Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

PubMed Central

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

PubMed

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

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.

Geophysical characterization of soil moisture spatial patterns in a tillage experiment

NASA Astrophysics Data System (ADS)

Martinez, G.; Vanderlinden, K.; Giráldez, J. V.; Muriel, J. L.

2009-04-01

Knowledge on the spatial soil moisture pattern can improve the characterisation of the hydrological response of either field-plots or small watersheds. Near-surface geophysical methods, such as electromagnetic induction (EMI), provide a means to map such patterns using non-invasive and non-destructive measurements of the soil apparent electrical conductivity (ECa. In this study ECa was measured using an EMI sensor and used to characterize spatially the hydrologic response of a cropped field to an intense shower. The study site is part of a long-term tillage experiment in Southern Spain in which Conventional Tillage (CT), Direct Drilling (DD) and Minimum Tillage (MT) are being evaluated since 1982. Soil ECa was measured before and after a rain event of 115 mm, near the soil surface and at deeper depth (ECas and ECad, respectively) using the EM38-DD EMI sensor. Simultaneously, elevation data were collected at each sampling point to generate a Digital Elevation Model (DEM). Soil moisture during the first survey was close to permanent wilting point and near field capacity during the second survey. For the first survey, both ECas and ECad, were higher in the CT and MT than in the DD plots. After the rain event, rill erosion appeared only in CT and MT plots were soil was uncovered, matching the drainage lines obtained from the DEM. Apparent electrical conductivity increased all over the field plot with higher increments in the DD plots. These plots showed the highest ECas and ECad values, in contrast to the spatial pattern found during the first sampling. Difference maps obtained from the two ECas and ECad samplings showed a clear difference between DD plots and CT and MT plots due to their distinct hydrologic response. Water infiltration was higher in the soil of the DD plots than in the MT and CT plots, as reflected by their ECad increment. Higher ECa increments were observed in the depressions of the terrain, where water and sediments accumulated. On the contrary, the most elevated places of the field showed lower ECa increments. When soil is wet topography dominates the hydrologic response of the field, while under drier conditions, hydraulic conductivity controls the soil water dynamics. These results show that when static soil properties, e.g. clay content, are spatially uniform, ECa can detect changes in dynamic properties like soil moisture content, characterizing their spatial pattern.

Variation in soil carbon dioxide efflux at two spatial scales in a topographically complex boreal forest

USGS Publications Warehouse

Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.

2012-01-01

Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.

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.

Prediction of iron oxide contents using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Marques, José, Jr.; Arantes Camargo, Livia

2015-04-01

Determining soil iron oxides using conventional analysis is relatively unfeasible when large areas are mapped, with the aim of characterizing spatial variability. Diffuse reflectance spectroscopy (DRS) is rapid, less expensive, non-destructive and sometimes more accurate than conventional analysis. Furthermore, this technique allows the simultaneous characterization of many soil attributes with agronomic and environmental relevance. This study aims to assess the DRS capability to predict iron oxides content -hematite and goethite - , characterizing their spatial variability in soils of Brazil. Soil samples collected from an 800-hectare area were scanned in the visible and near-infrared spectral range. Moreover, chemometric calibration was obtained through partial least-squares regression (PLSR). Then, spatial distribution maps of the attributes were constructed using predicted values from calibrated models through geostatistical methods. The studied area presented soils with varied contents of iron oxides as examples for the Oxisols and Entisols. In the spectra of each soil is observed that the reflectance decreases with the content of iron oxides present in the soil. In soils with a high content of iron oxides can be observed more pronounced concavities between 380 and 1100 nm which are characteristic of the presence of these oxides. In soils with higher reflectance it were observed concavity characteristics due to the presence of kaolinite, in agreement with the low iron contents of those soils. The best accuracy of prediction models [residual prediction deviation (RPD) = 1.7] was obtained for goethite within the visible region (380-800 nm), and for hematite (RPD = 2.0) within the visible near infrared (380-2300 nm). The maps of goethite and hematite predicted showed the spatial distribution pattern similar to the maps of clay and iron extracted by dithionite-citrate-bicarbonate, being consistent with the iron oxide contents of soils present in the study area. These results confirm the value of DRS in the mapping of iron oxides in large areas at detailed scale.

REGIONAL SOIL WATER RETENTION IN THE CONTIGUOUS US: SOURCES OF VARIABILITY AND VOLCANIC SOIL EFFECTS

EPA Science Inventory

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...

Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

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.

Soil moisture observations using L-, C-, and X-band microwave radiometers

NASA Astrophysics Data System (ADS)

Bolten, John Dennis

The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.

Spatial variation in soil properties and diffuse losses between and within grassland fields with similar short-term management.

PubMed

Peukert, S; Griffith, B A; Murray, P J; Macleod, C J A; Brazier, R E

2016-07-01

One of the major challenges for agriculture is to understand the effects of agricultural practices on soil properties and diffuse pollution, to support practical farm-scale land management. Three conventionally managed grassland fields with similar short-term management, but different ploughing histories, were studied on a long-term research platform: the North Wyke Farm Platform. The aims were to (i) quantify the between-field and within-field spatial variation in soil properties by geostatistical analysis, (ii) understand the effects of soil condition (in terms of nitrogen, phosphorus and carbon contents) on the quality of discharge water and (iii) establish robust baseline data before the implementation of various grassland management scenarios. Although the fields sampled had experienced the same land use and similar management for at least 6 years, there were differences in their mean soil properties. They showed different patterns of soil spatial variation and different rates of diffuse nutrient losses to water. The oldest permanent pasture field had the largest soil macronutrient concentrations and the greatest diffuse nutrient losses. We show that management histories affect soil properties and diffuse losses. Potential gains in herbage yield or benefits in water quality might be achieved by characterizing every field or by area-specific management within fields (a form of precision agriculture for grasslands). Permanent pasture per se cannot be considered a mitigation measure for diffuse pollution. The between- and within-field soil spatial variation emphasizes the importance of baseline characterization and will enable the reliable identification of any effects of future management change on the Farm Platform. Quantification of soil and water quality in grassland fields with contrasting management histories.Considerable spatial variation in soil properties and diffuse losses between and within fields.Contrasting management histories within and between fields strongly affected soil and water quality.Careful pasture management needed: the oldest pasture transferred the most nutrients from soil to water.

Soil carbon storage estimation in a forested watershed using quantitative soil-landscape modeling

Treesearch

James A. Thompson; Randall K. Kolka

2005-01-01

Carbon storage in soils is important to forest ecosystems. Moreover, forest soils may serve as important C sinks for ameliorating excess atmospheric CO2. Spatial estimates of soil organic C (SOC) storage have traditionally relied upon soil survey maps and laboratory characterization data. This approach does not account for inherent variability...

A simplified regional-scale electromagnetic induction - Salinity calibration model using ANOCOVA modeling techniques

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...

Concurrent temporal stability of the apparent electrical conductivity and soil water content

USDA-ARS?s Scientific Manuscript database

Knowledge of spatio-temporal soil water content (SWC) variability within agricultural fields is useful to improve crop management. Spatial patterns of soil water contents can be characterized using the temporal stability analysis, however high density sampling is required. Soil apparent electrical c...

Spatial Dependence of Physical Attributes and Mechanical Properties of Ultisol in a Sugarcane Field.

PubMed

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

PubMed Central

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

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

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.

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...

Distributed Soil Moisture Estimation in a Mountainous Semiarid Basin: Constraining Soil Parameter Uncertainty through Field Studies

NASA Astrophysics Data System (ADS)

Yatheendradas, S.; Vivoni, E.

2007-12-01

A common practice in distributed hydrological modeling is to assign soil hydraulic properties based on coarse textural datasets. For semiarid regions with poor soil information, the performance of a model can be severely constrained due to the high model sensitivity to near-surface soil characteristics. Neglecting the uncertainty in soil hydraulic properties, their spatial variation and their naturally-occurring horizonation can potentially affect the modeled hydrological response. In this study, we investigate such effects using the TIN-based Real-time Integrated Basin Simulator (tRIBS) applied to the mid-sized (100 km2) Sierra Los Locos watershed in northern Sonora, Mexico. The Sierra Los Locos basin is characterized by complex mountainous terrain leading to topographic organization of soil characteristics and ecosystem distributions. We focus on simulations during the 2004 North American Monsoon Experiment (NAME) when intensive soil moisture measurements and aircraft- based soil moisture retrievals are available in the basin. Our experiments focus on soil moisture comparisons at the point, topographic transect and basin scales using a range of different soil characterizations. We compare the distributed soil moisture estimates obtained using (1) a deterministic simulation based on soil texture from coarse soil maps, (2) a set of ensemble simulations that capture soil parameter uncertainty and their spatial distribution, and (3) a set of simulations that conditions the ensemble on recent soil profile measurements. Uncertainties considered in near-surface soil characterization provide insights into their influence on the modeled uncertainty, into the value of soil profile observations, and into effective use of on-going field observations for constraining the soil moisture response uncertainty.

Urban soil exploration through multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar.

PubMed

Van De Vijver, Ellen; Van Meirvenne, Marc; Vandenhaute, Laura; Delefortrie, Samuël; De Smedt, Philippe; Saey, Timothy; Seuntjens, Piet

2015-07-01

In environmental assessments, the characterization of urban soils relies heavily on invasive investigation, which is often insufficient to capture their full spatial heterogeneity. Non-invasive geophysical techniques enable rapid collection of high-resolution data and provide a cost-effective alternative to investigate soil in a spatially comprehensive way. This paper presents the results of combining multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar to characterize a former garage site contaminated with petroleum hydrocarbons. The sensor combination showed the ability to identify and accurately locate building remains and a high-density soil layer, thus demonstrating the high potential to investigate anthropogenic disturbances of physical nature. In addition, a correspondence was found between an area of lower electrical conductivity and elevated concentrations of petroleum hydrocarbons, suggesting the potential to detect specific chemical disturbances. We conclude that the sensor combination provides valuable information for preliminary assessment of urban soils.

Stochastical analysis of surfactant-enhanced remediation of denser-than-water nonaqueous phase liquid (DNAPL)-contaminated soils.

PubMed

Zhang, Renduo; Wood, A Lynn; Enfield, Carl G; Jeong, Seung-Woo

2003-01-01

Stochastical analysis was performed to assess the effect of soil spatial variability and heterogeneity on the recovery of denser-than-water nonaqueous phase liquids (DNAPL) during the process of surfactant-enhanced remediation. UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model, was used to simulate water flow and chemical transport processes in heterogeneous soils. Soil spatial variability and heterogeneity were accounted for by considering the soil permeability as a spatial random variable and a geostatistical method was used to generate random distributions of the permeability. The randomly generated permeability fields were incorporated into UTCHEM to simulate DNAPL transport in heterogeneous media and stochastical analysis was conducted based on the simulated results. From the analysis, an exponential relationship between average DNAPL recovery and soil heterogeneity (defined as the standard deviation of log of permeability) was established with a coefficient of determination (r2) of 0.991, which indicated that DNAPL recovery decreased exponentially with increasing soil heterogeneity. Temporal and spatial distributions of relative saturations in the water phase, DNAPL, and microemulsion in heterogeneous soils were compared with those in homogeneous soils and related to soil heterogeneity. Cleanup time and uncertainty to determine DNAPL distributions in heterogeneous soils were also quantified. The study would provide useful information to design strategies for the characterization and remediation of nonaqueous phase liquid-contaminated soils with spatial variability and heterogeneity.

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.

Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields

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.

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

PubMed Central

Skvortsova, Elena B.; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity. PMID:26010779

Universal spatial correlation functions for describing and reconstructing soil microstructure.

PubMed

Karsanina, Marina V; Gerke, Kirill M; Skvortsova, Elena B; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.

Designation of less favorable areas by the regionalization of soil degradation on various spatial scales

NASA Astrophysics Data System (ADS)

Pásztor, L.; Szabó, J.; Bakacsi, Zs.; Laborczi, A.

2009-04-01

One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in less favorable areas (LFA) in order (among others) to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. LFA assignment has both ecological and severe economical aspects. Delimitation of LFAs can be carried out by using biophysical diagnostic criteria on low soil productivity and poor climate conditions. Identification of low-productivity areas requires regionalization of soil functions related to food and other biomass production. This process can be carried out in different scales from national to local level, but always requires map-based pedological and further environmental information with appropriate spatial resolution. For the regionalization of less productive areas in national scale a functional approach was used which integrates the knowledge on soil degradation processes in nationwide level. Specific soil threats were classified into ranked categories. Supposing (quasi)uniform distribution of vulnerability measure along these classes, we introduced a "standardized" value as a ratio of the class order to the maximum class order expressed in percentage. For the overall spatial characterization of degradation status, spatial information was integrated in a result map by summarizing the degradation specific "standardized" cell values. This map in one hand has been used for the delineation of soil degradation regions. On the other hand appropriate spatial aggregation of index values on geographical and administrative regions is suitable for their quantitative comparison thus they can be ranked and this feature can be used for the identification of less favorable areas. At the more detailed, county level the Digital Kreybig Soil Information System was used as a tool of the regionalization of soil functions related to soil productivity. Concurrent spatial analysis of the suitability of soils for agricultural use and their sensitivity to physical and chemical degradation were carried out which resulted in a so-called ecotype-based characterization of land. As a spin-off, this classification was used for the designation of low productive areas suitable for hypogenous and cap fungi plantations as landuse alternative for croplands.

Characterizing permafrost soil active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

DOE PAGES

Yi, Yonghong; Kimball, John S.; Chen, Richard; ...

2017-05-30

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models. In this study, we developed a spatially integrated modelling and analysis framework combining field observations, local scale (~ 50 m) active layer thickness (ALT) and soil moisture maps derived from airborne low frequency (L + P-band) radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Model simulated ALT results show good correspondence with in-situ measurements in higher permafrost probability (PP ≥ 70 %) areas (n =more » 33, R = 0.60, mean bias = 1.58 cm, RMSE = 20.32 cm). The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr -1) and much larger increases (> 3 cm yr -1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). Uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was found to be the most important factor affecting model ALT accuracy. Here, potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of permafrost active layer conditions.« less

Characterizing permafrost soil active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yi, Yonghong; Kimball, John S.; Chen, Richard

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models. In this study, we developed a spatially integrated modelling and analysis framework combining field observations, local scale (~ 50 m) active layer thickness (ALT) and soil moisture maps derived from airborne low frequency (L + P-band) radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Model simulated ALT results show good correspondence with in-situ measurements in higher permafrost probability (PP ≥ 70 %) areas (n =more » 33, R = 0.60, mean bias = 1.58 cm, RMSE = 20.32 cm). The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr -1) and much larger increases (> 3 cm yr -1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). Uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was found to be the most important factor affecting model ALT accuracy. Here, potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of permafrost active layer conditions.« less

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

Mapping of hydropedologic spatial patterns in a steep headwater catchment

Treesearch

Cody P. Gillin; Scott W. Bailey; Kevin J. McGuire; John P. Gannon

2015-01-01

A hydropedologic approach can be used to describe soil units affected by distinct hydrologic regimes. We used field observations of soil morphology and geospatial information technology to map the distribution of five hydropedologic soil units across a 42-ha forested headwater catchment. Soils were described and characterized at 172 locations within Watershed 3, the...

Moment analysis description of wetting and redistribution plumes in wettable and water-repellent soils

NASA Astrophysics Data System (ADS)

Xiong, Yunwu; Furman, Alex; Wallach, Rony

2012-02-01

SummaryWater repellency has a significant impact on water flow patterns in the soil profile. Transient 2D flow in wettable and natural water-repellent soils was monitored in a transparent flow chamber. The substantial differences in plume shape and spatial water content distribution during the wetting and subsequent redistribution stages were related to the variation of contact angle while in contact with water. The observed plumes shape, internal water content distribution in general and the saturation overshoot behind the wetting front in particular in the repellent soils were associated with unstable flow. Moment analysis was applied to characterize the measured plumes during the wetting and subsequent redistribution. The center of mass and spatial variances determined for the measured evolving plumes were fitted by a model that accounts for capillary and gravitational driving forces in a medium of temporally varying wettability. Ellipses defined around the stable and unstable plumes' centers of mass and whose semi-axes represented a particular number of spatial variances were used to characterize plume shape and internal moisture distribution. A single probability curve was able to characterize the corresponding fractions of the total added water in the different ellipses for all measured plumes, which testify the competence and advantage of the moment analysis method.

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.

Prediction of Ba, Co and Ni for tropical soils using diffuse reflectance spectroscopy and X-ray fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Arantes Camargo, Livia; Marques Júnior, José; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angélica

2017-04-01

Environmental impact assessments may be assisted by spatial characterization of potentially toxic elements (PTEs). Diffuse reflectance spectroscopy (DRS) and X-ray fluorescence spectroscopy (XRF) are rapid, non-destructive, low-cost, prediction tools for a simultaneous characterization of different soil attributes. Although low concentrations of PTEs might preclude the observation of spectral features, their contents can be predicted using spectroscopy by exploring the existing relationship between the PTEs and soil attributes with spectral features. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Co, and Ni) and their spatial variability by means of diffuse reflectance spectroscopy (DRS) and X-ray fluorescence spectroscopy (XRF). For that, soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, and mineralogical properties, and then analyzed in DRS (visible + near infrared - VIS+NIR and medium infrared - MIR) and XRF equipment. PTE prediction models were calibrated using partial least squares regression (PLSR). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy using geostatistics. PTE prediction models were satisfactorily calibrated using MIR DRS for Ba, and Co (residual prediction deviation - RPD > 3.0), Vis DRS for Ni (RPD > 2.0) and FRX for all the studied PTEs (RPD > 1.8). DRS- and XRF-predicted values allowed the characterization and the understanding of spatial variability of the studied PTEs.

Spatial Distribution of Fungal Communities in an Arable Soil

PubMed Central

Moll, Julia; Hoppe, Björn; König, Stephan; Wubet, Tesfaye; Buscot, François; Krüger, Dirk

2016-01-01

Fungi are prominent drivers of ecological processes in soils, so that fungal communities across different soil ecosystems have been well investigated. However, for arable soils taxonomically resolved fine-scale studies including vertical itemization of fungal communities are still missing. Here, we combined a cloning/Sanger sequencing approach of the ITS/LSU region as marker for general fungi and of the partial SSU region for arbuscular mycorrhizal fungi (AMF) to characterize the microbiome in different maize soil habitats. Four compartments were analyzed over two annual cycles 2009 and 2010: a) ploughed soil in 0–10 cm, b) rooted soil in 40–50 cm, c) root-free soil in 60–70 cm soil depth and d) maize roots. Ascomycota was the most dominant phylum across all compartments. Fungal communities including yeasts and AMF differed strongly between compartments. Inter alia, Tetracladium, the overall largest MOTU (molecular operational taxonomic unit), occurred in all compartments, whereas Trichosporon dominated all soil compartments. Sequences belonging to unclassified Helotiales were forming the most abundant MOTUs exclusively present in roots. This study gives new insights on spatial distribution of fungi and helps to link fungal communities to specific ecological properties such as varying resources, which characterize particular niches of the heterogeneous soil environment. PMID:26840453

Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

2018-02-01

Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.

Effect of spatial variability on solute velocity and dispersion in two soils of the Argentinian Pampas

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.

Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

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.

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

Spatial characterization of soil properties and influence in soil formation in oak-grassland of Sierra Morena, S Spain

NASA Astrophysics Data System (ADS)

Román-Sánchez, Andrea; Cáceres, Francisco; Pédèches, Remi; Giráldez Cervera, Juan Vicente; Vanwalleghem, Tom

2016-04-01

The Mediterranean oak-grassland ecosystem is very important for the rural economy and for the biodiversity of south-western European countries like Spain and Portugal. Nevertheless these ecosystems are not well characterized especially their soils. In this report soil carbon has been evaluated and related to other properties. The principal factors controlling the structure, productivity and evolution of forest ecosystems are bedrock, climate, relief, vegetation and time. Soil carbon has an important influence in the soil and ecosystem structures. The purpose of this study is to determine the relationship between relief, soil properties, spatial distribution of soil carbon and their influence in soil formation and geomorphology. This work is part of another study which aims to elucidate the processes involved in the soil formation and to examine their behaviour on long-term with a modelling. In our study area, located in oak-grassland of Sierra Morena, in Cordoba, S Spain, have been studied 67 points at 6 depths in 262 hectares in order to determine carbon content varying between 0-6%, soil properties such as soil depth between 0-4 m, horizon depth and the rocks amount in surface. The relationship between the soil carbon, soil properties and the relief characteristic like slope, aspect, curvature can shed light the processes that affect the mechanisms of bedrock weathering and their interrelationship with geomorphological processes.

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

NASA Astrophysics Data System (ADS)

Yi, Yonghong; Kimball, John S.; Chen, Richard H.; Moghaddam, Mahta; Reichle, Rolf H.; Mishra, Umakant; Zona, Donatella; Oechel, Walter C.

2018-01-01

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale ( ˜ 50 m resolution) active layer thickness (ALT) and soil moisture maps derived from low-frequency (L + P-band) airborne radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modeled ALT results show good correspondence with in situ measurements in higher-permafrost-probability (PP ≥ 70 %) areas (n = 33; R = 0.60; mean bias = 1.58 cm; RMSE = 20.32 cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32±1.18 cm yr-1) and much larger increases (> 3 cm yr-1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modeling framework across a larger domain.

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.

Vegetation change alters soil profile δ15N values at the landscape scale in a subtropical savanna

NASA Astrophysics Data System (ADS)

Zhou, Y.; Mushinski, R. M.; Hyodo, A.; Wu, X. B.; Boutton, T. W.

2017-12-01

The assessment of spatial variation in soil δ15N could provide integrative insights on soil N cycling processes across multiple spatial scales. However, little is known about spatial patterns of δ15N within soil profiles in arid and semiarid ecosystems, especially those undergoing vegetation change with a distinct shift in dominance and/or functional type. We quantified how changes from grass to woody plant dominance altered spatial patterns of δ15N throughout a 1.2 m soil profile by collecting 320 spatially-specific soil cores in a 160 m × 100 m subtropical savanna landscape that has undergone encroachment by Prosopis glandulosa (an N2-fixer) during the past century. Leaf δ15N was comparable among different plant life-forms, while fine roots from woody species had significantly lower δ15N than herbaceous species across this landscape. Woody encroachment significantly decreased soil δ15N throughout the entire soil profile, and created horizontal spatial patterns of soil δ15N that strongly resembled the spatial distribution of woody patches and were evident within each depth increment. The lower soil δ15N values that characterized areas beneath woody canopies were mostly due to the encroaching woody species, especially the N2-fixer P. glandulosa, which delivered 15N-depleted organic matter via root turnover to soils along the profile. Soil δ15N increased with depth, reached maximum values at an intermediate depth, and decreased at greater depths. Higher δ15N values at intermediate soil depths were correlated with the presence of a subsurface clay-rich argillic horizon across this landscape which may favor more rapid rates of N-cycling processes that can cause N losses and 15N enrichment of the residual soil N. These results indicate that succession from grassland to woodland has altered spatial variation in soil δ15N across the landscape and to considerable depth, suggesting significant changes in the relative rates of N-inputs vs. N-losses in this subtropical system after vegetation change.

Prediction of Ba, Mn and Zn for tropical soils using iron oxides and magnetic susceptibility

NASA Astrophysics Data System (ADS)

Marques Júnior, José; Arantes Camargo, Livia; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angelica

2017-04-01

Agricultural activity is an important source of potentially toxic elements (PTEs) in soil worldwide but particularly in heavily farmed areas. Spatial distribution characterization of PTE contents in farming areas is crucial to assess further environmental impacts caused by soil contamination. Designing prediction models become quite useful to characterize the spatial variability of continuous variables, as it allows prediction of soil attributes that might be difficult to attain in a large number of samples through conventional methods. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Mn, Zn) and their spatial variability using iron oxides and magnetic susceptibility (MS). Soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, mineralogical properties, as well as magnetic susceptibility (MS). PTE prediction models were calibrated by multiple linear regression (MLR). MLR calibration accuracy was evaluated using the coefficient of determination (R2). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy by means of geostatistics. The high correlations between the attributes clay, MS, hematite (Hm), iron oxides extracted by sodium dithionite-citrate-bicarbonate (Fed), and iron oxides extracted using acid ammonium oxalate (Feo) with the elements Ba, Mn, and Zn enabled them to be selected as predictors for PTEs. Stepwise multiple linear regression showed that MS and Fed were the best PTE predictors individually, as they promoted no significant increase in R2 when two or more attributes were considered together. The MS-calibrated models for Ba, Mn, and Zn prediction exhibited R2 values of 0.88, 0.66, and 0.55, respectively. These are promising results since MS is a fast, cheap, and non-destructive tool, allowing the prediction of a large number of samples, which in turn enables detailed mapping of large areas. MS predicted values enabled the characterization and the understanding of spatial variability of the studied PTEs.

Spatial effects of aboveground biomass on soil ecological parameters and trace gas fluxes in a savannah ecosystem of Mount Kilimanjaro

NASA Astrophysics Data System (ADS)

Becker, Joscha; Gütlein, Adrian; Sierra Cornejo, Natalia; Kiese, Ralf; Hertel, Dietrich; Kuzyakov, Yakov

2015-04-01

The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation in this area consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. Canopy structure is known to affect microclimate, throughfall and evapotranspiration and thereby controls soil moisture conditions. Consequently, the canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine trends and changes of soil parameters and relate their spatial variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. Distances were calculated in relation to the crown radius. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass carbon C and N, soil respiration as well as root biomass and -density, soil temperature and soil water content. Each tree was characterized by crown spread, leaf area index and basal area. Preliminary results show that C and N stocks decreased about 50% with depth independently of distance to the tree. Soil water content under the tree crown increased with depth while it decreased under grass cover. Microbial Biomass C and N in the upper 10 cm decreased with distance (C: r²=0.22, p<0.001; N: r²=0.3, p<0.001) as well as total soil respiration. This decrease was affected by tree size but independent from tree species. We conclude that savannah ecosystems exhibit a large spatial variability of soil parameters within the upper horizons which is strongly depend on the structure of aboveground biomass.

Disturbance Impacts on Thermal Hot Spots and Hot Moments at the Peatland-Atmosphere Interface

NASA Astrophysics Data System (ADS)

Leonard, R. M.; Kettridge, N.; Devito, K. J.; Petrone, R. M.; Mendoza, C. A.; Waddington, J. M.; Krause, S.

2018-01-01

Soil-surface temperature acts as a master variable driving nonlinear terrestrial ecohydrological, biogeochemical, and micrometeorological processes, inducing short-lived or spatially isolated extremes across heterogeneous landscape surfaces. However, subcanopy soil-surface temperatures have been, to date, characterized through isolated, spatially discrete measurements. Using spatially complex forested northern peatlands as an exemplar ecosystem, we explore the high-resolution spatiotemporal thermal behavior of this critical interface and its response to disturbances by using Fiber-Optic Distributed Temperature Sensing. Soil-surface thermal patterning was identified from 1.9 million temperature measurements under undisturbed, trees removed and vascular subcanopy removed conditions. Removing layers of the structurally diverse vegetation canopy not only increased mean temperatures but it shifted the spatial and temporal distribution, range, and longevity of thermal hot spots and hot moments. We argue that linking hot spots and/or hot moments with spatially variable ecosystem processes and feedbacks is key for predicting ecosystem function and resilience.

Small-scale spatial variability of soil microbial community composition and functional diversity in a mixed forest

NASA Astrophysics Data System (ADS)

Wang, Qiufeng; Tian, Jing; Yu, Guirui

2014-05-01

Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

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.

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

NASA Technical Reports Server (NTRS)

Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

2013-01-01

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

The role of spatial heterogeneity of the environment in soil fauna recovery after fires

NASA Astrophysics Data System (ADS)

Gongalsky, K. B.; Zaitsev, A. S.

2016-12-01

Forest fires are almost always heterogeneous, leaving less-disturbed sites that are potentially suitable as habitats for soil-dwelling creatures. The recovery of large soil animal communities after fires is therefore dependent on the spatial structure of the burned habitats. The role of locally less disturbed sites in the survival of soil macrofauna communities along with traditionally considered immigration from the surrounding undisturbed habitats is shown by the example of burnt areas located in three geographically distant regions of European Russia. Such unburned soil cover sites (perfugia) occupy 5-10% of the total burned habitats. Initially, perfugia are characterized by much higher (200-300% of the average across a burned area) diversity and abundance of soil fauna. A geostatistical method made it possible to estimate the perfugia size for soil macrofauna at 3-8 m.

Spatial patterns in oxygen and redox sensitive biogeochemistry in tropical forest soils

Treesearch

Daniel Liptzin; Whendee L. Silver

2015-01-01

Humid tropical forest soils are characterized by warm temperatures, abundant rainfall, and high rates of biological activity that vary considerably in both space and time. These conditions, together with finely textured soils typical of humid tropical forests lead to periodic low redox conditions, even in well-drained upland environments. The relationship between redox...

Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics

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

Improving UK Chalk hydrometeorology across spatial scales using a small hydrometeorological network

NASA Astrophysics Data System (ADS)

Rosolem, Rafael; Iwema, Joost; Rahman, Mostaquimur; Desilets, Darin; Koltermann da Silva, Juliana

2016-04-01

Chalk in the UK acts as a primary aquifer providing up to 80% of the public water supply locally. Chalk outcrops are located over most of southern and eastern England. Despite its importance, the characterization of Chalk in hydrometeorological models is still very limited. There is a need for a comprehensive and coherent integration of observations and modeling efforts across spatial scales for better understanding Chalk hydrometeorology. Here we introduce the "A MUlti-scale Soil moisture-Evapotranspiration Dynamics" (AMUSED) project. AMUSED goal is to better identify the key dominant processes controlling changes in soil moisture and surface fluxes (e.g., evapotranspiration) across spatial scales by combining ground-based observations with hydrometeorological models and satellite remote sensing products. The AMUSED observational platform consists of three sites located in Upper Chalk region of the Lambourn Catchment located in southern England covering approximately 2 square-km characterized by distinct combinations of soil and vegetation types. The network includes standard meteorological measurements, an eddy covariance system for turbulent fluxes and cosmic-ray neutron sensors for integrated soil moisture estimates at intermediate scales. Here we present our initial results from our three sites.

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Electrical resistivity tomography to delineate greenhouse soil variability

NASA Astrophysics Data System (ADS)

Rossi, R.; Amato, M.; Bitella, G.; Bochicchio, R.

2013-03-01

Appropriate management of soil spatial variability is an important tool for optimizing farming inputs, with the result of yield increase and reduction of the environmental impact in field crops. Under greenhouses, several factors such as non-uniform irrigation and localized soil compaction can severely affect yield and quality. Additionally, if soil spatial variability is not taken into account, yield deficiencies are often compensated by extra-volumes of crop inputs; as a result, over-irrigation and overfertilization in some parts of the field may occur. Technology for spatially sound management of greenhouse crops is therefore needed to increase yield and quality and to address sustainability. In this experiment, 2D-electrical resistivity tomography was used as an exploratory tool to characterize greenhouse soil variability and its relations to wild rocket yield. Soil resistivity well matched biomass variation (R2=0.70), and was linked to differences in soil bulk density (R2=0.90), and clay content (R2=0.77). Electrical resistivity tomography shows a great potential in horticulture where there is a growing demand of sustainability coupled with the necessity of stabilizing yield and product quality.

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

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.

Soil moisture dynamics and dominant controls at different spatial scales over semiarid and semi-humid areas

NASA Astrophysics Data System (ADS)

Suo, Lizhu; Huang, Mingbin; Zhang, Yongkun; Duan, Liangxia; Shan, Yan

2018-07-01

Soil moisture dynamics plays an active role in ecological and hydrological processes, and it depends on a large number of environmental factors, such as topographic attributes, soil properties, land use types, and precipitation. However, studies must still clarify the relative significance of these environmental factors at different soil depths and at different spatial scales. This study aimed: (1) to characterize temporal and spatial variations in soil moisture content (SMC) at four soil layers (0-40, 40-100, 100-200, and 200-500 cm) and three spatial scales (plot, hillslope, and region); and (2) to determine their dominant controls in diverse soil layers at different spatial scales over semiarid and semi-humid areas of the Loess Plateau, China. Given the high co-dependence of environmental factors, partial least squares regression (PLSR) was used to detect relative significance among 15 selected environmental factors that affect SMC. Temporal variation in SMC decreased with increasing soil depth, and vertical changes in the 0-500 cm soil profile were divided into a fast-changing layer (0-40 cm), an active layer (40-100 cm), a sub-active layer (100-200 cm), and a relatively stable layer (200-500 cm). PLSR models simulated SMC accurately in diverse soil layers at different scales; almost all values for variation in response (R2) and goodness of prediction (Q2) were >0.5 and >0.0975, respectively. Upper and lower layer SMCs were the two most important factors that influenced diverse soil layers at three scales, and these SMC variables exhibited the highest importance in projection (VIP) values. The 7-day antecedent precipitation and 7-day antecedent potential evapotranspiration contributed significantly to SMC only at the 0-40 cm soil layer. VIP of soil properties, especially sand and silt content, which influenced SMC strongly, increased significantly after increasing the measured scale. Mean annual precipitation and potential evapotranspiration also influenced SMC at the regional scale significantly. Overall, this study indicated that dominant controls of SMC varied among three spatial scales on the Loess Plateau, and VIP was a function of spatial scale and soil depth.

Quantification of spatial distribution and spread of bacteria in soil at microscale

NASA Astrophysics Data System (ADS)

Juyal, Archana; Eickhorst, Thilo; Falconer, Ruth; Baveye, Philippe; Otten, Wilfred

2015-04-01

Soil bacteria play an essential role in functioning of ecosystems and maintaining of biogeochemical cycles. Soil is a complex heterogeneous environment comprising of highly variable and dynamic micro-habitats that have significant impacts on the growth and activity of resident microbiota including bacteria and fungi. Bacteria occupy a very small portion of available pore space in soil which demonstrates that their spatial arrangement in soil has a huge impact on the contact to their target and on the way they interact to carry out their functions. Due to limitation of techniques, there is scant information on spatial distribution of indigenous or introduced bacteria at microhabitat scale. There is a need to understand the interaction between soil structure and microorganisms including fungi for ecosystem-level processes such as carbon sequestration and improving the predictive models for soil management. In this work, a combination of techniques was used including X-ray CT to characterize the soil structure and in-situ detection via fluorescence microscopy to visualize and quantify bacteria in soil thin sections. Pseudomonas fluorescens bacteria were introduced in sterilized soil of aggregate size 1-2 mm and packed at bulk-densities 1.3 g cm-3 and 1.5 g cm-3. A subset of samples was fixed with paraformaldehyde and subsequently impregnated with resin. DAPI and fluorescence in situ hybridization (FISH) were used to visualize bacteria in thin sections of soil cores by epifluorescence microscopy to enumerate spatial distribution of bacteria in soil. The pore geometry of soil was quantified after X-ray microtomography scanning. The distribution of bacteria introduced locally reduced significantly (P

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, Dani; Tecon, Robin; Ebrahimi, Ali; Kleyer, Hannah; Ilie, Olga; Wang, Gang

2015-04-01

Microbial life in soil occurs within fragmented aquatic habitats formed in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world

Microbial Life in Soil - Linking Biophysical Models with Observations

NASA Astrophysics Data System (ADS)

Or, D.; Tecon, R.; Ebrahimi, A.; Kleyer, H.; Ilie, O.; Wang, G.

2014-12-01

Microbial life in soil occurs within fragmented aquatic habitats in complex pore spaces where motility is restricted to short hydration windows (e.g., following rainfall). The limited range of self-dispersion and physical confinement promote spatial association among trophically interdepended microbial species. Competition and preferences for different nutrient resources and byproducts and their diffusion require high level of spatial organization to sustain the functioning of multispecies communities. We report mechanistic modeling studies of competing multispecies microbial communities grown on hydrated surfaces and within artificial soil aggregates (represented by 3-D pore network). Results show how trophic dependencies and cell-level interactions within patchy diffusion fields promote spatial self-organization of motile microbial cells. The spontaneously forming patterns of segregated, yet coexisting species were robust to spatial heterogeneities and to temporal perturbations (hydration dynamics), and respond primarily to the type of trophic dependencies. Such spatially self-organized consortia may reflect ecological templates that optimize substrate utilization and could form the basic architecture for more permanent surface-attached microbial colonies. Hydration dynamics affect structure and spatial arrangement of aerobic and anaerobic microbial communities and their biogeochemical functions. Experiments with well-characterized artificial soil microbial assemblies grown on porous surfaces provide access to community dynamics during wetting and drying cycles detected through genetic fingerprinting. Experiments for visual observations of spatial associations of tagged bacterial species with known trophic dependencies on model porous surfaces are underway. Biophysical modeling provide a means for predicting hydration-mediated critical separation distances for activation of spatial self-organization. The study provides new modeling and observational tools that enable new mechanistic insights into how differences in substrate affinities among microbial species and soil micro-hydrological conditions may give rise to a remarkable spatial and functional order in an extremely heterogeneous soil microbial world.

Effect of Spatial Resolution for Characterizing Soil Properties from Imaging Spectrometer Data

NASA Astrophysics Data System (ADS)

Dutta, D.; Kumar, P.; Greenberg, J. A.

2015-12-01

The feasibility of quantifying soil constituents over large areas using airborne hyperspectral data [0.35 - 2.5 μm] in an ensemble bootstrapping lasso algorithmic framework has been demonstrated previously [1]. However the effects of coarsening the spatial resolution of hyperspectral data on the quantification of soil constituents are unknown. We use Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data collected at 7.6m resolution over Birds Point New Madrid (BPNM) floodway for up-scaling and generating multiple coarser resolution datasets including the 60m Hyperspectral Infrared Imager (HyspIRI) like data. HyspIRI is a proposed visible shortwave/thermal infrared mission, which will provide global data over a spectral range of 0.35 - 2.5μm at a spatial resolution of 60m. Our results show that the lasso method, which is based on point scale observational data, is scalable. We found consistent good model performance (R2) values (0.79 < R2 < 0.82) and correct classifications as per USDA soil texture classes at multiple spatial resolutions. The results further demonstrate that the attributes of the pdf for different soil constituents across the landscape and the within-pixel variance are well preserved across scales. Our analysis provides a methodological framework with a sufficient set of metrics for assessing the performance of scaling up analysis from point scale observational data and may be relevant for other similar remote sensing studies. [1] Dutta, D.; Goodwell, A.E.; Kumar, P.; Garvey, J.E.; Darmody, R.G.; Berretta, D.P.; Greenberg, J.A., "On the Feasibility of Characterizing Soil Properties From AVIRIS Data," Geoscience and Remote Sensing, IEEE Transactions on, vol.53, no.9, pp.5133,5147, Sept. 2015. doi: 10.1109/TGRS.2015.2417547.

Contrasting spatial patterns and ecological attributes of soil bacterial and archaeal taxa across a landscape

PubMed Central

Constancias, Florentin; Saby, Nicolas P A; Terrat, Sébastien; Dequiedt, Samuel; Horrigue, Wallid; Nowak, Virginie; Guillemin, Jean-Philippe; Biju-Duval, Luc; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2015-01-01

Even though recent studies have clarified the influence and hierarchy of environmental filters on bacterial community structure, those constraining bacterial populations variations remain unclear. In consequence, our ability to understand to ecological attributes of soil bacteria and to predict microbial community response to environmental stress is therefore limited. Here, we characterized the bacterial community composition and the various bacterial taxonomic groups constituting the community across an agricultural landscape of 12 km2, by using a 215 × 215 m systematic grid representing 278 sites to precisely decipher their spatial distribution and drivers at this scale. The bacterial and Archaeal community composition was characterized by applying 16S rRNA gene pyrosequencing directly to soil DNA from samples. Geostatistics tools were used to reveal the heterogeneous distribution of bacterial composition at this scale. Soil physical parameters and land management explained a significant amount of variation, suggesting that environmental selection is the major process shaping bacterial composition. All taxa systematically displayed also a heterogeneous and particular distribution patterns. Different relative influences of soil characteristics, land use and space were observed, depending on the taxa, implying that selection and spatial processes might be differentially but not exclusively involved for each bacterial phylum. Soil pH was a major factor determining the distribution of most of the bacterial taxa and especially the most important factor explaining the spatial patterns of α-Proteobacteria and Planctomycetes. Soil texture, organic carbon content and quality were more specific to a few number of taxa (e.g., β-Proteobacteria and Chlorobi). Land management also influenced the distribution of bacterial taxa across the landscape and revealed different type of response to cropping intensity (positive, negative, neutral or hump-backed relationships) according to phyla. Altogether, this study provided valuable clues about the ecological behavior of soil bacterial and archaeal taxa at an agricultural landscape scale and could be useful for developing sustainable strategies of land management. PMID:25922908

Sampling Soil for Characterization and Site Description

NASA Technical Reports Server (NTRS)

Levine, Elissa

1999-01-01

The sampling scheme for soil characterization within the GLOBE program is uniquely different from the sampling methods of the other protocols. The strategy is based on an understanding of the 5 soil forming factors (parent material, climate, biota, topography, and time) at each study site, and how each of these interact to produce a soil profile with unique characteristics and unique input and control into the atmospheric, biological, and hydrological systems. Soil profile characteristics, as opposed to soil moisture and temperature, vegetative growth, and atmospheric and hydrologic conditions, change very slowly, depending on the parameter being measured, ranging from seasonally to many thousands of years. Thus, soil information, including profile description and lab analysis, is collected only one time for each profile at a site. These data serve two purposes: 1) to supplement existing spatial information about soil profile characteristics across the landscape at local, regional, and global scales, and 2) to provide specific information within a given area about the basic substrate to which elements within the other protocols are linked. Because of the intimate link between soil properties and these other environmental elements, the static soil properties at a given site are needed to accurately interpret and understand the continually changing dynamics of soil moisture and temperature, vegetation growth and phenology, atmospheric conditions, and chemistry and turbidity in surface waters. Both the spatial and specific soil information can be used for modeling purposes to assess and make predictions about global change.

3D soil structure characterization of Biological Soil Crusts from Alpine Tarfala Valley

NASA Astrophysics Data System (ADS)

Mele, Giacomo; Gargiulo, Laura; Zucconi, Laura; D'Acqui, Luigi; Ventura, Stefano

2017-04-01

Cyanobacteria filaments, microfungal hyphae, lichen rhizinae and anchoring rhizoids of bryophytes all together contribute to induce formation of structure in the thin soil layer beneath the Biological Soil Crusts (BSCs). Quantitative assessment of the soil structure beneath the BSCs is primarily hindered by the fragile nature of the crusts. Therefore, the role of BSCs in affecting such soil physical property has been rarely addressed using direct measurements. In this work we applied non-destructive X-ray microtomography imaging on five different samples of BSCs collected in the Alpine Tarfala Valley (northern Sweden), which have already been characterized in terms of fungal biodiversity in a previous work. We obtained images of the 3D spatial organization of the soil underneath the BSCs and characterized its structure by applying procedures of image analysis allowing to determine pore size distribution, pore connectivity and aggregate size distribution. Results has then been correlated with the different fungal assemblages of the samples.

Spatial interpolation of soil organic carbon using apparent electrical conductivity as secondary information

NASA Astrophysics Data System (ADS)

Martinez, G.; Vanderlinden, K.; Ordóñez, R.; Muriel, J. L.

2009-04-01

Soil organic carbon (SOC) spatial characterization is necessary to evaluate under what circumstances soil acts as a source or sink of carbon dioxide. However, at the field or catchment scale it is hard to accurately characterize its spatial distribution since large numbers of soil samples are necessary. As an alternative, near-surface geophysical sensor-based information can improve the spatial estimation of soil properties at these scales. Electromagnetic induction (EMI) sensors provide non-invasive and non-destructive measurements of the soil apparent electrical conductivity (ECa), which depends under non-saline conditions on clay content, water content or SOC, among other properties that determine the electromagnetic behavior of the soil. This study deals with the possible use of ECa-derived maps to improve SOC spatial estimation by Simple Kriging with varying local means (SKlm). Field work was carried out in a vertisol in SW Spain. The field is part of a long-term tillage experiment set up in 1982 with three replicates of conventional tillage (CT) and Direct Drilling (DD) plots with unitary dimensions of 15x65m. Shallow and deep (up to 0.8m depth) apparent electrical conductivity (ECas and ECad, respectively) was measured using the EM38-DD EMI sensor. Soil samples were taken from the upper horizont and analyzed for their SOC content. Correlation coefficients of ECas and ECad with SOC were low (0.331 and 0.175) due to the small range of SOC values and possibly also to the different support of the ECa and SOC data. Especially the ECas values were higher in the DD plots. The normalized ECa difference (ΔECa), calculated as the difference between the normalized ECas and ECad values, distinguished clearly the CT and DD plots, with the DD plots showing positive ΔECa values and CT plots ΔECa negative values. The field was stratified using fuzzy k-means (FKM) classification of ΔECa (FKM1), and ECas and ECad (FKM2). The FKM1 map mainly showed the difference between CT and DD plots, while the FKM2 map showed both differences between CT and DD and topography-associated features. Using the FKM1 and FKM2 maps as secondary information accounted for 30% of the total SOC variability, whereas plot and management average SOC explained 44 and 41%, respectively. Cross validation of SKlm using FKM2 reduced the RMSE by 8% and increased the efficiency index almost 70% as compared to Ordinary Kriging. This work shows how ECa can improve the spatial characterization of SOC, despite its low correlation and the small size of the plots used in this study.

Spatial modeling of litter and soil carbon stocks with associated uncertainty on forest land in the conterminous United States

NASA Astrophysics Data System (ADS)

Cao, B.; Domke, G. M.; Russell, M.; McRoberts, R. E.; Walters, B. F.

2017-12-01

Forest ecosystems contribute substantially to carbon (C) storage. The dynamics of litter decomposition, translocation and stabilization into soil layers are essential processes in the functioning of forest ecosystems, as they control the cycling of soil organic matter and the accumulation and release of C to the atmosphere. Therefore, the spatial distributions of litter and soil C stocks are important in greenhouse gas estimation and reporting and inform land management decisions, policy, and climate change mitigation strategies. In this study, we explored the effects of spatial aggregation of climatic, biotic, topographic and soil input data on national estimates of litter and soil C stocks and characterized the spatial distribution of litter and soil C stocks in the conterminous United States. Data from the Forest Inventory and Analysis (FIA) program within the US Forest Service were used with vegetation phenology data estimated from LANDSAT imagery (30 m) and raster data describing relevant environmental parameters (e.g. temperature, precipitation, topographic properties) for the entire conterminous US. Litter and soil C stocks were estimated and mapped through geostatistical analysis and statistical uncertainty bounds on the pixel level predictions were constructed using a Monte Carlo-bootstrap technique, by which credible variance estimates for the C stocks were calculated. The sensitivity of model estimates to spatial aggregation depends on geographic region. Further, using long-term (30-year) climate averages during periods with strong climatic trends results in large differences in litter and soil C stock estimates. In addition, results suggest that local topographic aspect is an important variable in litter and soil C estimation at the continental scale.

Random field theory to interpret the spatial variability of lacustrine soils

NASA Astrophysics Data System (ADS)

Russo, Savino; Vessia, Giovanna

2015-04-01

The lacustrine soils are quaternary soils, dated from Pleistocene to Holocene periods, generated in low-energy depositional environments and characterized by soil mixture of clays, sands and silts with alternations of finer and coarser grain size layers. They are often met at shallow depth filling several tens of meters of tectonic or erosive basins typically placed in internal Appenine areas. The lacustrine deposits are often locally interbedded by detritic soils resulting from the failure of surrounding reliefs. Their heterogeneous lithology is associated with high spatial variability of physical and mechanical properties both along horizontal and vertical directions. The deterministic approach is still commonly adopted to accomplish the mechanical characterization of these heterogeneous soils where undisturbed sampling is practically not feasible (if the incoherent fraction is prevalent) or not spatially representative (if the cohesive fraction prevails). The deterministic approach consists on performing in situ tests, like Standard Penetration Tests (SPT) or Cone Penetration Tests (CPT) and deriving design parameters through "expert judgment" interpretation of the measure profiles. These readings of tip and lateral resistances (Rp and RL respectively) are almost continuous but highly variable in soil classification according to Schmertmann (1978). Thus, neglecting the spatial variability cannot be the best strategy to estimated spatial representative values of physical and mechanical parameters of lacustrine soils to be used for engineering applications. Hereafter, a method to draw the spatial variability structure of the aforementioned measure profiles is presented. It is based on the theory of the Random Fields (Vanmarcke 1984) applied to vertical readings of Rp measures from mechanical CPTs. The proposed method relies on the application of the regression analysis, by which the spatial mean trend and fluctuations about this trend are derived. Moreover, the scale of fluctuation is calculated to measure the maximum length beyond which profiles of measures are independent. The spatial mean trend can be used to identify "quasi-homogeneous" soil layers where the standard deviation and the scale of fluctuation can be calculated. In this study, five Rp profiles performed in the lacustrine deposits of the high River Pescara Valley have been analyzed. There, silty clay deposits with thickness ranging from a few meters to about 60m, and locally rich in sands and peats, are investigated. In this study, vertical trends of Rp profiles have been derived to be converted into design parameter mean trends. Furthermore, the variability structure derived from Rp readings can be propagated to design parameters to calculate the "characteristic values" requested by the European building codes. References Schmertmann J.H. 1978. Guidelines for Cone Penetration Test, Performance and Design. Report No. FHWA-TS-78-209, U.S. Department of Transportation, Washington, D.C., pp. 145. Vanmarcke E.H. 1984. Random Fields, analysis and synthesis. Cambridge (USA): MIT Press.

Microwave Soil Moisture Retrieval Under Trees Using a Modified Tau-Omega Model

USDA-ARS?s Scientific Manuscript database

IPAD is to provide timely and accurate estimates of global crop conditions for use in up-to-date commodity intelligence reports. A crucial requirement of these global crop yield forecasts is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogen...

Fluctuation of Indoor Radon and VOC Concentrations Due to Seasonal Variations

EPA Science Inventory

This research was conducted to better characterize the spatial and temporal variability of vapor intrusion by collecting a full year’s dataset of weekly measurements of subslab soil gas, external soil gas, and indoor air, on a single house that is impacted by vapor intrusion of r...

Scaling Properties and Spatial Interpolation of Soil Moisture

DTIC Science & Technology

2004-08-24

the sensitivities is useful not only for characterizing soil moisture but also for forecasting the vulnerability of a region’s water cycle to climate...regional water balance was presented that can be used to assess the impact of climatic fluctuations and changes on the water cycle of a region. In

Moment Analysis Characterizing Water Flow in Repellent Soils from On- and Sub-Surface Point Sources

NASA Astrophysics Data System (ADS)

Xiong, Yunwu; Furman, Alex; Wallach, Rony

2010-05-01

Water repellency has a significant impact on water flow patterns in the soil profile. Flow tends to become unstable in such soils, which affects the water availability to plants and subsurface hydrology. In this paper, water flow in repellent soils was experimentally studied using the light reflection method. The transient 2D moisture profiles were monitored by CCD camera for tested soils packed in a transparent flow chamber. Water infiltration experiments and subsequent redistribution from on-surface and subsurface point sources with different flow rates were conducted for two soils of different repellency degrees as well as for wettable soil. We used spatio-statistical analysis (moments) to characterize the flow patterns. The zeroth moment is related to the total volume of water inside the moisture plume, and the first and second moments are affinitive to the center of mass and spatial variances of the moisture plume, respectively. The experimental results demonstrate that both the general shape and size of the wetting plume and the moisture distribution within the plume for the repellent soils are significantly different from that for the wettable soil. The wetting plume of the repellent soils is smaller, narrower, and longer (finger-like) than that of the wettable soil compared with that for the wettable soil that tended to roundness. Compared to the wettable soil, where the soil water content decreases radially from the source, moisture content for the water-repellent soils is higher, relatively uniform horizontally and gradually increases with depth (saturation overshoot), indicating that flow tends to become unstable. Ellipses, defined around the mass center and whose semi-axes represented a particular number of spatial variances, were successfully used to simulate the spatial and temporal variation of the moisture distribution in the soil profiles. Cumulative probability functions were defined for the water enclosed in these ellipses. Practically identical cumulative probability functions (beta distribution) were obtained for all soils, all source types, and flow rates. Further, same distributions were obtained for the infiltration and redistribution processes. This attractive result demonstrates the competence and advantage of the moment analysis method.

Estimating Soil Organic Carbon Stocks and Spatial Patterns with Statistical and GIS-Based Methods

PubMed Central

Zhi, Junjun; Jing, Changwei; Lin, Shengpan; Zhang, Cao; Liu, Qiankun; DeGloria, Stephen D.; Wu, Jiaping

2014-01-01

Accurately quantifying soil organic carbon (SOC) is considered fundamental to studying soil quality, modeling the global carbon cycle, and assessing global climate change. This study evaluated the uncertainties caused by up-scaling of soil properties from the county scale to the provincial scale and from lower-level classification of Soil Species to Soil Group, using four methods: the mean, median, Soil Profile Statistics (SPS), and pedological professional knowledge based (PKB) methods. For the SPS method, SOC stock is calculated at the county scale by multiplying the mean SOC density value of each soil type in a county by its corresponding area. For the mean or median method, SOC density value of each soil type is calculated using provincial arithmetic mean or median. For the PKB method, SOC density value of each soil type is calculated at the county scale considering soil parent materials and spatial locations of all soil profiles. A newly constructed 1∶50,000 soil survey geographic database of Zhejiang Province, China, was used for evaluation. Results indicated that with soil classification levels up-scaling from Soil Species to Soil Group, the variation of estimated SOC stocks among different soil classification levels was obviously lower than that among different methods. The difference in the estimated SOC stocks among the four methods was lowest at the Soil Species level. The differences in SOC stocks among the mean, median, and PKB methods for different Soil Groups resulted from the differences in the procedure of aggregating soil profile properties to represent the attributes of one soil type. Compared with the other three estimation methods (i.e., the SPS, mean and median methods), the PKB method holds significant promise for characterizing spatial differences in SOC distribution because spatial locations of all soil profiles are considered during the aggregation procedure. PMID:24840890

Characterization of the spatial variability of soil available zinc at various sampling densities using grouped soil type information.

PubMed

Song, Xiao-Dong; Zhang, Gan-Lin; Liu, Feng; Li, De-Cheng; Zhao, Yu-Guo

2016-11-01

The influence of anthropogenic activities and natural processes involved high uncertainties to the spatial variation modeling of soil available zinc (AZn) in plain river network regions. Four datasets with different sampling densities were split over the Qiaocheng district of Bozhou City, China. The difference of AZn concentrations regarding soil types was analyzed by the principal component analysis (PCA). Since the stationarity was not indicated and effective ranges of four datasets were larger than the sampling extent (about 400 m), two investigation tools, namely F3 test and stationarity index (SI), were employed to test the local non-stationarity. Geographically weighted regression (GWR) technique was performed to describe the spatial heterogeneity of AZn concentrations under the non-stationarity assumption. GWR based on grouped soil type information (GWRG for short) was proposed so as to benefit the local modeling of soil AZn within each soil-landscape unit. For reference, the multiple linear regression (MLR) model, a global regression technique, was also employed and incorporated the same predictors as in the GWR models. Validation results based on 100 times realization demonstrated that GWRG outperformed MLR and can produce similar or better accuracy than the GWR approach. Nevertheless, GWRG can generate better soil maps than GWR for limit soil data. Two-sample t test of produced soil maps also confirmed significantly different means. Variogram analysis of the model residuals exhibited weak spatial correlation, rejecting the use of hybrid kriging techniques. As a heuristically statistical method, the GWRG was beneficial in this study and potentially for other soil properties.

Mapping the geogenic radon potential: methodology and spatial analysis for central Hungary.

PubMed

Szabó, Katalin Zsuzsanna; Jordan, Gyozo; Horváth, Ákos; Szabó, Csaba

2014-03-01

A detailed geogenic radon potential (GRP) mapping based on field soil gas radon and soil gas permeability measurements was carried out in this study. A conventional continuous variable approach was used in this study for GRP determination and to test its applicability to the selected area of Hungary. Spatial pattern of soil gas radon concentration, soil permeability and GRP and the relationship between geological formations and these parameters were studied by performing detailed spatial analysis. Exploratory data analysis revealed that higher soil gas radon activity concentration and GRP characterizes the mountains and hills than the plains. The highest values were found in the proluvial-deluvial sediments, rock debris on the downhill slopes eroded from hills. Among the Quaternary sediments, which characterize the study area, the fluvial sediment has the highest values, which are also located in the hilly areas. The lowest values were found in the plain areas covered by drift sand, fluvioeolic sand, fluvial sand and loess. As a conclusion, radon is related to the sediment cycle in the study area. A geogenic radon risk map was created, which assists human health risk assessment and risk reduction since it indicates the potential of the source of indoor radon. The map shows that low and medium geogenic radon potential characterizes the study area in central Hungary. High risk occurs only locally. The results reveal that Quaternary sediments are inhomogeneous from a radon point of view, fluvial sediment has medium GRP, whereas the other rock formations such as drift sand, fluioeolic sand, fluvial sand and loess, found in the study area, have low GRP. Copyright © 2013 Elsevier Ltd. All rights reserved.

Tradeoffs between vegetation management goals and livestock production under Adapative Grazing Management

USDA-ARS?s Scientific Manuscript database

Rangeland ecosystems are characterized by substantial temporal variability in weather overlaid on spatial variability associated with topography and soils (Fuhlendorf et al. 2012). Semiarid rangelands in particular are characterized by more extreme intra- and inter-annual variation in precipitation ...

Spatial Variability of Soil Physical Properties Obtained with Laboratory Methods and Their Relation to Field Electrical Resistivity Measurements

NASA Astrophysics Data System (ADS)

Dathe, A.; Nemes, A.; Bloem, E.; Patterson, M.; Gimenez, D.; Angyal, A.; Koestel, J. K.; Jarvis, N.

