), (ii) CM mixed with native soil at 15 t acre(-1), and (iii) no-mulch (NM) native soil for comparison purposes. At harvest, collard and kale green plants were graded according to USDA standards. Plants grown in CM and SS amended soil produced the greatest number of U.S. No. 1 grade of collard and kale greens compared to NM native soil. Across all treatments, concentrations of ascorbic acid and phenols were generally greater in kale than in collards. Overall, CM and SS enhanced total phenols and ascorbic acid contents of kale and collard compared to NM native soil. We investigated the chemical and physical properties of each of the three soil treatments that might explain variability among treatments and the impact of soil amendments on yield, phenols, and ascorbic acid contents of kale and collard green grown under this practice.
NASA Astrophysics Data System (ADS)
Novosadova, I.; Zahora, J.; Ruiz Sinoga, J. D.
2009-04-01
In the Mediterranean areas of Southern Spain, unsuitable agricultural practices with adverse environmental conditions (López Bermúdez and Albaladejo, 1990), have led to a permanent degradation and loss of soil fertility. This includes deterioration of the natural plant cover, which protects against erosion by contributing organic matter, the main prerequisite of ecosystem sustainability (Grace et al., 1994). Physico-chemical, microbiological and biochemical soil properties are very responsive and provide immediate and precise information on small changes occurring in soil (Dick and Tabatabai, 1993). There is increasing evidence that such parameters are also sensitive indicators of ecology stress suffered by a soil and its recovery, since microbial activity has a direct influence on the stability and fertility of ecosystems (Smith and Papendick, 1993). One method for recovering degraded soils of such semiarid regions, with their low organic matter content, is to enhance primary productivity and carbon sequestration without any additional nitrogen fertilization and preferably without incorporation of leguminous plants (Martinez Mena et al., 2008). Carbon rich materials can sustain microbial activity and growth, thus enhancing biogeochemical nutrient cycles (Pascual et al., 1997). The present study is focused in the role of physico-chemical and microbial soil properties in Mediterranean environment, in terms of in situ and ex situ microbial transformation of soil carbon and nitrogen, in order to characterise the key soil microbial activities which could strongly affect carbon and nitrogen turnover in soil and hereby soil fertility and soil organic matter "quality". These microbial activities could at unsuitable agricultural practices with adverse environmental conditions induce unfavourable hydrologycal tempo-spatial response. The final results shown modifications in the soil properties studied with the increasing of the aridity. Such changes suppose the soil degradation what make us the existence of soil degradational processes. Physico-chemical properties and soil microbiological activities analysed shown a higher relationship tend to the soil degradation along a pluviometric gradient selected. Biothic and abiothic factors are going to be more degraded conditions according with a reduction of pluviometric conditions. The soil degradation observed across the analysis of the more stable soil properties, that we can denominate from the slow cycle, bring as a consequence an important reduction of the vegetation cover, and therefore in the soil protection, decreasing their soil moisture content and their soil permeability and the cationic exchange capacity, as good key factor to determine the soil health. When these processes take place, an increase of runoff, high pedregosity and crusting may occur in the soil surface. Concerning the regional scale spatial variability, results of experimental field work conducted along a climatic transect, from the Mediterranean climate to the arid zone in the south of Spain, show that: (1) organic matter content, and aggregate size and stability decrease with aridity; (2) the rate of change of these variables along the climatic transect is non-linear and (3) the analysis of the soil properties shown a higher and inverse correlation between soil degradation levels and organic carbon sequestration capacity; (4) the soil respiration were tightly coupled with the carbon compounds available in soil (5) the in situ ammonification was nearly the same along a pluviometric gradient; (6) the nitrification was increasing with aridity identically in control soils, and after the addition of cellulose and raw silk; (7) the contact time of the water with the soil matrix was sufficient to retain NH4+, but insufficient for a retention of NO3-. (8) the key factor influencing the movement of nitrate and thereby promoting the losses of base cations was the frequency and intensity of precipitation not only a soil-internal N surplus. A steplike threshold exists at the semiarid area, which sharply separates the Mediterranean climate and arid ecogeomorphological systems (Lavee et al., 1998). This means that only a relatively small climatic change would be needed to shift the borders between these two systems. Acknowledgement This study was supported by the Research plan No. MSM6215648905, Ministry of Education, Czech Republic.
HDMR methods to assess reliability in slope stability analyses
NASA Astrophysics Data System (ADS)
Kozubal, Janusz; Pula, Wojciech; Vessia, Giovanna
2014-05-01
Stability analyses of complex rock-soil deposits shall be tackled considering the complex structure of discontinuities within rock mass and embedded soil layers. These materials are characterized by a high variability in physical and mechanical properties. Thus, to calculate the slope safety factor in stability analyses two issues must be taken into account: 1) the uncertainties related to structural setting of the rock-slope mass and 2) the variability in mechanical properties of soils and rocks. High Dimensional Model Representation (HDMR) (Chowdhury et al. 2009; Chowdhury and Rao 2010) can be used to carry out the reliability index within complex rock-soil slopes when numerous random variables with high coefficient of variations are considered. HDMR implements the inverse reliability analysis, meaning that the unknown design parameters are sought provided that prescribed reliability index values are attained. Such approach uses implicit response functions according to the Response Surface Method (RSM). The simple RSM can be efficiently applied when less than four random variables are considered; as the number of variables increases, the efficiency in reliability index estimation decreases due to the great amount of calculations. Therefore, HDMR method is used to improve the computational accuracy. In this study, the sliding mechanism in Polish Flysch Carpathian Mountains have been studied by means of HDMR. The Southern part of Poland where Carpathian Mountains are placed is characterized by a rather complicated sedimentary pattern of flysh rocky-soil deposits that can be simplified into three main categories: (1) normal flysch, consisting of adjacent sandstone and shale beds of approximately equal thickness, (2) shale flysch, where shale beds are thicker than adjacent sandstone beds, and (3) sandstone flysch, where the opposite holds. Landslides occur in all flysch deposit types thus some configurations of possible unstable settings (within fractured rocky-soil masses) resulting in sliding mechanisms have been investigated in this study. The reliability indices values drawn from the HDRM method have been compared with conventional approaches as neural networks: the efficiency of HDRM is shown in the case studied. References Chowdhury R., Rao B.N. and Prasad A.M. 2009. High-dimensional model representation for structural reliability analysis. Commun. Numer. Meth. Engng, 25: 301-337. Chowdhury R. and Rao B. 2010. Probabilistic Stability Assessment of Slopes Using High Dimensional Model Representation. Computers and Geotechnics, 37: 876-884.
NASA Astrophysics Data System (ADS)
Fischer, Christine; Hohenbrink, Tobias; Leimer, Sophia; Roscher, Christiane; Ravenek, Janneke; de Kroon, Hans; Kreutziger, Yvonne; Wirth, Christian; Eisenhauer, Nico; Gleixner, Gerd; Weigelt, Alexandra; Mommer, Liesje; Beßler, Holger; Schröder, Boris; Hildebrandt, Anke
2015-04-01
Soil moisture is the dynamic link between climate, soil and vegetation and the dynamics and variation are affected by several often interrelated factors such as soil texture, soil structural parameters (soil organic carbon) and vegetation parameters (belowground- and aboveground biomass). For the characterization and estimation of soil moisture and its variability and the resulting water fluxes and solute transports, the knowledge of the relative importance of these factors is of major challenge for hydrology and bioclimatology. Because of the heterogeneity of these factors, soil moisture varies strongly over time and space. Our objective was to assess the spatio-temporal variability of soil moisture and factors which could explain that variability, like soil properties and vegetation cover, in in a long term biodiversity experiment (Jena Experiment). The Jena Experiment consist 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional groups (legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design Soil moisture measurements were performed weekly April to September 2003-2005 and 2008-2013 using Delta T theta probe. Measurements were integrated to three depth intervals: 0.0 - 0.20, 0.20 - 0.40 and 0.40 - 0.70 m. We analyze the spatio-temporal patterns of soil water content on (i) the normalized time series and (ii) the first components obtained from a principal component analysis (PCA). Both were correlated with the design variables of the Jena Experiment (plant species richness and plant functional groups) and other influencing factors such as soil texture, soil structural variables and vegetation parameters. For the time stability of soil water content, the analysis showed that plots containing grasses was consistently drier than average at the soil surface in all observed years while plots containing legumes comparatively moister, but only up to the year 2008. In 0.40 - 0.70 m soil deep plots presence of small herbs led to higher than average soil moisture in some years (2008, 2012, 2013). Interestingly, plant species richness led to moister than average subsoil at the beginning of the experiment (2003 and 2004), which changed to lower than average up to the year 2010 in all depths. There was no effect of species diversity in the years since 2010, although species diversity generally increases leaf area index and aboveground biomass. The first component from the PCA analysis described the mean behavior in time of all soil moisture time series. The second component reflected the impact of soil depth. The first two components explained 76% of the data set total variance. The third component is linked to plant species richness and explained about 4 % of the total variance of soil moisture data. The fourth component, which explained 2.4 %, showed a high correlation to soil texture. Within this study we investigate the dominant factors controlling spatio-temporal patterns of soil moisture at several soil depths. Although climate and soil depths were the most important drivers, other factors like plant species richness and soil texture affected the temporal variation while certain plant functional groups were important for the spatial variability.
Spatio-temporal effects of low severity grassland fire on soil colour
NASA Astrophysics Data System (ADS)
Pereira, Paulo; Cerdà, Artemi; Bolutiene, Violeta; Pranskevicius, Mantas; Úbeda, Xavier; Jordán, Antonio; Zavala, Lorena; Mataix-Solera, Jorge
2013-04-01
Fire changes soil properties directly, through temperature, or indirectly with ash deposition and the temporal elimination of vegetal cover. Both influences change soil colour and soil properties. The degree of changes depends on fire severity that has important implications on soil organic matter, texture, mineralogy and hydrological properties and type of ash produced. The ash colour is different according to the temperature of combustion and burned specie and this property will have implications on soil colour. In addition, ash properties have a strong spatial variability. The aim of this work is to study the spatio-temporal effects of a low severity grassland fire on soil colour occurred in Lithuania, near Vilnius city (54° 42' N, 25° 08' E, 158 m.a.s.l.). After the fire it was designed a plot of 20x20m in a burned and unburned flat area. Soil colour was analysed immediately after the fire, and 2, 5, 7 and 9 months after the fire. In each sampling 25 soil samples were collected, carried out to the laboratory, dried at room temperature (20-24° C) and sieved with the <2mm mesh. Soil colour was observed with the Munsell colour chart and the soil chroma value (CV) was observed. Since data did not respected the Gaussian distribution a neperian logarithmic (ln) transformation was applied. Differences among time and between plots were observed with the repeated measures ANOVA test, followed by a Tukey HSD test. Differences were significant at a p<0.05. The spatial variability (SV) was assessed with the coefficient of variation using non transformed data. The results showed differences among time at a p<0.001, treatment at a p<0.01 and time x treatment at a p<0.01. This means that fire during the first 9 months changed significantly soil colour. The CV of the burned plot was lower than the control plot (darker colour), that is attributed to the deposition of charred material and charcoal. This ash produced in this fire was mainly black coloured. With the time the soil of the burned plot became lighter, due the movement of charred material and charcoal in depth through soil profile. After the fire SV was higher in the burned plot (13.27%) than in the unburned plot (7.95%). This major variability might be attributed to ash influence, since this fire did nit had direct effects on soil. Despite the reduced CV, some patches burned at higher severity, and ash was dark and light grey and this might had influences on soil colour SV. In the following measurements SV was very similar, but always slightly higher in the control plot than in the burned plot. Two months, unburned 15.52% and burned, 14.70%. Five months, unburned, 14.78% and burned 14.42%, Seven months, unburned, 15.15% and burned, 14.67%. Nine months, unburned, 18.96% and burned 17.84%. After the fire ash can be (re)distributed uncountable times. In the immediate period after the fire, finner ash produced at higher severities is easily transported by wind and can remix (Pereira et al., 2013a, Pereira et al., 2013b) and change soil colour. In this fire, vegetation recovered very fast, thus this process might occurred only in the first weeks after the fire (Pereira et al., 2013c). Since vegetation recovered fast, soil colour SV depended on carbon and charred material movement in depth soil profile. Further studies are needed on the soil colour evolution after the fire, since can be an indicator of soil properties such as temperature reached with implications in other soil properties. Acknowledgements The authors appreciated the support of the project "Litfire", Fire effects in Lithuanian soils and ecosystems (MIP-048/2011) funded by the Lithuanian Research Council, Spanish Ministry of Science and Innovation for funding through the HYDFIRE project CGL2010-21670-C02-01, FUEGORED (Spanish Network of Forest Fire Effects on Soils http://grupo.us.es/fuegored/) and to Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya. References Pereira, P. Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2013a) Modelling the impacts of wildfire on ash thickness in a short-term period, Land Degradation and Development (In press) DOI: 10.1002/ldr.2195 Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J., Martin, D.A., Jordan, A. Burguet, M. (2013b) Effects of fire on ash thickness in a Lithuanian grassland and short-term spatio-temporal changes. Solid Earth Discussions, 4 (1), 1545-1584. doi:10.5194/sed-4-1-2012 Pereira, P., Pranskevicius, M., Cepanko, V., Vaitkute, D., Pundyte, N., Ubeda, X., Mataix-Soler, J., Cerda, A., Martin, D.A. (2013c) Short time vegetation recovers after a spring grassland fire in Lithuania. Temporal and slope position effect, Flamma, 4(1), 13-17.
Preliminary study of soil permeability properties using principal component analysis
NASA Astrophysics Data System (ADS)
Yulianti, M.; Sudriani, Y.; Rustini, H. A.
2018-02-01
Soil permeability measurement is undoubtedly important in carrying out soil-water research such as rainfall-runoff modelling, irrigation water distribution systems, etc. It is also known that acquiring reliable soil permeability data is rather laborious, time-consuming, and costly. Therefore, it is desirable to develop the prediction model. Several studies of empirical equations for predicting permeability have been undertaken by many researchers. These studies derived the models from areas which soil characteristics are different from Indonesian soil, which suggest a possibility that these permeability models are site-specific. The purpose of this study is to identify which soil parameters correspond strongly to soil permeability and propose a preliminary model for permeability prediction. Principal component analysis (PCA) was applied to 16 parameters analysed from 37 sites consist of 91 samples obtained from Batanghari Watershed. Findings indicated five variables that have strong correlation with soil permeability, and we recommend a preliminary permeability model, which is potential for further development.
The effects of grazing intensity on soil processes in a Mediterranean protected area.
Panayiotou, Evaggelia; Dimou, Maria; Monokrousos, Nikolaos
2017-08-08
We investigated the temporal and among-site differentiation of soil functionality properties in fields under different grazing intensities (heavy and light) and compared them to those found in their adjacent hedgerows, consisting either of wooden shrubs (Rubus canescens) or of high trees (Populus sp.), during the cold and humid seasons of the year. We hypothesized that greater intensity of grazing would result in higher degradation of the soil system. The grazing factor had a significant effect on soil organic C and N, microbial biomass C, microbial biomass N, microbial activity, and β-glucosidase, while acid phosphatase and urease activity were not found to differ significantly among the management systems. The intensity of grazing affected mostly the chemical properties of soil (organic C and N) and altered significantly the composition of the soil microbial community, as lower C:N ratio of the microbial biomass indicates the dominance of bacteria over fungi in the heavily grazed fields. All estimated biological variables presented higher values in the humid period, although the pattern of differentiation was similar at both sampling times, revealing that site-specific variations were more pronounced than the time-specific ones. Our results indicate that not all C, N, and P dynamics were equally affected by grazing. Management plans applied to pastures, in order to improve soil quality properties and accelerate passive reforestation, should aim at the improvement of soil parameters related primarily to C and secondly to N cycle.
Soil heterogeneity in Mojave Desert shrublands: Biotic and abiotic processes
NASA Astrophysics Data System (ADS)
Caldwell, Todd G.; Young, Michael H.; McDonald, Eric V.; Zhu, Jianting
2012-09-01
Geological and ecological processes play critical roles in the evolution of desert piedmonts. Feedback between fast cyclic biotic and slow cumulative pedogenic processes on arid alluvial fan systems results in a heterogeneous landscape of interspace and canopy microsites. Defining the spatial extent between these processes will allow a better connection to ecosystem service and climate change. We use a soil chronosequence in the Mojave Desert and high spatial resolution infiltrometer measurements along transects radiating from canopies of perennial shrubs to assess the extent of biotic and abiotic processes and the heterogeneity of soil properties in arid shrublands. Results showed higher saturated conductivity under vegetation regardless of surface age, but it was more conspicuous on older, developed soils. At proximal locations to the shrub, bulk density, soil structure grade, silt, and clay content significantly increased radially from the canopy, while sand and organic material decreased. Soil properties at distal locations 2-5 times the canopy radius had no significant spatial correlation. The extent of the biotic influence of the shrub was 1.34 ± 0.32 times the canopy radius. Hydraulic properties were weakly correlated in space, but 75% of the variance could be attributed to sand content, soil structure grade, mean-particle diameter, and soil organic material, none of which are exclusively biotic or abiotic. The fast cyclic biotic processes occurring under vegetation are clearly overprinted on slow cumulative abiotic processes, resulting in the deterministic variability observed at the plant scale.
NASA Astrophysics Data System (ADS)
Göl, Ceyhun; Bulut, Sinan; Bolat, Ferhat
2017-10-01
The purpose of this research is to compare the spatial variability of soil organic carbon (SOC) in four adjacent land uses including the cultivated area, the grassland area, the plantation area and the natural forest area in the semi - arid region of Black Sea backward region of Turkey. Some of the soil properties, including total nitrogen, SOC, soil organic matter, and bulk density were measured on a grid with a 50 m sampling distance on the top soil (0-15 cm depth). Accordingly, a total of 120 samples were taken from the four adjacent land uses. Data was analyzed using geostatistical methods. The methods used were: Block kriging (BK), co - kriging (CK) with organic matter, total nitrogen and bulk density as auxiliary variables and inverse distance weighting (IDW) methods with the power of 1, 2 and 4. The methods were compared using a performance criteria that included root mean square error (RMSE), mean absolute error (MAE) and the coefficient of correlation (r). The one - way ANOVA test showed that differences between the natural (0.6653 ± 0.2901) - plantation forest (0.7109 ± 0.2729) areas and the grassland (1.3964 ± 0.6828) - cultivated areas (1.5851 ± 0.5541) were statistically significant at 0.05 level (F = 28.462). The best model for describing spatially variation of SOC was CK with the lowest error criteria (RMSE = 0.3342, MAE = 0.2292) and the highest coefficient of correlation (r = 0.84). The spatial structure of SOC could be well described by the spherical model. The nugget effect indicated that SOC was moderately dependent on the study area. The error distributions of the model showed that the improved model was unbiased in predicting the spatial distribution of SOC. This study's results revealed that an explanatory variable linked SOC increased success of spatial interpolation methods. In subsequent studies, this case should be taken into account for reaching more accurate outputs.
NASA Astrophysics Data System (ADS)
Green, Timothy R.; Erskine, Robert H.
2011-12-01
Dynamics of profile soil water vary with terrain, soil, and plant characteristics. The objectives addressed here are to quantify dynamic soil water content over a range of slope positions, infer soil profile water fluxes, and identify locations most likely influenced by multidimensional flow. The instrumented 56 ha watershed lies mostly within a dryland (rainfed) wheat field in semiarid eastern Colorado. Dielectric capacitance sensors were used to infer hourly soil water content for approximately 8 years (minus missing data) at 18 hillslope positions and four or more depths. Based on previous research and a new algorithm, sensor measurements (resonant frequency) were rescaled to estimate soil permittivity, then corrected for temperature effects on bulk electrical conductivity before inferring soil water content. Using a mass-conservation method, we analyzed multitemporal changes in soil water content at each sensor to infer the dynamics of water flux at different depths and landscape positions. At summit positions vertical processes appear to control profile soil water dynamics. At downslope positions infrequent overland flow and unsaturated subsurface lateral flow appear to influence soil water dynamics. Crop water use accounts for much of the variability in soil water between transects that are either cropped or fallow in alternating years, while soil hydraulic properties and near-surface hydrology affect soil water variability across landscape positions within each management zone. The observed spatiotemporal patterns exhibit the joint effects of short-term hydrology and long-term soil development. Quantitative methods of analyzing soil water patterns in space and time improve our understanding of dominant soil hydrological processes and provide alternative measures of model performance.
Łokas, Edyta; Wachniew, Przemysław; Jodłowski, Paweł; Gąsiorek, Michał
2017-11-01
A survey of artificial ( 137 Cs, 238 Pu, 239+240 Pu, 241 Am) and natural ( 226 Ra, 232 Th, 40 K, 210 Pb) radioactive isotopes in proglacial soils of an Arctic glacier have revealed high spatial variability of activity concentrations and inventories of the airborne radionuclides. Soil column 137 Cs inventories range from below the detection limit to nearly 120 kBq m -2 , this value significantly exceeding direct atmospheric deposition. This variability may result from the mixing of materials characterised by different contents of airborne radionuclides. The highest activity concentrations observed in the proglacial soils may result from the deposition of cryoconites, which have been shown to accumulate airborne radionuclides on the surface of glaciers. The role of cryoconites in radionuclide accumulation is supported by the concordant enrichment of the naturally occurring airborne 210 Pb in proglacial soil cores showing elevated levels of artificial radionuclides. The lithogenic radionuclides show less variability than the airborne radionuclides because their activity concentrations are controlled only by the mixing of material derived from the weathering of different parent rocks. Soil properties vary little within and between the profiles and there is no unequivocal relationship between them and the radionuclide contents. The inventories reflect the pathways and time variable inputs of soil material to particular sites of the proglacial zone. Lack of the airborne radionuclides reflects no deposition of material exposed to the atmosphere after the 1950s or its removal by erosion. Inventories above the direct atmospheric deposition indicate secondary deposition of radionuclide-bearing material. Very high inventories indicate sites where transport pathways of cryoconite material terminated. Copyright © 2017 Elsevier Ltd. All rights reserved.
Wang, Shufang; Wang, Xiaoke; Ouyang, Zhiyun
2012-01-01
Soil organic carbon (SOC) and total nitrogen (TN) contents as well as their relationships with site characteristics are of profound importance in assessing current regional, continental and global soil C and N stocks and potentials for C sequestration and N conservation to offset anthropogenic emissions of greenhouse gases. This study investigated contents and distribution of SOC and TN under different land uses, and the quantitative relationships between SOC or TN and site characteristics in the Upstream Watershed of Miyun Reservoir, North China. Overall, both SOC and TN contents in natural secondary forests and grasslands were much higher than in plantations and croplands. Land use alone explained 37.2% and 38.4% of variations in SOC and TN contents, respectively. The optimal models for SOC and TN, achieved by multiple regression analysis combined with principal component analysis (PCA) to remove the multicollinearity among site variables, showed that elevation, slope, soil clay and water contents were the most significant factors controlling SOC and TN contents, jointly explaining 70.3% of SOC and 67.1% of TN contents variability. Only does additional 1.9% and 3% increase in the interpretations of SOC and TN contents variability respectively when land use was added to regressions, probably due to environment factors determine land use. Therefore, environmental variables were more important for SOC and TN variability than land use in the study area, and should be taken into consideration in properly evaluating effects of future land use changes on SOC and TN on a regional scale.
Effects of Mulching on Soil Properties and Growth of Tea Olive (Osmanthus fragrans).
Ni, Xue; Song, Weiting; Zhang, Huanchao; Yang, Xiulian; Wang, Lianggui
2016-01-01
Different mulches have variable effects on soil physical properties and plant growth. This study aimed to compare the effects of mulching with inorganic (round gravel, RG), organic (wood chips, WC), and living (manila turf grass, MG) materials on soil properties at 0-5-cm and 5-10-cm depths, as well as on the growth and physiological features of Osmanthus fragrans L. 'Rixianggui' plants. Soil samples were collected at three different time points from field plots of O. fragrans plants treated with the different mulching treatments. Moisture at both soil depths was significantly higher after mulching with RG and WC than that in the unmulched control (CK) treatment. Mulching did not affect soil bulk density, pH, or total nitrogen content, but consistently improved soil organic matter. The available nitrogen in the soil increased after RG and WC treatments, but decreased after MG treatment during the experimental period. Mulching improved plant growth by increasing root activity, soluble sugar, and chlorophyll a content, as well as by providing suitable moisture conditions and nutrients in the root zone. Plant height and trunk diameter were remarkably increased after mulching, especially with RG and WC. However, while MG improved plant growth at the beginning of the treatment, the 'Rixianggui' plants later showed no improvement in growth. This was probably because MG competed with the plants for water and available nitrogen in the soil. Thus, our findings suggest that RG and WC, but not MG, improved the soil environment and the growth of 'Rixianggui' plants. Considering the effect of mulching on soil properties and plant growth and physiology, round gravel and wood chips appear to be a better choice than manila turf grass in 'Rixianggui' nurseries. Further studies are required to determine the effects of mulch quality and mulch-layer thickness on shoot and root growths.
Field Scale Spatial Modelling of Surface Soil Quality Attributes in Controlled Traffic Farming
NASA Astrophysics Data System (ADS)
Guenette, Kris; Hernandez-Ramirez, Guillermo
2017-04-01
The employment of controlled traffic farming (CTF) can yield improvements to soil quality attributes through the confinement of equipment traffic to tramlines with the field. There is a need to quantify and explain the spatial heterogeneity of soil quality attributes affected by CTF to further improve our understanding and modelling ability of field scale soil dynamics. Soil properties such as available nitrogen (AN), pH, soil total nitrogen (STN), soil organic carbon (SOC), bulk density, macroporosity, soil quality S-Index, plant available water capacity (PAWC) and unsaturated hydraulic conductivity (Km) were analysed and compared among trafficked and un-trafficked areas. We contrasted standard geostatistical methods such as ordinary kriging (OK) and covariate kriging (COK) as well as the hybrid method of regression kriging (ROK) to predict the spatial distribution of soil properties across two annual cropland sites actively employing CTF in Alberta, Canada. Field scale variability was quantified more accurately through the inclusion of covariates; however, the use of ROK was shown to improve model accuracy despite the regression model composition limiting the robustness of the ROK method. The exclusion of traffic from the un-trafficked areas displayed significant improvements to bulk density, macroporosity and Km while subsequently enhancing AN, STN and SOC. The ability of the regression models and the ROK method to account for spatial trends led to the highest goodness-of-fit and lowest error achieved for the soil physical properties, as the rigid traffic regime of CTF altered their spatial distribution at the field scale. Conversely, the COK method produced the most optimal predictions for the soil nutrient properties and Km. The use of terrain covariates derived from light ranging and detection (LiDAR), such as of elevation and topographic position index (TPI), yielded the best models in the COK method at the field scale.
Johnston, Marie R; Balster, Nick J; Zhu, Jun
2016-01-01
Prairie gardens have become a common addition to residential communities in the midwestern United States because prairie vegetation is native to the region, requires fewer resources to maintain than turfgrass, and has been promoted to help remediate urban soil. Although prairie systems typically have deeper and more diverse root systems than traditional turfgrass, no one has tested the effect of this vegetation type on the physical properties of urban soil. We hypothesized that residential prairie gardens would yield lower soil bulk density (BD), lower penetration resistance (PR), greater soil organic matter (SOM), and greater saturated hydraulic conductivity () compared with turfgrass lawns. To test this hypothesis, we examined 12 residential properties in Madison, WI, where homeowners had established a prairie garden within their turfgrass lawn. Despite a consistent trend in the difference between vegetation types, no significant main effects were found (i.e., a difference between vegetation types when averaged over depth) for any of the four soil properties measured in this study. Differences were found with depth and depended on a significant interaction with vegetation type. At the surface depth (0-0.15 m), soil beneath prairie gardens had 10% lower mean BD, 15% lower mean PR, 25% greater level of SOM, and 33% greater compared with soil beneath the adjacent lawns. These differences were not detected at deeper sampling intervals of 0.15 to 0.30 m and 0.30 to 0.45 m. Although not statistically significant, the consistent trend and direction among soil variables suggest that residential prairie gardens had changed the surface soil at a rate that marginally outpaced turfgrass and calls for controlled experiments to identify the mechanisms that might enhance these trends. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
NASA Astrophysics Data System (ADS)
Sharma, S.; Sarkar, D.; Datta, R.
2005-05-01
Land-applied arsenical pesticides have contributed elevated soil arsenic (As) levels. Many baseline risk assessments As-contaminated sites assume that all As present in the soil is bioavailable, thereby potentially overestimating the actual health risk. However, risk from As exposure is associated only with those forms of As that are potentially extractable by the human gastrointestinal juices. It has been demonstrated that As may exist in several geochemical forms depending on soil chemical properties, which may or may not be bioavailable. The current study aims at addressing the issue of soil variability on As bioavailability as a function of soil physico-chemical properties in a greenhouse setting involving dynamic interactions between soil, water and plants. Four different soils were chosen based on their potential differences with respect to As reactivity: Immokalee, an acid sand with low extractable Fe/Al, having minimal arsenic retention capacity; Millhopper, an acid sandy loam with high extractable Fe/Al oxides; Pahokee Muck soil with 85% soil organic matter (SOM) as well as high Fe/Al content; and Orelia soil with high clay and Fe/Al content. Soils were amended with sodium arsenate (675 and 1500 mg/Kg). Rice (Oryza sativa) was used as the test crop. A sequential extraction scheme was employed to identify the geochemical forms of As in soils (soluble, exchangeable, organic, Fe/Al-bound, Ca/Mg-bound, residual) immediately after spiking; after 3 mo; and after 6 mo of equilibration time. Concentrations of these As forms were correlated with the in-vitro bioavailable As fractions to identify those As fractions that are most likely to be bioavailable. Results from this study showed that there was little to no plant growth in the contaminated soils. Sequential extractions of the soil indicated that arsenic is strongly adsorbed onto soil amorphous iron/aluminum oxides, and the degree of arsenic retention is a direct function of equilibration time.
Stochastic Analysis and Probabilistic Downscaling of Soil Moisture
NASA Astrophysics Data System (ADS)
Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.
2017-12-01
Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.
Hseu, Zeng-Yei; Zehetner, Franz
2014-01-01
This study compared the extractability of Cd, Cu, Ni, Pb, and Zn by 8 extraction protocols for 22 representative rural soils in Taiwan and correlated the extractable amounts of the metals with their uptake by Chinese cabbage for developing an empirical model to predict metal phytoavailability based on soil properties. Chemical agents in these protocols included dilute acids, neutral salts, and chelating agents, in addition to water and the Rhizon soil solution sampler. The highest concentrations of extractable metals were observed in the HCl extraction and the lowest in the Rhizon sampling method. The linear correlation coefficients between extractable metals in soil pools and metals in shoots were higher than those in roots. Correlations between extractable metal concentrations and soil properties were variable; soil pH, clay content, total metal content, and extractable metal concentration were considered together to simulate their combined effects on crop uptake by an empirical model. This combination improved the correlations to different extents for different extraction methods, particularly for Pb, for which the extractable amounts with any extraction protocol did not correlate with crop uptake by simple correlation analysis. PMID:25295297
Self-organizing biochemical cycle in dynamic feedback with soil structure
NASA Astrophysics Data System (ADS)
Vasilyeva, Nadezda; Vladimirov, Artem; Smirnov, Alexander; Matveev, Sergey; Tyrtyshnikov, Evgeniy; Yudina, Anna; Milanovskiy, Evgeniy; Shein, Evgeniy
2016-04-01
In the present study we perform bifurcation analysis of a physically-based mathematical model of self-organized structures in soil (Vasilyeva et al., 2015). The state variables in this model included microbial biomass, two organic matter types, oxygen, carbon dioxide, water content and capillary pore size. According to our previous experimental studies, organic matter affinity to water is an important property affecting soil structure. Therefore, organic matter wettability was taken as principle distinction between organic matter types in this model. It considers general known biological feedbacks with soil physical properties formulated as a system of parabolic type non-linear partial differential equations with elements of discrete modeling for water and pore formation. The model shows complex behavior, involving emergence of temporal and spatial irregular auto-oscillations from initially homogeneous distributions. The energy of external impact on a system was defined by a constant oxygen level on the boundary. Non-linear as opposed to linear oxygen diffusion gives possibility of modeling anaerobic micro-zones formation (organic matter conservation mechanism). For the current study we also introduced population competition of three different types of microorganisms according to their mobility/feeding (diffusive, moving and fungal growth). The strongly non-linear system was solved and parameterized by time-optimized algorithm combining explicit and implicit (matrix form of Thomas algorithm) methods considering the time for execution of the evaluated time-step according to accuracy control. The integral flux of the CO2 state variable was used as a macroscopic parameter to describe system as a whole and validation was carried out on temperature series of moisture dependence for soil heterotrophic respiration data. Thus, soil heterotrophic respiration can be naturally modeled as an integral result of complex dynamics on microscale, arising from biological processes formulated as a sum of state variables products, with no need to introduce any saturation functions, such as Mikhaelis-Menten type kinetics, inside the model. Analyzed dynamic soil model is being further developed to describe soil structure formation and its effect on organic matter decomposition at macro-scale, to predict changes with external perturbations. To link micro- and macro-scales we additionally model soil particles aggregation process. The results from local biochemical soil organic matter cycle serve as inputs to aggregation process, while the output aggregate size distributions define physical properties in the soil profile, these in turn serve as dynamic parameters in local biochemical cycles. The additional formulation is a system of non-linear ordinary differential equations, including Smoluchowski-type equations for aggregation and reaction kinetics equations for coagulation/adsorption/adhesion processes. Vasilyeva N.A., Ingtem J.G., Silaev D.A. Nonlinear dynamical model of microbial growth in soil medium. Computational Mathematics and Modeling, vol. 49, p.31-44, 2015 (in Russian). English version is expected in corresponding vol.27, issue 2, 2016.
Pajares, Silvia; Escalante, Ana E; Noguez, Ana M; García-Oliva, Felipe; Martínez-Piedragil, Celeste; Cram, Silke S; Eguiarte, Luis Enrique; Souza, Valeria
2016-01-01
Arid ecosystems are characterized by high spatial heterogeneity, and the variation among vegetation patches is a clear example. Soil biotic and abiotic factors associated with these patches have also been well documented as highly heterogeneous in space. Given the low vegetation cover and little precipitation in arid ecosystems, soil microorganisms are the main drivers of nutrient cycling. Nonetheless, little is known about the spatial distribution of microorganisms and the relationship that their diversity holds with nutrients and other physicochemical gradients in arid soils. In this study, we evaluated the spatial variability of soil microbial diversity and chemical parameters (nutrients and ion content) at local scale (meters) occurring in a gypsum-based desert soil, to gain knowledge on what soil abiotic factors control the distribution of microbes in arid ecosystems. We analyzed 32 soil samples within a 64 m(2) plot and: (a) characterized microbial diversity using T-RFLPs of the bacterial 16S rRNA gene, (b) determined soil chemical parameters, and (c) identified relationships between microbial diversity and chemical properties. Overall, we found a strong correlation between microbial composition heterogeneity and spatial variation of cations (Ca(2), K(+)) and anions (HCO[Formula: see text], Cl(-), SO[Formula: see text]) content in this small plot. Our results could be attributable to spatial differences of soil saline content, favoring the patchy emergence of salt and soil microbial communities.
Reynolds, R.L.; Reheis, M.C.; Neff, J.C.; Goldstein, H.; Yount, J.
2006-01-01
In a semi-arid, upland setting on the Colorado Plateau that is underlain by nutrient-poor Paleozoic eolian sandstone, alternating episodes of dune activity and soil formation during the late Pleistocene and Holocene have produced dominantly sandy deposits that support grass and shrub communities. These deposits also contain eolian dust, especially in paleosols. Eolian dust in these deposits is indicated by several mineralogic and chemical disparities with local bedrock, but it is most readily shown by the abundance of titaniferous magnetite in the sandy deposits that is absent in local bedrock. Magnetite and some potential plant nutrients (especially, P, K, Na, Mn, and Zn) covary positively with depth (3-4 m) in dune-crest and dune-swale settings. Magnetite abundance also correlates strongly and positively with abundances of other elements (e.g., Ti, Li, As, Th, La, and Sc) that are geochemically stable in these environments. Soil-property variations with depth can be ascribed to three primary factors: (1) shifts in local geomorphic setting; (2) accumulation of relatively high amounts of atmospheric mineral dust inputs during periods of land-surface stability; and (3) variations in dust flux and composition that are likely related to changes in dust-source regions. Shifts in geomorphic setting are revealed by large variations in soil texture and are also expressed by changes in soil chemical and magnetic properties. Variable dust inputs are indicated by both changes in dust flux and changes in relations among magnetic, chemical, and textural properties. The largest of these changes is found in sediment that spans late Pleistocene to early Holocene time. Increased dust inputs to the central Colorado Plateau during this period may have been related to desiccation and shrinkage of large lakes from about 12 to 8 ka in western North America that exposed vast surfaces capable of emitting dust. Soil properties that result from variable dust accumulation and redistribution in these surficial deposits during the late Quaternary are important to modern ecosystem dynamics because some plants today utilize nutrients deposited as long ago as about 12-15 ky and because variations in fine-grained (silt) sediment, including eolian dust, influence soil-moisture capacity.
NASA Astrophysics Data System (ADS)
Jian, S.; Li, J.; Guo, C.; Hui, D.; Deng, Q.; Yu, C. L.; Dzantor, K. E.; Lane, C.
2017-12-01
Nitrogen (N) fertilizers are widely used to increase bioenergy crop yield but intensive fertilizations on spatial distributions of soil microbial processes in bioenergy croplands remains unknown. To quantify N fertilization effect on spatial heterogeneity of soil microbial biomass carbon (MBC) and N (MBN), we sampled top mineral horizon soils (0-15cm) using a spatially explicit design within two 15-m2 plots under three fertilization treatments in two bioenergy croplands in a three-year long fertilization experiment in Middle Tennessee, USA. The three fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha-1 in urea) and high N input (HN: 168 kg N ha-1 in urea). The two crops were switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.). Results showed that N fertilizations little altered central tendencies of microbial variables but relative to LN, HN significantly increased MBC and MBC:MBN (GG only). HN possessed the greatest within-plot variances except for MBN (GG only). Spatial patterns were generally evident under HN and LN plots and much less so under NN plots. Substantially contrasting spatial variations were also identified between croplands (GG>SG) and among variables (MBN, MBC:MBN > MBC). No significant correlations were identified between soil pH and microbial variables. This study demonstrated that spatial heterogeneity is elevated in microbial biomass of fertilized soils likely by uneven fertilizer application, the nature of soil microbial communities and bioenergy crops. Future researchers should better match sample sizes with the heterogeneity of soil microbial property (i.e. MBN) in bioenergy croplands.
When and where does preferential flow matter - from observation to large scale modelling
NASA Astrophysics Data System (ADS)
Weiler, Markus; Leistert, Hannes; Steinbrich, Andreas
2017-04-01
Preferential flow can be of relevance in a wide range of soils and the interaction of different processes and factors are still difficult to assess. As most studies (including our own studies) focusing on the effect of preferential flow are based on relatively high precipitation rates, there is always the question how relevant preferential flow is under natural conditions, considering the site specific precipitation characteristics, the effect of the drying and wetting cycle on the initial soil water condition and shrinkage cracks, the site specific soil properties, soil structure and rock fragments, and the effect of plant roots and soil fauna (e.g. earthworm channels). In order to assess this question, we developed the distributed, process-based model RoGeR (Runoff Generation Research) to include a large number relevant features and processes of preferential flow in soils. The model was developed from a large number of process based research and experiments and includes preferential flow in roots, earthworm channels, along rock fragments and shrinkage cracks. We parameterized the uncalibrated model at a high spatial resolution of 5x5m for the whole state of Baden-Württemberg in Germany using LiDAR data, degree of sealing, landuse, soil properties and geology. As the model is an event based model, we derived typical event based precipitation characteristics based on rainfall duration, mean intensity and amount. Using the site-specific variability of initial soil moisture derived from a water balance model based on the same dataset, we simulated the infiltration and recharge amounts of all event classes derived from the event precipitation characteristics and initial soil moisture conditions. The analysis of the simulation results allowed us to extracts the relevance of preferential flow for infiltration and recharge considering all factors above. We could clearly see a strong effect of the soil properties and land-use, but also, particular for clay rich soils a strong effect of the initial conditions due to the development of soil cracks. Not too surprisingly, the relevance of preferential flow was much lower when considering the whole range of precipitation events as only considering events with a high rainfall intensity. Also, the influence on infiltration and recharge were different. Despite the model can still be improved in particular considering more realistic information about the spatial and temporal variability of preferential flow by soil fauna and plants, the model already shows under what situation we need to be very careful when predicting infiltration and recharge with models considering only longer time steps (daily) or only matrix flow.
Spatial structure of soil properties at different scales of Mt. Kilimanjaro, Tanzania
NASA Astrophysics Data System (ADS)
Kühnel, Anna; Huwe, Bernd
2013-04-01
Soils of tropical mountain ecosystems provide important ecosystem services like water and carbon storage, water filtration and erosion control. As these ecosystems are threatened by global warming and the conversion of natural to human-modified landscapes, it is important to understand the implications of these changes. Within the DFG Research Unit "Kilimanjaro ecosystems under global change: Linking biodiversity, biotic interactions and biogeochemical ecosystem processes", we study the spatial heterogeneity of soils and the available water capacity for different land use systems. In the savannah zone of Mt. Kilimanjaro, maize fields are compared to natural savannah ecosystems. In the lower montane forest zone, coffee plantations, traditional home gardens, grasslands and natural forests are studied. We characterize the soils with respect to soil hydrology, emphasizing on the spatial variability of soil texture and bulk density at different scales. Furthermore soil organic carbon and nitrogen, cation exchange capacity and the pH-value are measured. Vis/Nir-Spectroscopy is used to detect small scale physical and chemical heterogeneity within soil profiles, as well as to get information of soil properties on a larger scale. We aim to build a spectral database for these soil properties for the Kilimanjaro region in order to get rapid information for geostatistical analysis. Partial least square regression with leave one out cross validation is used for model calibration. Results for silt and clay content, as well as carbon and nitrogen content are promising, with adjusted R² ranging from 0.70 for silt to 0.86 for nitrogen. Furthermore models for other nutrients, cation exchange capacity and available water capacity will be calibrated. We compare heterogeneity within and across the different ecosystems and state that spatial structure characteristics and complexity patterns in soil parameters can be quantitatively related to biodiversity and functional diversity parameters.
Tuo, Dengfeng; Xu, Mingxiang; Gao, Guangyao
2018-08-15
Wind and water erosion are two dominant types of erosion that lead to soil and nutrient losses. Wind and water erosion may occur simultaneously to varying extents in semi-arid regions. The contributions of wind and water erosion to total erosion and their effects on soil quality, however, remains elusive. We used cesium-137 ( 137 Cs) inventories to estimate the total soil erosion and used the Revised Universal Soil Loss Equation (RUSLE) to quantify water erosion in sloping croplands. Wind erosion was estimated from the subtraction of the two. We also used 137 Cs inventories to calculate total soil erosion and validate the relationships of the soil quality and erosion at different slope aspects and positions. The results showed that wind erosion (1460tkm -2 a -1 ) on northwest-facing slope was responsible for approximately 39.7% of the total soil loss, and water erosion (2216tkm -2 a -1 ) accounted for approximately 60.3%. The erosion rates were 58.8% higher on northwest- than on southeast-facing slopes. Northwest-facing slopes had lower soil organic carbon, total nitrogen, clay, and silt contents than southeast-facing slopes, and thus, the 137 Cs inventories were lower, and the total soil erosions were higher on the northwest-facing slopes. The variations in soil physicochemical properties were related to total soil erosion. The lowest 137 Cs inventories and nutrient contents were recorded at the upper positions on the northwest-facing slopes due to the successive occurrence of more severe wind and water erosion at the same site. The results indicated that wind and water could accelerate the spatial variability of erosion rate and soil properties and cause serious decreases in the nutrient contents in sloping fields. Our research could help researchers develop soil strategies to reduce soil erosion according to the dominant erosion type when it occurs in a hilly agricultural area. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Säurich, Annelie; Tiemeyer, Bärbel; Don, Axel; Burkart, Stefan
2017-04-01
Drained peatlands are hotspots of carbon dioxide (CO2) emissions from agriculture. As a consequence of both drainage induced mineralization and anthropogenic sand mixing, large areas of former peatlands under agricultural use contain soil organic carbon (SOC) at the boundary between mineral and organic soils. Studies on SOC dynamics of such "low carbon organic soils" are rare as the focus of previous studies was mainly either on mineral soils or "true" peat soil. However, the variability of CO2 emissions increases with disturbance and therefore, we have yet to understand the reasons behind the relatively high CO2 emissions of these soils. Peat properties, soil organic matter (SOM) quality and water content are obviously influencing the rate of CO2 emissions, but a systematic evaluation of the hydrological and biogeochemical drivers for mineralization of disturbed peatlands is missing. With this incubation experiment, we aim at assessing the drivers of the high variability of CO2 emissions from strongly anthropogenically disturbed organic soil by systematically comparing strongly degraded peat with and without addition of sand under different moisture conditions and for different peat types. The selection of samples was based on results of a previous incubation study, using disturbed samples from the German Agricultural Soil Inventory. We sampled undisturbed soil columns from topsoil and subsoil (three replicates of each) of ten peatland sites all used as grassland. Peat types comprise six fens (sedge, Phragmites and wood peat) and four bogs (Sphagnum peat). All sites have an intact peat horizon that is permanently below groundwater level and a strongly disturbed topsoil horizon. Three of the fen and two of the bog sites have a topsoil horizon altered by sand-mixing. In addition the soil profile was mapped and samples for the determination of soil hydraulic properties were collected. All 64 soil columns (including four additional reference samples) will be installed in a microcosm system under a constant temperature of 10°C. The water-saturated soil columns will be drained via suction plates at the bottom of the columns by stepwise increase of the suction. The head space of the soil columns will be permanently flushed with moistened synthetic air and CO2 concentrations will be measured via online gas chromatography. First results will be presented.
Cáceres, Lizethly; Fuentes, Roxana; Escudey, Mauricio; Fuentes, Edwar; Báez, María E
2010-06-09
Metsulfuron-methyl sorption/desorption behavior was studied through batch sorption experiments in three typical volcanic ash-derived soils belonging to Andisol and Ultisol orders. Their distinctive physical and chemical properties are acidic pH and variable surface charge. Organic matter content and mineral composition affected in different ways sorption of metsulfuron-methyl (K(OC) ranging from 113 to 646 mL g(-1)): organic matter and iron and aluminum oxides mainly through hydrophilic rather than hydrophobic interactions in Andisols, and Kaolinite group minerals, as major constituents of Ultisols, and iron and aluminum oxides only through hydrophilic interactions. The Freundlich model described metsulfuron-methyl behavior in all cases (R(2) > 0.992). K(f) values (3.1-14.4 microg(1-1/n) mL(1/n) g(-1)) were higher than those reported for different class of soils including some with variable charge. Hysteresis was more significant in Ultisols. A strong influence of pH and phosphate was established for both kinds of soil, intensive soil fertilization and liming being the most probable scenario for leaching of metsulfuron-methyl, particularly in Ultisols.
Dynamic aspects of soil water availability for isohydric plants: Focus on root hydraulic resistances
NASA Astrophysics Data System (ADS)
Couvreur, V.; Vanderborght, J.; Draye, X.; Javaux, M.
2014-11-01
Soil water availability for plant transpiration is a key concept in agronomy. The objective of this study is to revisit this concept and discuss how it may be affected by processes locally influencing root hydraulic properties. A physical limitation to soil water availability in terms of maximal flow rate available to plant leaves (Qavail) is defined. It is expressed for isohydric plants, in terms of plant-centered variables and properties (the equivalent soil water potential sensed by the plant, ψs eq; the root system equivalent conductance, Krs; and a threshold leaf water potential, ψleaf lim). The resulting limitation to plant transpiration is compared to commonly used empirical stress functions. Similarities suggest that the slope of empirical functions might correspond to the ratio of Krs to the plant potential transpiration rate. The sensitivity of Qavail to local changes of root hydraulic conductances in response to soil matric potential is investigated using model simulations. A decrease of radial conductances when the soil dries induces earlier water stress, but allows maintaining higher night plant water potentials and higher Qavail during the last week of a simulated 1 month drought. In opposition, an increase of radial conductances during soil drying provokes an increase of hydraulic redistribution and Qavail at short term. This study offers a first insight on the effect of dynamic local root hydraulic properties on soil water availability. By better understanding complex interactions between hydraulic processes involved in soil-plant hydrodynamics, better prospects on how root hydraulic traits mitigate plant water stress might be achieved.
Evapotranspiration measurement and modeling without fitting parameters in high-altitude grasslands
NASA Astrophysics Data System (ADS)
Ferraris, Stefano; Previati, Maurizio; Canone, Davide; Dematteis, Niccolò; Boetti, Marco; Balocco, Jacopo; Bechis, Stefano
2016-04-01
Mountain grasslands are important, also because one sixth of the world population lives inside watershed dominated by snowmelt. Also, grasslands provide food to both domestic and selvatic animals. The global warming will probably accelerate the hydrological cycle and increase the drought risk. The combination of measurements, modeling and remote sensing can furnish knowledge in such faraway areas (e.g.: Brocca et al., 2013). A better knowledge of water balance can also allow to optimize the irrigation (e.g.: Canone et al., 2015). This work is meant to build a model of water balance in mountain grasslands, ranging between 1500 and 2300 meters asl. The main input is the Digital Terrain Model, which is more reliable in grasslands than both in the woods and in the built environment. It drives the spatial variability of shortwave solar radiation. The other atmospheric forcings are more problematic to estimate, namely air temperature, wind and longwave radiation. Ad hoc routines have been written, in order to interpolate in space the meteorological hourly time variability. The soil hydraulic properties are less variable than in the plains, but the soil depth estimation is still an open issue. The soil vertical variability has been modeled taking into account the main processes: soil evaporation, root uptake, and fractured bedrock percolation. The time variability latent heat flux and soil moisture results have been compared with the data measured in an eddy covariance station. The results are very good, given the fact that the model has no fitting parameters. The space variability results have been compared with the results of a model based on Landsat 7 and 8 data, applied over an area of about 200 square kilometers. The spatial correlation is quite in agreement between the two models. Brocca et al. (2013). "Soil moisture estimation in alpine catchments through modelling and satellite observations". Vadose Zone Journal, 12(3), 10 pp. Canone et al. (2015). "Field measurements based model for surface irrigation efficiency assessment". Agric. Water Manag., 156(1) pp. 30-42
Sediment fingerprinting experiments to test the sensitivity of multivariate mixing models
NASA Astrophysics Data System (ADS)
Gaspar, Leticia; Blake, Will; Smith, Hugh; Navas, Ana
2014-05-01
Sediment fingerprinting techniques provide insight into the dynamics of sediment transfer processes and support for catchment management decisions. As questions being asked of fingerprinting datasets become increasingly complex, validation of model output and sensitivity tests are increasingly important. This study adopts an experimental approach to explore the validity and sensitivity of mixing model outputs for materials with contrasting geochemical and particle size composition. The experiments reported here focused on (i) the sensitivity of model output to different fingerprint selection procedures and (ii) the influence of source material particle size distributions on model output. Five soils with significantly different geochemistry, soil organic matter and particle size distributions were selected as experimental source materials. A total of twelve sediment mixtures were prepared in the laboratory by combining different quantified proportions of the < 63 µm fraction of the five source soils i.e. assuming no fluvial sorting of the mixture. The geochemistry of all source and mixture samples (5 source soils and 12 mixed soils) were analysed using X-ray fluorescence (XRF). Tracer properties were selected from 18 elements for which mass concentrations were found to be significantly different between sources. Sets of fingerprint properties that discriminate target sources were selected using a range of different independent statistical approaches (e.g. Kruskal-Wallis test, Discriminant Function Analysis (DFA), Principal Component Analysis (PCA), or correlation matrix). Summary results for the use of the mixing model with the different sets of fingerprint properties for the twelve mixed soils were reasonably consistent with the initial mixing percentages initially known. Given the experimental nature of the work and dry mixing of materials, geochemical conservative behavior was assumed for all elements, even for those that might be disregarded in aquatic systems (e.g. P). In general, the best fits between actual and modeled proportions were found using a set of nine tracer properties (Sr, Rb, Fe, Ti, Ca, Al, P, Si, K, Si) that were derived using DFA coupled with a multivariate stepwise algorithm, with errors between real and estimated value that did not exceed 6.7 % and values of GOF above 94.5 %. The second set of experiments aimed to explore the sensitivity of model output to variability in the particle size of source materials assuming that a degree of fluvial sorting of the resulting mixture took place. Most particle size correction procedures assume grain size affects are consistent across sources and tracer properties which is not always the case. Consequently, the < 40 µm fraction of selected soil mixtures was analysed to simulate the effect of selective fluvial transport of finer particles and the results were compared to those for source materials. Preliminary findings from this experiment demonstrate the sensitivity of the numerical mixing model outputs to different particle size distributions of source material and the variable impact of fluvial sorting on end member signatures used in mixing models. The results suggest that particle size correction procedures require careful scrutiny in the context of variable source characteristics.
Nonautonomous linear system of the terrestrial carbon cycle
NASA Astrophysics Data System (ADS)
Luo, Y.
2012-12-01
Carbon cycle has been studied by uses of observation through various networks, field and laboratory experiments, and simulation models. Much less has been done on theoretical thinking and analysis to understand fundament properties of carbon cycle and then guide observatory, experimental, and modeling research. This presentation is to explore what would be the theoretical properties of terrestrial carbon cycle and how those properties can be used to make observatory, experimental, and modeling research more effective. Thousands of published data sets from litter decomposition and soil incubation studies almost all indicate that decay processes of litter and soil organic carbon can be well described by first order differential equations with one or more pools. Carbon pool dynamics in plants and soil after disturbances (e.g., wildfire, clear-cut of forests, and plows of soil for cropping) and during natural recovery or ecosystem restoration also exhibit characteristics of first-order linear systems. Thus, numerous lines of empirical evidence indicate that the terrestrial carbon cycle can be adequately described as a nonautonomous linear system. The linearity reflects the nature of the carbon cycle that carbon, once fixed by photosynthesis, is linearly transferred among pools within an ecosystem. The linear carbon transfer, however, is modified by nonlinear functions of external forcing variables. In addition, photosynthetic carbon influx is also nonlinearly influenced by external variables. This nonautonomous linear system can be mathematically expressed by a first-order linear ordinary matrix equation. We have recently used this theoretical property of terrestrial carbon cycle to develop a semi-analytic solution of spinup. The new methods have been applied to five global land models, including NCAR's CLM and CABLE models and can computationally accelerate spinup by two orders of magnitude. We also use this theoretical property to develop an analytic framework to decompose modeled carbon cycle into a few traceable components so as to facilitate model intercompsirosn, benchmark analysis, and data assimilation of global land models.
NASA Astrophysics Data System (ADS)
Groh, J.; Vanderborght, J.; Puetz, T.; Gerke, H. H.; Rupp, H.; Wollschlaeger, U.; Stumpp, C.; Priesack, E.; Vereecken, H.
2015-12-01
Understanding water flow and solute transport in the unsaturated zone is of great importance for an appropriate land use management strategy. The quantification and prediction of water and solute fluxes through the vadose zone can help to improve management practices in order to limit potential risk on our fresh water resources. Water related solute transport and residence time is strongly affected by preferential flow paths in the soil. Water flow in soils depends on soil properties and site factors (climate or experiment conditions, land use) and are therefore important factors to understand preferential solute transport in the unsaturated zone. However our understanding and knowledge of which on-site properties or conditions define and enhance preferential flow and transport is still poor and mostly limited onto laboratory experimental conditions (small column length and steady state boundary conditions). Within the TERENO SOILCan lysimeter network, which was designed to study the effects of climate change on soil functions, a bromide tracer was applied on 62 lysimeter at eight different test sites between Dec. 2013 and Jan. 2014. The TERENO SOILCan infrastructure offers the unique possibility to study the occurrence of preferential flow and transport of various soil types under different natural transient hydrological conditions and land use (crop, bare and grassland) at eight TERENO SOILCan observatories. Working with lysimeter replicates at each observatory allows defining the spatial variability of preferential transport and flow. Additionally lysimeters in the network were transferred within and between observatories in order to subject them to different rainfall and temperature regimes and enable us to relate the soil type susceptibility of preferential flow and transport not only to site specific physical and land use properties, but also to different transient boundary conditions. Comparison and statistical analysis between preferential flow indicators 5% arrival time and potential key soil properties, site factors and boundary conditions will be presented in order to identify key properties which control the preferential transport in the vadose zone under transient hydrological conditions.
Soils of the Southwestern Part of the Pacific Coast of Russia
NASA Astrophysics Data System (ADS)
Kostenkov, N. M.; Zharikova, E. A.
2018-02-01
The diversity of soils in the southwestern part of the Pacific coast of Russia (Primorie region) is discussed. Overall, 17 soil types belonging to 8 soil orders have been described in this region, and their morphology and properties have been studied. The diversity of plant communities, geomorphic conditions, and parent materials and relatively mild (as compared with other parts of the Far East region of Russia) specify the great variability of soil cover patterns. Low sea terraces are occupied by various peat, organo-accumulative, and gley soils; poorly drained medium-high terraces are the areas of various dark-humus and darkhumus gleyed soils. Typical and gleyic dark-humus podbels, dark-humus, and dark-humus gleyed soils formed on the high sea terraces. Residual elevations are occupied by brown forest (burozemic) soils, including typical burozems, dark-humus burozems, and gleyic dark-humus burozems and by dark-humus podbels. Various alluvial, gleyic gray-humus, and mucky gley soils are developed on riverine plains. On general, darkhumus soils with the high (>10%) humus content predominate; the area of dark-humus podbels us estimated at about 20%, and the area of dark-humus burozems is about 12%. All the soils in this region are specified by increased acidity values. The exchangeable sodium content is often high in the upper soil horizons with maximum values (0.71-1.19 cmol(c)/kg) in the peat gleyzems, peaty dark-humus soils, mucky-gley soils, and eutrophic peat soils of sea terraces. The grouping of the soils with respect to their physicochemical and agrochemical properties is suggested.
NASA Astrophysics Data System (ADS)
Mladenova, I. E.; Jackson, T. J.; Bindlish, R.; Njoku, E. G.; Chan, S.; Cosh, M. H.
2012-12-01
We are currently evaluating potential improvements to the standard NASA global soil moisture product derived using observations acquired from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). A major component of this effort is a thorough review of the theoretical basis of available passive-based soil moisture retrieval algorithms suitable for operational implementation. Several agencies provide routine soil moisture products. Our research focuses on five well-establish techniques that are capable of carrying out global retrieval using the same AMSR-E data set as the NASA approach (i.e. X-band brightness temperature data). In general, most passive-based algorithms include two major components: radiative transfer modeling, which provides the smooth surface reflectivity properties of the soil surface, and a complex dielectric constant model of the soil-water mixture. These two components are related through the Fresnel reflectivity equations. Furthermore, the land surface temperature, vegetation, roughness and soil properties need to be adequately accounted for in the radiative transfer and dielectric modeling. All of the available approaches we have examined follow the general data processing flow described above, however, the actual solutions as well as the final products can be very different. This is primarily a result of the assumptions, number of sensor variables utilized, the selected ancillary data sets and approaches used to account for the effect of the additional geophysical variables impacting the measured signal. The operational NASA AMSR-E-based retrievals have been shown to have a dampened temporal response and sensitivity range. Two possible approaches to addressing these issues are being evaluated: enhancing the theoretical basis of the existing algorithm, if feasible, or directly adjusting the dynamic range of the final soil moisture product. Both of these aspects are being actively investigated and will be discussed in our talk. Improving the quality and reliability of the global soil moisture product would result in greater acceptance and utilization in the related applications. USDA is an equal opportunity provider and employer.
NASA Astrophysics Data System (ADS)
Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J.
2016-12-01
The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP.
NASA Astrophysics Data System (ADS)
Nikodem, Antonín; Kodešová, Radka; Jakšík, Ondřej; Fér, Miroslav; Klement, Aleš
2016-04-01
This study was carried out in Southern Moravia, in the Czech Republic. The original soil unit in the wider area is a Haplic Chernozem developed on loess. The intensive agricultural exploitation in combination with terrain morphology has resulted in a highly diversified soil spatial pattern. Nowadays the original soil unit is preserved only on top of relatively flat parts, and is gradually transformed by water erosion up to Regosols on the steepest slopes, while colluvial soils are formed in terrain depressions and at toe slopes due to sedimentation of previously eroded material. Soils within this area has been intensively investigated during the last several years (e.g. Jakšík et al., 2015; Vašát et al., 2014, 2015a,b). Soil sampling (disturbed and undisturbed 100-cm3 soil samples) was performed at 5 points of one elevation transect in November 2010 (after wheat sowing) and August 2011 (after wheat harvest). Disturbed soil samples were used to determine basic soil properties (grain size distribution and organic carbon content etc.). Undisturbed soil samples were used to determine the soil water retention curves and the hydraulic conductivity functions using the multiple outflow tests in Tempe cells and a numerical inversion with HYDRUS 1-D. Scaling factors (alpha-h for pressure head, alpha-theta for soil water contents and alpha-k for hydraulic conductivities) were used here to express soil hydraulic properties variability. Evaluated scaling factors reflected position within the elevation transect as well as time of soil sampling. In general large values of alpha-h, lower values of alpha-k and similar values of alpha-theta were obtained in 2010 in comparison to values obtained in 2011, which indicates development of soil structure during the vegetation season. Jakšík, O., Kodešová, R., Kubiš, A., Stehlíková, I., Drábek, O., Kapička, A. (2015): Soil aggregate stability within morphologically diverse areas. Catena, 127, 287-299. Vašát, R., Kodešová, R., Borůvka, L., Jakšík, O., Klement, A., Drábek, O. (2015a): Absorption features in soil spectra assessment. Applied Spectroscopy, 69(12), 1425-1431. Vašát, R., Kodešová, R., Borůvka, L., Klement, A., Jakšík, O., Gholizadeh, A. (2014): Consideration of peak parameters derived from continuum-removed spectra to predict extractable nutrients in soils with visible and near-infrared diffuse reflectance spectroscopy (VNIR-DRS). Geoderma, 232-234, 208-218. Vašát, R., Kodešová, R., Klement, A., Jakšík, O. (2015b): Predicting oxidizable carbon content via visible- and near-infrared diffuse reflectance spectroscopy in soils heavily affected by water erosion. Soil and Water Research, 10 (2), 74-77.
NASA Astrophysics Data System (ADS)
Morato, M. Carmen; Castellanos, M. Teresa; Bird, Nigel; Tarquis, Ana M.
2016-04-01
Soil variability has often been a constant expected factor to take in account in soil studies. This variability could be considered to be composed of "functional" variations plus random fluctuations or noise. Multifractal formalism, first proposed by Mandelbrot (1982), is suitable for variables with self-similar distribution on a spatial domain. Multifractal analysis can provide insight into spatial variability of crop or soil parameters. In soil science, it has been quite popular to characterize the scaling property of a variable measured along a transect as a mass distribution of a statistical measure on a length domain of the studied transect. To do this, it divides it into a number of self similar segments and estimate the partition function and mass function. Based on this, the multifractal spectra (MFS) is calculated. However, another technique can be applied focus its attention in the variations of a measure analyzing the moments of the absolute differences at different scales, the Generalized Structure Function (GSF), and extracting the Generalized Hurst exponents. The aim of this study is to compare both techniques in a transect data. A common 1024 m transect across arable fields at Silsoe in Bedfordshire, east-central England were analyzed with these two multifractal methods. Properties studied were total porosity (Porosity), gravimetric water content (GWC) and nitrogen oxide flux (NO2 flux). The results showed in both methods that NO2 flux presents a clear multifractal character and a weak one in the GWC and Porosity cases. Several parameters were calculated from both methods and are discussed. On the other hand, using the partition function all the scale ranges were used, meanwhile in the GSF a shorter range of scales showed linear behavior in the bilog plots used to estimate the parameters. GWC exhibits a linear pattern from increments of 4 till 256 meters, Porosity showed this behavior from 4 till 64 meters. In case of NO2 flux only from 32 to 256 meters showed it. However, the relation between the mass exponent function and the GSF, found in the literature, was positively verified in the three variables.
Letter Report for Characterization of Biochar
DOE Office of Scientific and Technical Information (OSTI.GOV)
Amonette, James E.
2013-04-09
On 27 November 2012, a bulk biochar sample was received for characterization of selected physical and chemical properties. The main purpose of the characterization was to help determine the degree to which biochar would be suitable as a soil amendment to aid in growth of plants. Towards this end, analyses to determine specific surface, pH, cation-exchange capacity, water retention, and wettability (i.e. surface tension) were conducted. A second objective was to determine how uniform these properties were in the sample. Towards this end, the sample was separated into fractions based on initial particle size and on whether the material wasmore » from the external surface or the internal portion of the particle. Based on the results, the biochar has significant liming potentials, significant cation-retention capacities, and highly variable plant-available moisture retention properties that, under the most favorable circumstances, could be helpful to plants. As a consequence, it would be quite suitable for addition to acidic soils and should enhance the fertility of those soils.« less
Merino, Agustín; Fonturbel, María T; Fernández, Cristina; Chávez-Vergara, Bruno; García-Oliva, Felipe; Vega, Jose A
2018-06-15
Simple, rapid and reliable methods of assessing soil burn severity (SBS) are required in order to prioritize post-fire emergency stabilization actions. SBS proxies based on visual identification and changes in soil organic matter (SOM) content and quality can be related to other soil properties in order to determine the extent to which soil is perturbed following fire. This task is addressed in the present study by an approach involving the use of differential scanning calorimetry-thermogravimetric analysis (DSC-TGA) to determine changes in SOM generated in soils subjected to different levels of SBS. Intact topsoil monoliths comprising the organic horizons and the surface mineral soil (alumic-humic umbrisols) were collected from a representative P. pinaster stand in NW Spain. The monoliths were experimentally burned in a combustion wind tunnel to simulate different fire conditions (fuel bed comprising forest pine litter and wood; air flow, 0.6 m s -1 ). Changes in OM properties in the soil organic layer and mineral soils samples (0-2 cm) at the different temperatures and SBS levels were identified. For both duff and mineral soil, the data revealed a temperature-induced increase in aromatic compounds and a concomitant decrease of carbohydrates and alkyl products. However, for a given temperature, the degree of carbonization/aromatization was lower in the mineral soil than in the duff, possibly due to the different composition of the OM and to the different combustion conditions. The low degree of aromatization of the organic matter suggests that this soil component could undergo subsequent biological degradation. SOM content and thermal recalcitrance (measured as T50) discriminated the SBS levels. Use of visual identification of SBS levels in combination with DSC-TGA enables rapid evaluation of the spatial variability of the effects of fire on SOM properties. This information is useful to predict soil degradation process and implement emergency soil stabilization techniques. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Araya, Samuel N.; Fogel, Marilyn L.; Asefaw Berhe, Asmeret
2017-02-01
Fire is a major driver of soil organic matter (SOM) dynamics, and contemporary global climate change is changing global fire regimes. We conducted laboratory heating experiments on soils from five locations across the western Sierra Nevada climosequence to investigate thermal alteration of SOM properties and determine temperature thresholds for major shifts in SOM properties. Topsoils (0 to 5 cm depth) were exposed to a range of temperatures that are expected during prescribed and wild fires (150, 250, 350, 450, 550, and 650 °C). With increase in temperature, we found that the concentrations of carbon (C) and nitrogen (N) decreased in a similar pattern among all five soils that varied considerably in their original SOM concentrations and mineralogies. Soils were separated into discrete size classes by dry sieving. The C and N concentrations in the larger aggregate size fractions (2-0.25 mm) decreased with an increase in temperature, so that at 450 °C the remaining C and N were almost entirely associated with the smaller aggregate size fractions ( < 0.25 mm). We observed a general trend of 13C enrichment with temperature increase. There was also 15N enrichment with temperature increase, followed by 15N depletion when temperature increased beyond 350 °C. For all the measured variables, the largest physical, chemical, elemental, and isotopic changes occurred at the mid-intensity fire temperatures, i.e., 350 and 450 °C. The magnitude of the observed changes in SOM composition and distribution in three aggregate size classes, as well as the temperature thresholds for critical changes in physical and chemical properties of soils (such as specific surface area, pH, cation exchange capacity), suggest that transformation and loss of SOM are the principal responses in heated soils. Findings from this systematic investigation of soil and SOM response to heating are critical for predicting how soils are likely to be affected by future climate and fire regimes.
Panchadcharam, Chandrawathani; Zakaria, Zunita; Abdul Aziz, Saleha
2016-01-01
Soil is considered to be a major reservoir of Burkholderia pseudomallei in the environment. This paper investigates soil physicochemical properties that may influence presence of B. pseudomallei in soil samples from small ruminant farms in Peninsular Malaysia. Soil samples were collected from the farms and cultured for B. pseudomallei. The texture, organic matter and water contents, pH, elemental contents, cation exchange capacities, carbon, sulfur and nitrogen contents were determined. Analysis of soil samples that were positive and negative for B. pseudomallei using multivariable logistic regression found that the odds of bacterial isolation from soil was significantly higher for samples with higher contents of iron (OR = 1.01, 95%CI = 1.00–1.02, p = 0.03), water (OR = 1.28, 95%CI = 1.05–1.55, p = 0.01) and clay (OR = 1.54, 95%CI = 1.15–2.06, p = 0.004) compared to the odds of isolation in samples with lower contents of the above variables. These three factors may have favored the survival of B. pseudomallei because iron regulates expression of respiratory enzymes, while water is essential for soil ecology and agent’s biological processes and clay retains water and nutrients. PMID:27635652
Soil microbial C:N ratio is a robust indicator of soil productivity for paddy fields
NASA Astrophysics Data System (ADS)
Li, Yong; Wu, Jinshui; Shen, Jianlin; Liu, Shoulong; Wang, Cong; Chen, Dan; Huang, Tieping; Zhang, Jiabao
2016-10-01
Maintaining good soil productivity in rice paddies is important for global food security. Numerous methods have been developed to evaluate paddy soil productivity (PSP), most based on soil physiochemical properties and relatively few on biological indices. Here, we used a long-term dataset from experiments on paddy fields at eight county sites and a short-term dataset from a single field experiment in southern China, and aimed at quantifying relationships between PSP and the ratios of carbon (C) to nutrients (N and P) in soil microbial biomass (SMB). In the long-term dataset, SMB variables generally showed stronger correlations with the relative PSP (rPSP) compared to soil chemical properties. Both correlation and variation partitioning analyses suggested that SMB N, P and C:N ratio were good predictors of rPSP. In the short-term dataset, we found a significant, negative correlation of annual rice yield with SMB C:N (r = -0.99), confirming SMB C:N as a robust indicator for PSP. In treatments of the short-term experiment, soil amendment with biochar lowered SMB C:N and improved PSP, while incorporation of rice straw increased SMB C:N and reduced PSP. We conclude that SMB C:N ratio does not only indicate PSP but also helps to identify management practices that improve PSP.
Temporal and spatial variability of soil biological activity at European scale
NASA Astrophysics Data System (ADS)
Mallast, Janine; Rühlmann, Jörg
2015-04-01
The CATCH-C project aims to identify and improve the farm-compatibility of Soil Management Practices including to promote productivity, climate change mitigation and soil quality. The focus of this work concentrates on turnover conditions for soil organic matter (SOM). SOM is fundamental for the maintenance of quality and functions of soils while SOM storage is attributed a great importance in terms of climate change mitigation. The turnover conditions depend on soil biological activity characterized by climate and soil properties. Soil biological activity was investigated using two model concepts: a) Re_clim parameter within the ICBM (Introductory Carbon Balance Model) (Andrén & Kätterer 1997) states a climatic factor summarizing soil water storage and soil temperature and its influence on soil biological activity. b) BAT (biological active time) approach derived from model CANDY (CArbon and Nitrogen Dynamic) (Franko & Oelschlägel 1995) expresses the variation of soil moisture, soil temperature and soil aeration as a time scale and an indicator of biological activity for soil organic matter (SOM) turnover. During an earlier stage both model concepts, Re_clim and BAT, were applied based on a monthly data to assess spatial variability of turnover conditions across Europe. This hampers the investigation of temporal variability (e.g. intra-annual). The improved stage integrates daily data of more than 350 weather stations across Europe presented by Klein Tank et al. (2002). All time series data (temperature, precipitation and potential evapotranspiration and soil texture derived from the European Soil Database (JRC 2006)), are used to calculate soil biological activity in the arable layer. The resulting BAT and Re_clim values were spatio-temporal investigated. While "temporal" refers to a long-term trend analysis, "spatial" includes the investigation of soil biological activity variability per environmental zone (ENZ, Metzger et al. 2005 representing similar conditions for precipitation, temperature and relief) to identify ranges and hence turnover conditions for each ENZ. We will discuss the analyzed results of both concepts to assess SOM turnover conditions across Europe for historical weather data and for Spain focusing on climate scenarios. Both concepts help to separate different turnover activities and to indicate organic matter input in order to maintain the given SOM. The assessment could provide recommendations for adaptations of soil management practices. CATCH-C is funded within the 7th Framework Programme for Research, Technological Development and Demonstration, Theme 2 - Biotechnologies, Agriculture & Food (Grant Agreement N° 289782).
Zhang, Chuan; Chen, Hong-Song; Zhang, Wei; Nie, Yun-Peng; Ye, Ying-Ying; Wang, Ke-Lin
2014-06-01
Surface soil water-physical properties play a decisive role in the dynamics of deep soil water. Knowledge of their spatial variation is helpful in understanding the processes of rainfall infiltration and runoff generation, which will contribute to the reasonable utilization of soil water resources in mountainous areas. Based on a grid sampling scheme (10 m x 10 m) and geostatistical methods, this paper aimed to study the spatial variability of surface (0-10 cm) soil water content, soil bulk density and saturated hydraulic conductivity on a typical shrub slope (90 m x 120 m, projected length) in Karst area of northwest Guangxi, southwest China. The results showed that the surface soil water content, bulk density and saturated hydraulic conductivity had different spatial dependence and spatial structure. Sample variogram of the soil water content was fitted well by Gaussian models with the nugget effect, while soil bulk density and saturated hydraulic conductivity were fitted well by exponential models with the nugget effect. Variability of soil water content showed strong spatial dependence, while the soil bulk density and saturated hydraulic conductivity showed moderate spatial dependence. The spatial ranges of the soil water content and saturated hydraulic conductivity were small, while that of the soil bulk density was much bigger. In general, the soil water content increased with the increase of altitude while it was opposite for the soil bulk densi- ty. However, the soil saturated hydraulic conductivity had a random distribution of large amounts of small patches, showing high spatial heterogeneity. Soil water content negatively (P < 0.01) correlated with the bulk density and saturated hydraulic conductivity, while there was no significant correlation between the soil bulk density and saturated hydraulic conductivity.