2017-12-01

Soil spatial heterogeneity plays a critical role for describing water and solute transport processes in the unsaturated zone. Although we have a sound understanding of the physical properties underlying this heterogeneity (like macropores causing preferential water flow), their quantification in a spatial context is still a challenge. To improve existing knowledge and modelling approaches we established a field experiment on an agriculturally used silty clay loam (Stagnosol) in SE Norway. Centimeter to decimeter scale heterogeneities were investigated in the field using electrical resistivity tomography (ERT) in a quasi-3D and a real 3D approach. More than 100 undisturbed soil samples were taken in the 2x1x1 m3plot investigated with 3D ERT to determine soil water retention, saturated and unsaturated hydraulic conductivities and bulk density in the laboratory. A subset of these samples was scanned at the computer tomography (CT) facility at the Swedish University of Agricultural Sciences in Uppsala, Sweden, with special emphasis on characterizing macroporosity. Results show that the ERT measurements captured the spatial distribution of bulk densities and reflected soil water contents. However, ERT could not resolve the large variation observed in saturated hydraulic conductivities from the soil samples. Saturated hydraulic conductivity was clearly related to the macroporosity visible in the CT scans obtained from the respective soil cores. Hydraulic conductivities close to saturation mainly changed with depths in the soil profile and therefore with bulk density. In conclusion, to quantify the spatial heterogeneity of saturated hydraulic conductivities scanning methods with a resolution smaller than the size of macropores have to be used. This is feasible only when the information obtained from for example CT scans of soil cores would be upscaled in a meaningful way.

Assessing the effects of land use changes on soil sensitivity to erosion in a highland ecosystem of semi-arid Turkey.

PubMed

Bayramin, Ilhami; Basaran, Mustafa; Erpul, Günay; Canga, Mustafa R

2008-05-01

There has been increasing concern in highlands of semiarid Turkey that conversion of these systems results in excessive soil erosion, ecosystem degradation, and loss of sustainable resources. An increasing rate of land use/cover changes especially in semiarid mountainous areas has resulted in important effects on physical and ecological processes, causing many regions to undergo accelerated environmental degradation in terms of soil erosion, mass movement and reservoir sedimentation. This paper, therefore, explores the impact of land use changes on land degradation in a linkage to the soil erodibility, RUSLE-K, in Cankiri-Indagi Mountain Pass, Turkey. The characterization of soil erodibility in this ecosystem is important from the standpoint of conserving fragile ecosystems and planning management practices. Five adjacent land uses (cropland, grassland, woodland, plantation, and recreational land) were selected for this research. Analysis of variance showed that soil properties and RUSLE-K statistically changed with land use changes and soils of the recreational land and cropland were more sensitive to water erosion than those of the woodland, grassland, and plantation. This was mainly due to the significant decreases in soil organic matter (SOM) and hydraulic conductivity (HC) in those lands. Additionally, soil samples randomly collected from the depths of 0-10 cm (D1) and 10-20 cm (D2) with irregular intervals in an area of 1,200 by 4,200 m sufficiently characterized not only the spatial distribution of soil organic matter (SOM), hydraulic conductivity (HC), clay (C), silt (Si), sand (S) and silt plus very fine sand (Si + VFS) but also the spatial distribution of RUSLE-K as an algebraically estimate of these parameters together with field assessment of soil structure to assess the dynamic relationships between soil properties and land use types. In this study, in order to perform the spatial analyses, the mean sampling intervals were 43, 50, 64, 78, 85 m for woodland, plantation, grassland, recreation, and cropland with the sample numbers of 56, 79, 72, 13, and 69, respectively, resulting in an average interval of 64 m for whole study area. Although nugget effect and nugget effect-sill ratio gave an idea about the sampling design adequacy, the better results are undoubtedly likely by both equi-probable spatial sampling and random sampling representative of all land uses.

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.

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

NASA Astrophysics Data System (ADS)

Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

2017-03-01

Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10-30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of ΔSOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) were used. To verify our method, results were compared with ΔSOC observed by soil resampling. Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of ΔSOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial differences and short-term temporal dynamics of ΔSOC.

Using radiocarbon to investigate soil respiration impacts on atmospheric CO2

NASA Astrophysics Data System (ADS)

Phillips, C. L.; LaFranchi, B. W.; McFarlane, K. J.; Desai, A. R.

2013-12-01

While soil respiration is believed to represent the largest single source of CO2 emissions on a global scale, there are few tools available to measure soil emissions at large spatial scales. We investigated whether radiocarbon (14C) abundance in CO2 could be used to detect and characterize soil emissions in the atmosphere, taking advantage of the fact that 14C abundance in soil carbon is elevated compared to the background atmosphere, a result of thermonuclear weapons testing during the mid-20th Century (i.e. bomb-C). Working in a temperate hardwood forest in Northern Wisconsin during 2011-12, we made semi-high-frequency measurements of CO2 at nested spatial scales from the soil subsurface to 150 m above ground level. These measurements were used to investigate seasonal patterns in respired C sources, and to evaluate whether variability in soil-respired Δ14C could also be detected in atmospheric measurements. In our ground-level measurements we found large seasonal variation in soil-respired 14CO2 that correlated with soil moisture, which was likely related to root activity. Atmospheric measurements of 14CO2 in the forest canopy (2 to 30m) were used to construct Keeling plots, and these provided larger spatial-scale estimates of respired 14CO2 that largely agreed with the soil-level measurements. In collaboration with the NOAA we also examined temporal patterns of 14CO2 at the Park Falls tall-tower (150m), and found elevated 14CO2 levels during summer months that likely resulted from increased respiration from heterotrophic sources. These results demonstrate that a fingerprint from soil-respired CO2 can be detected in the seasonal patterns of atmospheric 14CO2, even at a regionally-integrating spatial scale far from the soil surface.

Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes

NASA Astrophysics Data System (ADS)

Viaud, Valérie; Lacoste, Marine; Michot, Didier; Walter, Christian

2014-05-01

Soil organic carbon (SOC) has a crucial impact on global carbon storage at world scale. SOC spatial variability is controlled by the landscape patterns resulting from the continuous interactions between the physical environment and the society. Natural and anthropogenic processes occurring and interplaying at the landscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage and water erosion processes or spatial differentiation of land-use and land-management practices, strongly affect SOC dynamics. Inventories of SOC stocks, reflecting their spatial distribution, are thus key elements to develop relevant management strategies to improving carbon sequestration and mitigating climate change and soil degradation. This study aims to quantify SOC stocks and their spatial distribution in a 1,000-ha agricultural bocage landscape with dairy production as dominant farming system (Zone Atelier Armorique, LTER Europe, NW France). The site is characterized by high heterogeneity on short distance due to a high diversity of soils with varying waterlogging, soil parent material, topography, land-use and hedgerow density. SOC content and stocks were measured up to 105-cm depth in 200 sampling locations selected using conditioned Latin hypercube sampling. Additive sampling was designed to specifically explore SOC distribution near to hedges: 112 points were sampled at fixed distance on 14 transects perpendicular from hedges. We illustrate the heterogeneity of spatial and vertical distribution of SOC stocks at landscape scale, and quantify SOC stocks in the various landscape components. Using multivariate statistics, we discuss the variability and co-variability of existing spatial organization of cropping systems, environmental factors, and SOM stocks, over landscape. Ultimately, our results may contribute to improving regional or national digital soil mapping approaches, by considering the distribution of SOC stocks within each modeling unit and by accounting for the impact of sensitive ecosystems.

Soil organic carbon stocks in Alaska estimated with spatial and pedon data

USGS Publications Warehouse

Bliss, Norman B.; Maursetter, J.

2010-01-01

Temperatures in high-latitude ecosystems are increasing faster than the average rate of global warming, which may lead to a positive feedback for climate change by increasing the respiration rates of soil organic C. If a positive feedback is confirmed, soil C will represent a source of greenhouse gases that is not currently considered in international protocols to regulate C emissions. We present new estimates of the stocks of soil organic C in Alaska, calculated by linking spatial and field data developed by the USDA NRCS. The spatial data are from the State Soil Geographic database (STATSGO), and the field and laboratory data are from the National Soil Characterization Database, also known as the pedon database. The new estimates range from 32 to 53 Pg of soil organic C for Alaska, formed by linking the spatial and field data using the attributes of Soil Taxonomy. For modelers, we recommend an estimation method based on taxonomic subgroups with interpolation for missing areas, which yields an estimate of 48 Pg. This is a substantial increase over a magnitude of 13 Pg estimated from only the STATSGO data as originally distributed in 1994, but the increase reflects different estimation methods and is not a measure of the change in C on the landscape. Pedon samples were collected between 1952 and 2002, so the results do not represent a single point in time. The linked databases provide an improved basis for modeling the impacts of climate change on net ecosystem exchange.

Spatial distribution and sources of heavy metals in natural pasture soil around copper-molybdenum mine in Northeast China.

PubMed

Wang, Zhiqiang; Hong, Chen; Xing, Yi; Wang, Kang; Li, Yifei; Feng, Lihui; Ma, Silu

2018-06-15

The characterization of the content and source of heavy metals are essential to assess the potential threat of metals to human health. The present study collected 140 topsoil samples around a Cu-Mo mine (Wunugetushan, China) and investigated the concentrations and spatial distribution pattern of Cr, Ni, Zn, Cu, Mo and Cd in soil using multivariate and geostatistical analytical methods. Results indicated that the average concentrations of six heavy metals, especially Cu and Mo, were obviously higher than the local background values. Correlation analysis and principal component analysis divided these metals into three groups, including Cr and Ni, Cu and Mo, Zn and Cd. Meanwhile, the spatial distribution maps of heavy metals indicated that Cr and Ni in soil were no notable anthropogenic inputs and mainly controlled by natural factors because their spatial maps exhibited non-point source contamination. The concentrations of Cu and Mo gradually decreased with distance away from the mine area, suggesting that human mining activities may be crucial in the spreading of contaminants. Soil contamination of Zn were associated with livestock manure produced from grazing. In addition, the environmental risk of heavy metal pollution was assessed by geo-accumulation index. All the results revealed that the spatial distribution of heavy metals in soil were in agreement with the local human activities. Investigating and identifying the origin of heavy metals in pasture soil will lay the foundation for taking effective measures to preserve soil from the long-term accumulation of heavy metals. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Speciation of Soil Phosphorus Assessed by XANES Spectroscopy at Different Spatial Scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hesterberg, Dean; McNulty, Ian; Thieme, Juergen

Precise management of soil phosphorus (P) to meet competing demands of agriculture and environmental protection can benefit from more comprehensive characterization of P speciation in soils. Our objectives were to provide spatial context for spectroscopic analyses of soil P speciation in relation to molecular-scale species and landscape-scale management of P, and to compare soil P-species diversity from spectroscopic measurements at submicron and millimeter scales. The spatial range of ~26 orders of magnitude between atomic and field scales presents a challenge to upscaling and downscaling information from spectroscopic analyses of soils. Scanning fluorescence X-ray microscopy images of a 50-mm ´ 45-mmmore » area of an organic soil sample showed heterogeneous distributions of P, Al, and Si. Microscale X-ray absorption near edge structure (μ-XANES) spectra collected at the P K-edge from 12 spots on the soil sample exhibited diverse features that indicated variations in highly localized P speciation. Linear combination fitting analysis of the μ-XANES spectra included various proportions of three standards that appeared in fits for most spots and five standards that appeared in fits for one spot each. The fit to a bulk-soil spectrum was dominated by two of the common standards in the μ-XANES fits, and a fit to the sum of m-XANES spectra included four of the standards. Lastly, these results illustrate a gain in P species sensitivity from spatially resolved XANES analysis. Integrating spectroscopic analyses from multiple scales determines soil P species diversity and will ultimately help connect speciation to the chemical reactivity and mobility of P in soils.« less

Speciation of Soil Phosphorus Assessed by XANES Spectroscopy at Different Spatial Scales

DOE PAGES

Hesterberg, Dean; McNulty, Ian; Thieme, Juergen

2017-07-27

Precise management of soil phosphorus (P) to meet competing demands of agriculture and environmental protection can benefit from more comprehensive characterization of P speciation in soils. Our objectives were to provide spatial context for spectroscopic analyses of soil P speciation in relation to molecular-scale species and landscape-scale management of P, and to compare soil P-species diversity from spectroscopic measurements at submicron and millimeter scales. The spatial range of ~26 orders of magnitude between atomic and field scales presents a challenge to upscaling and downscaling information from spectroscopic analyses of soils. Scanning fluorescence X-ray microscopy images of a 50-mm ´ 45-mmmore » area of an organic soil sample showed heterogeneous distributions of P, Al, and Si. Microscale X-ray absorption near edge structure (μ-XANES) spectra collected at the P K-edge from 12 spots on the soil sample exhibited diverse features that indicated variations in highly localized P speciation. Linear combination fitting analysis of the μ-XANES spectra included various proportions of three standards that appeared in fits for most spots and five standards that appeared in fits for one spot each. The fit to a bulk-soil spectrum was dominated by two of the common standards in the μ-XANES fits, and a fit to the sum of m-XANES spectra included four of the standards. Lastly, these results illustrate a gain in P species sensitivity from spatially resolved XANES analysis. Integrating spectroscopic analyses from multiple scales determines soil P species diversity and will ultimately help connect speciation to the chemical reactivity and mobility of P in soils.« less

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.

Spatial Variability of Plant Available Water, Soil Organic Carbon, and Microbial Biomass under Divergent Land Uses: A Comparison among Regression-Kriging, Cokriging, and Regression-Cokriging

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.

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.

Interpolation Approaches for Characterizing Spatial Variability of Soil Properties in Tuz Lake Basin of Turkey

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.

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.

Searching for the right scale in catchment hydrology: the effect of soil spatial variability in simulated states and fluxes

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Zink, Matthias; Kumar, Rohini; Samaniego, Luis; Attinger, Sabine

2017-04-01

The advances in computer science and the availability of new detailed data-sets have led to a growing number of distributed hydrological models applied to finer and finer grid resolutions for larger and larger catchment areas. It was argued, however, that this trend does not necessarily guarantee better understanding of the hydrological processes or it is even not necessary for specific modelling applications. In the present study, this topic is further discussed in relation to the soil spatial heterogeneity and its effect on simulated hydrological state and fluxes. To this end, three methods are developed and used for the characterization of the soil heterogeneity at different spatial scales. The methods are applied at the soil map of the upper Neckar catchment (Germany), as example. The different soil realizations are assessed regarding their impact on simulated state and fluxes using the distributed hydrological model mHM. The results are analysed by aggregating the model outputs at different spatial scales based on the Representative Elementary Scale concept (RES) proposed by Refsgaard et al. (2016). The analysis is further extended in the present study by aggregating the model output also at different temporal scales. The results show that small scale soil variabilities are not relevant when the integrated hydrological responses are considered e.g., simulated streamflow or average soil moisture over sub-catchments. On the contrary, these small scale soil variabilities strongly affect locally simulated states and fluxes i.e., soil moisture and evapotranspiration simulated at the grid resolution. A clear trade-off is also detected by aggregating the model output by spatial and temporal scales. Despite the scale at which the soil variabilities are (or are not) relevant is not universal, the RES concept provides a simple and effective framework to quantify the predictive capability of distributed models and to identify the need for further model improvements e.g., finer resolution input. For this reason, the integration in this analysis of all the relevant input factors (e.g., precipitation, vegetation, geology) could provide a strong support for the definition of the right scale for each specific model application. In this context, however, the main challenge for a proper model assessment will be the correct characterization of the spatio- temporal variability of each input factor. Refsgaard, J.C., Højberg, A.L., He, X., Hansen, A.L., Rasmussen, S.H., Stisen, S., 2016. Where are the limits of model predictive capabilities?: Representative Elementary Scale - RES. Hydrol. Process. doi:10.1002/hyp.11029

Contrasting spatial patterns and ecological attributes of soil bacterial and archaeal taxa across a landscape.

PubMed

Constancias, Florentin; Saby, Nicolas P A; Terrat, Sébastien; Dequiedt, Samuel; Horrigue, Wallid; Nowak, Virginie; Guillemin, Jean-Philippe; Biju-Duval, Luc; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2015-06-01

Even though recent studies have clarified the influence and hierarchy of environmental filters on bacterial community structure, those constraining bacterial populations variations remain unclear. In consequence, our ability to understand to ecological attributes of soil bacteria and to predict microbial community response to environmental stress is therefore limited. Here, we characterized the bacterial community composition and the various bacterial taxonomic groups constituting the community across an agricultural landscape of 12 km(2) , by using a 215 × 215 m systematic grid representing 278 sites to precisely decipher their spatial distribution and drivers at this scale. The bacterial and Archaeal community composition was characterized by applying 16S rRNA gene pyrosequencing directly to soil DNA from samples. Geostatistics tools were used to reveal the heterogeneous distribution of bacterial composition at this scale. Soil physical parameters and land management explained a significant amount of variation, suggesting that environmental selection is the major process shaping bacterial composition. All taxa systematically displayed also a heterogeneous and particular distribution patterns. Different relative influences of soil characteristics, land use and space were observed, depending on the taxa, implying that selection and spatial processes might be differentially but not exclusively involved for each bacterial phylum. Soil pH was a major factor determining the distribution of most of the bacterial taxa and especially the most important factor explaining the spatial patterns of α-Proteobacteria and Planctomycetes. Soil texture, organic carbon content and quality were more specific to a few number of taxa (e.g., β-Proteobacteria and Chlorobi). Land management also influenced the distribution of bacterial taxa across the landscape and revealed different type of response to cropping intensity (positive, negative, neutral or hump-backed relationships) according to phyla. Altogether, this study provided valuable clues about the ecological behavior of soil bacterial and archaeal taxa at an agricultural landscape scale and could be useful for developing sustainable strategies of land management. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Demonstration/Validation of Incremental Sampling at Two Diverse Military Ranges and Development of an Incremental Sampling Tool

DTIC Science & Technology

2010-06-01

Sampling (MIS)? • Technique of combining many increments of soil from a number of points within exposure area • Developed by Enviro Stat (Trademarked...Demonstrating a reliable soil sampling strategy to accurately characterize contaminant concentrations in spatially extreme and heterogeneous...into a set of decision (exposure) units • One or several discrete or small- scale composite soil samples collected to represent each decision unit

Characterizing the risk assessment of heavy metals and sampling uncertainty analysis in paddy field by geostatistics and GIS.

PubMed

Liu, Xingmei; Wu, Jianjun; Xu, Jianming

2006-05-01

For many practical problems in environmental management, information about soil heavy metals, relative to threshold values that may be of practical importance is needed at unsampled sites. The Hangzhou-Jiaxing-Huzhou (HJH) Plain has always been one of the most important rice production areas in Zhejiang province, China, and the soil heavy metal concentration is directly related to the crop quality and ultimately the health of people. Four hundred and fifty soil samples were selected in topsoil in HJH Plain to characterize the spatial variability of Cu, Zn, Pb, Cr and Cd. Ordinary kriging and lognormal kriging were carried out to map the spatial patterns of heavy metals and disjunctive kriging was used to quantify the probability of heavy metal concentrations higher than their guide value. Cokriging method was used to minimize the sampling density for Cu, Zn and Cr. The results of this study could give insight into risk assessment of environmental pollution and decision-making for agriculture.

Prediction of erodibility in Oxisols using iron oxides, soil color and diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Arantes Camargo, Livia; Marques, José, Jr.

2015-04-01

The prediction of erodibility using indirect methods such as diffuse reflectance spectroscopy could facilitate the characterization of the spatial variability in large areas and optimize implementation of conservation practices. The aim of this study was to evaluate the prediction of interrill erodibility (Ki) and rill erodibility (Kr) by means of iron oxides content and soil color using multiple linear regression and diffuse reflectance spectroscopy (DRS) using regression analysis by least squares partial (PLSR). The soils were collected from three geomorphic surfaces and analyzed for chemical, physical and mineralogical properties, plus scanned in the spectral range from the visible and infrared. Maps of spatial distribution of Ki and Kr were built with the values calculated by the calibrated models that obtained the best accuracy using geostatistics. Interrill-rill erodibility presented negative correlation with iron extracted by dithionite-citrate-bicarbonate, hematite, and chroma, confirming the influence of iron oxides in soil structural stability. Hematite and hue were the attributes that most contributed in calibration models by multiple linear regression for the prediction of Ki (R2 = 0.55) and Kr (R2 = 0.53). The diffuse reflectance spectroscopy via PLSR allowed to predict Interrill-rill erodibility with high accuracy (R2adj = 0.76, 0.81 respectively and RPD> 2.0) in the range of the visible spectrum (380-800 nm) and the characterization of the spatial variability of these attributes by geostatistics.

Atypical soil carbon distribution across a tropical steepland forest catena

Treesearch

Kristofer D. Johnson; F.N. Scatena; Whendee L. Silver

2011-01-01

Soil organic carbon (SOC) in a humid subtropical forest in Puerto Rico is higher at ridge locations compared to valleys, and therefore opposite to what is commonly observed in other forested hillslope catenas. To better understand the spatial distribution of SOC in this system, plots previously characterized by topographic position, vegetation type and stand age were...

Three-dimensional mapping of soil chemical characteristics at micrometric scale: Statistical prediction by combining 2D SEM-EDX data and 3D X-ray computed micro-tomographic images

NASA Astrophysics Data System (ADS)

Hapca, Simona

2015-04-01

Many soil properties and functions emerge from interactions of physical, chemical and biological processes at microscopic scales, which can be understood only by integrating techniques that traditionally are developed within separate disciplines. While recent advances in imaging techniques, such as X-ray computed tomography (X-ray CT), offer the possibility to reconstruct the 3D physical structure at fine resolutions, for the distribution of chemicals in soil, existing methods, based on scanning electron microscope (SEM) and energy dispersive X-ray detection (EDX), allow for characterization of the chemical composition only on 2D surfaces. At present, direct 3D measurement techniques are still lacking, sequential sectioning of soils, followed by 2D mapping of chemical elements and interpolation to 3D, being an alternative which is explored in this study. Specifically, we develop an integrated experimental and theoretical framework which combines 3D X-ray CT imaging technique with 2D SEM-EDX and use spatial statistics methods to map the chemical composition of soil in 3D. The procedure involves three stages 1) scanning a resin impregnated soil cube by X-ray CT, followed by precision cutting to produce parallel thin slices, the surfaces of which are scanned by SEM-EDX, 2) alignment of the 2D chemical maps within the internal 3D structure of the soil cube, and 3) development, of spatial statistics methods to predict the chemical composition of 3D soil based on the observed 2D chemical and 3D physical data. Specifically, three statistical models consisting of a regression tree, a regression tree kriging and cokriging model were used to predict the 3D spatial distribution of carbon, silicon, iron and oxygen in soil, these chemical elements showing a good spatial agreement between the X-ray grayscale intensities and the corresponding 2D SEM-EDX data. Due to the spatial correlation between the physical and chemical data, the regression-tree model showed a great potential in predicting chemical composition in particular for iron, which is generally sparsely distributed in soil. For carbon, silicon and oxygen, which are more densely distributed, the additional kriging of the regression tree residuals improved significantly the prediction, whereas prediction based on co-kriging was less consistent across replicates, underperforming regression-tree kriging. The present study shows a great potential in integrating geo-statistical methods with imaging techniques to unveil the 3D chemical structure of soil at very fine scales, the framework being suitable to be further applied to other types of imaging data such as images of biological thin sections for characterization of microbial distribution. Key words: X-ray CT, SEM-EDX, segmentation techniques, spatial correlation, 3D soil images, 2D chemical maps.

Mapping and determinism of soil microbial community distribution across an agricultural landscape

PubMed Central

Constancias, Florentin; Terrat, Sébastien; Saby, Nicolas P A; Horrigue, Walid; Villerd, Jean; Guillemin, Jean-Philippe; Biju-Duval, Luc; Nowak, Virginie; Dequiedt, Samuel; Ranjard, Lionel; Chemidlin Prévost-Bouré, Nicolas

2015-01-01

Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity. PMID:25833770

Topographic Controls on Spatial Patterns of Soil Texture and Moisture in a Semi-arid Montane Catchment with Aspect-Dependent Vegetation

NASA Astrophysics Data System (ADS)

Lehman, B. M.; Niemann, J. D.

2008-12-01

Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no significant relationship with topographic indices. When the catchment average soil moisture is low, the variance of soil moisture increases with the average. When the average is high, the variance remains relatively constant. Little of the variation in soil moisture is explained by topographic indices when the catchment is either very wet or dry; however, when the average soil moisture takes on intermediate values, cos(aspect) is consistently the best predictor among the terrain indices considered.

Laboratory-based characterization of plutonium in soil particles using micro-XRF and 3D confocal XRF

DOE PAGES

McIntosh, Kathryn Gallagher; Cordes, Nikolaus Lynn; Patterson, Brian M.; ...

2015-03-29

The investigation of plutonium (Pu) in a soil matrix is of interest in safeguards, nuclear forensics, and environmental remediation activities. The elemental composition of two plutonium contaminated soil particles was characterized nondestructively using a pair of micro X-ray fluorescence spectrometry (micro-XRF) techniques including high resolution X-ray (hiRX) and 3D confocal XRF. The three dimensional elemental imaging capability of confocal XRF permitted the identification two distinct Pu particles within the samples: one external to the Ferich soil matrix and another co-located with Cu within the soil matrix. The size and morphology of the particles was assessed with X-ray transmission microscopy andmore » micro X-ray computed tomography (micro-CT) providing complementary morphological information. Limits of detection for a 30 μm Pu particle are <10 ng for each of the XRF techniques. Ultimately, this study highlights the capability for lab-based, nondestructive, spatially resolved characterization of heterogeneous matrices on the micrometer scale with nanogram sensitivity.« less

Spatial Variation in Soil Properties among North American Ecosystems and Guidelines for Sampling Designs

PubMed Central

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

Detecting small-scale spatial differences and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

NASA Astrophysics Data System (ADS)

Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

2017-04-01

Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial and temporal changes in SOC stocks, particularly pronounced on arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal as well as small-scale spatial dynamics of ΔSOC. Therefore, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) was used. To verify our method, results were compared with ΔSOC observed by soil resampling. AC measurements were performed from 2010 to 2014 under a silage maize/winter fodder rye/sorghum-Sudan grass hybrid/alfalfa crop rotation at a colluvial depression located in the hummocky ground moraine landscape of NE Germany. Widespread in large areas of the formerly glaciated Northern Hemisphere, this depression type is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity in soil properties, such as SOC and nitrogen (Nt). After monitoring the initial stage during 2010, soil erosion was experimentally simulated by incorporating topsoil material from an eroded midslope soil into the plough layer of the colluvial depression. SOC stocks were quantified before and after soil manipulation and at the end of the study period. AC-based ΔSOC values corresponded well with the tendencies and magnitude of the results observed in the repeated soil inventory. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial and short-term temporal dynamics of ΔSOC.

Assessment of the spatio-temporal distribution of soil properties in East Kolkata wetland ecosystem (A Ramsar site: 1208)

NASA Astrophysics Data System (ADS)

Pal, S.; Manna, S.; Aich, A.; Chattopadhyay, B.; Mukhopadhyay, S. K.

2014-06-01

The present investigation was made to characterize spatial and temporal variations in soil properties and to evaluate possible differences that could be dependent on the tannery effluent discharges, municipal sewage discharges, vegetation cover, soil settlement rate, crop rotation, etc. Soil total organic matter (TOM), cations like, Sodium (Na), Ammonium (NH4), Potassium (K), Calcium (Ca) and Magnesium (Mg) contents in the bank soils and bottom sediments were recorded from seven different characteristic sites in East Kolkata wetland ecosystem, a Ramsar site (Ramsar site No. 1208). The profile maps were constructed by geostatistical methods to describe the spatial distribution as well as temporal variations of all the factors to identify the influences of composite wastewaters. The work was initiated to identify causes and consequences of the waste dumping in the concerned region for the past hundred years and thereby to suggest necessary precautionary measures to prevent further loss of soil quality.

Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield.

PubMed

Rime, Thomas; Hartmann, Martin; Brunner, Ivano; Widmer, Franco; Zeyer, Josef; Frey, Beat

2015-03-01

Spatial patterns of microbial communities have been extensively surveyed in well-developed soils, but few studies investigated the vertical distribution of micro-organisms in newly developed soils after glacier retreat. We used 454-pyrosequencing to assess whether bacterial and fungal community structures differed between stages of soil development (SSD) characterized by an increasing vegetation cover from barren (vegetation cover: 0%/age: 10 years), sparsely vegetated (13%/60 years), transient (60%/80 years) to vegetated (95%/110 years) and depths (surface, 5 and 20 cm) along the Damma glacier forefield (Switzerland). The SSD significantly influenced the bacterial and fungal communities. Based on indicator species analyses, metabolically versatile bacteria (e.g. Geobacter) and psychrophilic yeasts (e.g. Mrakia) characterized the barren soils. Vegetated soils with higher C, N and root biomass consisted of bacteria able to degrade complex organic compounds (e.g. Candidatus Solibacter), lignocellulolytic Ascomycota (e.g. Geoglossum) and ectomycorrhizal Basidiomycota (e.g. Laccaria). Soil depth only influenced bacterial and fungal communities in barren and sparsely vegetated soils. These changes were partly due to more silt and higher soil moisture in the surface. In both soil ages, the surface was characterized by OTUs affiliated to Phormidium and Sphingobacteriales. In lower depths, however, bacterial and fungal communities differed between SSD. Lower depths of sparsely vegetated soils consisted of OTUs affiliated to Acidobacteria and Geoglossum, whereas depths of barren soils were characterized by OTUs related to Gemmatimonadetes. Overall, plant establishment drives the soil microbiota along the successional gradient but does not influence the vertical distribution of microbiota in recently deglaciated soils. © 2014 John Wiley & Sons Ltd.

Spatial vulnerability assessments by regression kriging

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor

2016-04-01

Two fairly different complex environmental phenomena, causing natural hazard were mapped based on a combined spatial inference approach. The behaviour is related to various environmental factors and the applied approach enables the inclusion of several, spatially exhaustive auxiliary variables that are available for mapping. Inland excess water (IEW) is an interrelated natural and human induced phenomenon causes several problems in the flat-land regions of Hungary, which cover nearly half of the country. The term 'inland excess water' refers to the occurrence of inundations outside the flood levee that originate from sources differing from flood overflow, it is surplus surface water forming due to the lack of runoff, insufficient absorption capability of soil or the upwelling of groundwater. There is a multiplicity of definitions, which indicate the complexity of processes that govern this phenomenon. Most of the definitions have a common part, namely, that inland excess water is temporary water inundation that occurs in flat-lands due to both precipitation and groundwater emerging on the surface as substantial sources. Radon gas is produced in the radioactive decay chain of uranium, which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on soil physical and meteorological parameters and can enter and accumulate in the buildings. Health risk originating from indoor radon concentration attributed to natural factors is characterized by geogenic radon potential (GRP). In addition to geology and meteorology, physical soil properties play significant role in the determination of GRP. Identification of areas with high risk requires spatial modelling, that is mapping of specific natural hazards. In both cases external environmental factors determine the behaviour of the target process (occurrence/frequncy of IEW and grade of GRP respectively). Spatial auxiliary information representing IEW or GRP forming environmental factors were taken into account to support the spatial inference of the locally experienced IEW frequency and measured GRP values respectively. An efficient spatial prediction methodology was applied to construct reliable maps, namely regression kriging (RK) using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Application of RK also provides the possibility of inherent accuracy assessment. The resulting maps are characterized by global and local measures of its accuracy. Additionally the method enables interval estimation for spatial extension of the areas of predefined risk categories. All of these outputs provide useful contribution to spatial planning, action planning and decision making. Acknowledgement: Our work was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Spatial distribution of ammonia-oxidizing bacteria and archaea across a 44-hectare farm related to ecosystem functioning

PubMed Central

Wessén, Ella; Söderström, Mats; Stenberg, Maria; Bru, David; Hellman, Maria; Welsh, Allana; Thomsen, Frida; Klemedtson, Leif; Philippot, Laurent; Hallin, Sara

2011-01-01

Characterization of spatial patterns of functional microbial communities could facilitate the understanding of the relationships between the ecology of microbial communities, the biogeochemical processes they perform and the corresponding ecosystem functions. Because of the important role the ammonia-oxidizing bacteria (AOB) and archaea (AOA) have in nitrogen cycling and nitrate leaching, we explored the spatial distribution of their activity, abundance and community composition across a 44-ha large farm divided into an organic and an integrated farming system. The spatial patterns were mapped by geostatistical modeling and correlations to soil properties and ecosystem functioning in terms of nitrate leaching were determined. All measured community components for both AOB and AOA exhibited spatial patterns at the hectare scale. The patchy patterns of community structures did not reflect the farming systems, but the AOB community was weakly related to differences in soil pH and moisture, whereas the AOA community to differences in soil pH and clay content. Soil properties related differently to the size of the communities, with soil organic carbon and total nitrogen correlating positively to AOB abundance, while clay content and pH showed a negative correlation to AOA abundance. Contrasting spatial patterns were observed for the abundance distributions of the two groups indicating that the AOB and AOA may occupy different niches in agro-ecosystems. In addition, the two communities correlated differently to community and ecosystem functions. Our results suggest that the AOA, not the AOB, were contributing to nitrate leaching at the site by providing substrate for the nitrite oxidizers. PMID:21228891

A Molecular Investigation of Soil Organic Carbon Composition, Variability, and Spatial Distribution Across an Alpine Catchment

NASA Astrophysics Data System (ADS)

Hsu, H. T.; Lawrence, C. R.; Winnick, M.; Druhan, J. L.; Williams, K. H.; Maher, K.; Rainaldi, G. R.; McCormick, M. E.

2016-12-01

The cycling of carbon through soils is one of the least understood aspects of the global carbon cycle and represents a key uncertainty in the prediction of land-surface response to global warming. Thus, there is an urgent need for advanced characterization of soil organic carbon (SOC) to develop and evaluate a new generation of soil carbon models. We hypothesize that shifts in SOC composition and spatial distribution as a function of soil depth can be used to constrain rates of transformation between the litter layer and the deeper subsoil (extending to a depth of approximately 1 m). To evaluate the composition and distribution of SOC, we collected soil samples from East River, a shale-dominated watershed near Crested Butte, CO, and characterized relative changes in SOC species as a function of depth using elemental analysis (EA), Fourier transform infrared spectroscopy (FT-IR) and bulk C X-ray absorption spectroscopy (XAS). Our results show that total organic carbon (TOC) decreases with depth, and high total inorganic carbon (TIC) content was found in deeper soils (after 75 cm), a characteristic of the bedrock (shale). The distribution of aliphatic C relative to the parent material generally decreases with depth and that polysaccharide can be a substantial component of SOC at various depths. On the other hand, the relative distribution of aromatic C, traditionally viewed as recalcitrant, only makes up a very small part of SOC regardless of depth. These observations confirm that molecular structure is not the only determinant of SOC turnover rate. To study other contributors to SOC decomposition, we studied changes in the spatial correlation of SOC and minerals using X-ray fluorescence spectroscopy (XRF) and scanning transmission X-ray microscopy (STXM). We found that aromatics mostly locate on the surface of small soil aggregates (1-10 μm). Polysaccharides and proteins, both viewed as labile traditionally, are more evenly distributed over the interior of the particles, which could limit microbial access and thus decrease decomposition rate. The speciation and spatial distribution results can be compared to field-measured CO2-fluxes, soil moisture, and radiocarbon data to assess the factors that control SOC turnover rates in different environments across the catchment and enhance the development of SOC models.

Soil pH Errors Propagation from Measurements to Spatial Predictions - Cost Benefit Analysis and Risk Assessment Implications for Practitioners and Modelers

NASA Astrophysics Data System (ADS)

Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.

2017-12-01

The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that need to be assessed against the risk. The modeling community can benefit from such analysis, however, error size and spatial distribution for global and regional predictions need to be assessed against the variability of other drivers and impact on management decisions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, Sarah L.; Gibbons, Sean M.; Owens, Sarah M.

Soil microbial communities are essential for ecosystem function, but linking community composition to biogeochemical processes is challenging because of high microbial diversity and large spatial variability of most soil characteristics. We investigated soil bacterial community structure in a switchgrass stand planted on soil with a history of grassland vegetation at high spatial resolution to determine whether biogeographic trends occurred at the centimeter scale. Moreover, we tested whether such heterogeneity, if present, influenced community structure within or among ecosystems. Pronounced heterogeneity was observed at centimeter scales, with abrupt changes in relative abundance of phyla from sample to sample. At the ecosystemmore » scale (> 10 m), however, bacterial community composition and structure were subtly, but significantly, altered by fertilization, with higher alpha diversity in fertilized plots. Moreover, by comparing these data with data from 1772 soils from the Earth Microbiome Project, it was found that 20% diverse globally sourced soil samples, while grassland soils shared approximately 40% of their operational taxonomic units with the current study. By spanning several orders of magnitude, the analysis suggested that extreme patchiness characterized community structure at smaller scales but that coherent patterns emerged at larger length scales.« less

Identification and Simulation of Subsurface Soil patterns using hidden Markov random fields and remote sensing and geophysical EMI data sets

NASA Astrophysics Data System (ADS)

Wang, Hui; Wellmann, Florian; Verweij, Elizabeth; von Hebel, Christian; van der Kruk, Jan

2017-04-01

Lateral and vertical spatial heterogeneity of subsurface properties such as soil texture and structure influences the available water and resource supply for crop growth. High-resolution mapping of subsurface structures using non-invasive geo-referenced geophysical measurements, like electromagnetic induction (EMI), enables a characterization of 3D soil structures, which have shown correlations to remote sensing information of the crop states. The benefit of EMI is that it can return 3D subsurface information, however the spatial dimensions are limited due to the labor intensive measurement procedure. Although active and passive sensors mounted on air- or space-borne platforms return 2D images, they have much larger spatial dimensions. Combining both approaches provides us with a potential pathway to extend the detailed 3D geophysical information to a larger area by using remote sensing information. In this study, we aim at extracting and providing insights into the spatial and statistical correlation of the geophysical and remote sensing observations of the soil/vegetation continuum system. To this end, two key points need to be addressed: 1) how to detect and recognize the geometric patterns (i.e., spatial heterogeneity) from multiple data sets, and 2) how to quantitatively describe the statistical correlation between remote sensing information and geophysical measurements. In the current study, the spatial domain is restricted to shallow depths up to 3 meters, and the geostatistical database contains normalized difference vegetation index (NDVI) derived from RapidEye satellite images and apparent electrical conductivities (ECa) measured from multi-receiver EMI sensors for nine depths of exploration ranging from 0-2.7 m. The integrated data sets are mapped into both the physical space (i.e. the spatial domain) and feature space (i.e. a two-dimensional space framed by the NDVI and the ECa data). Hidden Markov Random Fields (HMRF) are employed to model the underlying heterogeneities in spatial domain and finite Gaussian mixture models are adopted to quantitatively describe the statistical patterns in terms of center vectors and covariance matrices in feature space. A recently developed parallel stochastic clustering algorithm is adopted to implement the HMRF models and the Markov chain Monte Carlo based Bayesian inference. Certain spatial patterns such as buried paleo-river channels covered by shallow sediments are investigated as typical examples. The results indicate that the geometric patterns of the subsurface heterogeneity can be represented and quantitatively characterized by HMRF. Furthermore, the statistical patterns of the NDVI and the EMI data from the soil/vegetation-continuum system can be inferred and analyzed in a quantitative manner.

Multifractal analyis of soil invertebrates along a transect under different land uses

NASA Astrophysics Data System (ADS)

Machado Siqueira, Glécio; Alves Silva, Raimunda; Vidal-Vázquez, Eva; Paz-González, Antonio

2017-04-01

Soil fauna play a central role in many essential ecosystem processes. Land use and management can have a dramatic effect upon soil invertebrate community. Indices based on soil invertebrates abundance and diversity are fundamental for soil quality assessment. Many soil properties and attributes have been shown to exhibit spatial variabilityThe aim of this study was to analyze the scaling heterogeneity of the soil invertebrate community sampled using pitfall traps across a transect. The field study was conducted at Mata Roma municipality, Maranhão State, Brazil. Transects were marked under seven different agricultural/forestry land uses (millet, soybean, maize, eucalyptus, pasture, secondary savannah and native savannah). Native vegetation was considered as a reference, whereas the agricultural fields showed a range of soil use intensities. Along these transects 130 pitfall per land use were installed. First, differences in community assemblages and composition under different land use systems were evaluated using classical indices. Then, the spatial distribution of soil fauna trapped by pitfall techniques, characterized through generalized dimension, Dq, and singularity spectra, f(α) - α, showed a well-defined multifractal structure. Differences in scaling heterogeneity and other multifractal characteristics were examined in relation to land use intensification.

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

NASA Technical Reports Server (NTRS)

Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

2013-01-01

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

Variations in spatial patterns of soil-vegetation properties and the emergence of multiple resilience thresholds within different debris flow fan positions

NASA Astrophysics Data System (ADS)

Mohseni, Neda; Hosseinzadeh, Seyed Reza; Sepehr, Adel; Golzarian, Mahmood Reza; Shabani, Farzin

2017-08-01

Debris flow fans are non-equilibrium landforms resulting from the spatial variations of debris flows deposited on them. This geomorphic disturbance involving the asymmetric redistribution of water and sediment may create spatially heterogeneous patterns of soil-vegetation along landforms. In this research, founded on field-based observations, we characterized the spatial patterns of some soil (e.g., particle size distribution including fine and coarse covers, and infiltration capacity) and vegetation (e.g., plant distance, vegetation density, patch size, and average number of patches) properties within different debris flow fan positions (Upper, Middle, and Lower fan) located at the base of the Binaloud Mountain hillslope in northeastern Iran. Thereafter, using a mathematical model of dry land vegetation dynamics, we calculated response trends of the different positions to the same environmental harshness gradient. Field measurements of soil-vegetation properties and infiltration rates showed that the asymmetric redistribution of debris flow depositions can cause statistically significant differences (P < 0.05) in the spatial patterns of soil and eco-hydrological characteristics along different landform positions. The results showed that mean plant distance, mean vegetation density, and the average number of patches decreased as the coarse covers increased toward the Lower fan plots. Conversely, an increase in infiltration rate was observed. The simulation results on the aerial images taken from different positions, illustrated that positions with a heterogeneous distribution of vegetation patterns were not desertified to the same degree of aridity. Thus, the Middle and Lower positions could survive under harsher aridity conditions, due to the emergence of more varied spatial vegetation patterns than at the Upper fan position. The findings, based on a combined field and modeling approach, highlighted that debris flow as a geomorphic process with the asymmetric distribution of depositions on the gentle slope of an alluvial fan, can incur multiple resilience thresholds with different degrees of self-organization under stressful conditions over the spatial heterogeneities of soil-dependent vegetation structures.

Joint Assimilation of SMOS Brightness Temperature and GRACE Terrestrial Water Storage Observations for Improved Soil Moisture Estimation

NASA Technical Reports Server (NTRS)

Girotto, Manuela; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Rodell, Matthew

2017-01-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0 - 5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Joint assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for improved soil moisture estimation

NASA Astrophysics Data System (ADS)

Girotto, M.; Reichle, R. H.; De Lannoy, G.; Rodell, M.

2017-12-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0-5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Mapping and determinism of soil microbial community distribution across an agricultural landscape.

PubMed

Constancias, Florentin; Terrat, Sébastien; Saby, Nicolas P A; Horrigue, Walid; Villerd, Jean; Guillemin, Jean-Philippe; Biju-Duval, Luc; Nowak, Virginie; Dequiedt, Samuel; Ranjard, Lionel; Chemidlin Prévost-Bouré, Nicolas

2015-06-01

Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Improving Soil Moisture Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations

NASA Technical Reports Server (NTRS)

Girotto, Manuela

2018-01-01

Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).

Spatial pattern formation of microbes at the soil microscale affect soil C and N turnover in an individual-based microbial community model

NASA Astrophysics Data System (ADS)

Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie

2016-04-01

At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these pattern can be explained by the Turing mechanism. These pattern formation had strong consequences for process rates, as well as for C and N storage in the soil at the steady state: Scenarios that exhibited pattern formation were generally associated with higher C storage at steady state compared to those without pattern formation (i.e. at non-limiting conditions for microbes). Moreover, pattern formation lead to a spatial decoupling of C and N turnover processes, and to a spatial decoupling of microbial N mineralization and N immobilization. Taken together, our theoretical analysis shows that self-organisation may be a feature of the soil decomposer system, with consequences for process rates of microbial C and N turnover. Pattern formation through spatial self-organization, which has been observed on larger spatial scales in other resource-limited communities (e.g., vegetation patterns in arid or wetland eco-systems), may also occur at the soil microscale, leaving its mark on the soil's storage capacity for C and N.

Mapping Active Stream Lengths as a Tool for Understanding Spatial Variations in Runoff Generation

NASA Astrophysics Data System (ADS)

Erwin, E. G.; Gannon, J. P.; Zimmer, M. A.

2016-12-01

Recent studies have shown temporary stream channels respond in complex ways to precipitation. By investigating how stream networks expand and recede throughout rain events, we may further develop our understanding of runoff generation. This study focused on mapping the expansion and contraction of the stream network in two headwater catchments characterized by differing soil depths and slopes, located in North Carolina, USA. The first is a 43 ha catchment located in the Southern Appalachian region, characterized by incised, steep slopes and soils of varying thickness. The second is a 3.3 ha catchment located in the Piedmont region, characterized as low relief with deep, highly weathered soils. Over a variety of flow conditions, surveys of the entire stream network were conducted at 10 m intervals to determine presence or absence of surface water. These surveys revealed several reaches within the networks that were intermittent, with perennial flow upstream and downstream. Furthermore, in some tributaries, the active stream head moved up the channel in response to precipitation and at others it remained anchored in place. Moreover, when repeat surveys were performed during the same storm, hysteresis was observed in active stream length variations: stream length was not the same on the rising limb and falling limb of the hydrograph. These observations suggest there are different geomorphological controls or runoff generation processes occurring spatially throughout these catchments. Observations of wide spatial and temporal variability of active stream length over a variety of flow conditions suggest runoff dynamics, generation mechanisms, and contributing flowpath depths producing streamflow may be highly variable and not easily predicted from streamflow observations at a fixed point. Finally, the observation of similar patterns in differing geomorphic regions suggests these processes extend beyond unique site characterizations.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

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.

Spatiotemporal variability of hydrologic soil properties and the implications for overland flow and land management in a peri-urban Mediterranean catchment

NASA Astrophysics Data System (ADS)

Ferreira, C. S. S.; Walsh, R. P. D.; Steenhuis, T. S.; Shakesby, R. A.; Nunes, J. P. N.; Coelho, C. O. A.; Ferreira, A. J. D.

2015-06-01

Planning of semi-urban developments is often hindered by a lack of knowledge on how changes in land-use affect catchment hydrological response. The temporal and spatial patterns of overland flow source areas and their connectivity in the landscape, particularly in a seasonal climate, remain comparatively poorly understood. This study investigates seasonal variations in factors influencing runoff response to rainfall in a peri-urban catchment in Portugal characterized by a mosaic of landscape units and a humid Mediterranean climate. Variations in surface soil moisture, hydrophobicity and infiltration capacity were measured in six different landscape units (defined by land-use on either sandstone or limestone) in nine monitoring campaigns at key times over a one-year period. Spatiotemporal patterns in overland flow mechanisms were found. Infiltration-excess overland flow was generated in rainfalls during the dry summer season in woodland on both sandstone and limestone and on agricultural soils on limestone due probably in large part to soil hydrophobicity. In wet periods, saturation overland flow occurred on urban and agricultural soils located in valley bottoms and on shallow soils upslope. Topography, water table rise and soil depth determined the location and extent of saturated areas. Overland flow generated in upslope source areas potentially can infiltrate in other landscape units downslope where infiltration capacity exceeds rainfall intensity. Hydrophilic urban and agricultural-sandstone soils were characterized by increased infiltration capacity during dry periods, while forest soils provided potential sinks for overland flow when hydrophilic in the winter wet season. Identifying the spatial and temporal variability of overland flow sources and sinks is an important step in understanding and modeling flow connectivity and catchment hydrologic response. Such information is important for land managers in order to improve urban planning to minimize flood risk.

Spatiotemporal characterization of soil moisture fields in agricultural areas using cosmic-ray neutron probes and data fusion

NASA Astrophysics Data System (ADS)

Franz, Trenton; Wang, Tiejun

2015-04-01

Approximately 40% of global food production comes from irrigated agriculture. With the increasing demand for food even greater pressures will be placed on water resources within these systems. In this work we aimed to characterize the spatial and temporal patterns of soil moisture at the field-scale (~500 m) using the newly developed cosmic-ray neutron rover near Waco, NE USA. Here we mapped soil moisture of 144 quarter section fields (a mix of maize, soybean, and natural areas) each week during the 2014 growing season (May to September). The 12 by 12 km study domain also contained three stationary cosmic-ray neutron probes for independent validation of the rover surveys. Basic statistical analysis of the domain indicated a strong relationship between the mean and variance of soil moisture at several averaging scales. The relationships between the mean and higher order moments were not significant. Scaling analysis indicated strong power law behavior between the variance of soil moisture and averaging area with minimal dependence of mean soil moisture on the slope of the power law function. In addition, we combined the data from the three stationary cosmic-ray neutron probes and mobile surveys using linear regression to derive a daily soil moisture product at 1, 3, and 12 km spatial resolutions for the entire growing season. The statistical relationships derived from the rover dataset offer a novel set of observations that will be useful in: 1) calibrating and validating land surface models, 2) calibrating and validating crop models, 3) soil moisture covariance estimates for statistical downscaling of remote sensing products such as SMOS and SMAP, and 4) provide daily center-pivot scale mean soil moisture data for optimal irrigation timing and volume amounts.

Soil Bacteria and Fungi Respond on Different Spatial Scales to Invasion by the Legume Lespedeza cuneata.

PubMed

Yannarell, Anthony C; Busby, Ryan R; Denight, Michael L; Gebhart, Dick L; Taylor, Steven J

2011-01-01

The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader-microbe interactions. Lespedeza cuneata (Dum. Cours.) G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole-community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant.

Distribution of ancient carbon in buried soils in an eroding loess landscape

NASA Astrophysics Data System (ADS)

Szymanski, L. M.; Mason, J. A.; De Graaff, M. A.; Berhe, A. A.; Marin-Spiotta, E.

2017-12-01

Understanding the processes that contribute to the accumulation and loss of carbon in soils and the implications for land management is vital for mitigating climate change. Buried soils or paleosols that represent former surface horizons can store more organic carbon than mineral horizons at equivalent depths due to burial restricting microbial decomposition. The presence of buried soils defies modeled expectations of exponential declines in carbon concentrations with depth, especially in locations where successive depositional events lead to multiple buried soil layers. Buried soils are found in a diversity of depositional environments across latitudes and without accounting for their presence can lead to underestimates of regional carbon reservoirs. Here we present data on the spatial distribution of carbon in a paleosol loess sequence in Nebraska, focusing on one prominent paleosol, the Brady soil. The Brady soil has been identified throughout the Central Great Plains and began developing at the end of the Pleistocene and was subsequently buried by loess in the early Holocene (Mason et al. 2003). Preliminary analyses of the Brady soil at its deepest, 6-m below the surface, reveal large differences in the composition and degree of decomposition of organic matter from the modern soil. We sampled along burial and erosional transects to characterize spatial variability in the depth of Brady soil from the modern landscape surface and to determine how these differences may alter the amount and composition of organic carbon. A more accurate determination of the spatial extent and heterogeneity of buried soil carbon will improve regional estimates of carbon reservoirs. This assessment of its variability across the landscape will inform future planned work on the vulnerability of ancient carbon to disturbance.

Characterizing spatial and temporal variability in methane gas-flux dynamics of subtropical wetlands in the Big Cypress National Preserve, Florida

NASA Astrophysics Data System (ADS)

Sirianni, M.; Comas, X.; Shoemaker, B.

2017-12-01

Wetland methane emissions are highly variable both in space and time, and are controlled by changes in certain biogeochemical controls (i.e. organic matter availability; redox potential) and/or other environmental factors (i.e. soil temperature; water level). Consequently, hot spots (areas with disproportionally high emissions) may develop where biogeochemical and environmental conditions are especially conducive for enhancing certain microbial processes such as methanogenesis. The Big Cypress National Preserve is a collection of subtropical wetlands in southwestern Florida, including extensive forested (cypress, pine, hardwood) and sawgrass ecosystems that dry and flood annually in response to rainfall. In addition to rainfall, hydroperiod, fire regime, elevation above mean sea level, dominant vegetation type and underlying geological controls contribute to the development and evolution of organic and calcitic soils found throughout the Preserve. Currently, the U.S. Geological Survey employs eddy covariance methods within the Preserve to quantify carbon and methane exchanges over several spatially extensive vegetation communities. While eddy covariance towers are a convenient tool for measuring gas exchanges at the ecosystem scale, their spatially extensive footprint (hundreds of meters) may mask smaller scale spatial variabilities that may be conducive to the development of hot spots. Similarly, temporal resolution (i.e. sampling effort) at scales smaller that the eddy covariance measurement footprint is important since low resolution data may overlook rapid emission events and the temporal variability of discrete hot spots. In this work, we intend to estimate small-scale contributions of organic and calcitic soils to gas exchanges measured by the eddy covariance towers using a unique combination of ground penetrating radar (GPR), capacitance probes, gas traps, and time-lapse photography. By using an array of methods that vary in spatio-temporal resolution, we hope to better understand the uncertainties associated with measuring wetland methane fluxes across different spatial and temporal scales. Our results have implications for characterizing and refining methane flux estimates in subtropical peat soils that could be used for climate models.

Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils.

PubMed

Boente, C; Albuquerque, M T D; Fernández-Braña, A; Gerassis, S; Sierra, C; Gallego, J R

2018-08-01

When considering complex scenarios involving several attributes, such as in environmental characterization, a clearer picture of reality can be achieved through the dimensional reduction of data. In this context, maps facilitate the visualization of spatial patterns of contaminant distribution and the identification of enriched areas. A set, of 15 Potentially Toxic Elements (PTEs) - (As, Ba, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Se, Tl, V, and Zn), was measured in soil, collected in Langreo's municipality (80km 2 ), Spain. Relative enrichment (RE) is introduced here to refer to the proportion of elements present in a given context. Indeed, a novel approach is provided for research into PTE fate. This method involves studying the variability of PTE proportions throughout the study area, thereby allowing the identification of dissemination trends. Traditional geostatistical approaches commonly use raw data (concentrations) accepting that the elements analyzed make up the entirety of the soil. However, in geochemical studies the analyzed elements are just a fraction of the total soil composition. Therefore, considering compositional data is pivotal. The spatial characterization of PTEs considering raw and compositional data together allowed a broad discussion about, not only the PTEs concentration's distribution but also to reckon possible trends of relative enrichment (RE). Transformations to open closed data are widely used for this purpose. Spatial patterns have an indubitable interest. In this study, the Centered Log-ratio transformation (clr) was used, followed by its back-transformation, to build a set of compositional data that, combined with raw data, allowed to establish the sources of the PTEs and trends of spatial dissemination. Based on the obtained findings it was possible to conclude that the Langreo area is deeply affected by its industrial and mining legacy. City center is highly enriched in Pb and Hg and As shows enrichment in a northwesterly direction. Copyright © 2018 Elsevier B.V. All rights reserved.

Characterizing Watersheds with Geophysical Methods: Some uses of GPR and EMI in Hydropedological Investigations.

NASA Astrophysics Data System (ADS)

Doolittle, J.; Lin, H.; Jenkinson, B.; Zhou, X.

2006-05-01

The USDA-NRCS and its cooperators use ground-penetrating radar (GPR) and electromagnetic induction (EMI) as rapid, noninvasive tools to support soil surveys at different scales and levels of resolution. The effective use of GPR is site-specific and generally restricted to soils having low electrical conductivity (e.g., soils with low clay and soluble salt contents). In suitable soils, GPR provides high resolution data, which are used to estimate depths to soil horizons and geologic layers that restrict, redirect, and/or concentrate the flow of water through landscapes. In areas of coarse-textured soils, GPR has been used to map spatiotemporal variations in water-table depths and local ground-water flow patterns. Compared with GPR, EMI can be effectively used across a broader spectrum of soils and spatial scales, but provides lower resolution of subsurface features. EMI is used to refine and improve soil maps prepared with traditional soil survey methods. Differences in apparent conductivity (ECa) are associated with different soils and soil properties (e.g., clay, moisture and soluble salt contents). Apparent conductivity maps provide an additional layer of information, which directs soil sampling, aids the identification and delineation of some soil polygons, and enhances the quality of soil maps. More recently, these tools were used to characterize the hydropedological character of a small, steeply sloping, forested watershed. Within the watershed, EMI was used to characterize the principal soil-landscape components, and GPR was used to provide high resolution data on soil depth and layering within colluvial deposits located in swales and depressional areas.

Geo-Spatial Characterization of Soil Mercury and Arsenic at a High-Altitude Bolivian Gold Mine.

PubMed

Johnson, Glen D; Pavilonis, Brian; Caravanos, Jack; Grassman, Jean

2018-02-01

Soil mercury concentrations at a typical small-scale mine site in the Bolivian Andes were elevated (28-737 mg/kg or ppm) in localized areas where mercury amalgams were either formed or vaporized to release gold, but was not detectable beyond approximately 10 m from its sources. Arsenic was measurable, exceeding known background levels throughout the mine site (77-137,022 ppm), and was also measurable through the local village of Ingenio (36-1803 ppm). Although arsenic levels were high at all surveyed locations, its spatial pattern followed mercury, being highest where mercury was high.

Effects of vegetation structure on soil carbon, nutrients and greenhouse gas exchange in a savannah ecosystem of Mount Kilimanjaro Region

NASA Astrophysics Data System (ADS)

Becker, J.

2015-12-01

The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. The canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine spatial trends and changes of soil parameters and relate their variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass C and N, Natural δ13C, soil respiration, available nutrients, pH, cation exchange capacity (CEC) as well as root biomass and -density, soil temperature and soil water content. Concentrations and stocks of C and N fractions, CEC and K+ decreased up to 50% outside the crown covered area. Microbial C:N ratio and CO2 efflux was about 30% higher outside the crown. This indicates N limitation and low C use efficiency in soil outside the crown area. We conclude that the spatial structure of aboveground biomass in savanna ecosystems leads to a spatial variance in nutrient limitation. Therefore, the capability of a savanna ecosystem to act as a C sink is directly and indirectly dependent on the vegetation structure.

Pedologic influences on hillslope hydrology: The relationships between soil and hydrologic connectivity in a Californian oak-woodland

NASA Astrophysics Data System (ADS)

Alldritt, K.; O'Geen, A.; Dahlgren, R. A.