NASA Astrophysics Data System (ADS)
Kiani, M.; Hernandez Ramirez, G.; Quideau, S.
2016-12-01
Improved knowledge about the spatial variability of plant available water (PAW), soil organic carbon (SOC), and microbial biomass carbon (MBC) as affected by land-use systems can underpin the identification and inventory of beneficial ecosystem good and services in both agricultural and wild lands. Little research has been done that addresses the spatial patterns of PAW, SOC, and MBC under different land use types at a field scale. Therefore, we collected 56 soil samples (5-10 cm depth increment), using a nested cyclic sampling design within both a native grassland (NG) site and an irrigated cultivated (IC) site located near Brooks, Alberta. Using classical statistical and geostatistical methods, we characterized the spatial heterogeneities of PAW, SOC, and MBC under NG and IC using several geostatistical methods such as ordinary kriging (OK), regression-kriging (RK), cokriging (COK), and regression-cokriging (RCOK). Converting the native grassland to irrigated cultivated land altered soil pore distribution by reducing macroporosity which led to lower saturated water content and half hydraulic conductivity in IC compared to NG. This conversion also decreased the relative abundance of gram-negative bacteria, while increasing both the proportion of gram-positive bacteria and MBC concentration. At both studied sites, the best fitted spatial model was Gaussian based on lower RSS and higher R2 as criteria. The IC had stronger degree of spatial dependence and longer range of spatial auto-correlation revealing a homogenization of the spatial variability of soil properties as a result of intensive, recurrent agricultural activities. Comparison of OK, RK, COK, and RCOK approaches indicated that cokriging method had the best performance demonstrating a profound improvement in the accuracy of spatial estimations of PAW, SOC, and MBC. It seems that the combination of terrain covariates such as elevation and depth-to-water with kriging techniques offers more capability for incorporating explicit ancillary information in predictive soil mapping. Overall, identification of spatial patterns of soil properties in agricultural lands gives a bird's eye view to land owners to implement and improve management practices which lead to more sustainable production.
NASA Astrophysics Data System (ADS)
Mataix-Solera, Jorge; Zornoza, Raúl
2013-04-01
Although forest fires must be considered as a natural factor in Mediterranean ecosystems, the modification of its natural regime during last five decades has thansformed them in an environmental problem. In the Valencia region (E Spain) 1994 was the worst year in the history affecting more than 120,000 hectares. I started my Ph.D that year by studying the effects of fires in soil properties. The availability to be able to analyse a great set of different types of soil properties in the laboratories of University of Alicante allowed me to explore how fires could affect physical, chemical and micobiological soil properties. After years studying different soil properties, finding that several factors are involved, including: fire intensity and severity, vegetation, soil type, climate conditions, etc. (Mataix-Solera and Doerr, 2004; Mataix-Solera et al., 2008, 2011) my research as Ph-D supervisor has been focussed to investigate more in depth some selected properties, such as aggregate stability and water repellency (Arcenegui et al., 2007, 2008). But one of the main problems in the studies conducted with samples affected by wildfires is that for the evaluation of the fire impact in the soil it is necessary to have control (unburned) soil samples from a similar non-affected near area. The existing spatial variability under field conditions does not allow having comparable samples in some acses to develop a correct assessment. With this idea in mind one of my Ph.D researcher (R. Zornoza) dedicated his thesis to develope soil quality indices capable to assess the impact of soil perturbations without comparing groups of samples, but evaluating the equilibrium among different soil properties within each soil sample (Zornoza et al., 2007, 2008). Key words: wildfire, Mediterranean soils, soil degradation, wàter repellency, aggregate stability References: Arcenegui, V., Mataix-Solera, J., Guerrero, C., Zornoza, R., Mayoral, A.M., Morales, J., 2007. Factors controlling the water repellency induced by fire in calcareous Mediterranean forest soils. Eur. J. Soil Sci. 58, 1254-1259. Arcenegui, V., Mataix-Solera, J., Guerrero, C., Zornoza, R., Mataix-Beneyto, J., García-Orenes, F., 2008. Immediate effects of wildfires on water repellency and aggregate stability in Mediterranean calcareous soils. Catena 74, 219-226. Mataix-Solera, J., Doerr, S.H., 2004. Hydrophobicity and aggregate stability in calcareous topsoil from fire affected pine forests in southeastern Spain. Geoderma 118, 77-88. Mataix-Solera, J., Arcenegui, V., Guerrero, C., Jordán, M., Dlapa, P., Tessler, N., Wittenberg, L. 2008. Can terra rossa become water repellent by burning? A laboratory approach. Geoderma, 147, 178-184. Mataix-Solera, J., Cerdà, A., Arcenegui, V., Jordán, A., Zavala, L.M., 2011. Fire effects on soil aggregation: a review. Earth-Science Reviews 109, 44-60 Zornoza, R., Mataix-Solera, J., Guerrero, C., Arcenegui, V., Mayoral, A.M., Morales, J. Mataix-Beneyto, J., 2007b. Soil properties under natural forest in the Alicante Province of Spain. Geoderma. 142, 334-341. Zornoza, R., Mataix-Solera, J., Guerrero, C., Arcenegui, V., Mataix-Beneyto, J., Gómez, I., 2008. Validating the effectiveness and sensitivity of two soil quality indices based on natural forest soils under Mediterranean conditions. Soil Biology & Biochemistry. 40, 2079-2087.
NASA Astrophysics Data System (ADS)
Higgins, M. A.; Asner, G. P.; Perez, E.; Elespuru, N.; Alonso, A.
2014-03-01
Tropical forests vary substantially in aboveground properties such as canopy height, canopy structure, and plant species composition, corresponding to underlying variations in soils and geology. Forest properties are often difficult to detect and map in the field, however, due to the remoteness and inaccessibility of these forests. Spectral mixture analysis of Landsat imagery allows mapping of photosynthetic and nonphotosynthetic vegetation quantities (PV and NPV), corresponding to biophysical properties such as canopy openness, forest productivity, and disturbance. Spectral unmixing has been used for applications ranging from deforestation monitoring to identifying burn scars from past fires, but little is known about variations in PV and NPV in intact rainforest. Here we use spectral unmixing of Landsat imagery to map PV and NPV in northern Amazonia, and to test their relationship to soils and plant species composition. To do this we sampled 117 sites crossing a geological boundary in northwestern Amazonia for soil cation concentrations and plant species composition. We then used the Carnegie Landsat Analysis System to map PV and NPV for these sites from multiple dates of Landsat imagery. We found that soil cation concentrations and plant species composition consistently explain a majority of the variation in remotely sensed PV and NPV values. After combining PV and NPV into a single variable (PV-NPV), we determined that the influence of soil properties on canopy properties was inseparable from the influence of plant species composition. In all cases, patterns in PV and NPV corresponded to underlying geological patterns. Our findings suggest that geology and soils regulate canopy PV and NPV values in intact tropical forest, possibly through changes in plant species composition.
NASA Astrophysics Data System (ADS)
Higgins, M. A.; Asner, G. P.; Perez, E.; Elespuru, N.; Alonso, A.
2014-07-01
Tropical forests vary substantially in aboveground properties such as canopy height, canopy structure, and plant species composition, corresponding to underlying variations in soils and geology. Forest properties are often difficult to detect and map in the field, however, due to the remoteness and inaccessibility of these forests. Spectral mixture analysis of Landsat imagery allows mapping of photosynthetic and nonphotosynthetic vegetation quantities (PV and NPV), corresponding to biophysical properties such as canopy openness, forest productivity, and disturbance. Spectral unmixing has been used for applications ranging from deforestation monitoring to identifying burn scars from past fires, but little is known about variations in PV and NPV in intact rainforests. Here we use spectral unmixing of Landsat imagery to map PV and NPV in northern Amazonia, and to test their relationship to soils and plant species composition. To do this we sampled 117 sites crossing a geological boundary in northwestern Amazonia for soil cation concentrations and plant species composition. We then used the Carnegie Landsat Analysis System to map PV and NPV for these sites from multiple dates of Landsat imagery. We found that soil cation concentrations and plant species composition consistently explain a majority of the variation in remotely sensed PV and NPV values. After combining PV and NPV into a single variable (PV-NPV), we determined that the influence of soil properties on canopy properties was inseparable from the influence of plant species composition. In all cases, patterns in PV and NPV corresponded to underlying geological patterns. Our findings suggest that geology and soils regulate canopy PV and NPV values in intact tropical forests, possibly through changes in plant species composition.
Monokrousos, Nikolaos; Boutsis, George; Diamantopoulos, John D
2014-12-01
The aim of this study was to assess the seasonal development of the physicochemical (pH, organic C, organic N, extractable P, Ca(2+), Mg(2+)) and biological soil properties (microbial biomass, activities of urease, dehydrogenase and alkaline phosphatase) of the topsoil of mine deposition sites that differed based on the material used exclusively for their creation: (a) marlstones, (b) red-grey formations (RGF), and (c) fly ash (FA), during the first year after their creation. Our hypothesis was that all deposition sites, regardless the material they consist of, present equal opportunities for the establishment of spontaneous vegetation. All macronutrients concentrations (P, Ca(2+), and Mg(2+)) remained constant with time and were found to be higher in the FA sites. Organic C, organic N, all enzyme activities, and microbial biomass were higher in the RGF and marl depositions, with marl sites presenting the highest values. All values of biological variables, with the exception of alkaline phosphatase, increased with time. The alkaline environment along with the slow improvement in soil biological properties of the FA sites seemed to present the most unfavorable conditions for spontaneous vegetation growth. On the contrary, the other two spoil materials presented significant improvement in the initial stages of soil formation in terms of soil functionality.
Variability and scaling of hydraulic properties for 200 Area soils, Hanford Site
DOE Office of Scientific and Technical Information (OSTI.GOV)
Khaleel, R.; Freeman, E.J.
Over the years, data have been obtained on soil hydraulic properties at the Hanford Site. Much of these data have been obtained as part of recent site characterization activities for the Environmental Restoration Program. The existing data on vadose zone soil properties are, however, fragmented and documented in reports that have not been formally reviewed and released. This study helps to identify, compile, and interpret all available data for the principal soil types in the 200 Areas plateau. Information on particle-size distribution, moisture retention, and saturated hydraulic conductivity (K{sub s}) is available for 183 samples from 12 sites in themore » 200 Areas. Data on moisture retention and K{sub s} are corrected for gravel content. After the data are corrected and cataloged, hydraulic parameters are determined by fitting the van Genuchten soil-moisture retention model to the data. A nonlinear parameter estimation code, RETC, is used. The unsaturated hydraulic conductivity relationship can subsequently be predicted using the van Genuchten parameters, Mualem`s model, and laboratory-measured saturated hydraulic conductivity estimates. Alternatively, provided unsaturated conductivity measurements are available, the moisture retention curve-fitting parameters, Mualem`s model, and a single unsaturated conductivity measurement can be used to predict unsaturated conductivities for the desired range of field moisture regime.« less
Pyrogenic Carbon in forest soils across climate and soil property gradients in Switzerland
NASA Astrophysics Data System (ADS)
Reisser, Moritz; González Domínguez, Beatriz R.; Hagedorn, Frank; Abiven, Samuel
2016-04-01
Soil organic carbon (SOC) is an important measure for soil quality. Usually a high organic matter content in soils is favourable for most ecosystems. As a very stable component, pyrogenic organic carbon (PyC) can be of major interest to investigate to potential of organic matter, to persist very long in soils. Recent studies have shown, that the mean residence time of organic matter is not only due to its intrinsic chemical nature, but also to a variety of abiotic and biotic variables set by the ecosystem. Especially for PyC it is unclear, whether its content is related to fire regime, soil properties or other climatic conditions. In this study we wanted to investigate, how climatic and soil-related conditions are influencing the persistence of PyC in soils. Therefore we used a sample set from Swiss forest soil (n = 54), which was designed for the purpose of having most differing climatic conditions (aridity and temperature) and a large range of soil properties (pH between 3.4 and 7.6; clay content between 4.7 % and 60 %). The soils were sampled in the first 20 cm of the mineral horizon on a representative plot area of 40 x 40 m. The soils were sieved to 2 mm and dried prior to the analysis. We used the benzene polycarboxylic acids (BPCA) molecular marker method to quantify and characterize PyC in these soil samples. Despite the large span in environmental conditions, we observed rather small differences in the contribution of PyC to SOC between warmer and colder, as well as between wetter and dryer soils. The PyC content in SOC lies well in range with a global average for forest soils estimated in other studies. Stocks of PyC vary more than the content, because of the large range of SOC contents in the samples. The influence of other parameters like soil properties is still under investigation. Qualitative investigation of the BPCAs showed that the degree of condensation, defined by the relative amount of B6CA in the total BPCA, was higher in warmer soils. This might be explained by the fact that warmer conditions favour decomposition of organic matter and leave a higher relative amount of the most condensed and therefore also stable molecules.
NASA Astrophysics Data System (ADS)
Marinho, Mara de A.; Dafonte, Jorge D.; Armesto, Montserrat V.; Paz-González, Antonio; Raposo, Juan R.
2013-04-01
Spatial characterization of the variability of soil properties is a central point in site-specific agricultural management and precision agriculture. Geospatial measures of geophysical attributes are useful not only to rapidly characterize the spatial variability of soil properties but also for soil sampling optimization. This work reports partial results obtained at an experimental parcel under pasture located at Castro de Ribeira do Lea (Lugo/ Galicia/ Spain). An ECa automated survey was conducted in September 2011 employing an EM-38 DD (Geonics Ltd.) installed in a nonmetallic car, according to parallel lines spaced 10m one from each other and oriented at the east-west direction. The ECa values were recorded every second with a field computer and the locations were geo-referenced using a GPS. The entire survey was carried out in 1hour and 45 minutes and corrections due to differences in temperature were made. A total of 9.581 ECa registers were retained, configuring a sampling intensity of approximately 1 register per 1.5 m2. Employing the software ESAP 2.35 and the computational tool ESAP-RSSD, eighty positions were selected at the field to extract disturbed and undisturbed soil samples at two depths: 0.0-0.2m, 0.2-0.4m. Ten physical attributes (clay, silt, total sand, coarse sand and fine sand contents, soil bulk density, particle density, total porosity, soil water content, percentage of gravels) and 17 chemical attributes (soil organic matter-SOM, pH, P, K, Ca, Mg, Al, H+Al, Sum of bases-S, Cation exchange capacity-CEC, Base saturation-V%, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) were determined. The relationship between the geophysical variables and the soil attributes was performed using statistical and spatial analysis. There were significant correlations (p<0.01) between the geophysical variables and the textural attributes clay, silt, total sand and coarse sand contents. The biggest correlation (0.5623) was between ECa-V (vertical component) and clay content. Also, significant correlations (p<0.05) were found between the ECa-V and soil bulk density, total porosity, percentage of gravels and soil water content. Considering the chemical attributes, significant correlations (p< 0.01) were found between ECa-V and SOM and Cd, and between ECa-H (horizontal component) and SOM and Fe. Other significant correlations (p<0.05) were found between ECa-V and 6 soil chemical attributes: P, Ca, S, Fe, Ni and Pb. The biggest correlation was between ECa-V and SOM (-0.5942). In resume, clay content, SOM, Cd and Fe are the soil attributes better correlated with the observed variation of the ECa at the field. Additional analysis should be performed to compare the spatial patterns of these soil attributes and the ECa as a tool to proper define management zones in the area. Acknowledgements: This work was funded in part by Spanish Ministry of Science and Innovation (MICINN) in the frame of project CGL2009-13700-C02. Financial support from CAPES/GOV., Brazil, is also acknowledged by Prof. M. de A. Marinho.
Soil water repellency: the knowledge base, advances and challenges
NASA Astrophysics Data System (ADS)
Doerr, S. H.
2012-04-01
The topic of soil water repellency (SWR or soil hydrophobicity) has moved from being perhaps a little known curiosity a few decades ago to a well established sub-discipline of soil physics and soil hydrology. In terms of the number of journal publications, SWR is comparable with other physical soil properties or processes such as crusting, aggregation or preferential flow. SWR refers to a condition when soil does not wet readily when in contact with water. This may be evident at the soil surface, when SWR leads to prolonged ponding on soils despite the presence of sufficient pore openings, or in the soil matrix, as manifest by enhanced uneven wetting and preferential flow that is not caused by structural in homogeneity. Amongst major milestones advancing the knowledge base of SWR have been the recognition that: (1) many, if not most, soils can exhibit SWR when the soil moisture content falls below a critical threshold, (2) it can be induced (and destroyed) during vegetation fires, but many soils exhibit SWR irrespective of burning, (3) it can be caused, in principle, by a large variety of naturally-abundant chemical compounds, (4) it is typically highly variable in space, time and its degree (severity and persistence), and (5) its impacts on, for example, soil hydrology, erosion and plant growth have the potential to be very substantial, but also that impacts are often minor for naturally vegetated and undisturbed soils. Amongst the key challenges that remain are: (a) predicting accurately the conditions when soils prone to SWR actually develop this property, (b) unravelling, for fire effected environments, to what degree any presence of absence of SWR is due to fire and post-fire recovery, (c) the exact nature and origin the material causing SWR at the molecular level in different environments, (d) understanding the implications of the spatial and temporal variability at different scales, (e) the capability to model and predict under which environmental conditions its impacts are of significance, and (f) what changes to SWR and its implications we can expect under future climatic and land management conditions. This presentation aims to provide a brief overview of the main milestones reached to date in SWR research and of some of the key challenges for future research in this rapidly growing field.
Bilgili, Mehmet; Sahin, Besir; Sangun, Levent
2013-01-01
The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the "Enter" method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685-3.65% and 0.9988-0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy.
Comparing the performance of various digital soil mapping approaches to map physical soil properties
NASA Astrophysics Data System (ADS)
Laborczi, Annamária; Takács, Katalin; Pásztor, László
2015-04-01
Spatial information on physical soil properties is intensely expected, in order to support environmental related and land use management decisions. One of the most widely used properties to characterize soils physically is particle size distribution (PSD), which determines soil water management and cultivability. According to their size, different particles can be categorized as clay, silt, or sand. The size intervals are defined by national or international textural classification systems. The relative percentage of sand, silt, and clay in the soil constitutes textural classes, which are also specified miscellaneously in various national and/or specialty systems. The most commonly used is the classification system of the United States Department of Agriculture (USDA). Soil texture information is essential input data in meteorological, hydrological and agricultural prediction modelling. Although Hungary has a great deal of legacy soil maps and other relevant soil information, it often occurs, that maps do not exist on a certain characteristic with the required thematic and/or spatial representation. The recent developments in digital soil mapping (DSM), however, provide wide opportunities for the elaboration of object specific soil maps (OSSM) with predefined parameters (resolution, accuracy, reliability etc.). Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil map. This suggests the opportunity of optimization. For the creation of an OSSM one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). We started comprehensive analysis of the effects of the various DSM components on the accuracy of the output maps on pilot areas. The aim of this study is to compare and evaluate different digital soil mapping methods and sets of ancillary variables for producing the most accurate spatial prediction of texture classes in a given area of interest. Both legacy and recently collected data on PSD were used as reference information. The predictor variable data set consisted of digital elevation model and its derivatives, lithology, land use maps as well as various bands and indices of satellite images. Two conceptionally different approaches can be applied in the mapping process. Textural classification can be realized after particle size data were spatially extended by proper geostatistical method. Alternatively, the textural classification is carried out first, followed by the spatial extension through suitable data mining method. According to the first approach, maps of sand, silt and clay percentage have been computed through regression kriging (RK). Since the three maps are compositional (their sum must be 100%), we applied Additive Log-Ratio (alr) transformation, instead of kriging them independently. Finally, the texture class map has been compiled according to the USDA categories from the three maps. Different combinations of reference and training soil data and auxiliary covariables resulted several different maps. On the basis of the other way, the PSD were classified firstly into the USDA categories, then the texture class maps were compiled directly by data mining methods (classification trees and random forests). The various results were compared to each other as well as to the RK maps. The performance of the different methods and data sets has been examined by testing the accuracy of the geostatistically computed and the directly classified results to assess the most predictive and accurate method. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).
Beyond clay - using selective extractions to improve predictions of soil carbon content
NASA Astrophysics Data System (ADS)
Rasmussen, C.; Berhe, A. A.; Blankinship, J. C.; Crow, S. E.; Druhan, J. L.; Heckman, K. A.; Keiluweit, M.; Lawrence, C. R.; Marin-Spiotta, E.; Plante, A. F.; Schaedel, C.; Schimel, J.; Sierra, C. A.; Thompson, A.; Wagai, R.; Wieder, W. R.
2016-12-01
A central component of modern soil carbon (C) models is the use of clay content to scale the relative partitioning of decomposing plant material to respiration and mineral stabilized soil C. However, numerous pedon to plot scale studies indicate that other soil mineral parameters, such as Fe- or Al-oxyhydroxide content and specific surface area, may be more effective than clay alone for predicting soil C content and stabilization. Here we directly address the following question: Are there soil physicochemical parameters that represent mineral C association and soil C content that can replace or be used in conjunction with clay content as scalars in soil C models. We explored the relationship of soil C content to a number of soil physicochemical and physiographic parameters using the National Cooperative Soil Survey database that contains horizon level data for > 62,000 pedons spanning global ecoregions and geographic areas. The data indicated significant variation in the degree of correlation among soil C, clay and Fe-/Al-oxyhydroxides with increasing moisture variability. Specifically, dry, water-limited systems (PET/MAP > 1) presented strong positive correlations between clay and soil C, that decreased significantly to little or no correlation in wet, energy-limited systems (PET/MAP < 1). In contrast, the correlation of soil C to oxalate extractable Al+Fe increased significantly with increasing moisture availability. This pattern was particularly well expressed for subsurface B horizons. Multivariate analyses indicated similar patterns, with clear climate and ecosystem level variation in the degree of correlation among soil C and soil physicochemical properties. The results indicate a need to modify current soil C models to incorporate additional C partitioning parameters that better account for climate and ecoregion variability in C stabilization mechanisms.
NASA Astrophysics Data System (ADS)
Coppola, Antonio; Comegna, Alessandro; Dragonetti, Giovanna; Lamaddalena, Nicola; Zdruli, Pandi
2013-04-01
Interpreting and predicting the evolution of water resources and soils at regional scale are continuing challenges for natural scientists. Examples include non-point source (NPS) pollution of soil and surface and subsurface water from agricultural chemicals and pathogens, as well as overexploitation of groundwater resources. The presence and build up of NPS pollutants may be harmful for both soil and groundwater resources. The accumulation of salts and trace elements in soils can significantly impact crop productivity, while loading of salts, nitrates, trace elements and pesticides into groundwater supplies can deteriorate a source of drinking and irrigation water. Consequently, predicting the spatial distribution and fate of NPS pollutants in soils at applicative scales is now considered crucial for maintaining the fragile balance between crop productivity and the negative environmental impacts of NPS pollutants, which is a basis of sustainable agriculture. Soil scientists and hydrologists are regularly asked to assist state agencies to understand these critical environmental issues. The most frequent inquiries are related to the development of mathematical models needed for analyzing the impacts of alternative land-use and best management use and management of soil and water resources. Different modelling solutions exist, mainly differing on the role of the vadose zone and its horizontal and vertical variability in the predictive models. The vadose zone (the region from the soil surface to the groundwater surface) is a complex physical, chemical and biological ecosystem that controls the passage of NPS pollutants from the soil surface where they have been deposited or accumulated due to agricultural activities, to groundwater. Physically based distributed hydrological models require the internal variability of the vadose zone be explored at a variety of scales. The equations describing fluxes and storage of water and solutes in the unsaturated zone used in these modelling approaches have been developed at small space scales. Their extension to the applicative macroscale of the regional model is not a simple task mainly because of the heterogeneity of vadose zone properties, as well as of non-linearity of hydrological processes. Besides, one of the problems when applying distributed models is that spatial and temporal scales for data to be used as input in the models vary on a wide range of scales and are not always consistent with the model structure. Under these conditions, a strictly deterministic response to questions about the fate of a pollutant in the soil is impossible. At best, one may answer "this is the average behaviour within this uncertainty band". Consequently, the extension of these equations to account for regional-scale processes requires the uncertainties of the outputs be taken into account if the pollution vulnerability maps that may be drawn are to be used as agricultural management tools. A map generated without a corresponding map of associated uncertainties has no real utility. The stochastic stream tube approach is a frequently used to the water flux and solute transport through the vadose zone at applicative scales. This approach considers the field soil as an ensemble of parallel and statistically independent tubes, assuming only vertical flow. The stream tubes approach is generally used in a probabilistic framework. Each stream tube defines local flow properties that are assumed to vary randomly between the different stream tubes. Thus, the approach allows average water and solute behaviour be described, along with the associated uncertainty bands. These stream tubes are usually considered to have parameters that are vertically homogeneous. This would be justified by the large difference between the horizontal and vertical extent of the spatial applicative scale. Vertical is generally overlooked. Obviously, all the model outputs are conditioned by this assumption. The latter, in turn, is more dictated by the lack of information on vertical variability of soil properties. It is our opinion that, with sufficient information on soil horizonation and with an appropriate horizontal resolution, it may be demonstrated that model outputs may be largely sensitive to the vertical variability of stream tubes, even at applicative scales. Horizon differentiation is one of the main observations made by pedologists while describing soils and most analytical data are given according to soil horizons. Over the last decades, soil horizonation has been subjected to regular monitoring for mapping soil variation at regional scales. Accordingly, this study mainly aims to developing a regional-scale simulation approach for vadose zone flow and transport that use real soil profiles data based on information on vertical variability of soils. As to the methodology, the parallel column concept was applied to account for the effect of vertical heterogeneity on variability of water flow and solute transport in the vadose zone. Even if the stream tube approach was mainly introduced for (unrealistic) vertically homogeneous soils, we extended their use to real vertically variable soils. The approach relies on available datasets coming from different sources and offers quantitative answers to soil and groundwater vulnerability to non-point source of chemicals and pathogens at regional scale within a defined confidence interval. This result will be pursued through the design and building up of a spatial database containing 1). Detailed pedological information, 2). Hydrological properties mainly measured in the investigated area in different soil horizons, 3). Water table depth, 4). Spatially distributed climatic temporal series, and 5). Land use. The area of interest for the study is located in the sub-basin of Metaponto agricultural site, located in southern Basilicata Region in Italy, covering approximately 11,698 hectares, crossed by two main rivers, Sinni and Agri and from many secondary water bodies. Distributed output of soil pollutant leaching behaviour, with corresponding statistical uncertainties, will be provided and finally visualized in GIS maps. The example pollutants considered cover much of the practical pollution conditions one may found in the reality. Nevertheless, this regional- scale methodology may be applied to any specific pollutants for any soil, climatic and land use conditions. Also, as the approach is built on physically based equations, it may be extended to the predictions of any water and solute storage and fluxes (i.e., groundwater recharge) in the vadose zone. By integrating the scientific results with economic and political considerations, and with advanced information technologies, the NPS-pollution assessment may become a powerful decision support tool for guiding activities involving soil and groundwater resources and, more in general, for managing environmental resources.
Hyperspectral imagery for mapping crop yield for precision agriculture
USDA-ARS?s Scientific Manuscript database
Crop yield is perhaps the most important piece of information for crop management in precision agriculture. It integrates the effects of various spatial variables such as soil properties, topographic attributes, tillage, plant population, fertilization, irrigation, and pest infestations. A yield map...
NASA Astrophysics Data System (ADS)
Bourguignon, A.; Cerdan, O.; Desprats, J. F.; Marin, B.; Malam Issa, O.; Valentin, C.; Rajot, J. L.
2012-04-01
Land degradation and desertification are among the major environmental problems, resulting in reduced productivity and development of bare surfaces in arid and semi-arid areas of the world. One important factor that acts to increase soil stability and nutrient content, and thus to prevent water and wind erosion and enhance soil productivity of arid environment, is the presence of biological soil crusts (BSCs). They are the dominant ground cover and a key component of arid environments built up mainly by cyanobacteria. They enhance degraded soil quality by providing a stable and water-retaining substratum and increasing fertility by N and C fixations. The BioCrust project, funded by ANR (VMCS 2008), focuses on BSCs in the Sahelian zone of West Africa (Niger), a highly vulnerable zone facing soil degradation due to the harsh climatic conditions, with variable rainfall, and high anthropic pressure on land use. Unlike arid areas of developed countries (USA, Australia and Israel) or China where BSCs have been extensively studied, studies from Sahelian zone (Africa) are limited (neither the inventory of their different form nor the estimation of their spatial extension has been carried out). The form, structure and composition of BSCs vary depending on characteristics related to soils and biological composition. This study focuses on the soils characterisation using ground-based spectroradiometry. An extensive database was built included spectral measurements on BSCs, bare soils and vegetation that occur in the same area, visual criteria, in situ and laboratory measurements on the physical, chemical and biological characteristics of BSCs and their substratum. The work is carried out on geo-statistical processing of data acquired in sites along a north-south climatic gradient and three types of representative land uses. The investigated areas are highly vulnerable zone facing soil degradation due to the harsh climatic conditions, with variable rainfall, and high anthropic pressure on land use Soil surface disturbances due to the intensification of human activities. Spectral field and laboratory data were acquired in 2009, 2010 and 2011 with the FieldSpec Pro®. The spectra of soils with respect to different parameters are studied in details and their separability from BSCs, vegetation and vegetation residue as well are be analysed. First, the effect of the mineralogy and the geochemical variables on the soil reflectance properties is studied and then the feasibility to resolve some of these effects with satellite imagery (e. g., ASTER) will be tested in order to define the potential capability for identifying the locations of sensitive areas affected by soil degradation and appearance of BSCs.
A Catchment-Based Approach to Modeling Land Surface Processes in a GCM. Part 1; Model Structure
NASA Technical Reports Server (NTRS)
Koster, Randal D.; Suarez, Max J.; Ducharne, Agnes; Stieglitz, Marc; Kumar, Praveen
2000-01-01
A new strategy for modeling the land surface component of the climate system is described. The strategy is motivated by an arguable deficiency in most state-of-the-art land surface models (LSMs), namely the disproportionately higher emphasis given to the formulation of one-dimensional, vertical physics relative to the treatment of horizontal heterogeneity in surface properties -- particularly subgrid soil moisture variability and its effects on runoff generation. The new strategy calls for the partitioning of the continental surface into a mosaic of hydrologic catchments, delineated through analysis of high-resolution surface elevation data. The effective "grid" used for the land surface is therefore not specified by the overlying atmospheric grid. Within each catchment, the variability of soil moisture is related to characteristics of the topography and to three bulk soil moisture variables through a well-established model of catchment processes. This modeled variability allows the partitioning of the catchment into several areas representing distinct hydrological regimes, wherein distinct (regime-specific) evaporation and runoff parameterizations are applied. Care is taken to ensure that the deficiencies of the catchment model in regions of little to moderate topography are minimized.
A stochastic-geometric model of soil variation in Pleistocene patterned ground
NASA Astrophysics Data System (ADS)
Lark, Murray; Meerschman, Eef; Van Meirvenne, Marc
2013-04-01
In this paper we examine the spatial variability of soil in parent material with complex spatial structure which arises from complex non-linear geomorphic processes. We show that this variability can be better-modelled by a stochastic-geometric model than by a standard Gaussian random field. The benefits of the new model are seen in the reproduction of features of the target variable which influence processes like water movement and pollutant dispersal. Complex non-linear processes in the soil give rise to properties with non-Gaussian distributions. Even under a transformation to approximate marginal normality, such variables may have a more complex spatial structure than the Gaussian random field model of geostatistics can accommodate. In particular the extent to which extreme values of the variable are connected in spatially coherent regions may be misrepresented. As a result, for example, geostatistical simulation generally fails to reproduce the pathways for preferential flow in an environment where coarse infill of former fluvial channels or coarse alluvium of braided streams creates pathways for rapid movement of water. Multiple point geostatistics has been developed to deal with this problem. Multiple point methods proceed by sampling from a set of training images which can be assumed to reproduce the non-Gaussian behaviour of the target variable. The challenge is to identify appropriate sources of such images. In this paper we consider a mode of soil variation in which the soil varies continuously, exhibiting short-range lateral trends induced by local effects of the factors of soil formation which vary across the region of interest in an unpredictable way. The trends in soil variation are therefore only apparent locally, and the soil variation at regional scale appears random. We propose a stochastic-geometric model for this mode of soil variation called the Continuous Local Trend (CLT) model. We consider a case study of soil formed in relict patterned ground with pronounced lateral textural variations arising from the presence of infilled ice-wedges of Pleistocene origin. We show how knowledge of the pedogenetic processes in this environment, along with some simple descriptive statistics, can be used to select and fit a CLT model for the apparent electrical conductivity (ECa) of the soil. We use the model to simulate realizations of the CLT process, and compare these with realizations of a fitted Gaussian random field. We show how statistics that summarize the spatial coherence of regions with small values of ECa, which are expected to have coarse texture and so larger saturated hydraulic conductivity, are better reproduced by the CLT model than by the Gaussian random field. This suggests that the CLT model could be used to generate an unlimited supply of training images to allow multiple point geostatistical simulation or prediction of this or similar variables.
Evaluation of different field methods for measuring soil water infiltration
NASA Astrophysics Data System (ADS)
Pla-Sentís, Ildefonso; Fonseca, Francisco
2010-05-01
Soil infiltrability, together with rainfall characteristics, is the most important hydrological parameter for the evaluation and diagnosis of the soil water balance and soil moisture regime. Those balances and regimes are the main regulating factors of the on site water supply to plants and other soil organisms and of other important processes like runoff, surface and mass erosion, drainage, etc, affecting sedimentation, flooding, soil and water pollution, water supply for different purposes (population, agriculture, industries, hydroelectricity), etc. Therefore the direct measurement of water infiltration rates or its indirect deduction from other soil characteristics or properties has become indispensable for the evaluation and modelling of the previously mentioned processes. Indirect deductions from other soil characteristics measured under laboratory conditions in the same soils, or in other soils, through the so called "pedo-transfer" functions, have demonstrated to be of limited value in most of the cases. Direct "in situ" field evaluations have to be preferred in any case. In this contribution we present the results of past experiences in the measurement of soil water infiltration rates in many different soils and land conditions, and their use for deducing soil water balances under variable climates. There are also presented and discussed recent results obtained in comparing different methods, using double and single ring infiltrometers, rainfall simulators, and disc permeameters, of different sizes, in soils with very contrasting surface and profile characteristics and conditions, including stony soils and very sloping lands. It is concluded that there are not methods universally applicable to any soil and land condition, and that in many cases the results are significantly influenced by the way we use a particular method or instrument, and by the alterations in the soil conditions by the land management, but also due to the manipulation of the surface soil before and during the measurement. Due to the commonly found high variability, natural or induced by land management, of the soil surface and subsurface hydrological properties, and to the limitations imposed by the requirements of water for the measurements, there is proposed a simple and handy method, which do not use high volumes of water, adaptable to very different soil and land conditions, and that allow many repeated measurements with acceptable accuracy for most of the purposes. References Pla, I., 1997. A soil water balance model for monitoring soil erosion processes and effects on steep lands in the tropics. Soil Technology. 11(1):17-30. Elsevier Pla, I., 2006. Hydrological approach for assessing desertification processes in the Mediterranean region. In W.G. Kepner et al. (Editors), Desertification in the Mediterranean Region. A Security Issue. 579-600 Springer. Heidelberg (Germany) Reynolds W.D., B.T. Bowman, R.R. Brunke, C.F. Drury and C.S. Tan. 2000. Comparison of Tension Infiltrometer, Pressure Infiltrometer, and Soil Core Estimates of Saturated Hydraulic Conductivity . Soil Science Society of America Journal 64:478-484 Segal, E., S.A.Bradford, P. Shouse; N. Lazarovich, and D. Corwin. 2008. Integration of Hard and Soft Data to Characterize Field-Scale Hydraulic Properties for Flow and Transport Studies. Vadose Zone J 7:878-889 Young, E. 1991. Infiltration measurements, a review. Hydrological processes 5: 309-320.
Biogeochemistry of the Amazon River Basin: the role of aquatic ecosystems in the Amazon functioning
NASA Astrophysics Data System (ADS)
Victoria, R. L.; Ballester, V. R.; Krushe, A. V.; Richey, J. E.; Aufdenkampe, A. K.; Kavaguishi, N. L.; Gomes, B. M.; Victoria, D. D.; Montebello, A. A.; Niell, C.; Deegan, L.
2004-12-01
In this study we present the results of an integrated analysis of physical and anthropogenic controls of river biogeochemistry in Amazônia. At the meso-scale level, our results show that both soil properties and land use are the main drivers of river biogeochemistry and metabolism, with pasture cover and soil exchange cation capacity explaining 99% (p < 0.01) of the variability observed in surface water ions and nutrients concentrations. In small rivers, forest clearing can increase cations, P and C inputs. P and light are the main PPL limiting factors in forested streams, while in pasture streams N becomes limiting. P export to streams may increase or remain nearly undetectable after forest-to-pasture conversion, depending on soil type. Pasture streams on Oxisols have very low P export, while on Ultisols P export is increased. Conversions of forest to pasture leads to extensive growth of in channel Paspalum resulting in higher DOC concentrations and respiration rates. Pasture streams have higher DOC fluxes when compared to the forest ones. In pasture areas the soil are compacted, there is less infiltration and higher surface run off, leaching soil superficial layers and caring more DOC to the streams. In forest areas infiltration is deeper into the soils and canopy interaction is higher. Mineralogy and soil properties are key factors determining exports of nutrients to streams. Therefore, land use change effects on nutrient export from terrestrial to aquatic ecosystems and the atmosphere must be understood within the context of varying soil properties across the Amazon Basin.
Legay, N.; Baxendale, C.; Grigulis, K.; Krainer, U.; Kastl, E.; Schloter, M.; Bardgett, R. D.; Arnoldi, C.; Bahn, M.; Dumont, M.; Poly, F.; Pommier, T.; Clément, J. C.; Lavorel, S.
2014-01-01
Background and Aims Abiotic properties of soil are known to be major drivers of the microbial community within it. Our understanding of how soil microbial properties are related to the functional structure and diversity of plant communities, however, is limited and largely restricted to above-ground plant traits, with the role of below-ground traits being poorly understood. This study investigated the relative contributions of soil abiotic properties and plant traits, both above-ground and below-ground, to variations in microbial processes involved in grassland nitrogen turnover. Methods In mountain grasslands distributed across three European sites, a correlative approach was used to examine the role of a large range of plant functional traits and soil abiotic factors on microbial variables, including gene abundance of nitrifiers and denitrifiers and their potential activities. Key Results Direct effects of soil abiotic parameters were found to have the most significant influence on the microbial groups investigated. Indirect pathways via plant functional traits contributed substantially to explaining the relative abundance of fungi and bacteria and gene abundances of the investigated microbial communities, while they explained little of the variance in microbial activities. Gene abundances of nitrifiers and denitrifiers were most strongly related to below-ground plant traits, suggesting that they were the most relevant traits for explaining variation in community structure and abundances of soil microbes involved in nitrification and denitrification. Conclusions The results suggest that consideration of plant traits, and especially below-ground traits, increases our ability to describe variation in the abundances and the functional characteristics of microbial communities in grassland soils. PMID:25122656
A coupled approach for the three-dimensional simulation of pipe leakage in variably saturated soil
NASA Astrophysics Data System (ADS)
Peche, Aaron; Graf, Thomas; Fuchs, Lothar; Neuweiler, Insa
2017-12-01
In urban water pipe networks, pipe leakage may lead to subsurface contamination or to reduced waste water treatment efficiency. The quantification of pipe leakage is challenging due to inaccessibility and unknown hydraulic properties of the soil. A novel physically-based model for three-dimensional numerical simulation of pipe leakage in variably saturated soil is presented. We describe the newly implemented coupling between the pipe flow simulator HYSTEM-EXTRAN and the groundwater flow simulator OpenGeoSys and its validation. We further describe a novel upscaling of leakage using transfer functions derived from numerical simulations. This upscaling enables the simulation of numerous pipe defects with the benefit of reduced computation times. Finally, we investigate the response of leakage to different time-dependent pipe flow events and conclude that larger pipe flow volume and duration lead to larger leakage while the peak position in time has a small effect on leakage.
Combining climatic and soil properties better predicts covers of Brazilian biomes.
Arruda, Daniel M; Fernandes-Filho, Elpídio I; Solar, Ricardo R C; Schaefer, Carlos E G R
2017-04-01
Several techniques have been used to model the area covered by biomes or species. However, most models allow little freedom of choice of response variables and are conditioned to the use of climate predictors. This major restriction of the models has generated distributions of low accuracy or inconsistent with the actual cover. Our objective was to characterize the environmental space of the most representative biomes of Brazil and predict their cover, using climate and soil-related predictors. As sample units, we used 500 cells of 100 km 2 for ten biomes, derived from the official vegetation map of Brazil (IBGE 2004). With a total of 38 (climatic and soil-related) predictors, an a priori model was run with the random forest classifier. Each biome was calibrated with 75% of the samples. The final model was based on four climate and six soil-related predictors, the most important variables for the a priori model, without collinearity. The model reached a kappa value of 0.82, generating a highly consistent prediction with the actual cover of the country. We showed here that the richness of biomes should not be underestimated, and that in spite of the complex relationship, highly accurate modeling based on climatic and soil-related predictors is possible. These predictors are complementary, for covering different parts of the multidimensional niche. Thus, a single biome can cover a wide range of climatic space, versus a narrow range of soil types, so that its prediction is best adjusted by soil-related variables, or vice versa.
Combining climatic and soil properties better predicts covers of Brazilian biomes
NASA Astrophysics Data System (ADS)
Arruda, Daniel M.; Fernandes-Filho, Elpídio I.; Solar, Ricardo R. C.; Schaefer, Carlos E. G. R.
2017-04-01
Several techniques have been used to model the area covered by biomes or species. However, most models allow little freedom of choice of response variables and are conditioned to the use of climate predictors. This major restriction of the models has generated distributions of low accuracy or inconsistent with the actual cover. Our objective was to characterize the environmental space of the most representative biomes of Brazil and predict their cover, using climate and soil-related predictors. As sample units, we used 500 cells of 100 km2 for ten biomes, derived from the official vegetation map of Brazil (IBGE 2004). With a total of 38 (climatic and soil-related) predictors, an a priori model was run with the random forest classifier. Each biome was calibrated with 75% of the samples. The final model was based on four climate and six soil-related predictors, the most important variables for the a priori model, without collinearity. The model reached a kappa value of 0.82, generating a highly consistent prediction with the actual cover of the country. We showed here that the richness of biomes should not be underestimated, and that in spite of the complex relationship, highly accurate modeling based on climatic and soil-related predictors is possible. These predictors are complementary, for covering different parts of the multidimensional niche. Thus, a single biome can cover a wide range of climatic space, versus a narrow range of soil types, so that its prediction is best adjusted by soil-related variables, or vice versa.
NASA Astrophysics Data System (ADS)
Preston, Caroline M.; Simard, Martin; Bergeron, Yves; Bernard, Guy M.; Wasylishen, Roderick E.
2017-11-01
Wildfires are a major driver of carbon stocks and ecosystem development in Canadian boreal forests, but there is little information on amounts and properties of the charcoal produced. Using data and samples available from a previous study, we determined amounts, depth distribution and chemical properties of visually-determined charcoal (> 2 mm) in a boreal chronosequence in the Abitibi region of Quebec, Canada. Sites ranged from 24 to 2355 years since fire (ysf) and originated from low- and high-severity soil burns (> 5 cm or < 5 cm organic horizon unburned, respectively). Two or three pits were sampled at 1-cm depth intervals from 20 jack pine (Pinus banksiana) sites (one low severity and 19 high severity) and 31 black spruce (Picea mariana) sites (12 low severity and 19 high severity). Site-level charcoal stocks ranged from 50 to 5527 kg ha-1 with high within-site variability and lower stocks for the oldest sites. Depth distributions typically peaked around the organic-mineral interface, but some low-severity sites also had charcoal layers within the organic horizon. Means from 30 samples were 569 mg g-1 total C, 4.1 mg g-1 total N and 140 C/N (molar), with total C and C/N showing a trend of decline with time since fire, and total N showing an increase. Solid-state 13C CPMAS NMR spectra of nine samples showed high variability among the younger samples, but a trend to higher aromaticity for the older ones. A literature survey focusing on boreal forests similarly showed highly variable stocks and chemical properties of charcoal in organic horizon and upper mineral soil, with reduction of variance and lower stocks after several hundred years. This initial variation was also consistent with reports of highly variable temperatures and duration of charring in wildfires. Adding reports available for char production, and considering that most studies of char stocks and production are limited to the organic horizon (forest floor), suggests that initial production of charred material from boreal wildfires might be around 5-10 tonnes ha-1.
NASA Astrophysics Data System (ADS)
Bertoldi, Giacomo; Brenner, Johannes; Notarnicola, Claudia; Greifeneder, Felix; Nicolini, Irene; Della Chiesa, Stefano; Niedrist, Georg; Tappeiner, Ulrike
2015-04-01
Soil moisture content (SMC) is a key factor for numerous processes, including runoff generation, groundwater recharge, evapotranspiration, soil respiration, and biological productivity. Understanding the controls on the spatial and temporal variability of SMC in mountain catchments is an essential step towards improving quantitative predictions of catchment hydrological processes and related ecosystem services. The interacting influences of precipitation, soil properties, vegetation, and topography on SMC and the influence of SMC patterns on runoff generation processes have been extensively investigated (Vereecken et al., 2014). However, in mountain areas, obtaining reliable SMC estimations is still challenging, because of the high variability in topography, soil and vegetation properties. In the last few years, there has been an increasing interest in the estimation of surface SMC at local scales. On the one hand, low cost wireless sensor networks provide high-resolution SMC time series. On the other hand, active remote sensing microwave techniques, such as Synthetic Aperture Radars (SARs), show promising results (Bertoldi et al. 2014). As these data provide continuous coverage of large spatial extents with high spatial resolution (10-20 m), they are particularly in demand for mountain areas. However, there are still limitations related to the fact that the SAR signal can penetrate only a few centimeters in the soil. Moreover, the signal is strongly influenced by vegetation, surface roughness and topography. In this contribution, we analyse the spatial and temporal dynamics of surface and root-zone SMC (2.5 - 5 - 25 cm depth) of alpine meadows and pastures in the Long Term Ecological Research (LTER) Area Mazia Valley (South Tyrol - Italy) with different techniques: (I) a network of 18 stations; (II) field campaigns with mobile ground sensors; (III) 20-m resolution RADARSAT2 SAR images; (IV) numerical simulations using the GEOtop hydrological model (Rigon et al., 2006; Endrizzi et al., 2014). The objective of this work is to understand the physical controls of the observed SCM patterns. In particular, we want to investigate: • How the SMC signal propagates with depth, to understand the capability of SAR surface SMC observations to predict root-zone SMC. • The role of land management and vegetation properties with respect to soil and bedrock properties in determining SMC spatial variability and temporal patterns. In this context, we use the GEOtop model to understand if a relationship exists between the observed SMC patterns and the underlying runoff generation processes. Results show that meadows and pastures have different behaviours. Meadows are in general wetter because of irrigation and the presence of soils with higher organic content and higher water holding capacity. Moreover, surface and root depth SCM dynamics are correlated. In contrast, pastures are drier, with lower vegetation density and more compact soils due animal trampling. Because of shallow soils and impermeable bedrock, root zone SMC shows a different behaviour with respect to the surface, with occurrence of sub-surface saturation excess, as verified from numerical experiments performed with the hydrological model. Results suggest how SAR retrieved surface SMC can be used to extrapolate root zone SMC, when soil properties are homogenous and differences in vegetation density are properly accounted with a robust retrieval processes (Pasolli et al., in press 2015). However, in situations characterized by shallow subsurface saturation excess flow, a more sophisticated modelling approach is required to estimate root zone SMC using remote sensing observations. Bertoldi, G., Della, S., Notarnicola, C., Pasolli, L., Niedrist, G., & Tappeiner, U. (2014). Estimation of soil moisture patterns in mountain grasslands by means of SAR RADARSAT2 images and hydrological modeling, 516, 245-257. doi:10.1016/j.jhydrol.2014.02.018 Endrizzi, S., Gruber, S., Dall'Amico, M., & Rigon, R. (2014). GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects. Geoscientific Model Development, 7(6), 2831-2857. doi:10.5194/gmd-7-2831-2014 Pasolli, L., Notarnicola, C., Bertoldi, G., Bruzzone, L., Remegaldo, R., Niedrist, G, Della Chiesa S., Tappeiner, U., Zebisch, M. (2014): Multi-scale assessment of soil moisture variability in mountain areas by using active radar images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, in press 2015. Rigon, R., Bertoldi, G., & Over, T. M. (2006). GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets. Journal of Hydrometeorology, 7, 371-388. Vereecken, H., Huisman, J. A., Pachepsky, Y., Montzka, C., van der Kruk, J., Bogena, H., … Vanderborght, J. (2014). On the spatio-temporal dynamics of soil moisture at the field scale. Journal of Hydrology. doi:http://dx.doi.org/10.1016/j.jhydrol.2013.11.061
Green roof soil system affected by soil structural changes: A project initiation
NASA Astrophysics Data System (ADS)
Jelínková, Vladimíra; Dohnal, Michal; Šácha, Jan; Šebestová, Jana; Sněhota, Michal
2014-05-01
Anthropogenic soil systems and structures such as green roofs, permeable or grassed pavements comprise appreciable part of the urban watersheds and are considered to be beneficial regarding to numerous aspects (e.g. carbon dioxide cycle, microclimate, reducing solar absorbance and storm water). Expected performance of these systems is significantly affected by water and heat regimes that are primarily defined by technology and materials used for system construction, local climate condition, amount of precipitation, the orientation and type of the vegetation cover. The benefits and potencies of anthropogenic soil systems could be considerably threatened in case when exposed to structural changes of thin top soil layer in time. Extensive green roof together with experimental green roof segment was established and advanced automated monitoring system of micrometeorological variables was set-up at the experimental site of University Centre for Energy Efficient Buildings as an interdisciplinary research facility of the Czech Technical University in Prague. The key objectives of the project are (i) to characterize hydraulic and thermal properties of soil substrate studied, (ii) to establish seasonal dynamics of water and heat in selected soil systems from continuous monitoring of relevant variables, (iii) to detect structural changes with the use of X-ray Computed Tomography, (iv) to identify with the help of numerical modeling and acquired datasets how water and heat dynamics in anthropogenic soil systems are affected by soil structural changes. Achievements of the objectives will advance understanding of the anthropogenic soil systems behavior in conurbations with the temperate climate.
GlobalSoilMap France: High-resolution spatial modelling the soils of France up to two meter depth.
Mulder, V L; Lacoste, M; Richer-de-Forges, A C; Arrouays, D
2016-12-15
This work presents the first GlobalSoilMap (GSM) products for France. We developed an automatic procedure for mapping the primary soil properties (clay, silt, sand, coarse elements, pH, soil organic carbon (SOC), cation exchange capacity (CEC) and soil depth). The procedure employed a data-mining technique and a straightforward method for estimating the 90% confidence intervals (CIs). The most accurate models were obtained for pH, sand and silt. Next, CEC, clay and SOC were found reasonably accurate predicted. Coarse elements and soil depth were the least accurate of all models. Overall, all models were considered robust; important indicators for this were 1) the small difference in model diagnostics between the calibration and cross-validation set, 2) the unbiased mean predictions, 3) the smaller spatial structure of the prediction residuals in comparison to the observations and 4) the similar performance compared to other developed GlobalSoilMap products. Nevertheless, the confidence intervals (CIs) were rather wide for all soil properties. The median predictions became less reliable with increasing depth, as indicated by the increase of CIs with depth. In addition, model accuracy and the corresponding CIs varied depending on the soil variable of interest, soil depth and geographic location. These findings indicated that the CIs are as informative as the model diagnostics. In conclusion, the presented method resulted in reasonably accurate predictions for the majority of the soil properties. End users can employ the products for different purposes, as was demonstrated with some practical examples. The mapping routine is flexible for cloud-computing and provides ample opportunity to be further developed when desired by its users. This allows regional and international GSM partners with fewer resources to develop their own products or, otherwise, to improve the current routine and work together towards a robust high-resolution digital soil map of the world. Copyright © 2016 Elsevier B.V. All rights reserved.
Mapping soil texture classes and optimization of the result by accuracy assessment
NASA Astrophysics Data System (ADS)
Laborczi, Annamária; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Pásztor, László
2014-05-01
There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. The GlobalSoilMap.net (GSM) project aims to make a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution. Sand, silt and clay are among the mandatory GSM soil properties. Furthermore, soil texture class information is input data of significant agro-meteorological and hydrological models. Our present work aims to compare and evaluate different digital soil mapping methods and variables for producing the most accurate spatial prediction of texture classes in Hungary. In addition to the Hungarian Soil Information and Monitoring System as our basic data, digital elevation model and its derived components, geological database, and physical property maps of the Digital Kreybig Soil Information System have been applied as auxiliary elements. Two approaches have been applied for the mapping process. At first the sand, silt and clay rasters have been computed independently using regression kriging (RK). From these rasters, according to the USDA categories, we have compiled the texture class map. Different combinations of reference and training soil data and auxiliary covariables have resulted several different maps. However, these results consequentially include the uncertainty factor of the three kriged rasters. Therefore we have suited data mining methods as the other approach of digital soil mapping. By working out of classification trees and random forests we have got directly the texture class maps. In this way the various results can be compared to the RK maps. The performance of the different methods and data has been examined by testing the accuracy of the geostatistically computed and the directly classified results. We have used the GSM methodology to assess the most predictive and accurate way for getting the best among the several result maps. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).
NASA Astrophysics Data System (ADS)
Rodríguez-Sinobas, L.; Gil-Rodríguez, M.; Sánchez, R.; Losada, A.; Castañón, G.; Juana, L.; Laguna, F. V.; Benítez, J.
2010-05-01
Conventional drip irrigation is considered one of the most efficient irrigation systems. Alternatively to traditional surface drip irrigation systems (DI), laterals are deployed underneath the soil surface, as in subsurface drip irrigation (SDI), leading to a higher potential efficiency, which is of especial interest in places where water is a limited source. The design and management of DI and SDI systems involve selection of an appropriate combination of emitter discharge rate and spacing between emitters and the inlet pressure and irrigation time for any given set of soil, crop, and climatic conditions, as well as understanding the wetted zone pattern around the emitter. Likewise, water distribution is affected by soil hydraulic properties, initial water content, emitter discharge, irrigation frequency, evapotranspiration and root characteristics. However, complexity arousing of soil water properties and soil profile characteristics means that these are often not properly considered in the design and management of those systems. A better understanding of the infiltration process around the discharge point source should contribute to increase water use efficiency and thus to reduce the risk of environmental impact of irrigation. In this regard, numerical models have been proved to be a powerful tool to analyze the evolution of the wetting pattern during the distribution and redistribution processes, in order to explore irrigation management strategies, to set up the duration of irrigation, and finally to optimize water use efficiency. Also, irrigation design variables such as emitter spacing and discharge could also be assessed. In this study the suitability of the HYDRUS-2D to simulate infiltration process around an emitter during irrigation of a loamy soil with drip and SDI laterals has been addressed. The model was then applied in order to evaluate the main dimensions of the wetted soil volume surrounding the emitter during irrigation. Irrigation uniformity with DI and SDI laterals were determined by field evaluations at different inlet head pressures. Results were related with estimations made on water distribution within the soil that were simulated taking into account the emitter discharge at different lateral locations, initial soil water content, soil hydraulic properties and time of irrigation. Conclusions highlight the effect of emitter discharge, emitter spacing, and irrigation time on wetting patterns, and thus solute transport, in both drip and subsurface drip irrigation. The effect of emitter depth was also considered in SDI. Some recommendations for the design and management of these irrigation systems are also provided.
Merini, Luciano Jose; Cuadrado, Virginia; Giulietti, Ana María
2008-05-01
The 2,4-dichlorophenoxyacetic acid (2,4-D) is a hormone-like herbicide widely used in agriculture. Although its half life in soil is approximately two weeks, the thousands of tons introduced in the environment every year represent a risk for human health and the environment. Considering the toxic properties of this compound and its degradation products, it is important to assess and monitor the 2,4-D residues in agricultural soils. Furthermore, experiments of phyto/bioremediation are carried out to find economic and environmental friendly tools to restore the polluted soils. Accordingly, it is essential to accurately measure the amount of 2,4-D and its metabolites in soils. There is evidence that 2,4-D extraction from soil samples seriously depends on the physical and chemical properties of the soil, especially in those soils with high content of humic acids. The aim of this work was to assess the variables that influence the recovery and subsequent analysis of 2,4-D and its main metabolite (2,4-dichlorophenol) from those soils samples. The results showed that the recovery efficiency depends on the solvent and method used for the extraction, the amount and kind of solvent used for dissolving the herbicide and the soil water content at the moment of spiking. An optimized protocol for the extraction and quantification of 2,4-D and its main metabolite from soil samples is presented.
NASA Astrophysics Data System (ADS)
Wang, Tao; Zhou, Guoqing; Wang, Jianzhou; Zhou, Lei
2018-03-01
The artificial ground freezing method (AGF) is widely used in civil and mining engineering, and the thermal regime of frozen soil around the freezing pipe affects the safety of design and construction. The thermal parameters can be truly random due to heterogeneity of the soil properties, which lead to the randomness of thermal regime of frozen soil around the freezing pipe. The purpose of this paper is to study the one-dimensional (1D) random thermal regime problem on the basis of a stochastic analysis model and the Monte Carlo (MC) method. Considering the uncertain thermal parameters of frozen soil as random variables, stochastic processes and random fields, the corresponding stochastic thermal regime of frozen soil around a single freezing pipe are obtained and analyzed. Taking the variability of each stochastic parameter into account individually, the influences of each stochastic thermal parameter on stochastic thermal regime are investigated. The results show that the mean temperatures of frozen soil around the single freezing pipe with three analogy method are the same while the standard deviations are different. The distributions of standard deviation have a great difference at different radial coordinate location and the larger standard deviations are mainly at the phase change area. The computed data with random variable method and stochastic process method have a great difference from the measured data while the computed data with random field method well agree with the measured data. Each uncertain thermal parameter has a different effect on the standard deviation of frozen soil temperature around the single freezing pipe. These results can provide a theoretical basis for the design and construction of AGF.
NASA Astrophysics Data System (ADS)
Emamgolizadeh, S.; Bateni, S. M.; Shahsavani, D.; Ashrafi, T.; Ghorbani, H.
2015-10-01
The soil cation exchange capacity (CEC) is one of the main soil chemical properties, which is required in various fields such as environmental and agricultural engineering as well as soil science. In situ measurement of CEC is time consuming and costly. Hence, numerous studies have used traditional regression-based techniques to estimate CEC from more easily measurable soil parameters (e.g., soil texture, organic matter (OM), and pH). However, these models may not be able to adequately capture the complex and highly nonlinear relationship between CEC and its influential soil variables. In this study, Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) were employed to estimate CEC from more readily measurable soil physical and chemical variables (e.g., OM, clay, and pH) by developing functional relations. The GEP- and MARS-based functional relations were tested at two field sites in Iran. Results showed that GEP and MARS can provide reliable estimates of CEC. Also, it was found that the MARS model (with root-mean-square-error (RMSE) of 0.318 Cmol+ kg-1 and correlation coefficient (R2) of 0.864) generated slightly better results than the GEP model (with RMSE of 0.270 Cmol+ kg-1 and R2 of 0.807). The performance of GEP and MARS models was compared with two existing approaches, namely artificial neural network (ANN) and multiple linear regression (MLR). The comparison indicated that MARS and GEP outperformed the MLP model, but they did not perform as good as ANN. Finally, a sensitivity analysis was conducted to determine the most and the least influential variables affecting CEC. It was found that OM and pH have the most and least significant effect on CEC, respectively.
Non-Invasive Methods to Characterize Soil-Plant Interactions at Different Scales
NASA Astrophysics Data System (ADS)
Javaux, M.; Kemna, A.; Muench, M.; Oberdoerster, C.; Pohlmeier, A.; Vanderborght, J.; Vereecken, H.
2006-05-01
Root water uptake is a dynamic and non-linear process, which interacts with the soil natural variability and boundary conditions to generate heterogeneous spatial distributions of soil water. Soil-root fluxes are spatially variable due to heterogeneous gradients and hydraulic connections between soil and roots. While 1-D effective representation of the root water uptake has been successfully applied to predict transpiration and average water content profiles, finer spatial characterization of the water distribution may be needed when dealing with solute transport. Indeed, root water uptake affects the water velocity field, which has an effect on solute velocity and dispersion. Although this variability originates from small-scale processes, these may still play an important role at larger scales. Therefore, in addition to investigate the variability of the soil hydraulic properties, experimental and numerical tools for characterizing root water uptake (and its effects on soil water distribution) from the pore to the field scales are needed to predict in a proper way the solute transport. Obviously, non-invasive and modeling techniques which are helpful to achieve this objective will evolve with the scale of interest. At the pore scale, soil structure and root-soil interface phenomena have to be investigated to understand the interactions between soil and roots. Magnetic resonance imaging may help to monitor water gradients and water content changes around roots while spectral induced polarization techniques may be used to characterize the structure of the pore space. At the column scale, complete root architecture of small plants and water content depletion around roots can be imaged by magnetic resonance. At that scale, models should explicitly take into account the three-dimensional gradient dependency of the root water uptake, to be able to predict solute transport. At larger scales however, simplified models, which implicitly take into account the heterogeneous root water uptake along roots, should be preferred given the complexity of the system. At such scales, electrical resistance tomography or ground-penetrating radar can be used to map the water content changes and derive effective parameters for predicting solute transport.
Decina, Stephen M; Templer, Pamela H; Hutyra, Lucy R; Gately, Conor K; Rao, Preeti
2017-12-31
Atmospheric deposition of nitrogen (N) is a major input of N to the biosphere and is elevated beyond preindustrial levels throughout many ecosystems. Deposition monitoring networks in the United States generally avoid urban areas in order to capture regional patterns of N deposition, and studies measuring N deposition in cities usually include only one or two urban sites in an urban-rural comparison or as an anchor along an urban-to-rural gradient. Describing patterns and drivers of atmospheric N inputs is crucial for understanding the effects of N deposition; however, little is known about the variability and drivers of atmospheric N inputs or their effects on soil biogeochemistry within urban ecosystems. We measured rates of canopy throughfall N as a measure of atmospheric N inputs, as well as soil net N mineralization and nitrification, soil solution N, and soil respiration at 15 sites across the greater Boston, Massachusetts area. Rates of throughfall N are 8.70±0.68kgNha -1 yr -1 , vary 3.5-fold across sites, and are positively correlated with rates of local vehicle N emissions. Ammonium (NH 4 + ) composes 69.9±2.2% of inorganic throughfall N inputs and is highest in late spring, suggesting a contribution from local fertilizer inputs. Soil solution NO 3 - is positively correlated with throughfall NO 3 - inputs. In contrast, soil solution NH 4 + , net N mineralization, nitrification, and soil respiration are not correlated with rates of throughfall N inputs. Rather, these processes are correlated with soil properties such as soil organic matter. Our results demonstrate high variability in rates of urban throughfall N inputs, correlation of throughfall N inputs with local vehicle N emissions, and a decoupling of urban soil biogeochemistry and throughfall N inputs. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.
2015-06-01
Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate scale soil moisture estimates from the cosmic-ray sensing (CRS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower and runoff flumes used to close the water balance. We found an excellent agreement between the CRS method and the distributed sensor network (RMSE of 0.009 and 0.013 m3 m-3 at SRER and JER) at the hourly time scale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was obtained in soil moisture changes estimated from the CRS and watershed water balance methods (RMSE = 0.001 and 0.038 m3 m-3 at SRER and JER), with deviations due to bypassing of the CRS measurement depth during large rainfall events. This limitation, however, was used to show that drier-than-average conditions at SRER promoted plant water uptake from deeper layers, while the wetter-than-average period at JER resulted in leakage towards deeper soils. Using the distributed sensor network, we quantified the spatial variability of soil moisture in the CRS footprint and the relation between evapotranspiration and soil moisture, in both cases finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US. Furthermore, soil moisture spatial variability was related to evapotranspiration in a manner consistent with analytical relations derived using the CRS method, opening up new possibilities for understanding land-atmosphere interactions.
NASA Technical Reports Server (NTRS)
Roberts, Dar A.; Chadwick, Oliver A.; Batista, Getulio T.
2003-01-01
LBA research from the first phase of LBA focused on three broad categories: 1) mapping land cover and quantifying rates of change, persistence of pasture, and area of recovering forest; 2) evaluating the role of environmental factors and land-use history on soil biogeochemistry; and 3) quantifying the natural and human controls on stream nutrient concentrations. The focus of the research was regional, concentrating primarily in the state of RondBnia, but also included land-cover mapping in the vicinity of Maraba, Para, and Manaus, Amazonas. Remote sensing analysis utilized Landsat Thematic Mapper (TM) and Multispectral Scanner (MS S) data to map historical patterns of land-cover change. Specific questions addressed by the remote sensing component of the research included: 1) what is the areal extent of dominant land-cover classes? 2) what are the rates of change of dominant land cover through processes of deforestation, disturbance and regeneration? and 3) what are the dynamic properties of each class that characterize temporal variability, duration, and frequency of repeat disturbance? Biogeochemical analysis focused on natural variability and impacts of land-use/land-cover changes on soil and stream biogeochemical properties at the regional scale. An emphasis was given to specific soil properties considered to be primary limiting factors regionally, including phosphorus, nitrogen, base cations and cation-exchange properties. Stream sampling emphasized the relative effects of the rates and timing of land-cover change on stream nutrients, demonstrating that vegetation conversion alone does not impact nutrients as much as subsequent land use and urbanization.
NASA Astrophysics Data System (ADS)
Mayes, M. T.; Marin-Spiotta, E.; Ozdogan, M.; Erdogan, M. A.
2011-12-01
In ecosystems where intensive farming and grazing have been occurring for millennia, there is poor understanding of how present-day soil biogeochemical properties relate to factors associated with soil parent materials (e.g. texture, mineralogy), and the net effects of long-term land use practices. Soil organic carbon (SOC) and total soil nitrogen (TN) are important for their roles in maintaining soil structure, moisture, fertility and contributing to carbon sequestration. Our research used a state factor approach (Jenny 1981) to study effects of soil parent materials and land use practices on SOC, TN, and other properties across thirty-five sites in the Konya Basin, an arid region in south-central Turkey farmed and grazed for over 8,000 years. This project is one of the first to study land use impacts on soils at a landscape scale (500 km2) in south-central Turkey, and incorporate geospatial data (e.g. a satellite imagery-derived land cover map we developed) to aid selection of field sites. Focusing on the plough layer (0-25cm) in two depth intervals, we compared effects of agriculture, orchard cultivation and grazing land use practices and clay-loam alluvial, sandy-loam volcanic and lacustrine clay soils on soil properties using standard least squares regression analyses. SOC and TN depended strongly on parent materials, but not on land use. Averaged across both depth intervals, alluvial soil SOC and TN concentrations (19.4 ± 1.32 Mg/ha SOC, 2.86 ± 1.23 Mg/ha TN) were higher and significantly different than lacustrine (9.72 ± 3.01 Mg/ha SOC, 1.57 ± 0.69 Mg/ha TN) and volcanic soil concentrations (7.40 ± 1.72 Mg/ha SOC, 1.02 ± 0.35 Mg/ha TN). Land use significantly affected SOC and TN on alluvial soils, but not on volcanic or lacustrine soils. Our results demonstrate the potential for land use to have different effects on different soils in this region. Our data on SOC, TN and other soil properties illustrate patterns in regional SOC and TN variability not shown by previous modeling or soil survey efforts. We provide baseline information on SOC and TN that can inform benchmarks for future soil monitoring and land use planning in an arid region that is likely to be highly impacted by future climatic changes, agricultural intensification and urban development. Our results suggest the importance of accounting for soil physical properties, and land use effects that are dependent on soil parent materials in future efforts to model or account for SOC and TN in similar ancient agricultural landscapes.
Compositional Variability Associated with Stickney Crater on Phobos
NASA Technical Reports Server (NTRS)
Roush, T. L.; Hogan, R. C.
2001-01-01
Unsupervised clustering techniques identified four regions in and near Stickney crater on Phobos having unique spectral properties. These spectra are best matched by spectra of naturally occurring materials, e.g., lunar soils, meteorites, and rocks. Additional information is contained in the original extended abstract.
Multisensor on-the-go mapping of readily dispersible clay, particle size and soil organic matter
NASA Astrophysics Data System (ADS)
Debaene, Guillaume; Niedźwiecki, Jacek; Papierowska, Ewa
2016-04-01
Particle size fractions affect strongly the physical and chemical properties of soil. Readily dispersible clay (RDC) is the part of the clay fraction in soils that is easily or potentially dispersible in water when small amounts of mechanical energy are applied to soil. The amount of RDC in the soil is of significant importance for agriculture and environment because clay dispersion is a cause of poor soil stability in water which in turn contributes to soil erodibility, mud flows, and cementation. To obtain a detailed map of soil texture, many samples are needed. Moreover, RDC determination is time consuming. The use of a mobile visible and near-infrared (VIS-NIR) platform is proposed here to map those soil properties and obtain the first detailed map of RDC at field level. Soil properties prediction was based on calibration model developed with 10 representative samples selected by a fuzzy logic algorithm. Calibration samples were analysed for soil texture (clay, silt and sand), RDC and soil organic carbon (SOC) using conventional wet chemistry analysis. Moreover, the Veris mobile sensor platform is also collecting electrical conductivity (EC) data (deep and shallow), and soil temperature. These auxiliary data were combined with VIS-NIR measurement (data fusion) to improve prediction results. EC maps were also produced to help understanding RDC data. The resulting maps were visually compared with an orthophotography of the field taken at the beginning of the plant growing season. Models were developed with partial least square regression (PLSR) and support vector machine regression (SVMR). There were no significant differences between calibration using PLSR or SVMR. Nevertheless, the best models were obtained with PLSR and standard normal variate (SNV) pretreatment and the fusion with deep EC data (e.g. for RDC and clay content: RMSECV = 0,35% and R2 = 0,71; RMSECV = 0,32% and R2 = 0,73 respectively). The best models were used to predict soil properties from the field spectra collected with the VIS-NIR platform. Maps of soil properties were generated using natural neighbour (NN) interpolation. Calibration results were satisfactory for all soil properties and allowed for the generation of detailed maps. The spatial variability of RDC was in accordance with the field orthophotography. Areas of high RDC content were corresponding to area of bad plant development. Soil texture has been correctly predicted by VIS-NIR spectroscopy (laboratory or on-the-go) before. However, readily dispersible clay (an important parameter for soil stability) has never been investigated before. This study introduces the possibility of using VIS-NIR for predicting readily dispersible clay at field level. The results obtained could be used in preventing soil erosion. Acknowledgement: This research was financed by a National Science Centre grant (NCN - Poland) with decision number UMO-2012/07/B/ST10/04387
Chatterjee, Sourov; Santra, Priyabrata; Majumdar, Kaushik; Ghosh, Debjani; Das, Indranil; Sanyal, S K
2015-04-01
A large part of precision agriculture research in the developing countries is devoted towards precision nutrient management aspects. This has led to better economics and efficiency of nutrient use with off-farm advantages of environmental security. The keystone of precision nutrient management is analysis and interpretation of spatial variability of soils by establishing management zones. In this study, spatial variability of major soil nutrient contents was evaluated in the Ghoragacha village of North 24 Parganas district of West Bengal, India. Surface soil samples from 100 locations, covering different cropping systems of the village, was collected from 0 to 15 cm depth using 100×100 m grid system and analyzed in the laboratory to determine organic carbon (OC), available nitrogen (N), phosphorus (P), and potassium (K) contents of the soil as well as its water-soluble K (KWS), exchangeable K (KEX), and non-exchangeable forms of K (KNEX). Geostatistical analyses were performed to determine the spatial variation structure of each nutrient content within the village, followed by the generation of surface maps through kriging. Four commonly used semivariogram models, i.e., spherical, exponential, Gaussian, and linear models were fitted to each soil property, and the best one was used to prepare surface maps through krigging. Spherical model was found the best for available N and P contents, while linear and exponential model was the best for OC and available K, and for KWS and KNEK, Gausian model was the best. Surface maps of nutrient contents showed that N content (129-195 kg ha(-1)) was the most limiting factor throughout the village, while P status was generally very high ( 10-678 kg ha(-1)) in the soils of the present village. Among the different soil K fractions, KWS registered the maximum variability (CV 75%), while the remaining soil K fractions showed moderate to high variation. Interestingly, KNEX content also showed high variability, which essentially indicates reserve native K exploitation under intensive cultivation. These maps highlight the necessity of estimating the other soil K fractions as well for better understanding of soil K supplying capacity and K fertilization strategy rather than the current recommendations, based on the plant-available K alone. In conclusion, the present study revealed that the variability of nutrient distribution was a consequence of complex interactions between the cropping system, nutrient application rates, and the native soil characteristics, and such interactions could be utilized to develop the nutrient management strategies for intensive small-holder system.
Williamson, Tanja N.; Lee, Brad D.; Schoeneberger, Philip J.; McCauley, W. M.; Indorante, Samuel J.; Owens, Phillip R.
2014-01-01
Soil Survey Geographic Database (SSURGO) data are available for the entire United States, so are incorporated in many regional and national models of hydrology and environmental management. However, SSURGO does not provide an understanding of spatial variability and only includes saturated hydraulic conductivity (Ksat) values estimated from particle size analysis (PSA). This study showed model sensitivity to the substitution of SSURGO data with locally described soil properties or alternate methods of measuring Ksat. Incorporation of these different soil data sets significantly changed the results of hydrologic modeling as a consequence of the amount of space available to store soil water and how this soil water is moved downslope. Locally described soil profiles indicated a difference in Ksat when measured in the field vs. being estimated from PSA. This, in turn, caused a difference in which soil layers were incorporated in the hydrologic simulations using TOPMODEL, ultimately affecting how soil water storage was simulated. Simulations of free-flowing soil water, the amount of water traveling through pores too large to retain water against gravity, were compared with field observations of water in wells at five slope positions along a catena. Comparison of the simulated data with the observed data showed that the ability to model the range of conditions observed in the field varied as a function of three soil data sets (SSURGO and local field descriptions using PSA-derived Ksat or field-measured Ksat) and that comparison of absolute values of soil water storage are not valid if different characterizations of soil properties are used.