2013-12-01

Understanding what controls hydrologic connectivity and how it develops has important implications for ecosystem services. It can affect water quality, nutrient and sediment delivery to the stream, carbon and nitrogen cycling, and more. Bedrock topography and soil act in concert as primary physical controls on hydrologic connectivity. However, the important role soil can play is not well understood. A hillslope study was conducted to explore the dynamics between soil and hydrologic connectivity. The hillslope was in a zero-order watershed with a flashy ephemeral stream. It was located in an oak-woodland in the Californian northern Sierra foothills. The research objectives were to 1) identify and characterize hydrologically significant soil properties; 2) explore how soil stratigraphy and morphology influence hydrologic connectivity; and 3) examine potential causes for connection and disconnection of hydrologic flowpaths during and between rain storm events. During the 2012 wet season a 210-m hillslope transect was instrumented to collect soil moisture data every five minutes. The instruments were put at multiple locations and depths to capture the soil spatial variability. Once the soil became too dry for monitoring the transect was trenched, characterized and sampled. Texture, bulk density, saturated hydraulic conductivity and soil water retention curves were measured in the lab. Structure, color, redoximorphic features, soil horizon spatial differentiation, saprolite and bedrock characteristics, and coarse fragment percentage were recorded in the field. Prior to excavation an electromagnetic induction (EMI) and ground penetrating radar (GPR) survey in conjunction with the Natural Resource Conservation Service (NRCS) was performed along the hillslope. The goal of the survey was to explore non-invasive techniques to determine spatial variability of hydrologically significant soil horizons and bedrock. The GPR was found not to be reliable at the site. However, the EMI showed potential in showing the discontinuous distribution of the claypan, a horizon characterized by a large and abrupt increase in clay content and very low permeability. The data obtained from the transect excavation was used to create a two-dimensional hillslope model using HYDRUS-2D. Coupled with the soil moisture and local precipitation data the hillslope hydrology was modeled at individual storm event time scale. The field data showed that the hillslope was very complex and comprised of a discontinuous claypan, undulating bedrock topography and highly variable saprolite. The soil moisture data and modeling efforts showed that the surface horizons, which are highly permeable and contain numerous macropores, are the primary hydrologic flowpaths during storm events. The model showed that the presence of claypan decreased effective soil depth, increased antecedent wetness and created a perched water table. The model also showed that the undulating bedrock acted like a dam along the hillslope. The claypan network and undulating bedrock created isolated zones of wetness that only become connected and flow downhill into the stream when a storm caused the disconnected zones to rise in the highly permeable surface horizons.

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.

Integration of soil moisture and geophysical datasets for improved water resource management in irrigated systems

NASA Astrophysics Data System (ADS)

Finkenbiner, Catherine; Franz, Trenton E.; Avery, William Alexander; Heeren, Derek M.

2016-04-01

Global trends in consumptive water use indicate a growing and unsustainable reliance on water resources. Approximately 40% of total food production originates from irrigated agriculture. With increasing crop yield demands, water use efficiency must increase to maintain a stable food and water trade. This work aims to increase our understanding of soil hydrologic fluxes at intermediate spatial scales. Fixed and roving cosmic-ray neutron probes were combined in order to characterize the spatial and temporal patterns of soil moisture at three study sites across an East-West precipitation gradient in the state of Nebraska, USA. A coarse scale map was generated for the entire domain (122 km2) at each study site. We used a simplistic 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 (˜102m2) for variable rate irrigation, the individual wedge (˜103m2) for variable speed irrigation, and the quarter section (0.82 km2) for uniform rate irrigation. Additionally, we were able to generate a daily soil moisture product over the entire study area at various key modeling and remote sensing scales 12, 32, and 122 km2. Our soil moisture products and derived soil properties were then compared against spatial datasets (i.e. field capacity and wilting point) from the US Department of Agriculture Web Soil Survey. The results show that our "observed" field capacity was higher compared to the Web Soil Survey products. 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 depth and times in relation to soil moisture depletion below field capacity and above maximum allowable depletion. The incorporation of this non-contact and pragmatic geophysical method into current irrigation practices across the state and globe has the potential to greatly increase agricultural water use efficiency at scale.

Landscape Metrics to Predict Soil Spatial Patterns

NASA Astrophysics Data System (ADS)

Gillin, C. P.; McGuire, K. J.; Bailey, S.; Prisley, S.

2012-12-01

Recent literature has advocated the application of hydropedology, or the integration of hydrology and pedology, to better understand hydrologic flowpaths and soil spatial heterogeneity in a landscape. Hydropedology can be used to describe soil units affected by distinct topography, geology, and hydrology. Such a method has not been applied to digital soil mapping in the context of spatial variations in hydrological and biogeochemical processes. The purpose of this study is to use field observations of soil morphology, geospatial information technology, and a multinomial logistic regression model to predict the distribution of five hydropedological units (HPUs) across a 41-hectare forested headwater catchment in New England. Each HPU reflects varying degrees of lateral flow influence on soil development. Ninety-six soil characterization pits were located throughout the watershed, and HPU type was identified at each pit based on the presence and thickness of genetic soil horizons. Digital terrain analysis was conducted using ArcGIS and SAGA software to compute topographic and landscape metrics. Results indicate that each HPU occurs under specific topographic settings that influence subsurface hydrologic conditions. Among the most important landscape metrics are distance from stream, distance from bedrock outcrop, upslope accumulated area, the topographic wetness index, the downslope index, and curvature. Our project is unique in that it delineates high resolution soil units using a process-based morphological approach rather than a traditional taxonomical method taken by conventional soil surveys. Hydropedological predictor models can be a valuable tool for informing forest and land management decisions, water quality planning, soil carbon accounting, and understanding subsurface hydrologic dynamics. They can also be readily calibrated for regions of differing geology, topography, and climate regimes.

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.

Spatial relationships between lead sources and children's blood lead levels in the urban center of Indianapolis (USA).

PubMed

Morrison, Deborah; Lin, Qing; Wiehe, Sarah; Liu, Gilbert; Rosenman, Marc; Fuller, Trevor; Wang, Jane; Filippelli, Gabriel

2013-04-01

Urban children remain disproportionately at risk of having higher blood lead levels than their suburban counterparts. The Westside Cooperative Organization (WESCO), located in Marion County, Indianapolis, Indiana, has a history of children with high blood lead levels as well as high soil lead (Pb) values. This study aims at determining the spatial relationship between soil Pb sources and children's blood lead levels. Soils have been identified as a source of chronic Pb exposure to children, but the spatial scale of the source-recipient relationship is not well characterized. Neighborhood-wide analysis of soil Pb distribution along with a furnace filter technique for sampling interior Pb accumulation for selected homes (n = 7) in the WESCO community was performed. Blood lead levels for children aged 0-5 years during the period 1999-2008 were collected. The study population's mean blood lead levels were higher than national averages across all ages, race, and gender. Non-Hispanic blacks and those individuals in the Wishard advantage program had the highest proportion of elevated blood lead levels. The results show that while there is not a direct relationship between soil Pb and children's blood lead levels at a spatial scale of ~100 m, resuspension of locally sourced soil is occurring based on the interior Pb accumulation. County-wide, the largest predictor of elevated blood lead levels is the location within the urban core. Variation in soil Pb and blood lead levels on the community level is high and not predicted by housing stock age or income. Race is a strong predictor for blood lead levels in the WESCO community.

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

Four millennia of woodland structure and dynamics at the Arctic treeline of eastern Canada.

PubMed

Auger, Sarah; Payette, Serge

2010-05-01

Paleoecological analysis using complementary indicators of vegetation and soil can provide spatially explicit information on ecological processes influencing trajectories of long-term ecosystem change. Here we document the structure and dynamics of an old-growth woodland before and after its inception 1000 years ago. We infer vegetation and soil characteristics from size and age distributions of black spruce (Picea mariana (Mill.) B.S.P.), soil properties, plant fossils, and paleosols. Radiocarbon ages of charcoal on the ground and in the soil indicate that the fire return interval was approximately 300 years between 2750 and 1000 cal. yr BP. No fire evidence was found before and after this period despite the presence of spruce since 4200 cal. yr BP. The size structures of living and dead spruce suggest that the woodland is in equilibrium with present climate in absence of fire. Tree establishment and mortality occurred regularly since the last fire event around 950 cal. yr BP. Both layering and occasional seeding have contributed to stabilize the spatial distribution of spruce over the past 1000 years. Since initial afforestation, soil development has been homogenized by the changing spatial distribution of spruce following each fire. We conclude that the history of the woodland is characterized by vegetation shifts associated with fire and soil disturbances and by millennial-scale maintenance of the woodland's structure despite changing climatic conditions.

Relationship between apparent soil electrical conductivity (ECa) and soil attributes at an experimental parcel under pasture in a region of Galicia, Spain

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.

Spatial distribution of soil radon as a tool to recognize active faulting on an active volcano: the example of Mt. Etna (Italy).

PubMed

Neri, Marco; Giammanco, Salvatore; Ferrera, Elisabetta; Patanè, Giuseppe; Zanon, Vittorio

2011-09-01

This study concerns measurements of radon and thoron emissions from soil carried out in 2004 on the eastern flank of Mt. Etna, in a zone characterized by the presence of numerous seismogenic and aseismic faults. The statistical treatment of the geochemical data allowed recognizing anomaly thresholds for both parameters and producing distribution maps that highlighted a significant spatial correlation between soil gas anomalies and tectonic lineaments. The seismic activity occurring in and around the study area during 2004 was analyzed, producing maps of hypocentral depth and released seismic energy. Both radon and thoron anomalies were located in areas affected by relatively deep (5-10 km depth) seismic activity, while less evident correlation was found between soil gas anomalies and the released seismic energy. This study confirms that mapping the distribution of radon and thoron in soil gas can reveal hidden faults buried by recent soil cover or faults that are not clearly visible at the surface. The correlation between soil gas data and earthquakes depth and intensity can give some hints on the source of gas and/or on fault dynamics. Copyright © 2011 Elsevier Ltd. All rights reserved.

DOSoReMI.hu: collection of countrywide DSM products partly according to GSM.net specifications, partly driven by specific user demands

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor; Illés, Gábor; Bakacsi, Zsófia; Szabó, József

2017-04-01

Due to former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. In traditional soil mapping the creation of a new map was troublesome and laborious. As a consequence, robust maps were elaborated and rather the demands were fitted to the available map products. Until recently spatial soil information demands have been serviced with the available datasets either in their actual form or after certain specific and often enforced, thematic and spatial inference. Considerable imperfection may occur in the accuracy and reliability of the map products, since there might be significant discrepancies between the available data and the expected information. The DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project was started intentionally for the renewal of the national soil spatial infrastructure in Hungary. During our activities we have significantly extended the potential, how soil information requirements could be satisfied. Soil property, soil type as well as functional soil maps were targeted. The set of the applied digital soil mapping techniques has been gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. Soil property maps have been compiled partly according to GSM.net specifications, partly by slightly or more strictly changing some of their predefined parameters (depth intervals, pixel size, property etc.) according to the specific demands on the final products. The elaborated primary maps were further processed, since even DOSoReMI.hu intended to take steps for the regionalization of higher level soil information (processes, functions, and services) involving crop models in the spatial modelling. The framework of DOSoReMI.hu also provides opportunity for the elaboration of goal specific soil maps, with the prescription of the parameters (thematic, resolution, accuracy, reliability etc.) characterizing the map product. As a result, unique digital soil map products (in a more general meaning) were elaborated regionalizing specific soil (related) features, which were never mapped before, even nationally with high ( 1 ha) spatial resolution. Based upon the collected experiences, the full range of GSM.net products were also targeted. The web publishing of the results was also elaborated creating a proper WMS environment. Our paper will present the resulted national maps furthermore some conclusions drawn from the experiences.] Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA) under Grant K105167 and AGRARKLÍMA.2 VKSZ_12-1-2013-0034.

Spatial variability of detrended soil plow layer penetrometer resistance transect in a sugarcane field

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.

The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil.

PubMed

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2015-11-11

Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters.

A soil sampling reference site: the challenge in defining reference material for sampling.

PubMed

de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Jacimovic, Radojko; Jeran, Zvonka; Sansone, Umberto; van der Perk, Marcel

2008-11-01

In the frame of the international SOILSAMP project, funded and coordinated by the Italian Environmental Protection Agency, an agricultural area was established as a reference site suitable for performing soil sampling inter-comparison exercises. The reference site was characterized for trace element content in soil, in terms of the spatial and temporal variability of their mass fraction. Considering that the behaviour of long-lived radionuclides in soil can be expected to be similar to that of some stable trace elements and that the distribution of these trace elements in soil can simulate the distribution of radionuclides, the reference site characterised in term of trace elements, can be also used to compare the soil sampling strategies developed for radionuclide investigations.

Biogenic nitric oxide emission from a spruce forest soil in mountainous terrain

NASA Astrophysics Data System (ADS)

Falge, Eva; Bargsten, Anika; Behrendt, Thomas; Meixner, Franz X.

2010-05-01

The process-based spatial simulation model SVAT-CN was used to estimate biogenic nitric oxide (NO) emission by soils of a Norway spruce forest (Weidenbrunnen) in the Fichtelgebirge, Germany. SVAT-CN core is a combination of a multiple-layer soil water balance model and a multi-layered canopy gas exchange model. The soil modules comprise a flexible hybrid between a layered bucket model and classical basic liquid flow theory. Further soil processes include: heat transport, distribution of transpiration demand proportionally to soil resistance, reduction of leaf physiological parameters with limiting soil moisture. Spruce forest soils usually are characterized by a thick organic layer (raw humus), with the topmost centimetres being the location where most of the biogenic NO is produced. Within individual spruce forest stands the understory might be composed of patches characterized by different species (e.g. Vaccinium myrtillus, Picea abies, Deschampsia caespitosa), and NO production potentials. The effect of soil physical and chemical parameters and understory types on NO emission from the organic layer was investigated in laboratory incubation and fumigation experiments on soils sampled below the various understory covers found at the Weidenbrunnen site. Results from the laboratory experiments were used to parameterize multi-factorial regression models of soil NO emission with respect to its response to soil temperature and moisture. Parameterization of the spatial model SVAT-CN includes horizontal heterogeneity of over- and understory PAI, understory species distribution, soil texture, bulk density, thickness of organic layer. Simulations are run for intensive observations periods of 2007 and 2008 of the EGER (ExchanGE processes in mountainous Regions) project, a late summer/fall and an early summer period, providing estimates for different understory types (young spruce, blueberry, grass, and moss/litter patches). Validation of the model is being carried out at point scale, by comparison with measured soil moisture and temperature data at 12 locations at the Weidenbrunnen site. In addition model output is compared to soil NO emission data from dynamic chambers. Understory type was found to have a strong influence on the magnitude of soil NO emissions, with emissions from blueberry and young spruce one order of magnitude larger than those from grass or moss/litter patches.

Biological soil crusts exhibit a dynamic response to seasonal rain and release from grazing with implications for soil stability

USGS Publications Warehouse

Jimenez, Aguilar A.; Huber-Sannwald, E.; Belnap, J.; Smart, D.R.; Arredondo, Moreno J.T.

2009-01-01

In Northern Mexico, long-term grazing has substantially degraded semiarid landscapes. In semiarid systems, ecological and hydrological processes are strongly coupled by patchy plant distribution and biological soil crust (BSC) cover in plant-free interspaces. In this study, we asked: 1) how responsive are BSC cover/composition to a drying/wetting cycle and two-year grazing removal, and 2) what are the implications for soil erosion? We characterized BSC morphotypes and their influence on soil stability under grazed/non-grazed conditions during a dry and wet season. Light- and dark-colored cyanobacteria were dominant at the plant tussock and community level. Cover changes in these two groups differed after a rainy season and in response to grazing removal. Lichens with continuous thalli were more vulnerable to grazing than those with semi-continuous/discontinuous thalli after the dry season. Microsites around tussocks facilitated BSC colonization compared to interspaces. Lichen and cyanobacteria morphotypes differentially enhanced resistance to soil erosion; consequently, surface soil stability depends on the spatial distribution of BSC morphotypes, suggesting soil stability may be as dynamic as changes in the type of BSC cover. Longer-term spatially detailed studies are necessary to elicit spatiotemporal dynamics of BSC communities and their functional role in biotically and abiotically variable environments. ?? 2009 Elsevier Ltd.

Predicting future spatial distribution of SOC across entire France

NASA Astrophysics Data System (ADS)

Meersmans, Jeroen; Van Rompaey, Anton; Quine, Tim; Martin, Manuel; Pagé, Christian; Arrouays, Dominique

2013-04-01

Soil organic carbon (SOC) is widely recognized as a key factor controlling soil quality and as a crucial and active component of the global C-cycle. Hence, there exists a growing interest in monitoring and modeling the spatial and temporal behavior of this pool. So far, a large attempt has been made to map SOC at national scales for current and/or past situations. Despite some coarse predictions, detailed spatial SOC predictions for the future are still lacking. In this study we aim to predict future spatial evolution of SOC driven by climate and land use change for France up to the year 2100. Therefore, we combined 1) an existing model, predicting SOC as a function of soil type, climate, land use and management (Meersmans et al 2012), with 2) eight different IPCC spatial explicit climate change predictions (conducted by CERFACS) and 3) Land use change scenario predictions. We created business-as-usual land use change scenarios by extrapolating observed trends and calibrating logistic regression models, incorporating a large set of physical and socio-economic factors, at the regional level in combination with a multi-objective land allocation (MOLA) procedure. The resultant detailed projections of future SOC evolution across all regions of France, allow us to identify regions that are most likely to be characterized by a significant gain or loss of SOC and the degree to which land use decisions/outcomes control the scale of loss and gain. Therefore, this methodology and resulting maps can be considered as powerful tools to aid decision making concerning appropriate soil management, in order to enlarge SOC storage possibilities and reduce soil related CO2 fluxes.

Spatio-temporal variability of evapotranspiration and energy fluxes over Heihe River Basin, China

NASA Astrophysics Data System (ADS)

Xu, Z.; Liu, S.; Xu, T.; Song, L.; Wang, X.

2017-12-01

Evapotranspiration (ET) is an essential component of energy and water budgets and is an important process in the soil-plant-atmosphere continuum (SPAC). Some important ecosystem parameters and processes, such as soil moisture, vegetation productivity, ecosystem energy, water, and nutrient budgets, are influenced by ET. The Heihe River Basin (HRB) is the second largest inland river, with an area of approximately 140,000 km2. A diverse land covers are distributing in HRB, which is characterized by distinct cold and arid landscapes, glaciers, frozen soil, alpine meadow, forest, irrigated crops, riparian ecosystem, and desert from upstream to downstream. Up to now, there was not a quantitative characterization of ET and energy flux over HRB; therefore, special attention should be paid on this term. A comprehensive hydrometeorological observatory was established since 2008 and completed in 2013. The network included 3 superstations and 18 ordinary stations, covering the main underlying surfaces in the basin, including alpine meadow, cropland, desert, wetland, frozen soil, Tamarix chinensis, and Populus euphratica, etc. Reliable data were obtained after the routine instrument maintenance and carefully data processing. ET and energy flux observations were made more than 5 years (2012-2017) using eddy covariance (EC) systems and large aperture scintillometers (LAS), and the seasonal and interannual variability of ET and its influencing factors were quantitatively analyzed with ET in main underlying surfaces of 400-580 mm in alpine meadow (upstream), 600-700 mm in cropland (midstream), 500-650 mm in riparian forest (downstream), 40 mm in desert (downstream). Meanwhile, the spatial distributions of ET were investigated based on site observations using machine learning techniques. Further, ET partitioning (evaporation (E) and transpiration (T)) was acquired through a method of underlying water use efficiency based on EC observations. The spatial variations of E and T were also given using DTD (Dual-Temperature Difference) model. In this study, a quantitative spatial-temporal variability of ET was characterized as well as the characterizations of E and T, which was significant to understand the water cycle over HRB and helpful to the subsequent researchers.

The Soil Microbiome Influences Grapevine-Associated Microbiota

PubMed Central

Zarraonaindia, Iratxe; Owens, Sarah M.; Weisenhorn, Pamela; West, Kristin; Hampton-Marcell, Jarrad; Lax, Simon; Bokulich, Nicholas A.; Mills, David A.; Martin, Gilles; Taghavi, Safiyh; van der Lelie, Daniel

2015-01-01

ABSTRACT Grapevine is a well-studied, economically relevant crop, whose associated bacteria could influence its organoleptic properties. In this study, the spatial and temporal dynamics of the bacterial communities associated with grapevine organs (leaves, flowers, grapes, and roots) and soils were characterized over two growing seasons to determine the influence of vine cultivar, edaphic parameters, vine developmental stage (dormancy, flowering, preharvest), and vineyard. Belowground bacterial communities differed significantly from those aboveground, and yet the communities associated with leaves, flowers, and grapes shared a greater proportion of taxa with soil communities than with each other, suggesting that soil may serve as a bacterial reservoir. A subset of soil microorganisms, including root colonizers significantly enriched in plant growth-promoting bacteria and related functional genes, were selected by the grapevine. In addition to plant selective pressure, the structure of soil and root microbiota was significantly influenced by soil pH and C:N ratio, and changes in leaf- and grape-associated microbiota were correlated with soil carbon and showed interannual variation even at small spatial scales. Diazotrophic bacteria, e.g., Rhizobiaceae and Bradyrhizobium spp., were significantly more abundant in soil samples and root samples of specific vineyards. Vine-associated microbial assemblages were influenced by myriad factors that shape their composition and structure, but the majority of organ-associated taxa originated in the soil, and their distribution reflected the influence of highly localized biogeographic factors and vineyard management. PMID:25805735

The soil microbiome influences grapevine-associated microbiota

DOE PAGES

Zarraonaindia, Iratxe; Owens, Sarah M.; Weisenhorn, Pamela; ...

2015-03-24

Grapevine is a well-studied, economically relevant crop, whose associated bacteria could influence its organoleptic properties. In this study, the spatial and temporal dynamics of the bacterial communities associated with grapevine organs (leaves, flowers, grapes, and roots) and soils were characterized over two growing seasons to determine the influence of vine cultivar, edaphic parameters, vine developmental stage (dormancy, flowering, preharvest), and vineyard. Belowground bacterial communities differed significantly from those aboveground, and yet the communities associated with leaves, flowers, and grapes shared a greater proportion of taxa with soil communities than with each other, suggesting that soil may serve as a bacterialmore » reservoir. A subset of soil microorganisms, including root colonizers significantly enriched in plant growth-promoting bacteria and related functional genes, were selected by the grapevine. In addition to plant selective pressure, the structure of soil and root microbiota was significantly influenced by soil pH and C:N ratio, and changes in leaf- and grape-associated microbiota were correlated with soil carbon and showed interannual variation even at small spatial scales. Diazotrophic bacteria, e.g., Rhizobiaceae and Bradyrhizobium spp., were significantly more abundant in soil samples and root samples of specific vineyards. Vine-associated microbial assemblages were influenced by myriad factors that shape their composition and structure, but the majority of organ-associated taxa originated in the soil, and their distribution reflected the influence of highly localized biogeographic factors and vineyard management.« less

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

Space-time quantitative source apportionment of soil heavy metal concentration increments.

PubMed

Yang, Yong; Christakos, George; Guo, Mingwu; Xiao, Lu; Huang, Wei

2017-04-01

Assessing the space-time trends and detecting the sources of heavy metal accumulation in soils have important consequences in the prevention and treatment of soil heavy metal pollution. In this study, we collected soil samples in the eastern part of the Qingshan district, Wuhan city, Hubei Province, China, during the period 2010-2014. The Cd, Cu, Pb and Zn concentrations in soils exhibited a significant accumulation during 2010-2014. The spatiotemporal Kriging technique, based on a quantitative characterization of soil heavy metal concentration variations in terms of non-separable variogram models, was employed to estimate the spatiotemporal soil heavy metal distribution in the study region. Our findings showed that the Cd, Cu, and Zn concentrations have an obvious incremental tendency from the southwestern to the central part of the study region. However, the Pb concentrations exhibited an obvious tendency from the northern part to the central part of the region. Then, spatial overlay analysis was used to obtain absolute and relative concentration increments of adjacent 1- or 5-year periods during 2010-2014. The spatial distribution of soil heavy metal concentration increments showed that the larger increments occurred in the center of the study region. Lastly, the principal component analysis combined with the multiple linear regression method were employed to quantify the source apportionment of the soil heavy metal concentration increments in the region. Our results led to the conclusion that the sources of soil heavy metal concentration increments should be ascribed to industry, agriculture and traffic. In particular, 82.5% of soil heavy metal concentration increment during 2010-2014 was ascribed to industrial/agricultural activities sources. Using STK and SOA to obtain the spatial distribution of heavy metal concentration increments in soils. Using PCA-MLR to quantify the source apportionment of soil heavy metal concentration increments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence of management history and landscape variables on soil organic carbon and soil redistribution

USGS Publications Warehouse

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.

Mapping regional soil water erosion risk in the Brittany-Loire basin for water management agency

NASA Astrophysics Data System (ADS)

Degan, Francesca; Cerdan, Olivier; Salvador-Blanes, Sébastien; Gautier, Jean-Noël

2014-05-01

Soil water erosion is one of the main degradation processes that affect soils through the removal of soil particles from the surface. The impacts for environment and agricultural areas are diverse, such as water pollution, crop yield depression, organic matter loss and reduction in water storage capacity. There is therefore a strong need to produce maps at the regional scale to help environmental policy makers and soil and water management bodies to mitigate the effect of water and soil pollution. Our approach aims to model and map soil erosion risk at regional scale (155 000 km²) and high spatial resolution (50 m) in the Brittany - Loire basin. The factors responsible for soil erosion are different according to the spatial and time scales considered. The regional scale entails challenges about homogeneous data sets availability, spatial resolution of results, various erosion processes and agricultural practices. We chose to improve the MESALES model (Le Bissonnais et al., 2002) to map soil erosion risk, because it was developed specifically for water erosion in agricultural fields in temperate areas. The MESALES model consists in a decision tree which gives for each combination of factors the corresponding class of soil erosion risk. Four factors that determine soil erosion risk are considered: soils, land cover, climate and topography. The first main improvement of the model consists in using newly available datasets that are more accurate than the initial ones. The datasets used cover all the study area homogeneously. Soil dataset has a 1/1 000 000 scale and attributes such as texture, soil type, rock fragment and parent material are used. The climate dataset has a spatial resolution of 8 km and a temporal resolution of mm/day for 12 years. Elevation dataset has a spatial resolution of 50 m. Three different land cover datasets are used where the finest spatial resolution is 50 m over three years. Using these datasets, four erosion factors are characterized and quantified: the soil factors (soil sealing, erodibility and runoff), the rate of land cover over three years for each season and for 77 land use classes, the topographic factor (slope and drainage area) and the climate hazard (seasonal amount and rainfall erosivity). These modifications of the original MESALES model allow to better represent erosion risk for arable and bare land. We validated model results by stakeholder consultations and meetings over all the study area. The model has finally been modified taking into account validation results. Results are provided with a spatial resolution of 1 km, and then integrated into 2121 catchments. An erosion risk map for each season and an annual erosion risk map are produced. These new maps allow to organize in hierarchy 2121 catchments into three erosion risk classes. In the annual erosion risk map, 347 catchments have the highest erosion risk, which corresponds to 16 % of total Brittany-Loire basin area. Water management agency now uses these maps to identify priority areas and to plan specific preservation practices.

Statistical analysis of content of Cs-137 in soils in Bansko-Razlog region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kobilarov, R. G., E-mail: rkobi@tu-sofia.bg

Statistical analysis of the data set consisting of the activity concentrations of {sup 137}Cs in soils in Bansko–Razlog region is carried out in order to establish the dependence of the deposition and the migration of {sup 137}Cs on the soil type. The descriptive statistics and the test of normality show that the data set have not normal distribution. Positively skewed distribution and possible outlying values of the activity of {sup 137}Cs in soils were observed. After reduction of the effects of outliers, the data set is divided into two parts, depending on the soil type. Test of normality of themore » two new data sets shows that they have a normal distribution. Ordinary kriging technique is used to characterize the spatial distribution of the activity of {sup 137}Cs over an area covering 40 km{sup 2} (whole Razlog valley). The result (a map of the spatial distribution of the activity concentration of {sup 137}Cs) can be used as a reference point for future studies on the assessment of radiological risk to the population and the erosion of soils in the study area.« less

Towards an integrated soil moisture drought monitor for East Africa

USDA-ARS?s Scientific Manuscript database

Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived mo...

Flood effects on efflux and net production of nitrous oxide in river floodplain soils

NASA Astrophysics Data System (ADS)

Riaz, Muhammad; Bruderer, Christian; Niklaus, Pascal A.; Luster, Jörg

2016-04-01

Floodplain soils are often rich in nutrients and exhibit high spatial heterogeneity in terms of geomorphology, soil environmental conditions and substrate availability for processes involved in carbon and nutrient cycling. In addition, fluctuating water tables lead to temporally changing redox conditions. In such systems, there are ideal conditions for the occurrence of hot spots and moments of nitrous oxide emissions, a potent greenhouse gas. The factors that govern the spatial heterogeneity and dynamics of N2O formation in floodplain soils and the surface efflux of this gas are not fully understood. A particular issue is the contribution of N2O formation in the subsoil to surface efflux. We studied this question in the floodplain of a restored section of the Thur river (NE Switzerland) which is characterized by a flashy flow regime. As a consequence, the floodplain soils are unsaturated most of the time. We showed earlier that saturation during flood pulses leads to short phases of generally anoxic conditions followed by a drying phase with anoxic conditions within aggregates and oxic conditions in larger soil pores. The latter conditions are conducive for spatially closely-coupled nitrification-denitrification and related hot moments of nitrous oxide formation. In a floodplain zone characterized by about one meter of young, sandy sediments, that are mostly covered by the tall grass Phalaris arundinacea, we measured at several time points before and after a small flood event N2O surface efflux with the closed-chamber method, and assessed N2O concentrations in the soil air at four different depths using gas-permeable tubings. In addition, we calculated the N2O diffusivity in the soil from Radon diffusivity. The latter was estimated in-situ from the recovery of Radon concentration in the gas-permeable tubings after purging with ambient air. All these data were then used to calculate net N2O production rates at different soil depths with the gradient method. In addition, temperature, volumetric water content, as well as ammonium, nitrate and dissolved organic carbon in the soil solution were monitored at different depths in the observation plots. During not flood-affected conditions we observed weak diffusive gradients between subsoil and top soil, and net N2O production was maximum in the top soil. During the drying phase after a flood, diffusive gradients between subsoil and topsoil were more pronounced, and net N2O production in the subsoil increased. At all conditions, N2O efflux was more strongly correlated with N2O concentrations in the subsoil than those in the top soil. The complex interactions between soil moisture on one hand, and C and N substrate limitation on the other hand in determining N2O production at different soil depths will be discussed. Finally, the results will be put into the context of our earlier and ongoing studies that aim at elucidating the governing factors of spatial heterogeneity and dynamics of N2O emissions in floodplain soils.

Spatial variability of heavy metals in the coastal soils under long-term reclamation

NASA Astrophysics Data System (ADS)

Wang, Lin; Coles, Neil A.; Wu, Chunfa; Wu, Jiaping

2014-12-01

The coastal plain of Cixi City, China, has experienced over 1000 years of reclamation. With the rapid development of agriculture and industry after reclamation, successive inputs into agricultural soils have drastically modified the soil environment. To determine the spatial distribution of heavy metals and to evaluate the influence of anthropogenic activities, a total of 329 top soil samples were taken along a transect on the coastal plain. The samples collected across 11 sea dikes, were selected by a nested sampling methodology. Total Cu, Fe, Mn, Ni, Pb, and Zn concentrations, as well as their diethylenetriamine penta-acetic acid (DTPA) extractable (available) concentrations were determined. Results indicated that except for Zn concentrations, there was neither heavy metals pollution nor mineral deficiency in the soils. Heavy metals exhibited considerable spatial variability, obvious spatial dependence, and close relationships on the reclaimed land. For most metals, the reclamation history was the main influencing factor. Metals concentrations generally showed discontinuities around the position of sea dikes, and the longer reclamation histories tended to have higher metals concentrations than the recently reclaimed sectors. As for Cu and Zn total concentrations, stochastic factors, like industrial waste discharge, fertilization and pesticide application, probably led to the high nugget effect and altered this relationship. The 6th and 10th zones generally had the highest total metals concentrations, due to the concentration of household appliance manufacturers in these reclaimed areas. The first two zones were characterized by high available metals concentrations, probably due to the alternant flooding and emergence, low pH values and high organic matter contents in these paddy field soils. From the 3rd to 7th zones with the same land use history and soil type, metals concentrations, especially available concentrations, showed homogeneity. The nested sampling method adopted demonstrated that the 500-m interval was enough to capture the spatial variation of the metals. These results were useful in evaluating the variation in the environment quality of the soils under long-term reclamation and to formulate plans for future reclamation projects.

Improving the spatial representation of soil properties and hydrology using topographically derived watershed model initialization processes

NASA Astrophysics Data System (ADS)

Easton, Z. M.; Fuka, D.; Collick, A.; Kleinman, P. J. A.; Auerbach, D.; Sommerlot, A.; Wagena, M. B.

2015-12-01

Topography exerts critical controls on many hydrologic, geomorphologic, and environmental biophysical processes. Unfortunately many watershed modeling systems use topography only to define basin boundaries and stream channels and do not explicitly account for the topographic controls on processes such as soil genesis, soil moisture distributions and hydrological response. We develop and demonstrate a method that uses topography to spatially adjust soil morphological and soil hydrological attributes [soil texture, depth to the C-horizon, saturated conductivity, bulk density, porosity, and the field capacities at 33kpa (~ field capacity) and 1500kpa (~ wilting point) tensions]. In order to test the performance of the method the topographical adjusted soils and standard SSURGO soil (available at 1:20,000 scale) were overlaid on soil pedon pit data in the Grasslands Soil and Water Research Lab in Resiel, TX. The topographically adjusted soils exhibited significant correlations with measurements from the soil pits, while the SSURGO soil data showed almost no correlation to measured data. We also applied the method to the Grasslands Soil and Water Research watershed using the Soil and Water Assessment Tool (SWAT) model to 15 separate fields as a proxy to propagate changes in soil properties into field scale hydrological responses. Results of this test showed that the topographically adjusted soils resulted better model predictions of field runoff in 50% of the field, with the SSURGO soils preforming better in the remainder of the fields. However, the topographically adjusted soils generally predicted baseflow response more accurately, reflecting the influence of these soil properties on non-storm responses. These results indicate that adjusting soil properties based on topography can result in more accurate soil characterization and, in some cases improve model performance.

Farm scale application of EMI and FDR sensors to measuring and mapping soil water content

NASA Astrophysics Data System (ADS)

Rallo, Giovanni; Provenzano, Giuseppe

2017-04-01

Soil water content (SWC) controls most water exchange processes within and between the soil-plants-atmosphere continuum and can therefore be considered as a practical variable for irrigation farmer choices. A better knowledge of spatial SWC patterns could improve farmer's awareness about critical crop water status conditions and enhance their capacity to characterize their behavior at the field or farm scale. However, accurate soil moisture measurement across spatial and temporal scales is still a challenging task and, specifically at intermediate spatial (0.1-100 ha) and temporal (minutes to days) scales, a data gap remains that limits our understanding over reliability of the SWC spatial measurements and its practical applicability in irrigation scheduling. In this work we compare the integrated EM38 (Geonics Ltd. Canada) response, collected at different sensor positions above ground to that obtained by integrating the depth profile of volumetric SWC measured with Diviner 2000 (Sentek) in conjunction with the depth response function of the EM38 when operated in both horizontal and vertical dipole configurations. On a 1.0-ha Olive grove site in Sicliy (Italy), 200 data points were collected before and after irrigation or precipitation events following a systematic sampling grid with focused measurements around the tree. Inside two different zone of the field, characterized from different soil physical properties, two Diviner 2000 access tube (1.2 m) were installed and used for the EM38 calibration. After calibration, the work aimed to propose the combined use of the FDR and EMI sensors to measuring and mapping root zone soil water content. We found strong correlations (R2 = 0.66) between Diviner 2000 SWC averaged to a depth of 1.2 m and ECa from an EM38 held in the vertical mode above the soil surface. The site-specific relationship between FDR-based SWC and ECa was linear for the purposes of estimating SWC over the explored range of ECa monitored at field levels. Volumetric SWC changes in the root zone were observed by differencing the maps, where differences in the observed ECa are primarily the result of changes in soil water status. As with the data showed in the research, more structured patterns occur after wetting event, indicating the presence of subsurface flow or root water uptake paths. A vision for the future at hydrological watershed scale is to combine EMI measurements with FDR-based sensor networks, the last with the scope to constrain calibration of the EMI measurements.

Application of active distribute temperature sensing and fiber optic as sensors to determinate the unsaturated hydraulic conductivity curve

NASA Astrophysics Data System (ADS)

Zubelzu, Sergio; Rodriguez-Sinobas, Leonor; Sobrino, Fernando

2017-04-01

The development of methodologies for the characterization of soil water content through the use of distribute temperature sensing and fiber optic cable has allowed for modelling with high temporal and spatial accuracy water movement in soils. One of the advantage of using fiber optic as a sensor, compared with the traditional point water probes, is the possibility to measure the variable continuously along the cable every 0.125 m (up to a cable length of 1500) and every second. Traditionally, applications based on fiber optic as a soil water sensor apply the active heated fiber optic technique AHFO to follow the evolution soil water content during and after irrigation events or for hydrologic characterization. However, this paper accomplishes an original experience by using AHFO as a sensor to characterize the soil hydraulic conductivity curve in subsaturated conditions. The non lineal nature between the hidraulic conductivity curve and soil water, showing high slope in the range close to saturation ) favors the AHFO a most suitable sensor due to its ability to measure the variable at small time and length intervals. Thus, it is possible to obtain accurate and a large number of data to be used to estimate the hydraulic conductivity curve from de water flow general equation by numerical methods. Results are promising and showed the feasibility of this technique to estimate the hydraulic conductivity curve for subsaturated soils .

Quantifying Spatial Variability of Selected Soil Trace Elements and Their Scaling Relationships Using Multifractal Techniques

PubMed Central

Zhang, Fasheng; Yin, Guanghua; Wang, Zhenying; McLaughlin, Neil; Geng, Xiaoyuan; Liu, Zuoxin

2013-01-01

Multifractal techniques were utilized to quantify the spatial variability of selected soil trace elements and their scaling relationships in a 10.24-ha agricultural field in northeast China. 1024 soil samples were collected from the field and available Fe, Mn, Cu and Zn were measured in each sample. Descriptive results showed that Mn deficiencies were widespread throughout the field while Fe and Zn deficiencies tended to occur in patches. By estimating single multifractal spectra, we found that available Fe, Cu and Zn in the study soils exhibited high spatial variability and the existence of anomalies ([α(q)max−α(q)min]≥0.54), whereas available Mn had a relatively uniform distribution ([α(q)max−α(q)min]≈0.10). The joint multifractal spectra revealed that the strong positive relationships (r≥0.86, P<0.001) among available Fe, Cu and Zn were all valid across a wider range of scales and over the full range of data values, whereas available Mn was weakly related to available Fe and Zn (r≥0.18, P<0.01) but not related to available Cu (r = −0.03, P = 0.40). These results show that the variability and singularities of selected soil trace elements as well as their scaling relationships can be characterized by single and joint multifractal parameters. The findings presented in this study could be extended to predict selected soil trace elements at larger regional scales with the aid of geographic information systems. PMID:23874944

High resolution change estimation of soil moisture and its assimilation into a land surface model

NASA Astrophysics Data System (ADS)

Narayan, Ujjwal

Near surface soil moisture plays an important role in hydrological processes including infiltration, evapotranspiration and runoff. These processes depend non-linearly on soil moisture and hence sub-pixel scale soil moisture variability characterization is important for accurate modeling of water and energy fluxes at the pixel scale. Microwave remote sensing has evolved as an attractive technique for global monitoring of near surface soil moisture. A radiative transfer model has been tested and validated for soil moisture retrieval from passive microwave remote sensing data under a full range of vegetation water content conditions. It was demonstrated that soil moisture retrieval errors of approximately 0.04 g/g gravimetric soil moisture are attainable with vegetation water content as high as 5 kg/m2. Recognizing the limitation of low spatial resolution associated with passive sensors, an algorithm that uses low resolution passive microwave (radiometer) and high resolution active microwave (radar) data to estimate soil moisture change at the spatial resolution of radar operation has been developed and applied to coincident Passive and Active L and S band (PALS) and Airborne Synthetic Aperture Radar (AIRSAR) datasets acquired during the Soil Moisture Experiments in 2002 (SMEX02) campaign with root mean square error of 10% and a 4 times enhancement in spatial resolution. The change estimation algorithm has also been used to estimate soil moisture change at 5 km resolution using AMSR-E soil moisture product (50 km) in conjunction with the TRMM-PR data (5 km) for a 3 month period demonstrating the possibility of high resolution soil moisture change estimation using satellite based data. Soil moisture change is closely related to precipitation and soil hydraulic properties. A simple assimilation framework has been implemented to investigate whether assimilation of surface layer soil moisture change observations into a hydrologic model will potentially improve it performance. Results indicate an improvement in model prediction of near surface and deep layer soil moisture content when the update is performed to the model state as compared to free model runs. It is also seen that soil moisture change assimilation is able to mitigate the effect of erroneous precipitation input data.

Unlocking the Physiochemical Controls on Organic Carbon Dynamics from the Soil Pore- to Core-Scale

NASA Astrophysics Data System (ADS)

Smith, A. P.; Tfaily, M. M.; Bond-Lamberty, B. P.; Todd-Brown, K. E.; Bailey, V. L.

2015-12-01

The physical organization of soil includes pore networks of varying size and connectivity. These networks control microbial access to soil organic carbon (C) by spatially separating microorganisms and C by both distance and size exclusion. The extent to which this spatially isolated C is vulnerable to microbial transformation under hydrologically dynamic conditions is unknown, and limits our ability to predict the source and sink capacity of soils. We investigated the effects of shifting hydrologic connectivity and soil structure on greenhouse gas C emissions from surface soils collected from the Disney Wilderness Preserve (Florida, USA). We subjected intact soil cores and re-packed homogenized soil cores to simulated groundwater rise or precipitation, monitoring their CO2 and CH4 emissions over 24 hours. Soil pore water was then extracted from each core using different suctions to sample water retained by pore throats of different sizes and then characterized by Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry. Greater respiration rates were observed from homogenized cores compared to intact cores, and from soils wet from below, in which the wetting front is driven by capillary forces, filling fine pores first. This suggests that C located in fine pores may turn over via diffusion processes that lead to the colocation of this C with other resources and microorganisms. Both the complexity and concentration of soluble-C increased with decreasing pore size domains. Pore water extracted from homogenized cores had greater C concentrations than from intact cores, with the greatest concentrations in pore waters sampled from very fine pores, highlighting the importance of soil structure in physically protecting C. These results suggest that the spatial separation of decomposers from C is a key mechanism stabilizing C in these soils. Further research is ongoing to accurately represent this protection mechanism, and the conditions under which it breaks down, in new and improved Earth system models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zarraonaindia, Iratxe; Owens, Sarah M.; Weisenhorn, Pamela

Grapevine is a well-studied, economically relevant crop, whose associated bacteria could influence its organoleptic properties. In this study, the spatial and temporal dynamics of the bacterial communities associated with grapevine organs (leaves, flowers, grapes, and roots) and soils were characterized over two growing seasons to determine the influence of vine cultivar, edaphic parameters, vine developmental stage (dormancy, flowering, preharvest), and vineyard. Belowground bacterial communities differed significantly from those aboveground, and yet the communities associated with leaves, flowers, and grapes shared a greater proportion of taxa with soil communities than with each other, suggesting that soil may serve as a bacterialmore » reservoir. A subset of soil microorganisms, including root colonizers significantly enriched in plant growth-promoting bacteria and related functional genes, were selected by the grapevine. In addition to plant selective pressure, the structure of soil and root microbiota was significantly influenced by soil pH and C:N ratio, and changes in leaf- and grape-associated microbiota were correlated with soil carbon and showed interannual variation even at small spatial scales. Diazotrophic bacteria, e.g., Rhizobiaceae and Bradyrhizobium spp., were significantly more abundant in soil samples and root samples of specific vineyards. Vine-associated microbial assemblages were influenced by myriad factors that shape their composition and structure, but the majority of organ-associated taxa originated in the soil, and their distribution reflected the influence of highly localized biogeographic factors and vineyard management.« less

Relationship between apparent soil electrical conductivity (ECa) and soil attributes at an experimental parcel under pasture in a region of Galicia, Spain.

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.

Mercury in fruiting bodies of dark honey fungus (Armillaria solidipes) and beneath substratum soils collected from spatially distant areas.

PubMed

Falandysz, Jerzy; Mazur, Aneta; Kojta, Anna K; Jarzyńska, Grażyna; Drewnowska, Małgorzata; Dryżałowska, Anna; Nnorom, Innocent C

2013-03-15

This paper reports data on bioconcentration potential and baseline mercury concentrations of fruiting bodies of dark honey fungus (Armillaria solidipes) Peck and soil substrate layer (0-10 cm) from 12 spatially distant sites across Poland. Mercury content of caps, stipes and soil samples were determined using validated analytical procedure including cold-vapor atomic absorption spectroscopy after thermal decomposition of the sample matrix and further amalgamation and desorption of mercury from gold wool. Mean mercury concentrations ranged from 20 ± 8 to 300 ± 70 ng g(-1) dry weight (dw) in caps, from 20 ± 6 to 160 ± 40 ng g(-1) dw in stipes, and in underlying soil were from 20 ± 2 to 100 ± 130 ng g(-1) dw. The results showed that stipes mercury concentrations were 1.1- to 1.7-fold lower than those of caps. All caps and the majority of stipes were characterized by bioconcentration factor values > 1, indicating that dark honey fungus can be characterized as a moderate mercury accumulator. Occasional or relatively frequent eating of meals including caps of dark honey fungus is considered safe in view of the low total mercury content, and the mercury intake rates are below the current reference dose and provisionally tolerable weekly intake limits for this hazardous metal. © 2012 Society of Chemical Industry.

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra - coupling field observations with remote sensing data

NASA Astrophysics Data System (ADS)

Mikola, Juha; Virtanen, Tarmo; Linkosalmi, Maiju; Vähä, Emmi; Nyman, Johanna; Postanogova, Olga; Räsänen, Aleksi; Kotze, D. Johan; Laurila, Tuomas; Juutinen, Sari; Kondratyev, Vladimir; Aurela, Mika

2018-05-01

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm-3 in bare soil and lichen tundra and 89 g dm-3 in other LCTs. Total moss biomass varied from 0 to 820 g m-2, total vascular shoot mass from 7 to 112 g m-2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 °C in bare soil and lichen tundra, and varied from 5 to 9 °C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14-34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6-15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.

3D imaging of soil apparent electrical conductivity from VERIS data using a 1D spatially constrained inversion algorithm

NASA Astrophysics Data System (ADS)

Jesús Moral García, Francisco; Rebollo Castillo, Francisco Javier; Monteiro Santos, Fernando

2016-04-01

Maps of apparent electrical conductivity of the soil are commonly used in precision agriculture to indirectly characterize some important properties like salinity, water, and clay content. Traditionally, these studies are made through an empirical relationship between apparent electrical conductivity and properties measured in soil samples collected at a few locations in the experimental area and at a few selected depths. Recently, some authors have used not the apparent conductivity values but the soil bulk conductivity (in 2D or 3D) calculated from measured apparent electrical conductivity through the application of an inversion method. All the published works used data collected with electromagnetic (EM) instruments. We present a new software to invert the apparent electrical conductivity data collected with VERIS 3100 and 3150 (or the more recent version with three pairs of electrodes) using the 1D spatially constrained inversion method (1D SCI). The software allows the calculation of the distribution of the bulk electrical conductivity in the survey area till a depth of 1 m. The algorithm is applied to experimental data and correlations with clay and water content have been established using soil samples collected at some boreholes. Keywords: Digital soil mapping; inversion modelling; VERIS; soil apparent electrical conductivity.

Estimating Surface Soil Moisture in a Mixed-Landscape using SMAP and MODIS/VIIRS Data

NASA Astrophysics Data System (ADS)

Tang, J.; Di, L.; Xiao, J.

2017-12-01

Soil moisture, a critical parameter of earth ecosystem linking land surface and atmosphere, has been widely applied in many application (Di, 1991; Njoku et al. 2003; Western 2002; Zhao et al. 2014; McColl et al. 2017) from regional to continental or even global scale. The advent of satellite-based remote sensing, particular in the last two decades, has proven successful for mapping the surface soil moisture (SSM) from space (Petropoulos et al. 2015; Kim et al. 2015; Molero et al. 2016). The current soil moisture products, however, is not able to fully characterize the spatial and temporal variability of soil moisture at mixed landscape types (Albergel et al. 2013; Zeng et al. 2015). In this research, we derived the SSM at 1-km spatial resolution by using sensor observation and high-level products from SMAP and MODIS/VIIRS as well as metrorological, landcover, and soil data. Specifically, we proposed a practicable method to produce the originally planned SMAP L3_SM_A with comparable quality by downscaling the SMAP L3_SM_P product through a proved method, the geographically weighted regression method at mixed landscape in southern New Hampshire. This estimated SSM was validated using the Soil Climate Analysis Network (SCAN) from Natural Resources Conservation Service (NRCS) of United States Department of Agriculture (USDA).

Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and Precipitation Observations

NASA Astrophysics Data System (ADS)

A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Njoku, E. G.; Colliander, A.

2016-12-01

We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE and precipitation measurements from GPCP to delineate and characterize drought and water supply pattern and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply and have important implications for water resource management. We use these data to investigate the supply changes from different water components in relation to satellite based vegetation productivity metrics from MODIS, before, during and following the major drought events observed in the continental US during the past 13 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, and vegetation productivity. In Texas and surrounding semi-arid areas, we find that the spatial pattern of the vegetation-moisture relation follows the gradient in mean annual precipitation. In Texas, GRACE TWS and surface SM show strong coupling and similar characteristic time scale in relatively normal years, while during the 2011 onward hydrological drought, GRACE TWS manifests a longer time scale than that of surface SM, implying stronger drought persistence in deeper water storage. In the Missouri watershed, we find a spatially varying vegetation-moisture relationship where in the drier northwestern portion of the basin, the inter-annual variability in summer vegetation productivity is closely associated with changes in carry-on GRACE TWS from spring, whereas in the moist southeastern portion of the basin, summer precipitation is the dominant controlling factor on vegetation growth.

Extensive radioactive characterization of a phosphogypsum stack in SW Spain: 226Ra, 238U, 210Po concentrations and 222Rn exhalation rate.

PubMed

Abril, José-María; García-Tenorio, Rafael; Manjón, Guillermo

2009-05-30

Phosphogypsum (PG) is a by-product of the phosphate fertilizer industries that contains relatively high concentrations of uranium series radionuclides. The US-EPA regulates the agriculture use of PG, attending to its (226)Ra content and to the (222)Rn exhalation rate from inactive stacks. Measurements of (222)Rn exhalation rates in PG stacks typically show a large and still poorly understood spatial and temporal variability, and the published data are scarce. This work studies an inactive PG stack in SW Spain of about 0.5 km(2) from where PG can be extracted for agriculture uses, and an agriculture soil 75 km apart, being representative of the farms to be amended with PG. Activity concentrations of (226)Ra, (238)U and (210)Po have been measured in 30 PG samples (0-90 cm horizon) allowing for the construction of maps with spatial distributions in the PG stack and for the characterization of the associated PG inputs to agriculture soils. Averaged (226)Ra concentrations for the stack were 730+/-60 Bq kg(-1) (d.w.), over the US-EPA limit of 370 Bq kg(-1). (222)Rn exhalation rate has been measured by the charcoal canister method in 49 sampling points with 3 canisters per sampling point. Values in PG stack were under the US-EPA limit of 2600 Bq m(-2)h(-1), but they were one order of magnitude higher than those found in the agriculture soil. Variability in radon emissions has been studied at different spatial scales. Radon exhalation rates were correlated with (226)Ra concentrations and daily potential evapotranspiration (ETo). They increased with ETo in agriculture soils, but showed an opposite behaviour in the PG stack.

Characterizing regional soil mineral composition using spectroscopyand geostatistics

USGS Publications Warehouse

Mulder, V.L.; de Bruin, S.; Weyermann, J.; Kokaly, Raymond F.; Schaepman, M.E.

2013-01-01

This work aims at improving the mapping of major mineral variability at regional scale using scale-dependent spatial variability observed in remote sensing data. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and statistical methods were combined with laboratory-based mineral characterization of field samples to create maps of the distributions of clay, mica and carbonate minerals and their abundances. The Material Identification and Characterization Algorithm (MICA) was used to identify the spectrally-dominant minerals in field samples; these results were combined with ASTER data using multinomial logistic regression to map mineral distributions. X-ray diffraction (XRD)was used to quantify mineral composition in field samples. XRD results were combined with ASTER data using multiple linear regression to map mineral abundances. We testedwhether smoothing of the ASTER data to match the scale of variability of the target sample would improve model correlations. Smoothing was donewith Fixed Rank Kriging (FRK) to represent the mediumand long-range spatial variability in the ASTER data. Stronger correlations resulted using the smoothed data compared to results obtained with the original data. Highest model accuracies came from using both medium and long-range scaled ASTER data as input to the statistical models. High correlation coefficients were obtained for the abundances of calcite and mica (R2 = 0.71 and 0.70, respectively). Moderately-high correlation coefficients were found for smectite and kaolinite (R2 = 0.57 and 0.45, respectively). Maps of mineral distributions, obtained by relating ASTER data to MICA analysis of field samples, were found to characterize major soil mineral variability (overall accuracies for mica, smectite and kaolinite were 76%, 89% and 86% respectively). The results of this study suggest that the distributions of minerals and their abundances derived using FRK-smoothed ASTER data more closely match the spatial variability of soil and environmental properties at regional scale.

Carbon availability structures microbial community composition and function in soil aggregate fractions

NASA Astrophysics Data System (ADS)

Hofmockel, K. S.; Bach, E.; Williams, R.; Howe, A.

2014-12-01

Identifying the microbial metabolic pathways that most strongly influence ecosystem carbon (C) cycling requires a deeper understanding of the availability and accessibility of microbial substrates. A first step towards this goal is characterizing the relationships between microbial community function and soil C chemistry in a field context. For this perspective, soil aggregate fractions can be used as model systems that scale between microbe-substrate interactions and ecosystem C cycling and storage. The present study addresses how physicochemical variation among soil aggregate fractions influences the composition and functional potential of C cycling microbial communities. We report variation across soil aggregates using plot scale biological replicates from biofuel agroecosystems (fertilized, reconstructed, tallgrass prairie). Our results suggest that C and nitrogen (N) chemistry significantly differ among aggregate fractions. This leads to variation in microbial community composition, which was better characterized among aggregates than by using the whole soil. In fact by considering soil aggregation, we were able to characterize almost 2000 more taxa than whole soil alone, resulting in 65% greater community richness. Availability of C and N strongly influenced the composition of microbial communities among soil aggregate fractions. The normalized abundance of microbial functional guilds among aggregate fractions correlated with C and N chemistry, as did functional potential, measured by extracellular enzyme activity. Metagenomic results suggest that soil aggregate fractions select for functionally distinct microbial communities, which may significantly influence decomposition and soil C storage. Our study provides support for the premise that integration of soil aggregate chemistry, especially microaggregates that have greater microbial richness and occur at spatial scales relevant to microbial community functioning, may be necessary to understand the role of microbial communities on terrestrial C and N cycling.

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.

Soil N and C Geography of the Salmon River Watershed and the Oregon Coast

NASA Astrophysics Data System (ADS)

Kern, J. S.; Compton, J. E.; Johnson, M. G.

2003-12-01

Diverse soil and geology influence the rich terrestrial and aquatic biota of the Oregon Coast. We characterized the spatial patterns of soil organic C (SOC) and N by assembling county and forest soil surveys combined with new fieldwork, and analyses from sampled soils. The headlands have maximum SOC and N where wind deposited volcanic soil is coupled with a cool, moist climate. The SOC and N decreases inland in similar soils that have a less marine climate influence. The underlying geology (basalt or sedimentary rock) had no affect in SOC and N. The remainder of the watershed has less SOC and N depending on rock content and soil depth which were affected by lithology as well as microclimate, and tree stand history. Extrapolating SOC and N trends to the region provides information for an area with no significant N deposition from air pollution.

The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil

PubMed Central

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2015-01-01

Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters. PMID:26569243

Geostatistical conditional simulation for the assessment of contaminated land by abandoned heavy metal mining.

PubMed

Ersoy, Adem; Yunsel, Tayfun Yusuf; Atici, Umit

2008-02-01

Abandoned mine workings can undoubtedly cause varying degrees of contamination of soil with heavy metals such as lead and zinc has occurred on a global scale. Exposure to these elements may cause to harm human health and environment. In the study, a total of 269 soil samples were collected at 1, 5, and 10 m regular grid intervals of 100 x 100 m area of Carsington Pasture in the UK. Cell declustering technique was applied to the data set due to no statistical representativity. Directional experimental semivariograms of the elements for the transformed data showed that both geometric and zonal anisotropy exists in the data. The most evident spatial dependence structure of the continuity for the directional experimental semivariogram, characterized by spherical and exponential models of Pb and Zn were obtained. This study reports the spatial distribution and uncertainty of Pb and Zn concentrations in soil at the study site using a probabilistic approach. The approach was based on geostatistical sequential Gaussian simulation (SGS), which is used to yield a series of conditional images characterized by equally probable spatial distributions of the heavy elements concentrations across the area. Postprocessing of many simulations allowed the mapping of contaminated and uncontaminated areas, and provided a model for the uncertainty in the spatial distribution of element concentrations. Maps of the simulated Pb and Zn concentrations revealed the extent and severity of contamination. SGS was validated by statistics, histogram, variogram reproduction, and simulation errors. The maps of the elements might be used in the remediation studies, help decision-makers and others involved in the abandoned heavy metal mining site in the world.

Developing an ecosystem perspective from experimental monitoring programs: I. Demographic responses of a rare geothermal grass to soil temperature.

PubMed

Pavlik, B M; Enberg, A

2001-08-01

The geysers panic grass [Dichanthelium lanuginosum Spellenberg var. thermale (Bol.) Spellenberg or DILA] is exclusively associated with surface geothermal manifestations in Sonoma County, California, USA (38 degrees 46'N, 122 degrees 38'W). Steam extraction by power plants could alter the subsurface distribution of heat and water to the site, potentially impacting subpopulations of this rare plant. The purpose of this study was to use demographic monitoring to determine: (1) temporal and spatial patterns of soil temperature in relation to the distribution of established DILA individuals at Little Geysers, (2) in situ response of experimental populations of DILA to spatial variations in soil temperature, and (3) habitat requirements of DILA as an indicator of its tolerance to variations in surficial geothermal features. Thermocouple transects and a datalogger provided data for characterizing the spatial and temporal patterns of soil temperature in four microhabitats (fumarole, DILA stand, Andropogon stand, and cleared). Experimental populations were established by precisely sowing and monitoring DILA seeds in these microhabitats. The results indicated that spatial and temporal variations in soil temperature had significant effects on the processes of germination, growth, survivorship, and reproduction, thus producing a readily observed metapopulation patch dynamic in relation to geothermal activity. Seasonal depressions of soil temperature near the fumaroles by cold air and prolonged rainfall events also promoted the emergence and survival of DILA seedlings in a microhabitat that was previously too hot to occupy. Over longer periods of time, DILA metapopulation dynamism reflected climatic and geothermal variation. Drought years inhibited germination for lack of water, but more importantly for the lack of requisite soil temperature depressions in the fumarole microhabitat. Wet years promoted subpopulation expansion into transition areas that were once too hot and dry. There have also been shifts in the underground distribution of steam into areas distant from known geothermal features. The demographic responses of DILA to spatial and temporal variations in soil temperature indicate that heat is an absolutely essential component of the steam resource. In its absence, germination, seeding survivorship, growth, and maturation are significantly inhibited even if soil conditions are favorable and potential competitors are controlled. Ultimately, persistence of the species depends on maintaining the ecosystem dynamic of colonization and extirpation in response to variations in surficial geothermal features over long spatial and temporal scales. This should shift management perspective from its narrow focus on individual plants to a wider focus on monitoring the essential habitat component of steam.

Effects of slope aspect and site elevation on seasonal soil carbon dynamics in a forest catchment in the Austrian Limestone Alps

NASA Astrophysics Data System (ADS)

Kobler, Johannes; Zehetgruber, Bernhard; Jandl, Robert; Dirnböck, Thomas; Schindlbacher, Andreas

2017-04-01

Own to the complexity of landscape morphology, mountainous landscapes are characterized by substantial changes of site parameters (i.e. elevation, slope, aspect) within short distances. As these site parameters affect the spatial-temporal dynamics of landscape climate and therefore the spatial patterns of forest carbon (C) distribution, they pose a substantial impact on landscape-related soil C dynamics. Aspect and elevation form natural temperature gradients and thereby can be used as a surrogate to infer to potential climate change effects on forest C. We aimed at studying how slope aspect affected soil respiration, soil C stocks, tree increment and litter production along two elevation gradients in the Zöbelboden catchment, northern limestone Alps, Austria during 2015 and 2016. A preliminary assessment showed that soil respiration was significantly higher at the west facing slope across all elevations. Soil temperature was only slightly higher at the west facing slope, and warmer soil only partly explained the large difference in soil respiration between east and west facing slopes. Aspect had no clear effect on soil moisture, which seemed to be strongly affected by stocking density at the different forest sites. The dense grassy ground vegetation at some of the sites further seems to play a key role in determining soil respiration rates and litter input. A detailed analysis and C-budgets along the elevation gradients will be presented at the conference.

[Spatial variation characteristics of surface soil water content, bulk density and saturated hydraulic conductivity on Karst slopes].

PubMed

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.

Characterization for capillary barriers effects in a sand box test using time-lapsed GPR measurements

NASA Astrophysics Data System (ADS)

Kuroda, S.; Ishii, N.; Morii, T.

2017-12-01

Capillary barriers have been known as the method to protect subsurface regions against infiltration from soil surface. It is caused by essentially heterogeneous structure in permeability or soil physical property and produce non-uniform infiltration process then, in order to estimate the actual situation of the capillary barrier effect, the site-characterization with imaging technique like geophysical prospecting is effective. In this study, we examine the applicability of GPR to characterization for capillary barriers. We built a sand box with 90x340x90cm in which a thin high-permeable gravel layer was embedded as a capillary barrier. We conducted an infiltration test in the sand box using porous tube array for irrigation. It is expected to lead to non-uniform flow of soil water induced by capillary barrier effects. We monitored this process by various types of GPR measurements, including time-lapsed common offset profiling (COP) with multi- frequency antenna and transmission measurements like cross-borehole radar. At first, we conducted GPR common-offset survey. It could show the depth of capillary barrier in sand box. After that we conducted the infiltration test and GPR monitoring for infiltration process. GPR profiles can detect the wetting front and estimate water content change in the soil layer above the capillary barrier. From spatial change in these results we can estimate the effect of capillary barrier and the zone where the break through occur or not. Based on these results, we will discuss the applicability of GPR for monitoring the phenomena around the capillary barrier of soil. At first, we conducted GPR common-offset survey. It could show the depth of capillary barrier in sand box. After that we conducted the infiltration test and GPR monitoring for infiltration process. GPR profiles can detect the wetting front and estimate water content change in the soil layer above the capillary barrier. From spatial change in these results we can estimate the effect of capillary barrier and the zone where the break through occur. Based on these results, we will discuss the applicability of GPR for monitoring the phenomena around the capillary barrier of soil.

Heterogeneity of soil carbon pools and fluxes in a channelized and a restored floodplain section (Thur River, Switzerland)

NASA Astrophysics Data System (ADS)

Samaritani, E.; Shrestha, J.; Fournier, B.; Frossard, E.; Gillet, F.; Guenat, C.; Niklaus, P. A.; Pasquale, N.; Tockner, K.; Mitchell, E. A. D.; Luster, J.

2011-06-01

Due to their spatial complexity and dynamic nature, floodplains provide a wide range of ecosystem functions. However, because of flow regulation, many riverine floodplains have lost their characteristic heterogeneity. Restoration of floodplain habitats and the rehabilitation of key ecosystem functions, many of them linked to organic carbon (C) dynamics in riparian soils, has therefore become a major goal of environmental policy. The fundamental understanding of the factors that drive the processes involved in C cycling in heterogeneous and dynamic systems such as floodplains is however only fragmentary. We quantified soil organic C pools (microbial C and water extractable organic C) and fluxes (soil respiration and net methane production) in functional process zones of adjacent channelized and widened sections of the Thur River, NE Switzerland, on a seasonal basis. The objective was to assess how spatial heterogeneity and temporal variability of these pools and fluxes relate to physicochemical soil properties on one hand, and to soil environmental conditions and flood disturbance on the other hand. Overall, factors related to seasonality and flooding (temperature, water content, organic matter input) affected soil C dynamics more than soil properties did. Coarse-textured soils on gravel bars in the restored section were characterized by low base-levels of organic C pools due to low TOC contents. However, frequent disturbance by flood pulses led to high heterogeneity with temporarily and locally increased C pools and soil respiration. By contrast, in stable riparian forests, the finer texture of the soils and corresponding higher TOC contents and water retention capacity led to high base-levels of C pools. Spatial heterogeneity was low, but major floods and seasonal differences in temperature had additional impacts on both pools and fluxes. Soil properties and base levels of C pools in the dam foreland of the channelized section were similar to the gravel bars of the restored section. By contrast, spatial heterogeneity, seasonal effects and flood disturbance were similar to the forests, except for indications of high CH4 production that are explained by long travel times of infiltrating water favoring reducing conditions. Overall, the restored section exhibited both a larger range and a higher heterogeneity of organic C pools and fluxes as well as a higher plant biodiversity than the channelized section. This suggests that restoration has indeed led to an increase in functional diversity.

Heterogeneity of soil carbon pools and fluxes in a channelized and a restored floodplain section (Thur River, Switzerland)

NASA Astrophysics Data System (ADS)

Samaritani, E.; Shrestha, J.; Fournier, B.; Frossard, E.; Gillet, F.; Guenat, C.; Niklaus, P. A.; Tockner, K.; Mitchell, E. A. D.; Luster, J.

2011-01-01

Due to their spatial complexity and dynamic nature, floodplains provide a wide range of ecosystem functions. However, because of flow regulation, many riverine floodplains have lost their characteristic heterogeneity. Restoration of floodplain habitats and the rehabilitation of key ecosystem functions has therefore become a major goal of environmental policy. Many important ecosystem functions are linked to organic carbon (C) dynamics in riparian soils. The fundamental understanding of the factors that drive the processes involved in C cycling in heterogeneous and dynamic systems such as floodplains is however only fragmentary. We quantified soil organic C pools (microbial C and water extractable organic C) and fluxes (soil respiration and net methane production) in functional process zones of adjacent channelized and widened sections of the Thur River, NE Switzerland, on a seasonal basis. The objective was to assess how spatial heterogeneity and temporal variability of these pools and fluxes relate to physicochemical soil properties on one hand, and to soil environmental conditions and flood disturbance on the other hand. Overall, factors related to seasonality and flooding (temperature, water content, organic matter input) affected soil C dynamics more than soil properties did. Coarse-textured soils on gravel bars in the restored section were characterized by low base-levels of organic C pools due to low TOC contents. However, frequent disturbance by flood pulses led to high heterogeneity with temporarily and locally increased pools and soil respiration. By contrast, in stable riparian forests, the finer texture of the soils and corresponding higher TOC contents and water retention capacity led to high base-levels of C pools. Spatial heterogeneity was low, but major floods and seasonal differences in temperature had additional impacts on both pools and fluxes. Soil properties and base levels of C pools in the dam foreland of the channelized section were similar to the gravel bars of the restored section. By contrast, spatial heterogeneity, seasonal effects and flood disturbance were similar to the forests, except for indications of high CH4 production that are explained by long travel times of infiltrating water favouring reducing conditions. Overall, the restored section exhibited both a larger range and a higher heterogeneity of organic C pools and fluxes as well as a higher plant biodiversity than the channelized section. This suggests that restoration has indeed led to an increase in functional diversity.

Vegetation Structure Controls Carbon Sequestration Potential in a Savannah Ecosystem of Mt. Kilimanjaro Region

NASA Astrophysics Data System (ADS)

Becker, J. N.; Gutlein, A.; Sierra Cornejo, N.; Ralf, K.; Hertel, D.; Kuzyakov, Y.

2016-12-01

The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon (C) sequestration. Savanna ecosystems are increasingly pressured by climate and land-use changes, especially around populous areas such as the Mt. Kilimanjaro region. Savanna vegetation consists of grassland with isolated trees and is therefore characterized by high spatial variation and patchiness of canopy cover and aboveground biomass. Both are major regulators for soil ecological properties and soil-atmospheric trace gas exchange (CO2, N2O, CH4), especially in water-limited environments. Our objectives were to determine spatial trends in soil properties and trace-gas fluxes during the dry season and to relate above- and belowground processes and attributes. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. At each sampling point (0-10 & 10-30 cm depth) we measured soil C and nitrogen (N) storage, microbial biomass C and N, Natural δ13C, soil respiration, available nutrients, pH, cation exchange capacity (CEC) as well as root biomass and -density, soil temperature and soil water content. The tree species had no effect on soil parameters and gas fluxes under the crown. CEC, C and N fractions decreased up to 50% outside the crown-covered area. Tree leaf litter had a far lower C:N ratio than leaf litter of the C4-grass species. δ13C in soil under the crowns shifted about 15% in the direction of tree leaf litter δ13C compared to soil in open area reflecting the tree litter contribution to soil organic matter. The microbial C:N ratio and CO2 efflux were about 30% higher in the open area and strongly dependent on mineral N availability. This indicates N limitation and low C-use efficiency in soil under open grassland. We conclude that the spatial structure of aboveground biomass in savanna ecosystems leads to a spatial redistribution of nutrient availability and thus in C mineralization and sequestration. Therefore, the capability of savanna ecosystems to act as C sinks is both directly and indirectly dependent on the abundance of trees regardless of their N-fixing capability.

Spatial distribution patterns of soil mite communities and their relationships with edaphic factors in a 30-year tillage cornfield in northeast China.

PubMed

Liu, Jie; Gao, Meixiang; Liu, Jinwen; Guo, Yuxi; Liu, Dong; Zhu, Xinyu; Wu, Donghui

2018-01-01

Spatial distribution is an important topic in community ecology and a key to understanding the structure and dynamics of populations and communities. However, the available information related to the spatial patterns of soil mite communities in long-term tillage agroecosystems remains insufficient. In this study, we examined the spatial patterns of soil mite communities to explain the spatial relationships between soil mite communities and soil parameters. Soil fauna were sampled three times (August, September and October 2015) at 121 locations arranged regularly within a 400 m × 400 m monitoring plot. Additionally, we estimated the physical and chemical parameters of the same sampling locations. The distribution patterns of the soil mite community and the edaphic parameters were analyzed using a range of geostatistical tools. Moran's I coefficient showed that, during each sampling period, the total abundance of the soil mite communities and the abundance of the dominant mite populations were spatially autocorrelated. The soil mite communities demonstrated clear patchy distribution patterns within the study plot. These patterns were sampling period-specific. Cross-semivariograms showed both negative and positive cross-correlations between soil mite communities and environmental factors. Mantel tests showed a significant and positive relationship between soil mite community and soil organic matter and soil pH only in August. This study demonstrated that in the cornfield, the soil mite distribution exhibited strong or moderate spatial dependence, and the mites formed patches with sizes less than one hundred meters. In addition, in this long-term tillage agroecosystem, soil factors had less influence on the observed pattern of soil mite communities. Further experiments that take into account human activity and spatial factors should be performed to study the factors that drive the spatial distribution of soil microarthropods.

Spatial variability of soil and vegetation characteristics in an urban park in Tel-Aviv

NASA Astrophysics Data System (ADS)

Sarah, Pariente; Zhevelev, Helena M.; Oz, Atar

2010-05-01

Mosaic-like spatial patterns, consisting of divers soil microenvironments, characterize the landscapes of many urban parks. These microenvironments may differ in their pedological, hydrological and floral characteristics, and they play important roles in urban ecogeomorphic system functioning. In and around a park covering 50 ha in Tel Aviv, Israel, soil properties and herbaceous vegetation were measured in eight types of microenvironments. Six microenvironments were within the park: area under Ceratonia siliqua (Cs-U), area under Ficus sycomorus (Fi-U), a rest area under F. sycomorus (Re-U), an open area with bare soil (Oa-S), an open area with biological crusts (Oa-C), and an open area with herbaceous vegetation (Oa-V). Outside the park were two control microenvironments, located, respectively, on a flat area (Co-P) and an inclined open area (Co-S). The soil was sampled from two depths (0-2 and 5-10 cm), during the peak of the growing season (March). For each soil sample, moisture content, organic matter content, CaCO3 content, texture, pH, electrical conductivity, and soluble ions contents were determined in 1:1 water extraction. In addition, prior to the soil sampling, vegetation cover, number of species, and species diversity of herbaceous vegetation were measured. The barbecue fires and visitors in each of the microenvironments were counted. Whereas the soil organic matter and vegetation in Fi-U differed from those in the control(Co-P, Co-S), those in Oa-V were similar to those in the control. Fi-U was characterized by higher values of soil moisture, organic matter, penetration depth, and vegetation cover than Cs-U. Open microenvironments within the park (Oa-S, Oa-C, Oa-V) showed lower values of soil penetration than the control microenvironments. In Oa-V unique types of plants such as Capsella bursa-pastoris and Anagallis arvensis, which did not appear in the control microenvironments, were found. This was true also for Fi-U, in which species like Oxalis pes-caprae were found. Significant differences in soil and vegetation properties were found between Re-U and the rest of microenvironments. Differences in levels of human activities, in addition to differences in vegetation types, increased the spatial heterogeneity of soil properties. The rest microenvironment (Re-U) exhibited degraded soil conditions and can be regarded as forming the fragile areas of the park. An urban park offers potential for presence and growth of natural vegetation and, therefore, also for preservation of biodiversity. Natural vegetation, in its role as a part of the urban park, enriches the landscape diversity and thereby may contribute to the enjoyment of the visitors in the park.

Mapping CO2 emission in highly urbanized region using standardized microbial respiration approach

NASA Astrophysics Data System (ADS)

Vasenev, V. I.; Stoorvogel, J. J.; Ananyeva, N. D.

2012-12-01

Urbanization is a major recent land-use change pathway. Land conversion to urban has a tremendous and still unclear effect on soil cover and functions. Urban soil can act as a carbon source, although its potential for CO2 emission is also very high. The main challenge in analysis and mapping soil organic carbon (SOC) in urban environment is its high spatial heterogeneity and temporal dynamics. The urban environment provides a number of specific features and processes that influence soil formation and functioning and results in a unique spatial variability of carbon stocks and fluxes at short distance. Soil sealing, functional zoning, settlement age and size are the predominant factors, distinguishing heterogeneity of urban soil carbon. The combination of these factors creates a great amount of contrast clusters with abrupt borders, which is very difficult to consider in regional assessment and mapping of SOC stocks and soil CO2 emission. Most of the existing approaches to measure CO2 emission in field conditions (eddy-covariance, soil chambers) are very sensitive to soil moisture and temperature conditions. They require long-term sampling set during the season in order to obtain relevant results. This makes them inapplicable for the analysis of CO2 emission spatial variability at the regional scale. Soil respiration (SR) measurement in standardized lab conditions enables to overcome this difficulty. SR is predominant outgoing carbon flux, including autotrophic respiration of plant roots and heterotrophic respiration of soil microorganisms. Microbiota is responsible for 50-80% of total soil carbon outflow. Microbial respiration (MR) approach provides an integral CO2 emission results, characterizing microbe CO2 production in optimal conditions and thus independent from initial difference in soil temperature and moisture. The current study aimed to combine digital soil mapping (DSM) techniques with standardized microbial respiration approach in order to analyse and map CO2 emission and its spatial variability in highly urbanized Moscow region. Moscow region with its variability of bioclimatic conditions and high urbanization level (10 % from the total area) was chosen as an interesting case study. Random soil sampling in different soil zones (4) and land-use types (3 non-urban and 3 urban) was organized in Moscow region in 2010-2011 (n=242). Both topsoil (0-10 cm) and subsoil (10-150 cm) were included. MR for each point was analysed using standardized microbial (basal) respiration approach, including the following stages: 1) air dried soil samples were moisturised up to 55% water content and preincubated (7 days, 22° C) in a plastic bag with air exchange; 2) soil MR (in μg CO2-C g-1) was measured as the rate of CO2 production (22° C, 24 h) after incubating 2g soil with 0.2 μl distilled water; 3) the MR results were used to estimate CO2 emission (kg C m-2 yr-1). Point MR and CO2 emission results obtained were extrapolated for the Moscow region area using regression model. As a result, two separate CO2 maps for topsoil and subsoil were created. High spatial variability was demonstrated especially for the urban areas. Thus standardized MR approach combined with DSM techniques provided a unique opportunity for spatial analysis of soil carbon temporal dynamics at the regional scale.

Impact of Hydrologic and Micro-topographic Variabilities on Spatial Distribution of Mean Soil-Nitrogen Age

NASA Astrophysics Data System (ADS)

Woo, D.; Kumar, P.

2015-12-01

Excess reactive nitrogen in soils of intensively managed agricultural fields causes adverse environmental impact, and continues to remain a global concern. Many novel strategies have been developed to provide better management practices and, yet, the problem remains unresolved. The objective of this study is to develop a 3-dimensional model to characterize the spatially distributed ``age" of soil-nitrogen (nitrate and ammonia-ammonium) across a watershed. We use the general theory of age, which provides an assessment of the elapsed time since nitrogen is introduced into the soil system. Micro-topographic variability incorporates heterogeneity of nutrient transformations and transport associated with topographic depressions that form temporary ponds and produce prolonged periods of anoxic conditions, and roadside agricultural ditches that support rapid surface movement. This modeling effort utilizes 1-m Light Detection and Ranging (LiDAR) data. We find a significant correlation between hydrologic variability and mean nitrate age that enables assessment of preferential flow paths of nitrate leaching. The estimation of the mean nitrogen age can thus serve as a tool to disentangle complex nitrogen dynamics by providing the analysis of the time scales of soil-nitrogen transformation and transport processes without introducing additional parameters.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatially Distributed Characterization of Catchment Dynamics Using Travel-Time Distributions

NASA Astrophysics Data System (ADS)

Heße, F.; Zink, M.; Attinger, S.

2015-12-01

The description of storage and transport of both water and solved contaminants in catchments is very difficult due to the high heterogeneity of the subsurface properties that govern their fate. This heterogeneity, combined with a generally limited knowledge about the subsurface, results in high degrees of uncertainty. As a result, stochastic methods are increasingly applied, where the relevant processes are modeled as being random. Within these methods, quantities like the catchment travel or residence time of a water parcel are described using probability density functions (PDF). The derivation of these PDF's is typically done by using the water fluxes and states of the catchment. A successful application of such frameworks is therefore contingent on a good quantification of these fluxes and states across the different spatial scales. The objective of this study is to use travel times for the characterization of an ca. 1000 square kilometer, humid catchment in Central Germany. To determine the states and fluxes, we apply the mesoscale Hydrological Model mHM, a spatially distributed hydrological model to the catchment. Using detailed data of precipitation, land cover, morphology and soil type as inputs, mHM is able to determine fluxes like recharge and evapotranspiration and states like soil moisture as outputs. Using these data, we apply the above theoretical framework to our catchment. By virtue of the aforementioned properties of mHM, we are able to describe the storage and release of water with a high spatial resolution. This allows for a comprehensive description of the flow and transport dynamics taking place in the catchment. The spatial distribution of such dynamics is then compared with land cover and soil moisture maps as well as driving forces like precipitation and temperature to determine the most predictive factors. In addition, we investigate how non-local data like the age distribution of discharge flows are impacted by, and therefore allow to infer, local properties of the catchment.

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.

Two water worlds: Isotope evidence shows that trees and streams return different pools of water to the hydrosphere

EPA Science Inventory

Ecohydrological coupling at the watershed scale is poorly characterized. While soil-water storage is dynamic and strongly influenced by plants, few integrated tools exist for quantifying the spatial and temporal dynamics and interactions among the major components of the terrestr...

Quantifying the Spatial Distribution of Hill Slope Erosion Using a 3-D Laser Scanner

NASA Astrophysics Data System (ADS)

Scholl, B. N.; Bogonko, M.; He, Y.; Beighley, R. E.; Milberg, C. T.

2007-12-01

Soil erosion is a complicated process involving many interdependent variables including rainfall intensity and duration, drop size, soil characteristics, ground cover, and surface slope. The interplay of these variables produces differing spatial patterns of rill versus inter-rill erosion by changing the effective energy from rain drop impacts and the quantities and timing of sheet and shallow, concentrated flow. The objective of this research is to characterize the spatial patterns of rill and inter-rill erosion produced from simulated rainfall on different soil densities and surface slopes using a 3-D laser scanner. The soil used in this study is a sandy loam with bulk density due to compaction ranging from 1.25-1.65 g/cm3. The surface slopes selected for this study are 25, 33, and 50 percent and represent common slopes used for grading on construction sites. The spatial patterns of soil erosion are measured using a Trimble GX DR 200+ 3D Laser Scanner which employs a time of flight calculation averaged over 4 points using a class 2, pulsed, 532 nm, green laser at a distance of 2 to 11 m from the surface. The scanner measures point locations on an approximately 5 mm grid. The pre- and post-erosion scan surfaces are compared to calculate the change in volume and the dimensions of rills and inter-rill areas. The erosion experiments were performed in the Soil Erosion Research Laboratory (SERL), part of the Civil and Environmental Engineering department at San Diego State University. SERL experiments utilize a 3-m by 10-m tilting soil bed with a soil depth of 0.5 meters. Rainfall is applied to the soil surface using two overhead Norton ladder rainfall simulators, which produce realistic rain drop diameters (median = 2.25 mm) and impact velocities. Simulated storm events used in this study consist of rainfall intensities ranging from 5, 10 to 15 cm/hr for durations of 20 to 30 minutes. Preliminary results are presented that illustrate a change in runoff processes and erosion patterns as soil density increases and reduces infiltration characteristics. Total soil loss measured from the bottom of the erosion bed is compared to the volume of soil loss determined using the laser scanner. Due to soil consolidation during the experiment, the accuracy of measured soil loss from the laser scanner increases with increasing soil density. Ratios of rill and inter-rill erosions for each experiment are also presented. URL: http://spatialhydro.sdsu.edu

Assessing the Importance of Incorporating Spatial and Temporal Variability of Soil and Plant Parameters into Local Water Balance Models for Precision Agriculture: Investigations within a California Vineyard

NASA Astrophysics Data System (ADS)

Hubbard, S.; Pierce, L.; Grote, K.; Rubin, Y.

2003-12-01

Due Due to the high cash crop nature of premium winegrapes, recent research has focused on developing a better understanding of the factors that influence winegrape spatial and temporal variability. Precision grapevine irrigation schemes require consideration of the factors that regulate vineyard water use such as (1) plant parameters, (2) climatic conditions, and (3) water availability in the soil as a function of soil texture. The inability to sample soil and plant parameters accurately, at a dense enough resolution, and over large enough areas has limited previous investigations focused on understanding the influences of soil water and vegetation on water balance at the local field scale. We have acquired several novel field data sets to describe the small scale (decimeters to a hundred meters) spatial variability of soil and plant parameters within a 4 acre field study site at the Robert Mondavi Winery in Napa County, California. At this site, we investigated the potential of ground penetrating radar data (GPR) for providing estimates of near surface water content. Calibration of grids of 900 MHz GPR groundwave data with conventional soil moisture measurements revealed that the GPR volumetric water content estimation approach was valid to within 1 percent accuracy, and that the data grids provided unparalleled density of soil water content over the field site as a function of season. High-resolution airborne multispectral remote sensing data was also collected at the study site, which was converted to normalized difference vegetation index (NDVI) and correlated to leaf area index (LAI) using plant-based measurements within a parallel study. Meteorological information was available from a weather station of the California Irrigation management Information System, located less than a mile from our study area. The measurements were used within a 2-D Vineyard Soil Irrigation Model (VSIM), which can incorporate the spatially variable, high-resolution soil and plant-based information. VSIM, which is based on the concept that equilibrium exists between climate, soils, and LAI, was used to simulate vine water stress, water use, and irrigation requirements during a single year for the site. Using the simple water-balance model with the dense characterization data, we will discuss: (1) the ability to predict vineyard soil water content at the small scales of soil heterogeneity that are observed in nature at the local-scale, (2) the relative importance of plant, climate, and soil information to predictions of the soil water balance at the site, (3) the influence of crop cover in the water balance predictions.

Enhanced representation of soil NO emissions in the ...

EPA Pesticide Factsheets

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12 km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and

Downscaling Soil Moisture in the Southern Great Plains Through a Calibrated Multifractal Model for Land Surface Modeling Applications

NASA Technical Reports Server (NTRS)

Mascaro, Giuseppe; Vivoni, Enrique R.; Deidda, Roberto

2010-01-01

Accounting for small-scale spatial heterogeneity of soil moisture (theta) is required to enhance the predictive skill of land surface models. In this paper, we present the results of the development, calibration, and performance evaluation of a downscaling model based on multifractal theory using aircraft!based (800 m) theta estimates collected during the southern Great Plains experiment in 1997 (SGP97).We first demonstrate the presence of scale invariance and multifractality in theta fields of nine square domains of size 25.6 x 25.6 sq km, approximately a satellite footprint. Then, we estimate the downscaling model parameters and evaluate the model performance using a set of different calibration approaches. Results reveal that small-scale theta distributions are adequately reproduced across the entire region when coarse predictors include a dynamic component (i.e., the spatial mean soil moisture ) and a stationary contribution accounting for static features (i.e., topography, soil texture, vegetation). For wet conditions, we found similar multifractal properties of soil moisture across all domains, which we ascribe to the signature of rainfall spatial variability. For drier states, the theta fields in the northern domains are more intermittent than in southern domains, likely because of differences in the distribution of vegetation coverage. Through our analyses, we propose a regional downscaling relation for coarse, satellite-based soil moisture estimates, based on ancillary information (static and dynamic landscape features), which can be used in the study area to characterize statistical properties of small-scale theta distribution required by land surface models and data assimilation systems.

Local versus field scale soil heterogeneity characterization - a challenge for representative sampling in pollution studies

NASA Astrophysics Data System (ADS)

Kardanpour, Z.; Jacobsen, O. S.; Esbensen, K. H.

2015-06-01

This study is a contribution to development of a heterogeneity characterisation facility for "next generation" sampling aimed at more realistic and controllable pesticide variability in laboratory pots in experimental environmental contaminant assessment. The role of soil heterogeneity on quantification of a set of exemplar parameters, organic matter, loss on ignition (LOI), biomass, soil microbiology, MCPA sorption and mineralization is described, including a brief background on how heterogeneity affects sampling/monitoring procedures in environmental pollutant studies. The Theory of Sampling (TOS) and variographic analysis has been applied to develop a fit-for-purpose heterogeneity characterization approach. All parameters were assessed in large-scale profile (1-100 m) vs. small-scale (0.1-1 m) replication sampling pattern. Variographic profiles of experimental analytical results concludes that it is essential to sample at locations with less than a 2.5 m distance interval to benefit from spatial auto-correlation and thereby avoid unnecessary, inflated compositional variation in experimental pots; this range is an inherent characteristic of the soil heterogeneity and will differ among soils types. This study has a significant carrying-over potential for related research areas e.g. soil science, contamination studies, and environmental monitoring and environmental chemistry.

Characterizing Drought Impacted Soils in the San Joaquin Valley of California Using Remote Sensing

NASA Astrophysics Data System (ADS)

Wahab, L. M.; Miller, D.; Roberts, D. A.

2017-12-01

California's San Joaquin Valley is an extremely agriculturally productive region of the country, and understanding the state of soils in this region is an important factor in maintaining this high productivity. In this study, we quantified changing soil cover during the drought and analyzed spatial changes in salinity, organic matter, and moisture using unique soil spectral characteristics. We used data from the Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) from Hyperspectral Infrared Imager (HyspIRI) campaign flights in 2013 and 2014 over the San Joaquin Valley. A mixture model was applied to both images that identified non- photosynthetic vegetation, green vegetation, and soil cover fractions through image endmembers of each of these three classes. We optimized the spectral library used to identify these classes with Iterative Endmember Selection (IES), and the images were unmixed using Multiple Endmember Spectral Mixture Analysis (MESMA). Maps of soil electrical conductivity, organic matter, soil saturated moisture, and field moisture were generated for the San Joaquin Valley based on indices developed by Ben-Dor et al. [2002]. Representative polygons were chosen to quantify changes between years. Maps of spectrally distinct soils were also generated for 2013 and 2014, in order to determine the spatial distribution of these soil types as well as their temporal dynamics between years. We estimated that soil cover increased by 16% from 2013-2014. Six spectrally distinct soil types were identified for the region, and it was determined that the distribution of these soil types was not constant for most areas between 2013 and 2014. Changes in soil pH, electrical conductivity, and soil moisture were strongly tied in the region between 2013 and 2014.

Optimizing the Hydrological and Biogeochemical Simulations on a Hillslope with Stony Soil

NASA Astrophysics Data System (ADS)

Zhu, Q.

2017-12-01

Stony soils are widely distributed in the hilly area. However, traditional pedotransfer functions are not reliable in predicting the soil hydraulic parameters for these soils due to the impacts of rock fragments. Therefore, large uncertainties and errors may exist in the hillslope hydrological and biogeochemical simulations in stony soils due to poor estimations of soil hydraulic parameters. In addition, homogenous soil hydraulic parameters are usually used in traditional hillslope simulations. However, soil hydraulic parameters are spatially heterogeneous on the hillslope. This may also cause the unreliable simulations. In this study, we obtained soil hydraulic parameters using five different approaches on a tea hillslope in Taihu Lake basin, China. These five approaches included (1) Rossetta predicted and spatially homogenous, (2) Rossetta predicted and spatially heterogeneous), (3) Rossetta predicted, rock fragment corrected and spatially homogenous, (4) Rossetta predicted, rock fragment corrected and spatially heterogeneous, and (5) extracted from observed soil-water retention curves fitted by dual-pore function and spatially heterogeneous (observed). These five sets of soil hydraulic properties were then input into Hydrus-3D and DNDC to simulate the soil hydrological and biogeochemical processes. The aim of this study is testing two hypotheses. First, considering the spatial heterogeneity of soil hydraulic parameters will improve the simulations. Second, considering the impact of rock fragment on soil hydraulic parameters will improve the simulations.

Soil Parameters Drive the Structure, Diversity and Metabolic Potentials of the Bacterial Communities Across Temperate Beech Forest Soil Sequences.

PubMed

Jeanbille, M; Buée, M; Bach, C; Cébron, A; Frey-Klett, P; Turpault, M P; Uroz, S

2016-02-01

Soil and climatic conditions as well as land cover and land management have been shown to strongly impact the structure and diversity of the soil bacterial communities. Here, we addressed under a same land cover the potential effect of the edaphic parameters on the soil bacterial communities, excluding potential confounding factors as climate. To do this, we characterized two natural soil sequences occurring in the Montiers experimental site. Spatially distant soil samples were collected below Fagus sylvatica tree stands to assess the effect of soil sequences on the edaphic parameters, as well as the structure and diversity of the bacterial communities. Soil analyses revealed that the two soil sequences were characterized by higher pH and calcium and magnesium contents in the lower plots. Metabolic assays based on Biolog Ecoplates highlighted higher intensity and richness in usable carbon substrates in the lower plots than in the middle and upper plots, although no significant differences occurred in the abundance of bacterial and fungal communities along the soil sequences as assessed using quantitative PCR. Pyrosequencing analysis of 16S ribosomal RNA (rRNA) gene amplicons revealed that Proteobacteria, Acidobacteria and Bacteroidetes were the most abundantly represented phyla. Acidobacteria, Proteobacteria and Chlamydiae were significantly enriched in the most acidic and nutrient-poor soils compared to the Bacteroidetes, which were significantly enriched in the soils presenting the higher pH and nutrient contents. Interestingly, aluminium, nitrogen, calcium, nutrient availability and pH appeared to be the best predictors of the bacterial community structures along the soil sequences.

Relevant magnetic and soil parameters as potential indicators of soil conservation status of Mediterranean agroecosystems

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.

Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.

PubMed

Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao

2016-02-01

Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.

Wet-season spatial variability of N2O emissions from a tea field in subtropical central China

NASA Astrophysics Data System (ADS)

Fu, X.; Liu, X.; Li, Y.; Shen, J.; Wang, Y.; Zou, G.; Li, H.; Song, L.; Wu, J.

2015-01-01

Tea fields emit large amounts of nitrous oxide (N2O) to the atmosphere. Obtaining accurate estimations of N2O emissions from tea-planted soils is challenging due to strong spatial variability. We examined the spatial variability of N2O emissions from a red-soil tea field in Hunan province, China, on 22 April 2012 (in a wet season) using 147 static mini chambers approximately regular gridded in a 4.0 ha tea field. The N2O fluxes for a 30 min snapshot (10-10.30 a.m.) ranged from -1.73 to 1659.11 g N ha-1 d-1 and were positively skewed with an average flux of 102.24 g N ha-1 d-1. The N2O flux data were transformed to a normal distribution by using a logit function. The geostatistical analyses of our data indicated that the logit-transformed N2O fluxes (FLUX30t) exhibited strong spatial autocorrelation, which was characterized by an exponential semivariogram model with an effective range of 25.2 m. As observed in the wet season, the logit-transformed soil ammonium-N (NH4Nt), soil nitrate-N (NO3Nt), soil organic carbon (SOCt), total soil nitrogen (TSNt) were all found to be significantly correlated with FLUX30t (r=0.57-0.71, p<0.001). Three spatial interpolation methods (ordinary kriging, regression kriging and cokriging) were applied to estimate the spatial distribution of N2O emissions over the study area. Cokriging with NH4Nt and NO3Nt as covariables (r= 0.74 and RMSE =1.18) outperformed ordinary kriging (r= 0.18 and RMSE =1.74), regression kriging with the sample position as a predictor (r= 0.49 and RMSE =1.55) and cokriging with SOCt as a covariable (r= 0.58 and RMSE =1.44). The predictions of the three kriging interpolation methods for the total N2O emissions of the 4.0 ha tea field ranged from 148.2 to 208.1 g N d-1, based on the 30 min snapshots obtained during the wet season. Our findings suggested that to accurately estimate the total N2O emissions over a region, the environmental variables (e.g., soil properties) and the current land use pattern (e.g., tea row transects in the present study) must be included in spatial interpolation. Additionally, compared with other kriging approaches, the cokriging prediction approach showed great advantages in being easily deployed, and more importantly providing accurate regional estimation of N2O emissions from tea-planted soils.

Wet-season spatial variability in N2O emissions from a tea field in subtropical central China

NASA Astrophysics Data System (ADS)

Fu, X.; Liu, X.; Li, Y.; Shen, J.; Wang, Y.; Zou, G.; Li, H.; Song, L.; Wu, J.

2015-06-01

Tea fields emit large amounts of nitrous oxide (N2O) to the atmosphere. Obtaining accurate estimations of N2O emissions from tea-planted soils is challenging due to strong spatial variability. We examined the spatial variability in N2O emissions from a red-soil tea field in Hunan Province, China, on 22 April 2012 (in a wet season) using 147 static mini chambers approximately regular gridded in a 4.0 ha tea field. The N2O fluxes for a 30 min snapshot (10:00-10:30 a.m.) ranged from -1.73 to 1659.11 g N ha-1 d-1 and were positively skewed with an average flux of 102.24 g N ha-1 d-1. The N2O flux data were transformed to a normal distribution by using a logit function. The geostatistical analyses of our data indicated that the logit-transformed N2O fluxes (FLUX30t) exhibited strong spatial autocorrelation, which was characterized by an exponential semivariogram model with an effective range of 25.2 m. As observed in the wet season, the logit-transformed soil ammonium-N (NH4Nt), soil nitrate-N (NO3Nt), soil organic carbon (SOCt) and total soil nitrogen (TSNt) were all found to be significantly correlated with FLUX30t (r = 0.57-0.71, p < 0.001). Three spatial interpolation methods (ordinary kriging, regression kriging and cokriging) were applied to estimate the spatial distribution of N2O emissions over the study area. Cokriging with NH4Nt and NO3Nt as covariables (r = 0.74 and RMSE = 1.18) outperformed ordinary kriging (r = 0.18 and RMSE = 1.74), regression kriging with the sample position as a predictor (r = 0.49 and RMSE = 1.55) and cokriging with SOCt as a covariable (r = 0.58 and RMSE = 1.44). The predictions of the three kriging interpolation methods for the total N2O emissions of 4.0 ha tea field ranged from 148.2 to 208.1 g N d-1, based on the 30 min snapshots obtained during the wet season. Our findings suggested that to accurately estimate the total N2O emissions over a region, the environmental variables (e.g., soil properties) and the current land use pattern (e.g., tea row transects in the present study) must be included in spatial interpolation. Additionally, compared with other kriging approaches, the cokriging prediction approach showed great advantages in being easily deployed and, more importantly, providing accurate regional estimation of N2O emissions from tea-planted soils.

Linking spatial patterns of soil redistribution traced with 137Cs and soil nutrients in a Mediterranean mountain agroecosystem (NE Spain)

NASA Astrophysics Data System (ADS)

Quijano, Laura; Gaspar, Leticia; Navas, Ana

2016-04-01

Mediterranean mountain agroecosystems are prone to soil loss mainly due to the accelerated erosion as a consequence of human induced changes from agriculture and grazing practices over the last centuries and the climatic conditions (i.e. irregular and scarce precipitations and drought periods). Soil erosion leads to soil degradation inducing the loss of soil functions. The progressive decline of soil functions thereof soil quality is associated to a decrease of soil productivity and can threat the sustainability of cultivated soils. The use of fallout 137Cs as a soil movement tracer provides useful data to identify areas where loss and gain of 137Cs occurs and that of soil. This study aims to address soil movement and soil nutrient dynamics closely related to the status of soil degradation. A rain-fed cereal field (1.6 ha) representative of Mediterranean mountain agricultural landscapes (42°25'41''N 1°13'8''W) was selected to examine the effects of soil redistribution processes on the spatial variability of soil organic carbon (SOC) and nitrogen (SON) and their relationships with soil properties and topographic characteristics. From the hydrological point of view, the field is isolated due to the effect of landscape features and man-made structures. Climate is continental Mediterranean with an average annual rainfall of 500 mm and soils are Calcisols. The reference inventories of 137Cs and soil nutrients were established from 21 soil samples collected in nearby undisturbed areas under typical Mediterranean vegetation cover. A total of 156 bulk soil samples (30-50 cm depth) and 156 topsoil samples (5 cm) were collected on a 10 m grid. 137Cs and soil nutrients loss and gain areas were identified by comparing the reference inventories with the values of inventories at the sampling points. A new approach to characterize and measure active (ACF) and stable (SCF) carbon fraction contents by using a dry combustion method based on the oxidation temperature of carbon fractions to analyze the SOC pool dynamics is presented in this study. A detailed field topographic survey and mapping of the spatial variability of soil properties and nutrient contents from soil analyses displayed similar spatial patterns of 137Cs and soil nutrients that also were directly and significantly correlated (p≤0.01). As much as 70% of the surface of the study field had lower values of 137Cs inventory indicating a predominance of soil loss linked to a generalized loss of soil nutrients. SOC gain was found in less than 1% of the study field and there was a large loss of SON compared to the undisturbed reference site. Higher and significant (p≤0.01) contents of soil nutrients were found in topsoil samples than in the bulk ones. Furthermore, there was an enrichment of the relative contribution of ACF to total SOC in sampling points where there was a 137Cs gain in both bulk and topsoil samples. Understanding patterns of soil nutrients can be useful for developing and implementing land management strategies to preserve soil quality in Mediterranean agricultural areas.

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.

Effects of soil spatial variability at the hillslope and catchment scales on characteristics of rainfall-induced landslides

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.

Characterization and analysis of pasture degradation in Rondonia using remote sensing

NASA Astrophysics Data System (ADS)

Numata, Izaya

2006-04-01

Although pasture degradation has been a regional concern in Amazonian ecosystems, our ability to characterize and monitor pasture degradation under different environmental and human-related conditions is still limited. This dissertation evaluated pasture degradation as it varied due to environmental and human factors across different scales by combining field measures, ancillary data, and remote sensing. To better understand the link between pasture nutrients and soil chemistry, samples were analyzed in the laboratory demonstrating that pasture soil fertility and grass nutrients varied significantly according to soil order. Pastures established on Alfisols, nutrient-rich soils, had higher levels of Phosphorus in soil and grass compared to pastures established on Oxisols and Ultisols. To evaluate remote sensing measures of pasture biophysical properties related to pasture degradation, remote sensing analysis focused on a variety of sensors that provide a range in spatial, spectral and temporal scales, including Landsat Thematic Mapper (TM), a field spectrometer, Hyperion, and the Moderate Resolution Imaging Spectroradiometer (MODIS). Of the measures derived from Landsat, degraded pastures were best characterized by high non-photosynthetic vegetation (NPV) and low shade fractions, while pastures with high biomass were characterized by high green vegetation and low NPV fractions. Absorption features calculated from hyperspectral spectra collected in the field, including water and ligno-cellulose absorption depth and area, provided the best estimates of field grass measures. Temporal MODIS Normalized Difference Vegetation Index (NDVI) data were used to characterize changes in pasture quality across the region and through time. Degraded pastures were characterized by low temporal NDVI variation and occurred in dry or very wet climate conditions and on nutrient poor soils. Productive pastures were characterized by high temporal NDVI variation, were predominantly found more in the central part of the state, and were located in areas with milder climate conditions and relatively more fertile soils. As a general trend of regional pasture change in Rondonia, the proportions of productive pastures decreased and degraded pastures increased as pastures aged. The results obtained in this dissertation will contribute to understanding pasture sustainability needs for the future of Rondonia and provide the first step in monitoring pasture degradation in the Amazon using remote sensing.

Parameterizing a Large-scale Water Balance Model in Regions with Sparse Data: The Tigris-Euphrates River Basins as an Example

NASA Astrophysics Data System (ADS)

Flint, A. L.; Flint, L. E.

2010-12-01

The characterization of hydrologic response to current and future climates is of increasing importance to many countries around the world that rely heavily on changing and uncertain water supplies. Large-scale models that can calculate a spatially distributed water balance and elucidate groundwater recharge and surface water flows for large river basins provide a basis of estimates of changes due to future climate projections. Unfortunately many regions in the world have very sparse data for parameterization or calibration of hydrologic models. For this study, the Tigris and Euphrates River basins were used for the development of a regional water balance model at 180-m spatial scale, using the Basin Characterization Model, to estimate historical changes in groundwater recharge and surface water flows in the countries of Turkey, Syria, Iraq, Iran, and Saudi Arabia. Necessary input parameters include precipitation, air temperature, potential evapotranspiration (PET), soil properties and thickness, and estimates of bulk permeability from geologic units. Data necessary for calibration includes snow cover, reservoir volumes (from satellite data and historic, pre-reservoir elevation data) and streamflow measurements. Global datasets for precipitation, air temperature, and PET were available at very large spatial scales (50 km) through the world scale databases, finer scale WorldClim climate data, and required downscaling to fine scales for model input. Soils data were available through world scale soil maps but required parameterization on the basis of textural data to estimate soil hydrologic properties. Soil depth was interpreted from geomorphologic interpretation and maps of quaternary deposits, and geologic materials were categorized from generalized geologic maps of each country. Estimates of bedrock permeability were made on the basis of literature and data on driller’s logs and adjusted during calibration of the model to streamflow measurements where available. Results of historical water balance calculations throughout the Tigris and Euphrates River basins will be shown along with details of processing input data to provide spatial continuity and downscaling. Basic water availability analysis for recharge and runoff is readily available from a determinisitic solar radiation energy balance model and a global potential evapotranspiration model and global estimates of precipitation and air temperature. Future climate estimates can be readily applied to the same water and energy balance models to evaluate future water availability for countries around the globe.

The infield varietu of available forms in the forest-steppe of western part Central Chernozemic region

NASA Astrophysics Data System (ADS)

Belik, Anton; Devyatova, Tatiana; Bozhko, Svetlana; Gorbunova, Yulia

2016-04-01

The infield varietu of available forms in the forest-steppe of western part Central Chernozemic region The Central Chernozemic region of Russia has been a region with a strong agricultural industry and determines the food security of the state by most part. The soil cover of the region is represented mainly by chernozems and is favorable for the cultivation of major crops and produce high crop yields. However, the high development of agriculture in the territory of Central Chernozemic region are led to the development of agrogenic degradation processes which impacts on the growth of the soil cover complexity and contrast, and as a consequence a significant infield variety of soil fertility and yields of major crops. In this regard, very promising direction in CChR is the development and practical application technologies of precision agriculture, which implies the spatial variety of soil fertility analysis within specific fields and work areas, especially the content of available forms of nutrients. The aim of our research was a study of the agro-ecological characteristics of the spatial variety of the content by available forms to plants of major nutrients in representative areas of sloping agricultural landscapes with forest-steppe chernozems in the western part of Central Chernozemic region of Russia. The research of infield variety by content of available forms of major nutrients are carried in the fields of Russian Research Institute of Agriculture and Protect the Soil from Erosion experimental and industrial farm in Medvensky district of Kursk region. The area characterized by a complex organization of relief. The soil cover is represented by full-profile typical (conventional and carbonate), leached chernozems. The growth of contrast of the soil cover are largely determined by the appearance of eroded soils of these analogues, as well as zoogenic dug and accumulative soils All of the studied areas with the forest-steppe chernozems were characterized by pronounced variation in the content of available forms of nitrogen, phosphorus and potassium. In the most varied contents of available phosphorus and potassium (coefficients of variation increase by 1.2 - 1.3 times as the complexity of the soil cover and reduced 1.3 - 1.6 times as reducing the area of the site and the growth detailed studies). The least within the fields of content of nitrogen are varied at its most high average grade. As the most important factors determining the spatial variety of the batteries for the phosphorus and potassium should be made kind of soil, the degree of erosion, the depth of the carbonates. The above factors the humus content is added the level of applied agricultural technologies and the history of land use within the studied areas for the nitrogen. Thus, the identification of significant infield variety in the content of available forms of nutrients in the forest-steppe chernozems is the result of processes of water erosion. In terms of slope forest-steppe agricultural landscapes of Central Chernozemic region of spatial variability of available forms of nitrogen, phosphorus and potassium is an important factor, which is limited the yields and causes the most promising application the technologies of precision agriculture.

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).

Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

NASA Astrophysics Data System (ADS)

Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

2010-05-01

The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented the change in soil surface structure during crusting. The laser data were also used to create digital surface models (DSM) of the soil states for visual comparison. This research has shown that aggregate breakdown and soil crusting can be shown quantitatively by a decrease in sill variance (silt soil: 11.67 (control) to 1.08 (after 90 mins rainfall)). Features present within semi-variograms were spatially linked to features at the soil surface, such as soil cracks, tillage lines and areas of deposition. Directional semi-variograms were used to provide a spatially orientated component, where the directional sill variance associated with a soil crack was shown to increase from 7.95 to 19.33. Periodicity within semi-variogram was also shown to quantify the spatial scale of soil cracking networks and potentially surface flowpaths; an average distance between soil cracks of 37 mm closely corresponded to the distance of 38 mm shown in the semi-variogram. The results provide a strong basis for the future retrieval of spatio-temporal variations in soil surface condition. Furthermore, the presence of process-based information on hydrological pathways within semi-variograms may work towards an inclusion of geostatisically-derived information in land surface models and the understanding of complex surface processes at different spatial scales.

On the spatial distribution of the transpiration and soil moisture of a Mediterranean heterogeneous ecosystem in water-limited conditions.

NASA Astrophysics Data System (ADS)

Curreli, Matteo; Corona, Roberto; Montaldo, Nicola; Albertson, John D.; Oren, Ram

2014-05-01

Mediterranean ecosystems are characterized by a strong heterogeneity, and often by water-limited conditions. In these conditions contrasting plant functional types (PFT, e.g. grass and woody vegetation) compete for the water use. Both the vegetation cover spatial distribution and the soil properties impact the soil moisture (SM) spatial distribution. Indeed, vegetation cover density and type affects evapotranspiration (ET), which is the main lack of the soil water balance in these ecosystems. With the objective to carefully estimate SM and ET spatial distribution in a Mediterranean water-limited ecosystem and understanding SM and ET relationships, an extended field campaign is carried out. The study was performed in a heterogeneous ecosystem in Orroli, Sardinia (Italy). The experimental site is a typical Mediterranean ecosystem where the vegetation is distributed in patches of woody vegetation (wild olives mainly) and grass. Soil depth is low and spatially varies between 10 cm and 40 cm, without any correlation with the vegetation spatial distribution. ET, land-surface fluxes and CO2 fluxes are estimated by an eddy covariance technique based micrometeorological tower. But in heterogeneous ecosystems a key assumption of the eddy covariance theory, the homogeneity of the surface, is not preserved and the ET estimate may be not correct. Hence, we estimate ET of the woody vegetation using the thermal dissipation method (i.e. sap flow technique) for comparing the two methodologies. Due the high heterogeneity of the vegetation and soil properties of the field a total of 54 sap flux sensors were installed. 14 clumps of wild olives within the eddy covariance footprint were identified as the most representative source of flux and they were instrumented with the thermal dissipation probes. Measurements of diameter at the height of sensor installation (height of 0.4 m above ground) were recorded in all the clumps. Bark thickness and sapwood depth were measured on several trees to obtain a generalized estimates of sapwood depth. The known of allometric relationships between sapwood area, diameter and canopy cover area within the eddy covariance footprint helped for the application of a reliable scaling procedure of the local sap flow estimates which are in a good agreement with the estimates of ET eddy covariance based. Soil moisture were also extensively monitored through 25 probes installed in the eddy covariance footprint. Results show that comparing eddy covariance and sap flow ET estimates eddy covariance technique is still accurate in this heterogeneous field, whereas the key assumption, surface homogeneity, is not preserved. Furthermore, interestingly wild olives still transpire at higher rates for the driest soil moisture conditions, confirming the hydraulic redistribution from soil below the roots, and from roots penetrating deep cracks in the underlying basalt parent rock.

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.

Monitoring and Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and In-situ Observations.

NASA Astrophysics Data System (ADS)

A, G.; Velicogna, I.; Kimball, J. S.; Kim, Y.; Colliander, A.; Njoku, E. G.

2015-12-01

We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE, in-situ groundwater measurements and atmospheric moisture data to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depth in relation to satellite based vegetation metrics, including vegetation greenness (NDVI) measures from MODIS and related higher order productivity (GPP) before, during and following the major drought events observed in the continental US for the past 14 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, NDVI and GPP. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics. In Texas, we find that surface SM and GRACE TWS agree with each other in general, and both capture the underlying water supply constraints to vegetation growth. Triggered by a transit increase in precipitation following the 2011 hydrological drought, vegetation productivity in Texas shows more sensitivity to surface SM than TWS. In the Great Plains, the correspondence between TWS and vegetation productivity is modulated by temperature-induced atmosphere moisture stress and by the coupling between surface soil moisture and groundwater through irrigation.

Mustiscaling Analysis applied to field Water Content through Distributed Fiber Optic Temperature sensing measurements

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.

Identifying change in spatial accumulation of soil salinity in an inland river watershed, China.

PubMed

Wang, Yugang; Deng, Caiyun; Liu, Yan; Niu, Ziru; Li, Yan

2018-04-15

Soil salinity accumulation is strong in arid areas and it has become a serious environmental problem. Knowledge of the process and spatial changes of accumulated salinity in soil can provide an insight into the spatial patterns of soil salinity accumulation. This is especially useful for estimating the spatial transport of soil salinity at the watershed scale. This study aimed to identify spatial patterns of salt accumulation in the top 20cm soils in a typical inland watershed, the Sangong River watershed in arid northwest China, using geostatistics, spatial analysis technology and the Lorenz curve. The results showed that: (1) soil salt content had great spatial variability (coefficient variation >1.0) in both in 1982 and 2015, and about 56% of the studied area experienced transition the degree of soil salt content from one class to another during 1982-2015. (2) Lorenz curves describing the proportions of soil salinity accumulation (SSA) identified that the boundary between soil salinity migration and accumulation regions was 24.3m lower in 2015 than in 1982, suggesting a spatio-temporal inequality in loading of the soil salinity transport region, indicating significant migration of soil salinity from the upstream to the downstream watershed. (3) Regardless of migration or accumulation region, the mean value of SSA per unit area was 0.17kg/m 2 higher in 2015 than 1982 (p<0.01) and the increasing SSA per unit area in irrigated land significantly increased by 0.19kg/m 2 compared with the migration region. Dramatic accumulation of soil salinity in all land use types was clearly increased by 0.29kg/m 2 in this agricultural watershed during the studied period in the arid northwest of China. This study demonstrates the spatial patterns of soil salinity accumulation, which is particularly useful for estimating the spatial transport of soil salinity at the watershed scale. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Soil Greenhouse Gas Emissions from a Subtropical Mangrove in Hong Kong

NASA Astrophysics Data System (ADS)

Lai, D. Y. F.; Xu, J.

2014-12-01

The concept of "blue carbon" has received increasing attention recently, which points to the potential role of vegetated coastal wetlands in carbon sequestration. Yet, the magnitude and controls of greenhouse gas emissions from coastal wetland ecosystems, especially mangroves in the subtropical regions, are still largely unknown. In this study, we conducted chamber measurements in the Mai Po Marshes Nature Reserve of Hong Kong at monthly intervals to characterize the spatial and temporal variability of the emission of greenhouse gases, including CO2, CH4 and N2O from mangrove soils, and examine the influence of environmental and biotic variables on greenhouse gas fluxes. We found the highest mean CH4 and N2O emissions in autumn and the highest CO2 flux in summer. Along the tidal gradient, we observed significantly higher CH4 and N2O emissions from the middle zones and landward zones, respectively, while no clear spatial variation of CO2 emissions was observed. There were significantly higher soil greenhouse gas emissions from sites dominated by Avicennia marina than those dominated by Kandelia obovata, which might be due to the presence of pneumatophores which facilitated gas transport. We found a significant, negative correlation between CH4 flux and soil NO3-N concentration, while CO2 flux was positively correlation with total Kjeldahl nitrogen content. Soil temperature was positively correlated with the emissions of all three greenhouse gases, while water table depth was positively and negatively correlated with CH4 and N2O emissions, respectively. Our findings demonstrate the high spatial and temporal variability of greenhouse gas emissions from mangrove soils which could be attributed in part to the differences in environmental conditions and dominant plant species.

Digital mapping of soil properties in Zala County, Hungary for the support of county-level spatial planning and land management

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Fodor, Nándor; Bakacsi, Zsófia; Szabó, József; Illés, Gábor

2014-05-01

The main objective of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project is to significantly extend the potential, how demands on spatial soil related information could be satisfied in Hungary. Although a great amount of soil information is available due to former mappings and surveys, there are more and more frequently emerging discrepancies between the available and the expected data. The gaps are planned to be filled with optimized DSM products heavily based on legacy soil data, which still represent a valuable treasure of soil information at the present time. Impact assessment of the forecasted climate change and the analysis of the possibilities of the adaptation in the agriculture and forestry can be supported by scenario based land management modelling, whose results can be incorporated in spatial planning. This framework requires adequate, preferably timely and spatially detailed knowledge of the soil cover. For the satisfaction of these demands in Zala County (one of the nineteen counties of Hungary), the soil conditions of the agricultural areas were digitally mapped based on the most detailed, available recent and legacy soil data. The agri-environmental conditions were characterized according to the 1:10,000 scale genetic soil mapping methodology and the category system applied in the Hungarian soil-agricultural chemistry practice. The factors constraining the fertility of soils were featured according to the biophysical criteria system elaborated for the delimitation of naturally handicapped areas in the EU. Production related soil functions were regionalized incorporating agro-meteorological modelling. The appropriate derivatives of a 20m digital elevation model were used in the analysis. Multitemporal MODIS products were selected from the period of 2009-2011 representing different parts of the growing season and years with various climatic conditions. Additionally two climatic data layers, the 1:100.000 Geological Map of Hungary and the map of groundwater depth were used as auxiliary environmental covariables. Various soil related information were mapped in three distinct sets: (i) basic soil properties determining agri-environmental conditions (soil type according to the Hungarian genetic classification, rootable depth, sand and clay content for the 1st and 2nd soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological and management scenarios. The applied method(s) for the spatial inference of specific themes was/were suitably selected: regression and classification trees for categorical data, indicator kriging for probabilistic management of criterion information; and typically regression kriging for quantitative data. Our paper will present the mapping processes themselves, the resulted maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and by the European Union with the co-financing of the European Social Fund (TÁMOP-4.2.2.A-11/1/KONV-2012-0013.).