NASA Technical Reports Server (NTRS)
Mustard, John F.
1993-01-01
A linear mixing model is used to model the spectral variability of an AVIRIS scene from the western foothills of the Sierra Nevada and calibrate these radiance data to reflectance. Five spectral endmembers from the AVIRIS data, plus an ideal 'shade' endmember were required to model the continuum reflectance of each pixel in the image. Three of the endmembers were interpreted to model the surface constituents green vegetation, dry grass, and illumination. Comparison of the fraction images to the bedrock geology maps indicates that substrate composition must be a factor contributing to the spectral properties of these endmembers. Detailed examination of the reflectance spectra of the three soil endmembers reveals that differences in the amount of ferric and ferrous iron and/or organic constituents in the soils is largely responsible for the differences in spectral properties of these endmembers.
NASA Astrophysics Data System (ADS)
Weninger, Thomas; Kreiselmeier, Janis; Chandrasekhar, Parvathy; Jülich, Stefan; Schwärzel, Kai; Schwen, Andreas
2016-04-01
Estimation and modeling of soil water movement and the hydrologic balance of soils requires sound knowledge about hydraulic soil properties (HSP). The soil water characteristics, the hydraulic conductivity function and the pore size distribution (PSD) are commonly used instruments for the mathematical representation of HSP. Recent research highlighted the temporal variability of these functions caused by meteorological or land-use influences. State of the art modeling software for the continuous simulation of soil water movement uses a stationary approach for the HSP which means that their time dependent alterations and the subsequent effects on soil water balance is not considered. Mathematical approaches to describe the evolution of PSD are nevertheless known, but there is a lack of sound data basis for parameter estimation. Based on extensive field and laboratory measurements at 5 locations along a climatic gradient across Austria and Germany, this study will quantify short-term changes in HSP, detect driving forces and introduce a method to predict the effects of soil and land management actions on the soil water balance. Amongst several soil properties, field-saturated and unsaturated hydraulic conductivities will be determined using a hood infiltration experiments in the field as well as by evaporation and dewpoint potentiometer method in the lab. All measurements will be carried out multiple times over a span of 2 years which will allow a detailed monitoring of changes in HSP. Experimental sites where we expect significant inter-seasonal changes will be equipped with sensors for soil moisture and matric potential. The choice of experimental field sites follows the intention to involve especially the effects of tillage operations, different cultivation strategies, microclimatically effective structures and land-use changes. The international project enables the coverage of a broad range of soil types as well as climate conditions and hence will have broad applicability of the implemented model modifications.
The Plant Foliage Projective Coverage Change over the Northern Tibetan Plateau during 1957-2009
NASA Astrophysics Data System (ADS)
Cuo, L.
2015-12-01
Northern Tibetan Plateau is the headwater of the Yellow River, the Yangtze River and the Mekong River that support billions of the population. Vegetation change will affect the regional ecosystem and water balances through the changes in biomass and evapotranspiration. Dynamic vegetation growth is determined by physiological, morphological, bioclimatic and phenological properties. These properties are affected by climate variables such as air temperature, precipitation, soil temperature and concentration of CO2, etc. Due to climate change, some parts of the northern Tibetan Plateau are under the threat of desertification. Identifying the places of vegetation degradation and the dominant driven climatic factors will help mitigate the climate change impacts on ecosystem and water resources in this region. In this study, the changes of foliage projective coverages (FPCs) of various plant functional types (PFTs) existed in the northern Tibetan Plateau and the responses of FPCs to the four climate variables over 1957-2009 are examined. The dominant factors among the four climate variables are also identified. The Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) is modified and used for the investigation. The modified LPJ-DGVM can better account for soil temperature in the top 0.4-m depth where vegetation root concentrates over the northern Tibetan Plateau. The modified model is evaluated by using monthly and annual soil temperature observed at stations across the region, and the eco-geographic maps that describe plant types and spatial distributions developed from field surveys and satellite images for this region.
NASA Astrophysics Data System (ADS)
Maier, Martin; Paulus, Sinikka; Nicolai, Clara; Nauer, Philipp
2017-04-01
Soil-atmosphere fluxes of trace gases vary on different spatial scales, between landscapes and ecosystems down to the plot scale within apparently homogenous sites. The production and consumption of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) underlie different spatial and temporal changes, und thus, their interrelation is difficult to unravel. Small-scale variability in soil properties is well-known from soil surveys, affecting theoretically water availability for plants, soil aeration, vegetation, the local photosynthesis rate, and, eventually, greenhouse gas fluxes. We investigated the small scale variability of greenhouse gas fluxes in a homogenous Scots Pine stand in a former riparian flood plain. Soil-atmosphere fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) were carried out at 60 points on a 250 m2 plot with strata of diverse soil substrates and understory vegetation. Gas flux measurements were combined with soil physical lab measurements, and a soil vegetation survey. The soil was a source of CO2 and a sink for CH4 and N2O. No correlations between the fluxes and only weak correlations between the fluxes and soil physical factors were observed. CH4 and CO2 fluxes were significantly different for the soil-vegetation strata. Separating the dataset into the different soil-vegetation strata showed that CH4 consumption increased significantly with soil gas diffusivity and soil respiration. Methane consumption in the silt stratum was higher at a given soil gas diffusivity than in the sand stratum, indicating a higher methanotrophic microbe population and thus better habitats in silt. CH4 consumption increased with soil respiration in all strata, so that we speculate that the rhizosphere and decomposing organic litter (as origin of most of the soil respiration) facilitate a preferred habitat of methanotrophic microbes. The patterns of N2O consumption were more complex, but consumption seemed to be limited at locations with higher soil respiration. Thus, we conclude that soil texture has a significant effect on greenhouse gas fluxes on the plot scale and that the fluxes of CO2, CH4 and N2O are linked. Acknowledgement This research was financially supported by the project DFG (MA 5826/2-1).
NASA Technical Reports Server (NTRS)
Banin, Amos; Orenberg, James
1990-01-01
A series of variably proportioned iron/calcium smectite clays and iron loaded smectite clays containing iron up to the level found in the Martian soil were prepared from a typical montomorillonite clay using the Banin method. Evidence was obtained which supports the premise that these materials provide a unique and appropriate model soil system for the Martian surface in that they are consistent with the constraints imposed by the Viking surface elemental analysis, the reflectance data obtained by various spacecraft instruments and ground based telescopes, and the chemical reactivity measured by one of the Viking biology experiments, the Labeled Release (LR) experiment.
Lawrence, Gregory B.; Fernandez, Ivan J.; Richter, Daniel D.; Ross, Donald S.; Hazlett, Paul W.; Bailey, Scott W.; Oiumet, Rock; Warby, Richard A.F.; Johnson, Arthur H.; Lin, Henry; Kaste, James M.; Lapenis, Andrew G.; Sullivan, Timothy J.
2013-01-01
Environmental change is monitored in North America through repeated measurements of weather, stream and river flow, air and water quality, and most recently, soil properties. Some skepticism remains, however, about whether repeated soil sampling can effectively distinguish between temporal and spatial variability, and efforts to document soil change in forest ecosystems through repeated measurements are largely nascent and uncoordinated. In eastern North America, repeated soil sampling has begun to provide valuable information on environmental problems such as air pollution. This review synthesizes the current state of the science to further the development and use of soil resampling as an integral method for recording and understanding environmental change in forested settings. The origins of soil resampling reach back to the 19th century in England and Russia. The concepts and methodologies involved in forest soil resampling are reviewed and evaluated through a discussion of how temporal and spatial variability can be addressed with a variety of sampling approaches. Key resampling studies demonstrate the type of results that can be obtained through differing approaches. Ongoing, large-scale issues such as recovery from acidification, long-term N deposition, C sequestration, effects of climate change, impacts from invasive species, and the increasing intensification of soil management all warrant the use of soil resampling as an essential tool for environmental monitoring and assessment. Furthermore, with better awareness of the value of soil resampling, studies can be designed with a long-term perspective so that information can be efficiently obtained well into the future to address problems that have not yet surfaced.
The effect of soil properties on the toxicity of silver to the soil nitrification process.
Langdon, Kate A; McLaughlin, Mike J; Kirby, Jason K; Merrington, Graham
2014-05-01
Silver (Ag) is being increasingly used in a range of consumer products, predominantly as an antimicrobial agent, leading to a higher likelihood of its release into the environment. The present study investigated the toxicity of Ag to the nitrification process in European and Australian soils in both leached and unleached conditions. Overall, leaching of soils was found to have a minimal effect on the final toxicity data, with an average leaching factor of approximately 1. Across the soils, the toxicity was found to vary by several orders of magnitude, with concentrations of Ag causing a 50% reduction in nitrification relative to the controls (EC50) ranging from 0.43 mg Ag/kg to >640 mg Ag/kg. Interestingly, the dose-response relationships in most of the soils showed significant stimulation in nitrification at low Ag concentrations (i.e., hormesis), which in some cases produced responses up to double that observed in the controls. Soil pH and organic carbon were the properties found to have the greatest influence on the variations in toxicity thresholds across the soils, and significant relationships were developed that accounted for approximately 90% of the variability in the data. The toxicity relationships developed from the present study will assist in future assessment of potential Ag risks and enable the site-specific prediction of Ag toxicity. © 2014 SETAC.
Hu, Yu-Kun; Zhang, Ya-Lin; Liu, Guo-Fang; Pan, Xu; Yang, Xuejun; Li, Wen-Bing; Dai, Wen-Hong; Tang, Shuang-Li; Xiao, Tao; Chen, Ling-Yun; Xiong, Wei; Song, Yao-Bin; Dong, Ming
2017-02-24
Geographic patterns in leaf stoichiometry reflect plant adaptations to environments. Leaf stoichiometry variations along environmental gradients have been extensively studied among terrestrial plants, but little has been known about intraspecific leaf stoichiometry, especially for wetland plants. Here we analyzed the dataset of leaf N and P of a cosmopolitan wetland species, Phragmites australis, and environmental (geographic, climate and soil) variables from literature and field investigation in natural wetlands distributed in three climatic regions (subtropical, temperate and highland) across China. We found no clear geographic patterns in leaf nutrients of P. australis across China, except for leaf N:P ratio increasing with altitude. Leaf N and N:P decreased with mean annual temperature (MAT), and leaf N and P were closely related to soil pH, C:N ratio and available P. Redundancy analysis showed that climate and soil variables explained 62.1% of total variation in leaf N, P and N:P. Furthermore, leaf N in temperate region and leaf P in subtropical region increased with soil available P, while leaf N:P in subtropical region decreased with soil pH. These patterns in P. australis different from terrestrial plants might imply that changes in climate and soil properties can exert divergent effects on wetland and terrestrial ecosystems.
NASA Astrophysics Data System (ADS)
Abbaszadeh Afshar, Farideh; Ayoubi, Shamsollah; Besalatpour, Ali Asghar; Khademi, Hossein; Castrignano, Annamaria
2016-03-01
This study was conducted to estimate soil clay content in two depths using geophysical techniques (Ground Penetration Radar-GPR and Electromagnetic Induction-EMI) and ancillary variables (remote sensing and topographic data) in an arid region of the southeastern Iran. GPR measurements were performed throughout ten transects of 100 m length with the line spacing of 10 m, and the EMI measurements were done every 10 m on the same transect in six sites. Ten soil cores were sampled randomly in each site and soil samples were taken from the depth of 0-20 and 20-40 cm, and then the clay fraction of each of sixty soil samples was measured in the laboratory. Clay content was predicted using three different sets of properties including geophysical data, ancillary data, and a combination of both as inputs to multiple linear regressions (MLR) and decision tree-based algorithm of Chi-Squared Automatic Interaction Detection (CHAID) models. The results of the CHAID and MLR models with all combined data showed that geophysical data were the most important variables for the prediction of clay content in two depths in the study area. The proposed MLR model, using the combined data, could explain only 0.44 and 0.31% of the total variability of clay content in 0-20 and 20-40 cm depths, respectively. Also, the coefficient of determination (R2) values for the clay content prediction, using the constructed CHAID model with the combined data, was 0.82 and 0.76 in 0-20 and 20-40 cm depths, respectively. CHAID models, therefore, showed a greater potential in predicting soil clay content from geophysical and ancillary data, while traditional regression methods (i.e. the MLR models) did not perform as well. Overall, the results may encourage researchers in using georeferenced GPR and EMI data as ancillary variables and CHAID algorithm to improve the estimation of soil clay content.
Extracting Archaeological Feautres from GPR Surveys Conducted with Variable Soil Moisture Conditions
NASA Astrophysics Data System (ADS)
Morris, I. M.; Glisic, B.; Gonciar, A.
2017-12-01
As a common tool for subsurface archaeological prospection, ground penetrating radar (GPR) is a useful method for increasing the efficiency of archaeological excavations. Archaeological sites are often temporally and financially constrained, therefore having limited ability to reschedule surveys compromised by weather. Furthermore, electromagnetic GPR surveys are especially sensitive to variations in water content, soil type, and site-specific interference. In this work, GPR scans of a partially excavated Roman villa consisting of different construction materials and phases (limestone, andesite, brick) in central Romania are compared. Surveys were conducted with a 500 MHz GPR antenna in both dry (pre-rain event) and wet (post-rain event) conditions. Especially in time or depth slices, wet surveys present additional archaeological features that are not present or clear in the standard dry conditions, while simultaneously masking the clutter present in those scans. When dry, the limestone has a similar dielectric constant to the soil and does not provide enough contrast in electromagnetic properties for strong reflections despite the significant difference in their physical properties. Following precipitation, however, the electromagnetic properties of these two materials is dominated by their respective water content and the contrast is enhanced. For this reason, the wet surveys are particularly necessary for revealing reflections from the limestone features often invisible in dry surveys. GPR surveys conducted in variable environmental conditions provide unique archaeological information, with potential near-surface geophysical applications in nondestructive material characterization and identification.
Impact of alpine meadow degradation on soil hydraulic properties over the Qinghai-Tibetan Plateau
NASA Astrophysics Data System (ADS)
Zeng, Chen; Zhang, Fan; Wang, Quanjiu; Chen, Yingying; Joswiak, Daniel R.
2013-01-01
SummaryAlpine meadow soil is an important ecosystem component of the Qinghai-Tibetan Plateau. However, the alpine meadow soil is undergoing serious degradation mainly due to global climate change, overgrazing, human activities and rodents. In this paper, spatial sequencing was chosen over time succession sequencing to study the changes of soil hydraulic properties under different degrees of alpine meadow degradation. Soil saturated hydraulic conductivity (Ks) and Gardner α both at the surface and at 40-50 cm depth were investigated in the field using tension infiltrometers. Soil physical and chemical properties, together with the root index at 0-10 cm and 40-50 cm soil layer depths were also analyzed. Pearson correlations were adopted to study the relationships among the investigated factors and principal component analysis was performed to identify the dominant factor. Results show that with increasing degree of degradation, soil sand content increased while soil Ks and Gardner α as well as soil clay content, soil porosity decreased in the 0-10 cm soil layers, and organic matter and root gravimetric density decreased in both the 0-10 cm and 40-50 cm soil layers. However, soil moisture showed no significant changes with increasing degradation. With decreasing pressure head, soil unsaturated hydraulic conductivity reduced more slowly under degraded conditions than non-degraded conditions. Soil Ks and Gardner α were significantly correlated (P = 0.01) with bulk density, soil porosity, soil organic matter and root gravimetric density. Among these, soil porosity is the dominant factor explaining about 90% of the variability in total infiltration flow. Under non-degraded conditions, the infiltration flow principally depended on the presence of macropores. With increasing degree of degradation, soil macropores quickly changed to mesopores or micropores. The proportion of total infiltration flow through macropores and mesopores significantly decreased with the most substantial decrease observed for the macropores in the 0-10 cm soil layer. The substantial decrease of macropores caused a cut in soil moisture and hydraulic conductivity. This study improves the understanding and prediction of alpine meadow soil and ecosystem changes and provides guidelines for improving water flow modeling under the background of global climate change over the Qinghai-Tibetan Plateau and similar regions.
Development and application of a hillslope hydrologic model
Blain, C.A.; Milly, P.C.D.
1991-01-01
A vertically integrated two-dimensional lateral flow model of soil moisture has been developed. Derivation of the governing equation is based on a physical interpretation of hillslope processes. The lateral subsurface-flow model permits variability of precipitation and evapotranspiration, and allows arbitrary specification of soil-moisture retention properties. Variable slope, soil thickness, and saturation are all accommodated. The numerical solution method, a Crank-Nicolson, finite-difference, upstream-weighted scheme, is simple and robust. A small catchment in northeastern Kansas is the subject of an application of the lateral subsurface-flow model. Calibration of the model using observed discharge provides estimates of the active porosity (0.1 cm3/cm3) and of the saturated horizontal hydraulic conductivity (40 cm/hr). The latter figure is at least an order of magnitude greater than the vertical hydraulic conductivity associated with the silty clay loam soil matrix. The large value of hydraulic conductivity derived from the calibration is suggestive of macropore-dominated hillslope drainage. The corresponding value of active porosity agrees well with a published average value of the difference between total porosity and field capacity for a silty clay loam. ?? 1991.
Main Parameters of Soil Quality and it's Management Under Changing Climate
NASA Astrophysics Data System (ADS)
László Phd, M., ,, Dr.
2009-04-01
Reviewing Paper Introduction: Malcolm summarised the topic of soil quality and it's management in a well synthetized form in 2000. So, the soils are fundamental to the well-being and productivity of agricultural and natural ecosystems. Soil quality is a concept being developed to characterize the usefulness and health of soils. Soil quality includes soil fertility, potential productivity, contaminant levels and their effects, resource sustainability and environmental quality. A general definition of soil quality is the degree of fitness of a soil for a specific use. The existence of multiple definitions suggests that the soil quality concept continues to evolve (Kádár, 1992; Várallyay, 1992, 1994, 2005; Németh, 1996; Malcolm, 2000; Márton, 2005; Márton et al. 2007). Recent attention has focused on the sustainability of human uses of soil, based on concerns that soil quality may be declining (Boehn and Anderson, 1997). We use sustainable to mean that a use or management of soil will sustain human well-being over time. Lal (1995) described the land resources of the world (of which soil is one component) as "finite, fragile, and nonrenewable," and reported that only about 22% (3.26 billion ha) of the total land area on the globe is suitable for cultivation and at present, only about 3% (450 million ha) has a high agricultural production capacity. Because soil is in large but finite supply, and some soil components cannot be renewed within a human time frame, the condition of soils in agriculture and the environment is an issue of global concern (Howard, 1993; FAO, 1997). Concerns include soil losses from erosion, maintaining agricultural productivity and system sustainability, protecting natural areas, and adverse effects of soil contamination on human health (Haberern, 1992; Howard, 1993; Sims et al., 1997). Parr et al. (1992) state, "...soil degradation is the single most destructive force diminishing the world's soil resource base." Soil quality guidelines are intended to protect the ability of ecosystems to function properly (Kádár, 1992; Várallyay, 1992, 1994, 2005; Cook and Hendershot, 1996; Németh, 1996; Malcolm, 2000; Márton, 2005; Márton et al. 2007). The Hungarian Ministry of Environment and Water (HMEW, 2004) suggests that the Hungarian Regions should adopt a national policy "...that seeks to conserve and enhance soil quality...". Useful evaluation of soil quality requires agreement about why soil quality is important, how it is defined, how it should be measured, and how to respond to measurements with management, restoration, or conservation practices. Because determining soil quality requires one or more value judgments and because we have much to learn about soil, these issues are not easily addressed (Várallyay, 1992, 1994, 2005; Cook and Hendershot, 1996; Németh, 1996; Malcolm, 2000). Definitions of soil quality have been based both on human uses of soil and on the functions of soil within natural and agricultural ecosystems. For purposes of this work, we are showing soil quality within the context of managed agricultural ecosystems. To many in agriculture and agricultural research, productivity is analogous to soil quality. Maintaining soil quality is also a human health concern because air, groundwater and surface water consumed by humans can be adversely affected by mismanaged and contaminated soils, and because humans may be exposed to contaminated soils in residential areas (Kádár, 1992; Várallyay, 2005; Cook and Hendershot, 1996; Németh, 1996; Malcolm, 2000; Márton et al. 2007). Contamination may include heavy metals, toxic elements, excess nutrients, volatile and nonvolatile organics, explosives, radioactive isotopes and inhalable fibers (Sheppard et al., 1992; Cook and Hendershot, 1996). Soil quality is not determined by any single conserving or degrading process or property, and soil has both dynamic and relatively static properties that also vary spatially (Carter et al., 1997). Gregorich et al. (1994) state that "soil quality is a composite measure of both a soil's ability to function and how well it functions, relative to a specific use." Increasingly, contemporary discussion of soil quality includes the environmental cost of production and the potential for reclamation of degraded soils (Várallyay, 2005). Reasons for assessing soil quality in an agricultural or managed system may be somewhat different than reasons for assessing soil quality in a natural ecosystem. In an agricultural context, soil quality may be managed, to maximize production without adverse environmental effect, while in a natural ecosystem, soil quality may be observed, as a baseline value or set of values against which future changes in the system may be compared (Várallyay, 1994; Cook and Hendershot, 1996; Németh, 1996; Malcolm, 2000; Márton et al. 2007). Soil quality has historically been equated with agricultural productivity, and thus is not a new idea. Soil conservation practices to maintain soil productivity are as old as agriculture itself, with documentation dating to the Roman Empire (Jenny, 1961). The Storie Index (Storie, 1932) and USDA Land Capability Classification (Klingebiel and Montgomery, 1973) were developed to separate soils into different quality classes. Soil quality is implied in many decisions farmers make about land purchases and management, and in the economic value rural assessors place on agricultural land for purposes of taxation. Beginning in the 1930s, soil productivity ratings were developed in the United States and elsewhere to help farmers select crops and management practices that would maximize production and minimize erosion or other adverse environmental effects (Huddleston, 1984). These rating systems are important predecessors of recent attempts to quantitatively assess soil quality. In the 1970s, attempts were made to identify and protect soils of the highest productive capacity by defining "prime agricultural lands" (Miller, 1979). An idea related to soil quality is "carrying capacity". Carrying capacity is the number of individuals that can be supported in a given area (Budd, 1992). Soils with high productivity have high carrying capacity, and are considered to be high quality. Sustainability implies that a system does not exceed its carrying capacity over time. Recent attempts to define soil quality and develop indices to measure it have many of the properties of the earlier soil productivity ratings (Doran and Jones, 1996; Snakin et al., 1996; Seybold et al., 1997). Cox (1995) calls for national goals for soil quality that "... recognize the inherent links between soil, water and air quality." Haberern (1992) suggests that the decade of the 1990s is the time to study the soil as we have recognized and studied air quality and water quality in the preceding two decades. Air and water quality standards are generally based on maximum allowable concentrations of materials hazardous to human health. They are specified and enforced by regulators according to public uses of these resources. The result is that changes in air and water quality are now monitored to protect human health. With few exceptions, soil quality standards have not been set, nor have regulations been created regarding maintenance of soil quality (Várallyay, 2005; Cook and Hendershot, 1996; Malcolm, 2000; Márton et al. 2007). To the extent that soil has been the disposal site of hazardous wastes, as well as a pathway by which contamination or other applied chemicals may present a human health risk, sporadic 40 regulations of soil quality (in terms of contamination) does exist in the 27 European Union (EU) countries for not just new ones but an estimated 30 000 existing chemicals, today. These regulations are in the form of laws regulating hazardous waste, toxic substances, and pesticides. However, these standards are often contradictory, inconsistent with each other and with current methods of assessing risk. For example, in the United States, federal regulations supporting CERCLA (40 CFR) is a list of "hazardous substances" and the levels in various media (e.g., soil, water) to which the Environmental Protection Agency (EPA) must respond with a cleanup effort. However, EPA has fielded considerable controversy about contaminant levels and chemical forms that legitimately constitute a human health risk. Target cleanup levels have also been subject to debate and legislation. Soil quality assessment requires definition of a "clean" soil (Sims et al., 1997). From this point of view, good quality soil has been defined as posing "...no harm to any normal use by humans, plants or animals; not adversely affecting natural cycles or functions; and not contaminating other components of the environment" (Moen, 1988). The parallel to air and water quality is easy to draw on a conceptual level, but designation of soil quality standards is significantly complicated by soil variability and heterogeneity (Smith et al., 1993). Among the authors (Merker, 1956; Odell et al. 1984; Johnston et al., 1986; Reganold et al., 1990; Granatstein and Bezdicek, 1992; Kádár, 1992; Beke et al., 1994; Jenkinson et al., 1994; Schjenning et al., 1994; Murata et al., 1995; Biederbeck et al., 1996; Lindert et al., 1996; Romig et al., 1995; Warkentin, 1995; Carter et al., 1997; Gerzabeck et al., 1997; Seybold et al., 1997; Malcolm, 2000; Várallyay, 2005) and organizations defining soil quality are Larson and Pierce (1991), Karlen et al. (1997). The next section reviews some of the definitions and soil characteristics used to define soil quality. The reader should understand that the definition of soil quality and selection of soil characteristics needed to quantify soil quality are continuing to evolve. For example, Bouma (1989) recognized that an essential problem with definitions that produce carefully limited suitability classes is that empirical decisions must be made to separate the classes along what is essentially a continuum. That is, if soil organic matter is part of a soil quality definition, where on the continuum of soil organic matter content does one draw the line between a high quality and low quality soil? Does high organic matter content always indicate high soil quality? These are non-trivial questions under discussion by the soil science community. Carter et al. (1997) suggest a framework for evaluating soil quality that includes: 1. describing each soil function on which quality is to be based, 2. selecting soil characteristics or properties that influence the capacity of the soil to provide each function, 3. choosing indicators of characteristics that can be measured, and 4. using methods that provide accurate measurement of those indicators. The following soil functions appear frequently in the soil science literature: 1. soil maintains biological activity/productivity (Karlen et al., 1997), serves as medium for plant/crop growth (Arshad and Coen, 1992), supports plant productivity/yield (Arshad and Coen, 1992), supports human/animal health (Karlen et al., 1997); 2. partitions and regulates water/ solute flow through environment (Larson and Pierce, 1991; Arshad and Coen, 1992); 3. serves as an environmental buffer/filter (Larson and Pierce, 1991), maintains environmental quality (Arshad and Ccen, 1992); 4. cycles nutrients, water, energy and other elements through the biosphere (Anderson and Gregorich, 1984). Clearly, these functions are interrelated. Later in this chapter, discussion focuses on the first and third functions (productivity and environmental buffering) as encompassing those aspects of soil quality most debated in the literature. Larson and Pierce (1991) defined soil quality as "the capacity of a soil to function within the ecosystem boundaries and interact positively with the environment external to that ecosystem." Three soil functions are considered essential: provide a medium for plant growth, regulate and partition waterllow through the environment, and serve as an effective environmental filter. Arshad and Coen (1992) define soil quality as "the sustaining capability of a soil to accept, store and recycle water, minerals and energy for production of crops at optimum levels while preserving a healthy environment." They discuss terrain, climate and hydrology as site factors that contribute to soil quality and suggest that socioeconomic factors such as land use, operator and management should be included in a soil quality analysis. This approach is consistent with the FAO approach to land quality analysis (FAO, 1997). Karlen et al. (1992) define soil quality as "the ability of the soil to serve as a natural medium for the growth of plants that sustain human and animal life." Their definition is based on the role of soil quality in the long-term productivity of soil and maintenance of environmental quality. Doran and Parkin (1994) defined soil quality as "the capacity of a soil to function within ecosystem boundaries to sustain biological productivity, maintain environmental quality, and promote plant and animal health." Gregorich et al. (1994) define soil quality as "a composite measure of both a soil's ability to function and how well it functions relative to a specific use" or "the degree of fitness of a soil for a specific use." The Soil Science Society of America Ad Hoc Committee on Soil Health proposed that soil quality is "the capacity of a specific kind of soil to function, within natural or managed ecosystem boundaries, to sustain plant and animal productivity, maintain or enhance water and air quality, and support human health and habitation" (Karlen et al., 1997). This definition requires that five functions must be evaluated to describe soil quality: 1. sustaining biological activity, diversity, and productivity; 2. regulating and partitioning water and solute flow; 3. filtering, buffering, degrading, immobilizing and detoxifying organic and inorganic materials, including industrial and municipal byproducts and atmospheric deposition; 4. storing and cycling nutrients and other elements within the earth's biosphere; and 5. providing support of socioeconomic structures and protection for archeological treasures associated with human habitation. No soil is likely to successfully provide all of these functions, some of which occur in natural ecosystems and some of which are the result of human modification. We can summarize by saying that soil quality depends on the extent to which soil functions to benefit humans. Thus, for food production or mediation of contamination, soil quality means the extent to which a soil fulfills the role we have defined for it. Within agriculture, high quality equates to maintenance of high productivity without significant soil or environmental degradation. The Glossary of Soil Science terms produced by the Soil Science Society of America (1996) states that soil quality is an inherent attribute of a soil that is inferred from soil characteristics or indirect observations. To proceed from a dictionary definition to a measure of soil quality, a minimum dataset (MDS) of soil characteristics that represents soil quality must be selected and quantified (Papendick et al., 1995). The MDS may include biological, chemical or physical soil characteristics [Organic matter (OM), Aggregation (A), Bulk density (BD), Depth to hardpan (DH), Electrical conductivity (EC), Fertility (F), Respiration (R), pH, Soil test (ST), Yield (Y), Infiltration (I), Mineralizable nitrogen potential (MNP), Water holding capacity (WHC)]. For agriculture, the measurement of properties should lead to a relatively simple and accurate way to rank soils based on potential plant production without soil degradation. Unfortunately, commonly identified soil quality parameters may not correlate well with yield (Reganold, 1988). In the next section, we consider these four points concerning the selection and quantification of soil characteristics: 1. soil characteristics may be desirable or undesirable, 2. soil renewability involves judgment of the extent to which soil characteristics can be controlled or managed, 3. rates of change in soil characteristics vary, and 4. there may be significant temporal or spatial variation in soil characteristics. Components of soil quality definitions may include desirable and undesirable characteristics. Desirable soil characteristics may either be the presence of a property that benefits soil productivity and/or other important soil functions, or the absence of a property that is detrimental to these functions. A soil characteristic may include a range of values that contributes positively to quality and a range that contributes negatively. Soil pH, for example, may be a positive or negative characteristic depending on its value. Larson and Pierce (1991) suggest that ranges of property values can be defined as optimal, suboptimal or superoptimal. A pH range of 6 to 7.5 is optimal for production of most crops. Outside of this range, pH is suboptimal and soil quality is lower than at the optimal pH range. The complexity of the soil quality concept is illustrated by the fact that the choice of optimal pH range is crop or use dependent. Letey (1985) suggested that identification of a range of water content that is nonlimiting to plant productivity might be a good way of assessing the collective effect of soil physical characteristics that contribute to crop productivity. For soils of decreasing quality, the width of the nonlimiting water range decreases. Undesirable soil characteristics may be either the presence of contaminants or a range of values of soil characteristics that contribute negatively to soil quality. The presence of chemicals that inhibit plant root growth or the absence of nutrients that result in low yields or poor crop quality are examples of undesirable soil characteristics that lower soil quality. The extent to which soil is viewed as a renewable resource shapes our approach to soil quality. "Soil" in this context is the natural, three-dimensional, horizonated individual, not something created by earth moving machinery. For the purpose of assessing human impact on sustainability of soil quality, it may be appropriate to use only those soil properties that are slowly or nonrenewable. Shorter term assessments may be based on those properties that change rapidly and are subject to easy management. Willis and Evans (1977) argued that soil is not renewable over the short term based on studies that suggest that 30 to more than 1,000 years are required to develop 25 mm of surface soil from parent material by natural processes. Jenny (1980) also argued that soil is not renewable over the time scale to which humans relate. Howard (1993) suggests defining soil quality based on undisturbed natural soils and to set quality standards based on changes in soils which cannot be reversed naturally or by ecological approaches. The renewability of soil depends on the soil property considered. For example, once soil depth is reduced by wind or water erosion so that it is too shallow to support crops, it is not renewable within a human or management time frame. Some important soil characteristics are slowly renewable. Organic matter, most nutrients and some physical properties may be renewed through careful long-term management. Certain chemical properties (pH, salinity, N, P, K content) may be altered to a more satisfactory range for agriculture within a growing season or two, while removal of unwanted chemicals may take much longer. No soil property is permanent, but rates and frequency of change vary widely among properties. Soil properties also vary with ecosystem, arguably depending most on climate. In rangelands, for example, temporal variability is high and relatively unpredictable due to the strong dependence of soil properties on soil wetness (Herrick and Whitford, 1995). Variability in soil wetness is not restricted to rangelands and may be an especially important determinant of microbial community structure and function in both irrigated and rainfed agricultural systems. Arnold et al. (1990) suggest that changes in soil properties can be nonsystematic, periodic, or trend. Nonsystematic changes are short term and unpredictable. Periodic are predictable and trend changes tend to be in one direction over time. Carter et al. (1997) distinguish between dynamic soil properties that are most subject to change through human use and are strongly influenced by agronomic practices, and intrinsic or static properties that are not subject to rapid change or management. Examples of dynamic soil characteristics are the size, membership, distribution, and activity of a soil's microbiological community; the soil solution composition, pH, and nutrient ion concentrations, and the exchangeable cation population. Soils respond quickly to changes in conditions such as water content. As a result, the optimal frequency and distribution of soil measurements vary with the property being measured. Soil mineralogy, particle size distribution and soil depth are static soil quality indicators. Although changes occur continuously, they are slow under natural conditions. Organic matter content may be a dynamic variable, but the chemical properties of organic matter may change only over periods on the order of 100 to 1,500 years depending on texture. Soil properties that change quickly present a problem because many measurements are needed to know the average value and to determine if changes in the average indicate improvement or degradation of soil quality. Conversely, properties that change very slowly are insensitive measures of short-term changes in soil quality. Papendick et al. (1995) argue that the MDS required for soil quality analysis includes a mix of "dynamic" and relatively "static" properties. A soil quality assessment must specify area. One could use the pedon (the three-dimensional soil individual) as the unit of measure, or a soil map unit, a landscape, a field or an entire watershed. The choice will depend to some degree on what property is of interest and the spatial variability of the property. Karlen et al. (1997) propose that soil quality can be evaluated at scales ranging from points to regional, national and international. They suggest that the more detailed scales provide an opportunity to "understand" soil quality while larger scale approaches provide interdisciplinary monitoring of soil quality and changes in soil quality. Pennock et al. (1994) discuss scaling up data from discrete sampling points to landscape and regional scales. Soil physical characteristics [Aeration (A), Aggregate stability (AS), Bulk density (BD), Clay mineralogy (CM), Color (C), Consistence (dry (CD), moist (CM), wet (CW)), Depth to root limiting layer (DRLL), Hydraulic conductivity (HC), Oxygen diffusion rate (ODR), Particle size distribution (PSD), Penetration resistence (PR), Pore connectivity (PC), Pore size distribution (PSD), Soil strength (SS), Soil tilth (ST), Structure type (STY), Temperature (T), Total porosity (TP), Water-holding capacity (WHC)] are a necessary part of soil quality assessment because they often cannot be easily improved (Wagenet and Hutson, 1997). Larson and Pierce (1991) summarize the physical indicators of soil quality as those properties that influence crop production by determining: 1. whether a soil can accommodate unobstructed root growth and provide pore space of sufficient size and continuity for root penetration and expansion, 2. the extent to which the soil matrix will resist deformation, and 3. the capacity of soil for water supply and aeration. Factors such as effective rooting depth, porosity or pore size distribution, bulk density, hydraulic conductivity, soil strength and particle size distribution capture these soil functions (Malcolm, 2000; Várallyay, 2005). Reganold and Palmer (1995) use texture, color, dry and moist consistence, structure type, a structure index, bulk density of the 0-5 cm zone, penetration resistance of 0 to 20 and 20 to 40 cm zones and topsoil thickness as physical determinants of soil quality. Letey (1994) suggests that structure, texture, bulk density, and profile characteristics affect management practices in agriculture but are not directly related to plant productivity. He proposes that water potential, oxygen diffusion rate, temperature, and mechanical resistance directly affect plant growth, and thus are the best indicators of the physical quality of a soil for production. Soil tilth, a poorly defined term that describes the physical condition of soil, also may be an indicator of a soil's ability to support crops. Farmers may assess soil tilth by kicking a soil clod. More formal measurements to describe soil ti]th include bulk density, porosity, structure, roughness and aggregate characteristics (Karlen et al., 1992). Many of the processes that contribute to soil structure, aggregate stability, bulk density and porosity are not well understood, making soil tilth a difficult parameter to quantify. Soil depth is an easily measured and independent property that provides direct information about a soil's ability to support plants. Effective soil depth is the depth available for roots to explore for water and nutrients. Layers that restrict root growth or water movement include hard rock, naturally dense soil layers such as fragipans, petrocalcic and, petroferric horizons, duripans, and human-induced layers of high bulk density such as plow pans and traffic pans. Effective soil depth is a problem for agricultural use of over 50% of soils in Africa (Eswaran et al., 1997). Soil depth requirements vary with crop or species. Many vegetable crops, for example, are notably shallow rooted while grain crops and some legumes like alfalfa are deep rooted. Variation will be even greater in unmanaged, natural systems. Wheat yield in