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...

Chemical characterization and spatial distribution of PAHs and heavy hydrocarbons in rural sites of Campania Region, South Italy.

PubMed

Monaco, D; Riccio, A; Chianese, E; Adamo, P; Di Rosa, S; Fagnano, M

2015-10-01

In this paper, the behaviour and distribution patterns of heavy hydrocarbons and several polycyclic aromatic hydrocarbon (PAH) priority pollutants, as listed by the US Environmental Protection Agency, were evaluated in 891 soil samples. The samples were collected in three expected polluted rural sites in Campania (southern Italy) as part of the LIFE11 ECOREMED project, funded by the European Commission, to test innovative agriculture-based soil restoration techniques. These sites have been selected because they have been used for the temporary storage of urban and building waste (Teverola), subject to illicit dumping of unknown material (Trentola-Ducenta), or suspected to be polluted by metals due to agricultural practices (Giugliano). Chemical analysis of soil samples allowed the baseline pollution levels to be determined prior to any intervention. It was found that these areas can be considered contaminated for residential use, in accordance with Italian environmental law (Law Decree 152/2006). Statistical analysis applied to the data proved that average mean concentrations of heavy hydrocarbons could be as high as 140 mg/kg of dry soil with peaks of 700 mg/kg of dry soil, for the Trentola-Ducenta site; the median concentration of analytical results for hydrocarbon (HC) concentration for the Trentola-Ducenta and Giugliano sites was 63 and 73.4 mg/kg dry soil, respectively; for Teverola, the median level was 35 mg/kg dry soil. Some PAHs (usually benzo(a)pyrene) also exceeded the maximum allowed level in all sites. From the principal component analysis applied to PAH concentrations, it emerged that pollutants can be supposed to derive from a single source for the three sites. Diagnostic ratios calculated to determine possible PAH sources suggest petroleum combustion or disposal practice. Our sampling protocol also showed large dishomogeneity in soil pollutant spatial distribution, even at a scale as small as 3.3 m, indicating that variability could emerge at very short spatial scales.

Influence of Soil Heterogeneity on Mesoscale Land Surface Fluxes During Washita '92

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Jin, Hao

1998-01-01

The influence of soil heterogeneity on the partitioning of mesoscale land surface energy fluxes at diurnal time scales is investigated over a 10(exp 6) sq km domain centered on the Little Washita Basin, Oklahoma, for the period June 10 - 18, 1992. The sensitivity study is carried out using MM5/PLACE, the Penn State/NCAR MM5 model enhanced with the Parameterization for Land-Atmosphere-Cloud Exchange or PLACE. PLACE is a one-dimensional land surface model possessing detailed plant and soil water physics algorithms, multiple soil layers, and the capacity to model subgrid heterogeneity. A series of 12-hour simulations were conducted with identical atmospheric initialization and land surface characterization but with different initial soil moisture and texture. A comparison then was made of the simulated land surface energy flux fields, the partitioning of net radiation into latent and sensible heat, and the soil moisture fields. Results indicate that heterogeneity in both soil moisture and texture affects the spatial distribution and partitioning of mesoscale energy balance. Spatial averaging results in an overprediction of latent heat flux, and an underestimation of sensible heat flux. In addition to the primary focus on the partitioning of the land surface energy, the modeling effort provided an opportunity to examine the issue of initializing the soil moisture fields for coupled three-dimensional models. For the present case, the initial soil moisture and temperature were determined from off-line modeling using PLACE at each grid box, driven with a combination of observed and assimilated data fields.

Remote Sensing for Agriculture, Ecosystems and Hydrology III

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1999-01-01

The science need for remotely sensed soil moisture has been well established in the hydrologic, climate change and weather forecasting communities. In spite of this well documented science need there are currently no satellite missions flying or funded to make this very important geophysical measurement. There have been a number of experimental aircraft programs that have demonstrated the feasibility of using long wave microwave sensors for estimating soil moisture. Unfortunately, this science driver, soil moisture, imposes very difficult technical requirements for a satellite sensor system. Global soil moisture is driven by a spatial resolution on the order of 20 to 30 km and measurements need to be taken every two to three days to be useful to the science community. The principal sensor to accomplish the soil moisture measurements is an L- band passive microwave radiometer and achieving the spatial and temporal requirements requires a very large antenna. This paper describes the several alternatives to solve the very large antenna challenge and still meet the radiometer sensitivity requirement. The paper also discusses the alternatives considered to obtain the necessary ancillary data for characterizing the surface roughness, the surface temperature and the attenuation affects of vegetation needed to derive the geophysical parameter. Finally, the paper discusses proposed missions and how well they will meet the science requirements.

New generation of hydraulic pedotransfer functions for Europe

PubMed Central

Tóth, B; Weynants, M; Nemes, A; Makó, A; Bilas, G; Tóth, G

2015-01-01

A range of continental-scale soil datasets exists in Europe with different spatial representation and based on different principles. We developed comprehensive pedotransfer functions (PTFs) for applications principally on spatial datasets with continental coverage. The PTF development included the prediction of soil water retention at various matric potentials and prediction of parameters to characterize soil moisture retention and the hydraulic conductivity curve (MRC and HCC) of European soils. We developed PTFs with a hierarchical approach, determined by the input requirements. The PTFs were derived by using three statistical methods: (i) linear regression where there were quantitative input variables, (ii) a regression tree for qualitative, quantitative and mixed types of information and (iii) mean statistics of developer-defined soil groups (class PTF) when only qualitative input parameters were available. Data of the recently established European Hydropedological Data Inventory (EU-HYDI), which holds the most comprehensive geographical and thematic coverage of hydro-pedological data in Europe, were used to train and test the PTFs. The applied modelling techniques and the EU-HYDI allowed the development of hydraulic PTFs that are more reliable and applicable for a greater variety of input parameters than those previously available for Europe. Therefore the new set of PTFs offers tailored advanced tools for a wide range of applications in the continent. PMID:25866465

Temporal and spatial variations of soil carbon dioxide, methane, and nitrous oxide fluxes in a Southeast Asian tropical rainforest

NASA Astrophysics Data System (ADS)

Itoh, M.; Kosugi, Y.; Takanashi, S.; Hayashi, Y.; Kanemitsu, S.; Osaka, K.; Tani, M.; Nik, A. R.

2010-09-01

To clarify the factors controlling temporal and spatial variations of soil carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes, we investigated these gas fluxes and environmental factors in a tropical rainforest in Peninsular Malaysia. Temporal variation of CO2 flux in a 2-ha plot was positively related to soil water condition and rainfall history. Spatially, CO2 flux was negatively related to soil water condition. When CO2 flux hotspots were included, no other environmental factors such as soil C or N concentrations showed any significant correlation. Although the larger area sampled in the present study complicates explanations of spatial variation of CO2 flux, our results support a previously reported bipolar relationship between the temporal and spatial patterns of CO2 flux and soil water condition observed at the study site in a smaller study plot. Flux of CH4 was usually negative with little variation, resulting in the soil at our study site functioning as a CH4 sink. Both temporal and spatial variations of CH4 flux were positively related to the soil water condition. Soil N concentration was also related to the spatial distribution of CH4 flux. Some hotspots were observed, probably due to CH4 production by termites, and these hotspots obscured the relationship between both temporal and spatial variations of CH4 flux and environmental factors. Temporal variation of N2O flux and soil N2O concentration was large and significantly related to the soil water condition, or in a strict sense, to rainfall history. Thus, the rainfall pattern controlled wet season N2O production in soil and its soil surface flux. Spatially, large N2O emissions were detected in wet periods at wetter and anaerobic locations, and were thus determined by soil physical properties. Our results showed that, even in Southeast Asian rainforests where distinct dry and wet seasons do not exist, variation in the soil water condition related to rainfall history controlled the temporal variations of soil CO2 flux, CH4 uptake, and N2O emission. The soil water condition associated with soil hydraulic properties was also the important controlling factor of the spatial distributions of these gas fluxes.

Current advancements and challenges in soil-root interactions modelling

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Huber, Katrin; Abesha, Betiglu; Meunier, Felicien; Leitner, Daniel; Roose, Tiina; Javaux, Mathieu; Vanderborght, Jan; Vereecken, Harry

2015-04-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

Rates of root and organism growth, soil conditions, and temporal and spatial development of the rhizosphere.

PubMed

Watt, Michelle; Silk, Wendy K; Passioura, John B

2006-05-01

Roots growing in soil encounter physical, chemical and biological environments that influence their rhizospheres and affect plant growth. Exudates from roots can stimulate or inhibit soil organisms that may release nutrients, infect the root, or modify plant growth via signals. These rhizosphere processes are poorly understood in field conditions. We characterize roots and their rhizospheres and rates of growth in units of distance and time so that interactions with soil organisms can be better understood in field conditions. We review: (1) distances between components of the soil, including dead roots remnant from previous plants, and the distances between new roots, their rhizospheres and soil components; (2) characteristic times (distance(2)/diffusivity) for solutes to travel distances between roots and responsive soil organisms; (3) rates of movement and growth of soil organisms; (4) rates of extension of roots, and how these relate to the rates of anatomical and biochemical ageing of root tissues and the development of the rhizosphere within the soil profile; and (5) numbers of micro-organisms in the rhizosphere and the dependence on the site of attachment to the growing tip. We consider temporal and spatial variation within the rhizosphere to understand the distribution of bacteria and fungi on roots in hard, unploughed soil, and the activities of organisms in the overlapping rhizospheres of living and dead roots clustered in gaps in most field soils. Rhizosphere distances, characteristic times for solute diffusion, and rates of root and organism growth must be considered to understand rhizosphere development. Many values used in our analysis were estimates. The paucity of reliable data underlines the rudimentary state of our knowledge of root-organism interactions in the field.

Current Advancements and Challenges in Soil-Root Interactions Modelling

NASA Astrophysics Data System (ADS)

Schnepf, A.; Huber, K.; Abesha, B.; Meunier, F.; Leitner, D.; Roose, T.; Javaux, M.; Vanderborght, J.; Vereecken, H.

2014-12-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

Characterization of Soil Heterogeneity Across Scales in an Intensively Investigated Soil Volume

NASA Astrophysics Data System (ADS)

Patterson, Matthew; Gimenez, Daniel; Nemes, Attila; Dathe, Annette; French, Helen; Bloem, Esther; Koestel, John; Jarvis, Nick

2016-04-01

Heterogeneous water flow in undisturbed soils is a natural occurrence that is complex to model due to potential changes in hydraulic properties in soils over changes in space. The use of geophysical methods, such as Electrical Resistivity Tomography (ERT), can provide a minimally-invasive approximation of the spatial heterogeneity of the soil. This spatial distribution can then be combined with measured hydraulic properties to inform a model. An experiment was conducted on an Intensively Investigated Soil Volume (IISV), with dimensions of 2m x 1m x 0.8m, located in an agricultural field that is part of the Gryteland catchment in Ås, Norway. The location of the IISV was determined through surface ERT runs at two sequential resolutions. The first run was used to find an area of higher apparent electrical resistivity in a 23.5 x 11.5 m area with 0.5 m spacing. The second run measured apparent electrical resistivity in a 4.7 x 1 m area with 0.1 m spacing, from which the final IISV volume was derived. Distinct features found in the higher resolution run of the IISV, including a recent tire track from a harvester, were used as a spatial reference point for the installation of 20 pairs of TDR probes and tensiometers. The instruments measured water content, temperature and pressure potential at 10 minute intervals and ran continuously for a period of two weeks. After completion of the data collection the IISV was intensively sampled, with 30 samples taken for bulk density, 62 for hydraulic property measurements, and 20 to be used for both CT scanning and hydraulic property measurements. The measurement of hydraulic properties is ongoing and retention will be measured in the 0 - 100 cm range on a sand table, and from 100 - approx. 900 cm with an automated evaporation method. The formation of spatial clusters to represent the soil heterogeneity as relatively homogeneous units based on mesoscale properties like apparent electrical resistivity, bulk density, texture, in-situ measurements and image-derived properties at the microscale will be presented and discussed. Work combining the spatial clusters with estimated and measured hydraulic properties to inform the HYDRUS 3D model will also be discussed.

Comparison of spatial interpolation methods for soil moisture and its application for monitoring drought.

PubMed

Chen, Hui; Fan, Li; Wu, Wei; Liu, Hong-Bin

2017-09-26

Soil moisture data can reflect valuable information on soil properties, terrain features, and drought condition. The current study compared and assessed the performance of different interpolation methods for estimating soil moisture in an area with complex topography in southwest China. The approaches were inverse distance weighting, multifarious forms of kriging, regularized spline with tension, and thin plate spline. The 5-day soil moisture observed at 167 stations and daily temperature recorded at 33 stations during the period of 2010-2014 were used in the current work. Model performance was tested with accuracy indicators of determination coefficient (R 2 ), mean absolute percentage error (MAPE), root mean square error (RMSE), relative root mean square error (RRMSE), and modeling efficiency (ME). The results indicated that inverse distance weighting had the best performance with R 2 , MAPE, RMSE, RRMSE, and ME of 0.32, 14.37, 13.02%, 0.16, and 0.30, respectively. Based on the best method, a spatial database of soil moisture was developed and used to investigate drought condition over the study area. The results showed that the distribution of drought was characterized by evidently regional difference. Besides, drought mainly occurred in August and September in the 5 years and was prone to happening in the western and central parts rather than in the northeastern and southeastern areas.

Spatial and temporal patterns of spontaneous grass cover as a control measure of soil loss: a study case in an olive orchard microcatchment

NASA Astrophysics Data System (ADS)

Taguas, Encarnación; Vanderlinden, Karl; Pedrera-Parrilla, Aura; Giráldez, Juan V.; Gómez, Jose A.

2016-04-01

Spatial and temporal patterns of vegetal communities control local biogeophysical processes.. The use of cover crops and spontaneous grass cover as a soil erosion control measure is quite common, particularly in hilly agricultural areas. Spontaneous covers show usually irregular spatial and temporal patterns, resulting in a questionable efficiency and and unresolved management requirements. However, due to its zero cost, it is a helpful alternative for soil erosion control in marginal farms (Taguas et al., 2015). The main aim of this work was to characterize the spatial and temporal patterns of spontaneous grass cover in an olive orchard microcatchment to interpret its dependences on other physical features as well as its influence on soil loss control. The specific objectives were: i) to evaluate the relationships between the mean cover and the variables: accumulated precipitation, accumulated evapotranspiration and average minimum temperature for the preceding 5, 15, 30 and 60 days to the sampling date; ii) study the spatial aggregation degree of the cover, its temporal stability and its correlation with different topographical properties, the richness of species and the apparent electrical conductivity as a measure of soil variability; and iii) describe the influence of the cover on runoff and soil loss in the catchments. Cover percentage corresponding to spontaneous grass was evaluated on a seaonsal basis during 3 years (2011-2013), resulting in 12 surveys. A permanent and regular grid of 36 points covering the entire catchment (5-6 samples/ha) was used in each survey. At each location cover percentage was determined through image analyses. In order to explore the relations between cover percentage and meteorological variables, multiple linear regression was applied whereas the SADIE approach (Spatial analysis by distance indices; Perry, 1998) was used to describe possible spatial aggregation patterns and the correlation with features such as aspect, slope, drainage area, height, richness and apparent electrical conductivity. The mean annual cover percentage varied from 23% to 36% with a coefficient of variation of 57% and 6%, respectively. On the seasonal scale, the cover varied between 0.2% and 50% . Significant effects of accumulated precipitation during the precedubg 15 days on the cover percentage were detected. In addition, a permanent aggregated pattern of spontaneous grass was observed for different seasonal surveys with abundant preceding rainfall. No clear correlations were found with physical attributes with the exception of electrical conductivity (50 cm-depth). Finally, the differences found in the hydrological responses for similar events with different degrees of soil cover highlighted the role that spontaneous vegetation plays in the sediment discharge control during humid periods. REFERENCES: Perry, J. N., 1998. Measures of spatial pattern for counts. Ecology 79: 1008-1017. E. V. Taguas, C. Arroyo, A. Lora, G. Guzmán, K. Vanderlinden. J. A. Gómez. 2015. Exploring the linkage between spontaneous grass cover biodiversity and soil degradation in two olive orchard microcatchments with contrasting environmental and management conditions. SOIL, 1, 651-664.

Spatial disaggregation of complex soil map units at regional scale based on soil-landscape relationships

NASA Astrophysics Data System (ADS)

Vincent, Sébastien; Lemercier, Blandine; Berthier, Lionel; Walter, Christian

2015-04-01

Accurate soil information over large extent is essential to manage agronomical and environmental issues. Where it exists, information on soil is often sparse or available at coarser resolution than required. Typically, the spatial distribution of soil at regional scale is represented as a set of polygons defining soil map units (SMU), each one describing several soil types not spatially delineated, and a semantic database describing these objects. Delineation of soil types within SMU, ie spatial disaggregation of SMU allows improved soil information's accuracy using legacy data. The aim of this study was to predict soil types by spatial disaggregation of SMU through a decision tree approach, considering expert knowledge on soil-landscape relationships embedded in soil databases. The DSMART (Disaggregation and Harmonization of Soil Map Units Through resampled Classification Trees) algorithm developed by Odgers et al. (2014) was used. It requires soil information, environmental covariates, and calibration samples, to build then extrapolate decision trees. To assign a soil type to a particular spatial position, a weighed random allocation approach is applied: each soil type in the SMU is weighted according to its assumed proportion of occurrence in the SMU. Thus soil-landscape relationships are not considered in the current version of DSMART. Expert rules on soil distribution considering the relief, parent material and wetlands location were proposed to drive the procedure of allocation of soil type to sampled positions, in order to integrate the soil-landscape relationships. Semantic information about spatial organization of soil types within SMU and exhaustive landscape descriptors were used. In the eastern part of Brittany (NW France), 171 soil types were described; their relative area in the SMU were estimated, geomorphological and geological contexts were recorded. The model predicted 144 soil types. An external validation was performed by comparing predicted with effectively observed soil types derived from available soil maps at scale of 1:25.000 or 1:50.000. Overall accuracies were 63.1% and 36.2%, respectively considering or not the adjacent pixels. The introduction of expert rules based on soil-landscape relationships to allocate soil types to calibration samples enhanced dramatically the results in comparison with a simple weighted random allocation procedure. It also enabled the production of a comprehensive soil map, retrieving expected spatial organization of soils. Estimation of soil properties for various depths is planned using disaggregated soil types, according to the GlobalSoilmap.net specifications. Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., 2014. Disaggregating and harmonising soil map units through resampled classification trees. Geoderma 214, 91-100.

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).

Soils of wet valleys in the Larsemann Hills and Vestfold Hills oases (Princess Elizabeth Land, East Antarctica)

NASA Astrophysics Data System (ADS)

Mergelov, N. S.

2014-09-01

The properties and spatial distribution of soils and soil-like bodies in valleys of the coastal Larsemann Hills and Vestfold Hills oases—poorly investigated in terms of the soil areas of East Antarctica—are discussed. In contrast to Dry Valleys—large continental oases of Western Antarctica—the studied territory is characterized by the presence of temporarily waterlogged sites in the valleys. It is argued that the deficit of water rather than the low temperature is the major limiting factor for the development of living organisms and the pedogenesis on loose substrates. The moisture gradients in the surface soil horizons explain the spatial distribution of the different soils and biotic complexes within the studied valleys. Despite the permanent water-logging of the deep suprapermafrost horizons of most of the soils in the valleys, no gley features have been identified in them. The soils of the wet valleys in the Larsemann Hills oasis do not contain carbonates. They have a slightly acid or neutral reaction. The organic carbon and nitrogen contents are mainly controlled by the amount of living and dead biomass rather than by the humic substances proper. The larger part of the biomass is concentrated inside the mineral soil matrix rather than on the soil surface. The stresses caused by surface drying, strong winds, and ultraviolet radiation prevent the development of organisms on the surface of the soil and necessitate the search for shelter within the soil fine earth material (endoedaphic niche) or under the gravelly pavement (hypolithic niche). In the absence of higher plants, humified products of their decomposition, and rainwater that can wash the soil profile and upon the low content of silt and clay particles in the soil material, "classical" soil horizons are not developed. The most distinct (and, often, the only diagnosed) products of pedogenesis in these soils are represented by organomineral films on the surface of mineral particles.

Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination

PubMed Central

Ha, Hoehun; Rogerson, Peter A.; Olson, James R.; Han, Daikwon; Bian, Ling; Shao, Wanyun

2016-01-01

Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations. PMID:27649221

Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination.

PubMed

Ha, Hoehun; Rogerson, Peter A; Olson, James R; Han, Daikwon; Bian, Ling; Shao, Wanyun

2016-09-14

Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations.

Spatial pattern and heterogeneity of soil moisture along a transect in a small catchment on the Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan

2017-07-01

Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland > orchard > grassland > abandoned land > shrubland > forestland. Vertical distribution characteristics of soil moisture (0-500 cm) were similar among land use types. Highly significant (p < 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p > 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p > 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.

Mapping soil landscape as spatial continua: The Neural Network Approach

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing

2000-03-01

A neural network approach was developed to populate a soil similarity model that was designed to represent soil landscape as spatial continua for hydroecological modeling at watersheds of mesoscale size. The approach employs multilayer feed forward neural networks. The input to the network was data on a set of soil formative environmental factors; the output from the network was a set of similarity values to a set of prescribed soil classes. The network was trained using a conjugate gradient algorithm in combination with a simulated annealing technique to learn the relationships between a set of prescribed soils and their environmental factors. Once trained, the network was used to compute for every location in an area the similarity values of the soil to the set of prescribed soil classes. The similarity values were then used to produce detailed soil spatial information. The approach also included a Geographic Information System procedure for selecting representative training and testing samples and a process of determining the network internal structure. The approach was applied to soil mapping in a watershed, the Lubrecht Experimental Forest, in western Montana. The case study showed that the soil spatial information derived using the neural network approach reveals much greater spatial detail and has a higher quality than that derived from the conventional soil map. Implications of this detailed soil spatial information for hydroecological modeling at the watershed scale are also discussed.

Spatial distribution of polychlorinated dibenzo-p-dioxins and dibenzo-furans (PCDDs/Fs) in dust, soil, sediment and health risk assessment from an intensive electronic waste recycling site in Southern China.

PubMed

Hu, Jianfang; Xiao, Xiao; Peng, Ping'an; Huang, Weilin; Chen, Deyi; Cai, Ying

2013-10-01

Workshop dust, soil and sediment samples were collected to investigate the level and spatial distribution of PCDDs/Fs at an intensive electronic waste (e-waste) recycling site in Southern China, and also to characterize the dioxin emission in different e-waste recycling procedures. The concentrations of total PCDDs/Fs ranged from 1866 to 234292 ng kg(-1) for the dust samples, from 3187 to 63998 ng kg(-1) dry wt for the top soils, and 33718 ng kg(-1) for the surface sediment. All the samples were characterized by abnormally high concentrations of OCDD and an extremely low portion of PCDFs. Different e-waste recycling procedures may generate different congener profiles. Open burning and dismantling were the two procedures emitting relatively higher concentrations of PCDDs/Fs in this case, indicating that low-tech recycling operations were one of the major contributors of PCDDs/Fs to the environment. The variation and distinction of the concentrations and homologue/congener profiles among different environmental matrices reveal the characteristics of contaminant environmental behavior and fate during the transportation from "source" to "sink". Daily intake of PCDDs/Fs through soil ingestion and dermal absorption was negligible, but the rough estimated total PCDD/F intake dose far exceeded the tolerance daily intake value of 4 pg-TEQ per kg per day recommended by WHO, indicating that residents in Longtang were at a high risk of exposure to dioxins, especially children.

Spatial heterogeneity of subsurface soil texture drives the landscape-scale pattern of woody patches in a subtropical savanna

USDA-ARS?s Scientific Manuscript database

In the Rio Grande Plains of southern Texas, subtropical savanna vegetation is characterized by a two-phase pattern consisting of discrete woody patches embedded within a C4 grassland matrix. Prior trench transect studies have suggested that, on upland portions of the landscape, large woody patches (...

Fire metrology: Current and future directions in physics-based measurements

Treesearch

Robert L. Kremens; Alistair M.S. Smith; Matthew B. Dickinson

2010-01-01

The robust evaluation of fire impacts on the biota, soil, and atmosphere requires measurement and analysis methods that can characterize combustion processes across a range of temporal and spatial scales. Numerous challenges are apparent in the literature. These challenges have led to novel research to quantify the 1) structure and heterogeneity of the pre-fire...

Contamination and spatial variation of heavy metals in the soil-rice system in Nanxun County, Southeastern China.

PubMed

Zhao, Keli; Fu, Weijun; Ye, Zhengqian; Zhang, Chaosheng

2015-01-28

There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%). The spatial distribution of copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd) in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones.

Contamination and Spatial Variation of Heavy Metals in the Soil-Rice System in Nanxun County, Southeastern China

PubMed Central

Zhao, Keli; Fu, Weijun; Ye, Zhengqian; Zhang, Chaosheng

2015-01-01

There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%). The spatial distribution of copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd) in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones. PMID:25635917

Bioaccessible Porosity in Soil Aggregates and Implications for Biodegradation of High Molecular Weight Petroleum Compounds.

PubMed

Akbari, Ali; Ghoshal, Subhasis

2015-12-15

We evaluated the role of soil aggregate pore size on biodegradation of essentially insoluble petroleum hydrocarbons that are biodegraded primarily at the oil-water interface. The size and spatial distribution of pores in aggregates sampled from biodegradation experiments of a clayey, aggregated, hydrocarbon-contaminated soil with relatively high bioremediation end point were characterized by image analyses of X-ray micro-CT scans and N2 adsorption. To determine the bioaccessible pore sizes, we performed separate experiments to assess the ability of hydrocarbon degrading bacteria isolated from the soil to pass through membranes with specific sized pores and to access hexadecane (model insoluble hydrocarbon). Hexadecane biodegradation occurred only when pores were 5 μm or larger, and did not occur when pores were 3 μm and smaller. In clayey aggregates, ∼ 25% of the aggregate volume was attributed to pores larger than 4 μm, which was comparable to that in aggregates from a sandy, hydrocarbon-contaminated soil (~23%) scanned for comparison. The ratio of volumes of inaccessible pores (<4 μm) to bioaccessible pores (>4 μm) in the clayey aggregates was 0.32, whereas in the sandy aggregates it was approximately 10 times lower. The role of soil microstructure on attainable bioremediation end points could be qualitatively assessed in various soils by the aggregate characterization approach outlined herein.

Trends in Soil Moisture Reflect More Than Slope Position: Soils on San Cristóbal Island, Galápagos as a Case Study

NASA Astrophysics Data System (ADS)

Percy, M.; Singha, K.; Benninger, L. K.; Riveros-Iregui, D. A.; Mirus, B. B.

2015-12-01

The spatial and temporal distribution of soil moisture in tropical critical zones depends upon a number of variables including topographic position, soil texture, overlying vegetation, and local microclimates. We investigate the influences on soil moisture on a tropical basaltic island (San Cristóbal, Galápagos) across a variety of microclimates during the transition from the wetter to the drier season. We used multiple approaches to characterize spatial and temporal patterns in soil moisture at four sites across microclimates ranging from arid to very humid. The microclimates on San Cristóbal vary with elevation, so our monitoring includes two sites in the transitional zone at lower elevations, one in the humid zone at moderate elevations, and one in the very humid zone in higher elevations. We made over 250 near-surface point measurements per site using a Hydrosense II probe, and estimated the lateral variability in soil moisture across each site with an EM-31 electrical conductivity meter. We also monitored continuous time-series of in-situ soil moisture dynamics using three nested TDR probes collocated with meteorological stations at each of the sites. Preliminary analysis indicates that soils in the very humid zone have lower electrical conductivities across all the hillslopes as compared to the humid and transitional zones, which suggests that additional factors beyond climate and slope position are important. While soil texture across the very humid site is fairly uniform, variations in vegetation have a strong control on soil moisture patterns. At the remaining sites the vegetation patterns also have a very strong local influence on soil moisture, but correlation between the depth to clay layers and soil moisture patterns suggests that mineralogy is also important. Our findings suggest that the microclimatic setting is a crucial consideration for understanding relations between vegetation, soil texture, and soil-moisture dynamics in tropical critical zones.

Characterizing spatiotemporal dynamics of methane emissions from rice paddies in Northeast China from 1990 to 2010.

PubMed

Zhang, Yuan; Su, Shiliang; Zhang, Feng; Shi, Runhe; Gao, Wei

2012-01-01

Rice paddies have been identified as major methane (CH(4)) source induced by human activities. As a major rice production region in Northern China, the rice paddies in the Three-Rivers Plain (TRP) have experienced large changes in spatial distribution over the recent 20 years (from 1990 to 2010). Consequently, accurate estimation and characterization of spatiotemporal patterns of CH₄ emissions from rice paddies has become an pressing issue for assessing the environmental impacts of agroecosystems, and further making GHG mitigation strategies at regional or global levels. Integrating remote sensing mapping with a process-based biogeochemistry model, Denitrification and Decomposition (DNDC), was utilized to quantify the regional CH(4) emissions from the entire rice paddies in study region. Based on site validation and sensitivity tests, geographic information system (GIS) databases with the spatially differentiated input information were constructed to drive DNDC upscaling for its regional simulations. Results showed that (1) The large change in total methane emission that occurred in 2000 and 2010 compared to 1990 is distributed to the explosive growth in amounts of rice planted; (2) the spatial variations in CH₄ fluxes in this study are mainly attributed to the most sensitive factor soil properties, i.e., soil clay fraction and soil organic carbon (SOC) content, and (3) the warming climate could enhance CH₄ emission in the cool paddies. The study concluded that the introduction of remote sensing analysis into the DNDC upscaling has a great capability in timely quantifying the methane emissions from cool paddies with fast land use and cover changes. And also, it confirmed that the northern wetland agroecosystems made great contributions to global greenhouse gas inventory.

Characterizing Spatiotemporal Dynamics of Methane Emissions from Rice Paddies in Northeast China from 1990 to 2010

PubMed Central

Zhang, Yuan; Su, Shiliang; Zhang, Feng; Shi, Runhe; Gao, Wei

2012-01-01

Background Rice paddies have been identified as major methane (CH4) source induced by human activities. As a major rice production region in Northern China, the rice paddies in the Three-Rivers Plain (TRP) have experienced large changes in spatial distribution over the recent 20 years (from 1990 to 2010). Consequently, accurate estimation and characterization of spatiotemporal patterns of CH4 emissions from rice paddies has become an pressing issue for assessing the environmental impacts of agroecosystems, and further making GHG mitigation strategies at regional or global levels. Methodology/Principal Findings Integrating remote sensing mapping with a process-based biogeochemistry model, Denitrification and Decomposition (DNDC), was utilized to quantify the regional CH4 emissions from the entire rice paddies in study region. Based on site validation and sensitivity tests, geographic information system (GIS) databases with the spatially differentiated input information were constructed to drive DNDC upscaling for its regional simulations. Results showed that (1) The large change in total methane emission that occurred in 2000 and 2010 compared to 1990 is distributed to the explosive growth in amounts of rice planted; (2) the spatial variations in CH4 fluxes in this study are mainly attributed to the most sensitive factor soil properties, i.e., soil clay fraction and soil organic carbon (SOC) content, and (3) the warming climate could enhance CH4 emission in the cool paddies. Conclusions/Significance The study concluded that the introduction of remote sensing analysis into the DNDC upscaling has a great capability in timely quantifying the methane emissions from cool paddies with fast land use and cover changes. And also, it confirmed that the northern wetland agroecosystems made great contributions to global greenhouse gas inventory. PMID:22235268

Environmental impacts on the evapotranspiration of an water limited and heterogeneous Mediterranean ecosystem.

NASA Astrophysics Data System (ADS)

Mackay, D. S.; Ewers, B. E.; Sperry, J. S.; Frank, J. M.; Reed, D. E.

2014-12-01

Mediterranean water limited ecosystems are characterized by an heterogeneous spatial distribution of different plant functional types (PFT), such as grass and trees, competing for water use. Typically, during the dry summers, these ecosystems are characterized by a simple dual PFTs system with strong-resistant woody vegetation and bare soil, since grass died. The coupled use of sap flow measurements and eddy covariance technique is essential to estimate Evapotransiration (ET) in an heterogeneous ecosystem. An eddy covariance - micrometeorological tower has been installed since 2003 and 33 thermo-dissipation probes based on the Granier technique have installed at the Orroli site in Sardinia (Italy). The site landscape is a mixture of Mediterranean patchy vegetation types: wild olives, different shrubs and herbaceous species, which died during the summer. The sensors have been installed at the Orroli site into 15 wild olives clumps with different characteristics in terms of tree size, exposition to wind and solar radiation and soil depth. A network of 30 soil moisture sensors has also been installed for monitoring soil moisture spatial and temporal dynamics and their correlation with trees. Sap flow measurements show the significantly impacts on ET of soil moisture, radiation, vapor pressure deficit (VPD) and interestingly of tree position into the clump, showing double rates for the trees inside the wild olive clumps. The sap flow sensor outputs are analyzed for estimating innovative allometric relationships between sapwood area, diameter, canopy cover area, which are needed for the correct upscale of the local tree measurements to the site plot larger scale. Finally using an innovative scaling procedure, the sap-flow transpiration at field scale have been compared to the eddy covariance ET, showing the approximation of the eddy covariance technique. Finally the impact of environmental factors on ET for different soil depth and tree position is demonstrated.

Environmental impacts on the evapotranspiration of an water limited and heterogeneous Mediterranean ecosystem.

NASA Astrophysics Data System (ADS)

Montaldo, N.; Curreli, M.; Corona, R.; Oren, R.

2015-12-01

Mediterranean water limited ecosystems are characterized by an heterogeneous spatial distribution of different plant functional types (PFT), such as grass and trees, competing for water use. Typically, during the dry summers, these ecosystems are characterized by a simple dual PFTs system with strong-resistant woody vegetation and bare soil, since grass died. The coupled use of sap flow measurements and eddy covariance technique is essential to estimate Evapotransiration (ET) in an heterogeneous ecosystem. An eddy covariance - micrometeorological tower has been installed since 2003 and 33 thermo-dissipation probes based on the Granier technique have installed at the Orroli site in Sardinia (Italy). The site landscape is a mixture of Mediterranean patchy vegetation types: wild olives, different shrubs and herbaceous species, which died during the summer. The sensors have been installed at the Orroli site into 15 wild olives clumps with different characteristics in terms of tree size, exposition to wind and solar radiation and soil depth. A network of 30 soil moisture sensors has also been installed for monitoring soil moisture spatial and temporal dynamics and their correlation with trees. Sap flow measurements show the significantly impacts on ET of soil moisture, radiation, vapor pressure deficit (VPD) and interestingly of tree position into the clump, showing double rates for the trees inside the wild olive clumps. The sap flow sensor outputs are analyzed for estimating innovative allometric relationships between sapwood area, diameter, canopy cover area, which are needed for the correct upscale of the local tree measurements to the site plot larger scale. Finally using an innovative scaling procedure, the sap-flow transpiration at field scale have been compared to the eddy covariance ET, showing the approximation of the eddy covariance technique. Finally the impact of environmental factors on ET for different soil depth and tree position is demonstrated.

[Spatial heterogeneity and influencing factors of soil phosphorus concentration in a mid-subtropical Choerospondias axillaris deciduous broad-leaved forest, China.

PubMed

Hu, Rui Bin; Fang, Xi; Xiang, Wen Hua; Jiang, Fang; Lei, Pi Feng; Zhao, Li Juan; Zhu, Wen Juan; Deng, Xiang Wen

2016-03-01

In order to investigate spatial variations in soil phosphorus (P) concentration and the influencing factors, one permanent plot of 1 hm 2 was established and stand structure was surveyed in Choerospondias axillaries deciduous broadleaved forest in Dashanchong Forest Park in Changsha County, Hunan Province, China. Soil samples were collected with equidistant grid point sampling method and soil P concentration and its spatial variation were analyzed by using geo-statistics and geographical information system (GIS) techniques. The results showed that the variations of total P and available P concentrations in humus layer and in the soil profile at depth of 0-10, 10-20 and 20-30 cm were moderate and the available P showed higher variability in a specific soil layer compared with total P. Concentrations of total P and available P in soil decreased, while the variations increased with the increase in soil depth. The total P and available P showed high spatial autocorrelation, primarily resulted from the structural factors. The spatial heterogeneity of available P was stronger than that of total P, and the spatial autocorrelation ranges of total P and available P varied from 92.80 to 168.90 m and from 79.43 to 106.20 m in different soil layers, respectively. At the same soil depth, fractal dimensions of total P were higher than that of available P, with more complex spatial pattern, while available P showed stronger spatial correlation with stronger spatial structure. In humus layer and soil depths of 0-10, 10-20 and 20-30 cm, the spatial variation pattern of total P and available P concentrations showed an apparent belt-shaped and spot massive gradient change. The high value appeared at low elevation and valley position, and the low value appeared in the high elevation and ridge area. The total P and available P concentrations showed significantly negative correlation with elevation and litter, but the relationship with convexity, species, numbers and soil pH was not significant. The total P and available P exhibited significant positive correlations with soil organic carbon (SOC), total nitrogen concentration, indicating the leaching characteristics of soil P. Its spatial variability was affected by many interactive factors.

Spatial regression between soil surface elevation, water storage in root zone and biomass productivity of alfalfa within an irrigated field

NASA Astrophysics Data System (ADS)

Zeyliger, Anatoly; Ermolaeva, Olga

2014-05-01

Efficiency of water use for the irrigation purposes is connected to the variety of circumstances, factors and processes appearing along the transportation path of water from its sources to the root zone of the plant. Water efficiency of agricultural irrigation is connected with variety of circumstances, the impacts and the processes occurring during the transportation of water from water sources to plant root zone. Agrohydrological processes occur directly at the irrigated field, these processes linked to the infiltration of the applied water subsequent redistribution of the infiltrated water within the root zone. One of them are agrohydrological processes occurring directly on an irrigated field, connected with infiltration of water applied for irrigation to the soil, and the subsequent redistribution of infiltrated water in the root zone. These processes have the strongly pronounced spatial character depending on the one hand from a spatial variation of some hydrological characteristics of soils, and from other hand with distribution of volume of irrigation water on a surface of the area of an irrigated field closely linked with irrigation technology used. The combination of water application parameters with agrohydrological characteristics of soils and agricultural vegetation in each point at the surface of an irrigated field leads to formation of a vector field of intensity of irrigation water. In an ideal situation, such velocity field on a soil surface should represent uniform set of vertically directed collinear vectors. Thus values of these vectors should be equal to infiltration intensities of water inflows on a soil surface. In soil profile the field of formed intensities of a water flow should lead to formation in it of a water storage accessible to root system of irrigated crops. In practice this ideal scheme undergoes a lot of changes. These changes have the different nature, the reasons of occurrence and degree of influence on the processes connected with formation of water flow and water storage. The major changes are formed as a result of imposing of the intensity fields on a soil surface and its field capillary infiltration rate. Excess of the first intensity over the second in each point of soil surface leads to formation of a layer of intensity of water not infiltrated in soil. Thus generate the new field of vectors of intensity which can consist of vertically directed vector of speed of evaporation, a quasi horizontal vector of intensity of a surface water flow and quasi vertical vector of intensity of a preferential flow directed downwards. Principal cause of excess of irrigation water application intensity over capillary infiltration rate can be on the one hand spatial non-uniformity of irrigation water application, and with other spatial variability of capillary infiltration rate, connected with spatial variability of water storage in the top layers of soil. As a result the spatial redistribution of irrigation water over irrigated filed forms distortions of ideal model of irrigation water storage in root zone of soil profile. The major differences consist in increasing of water storage in the depressions of a relief of an irrigated field and accordingly in their reduction on elevated zones of a relief, as well as losses of irrigation water outside of boundaries of a root zone of an irrigated field, in vertical, and horizontal directions. One of key parameters characterizing interaction between irrigation technology and soil state an irrigated field are intensity of water application, intensity and volume of a capillary infiltration, the water storage in root zone at the moment of infiltration starting and a topography of an irrigated field. Fnalyzing of spatial links between these characteristics a special research had been carried out on irrigated by sprinkler machine called Fregate at alfalfa field during the summer of 2012. This research carried out at experimental farm of the research institute VolgNIIGiM situated at a left bank of Volga River of Saratov Region of Russia (N51.384650°, E46.055890°). The digital elevation model of soil surface has been created, as well as monitoring of spatial water storage with EM 38 device and of a biomass were carried out. Layers of corresponding spatial data have been created and analyzed. The carried out analysis of spatial regresses has shown presence of links between productivity of a biomass of a alfalfa, water storage and topography. The obtained results shows the significance to include spatial characteristics of the topography and water storage to the irrigation models, as well as adaptation of sprinkler technology to allow differentiate the volume and rate of the applied water within the field. Special attention should be done to quantify relationships between uniform technology of water application by sprinkler and spatial nonuniformity of moisture storage (zoning of high soil moisture in depressions) in soil and as consequence of infiltration capacity.

Drive by Soil Moisture Measurement: A Citizen Science Project

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.

2017-12-01

Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.

Mapping soil organic carbon content and composition across Australia to assess vulnerability to climate change

NASA Astrophysics Data System (ADS)

Viscarra Rossel, R. A.

2015-12-01

We can effectively monitor soil condition—and develop sound policies to offset the emissions of greenhouse gases—only with accurate data from which to define baselines. Currently, estimates of soil organic C for countries or continents are either unavailable or largely uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of organic C content and composition in the soil of Australia. The composition of soil organic C may be characterized by chemical separation or physical fractionation based on either particle size or particle density (Skjemstad et al., 2004; Gregorich et al., 2006; Kelleher&Simpson, 2006; Zimmermann et al., 2007). In Australia, for example, Skjemstad et al. (2004) used physical separation of soil samples into 50-2000 and <50-μm particle-size fractions followed by the measurement of char-carbon using solid-state 13C nuclear magnetic resonance (NMR) spectroscopy, giving the three OC pools, particulate organic carbon (POC), humic organic carbon (HOC) and resistant organic carbon (ROC; charcoal or char-carbon). We assembled and harmonized data from several sources to produce the most comprehensive set of data on the current stock of organic C in soil of the continent. Using them, we have produced a fine spatial resolution baseline map of organic C, POC, HOC and ROC at the continental scale. In this presentation I will describe how we made the maps and how we use them to assess the vulnerability of soil organic C to for instance climate change.

Field infiltration measurements in grassed roadside drainage ditches: Spatial and temporal variability

NASA Astrophysics Data System (ADS)

Ahmed, Farzana; Gulliver, John S.; Nieber, J. L.

2015-11-01

Roadside drainage ditches (grassed swales) are an attractive stormwater control measure (SCM) since they can reduce runoff volume by infiltrating water into the soil, filter sediments and associated pollutants out of the water, and settle solids onto the soil surface. In this study a total of 722 infiltration measurements were collected in five swales located in Twin-Cities, MN and one swale located in Madison, WI to characterize the field-saturated hydraulic conductivity (Kfs) derived from the infiltration measurements of these swales. Measurements were taken with a falling head device, the Modified Philip Dunne (MPD) infiltrometer, which allows the collection of simultaneous infiltration measurements at multiple locations with several infiltrometers. Field-saturated hydraulic conductivity was higher than expected for different soil texture classes. We hypothesize that this is due to plant roots creating macropores that break up the soil for infiltration. Statistical analysis was performed on the Kfs values to analyze the effect of initial soil moisture content, season, soil texture class and distance in downstream direction on the geometric mean Kfs value of a swale. Because of the high spatial variation of Kfs in the same swale no effect of initial soil moisture content, season and soil texture class was observed on the geometric mean Kfs value. But the distance in downstream direction may have positive or negative effect on the Kfs value. An uncertainty analysis on the Kfs value indicated that approximately twenty infiltration measurements is the minimum number to obtain a representative geometric mean Kfs value of a swale that is less than 350 m long within an acceptable level of uncertainty.

Spatial variability assessment of soil nutrients in an intense agricultural area, a case study of Rugao County in Yangtze River Delta Region, China

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.

Seedling establishment and physiological responses to temporal and spatial soil moisture changes

Treesearch

Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos

2016-01-01

In many forests of the world, the summer season (temporal element) brings drought conditions causing low soil moisture in the upper soil profile (spatial element) - a potentially large barrier to seedling establishment. We evaluated the relationship between initial seedling root depth, temporal and spatial changes in soil moisture during drought after...

Spatial variability of soil magnetic susceptibility in an agricultural field located in Eastern Ukraine

NASA Astrophysics Data System (ADS)

Menshov, Oleksandr; Pereira, Paulo; Kruglov, Oleksandr

2015-04-01

Magnetic susceptibility (MS) have been used to characterize soil properties. It gives an indirect information about heavy metals content and degree of human impacts on soil contamination derived from atmospheric pollution (Girault et al., 2011). This method is inexpensive in relation to chemical analysis and very useful to track soil pollution, since several toxic components deposited on soil surface are rich in particulates produced by oxidation processes (Boyko et al., 2004; Morton-Bernea et al., 2009). Thus, identify the spatial distribution of MS is of major importance, since can give an indirect information of high metals content (Dankoub et al., 2012). This allows also to distinguish the pedogenic and technogenic origin magnetic signal. For example Ukraine chernozems contain fine-grained oxidized magnetite and maghemite of pedogenic origin formed by weathering of the parent material (Jeleńska et al., 2004). However, to a correct understanding of variables distribution, the identification of the most accurate interpolation method is fundamental for a better interpretation of map information (Pereira et al., 2013). The objective of this work is to study the spatial variability of soil MS in an agricultural fields located in the Tcherkascy Tishki area (50.11°N, 36.43 °E, 162 m a.s.l), Ukraine. Soil MS was measured in 77 sampling points in a north facing slope. To estimate the best interpolation method, several interpolation methods were tested, as inverse distance to a weight (IDW) with the power of 1,2,3,4 and 5, Local Polynomial (LP) with the power of 1 and 2, Global Polynomial (GP), radial basis functions - spline with tension (SPT), completely regularized spline (CRS), multiquatratic (MTQ), inverse multiquatratic (IMTQ), and thin plate spline (TPS) - and some geostatistical methods as, ordinary kriging (OK), Simple Kriging (SK) and Universal Kriging (UK), used in previous works (Pereira et al., 2014). On average, the soil MS of the studied plot had 686.05 MS×10-9 m3/kg, and a minimum and a maximum value of 499.33 and 862.27 MS×10-9 m3/kg respectively. The standard deviation was 85.62 and the coefficient of variation 12.48%. This shows that the spatial variability of soil MS was low. The Global Morans I index was of 0.841, a z-score of 7.741 with a p<0.001, indicating that soil MS had a clustered pattern. The variogram results showed that the gaussian model was the the best fitted. The nugget effect was 0.1007. the sill 0.9905 and the nugget/sill ratio of 0.10, which shows that soil MS has a strong spatial dependency. The results of the interpolation tests showed that the errors distribution followed the normal distribution, the average predicted values were similar to the observed and the correlation between these two distributions was high (between 0.85-0.90) in all the cases. The method that predicted better soil MS was LP2 and the less accurate was SK. Soil MS presented high values in the southwestern part and low in the northeast area of the plot. It is clearly observed a increase of soil MS from the top of the slope to the bottom. Acknowledgments RECARE (Preventing and Remediating Degradation of Soils in Europe Through Land Care, FP7-ENV-2013-TWO STAGE), funded by the European Commission; and for the COST action ES1306 (Connecting European connectivity research). References Boyko, T., Scholger, R., Stanjek, H., MAGPROX team (2004) Topsoil magnetic suseptibility mapping as a tool for pollution monitoring: Repetability of in situ measurments. Journal of Applied Geophysics, 55, 249-259. Dankoub, Z., Ayoubi, S., Khademi, H., Sheng-Gao, L. (2012) Spatial distribution of magnetic properties and selected heavy metals in calcareous soils as affected by land use in the Isfahan Region, Central Iran. Pedosphere, 22, 33-47. Girault, F., Poitou, C., Perrier, F., Koirala, B.P., Bhattarai, M. (2011) Soil characterization using patterns of magnetic susceptibility versus effective radimu concentration. Natural Hazards Earth System Science, 11, 2285-2293. Jeleńska, M., Hasso-Agopsowicz, A., Kopcewicz, B., Sukhorada, A., Tyamina, K., Kądziałko-Hofmokl, M., Matviishina, Z. (2004) Magnetic properties of the profiles of polluted and non-polluted soils. A case study from Ukraine. Geophys. J. Int., 159, 104-116. Morton-Bernea, O., Hernandez, E., Martinez-Pichardo, E., Soler-Arechalde, A.M., Santa Cruz, R.L., Gonzalez-Hernandez, G., Beramendi-Orosco, L., Urritia-Fucugaushi, J. (2009) Mexico city topsoils: Heavy metals vs. magnetic susceptibility. Geoderma, 151, 121-125. Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. 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., Jordan, A. Burguet, M. (2013) Spatial models for monitoring the spatio-temporal evolution of ashes after fire - a case study of a burnt grassland in Lithuania, Solid Earth, 4, 153-165.

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Adapting the Caesium-137 technique to document soil redistribution rates associated with traditional cultivation practices in Haiti.

PubMed

Velasco, H; Astorga, R Torres; Joseph, D; Antoine, J S; Mabit, L; Toloza, A; Dercon, G; Walling, Des E

2018-03-01

Large-scale deforestation, intensive land use and unfavourable rainfall conditions are responsible for significant continuous degradation of the Haitian uplands. To develop soil conservation strategies, simple and cost-effective methods are needed to assess rates of soil loss from farmland in Haiti. The fallout radionuclide caesium-137 ( 137 Cs) provides one such means of documenting medium-term soil redistribution rates. In this contribution, the authors report the first use in Haiti of 137 Cs measurements to document soil redistribution rates and the associated pattern of erosion/sedimentation rates along typical hillslopes within a traditional upland Haitian farming area. The local 137 Cs reference inventory, measured at an adjacent undisturbed flat area, was 670 Bq m -2 (SD = 100 Bq m -2 , CV = 15%, n = 7). Within the study area, where cultivation commenced in 1992 after deforestation, three representative downslope transects were sampled. These were characterized by 137 Cs inventories ranging from 190 to 2200 Bq m -2 . Although, the study area was cultivated by the local farmers, the 137 Cs depth distributions obtained from the area differed markedly from those expected from a cultivated area. They showed little evidence of tillage mixing within the upper part of the soil or, more particularly, of the near-uniform activities normally associated with the plough layer or cultivation horizon. They were very similar to that found at the reference site and were characterized by high 137 Cs activities at the surface and much lower activities at greater depths. This situation is thought to reflect the traditional manual tillage practices which cause limited disturbance and mixing of the upper part of the soil. It precluded the use of the conversion models normally used to estimate soil redistribution rates from 137 Cs measurements on cultivated soils and the Diffusion and Migration conversion model frequently used for uncultivated soils was modified for application to the cultivated soils of the study area, in order to take account of the unusual local conditions. The model was also modified to take account of the fact that cultivation in the study area commenced in 1992, rather than predating the period of weapons test fallout which extended from the mid 1950s to the 1970s. Erosion rates on the upper parts of the hillside involved in the study were found to be relatively high and ca. -23 t ha -1 y -1 with low spatial variability. In the lower, flatter areas at the bottom of the slope, deposition occurred. Deposition rates were characterized by high spatial variability, ranging from 6.0 to 71 t ha -1 y -1 . Soil redistribution rates of this magnitude are a cause for concern and there is an urgent need to implement soil conservation measures to ensure the longer-term sustainability of the local agricultural practices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial relationships among cereal yields and selected soil physical and chemical properties.

PubMed

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.

Experimental evidence of the role of pores on movement and distribution of bacteria in soil

NASA Astrophysics Data System (ADS)

Kravchenko, Alexandra N.; Rose, Joan B.; Marsh, Terence L.; Guber, Andrey K.

2014-05-01

It has been generally recognized that micro-scale heterogeneity in soil environments can have a substantial effect on movement, fate, and survival of soil microorganisms. However, only recently the development of tools for micro-scale soil analyses, including X-ray computed micro-tomography (μ-CT), enabled quantitative analyses of these effects. The long-term goal of our work is to explore how differences in micro-scale characteristics of pore structures influence movement, spatial distribution patterns, and activities of soil microorganisms. Using X-ray μ-CT we found that differences in land use and management practices lead to development of contrasting patterns in pore size-distributions within intact soil aggregates. Then our experiments with Escherichia coli added to intact soil aggregates demonstrated that the differences in pore structures can lead to substantial differences in bacteria redistribution and movement within the aggregates. Specifically, we observed more uniform E.coli redistribution in aggregates with homogeneously spread pores, while heterogeneous pore structures resulted in heterogeneous E.coli patterns. Water flow driven by capillary forces through intact aggregate pores appeared to be the main contributor to the movement patterns of the introduced bacteria. Influence of pore structure on E.coli distribution within the aggregates further continued after the aggregates were subjected to saturated water flow. E. coli's resumed movement with saturated water flow and subsequent redistribution within the soil matrix was influenced by porosity, abundance of medium and large pores, pore tortuosity, and flow rates, indicating that greater flow accompanied by less convoluted pores facilitated E. coli transport within the intra-aggregate space. We also found that intra-aggregate heterogeneity of pore structures can have an effect on spatial distribution patterns of indigenous microbial populations. Preliminary analysis showed that in aggregates from an organic agricultural system with cover crops, characterized by greater intra-aggregate pore heterogeneity, bacteria of Actinobacteria and Firmicutes groups were more abundant in presence of large as compared to small pores. In contrast, no differences were observed in the aggregates from conventionally managed soil, overall characterized by homogeneous intra-aggregate pore patterns. Further research efforts are being directed towards quantification of the pore structure effects on activities and community composition of soil microorganisms.

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 ...

Evaluating spatial and temporal variations of rainfall erosivity, case of Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Meshesha, Derege Tsegaye; Tsunekawa, Atsushi; Tsubo, Mitsuru; Haregeweyn, Nigussie; Adgo, Enyew

2015-02-01

Land degradation in many Ethiopian highlands occurs mainly due to high rainfall erosivity and poor soil conservation practices. Rainfall erosivity is an indicator of the precipitation energy and ability to cause soil erosion. In Central Rift Valley (CRV) of Ethiopia, where the climate is characterized as arid and semiarid, rainfall is the main driver of soil erosion that in turn causes a serious expansion in land degradation. In order to evaluate the spatial and temporal variability of rainfall erosivity and its impact on soil erosion, long-term rainfall data (1980-2010) was used, and the monthly Fournier index (FI) and the annual modified Fournier index (MFI) were applied. Student's t test analysis was performed particularly to examine statistical significances of differences in average monthly and annual erosivity values. The result indicated that, in a similar spatial pattern with elevation and rainfall amount, average annual erosivity is also found being higher in western highlands of the valley and gradually decreased towards the east. The long-term average annual erosivity (MFI) showed a general decreasing trend in recent 10 years (2000-2010) as compared to previous 20 years (1980-1999). In most of the stations, average erosivity of main rainy months (May, June, July, and August) showed a decreasing trend, whereby some of them (about 33.3 %) are statically significant at 90 and 95 % confidence intervals but with high variation in spatial pattern of changes. The overall result of the study showed that rainfall aggression (erosivity) in the region has a general decreasing trend in the recent decade as compared to previous decades, especially in the western highlands of the valley. Hence, it implies that anthropogenic factors such as land use change being coupled with topography (steep slope) have largely contributed to increased soil erosion rate in the region.

Modeling Soil Organic Carbon Variation Along Climatic and Topographic Trajectories in the Central Andes

NASA Astrophysics Data System (ADS)

Gavilan, C.; Grunwald, S.; Quiroz, R.; Zhu, L.

2015-12-01

The Andes represent the largest and highest mountain range in the tropics. Geological and climatic differentiation favored landscape and soil diversity, resulting in ecosystems adapted to very different climatic patterns. Although several studies support the fact that the Andes are a vast sink of soil organic carbon (SOC) only few have quantified this variable in situ. Estimating the spatial distribution of SOC stocks in data-poor and/or poorly accessible areas, like the Andean region, is challenging due to the lack of recent soil data at high spatial resolution and the wide range of coexistent ecosystems. Thus, the sampling strategy is vital in order to ensure the whole range of environmental covariates (EC) controlling SOC dynamics is represented. This approach allows grasping the variability of the area, which leads to more efficient statistical estimates and improves the modeling process. The objectives of this study were to i) characterize and model the spatial distribution of SOC stocks in the Central Andean region using soil-landscape modeling techniques, and to ii) validate and evaluate the model for predicting SOC content in the area. For that purpose, three representative study areas were identified and a suite of variables including elevation, mean annual temperature, annual precipitation and Normalized Difference Vegetation Index (NDVI), among others, was selected as EC. A stratified random sampling (namely conditioned Latin Hypercube) was implemented and a total of 400 sampling locations were identified. At all sites, four composite topsoil samples (0-30 cm) were collected within a 2 m radius. SOC content was measured using dry combustion and SOC stocks were estimated using bulk density measurements. Regression Kriging was used to map the spatial variation of SOC stocks. The accuracy, fit and bias of SOC models was assessed using a rigorous validation assessment. This study produced the first comprehensive, geospatial SOC stock assessment in this undersampled region that serves as a baseline reference to assess potential impacts of climate and land use change.

County-scale spatial distribution of soil enzyme activities and enzyme activity indices in agricultural land: implications for soil quality assessment.

PubMed

Tan, Xiangping; Xie, Baoni; Wang, Junxing; He, Wenxiang; Wang, Xudong; Wei, Gehong

2014-01-01

Here the spatial distribution of soil enzymatic properties in agricultural land was evaluated on a county-wide (567 km(2)) scale in Changwu, Shaanxi Province, China. The spatial variations in activities of five hydrolytic enzymes were examined using geostatistical methods. The relationships between soil enzyme activities and other soil properties were evaluated using both an integrated total enzyme activity index (TEI) and the geometric mean of enzyme activities (GME). At the county scale, soil invertase, phosphatase, and catalase activities were moderately spatially correlated, whereas urease and dehydrogenase activities were weakly spatially correlated. Correlation analysis showed that both TEI and GME were better correlated with selected soil physicochemical properties than single enzyme activities. Multivariate regression analysis showed that soil OM content had the strongest positive effect while soil pH had a negative effect on the two enzyme activity indices. In addition, total phosphorous content had a positive effect on TEI and GME in orchard soils, whereas alkali-hydrolyzable nitrogen and available potassium contents, respectively, had negative and positive effects on these two enzyme indices in cropland soils. The results indicate that land use changes strongly affect soil enzyme activities in agricultural land, where TEI provides a sensitive biological indicator for soil quality.

Soils of the Galindez Island, Argentine archipelago, Western Antarctica

NASA Astrophysics Data System (ADS)

Abakumov, Evgeny; Parnikoza, Ivan

2015-04-01

Antarctic Peninsula is a part of Antarctica which is characterized by increased soil diversity, caused by specific of parent materials and diversity of non-vascular and vascular plants. Soils of Galindez Island have been investigated during the 18-th Ukranian Antarctic Expedition 2013/14. This Island situated in Argentine archipelago (coastal part of Antarctic Peninsula). Soils of Galindez Island presented by following types: Leptosols, Lithosols, Histic Lithosols and Leptosols and some Gleyic soils, located in lowlands and coastal parts. An average solum profile thickness is 3-19 cm which result from the small depth of debris's, underplayed by massive crystallic rocks. The permafrost layer is located within the massive rock, but not in coarse friable parent material. The soils with bird influence are widely spread both in coastal and central part of Island. In the coastal parts we can find typical Ornithosols in the penguin rockeries areas. The main aim of our investigation was characterization of soils formed under vegetation, exactly under Deschampsia antarctica Desv. localities. Argentine Islands is the central part of D. antarctica spreading area in region of Antarctic peninsula. Probably, these islands colonized by hairgrass mainly due to ornitogenic activity. So, coastal population appearance related with Larus dominicanus nest areas and feeding activity. Thus, we found typical post ornithogenic soils here. This kind of soils we also observed in population of hairgrass of Galindez mainland where it was connected with the other Antarctic bird - Catharacta maccormicki activity. Thus, the soil diversity and soil geochemistry of the Galindez Island are closely related to the activity of birds. The spatial pattern of soils, their chemistry and organic matter quality is discussed in relation with distribution of bird nesting and feeding activity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kennedy, R.P.; Kincaid, R.H.; Short, S.A.

This report presents the results of part of a two-task study on the engineering characterization of earthquake ground motion for nuclear power plant design. Task I of the study, which is presented in NUREG/CR-3805, Vol. 1, developed a basis for selecting design response spectra taking into account the characteristics of free-field ground motion found to be significant in causing structural damage. Task II incorporates additional considerations of effects of spatial variations of ground motions and soil-structure interaction on foundation motions and structural response. The results of Task II are presented in four parts: (1) effects of ground motion characteristics onmore » structural response of a typical PWR reactor building with localized nonlinearities and soil-structure interaction effects; (2) empirical data on spatial variations of earthquake ground motion; (3) soil-structure interaction effects on structural response; and (4) summary of conclusions and recommendations based on Tasks I and II studies. This report presents the results of the first part of Task II. The results of the other parts will be presented in NUREG/CR-3805, Vols. 3 to 5.« less

Spatial and seasonal variations of polycyclic aromatic hydrocarbons in Haihe Plain, China.

PubMed

Wang, Rong; Cao, Hongying; Li, Wei; Wang, Wei; Wang, Wentao; Zhang, Liwen; Liu, Jiumeng; Ouyang, Huiling; Tao, Shu

2011-05-01

A dynamic fugacity model was developed to simulate the spatial and seasonal variations of PAHs in Haihe Plain, China. The calculated and measured concentrations exhibited good consistency in magnitude with deviations within a factor of 4 in air and 2 in soil. The spatial distributions of PAHs in air were mainly controlled by emission while the seasonal variations were dominated by emission and gas-particle partition. In soil, the spatial distributions of PAHs were controlled by the soil organic carbon content while the seasonal variations were insignificant. The severest soil contamination was observed in Shanxi and followed by the southwest of Hebei province. Transfer fluxes of total PAHs between air and soil were calculated. The spatial distribution of air-to-soil flux was closely related to the landcover while the soil-to-air flux changed with soil organic matter content. Monte Carlo simulation was done to evaluate the uncertainty of the estimated results in air. Copyright © 2011 Elsevier Ltd. All rights reserved.

Toxicity Assessment of Contaminated Soils of Solid Domestic Waste Landfill

NASA Astrophysics Data System (ADS)

Pasko, O. A.; Mochalova, T. N.

2014-08-01

The paper delivers the analysis of an 18-year dynamic pattern of land pollutants concentration in the soils of a solid domestic waste landfill. It also presents the composition of the contaminated soils from different areas of the waste landfill during its operating period. The authors calculate the concentrations of the following pollutants: chrome, nickel, tin, vanadium, lead, cuprum, zinc, cobalt, beryllium, barium, yttrium, cadmium, arsenic, germanium, nitrate ions and petrochemicals and determine a consistent pattern of their spatial distribution within the waste landfill area as well as the dynamic pattern of their concentration. Test-objects are used in experiments to make an integral assessment of the polluted soil's impact on living organisms. It was discovered that the soil samples of an animal burial site are characterized by acute toxicity while the area of open waste dumping is the most dangerous in terms of a number of pollutants. This contradiction can be attributed to the synergetic effect of the polluted soil, which accounts for the regularities described by other researchers.

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation

PubMed Central

Davis, Harley T.; Aelion, C. Marjorie; McDermott, Suzanne; Lawson, Andrew B.

2009-01-01

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily-available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures. PMID:19361902

Terahertz Spectroscopy for Proximal Soil Sensing: An Approach to Particle Size Analysis

PubMed Central

Dworak, Volker; Mahns, Benjamin; Selbeck, Jörn; Weltzien, Cornelia

2017-01-01

Spatially resolved soil parameters are some of the most important pieces of information for precision agriculture. These parameters, especially the particle size distribution (texture), are costly to measure by conventional laboratory methods, and thus, in situ assessment has become the focus of a new discipline called proximal soil sensing. Terahertz (THz) radiation is a promising method for nondestructive in situ measurements. The THz frequency range from 258 gigahertz (GHz) to 350 GHz provides a good compromise between soil penetration and the interaction of the electromagnetic waves with soil compounds. In particular, soil physical parameters influence THz measurements. This paper presents investigations of the spectral transmission signals from samples of different particle size fractions relevant for soil characterization. The sample thickness ranged from 5 to 17 mm. The transmission of THz waves was affected by the main mineral particle fractions, sand, silt and clay. The resulting signal changes systematically according to particle sizes larger than half the wavelength. It can be concluded that THz spectroscopic measurements provide information about soil texture and penetrate samples with thicknesses in the cm range. PMID:29048392

Can the normalized soil moisture index improve the prediction of soil organic carbon based on hyperspectral remote sensing data?

NASA Astrophysics Data System (ADS)

van Wesemael, Bas; Nocita, Marco

2016-04-01

One of the problems for mapping of soil organic carbon (SOC) at large-scale based on visible - near and short wave infrared (VIS-NIR-SWIR) remote sensing techniques is the spatial variation of topsoil moisture when the images are collected. Soil moisture is certainly an aspect causing biased SOC estimations, due to the problems in discriminating reflectance differences due to either variations in organic matter or soil moisture, or their combination. In addition, the difficult validation procedures make the accurate estimation of soil moisture from optical airborne a major challenge. After all, the first millimeters of the soil surface reflect the signal to the airborne sensor and show a large spatial, vertical and temporal variation in soil moisture. Hence, the difficulty of assessing the soil moisture of this thin layer at the same moment of the flight. The creation of a soil moisture proxy, directly retrievable from the hyperspectral data is a priority to improve the large-scale prediction of SOC. This paper aims to verify if the application of the normalized soil moisture index (NSMI) to Airborne Prima Experiment (APEX) hyperspectral images could improve the prediction of SOC. The study area was located in the loam region of Wallonia, Belgium. About 40 samples were collected from bare fields covered by the flight lines, and analyzed in the laboratory. Soil spectra, corresponding to the sample locations, were extracted from the images. Once the NSMI was calculated for the bare fields' pixels, spatial patterns, presumably related to within field soil moisture variations, were revealed. SOC prediction models, built using raw and pre-treated spectra, were generated from either the full dataset (general model), or pixels belonging to one of the two classes of NSMI values (NSMI models). The best result, with a RMSE after validation of 1.24 g C kg-1, was achieved with a NSMI model, compared to the best general model, characterized by a RMSE of 2.11 g C kg-1. These results confirmed the advantage to controlling the effect of soil moisture on the detection of SOC. The NSMI proved to be a flexible concept, due to the possible use of different SWIR wavelengths, and ease of use, because measurements of soil moisture by other techniques are not needed. However, in the future, it will be important to assess the effectiveness of the NSMI for different soil types, and other hyperspectral sensors.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

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.

Spatial Modeling of Iron Transformations Within Artificial Soil Aggregates

NASA Astrophysics Data System (ADS)

Kausch, M.; Meile, C.; Pallud, C.

2008-12-01

Structured soils exhibit significant variations in transport characteristics at the aggregate scale. Preferential flow occurs through macropores while predominantly diffusive exchange takes place in intra-aggregate micropores. Such environments characterized by mass transfer limitations are conducive to the formation of small-scale chemical gradients and promote strong spatial variation in processes controlling the fate of redox-sensitive elements such as Fe. In this study, we present a reactive transport model used to spatially resolve iron bioreductive processes occurring within a spherical aggregate at the interface between advective and diffusive domains. The model is derived from current conceptual models of iron(hydr)oxide (HFO) transformations and constrained by literature and experimental data. Data were obtained from flow-through experiments on artificial soil aggregates inoculated with Shewanella putrefaciens strain CN32, and include the temporal evolution of the bulk solution composition, as well as spatial information on the final solid phase distribution within aggregates. With all iron initially in the form of ferrihydrite, spatially heterogeneous formation of goethite/lepidocrocite, magnetite and siderite was observed during the course of the experiments. These transformations were reproduced by the model, which ascribes a central role to divalent iron as a driver of HFO transformations and master variable in the rate laws of the considered reaction network. The predicted dissolved iron breakthrough curves also match the experimental ones closely. Thus, the computed chemical concentration fields help identify factors governing the observed trends in the solid phase distribution patterns inside the aggregate. Building on a mechanistic description of transformation reactions, fluid flow and solute transport, the model was able to describe the observations and hence illustrates the importance of small-scale gradients and dynamics of bioreductive processes for assessing bulk iron cycling. As HFOs are ubiquitous in soils, such process-level understanding of aggregate-scale iron dynamics has broad implications for the prediction of the subsurface fate of nutrients and contaminants that interact strongly with HFO surfaces.

Recently Deglaciated High-Altitude Soils of the Himalaya: Diverse Environments, Heterogenous Bacterial Communities and Long-Range Dust Inputs from the Upper Troposphere

PubMed Central

Stres, Blaz; Sul, Woo Jun; Murovec, Bostjan; Tiedje, James M.

2013-01-01

Background The Himalaya with its altitude and geographical position forms a barrier to atmospheric transport, which produces much aqueous-particle monsoon precipitation and makes it the largest continuous ice-covered area outside polar regions. There is a paucity of data on high-altitude microbial communities, their native environments and responses to environmental-spatial variables relative to seasonal and deglaciation events. Methodology/Principal Findings Soils were sampled along altitude transects from 5000 m to 6000 m to determine environmental, spatial and seasonal factors structuring bacterial communities characterized by 16 S rRNA gene deep sequencing. Dust traps and fresh-snow samples were used to assess dust abundance and viability, community structure and abundance of dust associated microbial communities. Significantly different habitats among the altitude-transect samples corresponded to both phylogenetically distant and closely-related communities at distances as short as 50 m showing high community spatial divergence. High within-group variability that was related to an order of magnitude higher dust deposition obscured seasonal and temporal rearrangements in microbial communities. Although dust particle and associated cell deposition rates were highly correlated, seasonal dust communities of bacteria were distinct and differed significantly from recipient soil communities. Analysis of closest relatives to dust OTUs, HYSPLIT back-calculation of airmass trajectories and small dust particle size (4–12 µm) suggested that the deposited dust and microbes came from distant continental, lacustrine and marine sources, e.g. Sahara, India, Caspian Sea and Tibetan plateau. Cyanobacteria represented less than 0.5% of microbial communities suggesting that the microbial communities benefitted from (co)deposited carbon which was reflected in the psychrotolerant nature of dust-particle associated bacteria. Conclusions/Significance The spatial, environmental and temporal complexity of the high-altitude soils of the Himalaya generates ongoing disturbance and colonization events that subject heterogeneous microniches to stochastic colonization by far away dust associated microbes and result in the observed spatially divergent bacterial communities. PMID:24086740

Soft X-ray spectromicroscopy study of mineral-organic matter associations in pasture soil clay fractions.

PubMed

Chen, Chunmei; Dynes, James J; Wang, Jian; Karunakaran, Chithra; Sparks, Donald L

2014-06-17

There is a growing acceptance that associations with soil minerals may be the most important overarching stabilization mechanism for soil organic matter. However, direct investigation of organo-mineral associations has been hampered by a lack of methods that can simultaneously characterize organic matter (OM) and soil minerals. In this study, STXM-NEXAFS spectroscopy at the C 1s, Ca 2p, Fe 2p, Al 1s, and Si 1s edges was used to investigate C associations with Ca, Fe, Al, and Si species in soil clay fractions from an upland pasture hillslope. Bulk techniques including C and N NEXAFS, Fe K-edge EXAFS spectroscopy, and XRD were applied to provide additional information. Results demonstrated that C was associated with Ca, Fe, Al, and Si with no separate phase in soil clay particles. In soil clay particles, the pervasive C forms were aromatic C, carboxyl C, and polysaccharides with the relative abundance of carboxyl C and polysaccharides varying spatially at the submicrometer scale. Only limited regions in the soil clay particles had aliphatic C. Good C-Ca spatial correlations were found for soil clay particles with no CaCO3, suggesting a strong role of Ca in organo-mineral assemblage formation. Fe EXAFS showed that about 50% of the total Fe in soils was contained in Fe oxides, whereas Fe-bearing aluminosilicates (vermiculite and Illite) accounted for another 50%. Fe oxides in the soil were mainly crystalline goethite and hematite, with lesser amounts of poorly crystalline ferrihydrite. XRD revealed that soil clay aluminosilicates were hydroxy-interlayered vermiculite, Illite, and kaolinite. C showed similar correlation with Fe to Al and Si, implying a similar association of Fe oxides and aluminosilicates with organic matter in organo-mineral associations. These direct microscopic determinations can help improve understanding of organo-mineral interactions in soils.

Spatial and temporal predictions of agricultural land prices using DSM techniques.

NASA Astrophysics Data System (ADS)

Carré, F.; Grandgirard, D.; Diafas, I.; Reuter, H. I.; Julien, V.; Lemercier, B.

2009-04-01

Agricultural land prices highly impacts land accessibility to farmers and by consequence the evolution of agricultural landscapes (crop changes, land conversion to urban infrastructures…) which can turn to irreversible soil degradation. The economic value of agricultural land has been studied spatially, in every one of the 374 French Agricultural Counties, and temporally- from 1995 to 2007, by using data of the SAFER Institute. To this aim, agricultural land price was considered as a digital soil property. The spatial and temporal predictions were done using Digital Soil Mapping techniques combined with tools mainly used for studying temporal financial behaviors. For making both predictions, a first classification of the Agricultural Counties was done for the 1995-2006 periods (2007 was excluded and served as the date of prediction) using a fuzzy k-means clustering. The Agricultural Counties were then aggregated according to land price at the different times. The clustering allows for characterizing the counties by their memberships to each class centroid. The memberships were used for the spatial prediction, whereas the centroids were used for the temporal prediction. For the spatial prediction, from the 374 Agricultural counties, three fourths were used for modeling and one fourth for validating. Random sampling was done by class to ensure that all classes are represented by at least one county in the modeling and validation datasets. The prediction was done for each class by testing the relationships between the memberships and the following factors: (i) soil variable (organic matter from the French BDAT database), (ii) soil covariates (land use classes from CORINE LANDCOVER, bioclimatic zones from the WorldClim Database, landform attributes and landform classes from the SRTM, major roads and hydrographic densities from EUROSTAT, average field sizes estimated by automatic classification of remote sensed images) and (iii) socio-economic factors (population density, gross domestic product and its combination with the population density obtained from EUROSTAT). Linear (Generalized Linear Models) and non-linear models (neural network) were used for building the relationships. For the validation, the relationships were applied to the validation datasets. The RMSE and the coefficient of determination (from a linear regression) between predicted and actual memberships, and the contingency table between the predicted and actual allocation classes were used as validation criteria. The temporal prediction was done on the year 2007 from the centroid land prices characterizing the 1995-2006 period. For each class, the land prices of the time-series 1995-2006 were modeled using an Auto-Regressive Moving Average approach. For the validation, the models were applied to the year 2007. The RMSE between predicted and actual prices is used as the validation criteria. We then discussed the methods and the results of the spatial and temporal validation. Based on this methodology, an extrapolation will be tested on another European country with land price market similar to France (to be determined).

Characterization of LANDSAT-4 TM and MSS Image Quality for Interpretation of Agricultural and Forest Resources

NASA Technical Reports Server (NTRS)

Degloria, S. D.; Colwell, R. N.

1984-01-01

Systematic analysis of both image and numeric data shows that the overall spectral, spatial, and radiometric quality of the TM data are excellent. Spectral variations in fallow fields are due to the vaiability in soil moisture and surface roughness resulting from the various stages of field preparation for small grains production. Spectrally, the addition of the first TM short wave infrared band (Band 5) significantly enhanced ability to discriminate different crop types. Bands 1, 5, and 6 contain saturated pixels due to high albedo effects, low moisture conditions, and high radiant temperatures of granite and dry, bare soil on south facing slopes, respectively. Spatially, the two fold decrease in interpixel distance and four fold decrease in area per pixel between the TM and MSS allow for improved discrimination of small fields, boundary conditions, road and stream networks in rough terrain, and small forest clearings resulting from various forest management practices.

Spatial characterization of acid rain stress in Canadian Shield Lakes

NASA Technical Reports Server (NTRS)

Tanis, Fred J.

1987-01-01

An analysis was performed to interpret the spatial aspects of lake acidification. Three types of relationships were investigated based upon the August to May seasonal scene pairing. In the first type of analysis ANOVA was used to examine the mean Thematic Mapper band one count by ecophysical strata. The primary difference in the two ecophysical strata is the soil type and depth over the underlying bedrock. Examination of the August to May difference values for TM band one produced similar results. Group A and B strata were the same as above. The third type of analysis examined the relationship between values of the August to May difference from polygons which have similar ecophysical properties with the exception of sulfate deposition. For this case lakes were selected from units with sandy soils over granitic rock types and the sulfate deposition was 1.5 or 2.5 g/sq m/yr.

Introduction of digital soil mapping techniques for the nationwide regionalization of soil condition in Hungary; the first results of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Dobos, Endre

2014-05-01

Due to the former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. Present soil data requirements are mainly fulfilled with these available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. With a recently started project (DOSoReMI.hu; Digital, Optimized, Soil Related Maps and Information in Hungary) we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied in Hungary. We started to compile digital soil related maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The spatial resolution of the targeted countrywide, digital, thematic maps is at least 1:50.000 (approx. 50-100 meter raster resolution). DOSoReMI.hu results are also planned to contribute to the European part of GSM.net products. In addition to the auxiliary, spatial data themes related to soil forming factors and/or to indicative environmental elements we heavily lean on the various national soil databases. The set of the applied digital soil mapping techniques is gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. In our paper we will present the first results. - Regression kriging (RK) has been used for the spatial inference of certain quantitative data, like particle size distribution components, rootable depth and organic matter content. In the course of RK-based mapping spatially segmented categorical information provided by the SMUs of Digital Kreybig Soil Information System (DKSIS) has been also used in the form of indicator variables. - Classification and regression trees (CART) were used to improve the spatial resolution of category-type soil maps (thematic downscaling), like genetic soil type and soil productivity maps. The approach was justified by the fact that certain thematic soil maps are not available in the required scale. Decision trees were applied for the understanding of the soil-landscape models involved in existing soil maps, and for the post-formalization of survey/compilation rules. The relationships identified and expressed in decision rules made the creation of spatially refined maps possible with the aid of high resolution environmental auxiliary variables. Among these co-variables, a special role was played by larger scale spatial soil information with diverse attributes. As a next step, the testing of random forests for the same purposes has been started. - 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 (related) map. This suggests the opportunity of optimization. For the creation of an object specific soil (related) map with predefined parameters (resolution, accuracy, reliability etc.) 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.). The first findings on the inclusion and joint usage of spatial soil data as well as on the consistency of various evaluations of the result maps will be also presented. Acknowledgement: Our work has been supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Influence of spatial variability of hydraulic characteristics of soils on surface parameters obtained from remote sensing data in infrared and microwaves

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.

Soil bioindicators as a usefull tools for land management and spatial planning processes: a case-study of prioritization of contaminated soil remediation

NASA Astrophysics Data System (ADS)

Grand, Cécile; Pauget, Benjamin; Villenave, Cécile; Le Guédard, Marina; Piron, Denis; Nau, Jean-François; Pérès, Guénola

2017-04-01

When setting up new land management, contaminated site remediation or soil use change are sometimes necessary to ensure soil quality and the restoration of the ecosystem services. The biological characterization of the soil can be used as complementary information to chemical data in order to better define the conditions for operating. Then, in the context of urban areas, elements on the soil biological quality can be taken into consideration to guide the land development. To assess this "biological state of soil health", some biological tools, called bioindicators, could provide comprehensive information to understand and predict the functioning of the soil ecosystem. In this context, a city of 200 thousand inhabitants has decided to integrate soil bioindicators in their soil diagnostic for their soil urban management. This city had to elaborate a spatial soil management in urban areas which presented soil contamination linked to a complex industrial history associated with bad uses of gardens not always safe for the environment. The project will lead to establish a Natural Urban Park (PNU) in order to develop recreational and leisure activities in a quality environment. In order to complete the knowledge of soil contamination and to assess the transfer of contaminants to the terrestrial ecosystem, a biological characterization of soils located in different areas was carried out using six bioindicators: bioindicators of accumulation which allowed to evaluate the transfers of soil contaminants towards the first 2 steps of a trophic chain (plants and soil fauna, e.g. snails), bioindicators of effects (Omega 3 index was used to assess the effects of soil contamination and to measure their impact on plants), bioindicators of soil functioning (measurement of microbial biomass, nematodes and earthworm community) ; the interest of these last bioindicators is that they also act on the functioning of ecosystems as on the dynamics of organic matter (mineralization) but also on the structuring of the soils. The results from 14 measurement points demonstrated the relatively low average transfers towards the plants and soil fauna although the transfers can be changing a lot in relation to heterogeneity of soil contamination. Results obtained from other bioindicators (nematodes, earthworms and bacterial biomass) showed that the different soils are on average of good biological quality and can benefit from a diversity and abundance of communities of soil organisms. The data obtained in this program underline that these tools can be used to evaluate soil functions (habitat for biodiversity, soil capacity to store contaminants, etc.) and, consequently, the services that the soil can give to humans. Moreover, these biological tools allowed to assess the biological quality of soils and their compatibility with the soil use and the necessity of soil remediation (excavation of hot-spots, surface cover etc ..).Taking into account not only the behavior of soil contaminants but also the environmental factors that influence the biological functioning of the soil, these tools can be useful for land management of large-scale sites and for brownfield conquest.

A hydroclimatological approach to predicting regional landslide probability using Landlab

NASA Astrophysics Data System (ADS)

Strauch, Ronda; Istanbulluoglu, Erkan; Nudurupati, Sai Siddhartha; Bandaragoda, Christina; Gasparini, Nicole M.; Tucker, Gregory E.

2018-02-01

We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

Spatial variation of urban soil geochemistry in a roadside sports ground in Galway, Ireland.

PubMed

Dao, Ligang; Morrison, Liam; Zhang, Chaosheng

2010-02-01

Characterization of spatial variation of urban soil geochemistry especially heavy metal pollution is essential for a better understanding of pollution sources and potential risks. A total of 294 surface soil samples were collected from a roadside sports ground in Galway, Ireland, and were analysed by ICP-OES for 23 chemical elements (Al, Ca, Ce, Co, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, S, Sc, Sr, Th, Ti, V, Y and Zn). Strong variations in soil geochemistry were observed and most elements, with the exception of Cu, Pb, P, S and Zn, showed multi-modal features, indicating the existence of mixed populations which proved difficult to separate. To evaluate the pollution level of the study area, the pollution index (PI) values were calculated based on a comparison with the Dutch target and intervention values. None of the concentrations of metal pollutants exceeded their intervention values, indicating the absence of serious contaminated soil, and the ratios to target values were therefore employed to produce the hazard maps. The spatial distribution and hazard maps for Cu, Pb and Zn indicated relatively high levels of pollution along the southern roadside extending almost 30m into the sports ground, revealing the strong influence of pollution from local traffic. However, heavy metal pollution was alleviated along the eastern roadside of the study area by the presence of a belt of shrubs. Therefore, in order to prevent further contamination from traffic emissions, the planting of hedging or erection of low walls should be considered as shields against traffic pollution for roadside parks. The results in this study are useful for management practices in sports and parks in urban areas. Copyright 2009 Elsevier B.V. All rights reserved.

Spatial distribution of soil-transmitted helminths, including Strongyloides stercoralis, among children in Zanzibar.

PubMed

Knopp, Stefanie; Mohammed, Khalfan A; Simba Khamis, I; Mgeni, Ali F; Stothard, J Russell; Rollinson, David; Marti, Hanspeter; Utzinger, Jürg

2008-11-01

A programme periodically distributing anthelminthic drugs to school-aged children for the control of soiltransmitted helminthiasis was launched in Zanzibar in the early 1990s. We investigated the spatial distribution of soiltransmitted helminth infections, including Strongyloides stercoralis, in 336 children from six districts in Unguja, Zanzibar, in 2007. One stool sample per child was examined with the Kato-Katz, Koga agar plate and Baermann methods. The point prevalence of the different helminth infections was compared to the geological characteristics of the study sites. The observed prevalences for Trichuris trichiura, Ascaris lumbricoides, hookworm and S. stercoralis were 35.5%, 12.2%, 11.9% and 2.2%, respectively, with considerable spatial heterogeneity. Whilst T. trichiura and hookworm infections were found in all six districts, no A. lumbricoides infections were recorded in the urban setting and only a low prevalence (2.2%) was observed in the South district. S. stercoralis infections were found in four districts with the highest prevalence (4.0%) in the West district. The prevalence of infection with any soil-transmitted helminth was highest in the North A district (69.6%) and lowest in the urban setting (22.4%). A. lumbricoides, hookworm and, with the exception of the North B district, S. stercoralis infections were observed to be more prevalent in the settings north of Zanzibar Town, which are characterized by alluvial clayey soils, moist forest regions and a higher precipitation. After a decade of large-scale administration of anthelminthic drugs, the prevalence of soil-transmitted helminth infections across Unguja is still considerable. Hence, additional measures, such as improving access to adequate sanitation and clean water and continued health education, are warranted to successfully control soil-transmitted helminthiasis in Zanzibar.

Evaluation of Electromagnetic Induction to Characterize and Map Sodium-Affected Soils in the Northern Great Plains of the United States

NASA Astrophysics Data System (ADS)

Brevik, E. C.; Heilig, J.; Kempenich, J.; Doolittle, J.; Ulmer, M.

2012-04-01

Sodium-affected soils (SAS) cover over 4 million hectares in the Northern Great Plains of the United States. Improving the classification, interpretation, and mapping of SAS is a major goal of the United States Department of Agriculture-Natural Resource Conservation Service (USDA-NRCS) as Northern Great Plains soil surveys are updated. Apparent electrical conductivity (ECa) as measured with ground conductivity meters has shown promise for mapping SAS, however, this use of this geophysical tool needs additional evaluation. This study used an EM-38 MK2-2 meter (Geonics Limited, Mississauga, Ontario), a Trimble AgGPS 114 L-band DGPS (Trimble, Sunnyvale, CA) and the RTmap38MK2 program (Geomar Software, Inc., Mississauga, Ontario) on an Allegro CX field computer (Juniper Systems, North Logan, UT) to collect, observe, and interpret ECa data in the field. The ECa map generated on-site was then used to guide collection of soil samples for soil characterization and to evaluate the influence of soil properties in SAS on ECa as measured with the EM-38MK2-2. Stochastic models contained in the ESAP software package were used to estimate the SAR and salinity levels from the measured ECa data in 30 cm depth intervals to a depth of 90 cm and for the bulk soil (0 to 90 cm). This technique showed promise, with meaningful spatial patterns apparent in the ECa data. However, many of the stochastic models used for salinity and SAR for individual depth intervals and for the bulk soil had low R-squared values. At both sites, significant variability in soil clay and water contents along with a small number of soil samples taken to calibrate the ECa values to soil properties likely contributed to these low R-squared values.

Soil cover patterns and SOC dynamics impacts on the soil processes, land management and ecosystem services in Central Region of Russia

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Chernikov, Vladimir; Yashin, Ivan; Geraskin, Mikhail; Morev, Dmitriy

2014-05-01

In the Central Region of Russia (CRR) the soil cover patterns usually play the very important role in the soil forming and degradation processes (SFP & SDP) potential and current rates, soil organic carbon (SOC) dynamics and pools, greenhouse gases (GHG) emissions and soluble SOC fluxes that we need take into attention for better assessment of the natural and especially man-changed ecosystems' services and for best land-use practices development. Central Region of Russia is the biggest one in RF according to its population and role in the economy. CRR is characterized by high spatial variability of soil cover due to as original landscape heterogeneity as complicated history of land-use practices during last 700 years. Our long-term researches include the wide zonal-provincial set of representative ecosystems and soil cover patterns with different types and history of land-use (forest, meadow-steppe and agricultural ones) from middle-taiga to steppe zones with different level of continentality. The carried out more than 30-years region- and local-scale researches of representative natural and rural landscapes in Tver', Yaroslavl', Kaluga, Moscow, Vladimir, Saransk (Mordovia), Kursk, Orel, Tambov, Voronezh and Saratov oblasts give us the interregional multi-factorial matrix of elementary soil cover patterns (ESCP) with different soil forming and degradation processes rates and soil organic carbon dynamics due to regionally specific soil-geomorphologic features, environmental and dominated microclimate conditions, land-use current practices and history. The validation and ranging of the limiting factors of SFP and SDP develop¬ment, soil carbon dynamics and sequestration potential, ecosystem (agroecosystem) principal services, land functional qualities and agroecological state have been done for dominating and most dynamical components of ESCP regional-typological forms - with application of SOC structure analysis, regional and local GIS, soil spatial patterns detail mapping, traditional regression kriging, correlation tree models and DSS adapted to concrete region and agrolandscape conditions. The outcomes of statistical process modeling show the essential amplification of erosion, dehumification, CO2, CH4 and N2O emission, soluble SOC fluxes, acidification or alkalization, disaggregation and overcompaction processes due to violation of environmentally sound land-use systems and traditional balances of organic matter, nutrients, Ca and Na in agrolandscapes. Due to long-term intensive and out-of-balance land-use practices the most zonal soils and soil cover pattern essentially lost not only their unique natural features (humus horizons depth till 1 m and more in case of Chernozems, 2-6 % of SOC and favorable agrophysical features), but ecosystem services and ecological functions including terrestrial ecosystem carbon balance and the GHG fluxes control. Key-site monitoring results and regional generalized data showed 1-1.5% SOC lost during last 50 years period and active processes of CO2 emission and humus profile eluvial-illuvial redistribution too. A drop of Corg content below threshold "humus limiting content" values (for different soils they vary from 1 to 3-4% of SOC) considerably reduces effectiveness of used fertilizers and possibility of sustai¬nable agronomy here. Forest-steppe Chernozems are usually characterized by higher stability than steppe ones. The ratio between erosive and biological losses in humus supplies can be ten-tatively estimated as fifty-fifty with strong spatial variability due to slope and land-use parameters. These processes have essentially different sets of environmental consequences and ecosystem services that we need to understand in frame of environmental and agroecological problems development prediction.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Evaluation of Karst Soil Erosion and Nutrient Loss Based on RUSLE Model in Guizhou Province

NASA Astrophysics Data System (ADS)

Zeng, Cheng; Li, Yangbing; Bai, Xiaoyong; Luo, Guangjie

2018-01-01

Based on GIS technology and RUSLE model, the spatial variation characteristics of soil erosion were analyzed in karst areas, and the relationship between soil erosion and soil nutrient loss was discussed. The results showed that the soil differences in spatial variation between nutrient losses. The results illustrate the total soil erosion in is 10316.31 × 104t • a-1, accounting for 84.95% of the total land area in Guizhou Province. The spatial distribution of soil erosion showing the characteristics of the southeast to the northwest strip. The annual average soil erosion modulu is 691.94 t • km-2 • a-1, of which karst is 720.28t • km-2 • a-1 and non-karst is 689.53 t • km-2 • a-1. The total nutrient losses such as soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP) and total potassium (TK) were 596.72 × 104t • a-1 due to soil erosion, and SOC, TN and TP and TK were 38.13, 1.61, 0.41 and 14.70t • km-2 • a-1, respectively. The average amount of loss and total loss are the largest in non-karst, and four kinds of nutrient is the smallest in karst gorge. The spatial variation of soil erosion in the study area is the process of increasing the erosion area with the increase of the erosion rate, and the difference of the spatial distribution of soil erosion determines the spatial distribution of soil nutrient loss.

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to be sought to explain the poor agreement in spatial patterns between satellite derived and modelled SSM. This presentation will hopefully contribute to the discussion of how SMOS and other observations can be used to prepare, carry-out and exploit a field campaign over the Iberian Peninsula which aims at improving our understanding of semi-arid land surface processes.

Geomorphic Controls on Floodplain Soil Organic Carbon in the Yukon Flats, Interior Alaska, From Reach to River Basin Scales

NASA Astrophysics Data System (ADS)

Lininger, K. B.; Wohl, E.; Rose, J. R.

2018-03-01

Floodplains accumulate and store organic carbon (OC) and release OC to rivers, but studies of floodplain soil OC come from small rivers or small spatial extents on larger rivers in temperate latitudes. Warming climate is causing substantial change in geomorphic process and OC fluxes in high latitude rivers. We investigate geomorphic controls on floodplain soil OC concentrations in active-layer mineral sediment in the Yukon Flats, interior Alaska. We characterize OC along the Yukon River and four tributaries in relation to geomorphic controls at the river basin, segment, and reach scales. Average OC concentration within floodplain soil is 2.8% (median = 2.2%). Statistical analyses indicate that OC varies among river basins, among planform types along a river depending on the geomorphic unit, and among geomorphic units. OC decreases with sample depth, suggesting that most OC accumulates via autochthonous inputs from floodplain vegetation. Floodplain and river characteristics, such as grain size, soil moisture, planform, migration rate, and riverine DOC concentrations, likely influence differences among rivers. Grain size, soil moisture, and age of surface likely influence differences among geomorphic units. Mean OC concentrations vary more among geomorphic units (wetlands = 5.1% versus bars = 2.0%) than among study rivers (Dall River = 3.8% versus Teedrinjik River = 2.3%), suggesting that reach-scale geomorphic processes more strongly control the spatial distribution of OC than basin-scale processes. Investigating differences at the basin and reach scale is necessary to accurately assess the amount and distribution of floodplain soil OC, as well as the geomorphic controls on OC.

Research on the degradation of tropical arable land soil: Part II. The distribution of soil nutrients in eastern part of Hainan Island

NASA Astrophysics Data System (ADS)

Wang, Dengfeng; Wei, Zhiyuan; Qi, Zhiping

Research on the temporal and spatial distribution of soil nutrients in tropical arable land is very important to promote the tropical sustainable agriculture development. Take the Eastern part of Hainan as research area, applying GIS spatial analysis technique, analyzing the temporal and spatial variation of soil N, P and K contents in arable land. The results indicate that the contents of soil N, P and K were 0.28%, 0.20% and 1.75% respectively in 2005. The concentrations of total N and P in arable land soil increased significantly from 1980s to 2005. The variances in contents of soil nutrients were closely related to the application of chemical fertilizers in recent years, and the uneven distribution of soil nutrient contents was a reflection of fertilizer application in research area. Fertilization can be planned based on the distribution of soil nutrients and the spatial analysis techniques, so as to sustain balance of soil nutrients contents.

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE PAGES

Shi, Yuning; Eissenstat, David M.; He, Yuting; ...

2018-05-12

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Yuning; Eissenstat, David M.; He, Yuting

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

Spatial heterogeneity of plant-soil feedback affects root interactions and interspecific competition.

PubMed

Hendriks, Marloes; Ravenek, Janneke M; Smit-Tiekstra, Annemiek E; van der Paauw, Jan Willem; de Caluwe, Hannie; van der Putten, Wim H; de Kroon, Hans; Mommer, Liesje

2015-08-01

Plant-soil feedback is receiving increasing interest as a factor influencing plant competition and species coexistence in grasslands. However, we do not know how spatial distribution of plant-soil feedback affects plant below-ground interactions. We investigated the way in which spatial heterogeneity of soil biota affects competitive interactions in grassland plant species. We performed a pairwise competition experiment combined with heterogeneous distribution of soil biota using four grassland plant species and their soil biota. Patches were applied as quadrants of 'own' and 'foreign' soils from all plant species in all pairwise combinations. To evaluate interspecific root responses, species-specific root biomass was quantified using real-time PCR. All plant species suffered negative soil feedback, but strength was species-specific, reflected by a decrease in root growth in own compared with foreign soil. Reduction in root growth in own patches by the superior plant competitor provided opportunities for inferior competitors to increase root biomass in these patches. These patterns did not cascade into above-ground effects during our experiment. We show that root distributions can be determined by spatial heterogeneity of soil biota, affecting plant below-ground competitive interactions. Thus, spatial heterogeneity of soil biota may contribute to plant species coexistence in species-rich grasslands. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

On the soil moisture estimate at basin scale in Mediterranean basins with the ASAR sensor: the Mulargia basin case study

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.

[Three-dimension temporal and spatial dynamics of soil water for the artificial vegetation in the center of Taklimakan desert under saline water drip-irrigation].

PubMed

Ding, Xin-yuan; Zhou, Zhi-bin; Xu, Xin-wen; Lei, Jia-qiang; Lu, Jing-jing; Ma, Xue-xi; Feng, Xiao

2015-09-01

Three-dimension temporal and spatial dynamics of the soil water characteristics during four irrigating cycles of months from April to July for the artificial vegetation in the center of Taklimakan Desert under saline water drip-irrigation had been analyzed by timely measuring the soil water content in horizontal and vertical distances 60 cm and 120 cm away from the irrigating drips, respectively. Periodic spatial and temporal variations of soil water content were observed. When the precipitation effect was not considered, there were no significant differences in the characteristics of soil water among the irrigation intervals in different months, while discrepancies were obvious in the temporal and spatial changes of soil moisture content under the conditions of rainfall and non-rainfall. When it referred to the temporal changes of soil water, it was a little higher in April but a bit lower in July, and the soil water content in June was the highest among four months because some remarkable events of precipitation happened in this month. However, as a whole, the content of soil moisture was reduced as months (from April to July) went on and it took a decreasing tendency along with days (1-15 d) following a power function. Meanwhile, the characteristics of soil water content displayed three changeable stages in an irrigation interval. When it referred to the spatial distributions of soil water, the average content of soil moisture was reduced along with the horizontal distance following a linear regression function, and varied with double peaks along with the vertical distance. In addition, the spatial distribution characteristics of the soil water were not influenced by the factors of precipitation and irrigating time but the physical properties of soil.

Dryland soil microbial communities display spatial biogeographic patterns associated with soil depth and soil parent material

USGS Publications Warehouse

Steven, Blaire; Gallegos-Graves, La Verne; Belnap, Jayne; Kuske, Cheryl R.

2013-01-01

Biological soil crusts (biocrusts) are common to drylands worldwide. We employed replicated, spatially nested sampling and 16S rRNA gene sequencing to describe the soil microbial communities in three soils derived from different parent material (sandstone, shale, and gypsum). For each soil type, two depths (biocrusts, 0–1 cm; below-crust soils, 2–5 cm) and two horizontal spatial scales (15 cm and 5 m) were sampled. In all three soils, Cyanobacteria and Proteobacteria demonstrated significantly higher relative abundance in the biocrusts, while Chloroflexi and Archaea were significantly enriched in the below-crust soils. Biomass and diversity of the communities in biocrusts or below-crust soils did not differ with soil type. However, biocrusts on gypsum soil harbored significantly larger populations of Actinobacteria and Proteobacteria and lower populations of Cyanobacteria. Numerically dominant operational taxonomic units (OTU; 97% sequence identity) in the biocrusts were conserved across the soil types, whereas two dominant OTUs in the below-crust sand and shale soils were not identified in the gypsum soil. The uniformity with which small-scale vertical community differences are maintained across larger horizontal spatial scales and soil types is a feature of dryland ecosystems that should be considered when designing management plans and determining the response of biocrusts to environmental disturbances.

Specificity of Cs-137 redistribution in toposequence of arable soils cultivated after the Chernobyl accident

NASA Astrophysics Data System (ADS)

Korobova, Elena; Romanov, Sergey; Baranchukov, Vladimir; Berezkin, Victor; Moiseenko, Fedor; Kirov, Sergey

2017-04-01

Investigations performed after the Chernobyl accident showed high spatial variation of radionuclide contamination of the soil cover in elementary landscape geochemical systems (ELGS) that characterize catena's structure. Our studies of Cs-137 distribution along and cross the slopes of local ridges in natural forested key site revealed a cyclic character of variation of the radionuclide surface activity along the studied transections (Korobova et al, 2008; Korobova, Romanov, 2009; 2011). We hypothesized that the observed pattern reflects a specific secondary migration of Cs-137 with water, and that this process could have taken place in any ELGS. To test this hypothesis a detailed field measurement of Cs-137 surface activity was performed in ELGS in agricultural area cultivated after the Chernobyl accident but later withdrawn from land-use. In situ measurements carried out by field gamma-spectrometry were accompanied by soil core sampling at the selected points. Soil samples were taken in increments of 2 cm down to 20 cm and of 5 cm down to 40 cm. The samples were analyzed for Cs-137 in laboratory using Canberra gamma-spectrometer with HP-Ge detector. Obtained results confirmed the fact of area cultivation down to 20 cm that was clearly traced by Cs-137 profile in soil columns. At the same time, the measurements also showed a cyclic character of Cs-137 variation in a sequence of ELGS from watershed to the local depression similar to that found in woodland key site. This proved that the observed pattern is a natural process typical for matter migration in ELGS independently of the vegetation type and ploughing. Therefore, spatial aspect is believed to be an important issue for development of adequate technique for a forecast of contamination of agricultural production and remediation of the soil cover on the local scale within the contaminated areas. References Korobova, E.M., Romanov, S.L., 2009. A Chernobyl 137Cs contamination study as an example for the spatial structure of geochemical fields and modeling of the geochemical field //Chemometrics and Intelligent Laboratory Systems, 99, 1-8. Korobova, E., Romanov S., 2011. Experience of mapping spatial structure of Cs-137 in natural landscape and patterns of its distribution in soil toposequence // Journal of Geochemical Exploration, 109, 1-3, 139-145. Korobova Elena, Sergey Romanov, Vladimir Samsonov, Fedor Moiseenko, 2008. Peculiarities of spatial structure of 137Cs contamination field in landscape toposequence: regularities in geo-field structure. Proceedings of the International Conference on Radioecology and Environmental Radioactivity, 15-20 June 2008, Bergen, Norway, Part 2, 182-186.

Digital Terroir Mapping in the Tokaj Historical Wine Region

NASA Astrophysics Data System (ADS)

Pásztor, László; Lukácsy, György; Szabó, József; László, Péter; Burai, Péter; Bakacsi, Zsófia; Koós, Sándor; Laborczi, Annamária; Takács, Katalin; Bekő, László

2015-04-01

Tokaj is a historical region for botritized dessert wine making, the famed Tokaji Wine Region has the distinction of being Europe's first classified wine region. Very recently the sustainable quality wine production in the region was targeted, which requires detailed and "terroir-based approach" characterization of viticultural land. Tokaj region consists of 27 villages, the total producing vineyard surface area is 5,500 hectares, and the total vineyard land exceeds 11,000 hectares. The Tokaj Kereskedőház Ltd. is the only state owned winery in Hungary. The company is integrating grapes for wine production from 1,100 hectares of vineyard, which consist of 3,500 parcels with average size of 0.3 hectares. In 2013 the Hungarian Government has decided to elaborate a sustainable quality wine production in the Tokaj region coordinated by the Tokaj Kereskedőház Ltd, the biggest wine producer. To achieve the target it is indispensable to assess the viticultural potential of the land. In 2013 the characterization of the vineyard land potential was started collecting detailed, up-to-date information on the main environmental factors (geology, geomorphology and soil) which comprise the terroir effect and combined with legacy data of climate. The Council of Wine Communities of Tokaj Region has decided to widen the survey for the whole wine region in the year 2014. The primary objective of our work was the execution of an appropriate terroir zoning, which was carried out by digital terroir mapping. As a start-up we adapted some concepts recently applied in French wine regions. The implementation was however carried out totally in spatial, digital environment. Four main sources of information have been used (i) airborne laser scanning, (ii) hyperspectral imaginary, (iii) digital soil maps compiled based on detailed soil survey and (iv) interpolated climatic data. Based on them pedoclimate, mesoclimate and soil water reservoir were spatially predicted. The operational spatial resolution was set to 25 meters as a compromise between the denser remotely sensed data and the resolution available by the spatial inference of the collected soil information by proper digital soil mapping techniques. Finally the plant available water content, the vigor potential and precocity (earliness) potential was calculated. Based on these three maps the optimal target of production (dessert wine, dry wine, sparkling wine) could be determined and the information could provide a basis for decisions made both prior to planting and during production. Acknowledgement: The authors are grateful to the Tokaj Kereskedőház Ltd. and to András Tombor, Head of the Supervisory Board of Tokaj Kereskedőház Ltd. who has been supporting the project for the survey of the state of vineyards. Digital soil mapping was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Atmospheric and geogenic CO2 within the crown and root of spruce (Picea abies L. Karst.) growing in a mofette area

NASA Astrophysics Data System (ADS)

Vodnik, D.; Thomalla, A.; Ferlan, M.; Levanič, T.; Eler, K.; Ogrinc, N.; Wittmann, C.; Pfanz, H.

2018-06-01

Mofettes are often investigated in ecology, either as extreme sites, natural analogues to future conditions under climate change, or model ecosystems for environmental impact assessments of carbon capture and storage systems. Much of this research, however, inadequately addresses the complexity of the gas environment at these sites, mainly focusing on aboveground CO2-enrichment. In the current research, the gaseous environment of Norway spruce (Picea abies (L) Karst.) trees growing at the Stavešinske slepice mofette (NE Slovenia) were studied by measuring both soil ([CO2]soil) and atmospheric CO2 concentrations ([CO2]air). Within the studied site (800 m2), soil CO2 enrichment was spatially heterogeneous; about 25% of the area was characterized by very high [CO2]soil (>40%) and hypoxic conditions. Aboveground gas measurements along vertical profiles not only revealed substantially elevated [CO2]air close to the ground (height up to 1.5 m), but also in the upper heights (20-25 m; crown layer). On the basis δ13C of CO2, it was shown that elevated CO2 relates to a geogenic source. Trees grown in high [CO2]soil were characterized by decreased radial growth; the δ13C of their wood was less negative than in trees growing in normal soil. Unfavorable gaseous soil conditions should generally be accepted as being by far the most important factor affecting (i.e. disturbing) the growth of mofette trees.

Spatial and temporal variability of groundwater recharge in Geba basin, Northern Ethiopia

NASA Astrophysics Data System (ADS)

Yenehun, Alemu; Walraevens, Kristine; Batelaan, Okke

2017-10-01

WetSpa, a physically based, spatially distributed watershed model, has been used to study the spatial and temporal variation of recharge in the Geba basin, Northern Ethiopia. The model covers an area of about 4, 249 km2 and integrates elevation, soil and land-use data, hydrometeorological and river discharge data. The Geba basin has a highly variable topography ranging from 1000 to 3280 m with an average slope of 12.9%. The area is characterized by a distinct wet and long dry season with a mean annual precipitation of 681 mm and temperatures ranging between 6.5 °C and 32 °C. The model was simulated on daily basis for nearly four years (January 1, 2000 to December 18, 2003). It resulted in a good agreement between measured and simulated streamflow hydrographs with Nash-Sutcliffe efficiency of almost 70% and 85% for, respectively, the calibration and validation. The water balance terms show very strong spatial and temporal variability, about 3.8% of the total precipitation is intercepted by the plant canopy; 87.5% infiltrates into the soil (of which 13% percolates, 2.7% flows laterally off and 84.2% evapotranspired from the root zone), and 7.2% is surface runoff. The mean annual recharge varies from about 45 mm (2003) to 208 mm (2001), with average of 98.6 mm/yr. On monthly basis, August has the maximum (73 mm) and December the lowest (0.1 mm) recharge. The mean annual groundwater recharge spatially varies from 0 to 371 mm; mainly controlled by the distribution of rainfall amount, followed by soil and land-use, and to a certain extent, slope. About 21% of Geba has a recharge larger than 120 mm and 1% less than 5 mm.

Assessing soil carbon vulnerability in the Western USA by geospatial modeling of pyrogenic and particulate carbon stocks

NASA Astrophysics Data System (ADS)

Ahmed, Zia U.; Woodbury, Peter B.; Sanderman, Jonathan; Hawke, Bruce; Jauss, Verena; Solomon, Dawit; Lehmann, Johannes

2017-02-01

To predict how land management practices and climate change will affect soil carbon cycling, improved understanding of factors controlling soil organic carbon fractions at large spatial scales is needed. We analyzed total soil organic (SOC) as well as pyrogenic (PyC), particulate (POC), and other soil organic carbon (OOC) fractions in surface layers from 650 stratified-sampling locations throughout Colorado, Kansas, New Mexico, and Wyoming. PyC varied from 0.29 to 18.0 mg C g-1 soil with a mean of 4.05 mg C g-1 soil. The mean PyC was 34.6% of the SOC and ranged from 11.8 to 96.6%. Both POC and PyC were highest in forests and canyon bottoms. In the best random forest regression model, normalized vegetation index (NDVI), mean annual precipitation (MAP), mean annual temperature (MAT), and elevation were ranked as the top four important variables determining PyC and POC variability. Random forests regression kriging (RFK) with environmental covariables improved predictions over ordinary kriging by 20 and 7% for PyC and POC, respectively. Based on RFK, 8% of the study area was dominated (≥50% of SOC) by PyC and less than 1% was dominated by POC. Furthermore, based on spatial analysis of the ratio of POC to PyC, we estimated that about 16% of the study area is medium to highly vulnerable to SOC mineralization in surface soil. These are the first results to characterize PyC and POC stocks geospatially using stratified sampling scheme at the scale of 1,000,000 km2, and the methods are scalable to other regions.

Models for root water uptake under deficit irrigation

NASA Astrophysics Data System (ADS)

Lazarovitch, Naftali; Krounbi, Leilah; Simunek, Jirka

2010-05-01

Modern agriculture, with its dependence on irrigation, fertilizers, and pesticide application, contributes significantly to the water and solute influx through the soil into the groundwater, specifically in arid areas. The quality and quantity of this water as it passes through the vadose zone is influenced primarily by plant roots. Root water uptake is a function of both a physical root parameter, commonly referred to as the root length density, and the soil water status. The location of maximum water uptake in a homogenous soil profile of uniform water content and hydraulic conductivity occurs in the soil layer containing the largest root length density. Under field conditions, in a drying soil, plants are both subject to, and the source of, great spatial variability in the soil water content. The upper soil layers containing the bulk of the root zone are usually the most water depleted, while the deeper regions of the soil profile containing fewer roots are wetter. Changes in the physiological functioning of plants have been shown to result from extended periods of water stress, but the short term effects of water stress on root water uptake are less well understood. While plants can minimize transpiration and the resulting growth rates under limiting conditions to conserve water, many plants maintain a constant potential transpiration rate long after the commencement of the drying process. Compensatory uptake, whereby plants respond to non-uniform, limiting conditions by increasing water uptake from areas in the root zone characterized by more favorable conditions, is one such mechanism by which plants sustain potential transpiration rates in drying soils. The development of models which accurately characterize temporal and spatial root water uptake patterns is important for agricultural resource optimization, upon which subsequent management decisions affecting resource conservation and environmental pollution are based. Numerical simulations of root water uptake in various irrigation and fertilization regimes provide a much-needed alternative to tiring and expensive field work. These simulations can aid in raising agricultural water use efficiency while preserving soil and water resources. In this research, controlled lab experiments were carried out in soil-packed lysimeters designed for plant cultivation. Both the water balance of the growing plants as well as the temporary matric head distribution in the soil profile were calculated and measured. The experiment was conducted with sweet sorghum grown in two different soil profiles with different hydraulic properties. The experiment provided the data necessary to calculate the parameters of various models used to simulate root water uptake, by using an inverse solution method imbedded in the HYDRUS-1D code. The observed increase in uptake from the wetter soil regions under drying conditions, as measured and calculated, sheds light on the dominant role of soil hydraulic properties over the root distribution, and consequently root water uptake.

Systems, methods, and software for determining spatially variable distributions of the dielectric properties of a heterogeneous 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

Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed, China.

PubMed

Wei, Jianbing; Feng, Hao; Cheng, Quanguo; Gao, Shiqian; Liu, Haiyan

2017-02-01

The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate-nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.

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 ...

Derivation of spatial patterns of soil hydraulic properties based on pedotransfer functions

USDA-ARS?s Scientific Manuscript database

Spatial patterns in soil hydrology are the product of the spatial distribution of soil hydraulic properties. These properties are notorious for the difficulties and high labor costs involved in measuring them. Often, there is a need to resort to estimating these parameters from other, more readily a...

Estimating spatial variations in water content of clay soils from time-lapse electrical conductivity surveys

USDA-ARS?s Scientific Manuscript database

Soil water content (theta) is one of the most important drivers for many biogeochemical fluxes at different temporal and spatial scales. Hydrogeophysical non-invasive sensors that measure the soil apparent electrical conductivity (ECa) have been widely used to infer spatial and temporal patterns of...

Spatial Distribution of Surface Soil Moisture in a Small Forested Catchment

EPA Science Inventory

Predicting the spatial distribution of soil moisture is an important hydrological question. We measured the spatial distribution of surface soil moisture (upper 6 cm) using an Amplitude Domain Reflectometry sensor at the plot scale (2 × 2 m) and small catchment scale (0.84 ha) in...

Spatial distribution and temporal trends of rainfall erosivity in mainland China for 1951-2010

Treesearch

Wei Qin; Qiankun Guo; Changqing Zuo; Zhijie Shan; Liang Ma; Ge Sun

2016-01-01

Rainfall erosivity is an important factor for estimating soil erosion rates. Understanding the spatial distributionand temporal trends of rainfall erosivity is especially critical for soil erosion risk assessment and soil conservationplanning in mainland China. However, reports on the spatial distribution and temporal trends of rainfall...

Thresholds for soil cover and weathering in mountainous landscapes

NASA Astrophysics Data System (ADS)

Dixon, Jean; Benjaram, Sarah

2017-04-01

The patterns of soil formation, weathering, and erosion shape terrestrial landscapes, forming the foundation on which ecosystems and human civilizations are built. Several fundamental questions remain regarding how soils evolve, especially in mountainous landscapes where tectonics and climate exert complex forcings on erosion and weathering. In these systems, quantifying weathering is made difficult by the fact that soil cover is discontinuous and heterogeneous. Therefore, studies that attempt to measure soil weathering in such systems face a difficult bias in measurements towards more weathered portions of the landscape. Here, we explore current understanding of erosion-weathering feedbacks, and present new data from mountain systems in Western Montana. Using field mapping, analysis of LiDAR and remotely sensed land-cover data, and soil chemical analyses, we measure soil cover and surface weathering intensity across multiple spatial scales, from the individual soil profile to a landscape perspective. Our data suggest that local emergence of bedrock cover at the surface marks a landscape transition from supply to kinetic weathering regimes in these systems, and highlights the importance of characterizing complex critical zone architecture in mountain landscapes. This work provides new insight into how landscape morphology and erosion may drive important thresholds for soil cover and weathering.

High heterogeneity in soil composition and quality in different mangrove forests of Venezuela.

PubMed

Otero, X L; Méndez, A; Nóbrega, G N; Ferreira, T O; Meléndez, W; Macías, F

2017-09-18

Mangrove forests play an important role in biogeochemical cycles of metals, nutrients, and C in coastal ecosystems. However, these functions could be strongly affected by the mangrove soil degradation. In this study, we performed an intensive sampling characterizing mangrove soils under different types of environment (lagoon/gulf) and vegetation (Rhizophora/Avicennia/dead mangrove) in the Venezuelan coast. To better understand the spatial heterogeneity of the composition and characteristics of the soils, a wide range of the soil attributes were analyzed. In general, the soils were anoxic (Eh < 200 mV), with a neutral pH and low concentration in toxic metals; nevertheless, they varied widely in the soil and its quality-defining parameters (e.g., clay contents, total organic carbon, Fe, Al, toxic trace metals). It is noteworthy that the mangroves presented a low Fe Pyrite content due to a limitation in the Fe oxyhydroxide contents, especially in soils with higher organic C content (TOC > 15%). Finally, the dead mangrove showed significantly lower amounts of TOC and fibers (in comparison to the well-preserved mangrove forest), which indicates that the C pools in mangrove soils are highly sensitive also to natural impact, such as ENSO.