Colorado was shown to decrease from 2,700 to 1,150 kg ha' over a 60-yr period of cultivation primarily due to decrease in soil depth (Bowman et al., 1990). Assessment of soil quality based on soil chemistry, whether the property is a contaminant or part of a healthy system, requires a sampling protocol, a method of chemical analysis, an understanding of how its chemistry affects biological systems and interacts with mineral forms, methods for location of possible contamination, and standards for soil characterization (Várallyay, 2005; Németh, 1996; Malcolm, 2000). Some soil chemical properties suggested as soil quality indicators are: Base saturation percentage (BSP), Cation exchange capacity (CEC), Contaminant availability (CA), Contaminant concentration (CC), Contaminant mobility (CM), Contaminant presence (CP), Electrical conductivity (EC), ESP, Nutrient cycling rates (NCR), Ph, Plant nutrient availability (PNA), Plant nutrient content (PNC) and SAR. Nutrient availability depends on soil physical and chemical processes, such as weathering and buffering, and properties such as organic matter content, CEC and pH (Kádár, 1992; Várallyay, 1992, 1994, 2005; Németh, 1996; Malcolm, 2000; Márton, 2005; Márton et al. 2007). At low and high pH, for example, some nutrients become unavailable to plants and some toxic elements become more available. Larson and Pierce (1991) chose those chemical properties that either inhibit root growth or that affect nutrient supply due to the quantity present or the availability. Reganold and Palmer (1995) used chemical parameters related to nutrient availability as measures of soil quality, including CEC, total N and P, pH and extractable P, S, Ca, Mg and K. Karlen et al. (1992) suggest that total and available plant nutrients, and nutrient cycling rates, should be included in soil quality assessments. Soil properties may be severely compromised by intended or unintended human additions of chemical compounds and soil productivity reduced if unwanted chemicals exceed safe thresholds. Data are required to determine whether or not a site is significantly polluted and if it requires clean-up (Sims et al., 1997). International standard methods have been created to maintain the quality of measurements (Hortensius and Welling, 1996). A difficult determination is the level of each chemical that is considered an ecological risk. Beck et al. (1995) provide a list of levels for organic chemicals adopted by The Netherlands and Canada. EPA uses similar lists for compounds considered hazardous (e.g., 40 CFR). Sims et al. (1997) argue that clean and unclean are two extremes of a continuum and that it is more appropriate to define the physical, chemical and biological state of the soil as acceptable or unacceptable. In The Netherlands, soil quality reference values have been created for heavy metals and organic chemicals based on a linear relationship with soil clay and organic matter content. The Dutch Ministry of Housing, Physical Planning and Environment has used the maximum of a range of reference values for a given substance as a provisional reference value for good soil quality (Howard, 1993). The focus of many soil quality definitions is soil biology [Organic carbon (OC), Microbial biomass (MB), C and N, Total bacterial biomass (TBB), Total fungal biomass (TFB), Potentially mineralizable N (PMN), Soil respiration (SR), Enzymes (Dehydrogenase, Phosphatase, Arlysulfatase), Biomass C/total organic carbon, Respiration/biomass, Microbial community fingerprinting (MCF), Substrate utilization (SU), Fatty acid analysis (FAA), Nucleic acid analysis (NAA)]. Soil supports a diverse population of organisms, ranging in size from viruses to large mammals, that usually interacts positively with plants and other system components (Paul and Clark, 1996). However, some soil organisms such as nematodes, bacterial and fungal pathogens reduce plant productivity. Many proposed soil quality definitions focus on the presence of beneficial rather than absence of detrimental organisms, although both are critically important. Various measures of microbial community viability have been suggested as measures or indices of soil quality. Community level studies consider species diversity and frequency of occurrence of species. Visser and Parkinson (1992) found that diverse soil microbiological criteria may be used to indicate deteriorating or improving soil quality. They suggested testing the biological criteria for soil quality at three levels: population, community and ecosystem. Microorganisms and microbial communities are dynamic and diverse, making them sensitive to changes in soil conditions (Kennedy and Papendick, 1995). Their populations include fungi, bacteria including actinomycetes, protozoa, and algae. Soil microorganisms form crucial symbiotic relationships with plants, including mycorrhizal infection for P and N acquisition and bacterial infection for fixation of atmospheric N. Authors emphasizing use of biological factors as indicators of soil quality often equate soil quality with relatively dynamic properties such as microbial biomass, microbial respiration, organic matter mineralization and denitrification, and organic matter content (Yakovchenko et al., 1996; Franzluebbers and Arshad, 1997), or soil microbial C, phospholipid analyses and soil enzymes (Gregorich et al., 1997), or total organic C and N (Franco-Vizcaino, 1997). Visser and Parkinson (1992) question the suitability of enzyme assays for microbial activity and soil quality assessments. Waksman (1927), who studied measurements of soil microorganisms that could indicate soil fertility, found that physical and chemical factors as well as soil biology were needed to predict soil fertility. Meso- and macrofauna populations have also been considered as part of soil quality definitions (Berry, 1994). One could choose to use presence or absence of a particular species or population of a particular species as a measure of soil quality. Stork and Eggleton (1992) discuss species richness as a powerful indicator of invertebrate community and soil quality, although determining the number of species is a problem. They suggest that keystone species, taxonomic diversity at the group level, and species richness of several dominant groups of invertebrates can be used as part of a soil quality definition. Measuring soil fauna populations involves decisions about which organisms to measure and how to measure them. An example is the earthworm population, the size of which is frequently mentioned as an important measure of soil quality. Measurement choices include numbers of organisms per volume or weight of soil, number of species, or a combination of numbers of organisms and species. Reganold and Palmer (1995) use total earthworms per square meter, total earthworm weight (g m-') and average individual earthworm weight as biological indicators of soil quality. Measurement of one or more components of the N cycle including ammonification, nitrification and nitrogen fixation, may be used to assess soil fertility and soil quality (Visser and Parkinson, 1992). Presumably, high rates of N turnover may infer a dynamic and healthy soil biological community. In contrast, low soil quality or poor soil health may be inferred from lack of N turnover. The interpretation of N turnover rates is highly dependent on the kinds of substrates added to soils and climate variables such as soil temperature and moisture. One needs to be careful when comparing N turnover rates within soils and among different soils to be sure that the cause of differences is a soil quality parameter and not natural variability. Presence of pesticide residues, for example, may reduce N turnover rate. In such an instance, both the presence of the pesticide and the N turnover rate would be needed to determine that the soil quality had been impaired. Production incorporates use of and need for functioning soil resources in agriculture, and environmental buffering incorporates the direct and indirect effects of human use on ecosystem function and human health (Kádár, 1992; Várallyay, 1992, 1994, 2005; Németh, 1996; Malcolm, 2000; Márton, 2005; Márton et al. 2007). Worldwide agriculture is the most extensive human land use, and soil characteristics are a critical determinant of agricultural productivity. Agriculture includes irrigated and rainfed cultivated cropland, permanent crops such as orchards and vineyards, irrigated pasture, range, and forestry. Each cropping system has distinct soil and soil management conditions for optimal production. It has been suggested that soil productivity is the net resultant of soil degradation processes and soil conservation practices (Parr et al., 1990). An appropriate definition of soil quality and the criteria necessary to evaluate and monitor soil quality is a step toward "the development of systematic criteria of sustainability". Issues to be considered when discussing soil quality for agriculture include: 1. How are productivity and sustainability related? 2. Is the cropping system in question cultivated or non-cultivated? 3. Is the cropping system in question an irrigated or dryland system? Sustainability of agricultural systems is critical to human welfare and is an a subject of research and debate (Letey, 1994). High productivity and sustainability must be converging goals if the growing human population is to be fed without destroying the resources necessary to produce food. Sustainability implies that a system is at a desirable steady state. Thermodynamically, soil is an open system through which matter and energy flow and a steady state is characterized by a minimum production of entropy (Andiscott, 1995). Ellert et al. (1997) review related literature on ways of assessing soil function on an ecosystem scale, commenting that the complexity and organization of living systems, which seem to defy the second law of thermodynamics (increasing disorder/entropy), may provide a means to broadly assess ecosystem function. The purpose of agriculture is to provide products for human sustenance and by definition is not sustainable unless the nutrients removed in the products are returned to the soil. Many of the arguments about the sustainability of agricultural systems relate to the form in which nutrients are most sustainably returned. No agricultural system will be sustainable in the long run without management that considers nutrient cycling and energy budgets. The more intense the agricultural system, the more energy and resources must be expended to maintain the system. The relative quality of a soil for agriculture can depend on the resources available to farmers. In the United States, resources may be readily available for management of dynamic soil properties such as nutrient or water status. In other countries, farmers may be resource poor, and agricultural systems are generally low input, meaning that large-scale irrigation is absent, use of fertilizers, pesticides, and herbicides is minimal, and high energy, mechanized equipment is not available (Eswaran et a1.,1997). This means, for example, that soil quality for agriculture will be more dependent on climate than if the same soils were part of a highly managed, irrigated system. Similarly, sustainability is more dependent on maintenance of dynamic soil properties because resources may not exist to remedy losses (Várallyay, 2005; Malcolm, 2000; Márton et al. 2007). It is difficult to overstate the importance of irrigation to food production. One-third of the total global harvest of food comes from the 17% (250 million ha) of the world's cropland that is irrigated (Hoffman et al., 1990); three-quarters of which are in developing countries (Tribe, 1994). India, China, the former Soviet Union, the United States and Pakistan have the greatest area of irrigated land. Should soil quality criteria be the same for irrigated and dryland agriculture? Sojka (1996) suggests that the arid and semi-arid soils that support most irrigated agriculture have thin erodible surfaces, characteristics that would classify such soils as having poor quality. Yet under irrigation, they feed much of the world. Without irrigation, for example, in many African soils, moisture stress becomes a significant factor limiting production, and the water-holding capacity of a soil becomes crucial (Eswaran et al., 1997). This suggests that a standard set of criteria based on potential productivity is not a sufficient definition of soil quality. Soils that are not cultivated are a much larger component of agriculture, broadly defined, than those that are cultivated. About 65% of the land in the United States is forest (284 million ha) or range land (312 million ha), with only about 284 million hacultivated (NRC,1994). Herrick and Whitford (1995) suggest that range land soils, which often serve multiple uses, present unique challenges and opportunities for assessing soil quality because spatial and temporal variability are higher than in cropped systems. On range lands and forest lands, food, fiber, timber production, biomass for fuel, wildlife, biodiversity, recreation, and water supply are all potential uses that may have diverse criteria for quality soils. Herrick and Whitford (1995) give the example of a thick O horizon that may be an indicator of good timber production but has no predictive value of soil quality for the rancher. The National Research Council (NRC, 1994) recommends that range land health be determined using three criteria: degree of soil stability and watershed function, integrity of nutrient cycles and energy flows, and presence of functioning recovery mechanisms. Soil erosion by wind and water and infiltration or capture of precipitation were selected as processes that could be used as indicators of soil stability and watershed function. Specific indicators or properties need to be related to these two broad processes. The amount of nutrients available, the speed with which nutrients cycle, and measures of the integrity of energy flow through the system were considered fundamental components of range land health. Finally, the capacity of range land ecosystems to react to change depends on recovery mechanisms that result in capture and cycling of nutrients, capture of energy, conservation of nutrients, energy and water, and resilience to change. Specific indicators include status of vegetation, age class and distribution (Kádár, 1992; Várallyay, 1992, 1994, 2005; Németh, 1996; Malcolm, 2000; Márton et al. 2007). The evaluation of land quality for forestry is a well-known practice. Indices range from quantitative through semi-quantitative to qualitative. Quantitative evaluations, such as site index, use regression equations to predict tree height at a predetermined tree age based on soil and climate data. Qualitative evaluations assign land to classes based on soil and climate properties. In soil science, the term "buffer" refers collectively to processes that constrain shifts in the dissolved concentration of any ion when it is added to or removed from the soil system (Singer and Munns, 1996). Soils "buffer" nutrients as well as contaminants and other solutes, via sorption to or incorporation into clay and organic materials. The extent to which a soil immobilizes or chemically alters substances that are toxic, thus effectively detoxifying them, reflects "quality" in the sense that humans or other biological components of the system are protected from harm. This is the basis for the European concept of soil quality (Moen, 1988; Siegrist, 1989; Denneman and Robberse, 1990). Lack of soil function in this category is reflected as direct toxicity or as contamination of air or water. Identifying substances that qualify as "contaminants" can be challenging because some, such as nitrates and phosphates, are important plant nutrients as well as potential water pollutants. An example is agricultural runoff containing N03 or soluble P (Yli-Halla et al., 1995). This chapter does not attempt a comprehensive review of research in this area, which is covered in an earlier chapter, but instead presents a few sample articles pertinent to this aspect of soil quality. Holden and Firestone (1997) define soil quality in this context as "the degree to which the physical, chemical, and biological characteristics of the soil serve to attenuate environmental pollution." Howard (1993) defines the ecological risk of a chemical in the environment as "the probability that a random species in a large community is exposed to a concentration of the chemical greater than its no-effect level." The extent to which a soil is capable of reducing the probability of exposure is a measure of its quality. A well-studied example of a common soil contaminant is Pb (McBride et al., 1997). Although legislated limits may be on a concentration basis in soil (e.g., 500 ftg kg-'), risk assessment techniques have attempted to account for the chemical form of Pb present, as well as the observed relative relationship between the amount of Pb present in soil and blood levels in local residents (Bowers and Gauthier, 1994). Critics have questioned analytical techniques used to determine bioavailable levels of Pb in soil, as well as the degree to which toxicity data account for its chemical fate and ecologically damaging properties (Cook and Hendershot, 1996). Natural variability of soils and variation within a soil series make average values or average background values inadequate for soil quality assessments. In addition, bioaccumulation and toxicity need to be considered when establishing levels of toxicants that may not be exceeded in a "high quality" soil for a given use (Traas et al. 1996). Another example is the effect of heavy metals such as Cr(VI) on soil biological properties. Based on a study of three New Zealand soils of contrasting texture, organic matter content, and CEC, Speir et al. (1995) propose an "ecological dose value" that represents the inhibitory effects of a heavy metal (in this case, Cr(VI)) on the kinetics of soil biological properties, and serves as a generic index for determination of permissible concentration levels for heavy metals in soils. A single soil characteristic is of limited use in evaluating differences in soil quality (Reganold and Palmer, 1995). Using more than one quantitative variable requires some system for combining the measurements into a useful index (Halvorson et al., 1996). The region, crop, or general soil use for which an index was created will likely limit its effectiveness outside the scope of its intended application. Even an index designed only to rate productivity is not likely to be useful for all crops and soils, leading Gersmehl and Brown (1990) to advocate regionally targeted systems. Rice is a good example of a crop requiring significantly different soil properties than other crops. It is a food staple for a large proportion of the world population. Approximately 146 million ha were in rice production in 1989 (FAO, 1989) mainly (90%) in Asia. High quality soils for paddy rice may be poor quality for most other irrigated and dryland crops because they may be saline or sodic, and high in clay with slow infiltration and permeability. These physical and chemical properties often constrain production of other crops. Although they are not reviewed here, various land suitability classifications specifically for rice have been developed since the turn of the century (Dent, 1978). Examples of several soil quality indexing systems are presented in the following sections. To some extent, recent attempts to enumerate the factors of soil quality resemble Jenny's (1941) introduction of the interrelated factors of soil formation. An index is categorized here as nonquantitative if it does not combine evaluated parameters into a numerical index that rates soils along a continuous scale. Examples are the USDA Land Capability Classification and the US Bureau of Reclamation (USBR) Irrigation Suitability. The purpose of the Land Capability Classification (LCC) was to place arable soils into groups based on their ability to sustain common cultivated crops that do not require specialized site conditioning or treatment (Klingebiel and Montgomery, 1973). Nonarable soils, unsuitable for long-term, sustained cultivation, are grouped according to their ability to support permanent vegetation, and according to the risk of soil damage if mismanaged. The LCC combines three rating values at different levels of abstraction: capability class, subclass, and unit. At the most general level, soils are placed in eight classes according to whether they (a) are capable of producing adapted plants under good management (classes I to N), (b) are capable of producing specialized crops under highly intensive management involving "elaborate practices for soil and water conservation" (classes V to VII), or (c) do not return on-site benefits as a result of management inputs for crops, grasses or trees without major reclamation (Klingebiel and Montgomery, 1973). The four possible limitations/hazards under the subclass rating are erosion hazard, wetness, rooting zone limitations and climate. The capability unit groups soils that have about the same responses to systems of management and have longtime estimated yields that do not vary by more than 25% under comparable management. The issue of critical limits is a difficult one in soils because of the range of potential uses and the interactions among variables (Arshad and Ccen, 1992). Several studies have shown that lands of higher LCC have higher productivity than lands of lower LCC (Patterson and Mackintosh, 1976; van Vliet et al., 1979; Reganold and Singer, 1984). In a study of 744 alfalfa, corn, cotton, sugar beet and wheat growing fields in the San Joaquin Valley of California, those with LCC ratings between 1 and 3 had significantly lower input/output ratios than fields with ratings between 3.01 and 6 (Reganold and Singer, 1984). This suggests that use of the LCC system provides an economically meaningful assessment of soil quality for agriculture. This was a frequently used system of land evaluation for irrigation in the Western US during the period of rapid expansion of water delivery systems (McRae and Burnham, 1981). It combines social and economic evaluations of the land with soil and other ecological variables to determine if the land has the productive capacity, once irrigated, to repay the investment necessary to bring water to an area. It recognizes the unique importance of irrigation to agriculture and the special qualities of soils that make them irrigable. Quantitative systems result in a numerical index, typically with the highest number being assigned to the best quality soils. Systems may be additive, multiplicative or more complex functions. They have two important advantages over nonquantitative systems: 1. they are easier to use with GIS and other automated data retrieval and display systems, and 2. they typically provide a continuous scale of assessment. No single national system is presently in use but several state or regional systems exist. Although he considered the productivity of the land to be dependent on 32 soil, climate and vegetative properties [Surface conditions: Physiographic position, Slope, Microrelief, Erosion deposition, External drainage, runoff. Soil physical conditions: Soil color, Soil depth, Soil density and porosity, Soil permeability, Soil texture, Stoniness, Soil structure, Soil workability-consistence, Internal drainage, Water-holding capacity, Plant-available water. Soil chemical conditions: Organic matter, Nitrogen, Reaction, Calcium carbonate, bases, Exchange capacity, Salts: Cl, SO Na, Toxicities, e.g., B, Available P, Available K, Minor elements, e.g., Zn, Fe, Fertility. Mineralogical conditions: Mineralogy. Climate: Precipitation Temperature Growing season Winds. Vegetativé cover: Natural vegetation], only nine properties were used in the SIR, because incorporating a greater number of factors made the system unwieldy. The nine factors are soil morphology (A), surface texture (B), slope (C), and six variables (X.) that rate drainage class, sodicity, acidity, erosion, microrelief and fertility; rated from 1% to 100%. These are converted to their decimal value and multiplied together (Storie, 1964). Values for each factor were derived from Storie's experience mapping and evaluating soils in California, and in soil productivity studies in cooperation with the California Agricultural Experiment Station cost-efficiency projects relating to orchard crops, grapes and cotton. In describing the SIR (SIR= [AxBxCxIIXi]x100), Storie (1932, 1964) explicitly mentioned "soil quality". Soils that were deep, had no restricting subsoil horizons, and held water well had the greatest potential for the widest range of crops. The usefulness of the SIR as a soil quality index would be greatest if there was a statistically significant relationship between SIR values and an economic indicator of land value. Reganold and Singer (1984) found that area-weighted average SIR values between 60 and 100 for 744 fields in the San Joaquin Valley of California had lower but statistically insignificant input/output ratios than fields with indices < 60. The lack of statistical significance does not mean that better quality lands could not be farmed at economically lower cost or at higher cost and higher output than the lower quality lands. We productivity index model (PI) was developed to evaluate soil productivity in the top 100 cm, especially with reference to potential productivity loss due to soil erosion (Neill, 1979; Kiniry et al., 1983). The PI model rates soils on the sufficiency for root growth based on potential available water storage capacity, bulk density, aeration, pH, and electrical conductivity. A value from zero to one is assigned to each property describing the importance of that parameter for root development. The product of these five index values is used to describe the fractional sufficiency of any soil layer for root development. Pierce et al. (1983) modified the PI to include the assumption that nutrients were not limiting and that climate, management and plant differences are constant. A number of authors found that it is useful to various degrees (Gantzer and McCarty, 1987; Lindstrom et al., 1992). Parr et al. (1992) suggest that a SQI could take the form of Equation: SQI = f (SP, P, E, H, ER, BD, FQ, MI) where SQI is a function of soil properties (SP), potential productivity (P), environmental factors (E), human and animal health (H), erodibility (ER), biological diversity (BD), food quality and safety (FQ) and management inputs (MI). Determination of the specific measurable indicators of each variable and the interactions among these diverse variables is a daunting task. Moreover, the mathematical method of combining these factors, as well as the resulting value that would indicate a high quality soil, is not specified. The inclusion of variables BD, FQ and MI make this a land quality index as suggested by FAO (1997). Larson and Pierce (1991) defined soil quality (Q) as the state of existence of soil relative to a standard or in terms of a degree of excellence. They argue that defining Q in terms of productivity is too limiting and does not serve us well. Rather, Q is defined as the sum of individual soil qualities q. and expressed as Equation: Q=f(qi ...qn). These authors do not identify the best subset of properties or their functional and quantitative relationship, but do suggest that a MDS should be selected from those soil characteristics in which changes are measurable and relatively rapid (i.e., "dynamic" properties), arguing that it is more important to know about changes in soil quality (dQ) than the magnitude of Q (Larson and Pierce, 1991). Changes in soil quality are a function of changes in soil characteristics (q) over time (t): dQ = f[(qi.t - qit0 )... (qn.t-qnt0)]. If dQ/dt is ≥0, the soil or ecosystem is improving relative to the standard at time to. If dQ/dt <0, soil degradation is occurring. Time zero can be selected to meet management needs or goals. If there is a drastic change in management, time zero can be defined as prior to the change. If a longer time period of comparison is considered more appropriate, properties of an uncultivated or pristine soil could be used. The MDS recommended by Larson and Pierce (1991) includes N mineralization potential or P buffering capacity, total organic C, labile organic C, texture, plant-available water capacity, structure (bulk density is recommended as a surrogate variable), strength, maximum rooting depth, pH and EC. In instances when data are unavailable, pedotransfer functions (Bouma, 1989) can be used to estimate values of soil characteristics. These estimates can then be used as part of the minimum dataset to estimate soil quality or changes in soil quality brought about by management. Although this is a quantitative system, some qualitative judgments are needed to make decisions about changes in soil quality. In particular, interpretation of the meaning of magnitude of changes in a characteristic or the number of characteristics to change from time zero to the time of the measurement is qualitative. The authors do not address how large a change in pH, soil depth, bulk density or organic C represents serious soil degradation, or the values that define soil as high or low quality. Karlen et al. (1994) developed QI based on a 10-year crop residue management study. QI is based on four soil functions: (1) accommodating water entry, (2) retaining and supplying water to plants, (3) resisting degradation, and (4) supporting plant growth. Numerous properties were measured and values normalized based on standard scoring functions. One function is based on the concept that more of a property is better, one that less is better and the third that an optimum is better. Lower threshold values receive a score of zero, upper threshold values receive a score of one, and baseline values receive a score of one-half. Priorities are then assigned to each value. For example, aggregate stability was given the highest weight among factors important in water entry. After normalizing, each value is then multiplied by its weighting factor (wt) and products are summed Equation: QI=qwe (wt) + qwt (wt)+qrd (wt) + qspg (wt). Subscripts refer to the four main functions described earlier. It should also be noted that resisting degradation (rd) and sustaining plant growth (spg) are assigned secondary and tertiary levels of properties that themselves are normalized and weighted before a final value is calculated and incorporated into Equation. The resulting index resulted in values between zero and one. Of the three systems in the study, the one with the highest rate of organic matter return to the soil had the highest index value, and the soil with the lowest had the lowest value. The authors suggest that this demonstrates the usefulness of the index for monitoring the status and change in status of a soil as a function of management. They also suggest that the index and the soil characteristics that go into the index may change as the index is refined (Karlen et al. 1994). Snakin et al. (1996) developed an index of soil degradation that assigns three separate values from one to five reflecting the degree to which a soil's physical, chemical, and biological properties are degraded, as well as the rate of degradation. The Canadian soil capability classification system is similar to the older US systems and is quantitative. In a study in southwestern Ontario, Patterson and Mackintosh (1976) found that high gross returns per ha were three times as likely if the productivity index of land, based on the soil capability classification, was between 90 and 100 than if it fell between 80 and 89. Smith et al. (1993) and Halvorson et al. (1996) propose a multiple-variable indicator transform procedure to combine values or ranges of values that represent the best estimate of soil quality. Their system converts measured data values into a single value according to specified criteria. They do not attempt to define soil quality or specify what soil characteristics are to be used. They combine this procedure with kriging to develop maps that indicate the probabilities of meeting a soil quality criterion on a landscape level. Critical threshold values must be known, assumed, or determined in order to separate different soil qualities. Numerous additive productivity rating systems have been developed for specific states, as reviewed by Huddleston (1984). In these systems, soil properties are assigned numerical values according to their expected impact on plant growth. The index is usually calculated as the sum of the values assigned to each property with 100 the maximum value. Huddleston (1984) notes advantages and disadvantages to such a system which are similar to those for many of the soil quality indices previously discussed. Additive systems become complex as the number of factors, cropping systems, and soil and climatic conditions increases. A unique problem of subtractive systems (one in which 100 is the starting point and values are deducted for problem conditions) is that negative values result when multiple factors are less than satisfactory. Soil quality is a concept being developed to characterize the usefulness and health of soils, because soils are fundamental to the well-being and productivity of agricultural and natural ecosystems. It is a compound characteristic that cannot be directly measured. Many definitions of soil quality can be found in the literature and no set of soil characteristics has been universally adopted to quantify definitions. Soil quality is often equated with agricultural productivity and sustainability. An approach toward developing soil quality definitions is one that assesses soil quality in the context of a soil's potential to perform given functions in a system; e.g., maintains productivity, partitions and regulates water and solute flow through an ecosystem, serves as an environmental buffer, and cycles nutrients, water, and energy through the biosphere. Air and water quality standards are usually based on maximum allowable concentrations of materials hazardous to human health. A definition of soil quality based on this concept would encompass only a fraction of the important roles soils play in agriculture and the environment but could be essential to soil remediation. To proceed from a definition to a measure of soil quality, a minimum dataset of soil characteristics that represent soil quality must be selected and quantified. Many soil physical, chemical and biological properties have been suggested to separate soils of different quality. These include desirable and undesirable properties. Desirable soil characteristics may either be the presence of a property that benefits crop productivity and environmental buffering and/or other important soil functions, or the absence of a property that is detrimental to these functions. In particular, absence of contaminants is an important soil quality characteristic. In selecting characteristics, it is necessary to recognize that some soil properties are static, in the sense that they change slowly over time and others are dynamic. In addition, spatial and temporal variability of soil properties must be considered when selecting the properties used to assess soil quality. A single soil property is of limited use in evaluating soil quality. Qualitative and quantitative soil quality indices have been suggested that combine quantitative values of soil properties. Quantitative systems may be additive, multiplicative or more complex functions. Regardless of the definition or suite of soil variables chosen to define and quantify soil quality, it is critical to human welfare that soils be managed to provide for human health and well-being while minimizing soil and environmental degradation. References Anderson, D.W., E.G. Gregorich. 1984. Effect of soil erosion on soil quality and productivity. p. 105-113. In Soil erosion and degradation. Proc. 2nd Ann. Western Prov. Conf. Rational. Water Soil Res. Manag. Sask., Saskatoon, Canada. Andiscott, T.M. 1995. Entropy and sustainability. Europ. J. Soil Sci. 46:161-168. Arnold, R.W., I. Zaboles., V.C. Targulian (ed.). 1990. Global soil change. Report of an IIASA-ISSS-UNEP task force on the role of soil in global change. International Institute for Applied Systems Analysis, Laxanberg, Austria. Arshad, M-A., G.M. Coen. 1992. Characterization of soil quality: Physical and chemical criteria. Am. J. Altern. Agr. 725-3 I . Beck, A.J., S.C. Wilson., R.E. Alcock., K.C. Jones. 1995. Kinetic constraints on the loss of organic chemicals from contaminated soils: Implications for soil-quality limits. Critical Rev. Environ. Sci. Technol. 25:1-43. Beke, G.J., H.H. Janzen., T. Entz. 1994. Salinity and nutrient distribution in soil profiles of long-term crop rota-tions. Can. J. Soil Sci. 74:229-234. Berry, E.C. 1994. Earthworms and other fauna in the soil, p. 61-90. In J.L. Hatfield and B A. Stewart (ed.) Soil biology: effects on soil quality. Lewis Publishers, Boca Raton, FL. Biederbeck, V.O., C.A. Campbell., H.U. Krainetz., D. Curtain., O.T Bouman. 1996. Soil microbial and biochemical properties after ten years of fertilization with urea and anhydrous ammonia. Can. J. Soil Sci. 76:7-14. Boehn, M.M., D.W. Anderson. 1997. A landscape-scale study of soil quality in three prairie farming systems. Soil Sci. Soc. Am. J. 61:1147-1159. Bouma, J. 1989. Land qualities in space and time. p. 3-13. In J. Bouma and A.K. Bregt (ed.) Land qualities in space and time. Pudoc, Wageningen, Netherlands. Bouma, J., A.K. Bregt (ed.). 1989. Land qualities in space and time. Pudoc, Wageningen, Netherlands. Bowers, T.S., T.D. Gauhier. 1994. Use of the output of a lead risk assessment model to establish soil lead cleanup levels. Environ. Geochem. Health 16:191-196. Bowman, R.A., J.D. Reeder., G.E. Schuman. 1990. Evaluation of selected soil physical, chemical and biological parameters as indicators of soil productivity. Proc. Int. Conf. on Soil Quality in Semi-arid Ag. 2:64-70. Univ. of Saskatchewan, Saskatoon, Canada. Budd, W.W. 1992. What capacity the land? J. Soil Water Conserv. 47:28-31. Carter, MR., E.G. Gregorich., D.W Anderson., J.W. Doran., H.H. Janzen., F.J. Pierce. 1997. Concepts of soil quality and their significance: /n E.G. Gregorich and M. Carter (ed.) Soil quality for crop production and ecosys-tem health. Elsevier Science Publishers, Amsterdam, Netherlands. Cook, N., W.H. Hendershot. 1996. The problem of establishing ecologically based soil quality criteria: The case of lead. Can J. Soil Sci. 76:335-342. Cox, C. 1995. Soil quality: Goals for national policy. J. Soil Water Conserv. 50:223. Denneman, C.A.J., J.G. Robberse. 1990. Ecotoxicological risk assessment as a base for development of soil quality criteria. p. 157-164. In F Arendt, M. Hinsenveld and W.J. van den Brink (ed.) Contaminated soil '90. Proc. Intl. KfK/I'NO Conf. on Contaminated Soil, Karlsruhe, Germany, Kluwer Academic Publishers, Dordrecht, Neth-erlands. Dent, F.J. 1978. Land suitability classification. p. 273-293. In Soils and rice. International Ri
Guagliardi, Ilaria; Rovella, Natalia; Apollaro, Carmine; Bloise, Andrea; De Rosa, Rosanna; Scarciglia, Fabio; Buttafuoco, Gabriele
2016-05-01
The study, which represents an innovative scientific strategy to approach the study of natural radioactivity in terms of spatial and temporal variability, was aimed to characterize the background levels of natural radionuclides in soil and rock in the urban and peri-urban soil of a southern Italy area; to quantify their variations due to radionuclide bearing minerals and soil properties, taking into account nature and extent of seasonality influence. Its main novelty is taking into account the effect of climate in controlling natural gamma radioactivity as well as analysing soil radioactivity in terms of soil properties and pedogenetic processes. In different bedrocks and soils, activities of natural radionuclides ((238)U, (232)Th (4) K) and total radioactivity were measured at 181 locations by means of scintillation γ-ray spectrometry. In addition, selected rocks samples were collected and analysed, using a Scanning Electron Microscope (SEM) equipped with an Energy Dispersive Spectrometer (EDS) and an X-Ray Powder Diffraction (XRPD), to assess the main sources of radionuclides. The natural-gamma background is intimately related to differing petrologic features of crystalline source rocks and to peculiar pedogenetic features and processes. The radioactivity survey was conducted during two different seasons with marked changes in the main climatic characteristics, namely dry summer and moist winter, to evaluate possible effects of seasonal climatic variations and soil properties on radioactivity measurements. Seasonal variations of radionuclides activities show their peak values in summer. The activities of (238)U, (232)Th and (4) K exhibit a positive correlation with the air temperature and are negatively correlated with precipitations. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Curioni, Giulio; Chapman, David N.; Metje, Nicole
2017-06-01
The electromagnetic (EM) soil properties are dynamic variables that can change considerably over time, and they fundamentally affect the performance of Ground Penetrating Radar (GPR). However, long-term field studies are remarkably rare and records of the EM soil properties and their seasonal variation are largely absent from the literature. This research explores the extent of the seasonal variation of the apparent permittivity (Ka) and bulk electrical conductivity (BEC) measured by Time Domain Reflectometry (TDR) and their impact on GPR results, with a particularly important application to utility detection. A bespoke TDR field monitoring station was specifically developed and installed in an anthropogenic sandy soil in the UK for 22 months. The relationship between the temporal variation of the EM soil properties and GPR performance has been qualitatively assessed, highlighting notably degradation of the GPR images during wet periods and a few days after significant rainfall events following dry periods. Significantly, it was shown that by assuming arbitrary average values (i.e. not extreme values) of Ka and BEC which do not often reflect the typical conditions of the soil, it can lead to significant inaccuracies in the estimation of the depth of buried targets, with errors potentially up to approximately 30% even over a depth of 0.50 m (where GPR is expected to be most accurate). It is therefore recommended to measure or assess the soil conditions during GPR surveys, and if this is not possible to use typical wet and dry Ka values reported in the literature for the soil expected at the site, to improve confidence in estimations of target depths.
Phenanthrene sorption with heterogeneous organic matter in a landfill aquifer material
Karapanagioti, H.K.; Sabatini, D.A.; Kleineidam, S.; Grathwohl, P.; Ligouis, B.
1999-01-01
Phenanthrene was used as a model chemical to study the sorption properties of Canadian River Alluvium aquifer material. Both equilibrium and kinetic sorption processes were evaluated through batch studies. The bulk sample was divided into subsamples with varying properties such as particle size, organic content, equilibration time, etc. in order to determine the effect of these properties on resulting sorption parameters. The data have been interpreted and the effect of experimental variables was quantified using the Freundlich isotherm model and a numerical solution of Fick's 2nd law in porous media. Microscopic organic matter characterization proved to be a valuable tool for explaining the results. Different organic matter properties and sorption mechanisms were observed for each soil subsample. Samples containing coal particles presented high Koc values. Samples with organic matter dominated by organic coatings on quartz grains presented low Koc values and contained a high percentage of fast sorption sites. The numerical solution of Fick's 2ndlaw requires the addition of two terms (fast and slow) in order to fit the kinetics of these heterogeneous samples properly. These results thus demonstrate the need for soil organic matter characterization in order to predict and explain the sorption properties of a soil sample containing heterogeneous organic matter and also the difficulty and complexity of modeling sorption in such samples.
Impediments to predicting site response: Seismic property estimation and modeling simplifications
Thompson, E.M.; Baise, L.G.; Kayen, R.E.; Guzina, B.B.
2009-01-01
We compare estimates of the empirical transfer function (ETF) to the plane SH-wave theoretical transfer function (TTF) within a laterally constant medium for invasive and noninvasive estimates of the seismic shear-wave slownesses at 13 Kiban-Kyoshin network stations throughout Japan. The difference between the ETF and either of the TTFs is substantially larger than the difference between the two TTFs computed from different estimates of the seismic properties. We show that the plane SH-wave TTF through a laterally homogeneous medium at vertical incidence inadequately models observed amplifications at most sites for both slowness estimates, obtained via downhole measurements and the spectral analysis of surface waves. Strategies to improve the predictions can be separated into two broad categories: improving the measurement of soil properties and improving the theory that maps the 1D soil profile onto spectral amplification. Using an example site where the 1D plane SH-wave formulation poorly predicts the ETF, we find a more satisfactory fit to the ETF by modeling the full wavefield and incorporating spatially correlated variability of the seismic properties. We conclude that our ability to model the observed site response transfer function is limited largely by the assumptions of the theoretical formulation rather than the uncertainty of the soil property estimates.
Spiridonov, S I; Mukusheva, M K; Gontarenko, I A; Fesenko, S V; Baranov, S A
2005-01-01
A mathematical model of 137Cs behaviour in the soil-plant system is presented. The model has been parameterized for the area adjacent to the testing area Ground Zero of the Semipalatinsk Test Site. The model describes the main processes responsible for the changes in 137Cs content in the soil solution and, thereby, dynamics of the radionuclide uptake by vegetation. The results are taken from predictive and retrospective calculations that reflect the dynamics of 137Cs distribution by species in soil after nuclear explosions. The importance of factors governing 137Cs accumulation in plants within the STS area is assessed. The analysis of sensitivity of the output model variable to changes in its parameters revealed that the key soil properties significantly influence the results of prediction of 137Cs content in plants.
Biotic context and soil properties modulate native plant responses to enhanced rainfall.
Eskelinen, Anu; Harrison, Susan
2015-11-01
The environmental and biotic context within which plants grow have a great potential to modify responses to climatic changes, yet few studies have addressed both the direct effects of climate and the modulating roles played by variation in the biotic (e.g. competitors) and abiotic (e.g. soils) environment. In a grassland with highly heterogeneous soils and community composition, small seedlings of two native plants, Lasthenia californica and Calycadenia pauciflora, were transplanted into factorially watered and fertilized plots. Measurements were made to test how the effect of climatic variability (mimicked by the watering treatment) on the survival, growth and seed production of these species was modulated by above-ground competition and by edaphic variables. Increased competition outweighed the direct positive impacts of enhanced rainfall on most fitness measures for both species, resulting in no net effect of enhanced rainfall. Both species benefitted from enhanced rainfall when the absence of competitors was accompanied by high soil water retention capacity. Fertilization did not amplify the watering effects; rather, plants benefitted from enhanced rainfall or competitor removal only in ambient nutrient conditions with high soil water retention capacity. The findings show that the direct effects of climatic variability on plant fitness may be reversed or neutralized by competition and, in addition, may be strongly modulated by soil variation. Specifically, coarse soil texture was identified as a factor that may limit plant responsiveness to altered water availability. These results highlight the importance of considering the abiotic as well as biotic context when making future climate change forecasts. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Shin, K. H.; Kim, K. H.; Ki, S. J.; Lee, H. G.
2017-12-01
The vulnerability assessment tool at a Tier 1 level, although not often used for regulatory purposes, helps establish pollution prevention and management strategies in the areas of potential environmental concern such as soil and ground water. In this study, the Neural Network Pattern Recognition Tool embedded in MATLAB was used to allow the initial screening of soil and groundwater pollution based on data compiled across about 1000 previously contaminated sites in Korea. The input variables included a series of parameters which were tightly related to downward movement of water and contaminants through soil and ground water, whereas multiple classes were assigned to the sum of concentrations of major pollutants detected. Results showed that in accordance with diverse pollution indices for soil and ground water, pollution levels in both media were strongly modulated by site-specific characteristics such as intrinsic soil and other geologic properties, in addition to pollution sources and rainfall. However, classification accuracy was very sensitive to the number of classes defined as well as the types of the variables incorporated, requiring careful selection of input variables and output categories. Therefore, we believe that the proposed methodology is used not only to modify existing pollution indices so that they are more suitable for addressing local vulnerability, but also to develop a unique assessment tool to support decision making based on locally or nationally available data. This study was funded by a grant from the GAIA project(2016000560002), Korea Environmental Industry & Technology Institute, Republic of Korea.
NASA Astrophysics Data System (ADS)
Stuart, Jason M.; Anderson, Russell; Lazzarino, Patrick; Kuehn, Kevin A.; Harvey, Omar R.
2018-05-01
Quantifying links between pyOM dynamics, environmental factors and processes is central to predicting ecosystem function and response to future perturbations. In this study, changes in carbon (TC), nitrogen (TN) , pH and relative recalcitrance (R50) for pine- and cordgrass-derived pyOM were measured at 3-6 weeks intervals throughout the first year of burial in the soil. Objectives were to 1) identify key environmental factors and processes driving early-stage pyOM dynamics, and 2) develop quantitative relationships between environmental factors and changes in pyOM properties. The study was conducted in sandy soils of a forested ecosystem in the Longleaf pine range, US with a focus on links between changes in pyOM properties, fire history (FH), cumulative precipitation (Pcum), average temperature (Tavg) and soil residence time (SRT). Pcum, SRT and Tavg were the main factors controlling TC and TN accounting for 77-91% and 64-96% of their respective variability. Fire history, along with Pcum, SRT and Tavg, exhibited significant controlling effects on pyOM, pH and R50 - accounting for 48-91% and 88-93% of respective variability. Volatilization of volatiles and leaching of water-soluble components (in summer) and the sorption of exogenous organic matter (fall through spring) were most plausibly controlling pyOM dynamics in this study. Overall, our results point to climatic and land management factors and physicochemical process as the main drivers of pyOM dynamics in the pine ecosystems of the Southeastern US.
NASA Astrophysics Data System (ADS)
Lohse, K. A.; McLain, J. E.; Harman, C. J.; Sivapalan, M.; Troch, P. A.
2010-12-01
Microbially-mediated soil carbon cycling is closely linked to soil moisture and temperature. Climate change is predicted to increase intra-annual precipitation variability (i.e. less frequent yet more intense precipitation events) and alter biogeochemical processes due to shifts in soil moisture dynamics and inputs of carbon. However, the responses of soil biology and chemistry to predicted climate change, and their concomitant feedbacks on ecosystem productivity and biogeochemical processes are poorly understood. We collected soils at three different elevations in the Santa Catalina Mountains, AZ and quantified carbon utilization during pre-monsoon precipitation conditions. Contrasting parent materials (schist and granite) were paired at each elevation. We expected climate to determine the overall activity of soil fungal and bacterial communities and diversity of soil C utilization, and differences in parent material to modify these responses through controls on soil physical properties. We used EcoPlateTM C utilization assays to determine the relative abundance of soil bacterial and fungal populations and rate and diversity of carbon utilization. Additional plates were incubated with inhibitors selective to fungal or bacterial activity to assess relative contribution of these microbial groups to overall C utilization. We analyzed soils for soil organic matter, total C and N, particle size analysis and soil moisture content via both gravimetric and volumetric methods to assess the influences of soil physical and chemical properties on the measured biological responses. Consistent with our expectations, overall microbial activity was highest at the uppermost conifer elevation sites compared to the middle and lower elevation sites. In contrast to our expectations, however, overall activity was lower at the mid elevation oak woodland sites compared to the low elevation desert sites. Also consistent with our expectations was the observation that overall activities were consistently higher in schist parent material compared to granite. Though differences between canopy and intercanopy carbon utilization were subtle, the diversity of carbon utilization differed, suggesting a potential role of root exudates in governing C utilization in these semiarid soils. Findings from this study suggest that soil physical properties due to parent material have primary impacts in constraining microbial growth and carbon utilization under changing climate conditions.
Surface water quality is related to conditions in the surrounding geophysical environment, including soils, landcover, and anthropogenic activities. A number of statistical methods may be used to analyze and explore relationships among variables. Single-, multiple- and multivaria...
Phosphorus retention by fly-ash amended filter media in aged bioretention cells
USDA-ARS?s Scientific Manuscript database
Bioretention cells (BRCs) have shown potential for stormwater quantity and quality control. However, the phosphorus (P) removal in BRC has been variable due to differences of soil properties in filter media. The objectives of this research were to identify and evaluate P accumulation in filter media...
DOT National Transportation Integrated Search
2015-05-01
The ultimate goals of this research were to improve quality, speed completion, and reduce risk in mechanically-stabilized : earth (MSE) wall projects. Research objectives were to assure (1) that variability in the corrosion properties of soil (pH, : ...
Dairy manure and tillage effects on soil fertility and corn yields.
Khan, Anwar U H; Iqbal, M; Islam, K R
2007-07-01
Organic amendments have received renewed attention to improve soil fertility for crop production. A randomized complete block split plot experiment was conducted to evaluate the dairy manure (DM) amendments of soil for corn (Zea mays L. cv. Monsanto 919) production under different tillage systems. Main plot treatments were no-till (NT), conventional tillage (CT), and deep tillage (DT), and subplot treatments were chemical fertilization (DM(0)), and DM at 10Mgha(-1)yr(-1) (DM(10)) and 20Mgha(-1)yr(-1) (DM(20)) with supplemental chemical fertilization. Results show that tillage and DM had significantly reduced bulk density (rho(b)) with greater porosity (f(t)) and hydraulic conductivity (K(fs)) than soils under NT and DM(0). Manuring was effective to improve soil physical properties in all tillage treatments. While manure significantly increased C sequestration, the N concentration was influenced by both tillage and manure with significant interaction. The CT significantly increased P as did the addition of manure. However, with manure, K was significantly increased in all tillage treatments. While tilled soils produced taller plants with higher grain yields, and water-use efficiency than NT soils, manuring, in contrast, increased corn harvest index. Manure exerted significant quadratic effect on corn biomass N and K uptake. The variable effects of tillage and dairy manuring on soil properties and corn growth are most probably related to "transitional period" in which soil ecosystems may have adjusting to a new equilibrium.
Assessing soil hydraulic characteristics using HYPROP and BEST: a comparison
NASA Astrophysics Data System (ADS)
Leitinger, Georg; Obojes, Nikolaus; Lassabatère, Laurent
2015-04-01
Knowledge of ecohydrological characteristics with high spatial resolution is a prerequisite for large-scale hydrological modelling. Data on soil hydraulic characteristics are of major importance, but measurements are often seen as time consuming and costly. In order to accurately model grassland productivity and in particular evapotranspiration, soil sampling and infiltration experiments at 25 grassland sites ranging from 900m to 2300m a.s.l. were conducted in the long term socio-ecological research (LTSER) site Stubai Valley, Tyrolean Alps, Austria, covering 265 km². Here we present a comparison of two methods to determine important hydrological properties of soils: (1) the evaporation method HYPROP (Hydraulic Property Analyzer; UMS Munich, 2010), and (2) the BEST-model (Beerkan Estimation of Soil Transfer Parameters; Lassabatère et al. (2006)), each determining the soil hydraulic characteristics and in particular the water retention curve. For the most abundant soil types we compared the pf-curves calculated from HYPROP data suing the Van Genuchten equation to the ones resulting from the comparatively time efficient BEST approach to find out if the latter is a suitable method to determine pf curves of alpine grassland soils. Except for the soil type Rendzina, the comparison of HYPROP and BEST showed slightly variations in the pF curves and resulting hydraulic characteristics. At the starting point BEST curves presented a slower dehydration, HYPROP a fast and continuous water loss. HYPROP analyses showed the highest variability in the measured values of Rendzina. Regarding BEST, the Alluvial Soils showed the highest variability. To assess equivalence between HYPROP and BEST we deduced several hydraulic characteristics from the pF curves, e.g. saturated water content, field capacity, permanent wilting point, pore size distribution, and minimum water retention. The comparison of HYPROP and BEST revealed that the results of soil water characteristics may depend on the methodological Approach with differences in equivalence between selected soil types. Thus, the used method is crucial to derive soil hydraulic parameters right from pF curves for water balance models. The results further showed that the BEST model is a promising method to determine soil water characteristics with minimal field- and laboratory work in large-scale studies. Reference: Lassabatère L, Angulo-Jaramillo R, Soria Ugalde JM, Cuenca R, Braud I and Haverkamp R (2006) Beerkan Estimation of Soil Transfer Parameters through Infiltration Experiments-BEST. Soil Sci. Soc. Am. J., 70: 521-532, doi:10.2136/sssaj2005.0026.
Spatial Dependence of Physical Attributes and Mechanical Properties of Ultisol in a Sugarcane Field.
Tavares, Uilka Elisa; Rolim, Mário Monteiro; de Oliveira, Veronildo Souza; Pedrosa, Elvira Maria Regis; Siqueira, Glécio Machado; Magalhães, Adriana Guedes
2015-01-01
This study investigates the effect of conventional tillage and application of the monoculture of sugar cane on soil health. Variables like density, moisture, texture, consistency limits, and preconsolidation stress were taken as indicators of soil quality. The measurements were made at a 120 × 120 m field cropped with sugar cane under conventional tillage. The objective of this work was to characterize the soil and to study the spatial dependence of the physical and mechanical attributes. Then, undisturbed soil samples were collected to measure bulk density, moisture content and preconsolidation stress and disturbed soil samples for classification of soil texture, and consistency limits. The soil texture indicated that soil can be characterized as sandy clay soil and a sandy clay loam soil, and the consistency limits indicated that the soil presents an inorganic low plasticity clay. The preconsolidation tests tillage in soil moisture content around 19% should be avoided or should be chosen a management of soil with lighter vehicles in this moisture content, to avoid risk of compaction. Using geostatistical techniques mapping was possible to identify areas of greatest conservation soil and greater disturbance of the ground.
Spatial Dependence of Physical Attributes and Mechanical Properties of Ultisol in a Sugarcane Field
Tavares, Uilka Elisa; Monteiro Rolim, Mário; Souza de Oliveira, Veronildo; Maria Regis Pedrosa, Elvira; Siqueira, Glécio Machado; Guedes Magalhães, Adriana
2015-01-01
This study investigates the effect of conventional tillage and application of the monoculture of sugar cane on soil health. Variables like density, moisture, texture, consistency limits, and preconsolidation stress were taken as indicators of soil quality. The measurements were made at a 120 × 120 m field cropped with sugar cane under conventional tillage. The objective of this work was to characterize the soil and to study the spatial dependence of the physical and mechanical attributes. Then, undisturbed soil samples were collected to measure bulk density, moisture content and preconsolidation stress and disturbed soil samples for classification of soil texture, and consistency limits. The soil texture indicated that soil can be characterized as sandy clay soil and a sandy clay loam soil, and the consistency limits indicated that the soil presents an inorganic low plasticity clay. The preconsolidation tests tillage in soil moisture content around 19% should be avoided or should be chosen a management of soil with lighter vehicles in this moisture content, to avoid risk of compaction. Using geostatistical techniques mapping was possible to identify areas of greatest conservation soil and greater disturbance of the ground. PMID:26167528
A hydro-mechanical framework for early warning of rainfall-induced landslides (Invited)
NASA Astrophysics Data System (ADS)
Godt, J.; Lu, N.; Baum, R. L.
2013-12-01
Landslide early warning requires an estimate of the location, timing, and magnitude of initial movement, and the change in volume and momentum of material as it travels down a slope or channel. In many locations advance assessment of landslide location, volume, and momentum is possible, but prediction of landslide timing entails understanding the evolution of rainfall and soil-water conditions, and consequent effects on slope stability in real time. Existing schemes for landslide prediction generally rely on empirical relations between landslide occurrence and rainfall amount and duration, however, these relations do not account for temporally variable rainfall nor the variably saturated processes that control the hydro-mechanical response of hillside materials to rainfall. Although limited by the resolution and accuracy of rainfall forecasts and now-casts in complex terrain and by the inherent difficulty in adequately characterizing subsurface materials, physics-based models provide a general means to quantitatively link rainfall and landslide occurrence. To obtain quantitative estimates of landslide potential from physics-based models using observed or forecasted rainfall requires explicit consideration of the changes in effective stress that result from changes in soil moisture and pore-water pressures. The physics that control soil-water conditions are transient, nonlinear, hysteretic, and dependent on material composition and history. In order to examine the physical processes that control infiltration and effective stress in variably saturated materials, we present field and laboratory results describing intrinsic relations among soil water and mechanical properties of hillside materials. At the REV (representative elementary volume) scale, the interaction between pore fluids and solid grains can be effectively described by the relation between soil suction, soil water content, hydraulic conductivity, and suction stress. We show that these relations can be obtained independently from outflow, shear strength, and deformation tests for a wide range of earth materials. We then compare laboratory results with measurements of pore pressure and moisture content from landslide-prone settings and demonstrate that laboratory results obtained for hillside materials are representative of field conditions. These fundamental relations provide a basis to combine observed or forecasted rainfall with in-situ measurements of soil water conditions using hydro-mechanical models that simulate transient variably saturated flow and slope stability. We conclude that early warning using an approach in which in-situ observations are used to establish initial conditions for hydro-mechanical models is feasible in areas of high landslide risk where laboratory characterization of materials is practical and accurate rainfall information can be obtained. Analogous to weather and climate forecasting, such models could then be applied in an ensemble fashion to obtain quantitative estimates of landslide probability and error. Application to broader regions likely awaits breakthroughs in the development of remotely sensed proxies of soil properties and subsurface moisture conditions.
Estimating plant available water content from remotely sensed evapotranspiration
NASA Astrophysics Data System (ADS)
van Dijk, A. I. J. M.; Warren, G.; Doody, T.
2012-04-01
Plant available water content (PAWC) is an emergent soil property that is a critical variable in hydrological modelling. PAWC determines the active soil water storage and, in water-limited environments, is the main cause of different ecohydrological behaviour between (deep-rooted) perennial vegetation and (shallow-rooted) seasonal vegetation. Conventionally, PAWC is estimated for a combination of soil and vegetation from three variables: maximum rooting depth and the volumetric water content at field capacity and permanent wilting point, respectively. Without elaborate local field observation, large uncertainties in PAWC occur due to the assumptions associated with each of the three variables. We developed an alternative, observation-based method to estimate PAWC from precipitation observations and CSIRO MODIS Reflectance-based Evapotranspiration (CMRSET) estimates. Processing steps include (1) removing residual systematic bias in the CMRSET estimates, (2) making spatially appropriate assumptions about local water inputs and surface runoff losses, (3) using mean seasonal patterns in precipitation and CMRSET to estimate the seasonal pattern in soil water storage changes, (4) from these, calculating the mean seasonal storage range, which can be treated as an estimate of PAWC. We evaluate the resulting PAWC estimates against those determined in field experiments for 180 sites across Australia. We show that the method produces better estimates of PAWC than conventional techniques. In addition, the method provides detailed information with full continental coverage at moderate resolution (250 m) scale. The resulting maps can be used to identify likely groundwater dependent ecosystems and to derive PAWC distributions for each combination of soil and vegetation type.
NASA Astrophysics Data System (ADS)
Hu, Guojie; Wu, Xiaodong; Zhao, Lin; Li, Ren; Wu, Tonghua; Xie, Changwei; Pang, Qiangqiang; Cheng, Guodong
2017-08-01
Soil temperature plays a key role in hydro-thermal processes in environments and is a critical variable linking surface structure to soil processes. There is a need for more accurate temperature simulation models, particularly in Qinghai-Xizang (Tibet) Plateau (QXP). In this study, a model was developed for the simulation of hourly soil surface temperatures with air temperatures. The model incorporated the thermal properties of the soil, vegetation cover, solar radiation, and water flux density and utilized field data collected from Qinghai-Xizang (Tibet) Plateau (QXP). The model was used to simulate the thermal regime at soil depths of 5 cm, 10 cm and 20 cm and results were compared with those from previous models and with experimental measurements of ground temperature at two different locations. The analysis showed that the newly developed model provided better estimates of observed field temperatures, with an average mean absolute error (MAE), root mean square error (RMSE), and the normalized standard error (NSEE) of 1.17 °C, 1.30 °C and 13.84 %, 0.41 °C, 0.49 °C and 5.45 %, 0.13 °C, 0.18 °C and 2.23 % at 5 cm, 10 cm and 20 cm depths, respectively. These findings provide a useful reference for simulating soil temperature and may be incorporated into other ecosystem models requiring soil temperature as an input variable for modeling permafrost changes under global warming.
Hirmas, D.R.; Graham, R.C.; Kendrick, K.J.
2011-01-01
Mountains comprise an extensive and visually prominent portion of the landscape in the Mojave Desert, California. Landform surface properties influence the role these mountains have in geomorphic processes such as dust flux and surface hydrology across the region. The primary goal of this study was to describe and quantify land surface properties of arid-mountain landforms as a step toward unraveling the role these properties have in soil-geomorphic processes. As part of a larger soil-geomorphic study, four major landform types were identified within the southern Fry Mountains in the southwestern Mojave Desert on the basis of topography and landscape position: mountaintop, mountainflank, mountainflat (intra-range low-relief surface), and mountainbase. A suite of rock, vegetation, and morphometric land surface characteristic variables was measured at each of 65 locations across the study area, which included an associated piedmont and playa. Our findings show that despite the variation within types, landforms have distinct land surface properties that likely control soil-geomorphic processes. We hypothesize that surface expression influences a feedback process at this site where water transports sediment to low lying areas on the landscape and wind carries dust and soluble salts to the mountains where they are washed between rocks, incorporated into the soil, and retained as relatively long-term storage. Recent land-based video and satellite photographs of the dust cloud emanating from the Sierra Cucapá Mountains in response to the 7.2-magnitude earthquake near Mexicali, Mexico, support the hypothesis that these landforms are massive repositories of dust.
Field Soil Water Retention of the Prototype Hanford Barrier and Its Variability with Space and Time
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Z. F.
Engineered surface barriers are used to isolate underlying contaminants from water, plants, animals, and humans. To understand the flow processes within a barrier and the barrier’s ability to store and release water, the field hydraulic properties of the barrier need to be known. In situ measurement of soil hydraulic properties and their variation over time is challenging because most measurement methods are destructive. A multiyear test of the Prototype Hanford Barrier (PHB) has yielded in situ soil water content and pressure data for a nine-year period. The upper 2 m layer of the PHB is a silt loam. Within thismore » layer, water content and water pressure were monitored at multiple depths at 12 water balance stations using a neutron probe and heat dissipation units. Valid monitoring data from 1995 to 2003 for 4 depths at 12 monitoring stations were used to determine the field water retention of the silt loam layer. The data covered a wide range of wetness, from near saturation to the permanent wilt point, and each retention curve contained 51 to 96 data points. The data were described well with the commonly used van Genuchten water retention model. It was found that the spatial variation of the saturated and residual water content and the pore size distribution parameter were relatively small, while that of the van Genuchten alpha was relatively large. The effects of spatial variability of the retention properties appeared to be larger than the combined effects of added 15% w/w pea gravel and plant roots on the properties. Neither of the primary hydrological processes nor time had a detectible effect on the water retention of the silt loam barrier.« less
NASA Astrophysics Data System (ADS)
Schneider, Christian; Heinrich, Jürgen
2017-04-01
The study analyzes the impact of a peasant and an industrialized agricultural land use system on soil degradation in two loess landscapes. The comparative method aims to test the hypothesis that different agricultural systems cause distinct differences in soil properties that can be documented by geo-chemical soil analysis. The two loess landscapes under investigation show great similarities in natural geo-ecological properties. Nevertheless, the land use system makes a significant difference in both research areas. The Polish Proszowice Plateau is characterized by traditional small-scale peasant agriculture. Small plots and fragmented ownership make it difficult to conjointly manage soil erosion. However, the Middle Saxonian Loess Region in Germany represents loess landscapes whose ecological functions were shaped by land consolidation measures resulting in the large-scale, high-input farming system. To identify representative small catchments for soil sampling relief heterogeneity analyses and a cluster analysis were performed to bridge scales between the landscape and the sub-catchment level. Geo-physical and geo-chemical laboratory techniques were used to analyze major soil properties. A total number of 346 sites were sampled and analyzed for geo-ecological, geomorphological, and pedological features. The results show distinct differences in soil properties between the two loess landscapes strongly influenced by agricultural use. However, despite big differences in agricultural management great similarities can also be found especially for mean soil organic carbon contents and plant nutrient values. At the same time, the greater variability of the soil mosaic is depicted by a higher variance of almost all soil properties common to traditional land use systems. Topsoils on arable land at the Proszowice Plateau also show a wider C/N ratio. Therefore, the soils there are less prone to degradation through mineralization of humic substances. The wider ratio is mainly caused by lower inputs of N-fertilizers, at least since 1990. At the same time, soil cultivation techniques and atmospheric deposits are not likely to make a significant difference. The topsoil horizons on arable lands at the Proszowice Plateau do not show significant differences in plant available nutrients like phosphorus, despite much lower P-inputs through mineral fertilizers since 1990. This is because of the high P-sorption capacity of the loess soils. Therefore, a long legacy effect of previous comparatively high mineral P-inputs between the 1960s and 80s can be observed. A similar effect occurs in the Middle Saxonian Loess Region. In contrast to the assumption of many scholars small-scale farming at the Proszowice Plateau has not lead to an under-supply of plant nutrients. The study has shown that significant differences in major soil properties can be observed because of different fertilizer inputs and partly because of different cultivation techniques. Also the traditional system increases soil heterogeneity. Contrary to expectations the study has shown that the small-scale peasant farming system resulted in similar mean soil organic carbon and phosphorus contents like the industrialized high-input farming system. A further study could include investigations of the effects of soil amendments like herbicides and pesticide on soil degradation.
Changes in climate variability with reference to land quality and agriculture in Scotland.
Brown, Iain; Castellazzi, Marie
2015-06-01
Classification and mapping of land capability represents an established format for summarising spatial information on land quality and land-use potential. By convention, this information incorporates bioclimatic constraints through the use of a long-term average. However, climate change means that land capability classification should also have a dynamic temporal component. Using an analysis based upon Land Capability for Agriculture in Scotland, it is shown that this dynamism not only involves the long-term average but also shorter term spatiotemporal patterns, particularly through changes in interannual variability. Interannual and interdecadal variations occur both in the likelihood of land being in prime condition (top three capability class divisions) and in class volatility from year to year. These changing patterns are most apparent in relation to the west-east climatic gradient which is mainly a function of precipitation regime and soil moisture. Analysis is also extended into the future using climate results for the 2050s from a weather generator which show a complex interaction between climate interannual variability and different soil types for land quality. In some locations, variability of land capability is more likely to decrease because the variable climatic constraints are relaxed and the dominant constraint becomes intrinsic soil properties. Elsewhere, climatic constraints will continue to be influential. Changing climate variability has important implications for land-use planning and agricultural management because it modifies local risk profiles in combination with the current trend towards agricultural intensification and specialisation.
Usefulness of Mehlich-3 test in the monitoring of phosphorus dispersion from Polish arable soils.
Szara, Ewa; Sosulski, Tomasz; Szymańska, Magdalena; Szyszkowska, Katarzyna
2018-04-19
A considerable area of soils with low abundance of plant-available phosphorus and relatively low consumption of phosphorus fertilisers recorded in Poland over the last 20-25 years suggests that the dispersion of phosphates from arable soils in Poland can be low. The literature, however, provides reports on a considerable share of Polish agriculture in phosphorus pollution of Baltic Sea waters. The literature provides no data concerning phosphorus sorption parameters of arable soils in Poland. Due to this, the study involved the analysis of sorption properties: 1-point phosphorus sorption index (PSI) and degree of phosphorus saturation, based on molar ratio P, Al, and Fe determined by the Mehlich-3 method (DPS-1 M3 = P / (Al + Fe) and DPS-2 M3 = P / Al), 59 soils representing the main types of texture of soils in Poland, characterised by variable content of plant-available phosphorus by Egner-Riehm DL, organic carbon, and soil pH. The obtained results suggest that the soil texture has a lower effect on sorption properties (PSI) than the degree of acidification. Sorption parameters of soils increased with soil acidification as a result of an increase in the content of Al and Fe extracted by the Mehlich-3 extract in strongly acidified soils. An important finding of our study was evidencing that within the same class of abundance in plant-available phosphorus, the soils varied in the degree of phosphorus saturation and content of active phosphorus. This suggests the possibility of losses of phosphorus even from soils with low abundance of the component provided they are characterised by a high value of parameters DPS-1 M3 and DPS-2 M3 .
NASA Astrophysics Data System (ADS)
Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron
2016-02-01
Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.
Štursová, Martina; Bárta, Jiří; Šantrůčková, Hana; Baldrian, Petr
2016-12-01
Forests are recognised as spatially heterogeneous ecosystems. However, knowledge of the small-scale spatial variation in microbial abundance, community composition and activity is limited. Here, we aimed to describe the heterogeneity of environmental properties, namely vegetation, soil chemical composition, fungal and bacterial abundance and community composition, and enzymatic activity, in the topsoil in a small area (36 m 2 ) of a highly heterogeneous regenerating temperate natural forest, and to explore the relationships among these variables. The results demonstrated a high level of spatial heterogeneity in all properties and revealed differences between litter and soil. Fungal communities had substantially higher beta-diversity than bacterial communities, which were more uniform and less spatially autocorrelated. In litter, fungal communities were affected by vegetation and appeared to be more involved in decomposition. In the soil, chemical composition affected both microbial abundance and the rates of decomposition, whereas the effect of vegetation was small. Importantly, decomposition appeared to be concentrated in hotspots with increased activity of multiple enzymes. Overall, forest topsoil should be considered a spatially heterogeneous environment in which the mean estimates of ecosystem-level processes and microbial community composition may confound the existence of highly specific microenvironments. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Wickland, Kimberly P.; Waldrop, Mark P.; Aiken, George R.; Koch, Joshua C.; Torre Jorgenson, M.; Striegl, Robert G.
2018-06-01
Permafrost (perennially frozen) soils store vast amounts of organic carbon (C) and nitrogen (N) that are vulnerable to mobilization as dissolved organic carbon (DOC) and dissolved organic and inorganic nitrogen (DON, DIN) upon thaw. Such releases will affect the biogeochemistry of permafrost regions, yet little is known about the chemical composition and source variability of active-layer (seasonally frozen) and permafrost soil DOC, DON and DIN. We quantified DOC, total dissolved N (TDN), DON, and DIN leachate yields from deep active-layer and near-surface boreal Holocene permafrost soils in interior Alaska varying in soil C and N content and radiocarbon age to determine potential release upon thaw. Soil cores were collected at three sites distributed across the Alaska boreal region in late winter, cut in 15 cm thick sections, and deep active-layer and shallow permafrost sections were thawed and leached. Leachates were analyzed for DOC, TDN, nitrate (NO3 ‑), and ammonium (NH4 +) concentrations, dissolved organic matter optical properties, and DOC biodegradability. Soils were analyzed for C, N, and radiocarbon (14C) content. Soil DOC, TDN, DON, and DIN yields increased linearly with soil C and N content, and decreased with increasing radiocarbon age. These relationships were significantly different for active-layer and permafrost soils such that for a given soil C or N content, or radiocarbon age, permafrost soils released more DOC and TDN (mostly as DON) per gram soil than active-layer soils. Permafrost soil DOC biodegradability was significantly correlated with soil Δ14C and DOM optical properties. Our results demonstrate that near-surface Holocene permafrost soils preserve greater relative potential DOC and TDN yields than overlying seasonally frozen soils that are exposed to annual leaching and decomposition. While many factors control the fate of DOC and TDN, the greater relative yields from newly thawed Holocene permafrost soils will have the largest potential impact in areas dominated by organic-rich soils.
Preliminary Evaluation of TM for Soils Information
NASA Technical Reports Server (NTRS)
Thompson, D. R.; Henderson, K. E.; Houston, A. G.; Pitts, D. E.
1984-01-01
Thematic mapper data acquired over Mississippi County, Arkansas, were examined for utility in separating soil associations within generally level alluvium deposited by the Mississippi River. The 0.76 to 0.90 micron (Band 4) and the 1.55 to 1.75 micron (Band 5) were found to separate the different soil associations fairly well when compared to the USDA-SCS general soil map. The thermal channel also appeared to provide information at this level. A detailed soil survey was available at the field level along with ground observations of crop type, plant height, percent cover and growth stage. Soils within the fields ranged from uniform to soils that occur as patches of sand that stand out strongly against the intermingled areas of dark soil. Examination of the digital values of individual TM bands at the field level indicates that the influence of the soil is greater in TM than it was in MSS bands. The TM appears to provide greater detail of within field variability caused by soils than MSS and thus should provide improved information relating to crop and soil properties. However, this soil influence may cause crop identification classification procedures to have to account for the soil in their algorithms.
Vegetation-induced spatial variability of soil redox properties in wetlands
NASA Astrophysics Data System (ADS)
Szalai, Zoltán; Jakab, Gergely; Kiss, Klaudia; Ringer, Marianna; Balázs, Réka; Zacháry, Dóra; Horváth Szabó, Kata; Perényi, Katalin
2016-04-01
Vegetation induced land patches may result spatial pattern of on soil Eh and pH. These spatial pattern are mainly emerged by differences of aeration and exudation of assimilates. Present paper focuses on vertical extent and temporal dynamics of these patterns in wetlands. Two study sites were selected: 1. a plain wetland on calcareous sandy parent material (Ceglédbercel, Danube-Tisza Interfluve, Hungary); 2. headwater wetland with calcareous loamy parent material (Bátaapáti, Hungary). Two vegetation patches were studied in site 1: sedgy (dominated by Carex riparia) and reedy (dominated by Phragmites australis). Three patches were studied in site2: sedgy1 (dominated by C vulpina), sedgy 2 (C. riparia); nettle-horsetail (Urtica dioica and Equisetum arvense). Boundaries between patches were studied separately. Soil redox, pH and temperature studied by automated remote controlled instruments. Three digital sensors (Ponsell) were installed in each locations: 20cm and 40cm sensors represent the solum and 100 cm sensor monitors the subsoil). Groundwater wells were installed near to triplets for soil water sampling. Soil Eh, pH and temperature values were recorded in each 10 minutes. Soil water sampling for iron and DOC were carried out during saturated periods. Spatial pattern of soil Eh is clearly caused by vegetation. We measured significant differences between Eh values of the studied patches in the solum. We did not find this kinds horizontal differences in the subsoil. Boundaries of the patches usually had more reductive soil environment than the core areas. We have found temporal dynamics of the spatial redox pattern. Differences were not so well expressed during wintertime. These spatial patterns had influence on the DOC and iron content of porewater, as well. Highest temporal dynamics of soil redox properties and porewater iron could be found in the boundaries. These observations refer to importance patchiness of vegetation on soil chemical properties in wetlands. Authors are grateful to Hungarian Scientific research Fund (K100180)
NASA Astrophysics Data System (ADS)
Gibson, Justin; Franz, Trenton E.
2018-06-01
The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to the common practice of soil grid sampling every 1 ha.
Efficient use of animal manure on cropland--economic analysis.
Araji, A A; Abdo, Z O; Joyce, P
2001-09-01
Manure contains all the macro- and microelements needed for plant growth; however, it represents one of the most underutilized resources in the US. The major problem with the use of manure on cropland is the direct effect of its composition on application cost. This cost is a function of the mineralization process of organic matter. The mineralization process is influenced by the properties of the manure, properties of the soil, moisture, and temperature. This study evaluates the simultaneous effect of these variables on the optimal use of manure on cropland. The results show that the properties of manure and soil significantly affect the mineralization of organic nitrogen and thus the optimal quantity of manure required to satisfy the nutrient requirement of crops in a given rotation system. Manure application costs range from a low of 18% of the cost of commercial fertilizer for chicken manure applied to one type of soil, to a high of 125% of the cost of commercial fertilizer for cow manure applied to another type of soil. The maximum distance to transfer manure to the field, that will equate its application cost to the cost of commercial fertilizer, ranges from a high of 35 km (22 miles) for chicken manure applied to one type of soil, to a low of 1 km (0.62 miles) for cow manure applied to another type of soil. For rotation system 2, manure application costs range from a low of 37% of the cost of commercial fertilizer for chicken manure applied to one type of soil, to a high of 136% of the cost of commercial fertilizer for cow manure applied to another type of soil. The maximum distance to transfer manure to the field, that will equate its cost to the cost of commercial fertilizer, ranges from a high of 20 km (12.5 miles) for chicken manure applied to one type of soil, to a low of 0 km (0 miles) for cow manure applied to another type of soil.
Torres, Maria Odete; Neves, Maria Manuela
2016-04-18
The mountainous massif of Sicó, in the centre of Portugal, is an extensive area composed of calcareous Jurassic formations. Hillside calcareous soils, with high pH, present chemical restrictions to support plant growth and are subjected to important erosion processes leading to their degradation if not protected by vegetation. In a first year of study some soil physicochemical characteristics have been measured in some geo-referenced locations of a larger design experiment and an exploratory spatial analysis has been performed. The objective of this study was to present some suggestions in order to give sustainable phosphorus fertiliser recommendations aiming to establish pastures in these soils and thus support traditional livestock activity. Ten years apart, those soil characteristics have been measured again in the same locations and comparisions have been made. The objective was to understand the variability of the soil properties under study in order to better adequate the fertiliser soil management regarding the area restoration.
Soil mixing of stratified contaminated sands.
Al-Tabba, A; Ayotamuno, M J; Martin, R J
2000-02-01
Validation of soil mixing for the treatment of contaminated ground is needed in a wide range of site conditions to widen the application of the technology and to understand the mechanisms involved. Since very limited work has been carried out in heterogeneous ground conditions, this paper investigates the effectiveness of soil mixing in stratified sands using laboratory-scale augers. This enabled a low cost investigation of factors such as grout type and form, auger design, installation procedure, mixing mode, curing period, thickness of soil layers and natural moisture content on the unconfined compressive strength, leachability and leachate pH of the soil-grout mixes. The results showed that the auger design plays a very important part in the mixing process in heterogeneous sands. The variability of the properties measured in the stratified soils and the measurable variations caused by the various factors considered, highlighted the importance of duplicating appropriate in situ conditions, the usefulness of laboratory-scale modelling of in situ conditions and the importance of modelling soil and contaminant heterogeneities at the treatability study stage.
Horak, W.F.
1988-01-01
Effective management of ground-water resources requires knowledge of all components of the water budget for the aquifer of interest. Efforts to simulate ground-water flow prior to development and the effects of proposed pumping in several of North Dakota's shallow glacial aquifers have been hindered by the lack of reliable estimates of ground-water recharge. This study was done to (1) review the methods that have been used to measure recharge, (2) review the theory of unsaturated flow and the methods for characterizing the physical properties of unsaturated media, (3) consider the relative merits of a rigorous data-intensive approach versus an estimation approach to the study of recharge, and (4) review past and current agronomic research in North Dakota for applicability of the research and the data generated to the study of recharge.Direct, quantitative techniques for evaluating recharge are rarely applied. The theory for computing fluxes in unsaturated media is well established and numerous physics-based models that effectively implement the theory are available, but the data required for the models generally are lacking. Many parametric approaches have been developed to avoid the large data requirements of the physics-based approaches for analyzing flow in the unsaturated zone. However, the parametric approaches normally include fitting coefficients that must be calibrated for every study site, thereby detracting from the general utility of the parametric approach. The functional relation of matric potential to moisture content is required for physics-based soil-water models, whether analytic or numeric. Laboratory methods to determine these relations are tedious, costly, and may not give results representative of the soils as they occur in the field. Many models have been proposed to estimate the moisture-characteristic curve and hydraulic-conductivity function from basic soil properties, but none yield results that are universally satisfactory. In situ methods, because they require minimal disturbance of the soil profile and may be used repeatedly on the same soil mass, have become the preferred means for acquiring physical data, especially hydraulic conductivity. Hydro logic investigations, except for recent studies of hazardous-waste disposal sites, rarely have included physical characterizations of unsaturated media. Any of four phenomena could hinder attempts to simulate unsaturated flow in settings typical of North Dakota; variability of soil properties, hysteresis, frozen ground, and macropore development. The spatial and temporal variability of soil properties probably is the greatest complicating phenomenon and must be dealt with by detailed characterization of the properties. Hysteresis can detract from the accuracy of flow calculations for some soils under certain conditions but, for the present, our scant knowledge of soil physical properties is a greater hindrance to reliable soi1-water mode 1 ing than is the hysteresis phenomenon. A1 though seasona1ly frozen ground undoubtedly affects hydrologic processes in North Dakota, much more research is needed before meaningful quantitative treatment is possible. Finally, macropores can influence soil-water movement significantly, but macropore development may not be common on the intensively farmed, coarse-textured soils that typically overlie North Dakota's glacial aquifers. Lysimetry currently is the only reliable means of analyzing macropore flow.The soil-related research that has been conducted in North Dakota to date (1983) provides little of the type of information required to estimate ground-water recharge. Useful data could be developed by systematically evaluating the hydraulic characteristics of the prominent soil types overlying North Dakota's shallow glacial aquifers. These data would be required to enable use of a physics-based approach to estimating recharge. The size of the aquifer under study, its economic value, and the resources available for data collection should be considered when choosing between parametric or physics-based methods.
Contribution of ants in modifying of soil acidity and particle size distribution
NASA Astrophysics Data System (ADS)
Morgun, Alexandra; Golichenkov, Maxim
2015-04-01
Being a natural body, formed by the influence of biota on the upper layers of the Earth's crust, the soil is the most striking example of biogenic-abiogenic interactions in the biosphere. Invertebrates (especially ants that build soil nests) are important agents that change soil properties in well developed terrestrial ecosystems. Impact of soil microorganisms on soil properties is particularly described in numerous literature and concerns mainly chemical properties and general indicators of soil biological activity. Influence of ants (as representatives of the soil mesofauna) mostly appears as mechanical movement of soil particles and aggregates, and chemical effects caused by concentration of organic matter within the ant's nest. The aim of this research was to evaluate the effect of ants on physical and chemical soil attributes such as particle size distribution and soil acidity. The samples were taken from aerial parts of Lasius niger nests, selected on different elements of the relief (summit position, slope, terrace and floodplain) in the Arkhangelsk region (north of the European part of Russia) and compared with the specimens of the upper horizons of the reference soils. Particle size distribution was determined by laser diffraction method using laser diffraction particle size analyzer «Analysette 22 comfort» (FRITSCH, Germany). The acidity (pH) was determined by potentiometry in water suspension. Particle size distribution of the samples from the nests is more variable as compared to the control samples. For example, the content of 5-10 μm fraction ranges from 9% to 12% in reference soils, while in the anthill samples the variation is from 8% to 15%. Similarly, for 50-250 μm fraction - it ranges from 15% to 18% in reference soils, whereas in anthills - from 6% to 29%. The results of particle size analysis showed that the reference sample on the terrace has silty loam texture and nests soil L. niger are medium loam. The reference soil on the slope is characterized as medium loam, and ant's nest material has silty loam texture. The control samples of soil and ants nests on the summit position are similar and have medium loam texture. Generally we outline that the particle size distribution of anthill samples shows more variability. We assume that ants operate with small soil aggregates, in which fine fractions may link together coarser particles. pH measurements show that the reference soils have a strongly acidic reaction on the summit position (pH 4.6), slightly acidic on the slope (pH 5.5) and neutral on the terrace and on the floodplain (pH 7.2). While the material of the anthills tends to be slightly alkalinized on the summit (pH 4.8) and alkalinized on the slope (pH 7.2), but acidified to neutral on the floodplain and terrace (pH 6.4 and 5.7). Therefore, the ants form specific physico-chemical conditions that are different from the surrounding (native) soil, significantly increasing the complexity of soil cover structure. This is a clear example of ecosystem engineering functions of ants in nature. Increased complexity of soil pattern is the result of variations in pH and particle size distribution. Both cause the preconditions for the formation of new environmental niches and enhance biodiversity in natural ecosystems.
Attributing spatial and temporal changes in soil C in the UK to environmental drivers
NASA Astrophysics Data System (ADS)
Thomas, Amy; Cosby, Bernard; Quin, Sam; Henrys, Pete; Robinson, David; Emmett, Bridget
2015-04-01
The largest terrestrial pool of carbon is found in soils. Understanding how soil C responds to drivers of change (land use and management, atmospheric deposition, climate change) and how these responses are modified by inherent soil properties is crucial if we are to manage soils more sustainably in the future. Here we attempt to attribute spatial and temporal changes in UK soil C to environmental drivers using data from the UK Countryside Survey (CS), a national soil survey across England, Scotland and Wales repeated in 1978, 1998 and 2007. A mixed model approach was used to model soil C concentration (g C kg-1) and density (t C ha-1) and their absolute changes for the time periods 1978-1998, 1998-2007 and 1978-2007 across the CS sites using a variety of explanatory variables: soil (parent material, pH, moisture, Olsen-P, Shannon Diversity Index); atmospheric deposition (nitrogen and sulphur); climate (growing degree days and rain); and land use (aggregate vegetation class). Spatially, prediction of soil C concentration was good; soil moisture, pH, vegetation class and dominant grain size were all significant predictors. Field capacity also appeared to be important; however this data was only collected for a fraction of sites. N% was also strongly related to soil C concentration and density, as would be expected due to coupling of C and N in soil OM pools. Although N may drive soil C through impact on plant productivity, this cannot be separated from correlated C and N losses with OM decomposition, and hence N was not included as a driver for modelling. Predictive power for C density is not as strong as for concentration, which may reflect nonlinear relationships not represented by the modelling approach. Temporally, change in soil C is more difficult to explain, and model predictive power was lower. Change in soil pH was important in explaining change in C concentration and density, along with change in atmospheric deposition; decrease in deposition and associated soil acidity (increase in pH) was associated with a decrease in soil C concentration and density. Change in soil moisture or rainfall was also important. Inherent soil and site properties such as soil texture, vegetation class and parent material appeared to contribute most to the prediction of soil C change through modulation of the relationship between change in soil C and change in pH. Including anthropogenic and natural drivers in models of soil C stocks and changes in the UK enables assessment of the relative importance of each across the UK CS sites, however interactions among the drivers are more difficult to disentangle. Given the statistical significance of a number of drivers and soil variables in predicting soil C stocks and changes in the UK, it is important that these continue to be measured to allow better model development and more reliable predictions of future soil C conditions.
NASA Astrophysics Data System (ADS)
Angulo-Martinez, Marta; Alastrué, Juan; Moret-Fernández, David; Beguería, Santiago; López, Mariví; Navas, Ana
2017-04-01
Rainfall simulation experiments were carried out in order to study soil crust formation and its relation with soil infiltration parameters—sorptivity (S) and hydraulic conductivity (K)—on four common agricultural soils with contrasted properties; namely, Cambisol, Gypsisol, Solonchak, and Solonetz. Three different rainfall simulations, replicated three times each of them, were performed over the soils. Prior to rainfall simulations all soils were mechanically tilled with a rototiller to create similar soil surface conditions and homogeneous soils. Rainfall simulation parameters were monitored in real time by a Thies Laser Precipitation Monitor, allowing a complete characterization of simulated rainfall microphysics (drop size and velocity distributions) and integrated variables (accumulated rainfall, intensity and kinetic energy). Once soils dried after the simulations, soil penetration resistance was measured and soil hydraulic parameters, S and K, were estimated using the disc infiltrometry technique. There was little variation in rainfall parameters among simulations. Mean intensity and mean median diameter (D50) varied in simulations 1 ( 0.5 bar), 2 ( 0.8 bar) and 3 ( 1.2 bar) from 26.5 mm h-1 and 0.43 mm (s1) to 40.5 mm h-1 and 0.54 mm (s2) and 41.1 mm h-1 and 0.56 mm for (s3), respectively. Crust formation by soil was explained by D50 and subsequently by the total precipitation amount and the percentage of silt and clay in soil, being Cambisol and Gypsisol the soils that showed more increase in penetration resistance by simulation. All soils showed similar S values by simulations which were explained by rainfall intensity. Different patterns of K were shown by the four soils, which were explained by the combined effect of D50 and intensity, together with soil physico-chemical properties. This study highlights the importance of monitoring all precipitation parameters to determine their effect on different soil processes.
NASA Astrophysics Data System (ADS)
Pereira, Paulo; Burguet, Maria; Cerdà, Artemi
2013-04-01
Soil water repellency (SWR) is a natural property of soils. Among other factors, SWR depends on soil moisture, mineralogy, texture, pH, organic matter, aggregate stability, fungal and microbiological activity and plant cover. It has implications on plant growth, superficial and subsurface hydrology and soil erosion. It is well known that SWR is temporarily, increasing when soils are dry and decreasing when moist. In agriculture, soil micro-topography is very heterogeneous with implications on surface water distribution and wettability. Normally, SWR studies are focused on large interval time (e.g, monthly or seasonally). The objective of this work is the study of SWR in a temporal scale and its variability in an abandoned agriculture field in Lithuania. An experimental plot with 21 m2 (07x03 m) was designed in a flat area. Inside this plot SWR was measured in the field, placing three droplets of water on the soil surface and counting the time that takes to infiltrate. A total of 105 sampling points were measured per sampling period. Soil water repellency was measured after a period of 14 days without rainfall and in the seven consequent weeks (one measurement per week between 28th May and 07th of July 2012). The results showed that in this small plot, SWR was observed in the first (May 28), third and fourth measurements (08th of June and 16th). It was observed an increasing of the percentage of hydrophobic points (Water Drop Penetration Test ≥5 seconds) between the first and the fourth measurement, decreasing thereafter. Significant differences of SWR were observed among all periods (F=78.32, p<0.0001). The coefficient of variation (CV%) changed strikingly, 361.10 % (8th of May), 151.78 % (01st of June), 83.77% (08th of June), 125.87% (16th of June), 0.45 (22nd of June), 121%(31st of June) and 67.13% (7th of July). The correlation between the mean SWR and the CV% is 0.75, p<0.05. The changes were attributed to different soil moisture conditions. The differences were also identified in the spatial pattern of SWR (assessed with the Global Moran's I Index). May 28, June 22 and July 7, SWR presented a random pattern, meanwhile in the remaining sampling periods, the spatial pattern was clustered. These results suggest that spatial variability increases with SWR, and that soil wettability changes at weekly scale, with unknown implications on plant water availability.. Overall, at small plot scale, SWR can change importantly in time and space leading to a complex dynamic of soil hydrological properties. More than soil moisture, other factors can rule these temporal and spatial changes in SWR. Further research is needed to accurate this situation.
NASA Astrophysics Data System (ADS)
Nataningtyas, Dilin Rahayu; Morita, Shunsuke; Hatano, Ryusuke
2017-12-01
In the context of global warming, the increase of N2O gas production from the agricultural area has gained enhancing concern due to N2O is a potent greenhouse gas and an ozone depleted substance. While adding clipping grass has been accepted to replace N-fertilizer input in urban law management its effect on soil gas emission still questionable. A laboratory incubation study had been conducted to evaluate the effect of soil water content and grass recycling on greenhouse gas emission from an urban lawn. The soil samples were taken from Yurigahara Park, Sapporo, Hokkaido Japan. The 17 days at 25°C incubation study was started after adjusting soil water content to 35% and 50% with and without adding the clipping grass on soil surfaces. Greenhouse gas emissions were higher with the addition of grass, however, for NO and N2O considerably higher in 35% than 50% water content. The denitrification process was responsible for the N2O increase in this action. Soil chemical and microbial properties, pH, WEOC, NO3--N, NH4+-N and microbial biomass nitrogen (MBN) as well as N-grass content were also measured to know their correlation with N2O emission. The fine-scale heterogeneity occurred in the soil has impact on the variability of soil chemical properties that influenced the N2O emission. In the other hand, the effect of grass recycling appeared to increased soil N-inorganic contents and stimulated the N-gaseous concentration.
Soil Organic Carbon Estimation and Mapping Using "on-the-go" VisNIR Spectroscopy
NASA Astrophysics Data System (ADS)
Brown, D. J.; Bricklemyer, R. S.; Christy, C.
2007-12-01
Soil organic carbon (SOC) and other soil properties related to carbon sequestration (eg. soil clay content and mineralogy) vary spatially across landscapes. To cost effectively capture this variability, new technologies, such as Visible and Near Infrared (VisNIR) spectroscopy, have been applied to soils for rapid, accurate, and inexpensive estimation of SOC and other soil properties. For this study, we evaluated an "on the go" VisNIR sensor developed by Veris Technologies, Inc. (Salinas, KS) for mapping SOC, soil clay content and mineralogy. The Veris spectrometer spanned 350 to 2224 nm with 8 nm spectral resolution, and 25 spectra were integrated every 2 seconds resulting in 3 -5 m scanning distances on the ground. The unit was mounted to a mobile sensor platform pulled by a tractor, and scanned soils at an average depth of 10 cm through a quartz-sapphire window. We scanned eight 16.2 ha (40 ac) wheat fields in north central Montana (USA), with 15 m transect intervals. Using random sampling with spatial inhibition, 100 soil samples from 0-10 cm depths were extracted along scanned transects from each field and were analyzed for SOC. Neat, sieved (<2 mm) soil sample materials were also scanned in the lab using an Analytical Spectral Devices (ASD, Boulder, CO, USA) Fieldspec Pro FR spectroradiometer with a spectral range of 350-2500 and spectral resolution of 2-10 nm. The analyzed samples were used to calibrate and validate a number of partial least squares regression (PLSR) VisNIR models to compare on-the-go scanning vs. higher spectral resolution laboratory spectroscopy vs. standard SOC measurement methods.
NASA Astrophysics Data System (ADS)
Couvreur, V.; Kandelous, M. M.; Moradi, A. B.; Baram, S.; Mairesse, H.; Hopmans, J. W.
2014-12-01
There is a worldwide growing concern for agricultural lands input to groundwater pollution. Nitrate contamination of groundwater across the Central Valley of California has been related to its diverse and intensive agricultural practices. However, there has been no study comparing leaching of nitrate in each individual agricultural land within the complex and diversely managed studied area. A combined field monitoring and modeling approach was developed to quantify from simple measurements the leaching of water and nitrate below the root zone. The monitored state variables are soil water content at several depths within the root zone, soil matric potential at two depths below the root zone, and nitrate concentration in the soil solution. In the modeling part, unsaturated water flow and solute transport are simulated with the software HYDRUS in a soil profile fragmented in up to two soil hydraulic types, whose effective hydraulic properties are optimized with an inverse modeling method. The applicability of the method will first be demonstrated "in-silico", with synthetic soil water dynamics data generated with HYDRUS, and considering the soil column as the layering of several soil types characterized in-situ. The method will then be applied to actual soil water status data from various crops in California including tomato, citrus, almond, pistachio, and walnut. Eventually, improvements of irrigation and fertilization management practices (i.e. mainly questions of quantity and frequency of application minimizing leaching under constraint of water and nutrient availability) will be investigated using coupled modeling and optimization tools.
Mirus, Benjamin B.
2015-01-01
Incorporating the influence of soil structure and horizons into parameterizations of distributed surface water/groundwater models remains a challenge. Often, only a single soil unit is employed, and soil-hydraulic properties are assigned based on textural classification, without evaluating the potential impact of these simplifications. This study uses a distributed physics-based model to assess the influence of soil horizons and structure on effective parameterization. This paper tests the viability of two established and widely used hydrogeologic methods for simulating runoff and variably saturated flow through layered soils: (1) accounting for vertical heterogeneity by combining hydrostratigraphic units with contrasting hydraulic properties into homogeneous, anisotropic units and (2) use of established pedotransfer functions based on soil texture alone to estimate water retention and conductivity, without accounting for the influence of pedon structures and hysteresis. The viability of this latter method for capturing the seasonal transition from runoff-dominated to evapotranspiration-dominated regimes is also tested here. For cases tested here, event-based simulations using simplified vertical heterogeneity did not capture the state-dependent anisotropy and complex combinations of runoff generation mechanisms resulting from permeability contrasts in layered hillslopes with complex topography. Continuous simulations using pedotransfer functions that do not account for the influence of soil structure and hysteresis generally over-predicted runoff, leading to propagation of substantial water balance errors. Analysis suggests that identifying a dominant hydropedological unit provides the most acceptable simplification of subsurface layering and that modified pedotransfer functions with steeper soil-water retention curves might adequately capture the influence of soil structure and hysteresis on hydrologic response in headwater catchments.
NASA Astrophysics Data System (ADS)
Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas
2014-05-01
In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.
Critical shear stress for erosion of cohesive soils subjected to temperatures typical of wildfires
Moody, J.A.; Dungan, Smith J.; Ragan, B.W.
2005-01-01
[1] Increased erosion is a well-known response after wildfire. To predict and to model erosion on a landscape scale requires knowledge of the critical shear stress for the initiation of motion of soil particles. As this soil property is temperature-dependent, a quantitative relation between critical shear stress and the temperatures to which the soils have been subjected during a wildfire is required. In this study the critical shear stress was measured in a recirculating flume using samples of forest soil exposed to different temperatures (40??-550??C) for 1 hour. Results were obtained for four replicates of soils derived from three different types of parent material (granitic bedrock, sandstone, and volcanic tuffs). In general, the relation between critical shear stress and temperature can be separated into three different temperature ranges (275??C), which are similar to those for water repellency and temperature. The critical shear stress was most variable (1.0-2.0 N m-2) for temperatures 2.0 N m-2) between 175?? and 275??C, and was essentially constant (0.5-0.8 N m-2) for temperatures >275??C. The changes in critical shear stress with temperature were found to be essentially independent of soil type and suggest that erosion processes in burned watersheds can be modeled more simply than erosion processes in unburned watersheds. Wildfire reduces the spatial variability of soil erodibility associated with unburned watersheds by eliminating the complex effects of vegetation in protecting soils and by reducing the range of cohesion associated with different types of unburned soils. Our results indicate that modeling the erosional response after a wildfire depends primarily on determining the spatial distribution of the maximum soil temperatures that were reached during the wildfire. Copyright 2005 by the American Geophysical Union.
Seasonal variability of soil aggregate stability
NASA Astrophysics Data System (ADS)
Rohoskova, M.; Kodesova, R.; Jirku, V.; Zigova, A.; Kozak, J.
2009-04-01
Seasonal variability of soil properties measured in surface horizons of three soil types (Haplic Luvisol, Greyic Phaeozem, Haplic Cambisol) was studied in years 2007 and 2008. Undisturbed and disturbed soil samples were taken every month to evaluate field water content, bulk density, porosity, ration of gravitational and capillary pores, pHKCl and pHH2O, organic matter content and its quality, aggregate stability using WSA index. In addition, micromorphological features of soil aggregates were studied in thin soil sections that were made from undisturbed large soil aggregates. Results showed that soil aggregate stability depended on stage of the root zone development, soil management and climatic conditions. Larger aggregate stabilities and also larger ranges of measure values were obtained in the year 2007 then those measured in 2008. This was probably caused by lower precipitations and consequently lower soil water contents observed in 2007 than those measured in 2008. The highest aggregate stability was measured at the end of April in the years 2007 and 2008 in Haplic Luvisol and Greyic Phaeozem, and at the end of June in the year 2007 and at the beginning of June in 2008 in Haplic Cambisol. In all cases aggregate stability increased during the root growth and then gradually decreased due to summer rainfall events. Aggregate stability reflected aggregate structure and soil pore system development, which was documented on micromorphological images and evaluated using the ration of gravitational and capillary pores measured on the undisturbed sol samples. Acknowledgement: Authors acknowledge the financial support of the Grant Agency of the Czech Republic grant No. 526/08/0434, and the Ministry of Education, Youth and Sports grant No. MSM 6046070901.
Selenium deficiency risk predicted to increase under future climate change
Jones, Gerrad D.; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P.; Seneviratne, Sonia I.; Smith, Pete; Winkel, Lenny H. E.
2017-01-01
Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980–1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate–soil interactions. Using moderate climate-change scenarios for 2080–2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate–soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change. PMID:28223487
Selenium deficiency risk predicted to increase under future climate change.
Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E
2017-03-14
Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.
Transformation and contamination of soils in iron ore mining areas (a review)
NASA Astrophysics Data System (ADS)
Zamotaev, I. V.; Ivanov, I. V.; Mikheev, P. V.; Belobrov, V. P.
2017-03-01
Current concepts of soil transformation and contamination in iron ore mining areas have been reviewed. Changes of soils and ecosystems in the mining areas are among the largest-scale impacts of economic activity on the nature. Regularities in the radial differentiation, spatial distribution, and accumulation of heavy metals in soils of different natural zones are analyzed. The effects of mining technogenesis and gas-dust emissions from enterprises on soil microbial communities and fauna are considered. In zones of longterm atmotechnogenic impact of mining and processing plants, the stable state of ecosystems is lost and/or a new technoecosystem different from the natural one, with own microbial cenosis, is formed, where communities of soil organisms are in the stress state. In the ore mining regions, embriozems are formed, which pass through specific stages of technogenically-determined development, as well as technosols, chemozems, and technogenic surface formations with variable material compositions and properties. Technogenic soils and soil-like bodies form a soil cover differing from the initial one, whose complexity and contrast are not related to the natural factors of differentiation.
NASA Astrophysics Data System (ADS)
Kluiving, Sjoerd; Kok, Marielle; van Suijlekom, Jan-Jaap; Kasse, Kees
2015-04-01
In the province of North-Brabant in the southern Netherlands a diverse geological substrate is present variable in chronology, sediment properties, and soil profiles. The human influence on soil quality and topography has a history of millennia while new developments related to the horsification of the landscape in this region allow an insight in the soil patterns with associated landscape evolution. The objective in this project is to show that records of soils and landscape in this area are able to demonstrate the evolutional history and disseminate the pedological and geological knowledge to a wider audience in demonstrating that soil records and associated landscape evolution reveal a regional identity that can be very useful to apply in landscape architectural projects, such as in the horsification of the landscape. Soil records show landscape evolution has progressed in three distinct phases: 1) The oldest deposits in the region are formed by river sediments that reflect a fluvial environment that was present 800.000 years ago in the Lower-Pleistocene. Old courses of the rivers Rhine and Meuse deposited gravelly white sands and clay layers that have a distinct effect on hydrological properties. 2) Eolian sands dating from the Late Glacial, deposited 12.000-14.000 years before present were deposited by western wind directions, obvious from large scale linear and parabolic dune ridges. These sandy deposits have endured soil acidification and podzolisation resulting in classic Umbric Podzol profiles testifying of a prolonged period of landscape evolution. 3) Tree removal in the Holocene by man created unprotected open sand plains that were eroded and deposited by wind processes in small scale ridges with steep slopes up till approximately 500 years ago. These drift sands have a widespread occurrence and can be recognized in thin micro-podzol profiles in association with a distinct morphology of steep sloped dunes. Multiple soil horizons reflect different time periods elapsed and specific 'open landscape' environments, as these thin podzolic horizons testify. Future research will involve cartographic mapping by soil coring, as well as OSL dating, next to an ecological field reconnaissance. In this poster we will show how the soil in this region beholds an entire landscape history, and how that information can be combined with nature development in landscape architectural plans.
Static sampling of dynamic processes - a paradox?
NASA Astrophysics Data System (ADS)
Mälicke, Mirko; Neuper, Malte; Jackisch, Conrad; Hassler, Sibylle; Zehe, Erwin
2017-04-01
Environmental systems monitoring aims at its core at the detection of spatio-temporal patterns of processes and system states, which is a pre-requisite for understanding and explaining their baffling heterogeneity. Most observation networks rely on distributed point sampling of states and fluxes of interest, which is combined with proxy-variables from either remote sensing or near surface geophysics. The cardinal question on the appropriate experimental design of such a monitoring network has up to now been answered in many different ways. Suggested approaches range from sampling in a dense regular grid using for the so-called green machine, transects along typical catenas, clustering of several observations sensors in presumed functional units or HRUs, arrangements of those cluster along presumed lateral flow paths to last not least a nested, randomized stratified arrangement of sensors or samples. Common to all these approaches is that they provide a rather static spatial sampling, while state variables and their spatial covariance structure dynamically change in time. It is hence of key interest how much of our still incomplete understanding stems from inappropriate sampling and how much needs to be attributed to an inappropriate analysis of spatial data sets. We suggest that it is much more promising to analyze the spatial variability of processes, for instance changes in soil moisture values, than to investigate the spatial variability of soil moisture states themselves. This is because wetting of the soil, reflected in a soil moisture increase, is causes by a totally different meteorological driver - rainfall - than drying of the soil. We hence propose that the rising and the falling limbs of soil moisture time series belong essentially to different ensembles, as they are influenced by different drivers. Positive and negative temporal changes in soil moisture need, hence, to be analyzed separately. We test this idea using the CAOS data set as a benchmark. Specifically, we expect the covariance structure of the positive temporal changes of soil moisture to be dominated by the spatial structure of rain- and through-fall and saturated hydraulic conductivity. The covariance in temporarily decreasing soil moisture during radiation driven conditions is expect to be dominated by the spatial structure of retention properties and plant transpiration. An analysis of soil moisture changes has furthermore the advantage that those are free from systematic measurement errors.
Improved chemometric methodologies for the assessment of soil carbon sequestration mechanisms
NASA Astrophysics Data System (ADS)
Jiménez-González, Marco A.; Almendros, Gonzalo; Álvarez, Ana M.; González-Vila, Francisco J.
2016-04-01
The factors involved soil C sequestration, which is reflected in the highly variable content of organic matter in the soils, are not yet well defined. Therefore, their identification is crucial for understanding Earth's biogeochemical cycle and global change. The main objective of this work is to contribute to a better qualitative and quantitative assessment of the mechanisms of organic C sequestration in the soil, using omic approaches not requiring the detailed knowledge of the structure of the material under study. With this purpose, we have carried out a series of chemometric approaches on a set of widely differing soils (35 representative ecosystems). In an exploratory phase, we used multivariate statistical models (e.g., multidimensional scaling, discriminant analysis with automatic backward variable selection…) to analyze arrays of more than 200 independent soil variables (physicochemical, spectroscopic, pyrolytic...) in order to select those factors (descriptors or proxies) that explain most of the total system variance (content and stability of the different C forms). These models showed that the factors determining the stabilization of organic material are greatly dependent on the soil type. In some cases, the molecular structure of organic matter seemed strongly correlated with their resilience, while in other soil types the organo-mineral interactions played a significant bearing on the accumulation of selectively preserved C forms. In any case, it was clear that the factors driving the resilience of organic matter are manifold and not exclusive. Consequently, in a second stage, prediction models of the soil C content and their biodegradability (laboratory incubation experiments) were carried out by massive data processing by partial least squares (PLS) regression of data from Py-GC-MS and Py-MS. In some models, PLS was applied to a matrix of 150 independent variables corresponding to major pyrolysis compounds (peak areas) from the 35 samples of whole soils. The variable importance in the projection (VIP) histogram obtained from this treatment (total C and total mineralization coefficients as dependent variables) illustrated the contribution of the individual compounds to the total inertia of the models (e.g., carbohydrate-derived compounds, methoxyphenols, or specific alkylbenzenes were relevant in explaining the total quality and the biodegradation rates of the organic matter). Further simplified models consisting of direct PLS analysis of the debugged ion matrix calculated by averaging all ions (45 - 250 amu) in the whole chromatographic area in the 5-60 min range (here referred to as 'rebuilt MS spectra' or 'Py-MS spectra' when obtained connecting directly the pyrolyser to the MS detector through suitable interfaces) were carried out. The above three approaches coincided in pointing out that C sequestration behave as an emergent soil property depending on the complexity of its progressive molecular levels. Most of the total variance is explained by specific assemblages of variables, strongly depending on the soil types. On the other hand, chemical biodiversity (e.g., Shannon indices or coefficients from multivariate data models) behaved as a common background in the prediction models including very different soil types. In fact, assessment of chemodiversity of the pyrolytic compound assemblages (or the Py-MS ion data) would represent a valid clue for the assessment of the extent to which the original biomass has been diagenetically reworked into chaotic structures with non-repeatable units, providing a useful proxy to forecast at least a portion of the total variance in the soil organic matter biodegradability.
Peatlands and potatoes; organic wetland soils in Uganda
NASA Astrophysics Data System (ADS)
Farmer, Jenny; Langan, Charlie; Gimona, Alessandro; Poggio, Laura; Smith, Jo
2017-04-01
Land use change in Uganda's wetlands has received very little research attention. Peat soils dominate the papyrus wetlands of the south west of the country, but the areas they are found in have been increasingly converted to potato cultivation. Our research in Uganda set out to (a) document both the annual use of and changes to these soils under potato cultivation, and (b) the extent and condition of these soils across wetland systems. During our research we found it was necessary to develop locally appropriate protocols for sampling and analysis of soil characteristics, based on field conditions and locally available resources. Over the period of one year we studied the use of the peat soil for potato cultivation by smallholder farmers in Ruhuma wetland and measured changes to surface peat properties and soil nutrients in fields over that time. Farmer's use of the fields changed over the year, with cultivation, harvesting and fallow periods, which impacted on soil micro-topography. Measured soil properties changed over the course of the year as a result of the land use, with bulk density, nitrogen content, potassium and magnesium all reducing. Comparison of changes in soil carbon stocks over the study period were difficult to make as it was not possible to reach the bottom of the peat layer. However, a layer of fallow weeds discarded onto the soil prior to preparation of the raised potato beds provided a time marker which gave insight into carbon losses over the year. To determine the peatland extent, a spatial survey was conducted in the Kanyabaha-Rushebeya wetland system, capturing peat depths and key soil properties (bulk density, organic matter and carbon contents). Generalised additive models were used to map peat depth and soil characteristics across the system, and maps were developed for these as well as drainage and land use classes. Comparison of peat cores between the two study areas indicates spatial variability in peat depths and the influence of neighbouring mineral soil hillslopes. Our work provides valuable insight into the condition and use of these tropical peat soils, which are under-researched yet highly depended upon by local communities, with wider climate impacts. Cultivation of these peat soils has implications for their future sustainability and use, and having insight into the impacts of land management on these soils improves local and national level capacity for better soil management.
NASA Astrophysics Data System (ADS)
Nasta, Paolo; Romano, Nunzio
2016-01-01
This study explores the feasibility of identifying the effective soil hydraulic parameterization of a layered soil profile by using a conventional unsteady drainage experiment leading to field capacity. The flux-based field capacity criterion is attained by subjecting the soil profile to a synthetic drainage process implemented numerically in the Soil-Water-Atmosphere-Plant (SWAP) model. The effective hydraulic parameterization is associated to either aggregated or equivalent parameters, the former being determined by the geometrical scaling theory while the latter is obtained through the inverse modeling approach. Outcomes from both these methods depend on information that is sometimes difficult to retrieve at local scale and rather challenging or virtually impossible at larger scales. The only knowledge of topsoil hydraulic properties, for example, as retrieved by a near-surface field campaign or a data assimilation technique, is often exploited as a proxy to determine effective soil hydraulic parameterization at the largest spatial scales. Comparisons of the effective soil hydraulic characterization provided by these three methods are conducted by discussing the implications for their use and accounting for the trade-offs between required input information and model output reliability. To better highlight the epistemic errors associated to the different effective soil hydraulic properties and to provide some more practical guidance, the layered soil profiles are then grouped by using the FAO textural classes. For the moderately heterogeneous soil profiles available, all three approaches guarantee a general good predictability of the actual field capacity values and provide adequate identification of the effective hydraulic parameters. Conversely, worse performances are encountered for the highly variable vertical heterogeneity, especially when resorting to the "topsoil-only" information. In general, the best performances are guaranteed by the equivalent parameters, which might be considered a reference for comparisons with other techniques. As might be expected, the information content of the soil hydraulic properties pertaining only to the uppermost soil horizon is rather inefficient and also not capable to map out the hydrologic behavior of the real vertical soil heterogeneity since the drainage process is significantly affected by profile layering in almost all cases.
NASA Astrophysics Data System (ADS)
Tripathi, G.; Deora, R.; Singh, G.
2013-07-01
Studies to understand litter processes and soil properties are useful for maintaining pastureland productivity as animal husbandry is the dominant occupation in the hot arid region. We aimed to quantify how micro-habitats and combinations of litters of the introduced leguminous tree Colophospermum mopane with the grasses Cenchrus ciliaris or Lasiurus sindicus influence decomposition rate and soil nutrient changes in a hot desert silvopasture system. Litter bags with tree litter alone (T), tree + C. ciliaris in 1:1 ratio (TCC) and tree + L. sindicus 1:1 ratio (TLS) litter were placed inside and outside of the C. mopane canopy and at the surface, 3-7 cm and 8-12 cm soil depths. We examined litter loss, soil fauna abundance, organic carbon (SOC), total (TN), ammonium (NH4-N) and nitrate (NO3-N) nitrogen, phosphorus (PO4-P), soil respiration (SR) and dehydrogenase activity (DHA) in soil adjacent to each litter bag. After 12 months exposure, the mean residual litter was 40.2% of the initial value and annual decomposition rate constant (k) was 0.98 (0.49-1.80). Highest (p < 0.01) litter loss was in the first four months, when faunal abundance, SR, DHA and humidity were highest but it decreased with time. These variables and k were highest under the tree canopies. The litter loss and k were highest (p < 0.01) in TLS under the tree canopy, but the reverse trend was found for litter outside the canopy. Faunal abundance, litter loss, k, nutrient release and biochemical activities were highest (p < 0.01) in the 3-7 cm soil layer. Positive correlations of litter loss and soil fauna abundance with soil nutrients, SR and DHA demonstrated the interactions of litter quality and micro-habitats together with soil fauna on increased soil fertility. These results suggest that a Colophospermum mopane and L. sindicus silvopasture system best promotes faunal abundance, litter decomposition and soil fertility. The properties of these species and the associated faunal resources may be utilised as an ecosystem-restoration strategy in designing a silvopasture system. This may help to control land degradation and increase productivity sustainably in this environment.
Sub-parcel terroir mapping supported by UAV-based hyperspectral imagery
NASA Astrophysics Data System (ADS)
Takács, Katalin; Árvai, Mátyás; Koós, Sándor; Deák, Márton; Bakacsi, Zsófia; László, Péter; Pásztor, László
2017-04-01
There is a greater need to better understand the regional-to-parcel variations in viticultural potential. The differentiation and mapping of the variability of grape and wine quality require comprehensive spatial modelling of climatic, topographic and soil properties and a "terroir-based approach". Using remote and proximal sensing sensors and instruments are the most effective way for surveying vineyard status, such as geomorphologic and soil conditions, plant water and nutrient availability, plant health. UAV (Unmanned Aerial Vechicle) platforms are ideal for the remote monitoring of small and medium size vineyards, because flight planning is flexible and very high spatial ground resolution (even centimeters) can be achieved. Using hyperspectral remote sensing techniques the spectral response of the vegetation and the bare soil surface can be analyzed in very high spectral resolution, which can support terroir mapping on a sub-parcel level. Our study area is located in Hungary, in the Tokaj Wine Region, which is a historical region for botrityzed dessert wine making. The area of Tokaj Wine Region was formed mostly by Miocene volcanic activity, where andesite, rhyolite lavas and tuffs are characteristic and loess cover also occurs in some regions. The various geology and morphology of this area result diversity in soil types and soil properties as well. The study site was surveyed by a Cubert UHD-185 hyperspectral camera set on a Cortex Octocopter platform. The hyperspectral images were acquired in VIS-NIR (visible and near-infrared; 450-950 nm), with 4 nm sampling interval. The image acquisition was carried out at bare soil conditions, therefore the most important soil properties, which has dominant role by the delineation of terroir, can be predicted. In our paper we will present the first results of the hyperspectral survey.
Chemical behavior of residential lead in urban yards in the United States.
Elless, M P; Bray, C A; Blaylock, M J
2007-07-01
Long after federal regulations banned the use of lead-based paints and leaded gasoline, residential lead remains a persistent challenge. Soil lead is a significant contributor to this hazard and an improved understanding of physicochemical properties is likely to be useful for in situ abatement techniques such as phytoremediation and chemical stabilization. A laboratory characterization of high-lead soils collected from across the United States shows that the lead contaminants were concentrating in the silt and clay fractions, in the form of discrete particles of lead, as observed by scanning electron microscopy coupled with energy dispersive X-ray analysis. Soil lead varied widely in its solubility behavior as assessed by sequential and chelate extractions. Because site-specific factors (e.g., soil pH, texture, etc.) are believed to govern the solubility of the lead, understanding the variability in these characteristics at each site is necessary to optimize in situ remediation or abatement of these soils.