Methodological approach for evaluating the response of soil hydrological behavior to irrigation with treated municipal wastewater

NASA Astrophysics Data System (ADS)

Coppola, A.; Santini, A.; Botti, P.; Vacca, S.; Comegna, V.; Severino, G.

2004-06-01

This paper aims mainly to provide experimental evidence of the consequences of urban wastewater reuse in irrigation practices on the hydrological behavior of soils. The effects on both the hydraulic and dispersive properties of representative soils in southern Sardinia are illustrated. Ten undisturbed soil monoliths, 120 cm in height and 40 cm in diameter, were collected from plots previously selected through a soil survey. Soil hydraulic and solute transport properties were determined before and after application of wastewater using transient water infiltration and steady state-solute transport column experiments. Detailed spatial-temporal information on the propagation of water and solute through the soil profiles were obtained by monitoring soil water contents, θ, pressure heads, h, and solute concentrations, C, measured by a network of time domain reflectometry probes, tensiometers and solution samplers horizontally inserted in each column at different depths. A disturbed layer at the soil surface, which expands in depth with time, was observed, characterized by reduced soil porosity, translation of pore size distribution towards narrower pores and consequent decrease in water retention, hydraulic conductivity and hydrodynamic dispersion. It is shown that these changes occurring in the disturbed soil layer, although local by nature, affect the hydrological behavior of the whole soil profile. Due to the disturbed layer formation, the soil beneath never saturates. Such behavior has important consequences on the solute transport in soils, as unsaturated conditions mean higher residence times of solutes, even of those normally characterized by considerable mobility (e.g. boron), which may accumulate along the profile. The results mainly provide experimental evidence that knowledge of the chemical and microbiological composition of the water is not sufficient to evaluate its suitability for irrigation. Other factors, mainly soil physical and hydrological characteristics, should be considered in order to define appropriate guidelines for wastewater management.

Remote sensing research for agricultural applications. [San Joaquin County, California and Snake River Plain and Twin Falls area, Idaho

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.

Using agricultural practices information for multiscale environmental assessment of phosphorus risk

NASA Astrophysics Data System (ADS)

Matos Moreira, Mariana; Lemercier, Blandine; Michot, Didier; Dupas, Rémi; Gascuel-Odoux, Chantal

2015-04-01

Phosphorus (P) is an essential nutrient for plant growth. In intensively farmed areas, excessive applications of animal manure and mineral P fertilizers to soils have raised both economic and ecological concerns. P accumulation in agricultural soils leads to increased P losses to surface waterbodies contributing to eutrophication. Increasing soil P content over time in agricultural soils is often correlated with agricultural practices; in Brittany (NW France), an intensive livestock farming region, soil P content is well correlated with animal density (Lemercier et al.,2008). Thus, a better understanding of the factors controlling P distribution is required to enable environmental assessment of P risk. The aim of this study was to understand spatial distribution of extractable (Olsen method) and total P contents and its controlling factors at the catchment scale in order to predict P contents at regional scale (Brittany). Data on soil morphology, soil tests (including P status, particles size, organic carbon…) for 198 punctual positions, crops succession since 20 years, agricultural systems, field and animal manure management were obtained on a well-characterized catchment (ORE Agrhys, 10 km²). A multivariate analysis with mixed quantitative variables and factors and a digital soil mapping approach were performed to identify variables playing a significant role in soil total and extractable P contents and distribution. Spatial analysis was performed by means of the Cubist model, a decision tree-based algorithm. Different scenarios were assessed, considering various panels of predictive variables: soil data, terrain attributes derived from digital elevation model, gamma-ray spectrometry (from airborne geophysical survey) and agricultural practices information. In the research catchment, mean extractable and total P content were 140.0 ± 63.4 mg/kg and 2862.7 ± 773.0 mg/kg, respectively. Organic and mineral P inputs, P balance, soil pH, and Al contents were positively correlated with soil P contents. Also land use, crop rotation and livestock production system influenced P contents. The highest mean values of P were found in croplands and close to pig farms. The lowest mean values of P were found in pastures and nearby dairy farms. The spatial analysis showed that sand content, geophysical parameters and P input by organic fertilization were the most significant variables for the linear predictive model of extractable P contents. For total P, geophysical parameters and P balance had the highest importance for the respective linear predictive model. This study revealed that agricultural practices information plays a significant role in soil P distribution. Once controlling factors of P spatial distribution were identified, relationships could be extrapolated at regional scale using the National Soil Test Database providing information on extractable P content and available information on agricultural practices in order to improve predictions of total P content at regional scale. Lemercier B., Gaudin, L., Walter C., Aurousseau P., Arrouays D., Schvartz C., Saby N., Follain S., Abrassart J., 2008. Soil phosphorus monitoring at the regional level by means of a soil test database. Soil Use and Management, 24, 131-138.

Using soil residence time to delineate spatial and temporal patterns of transient landscape response

NASA Astrophysics Data System (ADS)

Almond, Peter; Roering, Josh; Hales, T. C.

2007-09-01

On hillslopes the balance between soil transport and production determines local soil thickness and the age distribution of particles that comprise the soil (where age refers to the time elapsed since detachment from bedrock). The mean of this age distribution is defined as the residence time, and in a landscape with time-invariant topography (i.e., morphologic steady state), the spatial uniformity of soil production ensures that the residence time of soils is spatially invariant. Thus, given constant soil-forming factors, spatial variation of soil properties reflects differences in residence time driven by nonuniform soil production. Spatially extensive soil databases, which are often freely available in electronic form, provide a cheap and accessible means of analyzing patterns of soil residence time and quantifying landscape dynamics. Here we use a soil chronosequence to calibrate a chronofunction describing the reddening of soils in the Oregon Coast Range, which is then used to quantify the spatial distribution of soil residence time. In contrast to the popular conception that the Oregon Coast Range experiences uniform erosion, we observe systematic variations in soil residence time driven by stream capture, deep-seated landsliding, and lateral channel migration. Large, contiguous areas with short residence time soils (hue 10YR) occur west of the Siuslaw River-Long Tom Creek drainage divide, whereas soil patches with redder hues of 7.5YR or 5YR indicate longer residence times and transient landscape conditions. These zones of red soils (5YR) occur east of the Siuslaw-Long Tom divide, coinciding with low-gradient ridge and valley topography and deeply alluviated valleys resulting from drainage reversal in the Quaternary. Patches of red soils are also associated with deep-seated landslides at various locations in our study area. Our calculated soil residence times appear subject to overestimation resulting from limitations of the simple weathering index used here and chronofunction calibration uncertainties. Nonetheless, our soil residence time estimates appear accurate to within an order of magnitude and provide a useful constraint on landscape dynamics over geomorphic timescales.

Biological framework for soil aggregation: Implications for ecological functions.

NASA Astrophysics Data System (ADS)

Ghezzehei, Teamrat; Or, Dani

2016-04-01

Soil aggregation is heuristically understood as agglomeration of primary particles bound together by biotic and abiotic cementing agents. The organization of aggregates is believed to be hierarchical in nature; whereby primary particles bond together to form secondary particles and subsequently merge to form larger aggregates. Soil aggregates are not permanent structures, they continuously change in response to internal and external forces and other drivers, including moisture, capillary pressure, temperature, biological activity, and human disturbances. Soil aggregation processes and the resulting functionality span multiple spatial and temporal scales. The intertwined biological and physical nature of soil aggregation, and the time scales involved precluded a universally applicable and quantifiable framework for characterizing the nature and function of soil aggregation. We introduce a biophysical framework of soil aggregation that considers the various modes and factors of the genesis, maturation and degradation of soil aggregates including wetting/drying cycles, soil mechanical processes, biological activity and the nature of primary soil particles. The framework attempts to disentangle mechanical (compaction and soil fragmentation) from in-situ biophysical aggregation and provides a consistent description of aggregate size, hierarchical organization, and life time. It also enables quantitative description of biotic and abiotic functions of soil aggregates including diffusion and storage of mass and energy as well as role of aggregates as hot spots of nutrient accumulation, biodiversity, and biogeochemical cycles.

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; Rodell, Matthew; Li, Bailing; Reichle, Rolf; Zaitchik, Benjamin F.

2012-01-01

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

Biotic and abiotic controls on diurnal fluctuations in labile soil phosphorus of a wet tropical forest.

PubMed

Vandecar, Karen L; Lawrence, Deborah; Wood, Tana; Oberbauer, Steven F; Das, Rishiraj; Tully, Katherine; Schwendenmann, Luitgard

2009-09-01

The productivity of many tropical wet forests is generally limited by bioavailable phosphorus (P). Microbial activity is a key regulator of P availability in that it determines both the supply of P through organic matter decomposition and the depletion of bioavailable P through microbial uptake. Both microbial uptake and mineralization occur rapidly, and their net effect on P availability varies with soil moisture, temperature, and soil organic matter quantity and quality. Exploring the mechanisms driving P availability at fine temporal scales can provide insight into the coupling of carbon, water, and nutrient cycles, and ultimately, the response of tropical forests to climate change. Despite the recognized importance of P cycling to the dynamics of wet tropical forests and their potential sensitivity to short-term fluctuations in bioavailable P, the diurnal pattern of P remains poorly understood. This study quantifies diurnal fluctuations in labile soil P and evaluates the importance of biotic and abiotic factors in driving these patterns. To this end, measurements of labile P were made every other hour in a Costa Rican wet tropical forest oxisol. Spatial and temporal variation in Bray-extractable P were investigated in relation to ecosystem carbon flux, soil CO2 efflux, soil moisture, soil temperature, solar radiation, and sap-flow velocity. Spatially averaged bi-hourly (every two hours) labile P ranged from 0.88 to 2.48 microg/g across days. The amplitude in labile P throughout the day was 0.61-0.82 microg/g (41-54% of mean P concentrations) and was characterized by a bimodal pattern with a decrease at midday. Labile P increased with soil CO2 efflux and soil temperature and declined with increasing sap flow and solar radiation. Together, soil CO2 efflux, soil temperature, and sap flow explained 86% of variation in labile P.

Using the Spatial Persistence of Soil Moisture Patterns to Estimate Catchment Soil Moisture in Semi-arid Areas

NASA Astrophysics Data System (ADS)

Willgoose, G. R.

2006-12-01

In humid catchments the spatial distribution of soil water is dominated by subsurface lateral fluxes, which leads to a persistent spatial pattern of soil moisture principally described by the topographic index. In contrast, semi-arid, and dryer, catchments are dominated by vertical fluxes (infiltration and evapotranspiration) and persistent spatial patterns, if they exist, are subtler. In the first part of this presentation the results of a reanalysis of a number of catchment-scale long-term spatially-distributed soil moisture data sets are presented. We concentrate on Tarrawarra and SASMAS, both catchments in Australia that are water-limited for at least part of the year and which have been monitored using a variety of technologies. Using the data from permanently installed instruments (neutron probe and reflectometry) both catchments show persistent patterns at the 1-3 year timescale. This persistent pattern is not evident in the field campaign data where field portable instruments (reflectometry) instruments were used. We argue, based on high-resolution soil moisture semivariograms, that high short-distance variability (100mm scale) means that field portable instrument cannot be replaced at the same location with sufficient accuracy to ensure deterministic repeatability of soil moisture measurements from campaign to campaign. The observed temporal persistence of the spatial pattern can be caused by; (1) permanent features of the landscape (e.g. vegetation, soils), or (2) long term memory in the soil moisture store. We argue that it is permanent in which case it is possible to monitor the soil moisture status of a catchment using a single location measurement (continuous in time) of soil moisture using a permanently installed reflectometry instrument. This instrument will need to be calibrated to the catchment averaged soil moisture but the temporal persistence of the spatial pattern of soil moisture will mean that this calibration will be deterministically stable with time. In the second part of this presentation we will explore aspects of the calibration using data from the SASMAS site using the multiscale spatial resolution data (100m to 10km) provided by permanently installed reflectometry instruments, and how this single site measurement technique may complement satellite data.

Exploratory and spatial data analysis (EDA-SDA) for determining regional background levels and anomalies of potentially toxic elements in soils from Catorce-Matehuala, Mexico

USGS Publications Warehouse

Chiprés, J.A.; Castro-Larragoitia, J.; Monroy, M.G.

2009-01-01

The threshold between geochemical background and anomalies can be influenced by the methodology selected for its estimation. Environmental evaluations, particularly those conducted in mineralized areas, must consider this when trying to determinate the natural geochemical status of a study area, quantifying human impacts, or establishing soil restoration values for contaminated sites. Some methods in environmental geochemistry incorporate the premise that anomalies (natural or anthropogenic) and background data are characterized by their own probabilistic distributions. One of these methods uses exploratory data analysis (EDA) on regional geochemical data sets coupled with a geographic information system (GIS) to spatially understand the processes that influence the geochemical landscape in a technique that can be called a spatial data analysis (SDA). This EDA-SDA methodology was used to establish the regional background range from the area of Catorce-Matehuala in north-central Mexico. Probability plots of the data, particularly for those areas affected by human activities, show that the regional geochemical background population is composed of smaller subpopulations associated with factors such as soil type and parent material. This paper demonstrates that the EDA-SDA method offers more certainty in defining thresholds between geochemical background and anomaly than a numeric technique, making it a useful tool for regional geochemical landscape analysis and environmental geochemistry studies.

Subsurface flow and vegetation patterns in tidal environments

NASA Astrophysics Data System (ADS)

Ursino, Nadia; Silvestri, Sonia; Marani, Marco

2004-05-01

Tidal environments are characterized by a complex interplay of hydrological, geomorphic, and biological processes, and their understanding and modeling thus require the explicit description of both their biotic and abiotic components. In particular, the presence and spatial distribution of salt marsh vegetation (a key factor in the stabilization of the surface soil) have been suggested to be related to topographic factors and to soil moisture patterns, but a general, process-based comprehension of this relationship has not yet been achieved. The present paper describes a finite element model of saturated-unsaturated subsurface flow in a schematic salt marsh, driven by tidal fluctuations and evapotranspiration. The conditions leading to the establishment of preferentially aerated subsurface zones are studied, and inferences regarding the development and spatial distribution of salt marsh vegetation are drawn, with important implications for the overall ecogeomorphological dynamics of tidal environments. Our results show that subsurface water flow in the marsh induces complex water table dynamics, even when the tidal forcing has a simple sinusoidal form. The definition of a space-dependent aeration time is then proposed to characterize root aeration. The model shows that salt marsh subsurface flow depends on the distance from the nearest creek or channel and that the subsurface water movement near tidal creeks is both vertical and horizontal, while farther from creeks, it is primarily vertical. Moreover, the study shows that if the soil saturated conductivity is relatively low (10-6 m s-1, values quite common in salt marsh areas), a persistently unsaturated zone is present below the soil surface even after the tide has flooded the marsh; this provides evidence of the presence of an aerated layer allowing a prolonged presence of oxygen for aerobic root respiration. The results further show that plant transpiration increases the extent and persistence of the aerated layer, thereby introducing a strong positive feedback: Pioneer plants on marsh edges have the effect of increasing soil oxygen availability, thus creating the conditions for the further development of other plant communities.

Spatial distribution of enzyme driven reactions at micro-scales

NASA Astrophysics Data System (ADS)

Kandeler, Ellen; Boeddinghaus, Runa; Nassal, Dinah; Preusser, Sebastian; Marhan, Sven; Poll, Christian

2017-04-01

Studies of microbial biogeography can often provide key insights into the physiologies, environmental tolerances, and ecological strategies of soil microorganisms that dominate in natural environments. In comparison with aquatic systems, soils are particularly heterogeneous. Soil heterogeneity results from the interaction of a hierarchical series of interrelated variables that fluctuate at many different spatial and temporal scales. Whereas spatial dependence of chemical and physical soil properties is well known at scales ranging from decimetres to several hundred metres, the spatial structure of soil enzymes is less clear. Previous work has primarily focused on spatial heterogeneity at a single analytical scale using the distribution of individual cells, specific types of organisms or collective parameters such as bacterial abundance or total microbial biomass. There are fewer studies that have considered variations in community function and soil enzyme activities. This presentation will give an overview about recent studies focusing on spatial pattern of different soil enzymes in the terrestrial environment. Whereas zymography allows the visualization of enzyme pattern in the close vicinity of roots, micro-sampling strategies followed by MUF analyses clarify micro-scale pattern of enzymes associated to specific microhabitats (micro-aggregates, organo-mineral complexes, subsoil compartments).

Spatial Analysis of PAHs in Soils along an Urban-Suburban-Rural Gradient: scale effect, distribution patterns, diffusion and influencing factors

NASA Astrophysics Data System (ADS)

Peng, Chi; Wang, Meie; Chen, Weiping

2016-11-01

Spatial statistical methods including Cokriging interpolation, Morans I analysis, and geographically weighted regression (GWR) were used for studying the spatial characteristics of polycyclic aromatic hydrocarbon (PAH) accumulation in urban, suburban, and rural soils of Beijing. The concentrations of PAHs decreased spatially as the level of urbanization decreased. Generally, PAHs in soil showed two spatial patterns on the regional scale: (1) regional baseline depositions with a radius of 16.5 km related to the level of urbanization and (2) isolated pockets of soil contaminated with PAHs were found up to around 3.5 km from industrial point sources. In the urban areas, soil PAHs showed high spatial heterogeneity on the block scale, which was probably related to vegetation cover, land use, and physical soil disturbance. The distribution of total PAHs in urban blocks was unrelated to the indicators of the intensity of anthropogenic activity, namely population density, light intensity at night, and road density, but was significantly related to the same indicators in the suburban and rural areas. The moving averages of molecular ratios suggested that PAHs in the suburban and rural soils were a mix of local emissions and diffusion from urban areas.

The underlying processes of a soil mite metacommunity on a small scale.

PubMed

Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.

The underlying processes of a soil mite metacommunity on a small scale

PubMed Central

Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906

Regional Impacts of Woodland Expansion on Nitrogen Oxide Emissions from Texas Savannahs: Combining Field, Modeling and Remote Sensing Approaches

NASA Technical Reports Server (NTRS)

Asner, Gregory P. (Principal Investigator)

2003-01-01

Woody encroachment has contributed to documented changes world-wide and locally in the southwestern U.S. Specifically, in North Texas rangelands encroaching mesquite (Prosopis glandulosa var. glandulosa) a known N-fixing species has caused changes in aboveground biomass. While measurements of aboveground plant production are relatively common, measures of soil N availability are scarce and vary widely. N trace gas emissions (nitric and nitrous oxide) flom soils reflect patterns in current N cycling rates and availability as they are stimulated by inputs of organic and inorganic N. Quantification of N oxide emissions from savanna soils may depend upon the spatial distribution of woody plant canopies, and specifically upon the changes in N availability and cycling and subsequent N trace gas production as influenced by the shift from herbaceous to woody vegetation type. The main goal of this research was to determine whether remotely sensible parameters of vegetation structure and soil type could be used to quantify biogeochemical changes in N at local, landscape and regional scales. To accomplish this goal, field-based measurements of N trace gases were carried out between 2000-2001, encompassing the acquisition of imaging spectrometer data from the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) on September 29, 2001. Both biotic (vegetation type and soil organic N) and abiotic (soil type, soil pH, temperature, soil moisture, and soil inorganic N) controls were analyzed for their contributions to observed spatial and temporal variation in soil N gas fluxes. These plot level studies were used to develop relationships between spatially extensive, field-based measurements of N oxide fluxes and remotely sensible aboveground vegetation and soil properties, and to evaluate the short-term controls over N oxide emissions through intensive field wetting experiments. The relationship between N oxide emissions, remotely-sensed parameters (vegetation cover, and soil type), and physical controls (soil moisture, and temperature) permitted the regional scale quantification of soil N oxides emissions. Landscape scale analysis linking N oxide emissions with cover change revealed an alleviation from N limitation following mesquite invasion. This study demonstrated the advantage of using N trace gases as a measure of ecosystem N availability combined with remote sensing to characterize the spatial heterogeneity in ecosystem parameters at a scale commensurate with field-based measurements of these properties. Woody vegetation encroachment provided an opportunity to capitalize on detection of the remotely-sensible parameter of woody cover as it relates to belowground biogeochemical processes that determine N trace gas production. The first spatially-explicit estimates of NO flux were calculated based on Prosopis fractional cover derived from high resolution remote sensing estimates of fractional woody cover (< 4 m) for a 120 sq km region of North Texas. An assessment of both N stocks and fluxes from the study revealed an alleviation of N limitation at this site experiencing recent woody encroachment. Many arid and semi-arid regions of the world are experiencing woody invasions, often of N-fixing species. The issue of woody encroachment is in the center of an ecological and political debate. Improving the links between biogeochemical processes and remote sensing of ecosystem properties will improve our understanding of biogeochemical processes at the regional scale, thus providing a means to address issues of land-use and land-cover change.

A Centimeter-Scale Investigation of Geochemical Hotspots in a Soil Lysimeter

NASA Astrophysics Data System (ADS)

Umanzor, M.; Wang, Y.; Dontsova, K.; Chorover, J.; Troch, P. A. A.

2016-12-01

Studying the co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled Earth-system processes. Such knowledge is imperative for improving predictions of hydro-biogeochemical cycles, especially under climate change scenarios. Hotspots may form in porous media that is undergoing biogeochemical weathering at locations where reactants accumulate to threshold values along hydrologic flow paths. This is expected to occur in weatherable silicate media, like granular basalt. To examine such processes during incipient soil formation, we constructed a sloping weighing lysimeter 2-m in length, 0.5-m in width and 1-m in depth. Mini-LEO was filled with crushed granular basalt rock with a known initial chemical composition. After 18 months of irrigation and intensive hydrological study, the model "landscape" was divided into a 3D matrix of 324 voxels and excavated. Collected samples were subjected to detailed hydro-bio-geochemical analysis to assess the formation of geochemical heterogeneity. A five-step sequential extraction was employed to characterize incongruent mineral weathering, and its relation to the spatial distribution of microbial composition (in a related study). The changes in Fe and Mn concentration and speciation along the lysimeter length and depth (as measured by each step of the sequential extraction) was quantified to characterize spatial distribution of weathering processes. Results are being used to assist in understanding not only spatial and temporal distribution of basalt weathering on the slope, but also, connections between hydrological and biogeochemical cycles that lead to formation of hotspots.

Measuring spatial variability in soil characteristics

DOEpatents

Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard

2002-01-01

The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.

HESS Opinions: Functional units: a novel framework to explore the link between spatial organization and hydrological functioning of intermediate scale catchments

NASA Astrophysics Data System (ADS)

Zehe, E.; Ehret, U.; Pfister, L.; Blume, T.; Schröder, B.; Westhoff, M.; Jackisch, C.; Schymanski, S. J.; Weiler, M.; Schulz, K.; Allroggen, N.; Tronicke, J.; Dietrich, P.; Scherer, U.; Eccard, J.; Wulfmeyer, V.; Kleidon, A.

2014-03-01

This opinion paper proposes a novel framework for exploring how spatial organization alongside with spatial heterogeneity controls functioning of intermediate scale catchments of organized complexity. Key idea is that spatial organization in landscapes implies that functioning of intermediate scale catchments is controlled by a hierarchy of functional units: hillslope scale lead topologies and embedded elementary functional units (EFUs). We argue that similar soils and vegetation communities and thus also soil structures "co-developed" within EFUs in an adaptive, self-organizing manner as they have been exposed to similar flows of energy, water and nutrients from the past to the present. Class members of the same EFU (class) are thus deemed to belong to the same ensemble with respect to controls of the energy balance and related vertical flows of capillary bounded soil water and heat. Class members of superordinate lead topologies are characterized by the same spatially organized arrangement of EFUs along the gradient driving lateral flows of free water as well as a similar surface and bedrock topography. We hence postulate that they belong to the same ensemble with respect to controls on rainfall runoff transformation and related vertical and lateral fluxes of free water. We expect class members of these functional units to have a distinct way how their architecture controls the interplay of state dynamics and integral flows, which is typical for all members of one class but dissimilar among the classes. This implies that we might infer on the typical dynamic behavior of the most important classes of EFU and lead topologies in a catchment, by thoroughly characterizing a few members of each class. A major asset of the proposed framework, which steps beyond the concept of hydrological response units, is that it can be tested experimentally. In this respect, we reflect on suitable strategies based on stratified observations drawing from process hydrology, soil physics, geophysics, ecology and remote sensing which are currently conducted in replicates of candidate functional units in the Attert basin (Luxembourg), to search for typical and similar functional and structural characteristics. A second asset of this framework is that it blueprints a way towards a structurally more adequate model concept for water and energy cycles in intermediate scale catchments, which balances necessary complexity with falsifiability. This is because EFU and lead topologies are deemed to mark a hierarchy of "scale breaks" where simplicity with respect to the energy balance and stream flow generation emerges from spatially organized process-structure interactions. This offers the opportunity for simplified descriptions of these processes that are nevertheless physically and thermodynamically consistent. In this respect we reflect on a candidate model structure that (a) may accommodate distributed observations of states and especially terrestrial controls on driving gradients to constrain the space of feasible model structures and (b) allows testing the possible added value of organizing principles to understand the role of spatial organization from an optimality perspective.

Emerald ash borer and the urban forest: Changes in landslide potential due to canopy loss scenarios in the City of Pittsburgh, PA.

PubMed

Pfeil-McCullough, Erin; Bain, Daniel J; Bergman, Jeffery; Crumrine, Danielle

2015-12-01

Emerald ash borer is expected to kill thousands of ash trees in the eastern U.S. This research develops tools to predict the effect of ash tree loss from the urban canopy on landslide susceptibility in Pittsburgh, PA. A spatial model was built using the SINMAP (Stability INdex MAPping) model coupled with spatially explicit scenarios of tree loss (0%, 25%, 50%, and 75% loss of ash trees from the canopy). Ash spatial distributions were estimated via Monte Carlo methods and available vegetation plot data. Ash trees are most prevalent on steeper slopes, likely due to urban development patterns. Therefore, ash loss disproportionately increases hillslope instability. A 75% loss of ash resulted in roughly 800 new potential landslide initiation locations. Sensitivity testing reveals that variations in rainfall rates, and friction angles produce minor changes to model results relative to the magnitude of parameter variation, but reveal high model sensitivity to soil density and root cohesion values. The model predictions demonstrate the importance of large canopy species to urban hillslope stability, particularly on steep slopes and in areas where soils tend to retain water. To improve instability predictions, better characterization of urban soils, particularly spatial patterns of compaction and species specific root cohesion is necessary. The modeling framework developed in this research will enhance assessment of changes in landslide risk due to tree mortality, improving our ability to design economically and ecologically sustainable urban systems. Copyright © 2015 Elsevier B.V. All rights reserved.

An Improved GRACE Terrestrial Water Storage Assimilation System For Estimating Large-Scale Soil Moisture and Shallow Groundwater

NASA Astrophysics Data System (ADS)

Girotto, M.; De Lannoy, G. J. M.; Reichle, R. H.; Rodell, M.

2015-12-01

The Gravity Recovery And Climate Experiment (GRACE) mission is unique because it provides highly accurate column integrated estimates of terrestrial water storage (TWS) variations. Major limitations of GRACE-based TWS observations are related to their monthly temporal and coarse spatial resolution (around 330 km at the equator), and to the vertical integration of the water storage components. These challenges can be addressed through data assimilation. To date, it is still not obvious how best to assimilate GRACE-TWS observations into a land surface model, in order to improve hydrological variables, and many details have yet to be worked out. This presentation discusses specific recent features of the assimilation of gridded GRACE-TWS data into the NASA Goddard Earth Observing System (GEOS-5) Catchment land surface model to improve soil moisture and shallow groundwater estimates at the continental scale. The major recent advancements introduced by the presented work with respect to earlier systems include: 1) the assimilation of gridded GRACE-TWS data product with scaling factors that are specifically derived for data assimilation purposes only; 2) the assimilation is performed through a 3D assimilation scheme, in which reasonable spatial and temporal error standard deviations and correlations are exploited; 3) the analysis step uses an optimized calculation and application of the analysis increments; 4) a poor-man's adaptive estimation of a spatially variable measurement error. This work shows that even if they are characterized by a coarse spatial and temporal resolution, the observed column integrated GRACE-TWS data have potential for improving our understanding of soil moisture and shallow groundwater variations.

A multi-technique approach to assess chemical speciation of phosphate in soils

NASA Astrophysics Data System (ADS)

Belchior Abdala, Dalton; Rodrigues, Marcos; Herrera, Wilfrand; Pavinato, Paulo Sergio

2017-04-01

Soil scientists see chemical characterization of phosphorus (e.g., chemical speciation) as a winning strategy to increase phosphorus use efficiency in agriculture, to understand the fate of applied P fertilizer in soils and to devise strategies to minimize P losses to the environment. Phosphorus (P) is majorly presented in soils as phosphate, bound to mineral components of soils such as Al-, Ca- and Fe-(hydr)oxides or associated with organic molecules, being thus generally referred to as organic phosphates. In addition, because of the turnover of P between plants and microbes, it delivers P back to soils as a mixture of species with high spatial and chemical heterogeneity, adding complexity to the determination of the P species contained in environmental samples. Therefore, due to the variety of forms that phosphate can present in soils, its precise chemical characterization can only be achieved using a set of analytical techniques. Although established methodologies (e. g., soil test P, sequential chemical fractionation, P isotherms) have been useful to subsidize information for the establishment of policies and guidelines for soil management and P fertilizers use, they have failed to provide detailed information on P chemistry and reactivity in soils in a more satisfactory manner, which are critical to predict P bioavailability to plants and loss potential to the environment. More recently, the association of wet chemistry analysis with spectroscopy and microscopy techniques has arguably represented the most successful means to chemically speciate phosphate in soils. This is because using qualitative (chemical speciation), quantitative (chemical fractionation) and spatial (microscopy) data allows for triangulation of information, thereby reducing bias and increasing validity of the results. The analysis framework that we propose in this study includes the use of (i) sequential chemical fractionation of soil P to determine the partitioning of P within the different P pools considered in the fractionation protocol, (ii) two synchrotron-based X-ray absorption spectroscopic techniques, XANES and EXAFS, for chemical characterization of the P forms and mineralogy of Fe-(hydr)oxides present in a sample, and (iii) Scanning Electron Microscopy and Energy-Dispersive spectroscopy, SEM/EDS, to provide complimentary information to corroborate and aid in the interpretation of our P XANES data. It was shown that the combination of techniques can assist us not only in the determination of the P chemical species present in a given material, but also to better understand the complex and dynamic processes to which P is subjected in soils. The association of spectroscopy (XANES and EXAFS) and microscopy (SEM/EDS) with wet chemistry data in this study was key to shift our understanding of the relationship between P and other soil mineral components from a macroscopic into a microscopic one. This represents a strong driving force to integrate the results of multi-analytical techniques into a more complete understanding of the systems under study. In addition, we provide a library of reference spectra for P K-edge XANES containing P sorbed to single and binary mixtures of mineral analogues intended to assist in the identification of P sorbed species commonly found in soils and sediments. Key-words: P K-edge XANES, Fe K-edge EXAFS, sequential chemical fractionation, soil phosphorus

Geophysical surveys combined with laboratory soil column experiments to identify and explore risk areas for soil and water pollution in feedlots

NASA Astrophysics Data System (ADS)

Espejo-Pérez, Antonio Jesus; Sainato, Claudia Mabel; Jairo Márquez-Molina, John; Giráldez, Juan Vicente; Vanderlinden, Karl

2014-05-01

Changes of land use without a correct planning may produce its deterioration with their social, economical and environmental irreversible consequences over short to medium time range. In Argentina, the expansion of soybean fields induced a reduction of the area of pastures dedicated to stockbreeding. As cattle activity is being progressively concentrated on small pens, at feedlots farms, problems of soil and water pollution, mainly by nitrate, have been detected. The characterization of the spatial and temporal variability of soil water content is very important because the mostly advective transport of solutes. To avoid intensive soil samplings, very expensive, one has to recur to geophysical exploration methods. The objective of this work was to identify risk areas within a feedlot of the NW zone of Buenos Aires Province, in Argentina through geophysical methods. The surveys were carried out with an electromagnetic induction profiler EMI-400 (GSSI) and a Time domain Reflectometry (TDR) survey of depth 0-0.10 m with soil sampling and measurement of moisture content with gravimetric method (0-1.0 m). Several trenches were dug inside the pens and also at a test site, where texture, apparent density, saturated hydraulic conductivity (Ks), electrical conductivity of the saturation paste extract and organic matter content (OM) were measured. The water retention curves for these soils were also determined. At one of the pens undisturbed soil columns were extracted at 3 locations. Laboratory analysis for 0-1.0 m indicated that soil texture was classified as sandy loam, average organic matter content (OM) was greater than 2.3% with low values of apparent density in the first 10 cm. The range of spatial dependence of data suggested that the number of soil samples could be reduced. Soil apparent electrical conductivity (ECa) and soil moisture were well correlated and indicated a clear spatial pattern in the corrals. TDR performance was acceptable to identify the spatial pattern of moisture, although the absolute values were far from the real values obtained by gravimetric method due to the effect of the high OM. The lower zone in one of the pens showed greater values of ECa and soil moisture, in agreement with a major water retention and a lower Ks. The water retention was higher in the other corral with higher variability in Ks. A general decrease of soil moisture was found near 0.2 m soil depth. Leaching experiments detected greater volumes with higher electrical conductivity in low lying areas of the pen. Although differences were not observed as clearly as before, the low and intermediate low areas of the pen showed a faster rate of leaching. In summary geophysical surveys allowed identifying risk areas of high ECa and moisture which in fact had higher volumes of leachate with elevated electrical conductivities. This may be a good approach to control and reduce soil and groundwater contamination and to model in future works the process in order to establish management decisions.

Digital soil mapping in assessment of land suitability for organic farming

NASA Astrophysics Data System (ADS)

Ghambashidze, Giorgi; Kentchiashvili, Naira; Tarkhnishvili, Maia; Jolokhava, Tamar; Meskhi, Tea

2017-04-01

Digital soil mapping (DSM) is a fast-developing sub discipline of soil science which gets more importance along with increased availability of spatial data. DSM is based on three main components: the input in the form of field and laboratory observational methods, the process used in terms of spatial and non-spatial soil inference systems, and the output in the form of spatial soil information systems, which includes outputs in the form of rasters of prediction along with the uncertainty of prediction. Georgia is one of the countries who are under the way of spatial data infrastructure development, which includes soil related spatial data also. Therefore, it is important to demonstrate the capacity of DSM technics for planning and decision making process, in which assessment of land suitability is a major interest for those willing to grow agricultural crops. In that term land suitability assessment for establishing organic farms is in high demand as market for organically produced commodities is still increasing. It is the first attempt in Georgia to use DSM to predict areas with potential for organic farming development. Current approach is based on risk assessment of soil pollution with toxic elements (As, Hg, Pb, Cd, Cr) and prediction of bio-availability of those elements to plants on example of the region of Western Georgia, where detailed soil survey was conducted and spatial database of soil was created. The results of the study show the advantages of DSM at early stage assessment and depending on availability and quality of the input data, it can achieve acceptable accuracy.

Spatial and temporal variability of throughfall and soil moisture in a deciduous forest in the low mountain ranges (Hesse, Germany)

NASA Astrophysics Data System (ADS)

Chifflard, Peter; Weishaupt, Philipp; Reiss, Martin

2017-04-01

Spatial and temporal patterns of throughfall can affect the heterogeneity of ecological, biogeochemical and hydrological processes at a forest floor and further the underlying soil. Previous research suggests different factors controlling the spatial and temporal patterns of throughfall, but most studies focus on coniferous forest, where the vegetation coverage is more or less constant over time. In deciduous forests the leaf area index varies due to the leaf fall in autumn which implicates a specific spatial and temporal variability of throughfall and furthermore of the soil moisture. Therefore, in the present study, the measurements of throughfall and soil moisture in a deciduous forest in the low mountain ranges focused especially on the period of leaf fall. The aims of this study were: 1) to detect the spatial and temporal variability of both the throughfall and the soil moisture, 2) to examine the temporal stability of the spatial patterns of the throughfall and soil moisture and 3) relate the soil moisture patterns to the throughfall patterns and further to the canopy characteristics. The study was carried out in a small catchment on middle Hesse (Germany) which is covered by beech forest. Annual mean air temperature is 9.4°C (48.9˚F) and annual mean precipitation is 650 mm. Base materials for soil genesis is greywacke and clay shale from Devonian deposits. The soil type at the study plot is a shallow cambisol. The study plot covers an area of about 150 m2 where 77 throughfall samplers where installed. The throughfall and the soil moisture (FDR-method, 20 cm depth) was measured immediately after every rainfall event at the 77 measurement points. During the period of October to December 2015 altogether 7 events were investigated. The geostatistical method kriging was used to interpolate between the measurements points to visualize the spatial patterns of each investigated parameter. Time-stability-plots were applied to examine temporal scatters of each investigated parameter. The spearmen and pearson correlation coefficients were applied to detect the relationship between the different investigated parameters. First results show that the spatial variability of throughfall decreases if the total amount of the throughfall increases. The soil moisture shows a similar behavior. It`s spatial variability decreases if higher soil moisture values were measured. Concerning the temporal stability of throughfall it can be shown that it is very high during the leaf-free period, although the rainfall events have different total througfall amounts. The soil moisture patterns consists of a low temporal stability and additionally only during one event a significant correlations between throughfall and soil moisture patterns exists. This implies that other factors than the throughfall patterns control the spatial patterns of soil moisture.

Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition.

PubMed

Viscarra Rossel, Raphael A; Lobsey, Craig R; Sharman, Chris; Flick, Paul; McLachlan, Gordon

2017-05-16

Soil information is needed for environmental monitoring to address current concerns over food, water and energy securities, land degradation, and climate change. We developed the Soil Condition ANalysis System (SCANS) to help address these needs. It integrates an automated soil core sensing system (CSS) with statistical analytics and modeling to characterize soil at fine depth resolutions and across landscapes. The CSS's sensors include a γ-ray attenuation densitometer to measure bulk density, digital cameras to image the measured soil, and a visible-near-infrared (vis-NIR) spectrometer to measure iron oxides and clay mineralogy. The spectra are also modeled to estimate total soil organic carbon (C), particulate, humus, and resistant organic C (POC, HOC, and ROC, respectively), clay content, cation exchange capacity (CEC), pH, volumetric water content, available water capacity (AWC), and their uncertainties. Measurements of bulk density and organic C are combined to estimate C stocks. Kalman smoothing is used to derive complete soil property profiles with propagated uncertainties. The SCANS provides rapid, precise, quantitative, and spatially explicit information about the properties of soil profiles with a level of detail that is difficult to obtain with other approaches. The information gained effectively deepens our understanding of soil and calls attention to the central role soil plays in our environment.

An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture-data assimilation

NASA Astrophysics Data System (ADS)

Cenci, Luca; Pulvirenti, Luca; Boni, Giorgio; Chini, Marco; Matgen, Patrick; Gabellani, Simone; Squicciarino, Giuseppe; Pierdicca, Nazzareno

2017-11-01

The assimilation of satellite-derived soil moisture estimates (soil moisture-data assimilation, SM-DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM-DA in recent years (e.g. the Advanced SCATterometer - ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM-DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014-February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM-DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM-DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further research activities, we believe this research is timely in order to enhance our understanding of the potential contribution of the S1 data within the SM-DA framework for flash flood risk mitigation.

Microbial drivers of spatial heterogeneity of nitrous oxide pulse dynamics following drought in an experimental tropical rainforest

NASA Astrophysics Data System (ADS)

Young, J. C.; Sengupta, A.; U'Ren, J.; Van Haren, J. L. M.; Meredith, L. K.

2017-12-01

Nitrous oxide (N2O) is a long-lived, potent greenhouse gas with increasing atmospheric concentrations. Soil microbes in agricultural and natural ecosystems are the dominant source of N2O, which involves complex interactions between N-cycling microbes, metabolisms, soil properties, and plants. Tropical rainforests are the largest natural source of N2O, however the microbial and environmental drivers are poorly understood as few studies have been performed in these environments. Thus, there is an urgent need for further research to fill in knowledge gaps regarding tropical N-cycling, and the response of soil microbial communities to changes in precipitation patterns, temperature, nitrogen deposition, and land use. To address this data gap, we performed a whole-forest drought in the tropical rainforest biome in Biosphere 2 (B2) and analyzed connections between soil microbes, forest heterogeneity, and N2O emissions. The B2 rainforest is the hottest tropical rainforest on Earth, and is an important model system for studying the response of tropical forests to warming with controlled experimentation. In this study, we measured microbial community abundance and diversity profiles (16S rRNA and ITS2 amplicon sequencing) along with their association with soil properties (e.g. pH, C, N) during the drought and rewetting at five locations (3 depths), including regions that have been previously characterized with high and low N2O drought pulse dynamics (van Haren et al., 2005). In this study, we present the spatial distribution of soil microbial communities within the rainforest at Biosphere 2 and their correlations with edaphic factors. In particular, we focus on microbial, soil, and plant factors that drive high and low N2O pulse zones. As in the past, we found that N2O emissions were highest in response to rewetting in a zone hypothesized to be rich in nutrients from a nearby sugar palm. We will characterize microbial indicator species and nitrogen cycling genes to better resolve N cycling across the forest. Understanding how N2O formation is mediated by soil microbes in response to drought in tropical rainforests is challenging given the great diversity of microbial communities and metabolisms involved, but is critical for understanding the source of global increases in atmospheric N2O.

Soil nutrient-landscape relationships in a lowland tropical rainforest in Panama

USGS Publications Warehouse

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.

Ground-based Remote Sensing for Quantifying Subsurface and Surface Co-variability to Scale Arctic Ecosystem Functioning

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.

SoilGrids1km — Global Soil Information Based on Automated Mapping

PubMed Central

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

Sensitivity of convective precipitation to soil moisture and vegetation during break spell of Indian summer monsoon

NASA Astrophysics Data System (ADS)

Kutty, Govindan; Sandeep, S.; Vinodkumar; Nhaloor, Sreejith

2017-07-01

Indian summer monsoon rainfall is characterized by large intra-seasonal fluctuations in the form of active and break spells in rainfall. This study investigates the role of soil moisture and vegetation on 30-h precipitation forecasts during the break monsoon period using Weather Research and Forecast (WRF) model. The working hypothesis is that reduced rainfall, clear skies, and wet soil condition during the break monsoon period enhance land-atmosphere coupling over central India. Sensitivity experiments are conducted with modified initial soil moisture and vegetation. The results suggest that an increase in antecedent soil moisture would lead to an increase in precipitation, in general. The precipitation over the core monsoon region has increased by enhancing forest cover in the model simulations. Parameters such as Lifting Condensation Level, Level of Free Convection, and Convective Available Potential Energy indicate favorable atmospheric conditions for convection over forests, when wet soil conditions prevail. On spatial scales, the precipitation is more sensitive to soil moisture conditions over northeastern parts of India. Strong horizontal gradient in soil moisture and orographic uplift along the upslopes of Himalaya enhanced rainfall over the east of Indian subcontinent.

Variability in Soil Properties at Different Spatial Scales (1 m to 1 km) in a Deciduous Forest Ecosystem

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

Determination of erosion thresholds and aeolian dune stabilization mechanisms via robotic shear strength measurements

NASA Astrophysics Data System (ADS)

Qian, F.; Lee, D. B.; Bodek, S.; Roberts, S.; Topping, T. T.; Robele, Y.; Koditschek, D. E.; Jerolmack, D. J.

2017-12-01

Understanding the parameters that control the spatial variation in aeolian soil erodibility is crucial to the development of sediment transport models. Currently, in-situ measurements of erodibility are time consuming and lack robustness. In an attempt to remedy this issue, we perform field and laboratory tests to determine the suitability of a novel mechanical shear strength method to assess soil erodibility. These tests can be performed quickly ( 1 minute) by a semi-autonomous robot using its direct-drive leg, while environmental controls such as soil moisture and grain size are simultaneously characterized. The robot was deployed at White Sands National Monument to delineate and understand erodibility gradients at two different scales: (1) from dry dune crest to moist interdune (distance 10s m), where we determined that shear strength increases by a factor of three with increasing soil moisture; and (2) from barren barchan dunes to vegetated and crusted parabolics downwind (distance 5 km), where we found that shear strength was enhanced by a factor of two relative to loose sand. Interestingly, shear strength varied little from carbonate-crusted dune surfaces to bio-crust covered interdunes in the downwind parabolic region, indicating that varied surface crusts contribute similarly to erosion resistance. To isolate the control of soil moisture on erodibility, we performed laboratory experiments in a sandbox. These results verify that the observed increase in soil erodibility from barchan crest to interdune at White Sands is dominated by soil moisture, and the variation in parabolic dune and barchan interdune areas results from a combination of soil moisture, bio-activity, and crust development. This study highlights that spatial variation of soil erodibility in arid environments is large enough to significantly affect sediment transport, and that probing soil erodibility with a robot has the potential to improve our understanding of this multifaceted problem.

Topographic variations of water supply and plant hydraulics in a mountainous forest

NASA Astrophysics Data System (ADS)

Tai, X.; Mackay, D. S.; Ewers, B. E.; Parsekian, A.; Sperry, J.; Beverly, D.; Speckman, H. N.; Ohara, N.; Fantello, N.; Kelleners, T.; Fullhart, A. T.

2017-12-01

How plants respond to variable local water supply in complex soil-topography systems is not clear although critical. This has been attributed to a lack of integrated models that can resolve relevant hydrological and physiological mechanisms and intensive field monitoring to inform/evaluate such a model. This research addresses these knowledge gaps by leveraging a newly developed distributed plant hydraulics model, ParFlow-TREES, and detailed geophysical and physiological measurements. Observations of sap flow, leaf water potentials, micrometeorology, and electrical resistivity tomography (ERT) are combined with the model to examine the key mechanisms affecting the spatial distribution of soil water and tree water stress. Modeling results showed higher soil water condition at bottom of the hillslope on average, corroborating the ERT-derived soil moisture observations. Hydraulic traits are critical to capture the sap flux dynamics of species with contrasting leaf water potential regulation strategies and heterogeneous soil drying at different hillslope positions. These results suggested the integrated effect of topography and plants on the evolvement of soil moisture distribution. Furthermore, sensitivity analysis demonstrated the importance of using distributed observations to validate/calibrate distributed models. Focusing on lumped variables or only one particular variable might give misleading conclusions. Co-located observations improve the characterization of plant traits and local living environment, providing key information needed as a first step in resolving the form and function of the critical zone from bedrock to atmosphere. We will discuss the broader implications and potential applications of this intensive data-model comparison at other sites and greater spatial extent.

Mapping soil textural fractions across a large watershed in north-east Florida.

PubMed

Lamsal, S; Mishra, U

2010-08-01

Assessment of regional scale soil spatial variation and mapping their distribution is constrained by sparse data which are collected using field surveys that are labor intensive and cost prohibitive. We explored geostatistical (ordinary kriging-OK), regression (Regression Tree-RT), and hybrid methods (RT plus residual Sequential Gaussian Simulation-SGS) to map soil textural fractions across the Santa Fe River Watershed (3585 km(2)) in north-east Florida. Soil samples collected from four depths (L1: 0-30 cm, L2: 30-60 cm, L3: 60-120 cm, and L4: 120-180 cm) at 141 locations were analyzed for soil textural fractions (sand, silt and clay contents), and combined with textural data (15 profiles) assembled under the Florida Soil Characterization program. Textural fractions in L1 and L2 were autocorrelated, and spatially mapped across the watershed. OK performance was poor, which may be attributed to the sparse sampling. RT model structure varied among textural fractions, and the model explained variations ranged from 25% for L1 silt to 61% for L2 clay content. Regression residuals were simulated using SGS, and the average of simulated residuals were used to approximate regression residual distribution map, which were added to regression trend maps. Independent validation of the prediction maps showed that regression models performed slightly better than OK, and regression combined with average of simulated regression residuals improved predictions beyond the regression model. Sand content >90% in both 0-30 and 30-60 cm covered 80.6% of the watershed area. Copyright 2010 Elsevier Ltd. All rights reserved.

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

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.

Climatic and landscape controls on travel time distributions across Europe

NASA Astrophysics Data System (ADS)

Kumar, Rohini; Rao, Suresh; Hesse, Falk; Borchardt, Dietrich; Fleckenstein, Jan; Jawitz, James; Musolff, Andreas; Rakovec, Oldrich; Samaniego, Luis; Yang, Soohyun; Zink, Matthias; Attinger, Sabine

2017-04-01

Travel time distributions (TTDs) are fundamental descriptors to characterize the functioning of storage, mixing and release of water and solutes in a river basin. Identifying the relative importance (and controls) of climate and landscape attributes on TDDs is fundamental to improve our understanding of the underlying mechanism controlling the spatial heterogeneity of TTDs, and their moments (e.g., mean TT). Studies aimed at elucidating such controls have focused on either theoretical developments to gain (physical) insights using mostly synthetic datasets or empirical relationships using limited datasets from experimental sites. A study painting a general picture of emerging controls at a continental scale is still lacking. In this study, we make use of spatially resolved hydrologic fluxes and states generated through an observationally driven, mesoscale Hydrologic Model (mHM; www.ufz.de/mhm) to comprehensively characterize the dominant controls of climate and landscape attributes on TDDs in the vadose zone across the entire European region. mHM uses a novel Multiscale Parameter Regionalization (MPR; Samaniego et al., 2010 and Kumar et al., 2013) scheme that encapsulates fine scale landscape attributes (e.g., topography, soil, and vegetation characteristics) to account for the sub-grid variability in model parameterization. The model was established at 25 km spatial resolution to simulate the daily gridded fluxes and states over Europe for the period 1955-2015. We utilized recent developments in TTDs theory (e.g., Botter et al., 2010, Harman et al., 2011) to characterize the stationary and non-stationary behavior of water particles transported through the vadose zone at every grid cell. Our results suggest a complex set of interactions between climate and landscape properties controlling the spatial heterogeneity of the mean travel time (TT). The spatial variability in the mean TT across the Pan-EU generally follows the climatic gradient with lower values in humid regions and higher in semi-arid or drier regions. The results signifies the role of a landscape attributes like plant available soil-water-storage capacity, when expressed in a dimensionless number that also include climate attributes such as average rain depth and aridity index, forms a potentially useful predictor for explaining the spatial heterogeneity of mean TTs. Finally, the study also highlights the time-varying behavior of TTDs and discusses the seasonal variation in mean TTs across Europe.

Site Classification using Multichannel Channel Analysis of Surface Wave (MASW) method on Soft and Hard Ground

NASA Astrophysics Data System (ADS)

Ashraf, M. A. M.; Kumar, N. S.; Yusoh, R.; Hazreek, Z. A. M.; Aziman, M.

2018-04-01

Site classification utilizing average shear wave velocity (Vs(30) up to 30 meters depth is a typical parameter. Numerous geophysical methods have been proposed for estimation of shear wave velocity by utilizing assortment of testing configuration, processing method, and inversion algorithm. Multichannel Analysis of Surface Wave (MASW) method is been rehearsed by numerous specialist and professional to geotechnical engineering for local site characterization and classification. This study aims to determine the site classification on soft and hard ground using MASW method. The subsurface classification was made utilizing National Earthquake Hazards Reduction Program (NERHP) and international Building Code (IBC) classification. Two sites are chosen to acquire the shear wave velocity which is in the state of Pulau Pinang for soft soil and Perlis for hard rock. Results recommend that MASW technique can be utilized to spatially calculate the distribution of shear wave velocity (Vs(30)) in soil and rock to characterize areas.

Mapping iron oxides and the color of Australian soil using visible-near-infrared reflectance spectra

NASA Astrophysics Data System (ADS)

Viscarra Rossel, R. A.; Bui, E. N.; de Caritat, P.; McKenzie, N. J.

2010-12-01

Iron (Fe) oxide mineralogy in most Australian soils is poorly characterized, even though Fe oxides play an important role in soil function. Fe oxides reflect the conditions of pH, redox potential, moisture, and temperature in the soil environment. The strong pigmenting effect of Fe oxides gives most soils their color, which is largely a reflection of the soil's Fe mineralogy. Visible-near-infrared (vis-NIR) spectroscopy can be used to identify and measure the abundance of certain Fe oxides in soil, and the visible range can be used to derive tristimuli soil color information. The aims of this paper are (1) to measure the abundance of hematite and goethite in Australian soils from their vis-NIR spectra, (2) to compare these results to measurements of soil color, and (3) to describe the spatial variability of hematite, goethite, and soil color and map their distribution across Australia. We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer with a wavelength range of 350-2500 nm. We determined the Fe oxide abundance for each sample using the diagnostic absorption features of hematite (near 880 nm) and goethite (near 920 nm) and derived a normalized iron oxide difference index (NIODI) to better discriminate between them. The NIODI was generalized across Australia with its spatial uncertainty using sequential indicator simulation, which resulted in a map of the probability of the occurrence of hematite and goethite. We also derived soil RGB color from the spectra and mapped its distribution and uncertainty across the country using sequential Gaussian simulations. The simulated RGB color values were made into a composite true color image and were also converted to Munsell hue, value, and chroma. These color maps were compared to the map of the NIODI, and both were used to interpret our results. The work presented here was validated by randomly splitting the data into training and test data sets, as well as by comparing our results to existing studies on the distribution of Fe oxides in Australian soils.

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

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.

Heavy metal pollution in farmland irrigated with river water near a steel plant—magnetic and geochemical signature

NASA Astrophysics Data System (ADS)

Zhang, Chunxia; Appel, Erwin; Qiao, Qingqing

2013-03-01

The presence of heavy metals (HMs) in the environment is a major threat for humans. Magnetic proxies provide a rapid method for assessing the degree of HM pollution in environment. We have studied farmland soil irrigated with polluted river water in the vicinity of a steel plant in Loudi city (Hunan Province, China) to test the efficiency of magnetic methods for detecting the degree of HM pollution. Both magnetic and non-magnetic (microscopic, chemical and statistical) methods were used to characterize these farmland soils. Enhanced magnetic concentration values were found in the upper arable soil horizon (0-20 cm), which is related to the presence of spherical ˜10 to 30 μm sized magnetite particles. The spatial distribution of magnetic concentration and HM contents in the farmland soils matches with the spatial pattern of these parameters in river sediments. These findings provide evidence that HM pollution of the farmland soil is mainly caused by irrigation with wastewater. HMs Zn, Pb, Cu, Cd, Co, Ni, V are well correlate with magnetic susceptibility (χ). The pollution load index (PLI) of all nine anthropogenic HMs (including also Cr and Mo) and log10(χ) are significantly correlated. Using the resulting linear PLI-log10(χ) function, values of χ can serve as a convenient tool for semi-quantifying the degree of HM pollution in the uppermost ˜20 cm of the studied farmland soils. These findings suggest that magnetic methods can generally serve as a convenient tool for detecting and mapping HM pollution in farmland soil irrigated with wastewater from sites nearby heavy industrial activities.

Retrospective 70 y-spatial analysis of repeated vine mortality patterns using ancient aerial time series, Pléiades images and multi-source spatial and field data

NASA Astrophysics Data System (ADS)

Vaudour, E.; Leclercq, L.; Gilliot, J. M.; Chaignon, B.

2017-06-01

For any wine estate, there is a need to demarcate homogeneous within-vineyard zones ('terroirs') so as to manage grape production, which depends on vine biological condition. Until now, the studies performing digital zoning of terroirs have relied on recent spatial data and scant attention has been paid to ancient geoinformation likely to retrace past biological condition of vines and especially occurrence of vine mortality. Is vine mortality characterized by recurrent and specific patterns and if so, are these patterns related to terroir units and/or past landuse? This study aimed at performing a historical and spatial tracing of vine mortality patterns using a long time-series of aerial survey images (1947-2010), in combination with recent data: soil apparent electrical conductivity EM38 measurements, very high resolution Pléiades satellite images, and a detailed field survey. Within a 6 ha-estate in the Southern Rhone Valley, landuse and planting history were retraced and the map of missing vines frequency was constructed from the whole time series including a 2015-Pléiades panchromatic band. Within-field terroir units were obtained from a support vector machine classifier computed on the spectral bands and NDVI of Pléiades images, EM38 data and morphometric data. Repeated spatial patterns of missing vines were highlighted throughout several plantings, uprootings, and vine replacements, and appeared to match some within-field terroir units, being explained by their specific soil characteristics, vine/soil management choices and the past landuse of the 1940s. Missing vines frequency was spatially correlated with topsoil CaCO3 content, and negatively correlated with topsoil iron, clay, total N, organic C contents and NDVI. A retrospective spatio-temporal assessment of terroir therefore brings a renewed focus on some key parameters for maintaining a sustainable grape production.

Application of spatial pedotransfer functions to understand soil modulation of vegetation response to climate

USDA-ARS?s Scientific Manuscript database

A fundamental knowledge gap in understanding land-atmosphere interactions is accurate, high resolution spatial representation of soil physical and hydraulic properties. We present a novel approach to predict hydraulic soil parameters by combining digital soil mapping techniques with pedotransfer fun...

Detecting seasonal variations of soil parameters via field measurements and stochastic simulations in the hillslope

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; An, Hyunuk; Kim, Sanghyun

2015-04-01

Soil moisture, a critical factor in hydrologic systems, plays a key role in synthesizing interactions among soil, climate, hydrological response, solute transport and ecosystem dynamics. The spatial and temporal distribution of soil moisture at a hillslope scale is essential for understanding hillslope runoff generation processes. In this study, we implement Monte Carlo simulations in the hillslope scale using a three-dimensional surface-subsurface integrated model (3D model). Numerical simulations are compared with multiple soil moistures which had been measured using TDR(Mini_TRASE) for 22 locations in 2 or 3 depths during a whole year at a hillslope (area: 2100 square meters) located in Bongsunsa Watershed, South Korea. In stochastic simulations via Monte Carlo, uncertainty of the soil parameters and input forcing are considered and model ensembles showing good performance are selected separately for several seasonal periods. The presentation will be focused on the characterization of seasonal variations of model parameters based on simulations with field measurements. In addition, structural limitations of the contemporary modeling method will be discussed.

Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

2017-12-01

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

Soil moisture downscaling using a simple thermal based proxy

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Niesel, Jonathan

2016-04-01

Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

X-ray computed microtomography analysis of the influence of different agricultural treatments on the topsoil porosity of a Grey Brown Luvisol from Ontario

NASA Astrophysics Data System (ADS)

Taina, I. A.; Heck, R. J.; Scaiff, N. T.

2009-05-01

One of the most important applications of X-ray computed tomography (CT) for the study of soil is the characterization of the shape and spatial distribution of pores. Analysis of 3D X-ray CT image data, related to different pore categories, can provide insight to soil structural changes, which have implications in water infiltration and soil aeration, resulting from agricultural practices. The aim of this study was to evaluate changes in the spatial characteristics of voids, due to tillage practices, in the Ap horizon of an Orthic Grey- Brown Luvisol (located at the Elora Research Station of the University of Guelph). Undisturbed oriented soil samples were collected from ten plots representing different tillage treatments: spring moldboard plow, spring moldboard plow, cultivate and pack, fall moldboard plow, cultivate and pack, spring tandem disc, no cultivator, fall offset disc, fall offset disc, cultivate and pack, fall chisel plow, cultivate and pack, zero zone till (soys twin rows), zero tillage (long term), and zero tillage (corn residue removed in row, soys twin rows). Since the utilization of standardized classes, in the quantification of similar features, proved to be necessary in order to obtain comparable results, categories of pores, separated according to their size, circularity and orientation were considered in the interpretation of data. Total volume of pores and volume percentage of each class were calculated, revealing substantial differences among the analyzed soil samples.

Estimating the spatial distribution of soil organic matter density and geochemical properties in a polygonal shaped Arctic Tundra using core sample analysis and X-ray computed tomography

NASA Astrophysics Data System (ADS)

Soom, F.; Ulrich, C.; Dafflon, B.; Wu, Y.; Kneafsey, T. J.; López, R. D.; Peterson, J.; Hubbard, S. S.

2016-12-01

The Arctic tundra with its permafrost dominated soils is one of the regions most affected by global climate change, and in turn, can also influence the changing climate through biogeochemical processes, including greenhouse gas release or storage. Characterization of shallow permafrost distribution and characteristics are required for predicting ecosystem feedbacks to a changing climate over decadal to century timescales, because they can drive active layer deepening and land surface deformation, which in turn can significantly affect hydrological and biogeochemical responses, including greenhouse gas dynamics. In this study, part of the Next-Generation Ecosystem Experiment (NGEE-Arctic), we use X-ray computed tomography (CT) to estimate wet bulk density of cores extracted from a field site near Barrow AK, which extend 2-3m through the active layer into the permafrost. We use multi-dimensional relationships inferred from destructive core sample analysis to infer organic matter density, dry bulk density and ice content, along with some geochemical properties from nondestructive CT-scans along the entire length of the cores, which was not obtained by the spatially limited destructive laboratory analysis. Multi-parameter cross-correlations showed good agreement between soil properties estimated from CT scans versus properties obtained through destructive sampling. Soil properties estimated from cores located in different types of polygons provide valuable information about the vertical distribution of soil and permafrost properties as a function of geomorphology.

Elaboration of a framework for the compilation of countrywide, digital maps for the satisfaction of recent demands on spatial, soil related information in Hungary

NASA Astrophysics Data System (ADS)

Pásztor, László; Dobos, Endre; Szabó, József; Bakacsi, Zsófia; Laborczi, Annamária

2013-04-01

There is a heap of evidences that demands on soil related information have been significant worldwide and it is still increasing. Soil maps were typically used for long time to satisfy these demands. By the spread of GI technology, spatial soil information systems (SSIS) and digital soil mapping (DSM) took the role of traditional soil maps. Due to the relatively high costs of data collection, new conventional soil surveys and inventories are getting less and less frequent, which fact valorises legacy soil information and the systems which are serving the their digitally processed version. The existing data contain a wealth of information that can be exploited by proper methodology. Not only the degree of current needs for soil information has changed but also its nature. Traditionally the agricultural functions of soils were focussed on, which was also reflected in the methodology of data collection and mapping. Recently the multifunctionality of soils is getting to gain more and more ground; consequently information related to additional functions of soils becomes identically important. The new types of information requirements however cannot be fulfilled generally with new data collections at least not on such a level as it was done in the frame of traditional soil surveys. Soil monitoring systems have been established for the collection of recent information on the various elements of the DPSIR (Driving Forces-Pressures-State-Impacts-Responses) framework, but the primary goal of these systems has not been mapping by all means. And definitely this is the case concerning the two recently working Hungarian soil monitoring systems. In Hungary, presently soil data requirements are fulfilled with the recently available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. Since, similarly to the great majority of the world, large-scale, comprehensive new surveys cannot be expected in the near future, the actually available legacy data should be relied on. With a recently started project we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied. In the frame of our project we plan the execution of spatial and thematic data mining of significant amount of soil related information available in the form of legacy soil data as well as digital databases and spatial soil information systems. In the course of the analyses we will lean on auxiliary, spatial data themes related to environmental elements. Based on the established relationships we will convert and integrate the specific data sets for the regionalization of the various, derived soil parameters. By the aid of GIS and geostatistical tools we will carry out the spatial extension of certain pedological variables featuring the (including degradation) state, processes or functions of soils. We plan to compile digital soil maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The targeted spatial resolution of the proposed countrywide, digital, thematic soil property and function maps is at least 1:50.000 (approx. 50-100 meter raster). Our stressful objective is the definite solution of the regionalization of the information collected in the frame of two recent, contemporary, national, systematic soil data collection (not designed for mapping purpose) on the recent state of soils, in order to produce countrywide maps for the spatial inventory of certain soil properties, processes and functions with sufficient accuracy and reliability.

Irrigation scheduling of green areas based on soil moisture estimation by the active heated fiber optic distributed temperature sensing AHFO

NASA Astrophysics Data System (ADS)

Zubelzu, Sergio; Rodriguez-Sinobas, Leonor; Sobrino, Fernando; Sánchez, Raúl

2017-04-01

Irrigation programing determines when and how much water apply to fulfill the plant water requirements depending of its phenology stage and location, and soil water content. Thus, the amount of water, the irrigation time and the irrigation frequency are variables that must be estimated. Likewise, irrigation programing has been based in approaches such as: the determination of plant evapotranspiration and the maintenance of soil water status between a given interval or soil matrix potential. Most of these approaches are based on the measurements of soil water sensors (or tensiometers) located at specific points within the study area which lack of the spatial information of the monitor variable. The information provided in such as few points might not be adequate to characterize the soil water distribution in irrigation systems with poor water application uniformity and thus, it would lead to wrong decisions in irrigation scheduling. Nevertheless, it can be overcome if the active heating pulses distributed fiber optic temperature measurement (AHFO) is used. This estimates the temperature variation along a cable of fiber optic and then, it is correlated with the soil water content. This method applies a known amount of heat to the soil and monitors the temperature evolution, which mainly depends on the soil moisture content. Thus, it allows estimations of soil water content every 12.5 cm along the fiber optic cable, as long as 1500 m (with 2 % accuracy) , every second. This study presents the results obtained in a green area located at the ETSI Agronómica, Agroalimentaria y Biosistesmas in Madrid. The area is irrigated by an sprinkler irrigation system which applies water with low uniformity. Also, it has deployed and installation of 147 m of fiber optic cable at 15 cm depth. The Distribute Temperature Sensing unit was a SILIXA ULTIMA SR (Silixa Ltd, UK) with spatial and temporal resolution of 0.29 m and 1 s, respectively. In this study, heat pulses of 7 W/m for 2 min were applied uniformly along the fiber optic cable and the thermal response on an adjacent cable was monitored prior, during and after the irrigation event. Data was logged every 0.3 m and every 5 s then, the heating and drying phase integer (called Tcum) was determined following the approach of Sayde et al., (2010). Thus, the infiltration and redistribution of soil water content was fully characterized. The results are promising since the water spatial variability within the soil is known and it can be correlated with the water distribution in the irrigation unit to make better irrigation scheduling in the green area improving water/nutrient/energy efficiency.. Reference Létourneau, G., Caron, J., Anderson, L., & Cormier, J. (2015). Matric potential-based irrigation management of field-grown strawberry: Effects on yield and water use efficiency. Agricultural Water Management, 161, 102-113. Liang, X., Liakos, V., Wendroth, O., & Vellidis, G. (2016). Scheduling irrigation using an approach based on the van Genuchten model. Agricultural Water Management, 176, 170-179. Sayde,C., Gregory, C., Gil-Rodriguez, M., Tufillaro, N., Tyler, S., van de Giesen, N., English, M. Cuenca, R. and Selker, J. S.. 2010. Feasibility of soil moisture monitoring with heated fiber optics. Water Resources Research. Vol.46 (6). DOI: 10.1029/2009WR007846 Stirzaker, R. J., Maeko, T. C., Annandale, J. G., Steyn, J. M., Adhanom, G. T., & Mpuisang, T. (2017). Scheduling irrigation from wetting front depth. Agricultural Water Management, 179, 306-313.

Vadose zone studies at an industrial contaminated site: the vadose zone monitoring system and cross-hole geophysics

NASA Astrophysics Data System (ADS)

Fernandez de Vera, Natalia; Beaujean, Jean; Jamin, Pierre; Nguyen, Frédéric; Dahan, Ofer; Vanclooster, Marnik; Brouyère, Serge

2014-05-01

In order to improve risk characterization and remediation measures for soil and groundwater contamination, there is a need to improve in situ vadose zone characterization. However, most available technologies have been developed in the context of agricultural soils. Such methodologies are not applicable at industrial sites, where soils and contamination differ in origin and composition. In addition, most technologies are applicable only in the first meters of soils, leaving deeper vadose zones with lack of information, in particular on field scale heterogeneity. In order to overcome such difficulties, a vadose zone experiment has been setup at a former industrial site in Belgium. Industrial activities carried out on site left a legacy of soil and groundwater contamination in BTEX, PAH, cyanide and heavy metals. The experiment comprises the combination of two techniques: the Vadose Zone Monitoring System (VMS) and cross-hole geophysics. The VMS allows continuous measurements of water content and temperature at different depths of the vadose zone. In addition, it provides the possibility of pore water sampling at different depths. The system is formed by a flexible sleeve containing monitoring units along its depth which is installed in a slanted borehole. The flexible sleeve contains three types of monitoring units in the vadose zone: Time Domain Transmissometry (TDT), which allows water content measurements; Vadose Sampling Ports (VSP), used for collecting water samples coming from the matrix; the Fracture Samplers (FS), which are used for retrieving water samples from the fractures. Cross-hole geophysics techniques consist in the injection of an electrical current using electrodes installed in vertical boreholes. From measured potential differences, detailed spatial patterns about electrical properties of the subsurface can be inferred. Such spatial patterns are related with subsurface heterogeneities, water content and solute concentrations. Two VMS were installed in two slanted boreholes on site, together with four vertical boreholes containing electrodes for geophysical measurements. Currently the site is being monitored under natural recharge conditions. Initial results show the reaction of the vadose zone to rainfall events, as well as chemical evolution of soil water with depth.

Combining local scaling and global methods to detect soil pore space

NASA Astrophysics Data System (ADS)

Martin-Sotoca, Juan Jose; Saa-Requejo, Antonio; Grau, Juan B.; Tarquis, Ana M.

2017-04-01

The characterization of the spatial distribution of soil pore structures is essential to obtain different parameters that will influence in several models related to water flow and/or microbial growth processes. The first step in pore structure characterization is obtaining soil images that best approximate reality. Over the last decade, major technological advances in X-ray computed tomography (CT) have allowed for the investigation and reconstruction of natural porous media architectures at very fine scales. The subsequent step is delimiting the pore structure (pore space) from the CT soil images applying a thresholding. Many times we could find CT-scan images that show low contrast at the solid-void interface that difficult this step. Different delimitation methods can result in different spatial distributions of pores influencing the parameters used in the models. Recently, new local segmentation method using local greyscale value (GV) concentration variabilities, based on fractal concepts, has been presented. This method creates singularity maps to measure the GV concentration at each point. The C-A method was combined with the singularity map approach (Singularity-CA method) to define local thresholds that can be applied to binarize CT images. Comparing this method with classical methods, such as Otsu and Maximum Entropy, we observed that more pores can be detected mainly due to its ability to amplify anomalous concentrations. However, it delineated many small pores that were incorrect. In this work, we present an improve version of Singularity-CA method that avoid this problem basically combining it with the global classical methods. References Martín-Sotoca, J.J., A. Saa-Requejo, J.B. Grau, A.M. Tarquis. New segmentation method based on fractal properties using singularity maps. Geoderma, 287, 40-53, 2017. Martín-Sotoca, J.J, A. Saa-Requejo, J.B. Grau, A.M. Tarquis. Local 3D segmentation of soil pore space based on fractal properties using singularity maps. Geoderma, http://dx.doi.org/10.1016/j.geoderma.2016.11.029. Torre, Iván G., Juan C. Losada and A.M. Tarquis. Multiscaling properties of soil images. Biosystems Engineering, http://dx.doi.org/10.1016/j.biosystemseng.2016.11.006.

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.

Spatial Variability of Soil Water and Soil Organic Carbon Contents Under Different Degradation Degrees of Alpine Meadow Soil over the Qinghai-Tibetan Plateau

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.

Accessibility, searchability, transparency and engagement of soil carbon data: The International Soil Carbon Network

NASA Astrophysics Data System (ADS)

Harden, Jennifer W.; Hugelius, Gustaf; Koven, Charlie; Sulman, Ben; O'Donnell, Jon; He, Yujie

2016-04-01

Soils are capacitors for carbon and water entering and exiting through land-atmosphere exchange. Capturing the spatiotemporal variations in soil C exchange through monitoring and modeling is difficult in part because data are reported unevenly across spatial, temporal, and management scales and in part because the unit of measure generally involves destructive harvest or non-recurrent measurements. In order to improve our fundamental basis for understanding soil C exchange, a multi-user, open source, searchable database and network of scientists has been formed. The International Soil Carbon Network (ISCN) is a self-chartered, member-based and member-owned network of scientists dedicated to soil carbon science. Attributes of the ISCN include 1) Targeted ISCN Action Groups which represent teams of motivated researchers that propose and pursue specific soil C research questions with the aim of synthesizing seminal articles regarding soil C fate. 2) Datasets to date contributed by institutions and individuals to a comprehensive, searchable open-access database that currently includes over 70,000 geolocated profiles for which soil C and other soil properties. 3) Derivative products resulting from the database, including depth attenuation attributes for C concentration and storage; C storage maps; and model-based assessments of emission/sequestration for future climate scenarios. Several examples illustrate the power of such a database and its engagement with the science community. First, a simplified, data-constrained global ecosystem model estimated a global sensitivity of permafrost soil carbon to climate change (g sensitivity) of -14 to -19 Pg C °C-1 of warming on a 100 years time scale. Second, using mathematical characterizations of depth profiles for organic carbon storage, C at the soil surface reflects Net Primary Production (NPP) and its allotment as moss or litter, while e-folding depths are correlated to rooting depth. Third, storage of deep C is highly correlated with bulk density and porosity of the rock/sediment matrix. Thus C storage is most stable at depth, yet is susceptible to changes in tillage, rooting depths, and erosion/sedimentation. Fourth, current ESMs likely overestimate the turnover time of soil organic carbon and subsequently overestimate soil carbon sequestration, thus datasets combined with other soil properties will help constrain the ESM predictions. Last, analysis of soil horizon and carbon data showed that soils with a history of tillage had significantly lower carbon concentrations in both near-surface and deep layers, and that the effect persisted even in reforested areas. In addition to the opportunities for empirical science using a large database, the database has great promise for evaluation of biogeochemical and earth system models. The preservation of individual soil core measurements avoids issues with spatial averaging while facilitating evaluation of advanced model processes such as depth distributions of soil carbon, land use impacts, and spatial heterogeneity.

Spatial mapping of lead, arsenic, iron, and polycyclic aromatic hydrocarbon soil contamination in Sydney, Nova Scotia: community impact from the coke ovens and steel plant.

PubMed

Lambert, Timothy W; Boehmer, Jennifer; Feltham, Jason; Guyn, Lindsay; Shahid, Rizwan

2011-01-01

This paper presents spatial maps of the arsenic, lead, and polycyclic aromatic hydrocarbon (PAH) soil contamination in Sydney, Nova Scotia, Canada. The spatial maps were designed to create exposure cohorts to help understand the observed increase in health effects. To assess whether contamination can be a proxy for exposures, the following hypothesis was tested: residential soils were impacted by the coke oven and steel plant industrial complex. The spatial map showed contaminants are centered on the industrial facility, significantly correlated, and exceed Canadian health risk-based soil quality guidelines. Core samples taken at 5-cm intervals suggest a consistent deposition over time. The concentrations in Sydney significantly exceed background Sydney soil concentrations, and are significantly elevated compared with North Sydney, an adjacent industrial community. The contaminant spatial maps will also be useful for developing cohorts of exposure and guiding risk management decisions.

Effect of Downscaled Forcings and Soil Texture Properties on Hyperresolution Hydrologic Simulations in a Regional Basin in Northwest Mexico

NASA Astrophysics Data System (ADS)

Ko, A.; Mascaro, G.; Vivoni, E. R.

2017-12-01

Hyper-resolution (< 1 km) hydrological modeling is expected to support a range of studies related to the terrestrial water cycle. A critical need for increasing the utility of hyper-resolution modeling is the availability of meteorological forcings and land surface characteristics at high spatial resolution. Unfortunately, in many areas these datasets are only available at coarse (> 10 km) scales. In this study, we address some of the challenges by applying a parallel version of the Triangulated Irregular Network (TIN)-based Real Time Integrated Basin Simulator (tRIBS) to the Rio Sonora Basin (RSB) in northwest Mexico. The RSB is a large, semiarid watershed ( 21,000 km2) characterized by complex topography and a strong seasonality in vegetation conditions, due to the North American monsoon. We conducted simulations at an average spatial resolution of 88 m over a decadal (2004-2013) period using spatially-distributed forcings from remotely-sensed and reanalysis products. Meteorological forcings were derived from the North American Land Data Assimilation System (NLDAS) at the original resolution of 12 km and were downscaled at 1 km with techniques accounting for terrain effects. Two grids of soil properties were created from different sources, including: (i) CONABIO (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) at 6 km resolution; and (ii) ISRIC (International Soil Reference Information Centre) at 250 m. Time-varying vegetation parameters were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) composite products. The model was first calibrated and validated through distributed soil moisture data from a network of 20 soil moisture stations during the monsoon season. Next, hydrologic simulations were conducted with five different combinations of coarse and downscaled forcings and soil properties. Outputs in the different configurations were then compared with independent observations of soil moisture, and with estimates of land surface temperature (1 km, daily) and evapotranspiration (1 km, monthly) from MODIS. This study is expected to support the community involved in hyper-resolution hydrologic modeling by identifying the crucial factors that, if available at higher resolution, lead to the largest improvement of the simulation prognostic capability.

Coupling transfer function and GIS for assessing non-point-source groundwater vulnerability at regional scale

NASA Astrophysics Data System (ADS)

Coppola, A.; Comegna, V.; de Simone, L.

2009-04-01

Non-point source (NPS) pollution in the vadose zone is a global environmental problem. The knowledge and information required to address the problem of NPS pollutants in the vadose zone cross several technological and sub disciplinary lines: spatial statistics, geographic information systems (GIS), hydrology, soil science, and remote sensing. The main issues encountered by NPS groundwater vulnerability assessment, as discussed by Stewart [2001], are the large spatial scales, the complex processes that govern fluid flow and solute transport in the unsaturated zone, the absence of unsaturated zone measurements of diffuse pesticide concentrations in 3-D regional-scale space as these are difficult, time consuming, and prohibitively costly, and the computational effort required for solving the nonlinear equations for physically-based modeling of regional scale, heterogeneous applications. As an alternative solution, here is presented an approach that is based on coupling of transfer function and GIS modeling that: a) is capable of solute concentration estimation at a depth of interest within a known error confidence class; b) uses available soil survey, climatic, and irrigation information, and requires minimal computational cost for application; c) can dynamically support decision making through thematic mapping and 3D scenarios This result was pursued through 1) the design and building of a spatial database containing environmental and physical information regarding the study area, 2) the development of the transfer function procedure for layered soils, 3) the final representation of results through digital mapping and 3D visualization. One side GIS modeled environmental data in order to characterize, at regional scale, soil profile texture and depth, land use, climatic data, water table depth, potential evapotranspiration; on the other side such information was implemented in the up-scaling procedure of the Jury's TFM resulting in a set of texture based travel time probability density functions for layered soils each describing a characteristic leaching behavior for soil profiles with similar hydraulic properties. Such behavior, in terms of solute travel time to water table, was then imported back into GIS and finally estimation groundwater vulnerability for each soil unit was represented into a map as well as visualized in 3D.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.

PubMed

Hapca, Simona; Baveye, Philippe C; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

PubMed Central

Hapca, Simona; Baveye, Philippe C.; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution. PMID:26372473

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.

The impact of soil redistribution on SOC pools in a Mediterranean agroforestry catchment

NASA Astrophysics Data System (ADS)

Quijano, Laura; Gaspar, Leticia; Lizaga, Iván; Navas, Ana

2017-04-01

Soil redistribution processes play an important role influencing the spatial distribution patterns of soil and associated soil organic carbon (SOC) at landscape scale. Information on drivers of SOC dynamics is key for evaluating both soil degradation and SOC stability that can affect soil quality and sustainability. 137Cs measurements provide a very effective tool to infer spatial patterns of soil redistribution and quantify soil redistribution rates in different landscapes, but to date these data are scarce in mountain Mediterranean agroecosystems. We evaluate the effect of soil redistribution on SOC and SOC pools in relation to land use in a Mediterranean mountain catchment (246 ha). To this purpose, two hundred and four soil bulk cores were collected on a 100 m grid in the Estaña lakes catchment located in the central sector of the Spanish Pyrenees (31T 4656250N 295152E). The study area is an agroforestry and endorheic catchment characterized by the presence of evaporite dissolution induced dolines, some of which host permanent lakes. The selected landscape is representative of rainfed areas of Mediterranean continental climate with erodible lithology and shallow soils, and characterized by an intense anthropogenic activity through cultivation and water management. The cultivated and uncultivated areas are heterogeneously distributed. SOC and SOC pools (the active and decomposable fraction, ACF and the stable carbon fraction SCF) were measured by the dry combustion method and soil redistribution rates were derived from 137Cs measurements. The results showed that erosion predominated in the catchment, most of soil samples were identified as eroded sites (n=114) with an average erosion rate of 26.9±51.4 Mg ha-1 y-1 whereas the mean deposition rate was 13.0±24.2 Mg ha-1 y-1. In cultivated soils (n=54) the average of soil erosion rate was significantly higher (78.5±74.4 Mg ha-1 y-1) than in uncultivated soils (6.8±10.4 Mg ha-1 y-1). Similarly, the mean of soil deposition rate in cultivated soils (n=22) was significantly higher (42.6±35.1 Mg ha-1 y-1) than in uncultivated soils (3.4±3.2 Mg ha-1 y-1). The mean SOC content for all soil samples was 2.5±2.0%. In uncultivated soils, significantly higher (P<0.01) amounts of SOC (3.0±2.6%), ACF (2.1±0.7%) and SCF (0.9±0.4%) were found compared to cultivated soils where the means were 1.1±0.7%, 0.7±0.5% and 0.4±0.3%, respectively. Significant (P<0.05) correlations between SOC, SOC pools and soil redistribution rates indicate that the distribution of SOC pools were significantly affected by soil redistribution in the study area. SOC and SOC pools were significantly higher at depositional (n=90, 2.8±1.8%) than at eroded sampling points (2.2±2.1%). ACF shows greater differences at eroding sites and at depositional sites than SCF reflecting that ACF is more sensitive to soil redistribution processes. Our findings emphasize the role of soil redistribution and land use in influencing the dynamics of SOC, information that can be also relevant in soil management. Improving the knowledge on the relationships between land use, soil redistribution processes and SOC fractions is of interest, especially in these Mediterranean rapidly changing landscapes.

Soil moisture controlled runoff mechanisms in a small agricultural catchment in Austria.

NASA Astrophysics Data System (ADS)

Vreugdenhil, Mariette; Szeles, Borbala; Silasari, Rasmiaditya; Hogan, Patrick; Oismueller, Markus; Strauss, Peter; Wagner, Wolfgang; Bloeschl, Guenter

2017-04-01

Understanding runoff generation mechanisms is pivotal for improved estimation of floods in small catchments. However, this requires in situ measurements with a high spatial and temporal resolution of different land surface parameters, which are rarely available distributed over the catchment scale and for a long period. The Hydrological Open Air Laboratory (HOAL) is a hydrological observatory which comprises a complex agricultural catchment, covering 66 ha. Due to the agricultural land use and low permeability of the soil part of the catchment was tile drained in the 1940s. The HOAL is equipped with an extensive soil moisture network measuring at 31 locations, 4 rain gauges and 12 stream gauges. By measuring with so many sensors in a complex catchment, the collected data enables the investigation of multiple runoff mechanisms which can be observed simultaneously in different parts of the catchment. The aim of this study is to identify and characterize different runoff mechanisms and the control soil moisture dynamics exert on them. As a first step 72 rainfall events were identified within the period 2014-2015. By analyzing event discharge response, measured at the different stream gauges, and root zone soil moisture, four different runoff mechanisms are identified. The four mechanisms exhibit contrasting soil moisture-discharge relationships. In the presented study we characterize the runoff response types by curve-fitting the discharge response to the soil moisture state. The analysis provides insights in the main runoff processes occurring in agricultural catchments. The results of this study a can be of assistance in other catchments to identify catchment hydrologic response.

Spatial and temporal variation of moisture content in the soil profiles of two different agricultural fields of semi-arid region.

PubMed

Baskan, Oguz; Kosker, Yakup; Erpul, Gunay

2013-12-01

Modeling spatio-temporal variation of soil moisture with depth in the soil profile plays an important role for semi-arid crop production from an agro-hydrological perspective. This study was performed in Guvenc Catchment. Two soil series that were called Tabyabayir (TaS) and Kervanpinari (KeS) and classified as Leptosol and Vertisol Soil Groups were used in this research. The TeS has a much shallower (0-34 cm) than the KeS (0-134 cm). At every sampling time, a total of geo-referenced 100 soil moisture samples were taken based on horizon depths. The results indicated that soil moisture content changed spatially and temporally with soil texture and profile depth significantly. In addition, land use was to be important factor when soil was shallow. When the soil conditions were towards to dry, higher values for the coefficient of variation (CV) were observed for TaS (58 and 43% for A and C horizons, respectively); however, the profile CV values were rather stable at the KeS. Spatial variability range of TaS was always higher at both dry and wet soil conditions when compared to that of KeS. Excessive drying of soil prevented to describe any spatial model for surface horizon, additionally resulting in a high nugget variance in the subsurface horizon for the TaS. On the contrary to TaS, distribution maps were formed all horizons for the KeS at any measurement times. These maps, depicting both dry and wet soil conditions through the profile depth, are highly expected to reduce the uncertainty associated with spatially and temporally determining the hydraulic responses of the catchment soils.

Nitrogen Fertilization Elevated Spatial Heterogeneity of Soil Microbial Biomass Carbon and Nitrogen in Switchgrass and Gamagrass Croplands

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.

Visible and infrared spectroscopy to evaluate soil quality in degraded sites: an applicative study in southern Italy

NASA Astrophysics Data System (ADS)

Ancona, Valeria; Matarrese, Raffaella; Salvatori, Rosamaria; Salzano, Roberto; Regano, Simona; Calabrese, Angelantonio; Campanale, Claudia; Felice Uricchio, Vito

2014-05-01

Land degradation processes like organic matter impoverishment and contamination are growing increasingly all over the world due to a non-rational and often sustainable spread of human activities on the territory. Consequently the need to characterize and monitor degraded sites is becoming very important, with the aim to hinder such main threats, which could compromise drastically, soil quality. Visible and infrared spectroscopy is a well-known technique/tool to study soil properties. Vis-NIR spectral reflectance, in fact, can be used to characterize spatial and temporal variation in soil constituents (Brown et al., 2006; Viscarra Rossel et al., 2006), and potentially its surface structure (Chappell et al., 2006, 2007). It is a rapid, non-destructive, reproducible and cost-effective analytical method to analyse soil properties and therefore, it can be a useful method to study land degradation phenomena. In this work, we present the results of proximal sensing investigations of three degraded sites (one affected by organic and inorganic contamination and two affected by soil organic matter decline) situated southern Italy close to Taranto city (in Apulia Region). A portable spectroradiometer (ASD-FieldSpec) was used to measure the reflectance properties in the spectral range between 350-2500 nm of the soil, in the selected sites, before and after a recovery treatment by using compost (organic fertilizer). For each measurement point the soil was sampled in order to perform chemical analyses to evaluate soil quality status. Three in-situ campaigns have been carried out (September 2012, June 2013, and September 2013), collecting about 20 soil samples for each site and for each campaign. Chemical and spectral analyses have been focused on investigating soil organic carbon, carbonate content, texture and, in the case of polluted site, heavy metals and organic toxic compounds. Statistical analyses have been carried out to test a prediction model of different soil quality indicators based on the spectral signatures behaviour of each sample ranging.

Spatial variability of total carbon and soil organic carbon in agricultural soils in Baranja region, Croatia

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.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

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.

Pattern of ground deformation in Kathmandu valley during 2015 Gorkha Earthquake, central Nepal

NASA Astrophysics Data System (ADS)

Ghimire, S.; Dwivedi, S. K.; Acharya, K. K.

2016-12-01

The 25th April 2015 Gorkha Earthquake (Mw=7.8) epicentered at Barpak along with thousands of aftershocks released seismic moment nearly equivalent to an 8.0 Magnitude earthquake rupturing a 150km long fault segment. Although Kathmandu valley was supposed to be severely devastated by such major earthquake, post earthquake scenario is completely different. The observed destruction is far less than anticipated as well as the spatial pattern is different than expected. This work focuses on the behavior of Kathmandu valley sediments during the strong shaking by the 2015 Gorkha Earthquake. For this purpose spatial pattern of destruction is analyzed at heavily destructed sites. To understand characteristics of subsurface soil 2D-MASW survey was carried out using a 24-channel seismograph system. An accellerogram recorded by Nepal Seismological Center was analyzed to characterize the strong ground motion. The Kathmandu valley comprises fluvio-lacustrine deposit with gravel, sand, silt and clay along with few exposures of basement rocks within the sediments. The observations show systematic repetition of destruction at an average interval of 2.5km mostly in sand, silt and clay dominated formations. Results of 2D-MASW show the sites of destruction are characterized by static deformation of soil (liquefaction and southerly dipping cracks). Spectral analysis of the accelerogram indicates maximum power associated with frequency of 1.0Hz. The result of this study explains the observed spatial pattern of destruction in Kathmandu valley. This is correlated with the seismic energy associated with the frequency of 1Hz, which generates an average wavelength of 2.5km with an average S-wave velocity of 2.5km/s. The cumulative effect of dominant frequency and associated wavelength resulted in static deformation of surface soil layers at an average interval of 2.5km. This phenomenon clearly describes the reason for different scenario than that was anticipated in Kathmandu valley.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Spatial variability of soil carbon, pH, available phosphorous and potassium in organic farm located in Mediterranean Croatia

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

Aspects of spatial and temporal aggregation in estimating regional carbon dioxide fluxes from temperate forest soils

NASA Technical Reports Server (NTRS)

Kicklighter, David W.; Melillo, Jerry M.; Peterjohn, William T.; Rastetter, Edward B.; Mcguire, A. David; Steudler, Paul A.; Aber, John D.

1994-01-01

We examine the influence of aggregation errors on developing estimates of regional soil-CO2 flux from temperate forests. We find daily soil-CO2 fluxes to be more sensitive to changes in soil temperatures (Q(sub 10) = 3.08) than air temperatures (Q(sub 10) = 1.99). The direct use of mean monthly air temperatures with a daily flux model underestimates regional fluxes by approximately 4%. Temporal aggregation error varies with spatial resolution. Overall, our calibrated modeling approach reduces spatial aggregation error by 9.3% and temporal aggregation error by 15.5%. After minimizing spatial and temporal aggregation errors, mature temperate forest soils are estimated to contribute 12.9 Pg C/yr to the atmosphere as carbon dioxide. Georeferenced model estimates agree well with annual soil-CO2 fluxes measured during chamber studies in mature temperate forest stands around the globe.

Spatial variability of isoproturon mineralizing activity within an agricultural field: geostatistical analysis of simple physicochemical and microbiological soil parameters.

PubMed

El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F

2007-02-01

We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.

Geostatistics, remote sensing and precision farming.

PubMed

Mulla, D J

1997-01-01

Precision farming is possible today because of advances in farming technology, procedures for mapping and interpolating spatial patterns, and geographic information systems for overlaying and interpreting several soil, landscape and crop attributes. The key component of precision farming is the map showing spatial patterns in field characteristics. Obtaining information for this map is often achieved by soil sampling. This approach, however, can be cost-prohibitive for grain crops. Soil sampling strategies can be simplified by use of auxiliary data provided by satellite or aerial photo imagery. This paper describes geostatistical methods for estimating spatial patterns in soil organic matter, soil test phosphorus and wheat grain yield from a combination of Thematic Mapper imaging and soil sampling.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

NASA Technical Reports Server (NTRS)

Kim, Edward

2011-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions

NASA Technical Reports Server (NTRS)

Kim, Edward

2012-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.

Developing erosion models for integrated coastal zone management: a case study of The New Caledonia west coast.

PubMed

Dumas, Pascal; Printemps, Julia; Mangeas, Morgan; Luneau, Gaelle

2010-01-01

The tropical climate and human pressures (mining industry, forest fires) cause significant sediment inputs into the New Caledonia lagoon and are a major cause of degradation of the fringing reefs. The erosion process is spatially characterized on the west coast of New Caledonia to assess potential sediment inputs in the marine area. This paper describes the methodologies that are used to map soil sensitivity to erosion using remote sensing and a geographic information system tool. A cognitive approach, multi-criteria evaluation model and Universal Soil Loss Equation are implemented. This article compares the relevance of each model in order to spatialize and quantify potential erosion at catchment basin scale. These types of studies provide valuable results for focusing on areas subject to erosion and serve as a decision-making tool for the minimization of lagoon vulnerability to the natural and human dynamics on the level of the catchment basins. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

[MODIS-driven estimation of regional evapotranspiration in Karst area of Southwest China based on the Penman-Monteith-Leuning algorithm.

PubMed

Zhong, Hao Zhe; Xu, Xian Li; Zhang, Rong Fei; Liu, Mei Xian

2018-05-01

Karst area in southwestern China is characterized with complex topography, low soil water capacity, and fragile ecosystem. Accurate estimation of regional evapotranspiration is essential for ecological restoration and water resources management in southwestern China. Based on observed evapotranspiration and meteorological data, this study aimed to estimate spatial upscale evapotranspiration using the MOD15A2 LAI and Penman-Monteith-Leuning (PML) model, within which the stomatal conductance and soil wetness index were optimized by the least-square method. The results showed that the modeled ET well fitted with the observations, with the determination coefficient, Nash efficiency coefficient and RMSE being 0.85, 0.75 and 1.56 mm·d -1 , respectively. The ET exhibited clear seasonality and reached to its maximum in summer, coinciding with vegetation phenology. The annual ET ranged from 534 to 1035 mm·a -1 , with strong spatial heterogeneity which highly related to the precipitation. Evapotranspiration may be affected by precipitation as well as land use types.

Analyzing spatial patterns linked to the ecology of herbivores and their natural enemies in the soil.

PubMed

Campos-Herrera, R; Ali, J G; Diaz, B M; Duncan, L W

2013-09-30

Modern agricultural systems can benefit from the application of concepts and models from applied ecology. When understood, multitrophic interactions among plants, pests, diseases and their natural enemies can be exploited to increase crop production and reduce undesirable environmental impacts. Although the understanding of subterranean ecology is rudimentary compared to the perspective aboveground, technologies today vastly reduce traditional obstacles to studying cryptic communities. Here we emphasize advantages to integrating as much as possible the use of these methods in order to leverage the information gained from studying communities of soil organisms. PCR-based approaches to identify and quantify species (real time qPCR and next generation sequencing) greatly expand the ability to investigate food web interactions because there is less need for wide taxonomic expertise within research programs. Improved methods to capture and measure volatiles in the soil atmosphere in situ make it possible to detect and study chemical cues that are critical to communication across trophic levels. The application of SADIE to directly assess rather than infer spatial patterns in belowground agroecosystems has improved the ability to characterize relationships between organisms in space and time. We review selected methodology and use of these tools and describe some of the ways they were integrated to study soil food webs in Florida citrus orchards with the goal of developing new biocontrol approaches.

Effects of low-scale landscape structures on aeolian transport processes on arable land

NASA Astrophysics Data System (ADS)

Siegmund, Nicole; Funk, Roger; Koszinsky, Sylvia; Buschiazzo, Daniel Eduardo; Sommer, Michael

2018-06-01

The landscape of the semiarid Pampa in central Argentina is characterized by late Pleistocene aeolian deposits, covering large plains with sporadic dune structures. Since the current land use changed from extensive livestock production within the Caldenal forest ecosystem to arable land, the wind erosion risk increased distinctly. We measured wind erosion and deposition patterns at the plot scale and investigated the spatial variability of the erosion processes. The wind-induced mass-transport was measured with 18 Modified Wilson and Cooke samplers (MWAC), installed on a 1.44 ha large field in a 20 × 40 m grid. Physical and chemical soil properties from the upper soil as well as a digital elevation model were recorded in a 20 × 20 m grid. In a 5-month measuring campaign data from seven storms with three different wind directions was obtained. Results show very heterogeneous patterns of erosion and deposition for each storm and indicate favoured erosion on windward and deposits on leeward terrain positions. Furthermore, a multiple regression model was build, explaining up to 70% of the spatial variance of erosion by just using four predictors: topsoil thickness, relative elevation, soil organic carbon content and slope direction. Our findings suggest a structure-process-structure complex where the landscape structure determines the effects of recent wind erosion processes which again slowly influence the structure, leading to a gradual increase of soil heterogeneity.

Analyzing spatial patterns linked to the ecology of herbivores and their natural enemies in the soil

PubMed Central

Campos-Herrera, R.; Ali, J. G.; Diaz, B. M.; Duncan, L. W.

2013-01-01

Modern agricultural systems can benefit from the application of concepts and models from applied ecology. When understood, multitrophic interactions among plants, pests, diseases and their natural enemies can be exploited to increase crop production and reduce undesirable environmental impacts. Although the understanding of subterranean ecology is rudimentary compared to the perspective aboveground, technologies today vastly reduce traditional obstacles to studying cryptic communities. Here we emphasize advantages to integrating as much as possible the use of these methods in order to leverage the information gained from studying communities of soil organisms. PCR-based approaches to identify and quantify species (real time qPCR and next generation sequencing) greatly expand the ability to investigate food web interactions because there is less need for wide taxonomic expertise within research programs. Improved methods to capture and measure volatiles in the soil atmosphere in situ make it possible to detect and study chemical cues that are critical to communication across trophic levels. The application of SADIE to directly assess rather than infer spatial patterns in belowground agroecosystems has improved the ability to characterize relationships between organisms in space and time. We review selected methodology and use of these tools and describe some of the ways they were integrated to study soil food webs in Florida citrus orchards with the goal of developing new biocontrol approaches. PMID:24137165

Spatially variable natural selection and the divergence between parapatric subspecies of lodgepole pine (Pinus contorta, Pinaceae).

PubMed

Eckert, Andrew J; Shahi, Hurshbir; Datwyler, Shannon L; Neale, David B

2012-08-01

Plant populations arrayed across sharp environmental gradients are ideal systems for identifying the genetic basis of ecologically relevant phenotypes. A series of five uplifted marine terraces along the northern coast of California represents one such system where morphologically distinct populations of lodgepole pine (Pinus contorta) are distributed across sharp soil gradients ranging from fertile soils near the coast to podzolic soils ca. 5 km inland. A total of 92 trees was sampled across four coastal marine terraces (N = 10-46 trees/terrace) located in Mendocino County, California and sequenced for a set of 24 candidate genes for growth and responses to various soil chemistry variables. Statistical analyses relying on patterns of nucleotide diversity were employed to identify genes whose diversity patterns were inconsistent with three null models. Most genes displayed patterns of nucleotide diversity that were consistent with null models (N = 19) or with the presence of paralogs (N = 3). Two genes, however, were exceptional: an aluminum responsive ABC-transporter with F(ST) = 0.664 and an inorganic phosphate transporter characterized by divergent haplotypes segregating at intermediate frequencies in most populations. Spatially variable natural selection along gradients of aluminum and phosphate ion concentrations likely accounted for both outliers. These results shed light on some of the genetic components comprising the extended phenotype of this ecosystem, as well as highlight ecotones as fruitful study systems for the detection of adaptive genetic variants.

An analysis of soil moisture and vegetation conditions during a period of rapid subseasonal oscillations between drought and pluvials over Texas during 2015

NASA Astrophysics Data System (ADS)

Hunt, E. D.; Otkin, J.; Zhong, Y.

2017-12-01

Flash drought, characterized by the rapid onset of abnormally warm and dry weather conditions that leads to the rapid depletion of soil moisture and rapid deteriorations in vegetation health. Flash recovery, on the other hand, is characterized by a period(s) of intense precipitation where drought conditions are quickly eradicated and may be replaced by saturated soils and flooding. Both flash drought and flash recovery are closely tied to the rapid depletion or recharge of root zone soil moisture; therefore, soil moisture observations are very useful for monitoring their evolution. However, in-situ soil moisture observations tend to be concentrated over small regions and thus other methods are needed to provide a spatially continuous depiction of soil moisture conditions. One option is to use top soil moisture retrievals from the Soil Moisture Active Passive (SMAP) sensor. SMAP provides routine coverage of surface soil moisture (0-5 cm) over most of the globe, including the timespan (2015) and region of interest (Texas) that are the focus of our study. This region had an unusual sequence of flash recovery-flash drought-flash recovery during an six-month period during 2015 that provides a valuable case study of rapid transitions between extreme soil moisture conditions. During this project, SMAP soil moisture retrievals are being used in combination with in-situ soil moisture observations and assimilated into the Land Information System (LIS) to provide information about soil moisture content. LIS also provides greenness vegetation fraction data over large regions. The relationship between soil moisture and vegetation conditions and the response of the vegetation to the rapidly changing conditions are also assessed using the satellite thermal infrared based Evaporative Stress Index (ESI) that depicts anomalies in evapotranspiration, along with other vegetation datasets (leaf area index, greenness fraction) derived using MODIS observations. Preliminary results with the Noah land surface model (inside of LIS) shows that it broadly captured the soil moisture evolution during the 2015 sequence but tended to underestimate the magnitude of soil moisture anomalies. The ESI also showed negative anomalies during the drought. These and other results will be presented at the annual meeting.

Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.

PubMed

Li, Mingming; Zhang, Xingchang; Zhen, Qing; Han, Fengpeng

2013-01-01

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g · kg(-1). The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0-10 and 10-20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.

Soil water content spatial pattern estimated by thermal inertia from air-borne sensors

NASA Astrophysics Data System (ADS)

Coppola, Antonio; Basile, Angelo; Esposito, Marco; Menenti, Massimo; Buonanno, Maurizio

2010-05-01

Remote sensing of soil water content from air- or space-borne platforms offer the possibility to provide large spatial coverage and temporal continuity. The water content can be actually monitored in a thin soil layer, usually up to a depth of 0.05m below the soil surface. To the contrary, difficulties arise in the estimation of the water content storage along the soil profile and its spatial (horizontal) distribution, which are closely connected to soil hydraulic properties and their spatial distribution. A promising approach for estimating soil water contents profiles is the integration of remote sensing of surface water content and hydrological modeling. A major goal of the scientific group is to develop a practical and robust procedure for estimating water contents throughout the soil profile from surface water content. As a first step, in this work, we will show some preliminary results from aircraft images analysis and their validation by field campaigns data. The data extracted from the airborne sensors provided the opportunity of retrieving land surface temperatures with a very high spatial resolution. The surface water content pattern, as deduced by the thermal inertia estimations, was compared to the surface water contents maps measured in situ by time domain reflectometry-based probes.

Principal factors of soil spatial heterogeneity and ecosystem services at the Central Chernozemic Region of Russia

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Valentini, Riccardo

2013-04-01

The essential spatial heterogeneity is mutual feature for most natural and man-changed soils at the Central Chernozemic Region of Russia which is not only one of the biggest «food baskets» in RF but very important regulator of ecosystem principal services at the European territory of Russia. The original spatial heterogeneity of dominated here forest-steppe and steppe Chernozems and the other soils has been further complicated by a specific land-use history and different-direction soil successions due to environmental changes and more than 1000-year history of human impacts. The carried out long-term researches of representative natural, rural and urban landscapes in Kursk, Orel, Tambov and Voronezh oblasts give us the regional multi-factorial matrix of elementary soil cover patterns (ESCP) with different land-use practices and history, soil-geomorphologic features, environmental and microclimate conditions. The validation and ranging of the limiting factors of ESCP regulation and development, ecosystem principal services, land functional qualities and agroecological state have been done for dominating and most dynamical components of ESCP regional-typological forms - with application of regional and local GIS, soil spatial patterns mapping, traditional regression kriging, correlation tree models. The outcomes of statistical modeling show the essential amplification of erosion, dehumification and CO2 emission, acidification and alkalization, disaggregation and overcompaction processes due to violation of agroecologically sound land-use systems and traditional balances of organic matter, nutrients, Ca and Na in agrolandscapes. Due to long-term intensive and out-of-balance land-use practices the famous Russian Chernozems begin to lose not only their unique natural features of (around 1 m of humus horizon, 4-6% of Corg and favorable agrophysical features), but traditional soil cover patterns, ecosystem services and agroecological functions. Key-site monitoring results and regional generalized data showed 1-1.5 % Corg lost during last 50 years period and active processes of CO2 emission and humus profile eluvial-illuvial redistribution too. Forest-steppe Chernozems are usually characterized by higher stability than steppe ones. The ratio between erosive and biological losses in humus supplies can be ten¬tatively estimated as fifty-fifty with strong spatial variability due to slope and land-use parameters. These processes have essentially different sets of environmental consequences and ecosystem services that we need to understand in frame of agroecological problems development prediction. A drop of Corg content below threshold "humus limiting content" values (3-4% of Corg) considerably reduces effectiveness of used fertilizers and possibility of sustainable agronomy here. This problem environmental and agroecological situation can be essentially improved by new federal law on environmentally friendly agriculture but it's draft is still in the process of deliberation. Quantitative analysis of principal ecosystem services, soil cover patterns and degradation processes in parameters of land qualities help us in developing different-scale projects for agricultural and urban land-use, taking into attention not only economical benefits but environmental functions too. The conceptions of ecosystem services and local land resource management are becoming more and more popular at the Central Chernozemic Region of Russia due to innovation application of basic agroecology, ecological monitoring and soil science achievements.

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

NASA Astrophysics Data System (ADS)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

Microrelief and vegetation as the factors of spatial redistribution of nutrients in the soils of forest ecosystems

NASA Astrophysics Data System (ADS)

Chernitsova, Olga; Krechetov, Pavel

2017-04-01

The study is aimed at the identifying factors and mechanisms controlling the redistribution of nutrients in the profile of sod-podzolic soils (Umbric Albeluvisols Abruptic in WRB, 2006). The data of chemical analyzes of soil samples of soddy-pale-podzolic soils under mixed coniferous-deciduous forests, picked from the genetic horizons of 28 soil profiles up to the depth of 120-150 cm in the key area with a polygonal-block microrelief (58.39°N, 56.52°E) were used. Soil profiles were placed at the key area considering vegetation and microrelief. Samples were analyzed for humus content, available forms of N, P, K, Ca, Mg and soil texture. Published data on the capacity and the structure of biogeochemical cycling in forest phytocenoses of different ages in the southern taiga were summarized. Field sketches were used for the construction of the digital elevation model of the key area and for plotting the vegetation map showing the crowns' projections of trees and shrubs of different species. Using spatial interpolation in GIS, series of schematic maps were created that characterize the depth of the lower boundary of genetic horizons and their thickness, as well as the texture of the different soil horizons, humus content and distribution of nutrients at different depths. These schematic maps were analyzed for patterns of radial and lateral differentiation of all examined features. Pronounced textural differentiation of soils of micro-elevations and poor textural differentiation of soil of micro-depressions are revealed. It is shown that in the soils with the positions from micro-elevations through flat surfaces to micro-depressions the humus content in the upper layers (horizon A) increases 1.6-1.7 times, the content of nitrogen ‒ 1.4-1.5, phosphorus ‒ 2.6 8.4, calcium and magnesium cations ‒ 1.8-2.9 times. This differentiation in nutrients' content is coming along with the settlement of more demanding to soil fertility plants in micro-depressions. Also the bimodal distribution of the available forms of potassium, phosphorus, calcium, magnesium in the soil profile was revealed. The first maximum of nutrients content is detected in the humus-accumulative horizon A, the second - in the illuvial horizon Bt. The eluvial horizons EL are characterized by the minimum values. Considering the thickness of soil horizons, supplies of available forms of phosphorus, potassium, calcium and magnesium were estimated, which are 1.5-2.5 times higher in deeper soil horizons than in the upper ones. The complex ecological and geochemical structure of forest ecosystems is regulated by both the lateral additional supply of mobile chemical compounds by the surface and subsurface runoff, including melted snow water, as well as the peculiarities of biogeochemical cycling (the age of the forest, the penetration depth of suction roots of various species of trees, the chemical composition of the litter).

Drought characteristics' role in widespread aspen forest mortality across Colorado, USA.

PubMed

Anderegg, Leander D L; Anderegg, William R L; Abatzoglou, John; Hausladen, Alexandra M; Berry, Joseph A

2013-05-01

Globally documented widespread drought-induced forest mortality has important ramifications for plant community structure, ecosystem function, and the ecosystem services provided by forests. Yet the characteristics of drought seasonality, severity, and duration that trigger mortality events have received little attention despite evidence of changing precipitation regimes, shifting snow melt timing, and increasing temperature stress. This study draws upon stand level ecohydrology and statewide climate and spatial analysis to examine the drought characteristics implicated in the recent widespread mortality of trembling aspen (Populus tremuloides Michx.). We used isotopic observations of aspen xylem sap to determine water source use during natural and experimental drought in a region that experienced high tree mortality. We then drew upon multiple sources of climate data to characterize the drought that triggered aspen mortality. Finally, regression analysis was used to examine the drought characteristics most associated with the spatial patterns of aspen mortality across Colorado. Isotopic analysis indicated that aspens generally utilize shallow soil moisture with little plasticity during drought stress. Climate analysis showed that the mortality-inciting drought was unprecedented in the observational record, especially in 2002 growing season temperature and evaporative deficit, resulting in record low shallow soil moisture reserves. High 2002 summer temperature and low shallow soil moisture were most associated with the spatial patterns of aspen mortality. These results suggest that the 2002 drought subjected Colorado aspens to the most extreme growing season water stress of the past century by creating high atmospheric moisture demand and depleting the shallow soil moisture upon which aspens rely. Our findings highlight the important role of drought characteristics in mediating widespread aspen forest mortality, link this aspen die-off to regional climate change trends, and provide insight into future climate vulnerability of these forests. © 2013 Blackwell Publishing Ltd.

Spatial and Temporal Evaluation of Soil Erosion with RUSLE: A Case Study in an Olive Orchard Microcathment in Spain

EPA Science Inventory

Soil loss is commonly estimated using the Revised Universal Soil Loss Equation (RUSLE). Since RUSLE is an empirically based soil loss model derived from surveys on plots, the high spatial and temporal variability of erosion in Mediterranean environments and scale effects provoke...

Spatial and Temporal Evaluation of Soil Erosion with RUSLE: A case Study in an Olive Orchard Microcathment in Spain

EPA Science Inventory

Soil loss is commonly estimated using the Revised Universal Soil Loss Equation (RUSLE). Since RUSLE is an empirically based soil loss model derived from surveys on plots, the high spatial and temporal variability of erosion in Mediterranean environments and scale effects provo...

Evaluation of Ku-Band Sensitivity To Soil Moisture: Soil Moisture Change Detection Over the NAFE06 Study Area

USDA-ARS?s Scientific Manuscript database

A very promising technique for spatial disaggregation of soil moisture is on the combination of radiometer and radar observations. Despite their demonstrated potential for long term large scale monitoring of soil moisture, passive and active have their disadvantages in terms of temporal and spatial ...

[Spatial heterogeneity of surface soil mineral components in a small catchment in Karst peak-cluster depression area, South China].

PubMed

Gao, Peng; Fu, Tong-Gang; Wang, Ke-Lin; Chen, Hong-Song; Zeng, Fu-Ping

2013-11-01

A total of 163 soil samples (0-20 cm layer) were collected from the grid sampling plots (80 m x 80 m) in Huanjiang Observation and Research Station of Karst Ecosystem in a small catchment in Karst cluster-peak depression area, South China. By using classical statistics and geostatistics, the spatial heterogeneity of mineral components (SiO2, Fe2O3, CaO, MgO, Al2O3, MnO, and TiO2) in the soils were studied. The contents of the seven soil mineral components in the study area differed greatly, being in the order of SiO2 > Al2O3 > CaO > MgO > Fe2O3 > TiO2 > MnO, and the variance coefficients also varied obviously, in the order of CaO > MgO > Fe2O3 > TiO2 > SiO2 > Al2O3 > MnO. The seven mineral components accounted for 69.4% of the total soil mass. The spatial patterns and the fittest models of the seven soil mineral components differed from each other. All the seven soil mineral components had a strong spatial autocorrelation, with shorter variation ranges and stronger spatial dependence. The Kriging contour maps indicated that the distribution patterns of soil SiO2, Fe2O3, Al2O3, MnO, and TiO2 were similar, being higher in south and east, lower in north and west, higher in depression, and lower in slope, while the distribution patterns of soil CaO and MgO were in adverse. Natural conditions (vegetation, bare rock rate, slope degree, and slope aspect, etc. ) and human disturbance were the most important factors affecting the spatial patterns of the soil mineral components.

Spatial variability of soils in a seasonally dry tropical forest

NASA Astrophysics Data System (ADS)

Pulla, Sandeep; Riotte, Jean; Suresh, Hebbalalu; Dattaraja, Handanakere; Sukumar, Raman

2016-04-01

Soil structures communities of plants and soil organisms in tropical forests. Understanding the controls of soil spatial variability can therefore potentially inform efforts towards forest restoration. We studied the relationship between soils and lithology, topography, vegetation and fire in a seasonally dry tropical forest in southern India. We extensively sampled soil (available nutrients, Al, pH, and moisture), rocks, relief, woody vegetation, and spatial variation in fire burn frequency in a permanent 50-ha plot. Lower elevation soils tended to be less moist and were depleted in several nutrients and clay. The availability of several nutrients was, in turn, linked to whole-rock chemical composition differences since some lithologies were associated with higher elevations, while the others tended to dominate lower elevations. We suggest that local-scale topography in this region has been shaped by the spatial distribution of lithologies, which differ in their susceptibility to weathering. Nitrogen availability was uncorrelated with the presence of trees belonging to Fabaceae, a family associated with N-fixing species. No effect of burning on soil parameters could be discerned at this scale.

Spatial patterns of soil pH and the factors that influence them in plantation forests of northern China

NASA Astrophysics Data System (ADS)

Hong, Songbai; Liu, Yongwen; Piao, Shilong

2017-04-01

Climate and anthropogenic activities such as afforestation and nitrogen deposition all impact soil pH. Understanding the spatial pattern of soil pH and the factors that influence it can provide basic information for generating appropriate strategies for soil resource management and protection, especially in light of increasing anthropogenic influences and climate change. In this study, we investigated the spatial and vertical pattern of soil pH and evaluated the influence of climate and nitrogen deposition using 1647 soil profiles 1 meter in depth from 549 plots in plantation forests of northern China. We found that soil pH decreased from the southwest to the northeast in the study region and had a similar spatial pattern before and after afforestation. Furthermore, our results show that climate and nitrogen deposition fundamentally influence the pattern of soil pH. Specifically, increasing precipitation significantly decreased soil pH (with a mean rate of 0.3 for every 100 mm rainfall, p<0.001), whereas increasing temperature significantly increased soil pH (0.13 for every degree centigrade, p<0.001). Nitrogen deposition, especially nitrate nitrogen, significantly decreased soil pH (p<0.01). All these factors impact soil pH directly and indirectly through climate-plant-soil interactions. As the risks from both climate change and nitrogen deposition increase, there is an urgent need to further understanding of soil pH dynamics and to develop informed policies to protect soil resources.

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.

Spatial and temporal variability of hyperspectral signatures of terrain

NASA Astrophysics Data System (ADS)

Jones, K. F.; Perovich, D. K.; Koenig, G. G.

2008-04-01

Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

Urban gray vs. urban green vs. soil protection — Development of a systemic solution to soil sealing management on the example of Germany

DOE Office of Scientific and Technical Information (OSTI.GOV)

Artmann, Martina, E-mail: m.artmann@ioer.de

Managing urban soil sealing is a difficult venture due to its spatial heterogeneity and embedding in a socio-ecological system. A systemic solution is needed to tackle its spatial, ecological and social sub-systems. This study develops a guideline for urban actors to find a systemic solution to soil sealing management based on two case studies in Germany: Munich and Leipzig. Legal-planning, informal-planning, economic-fiscal, co-operative and informational responses were evaluated by indicators to proof which strategy considers the spatial complexity of urban soil sealing (systemic spatial efficiency) and, while considering spatial complexity, to assess what the key management areas for action aremore » to reduce the ecological impacts by urban soil sealing (ecological impact efficiency) and to support an efficient implementation by urban actors (social implementation efficiency). Results suggest framing the systemic solution to soil sealing management through a cross-scale, legal-planning development strategy embedded in higher European policies. Within the socio-ecological system, the key management area for action should focus on the protection of green infrastructure being of high value for actors from the European to local scales. Further efforts are necessary to establish a systemic monitoring concept to optimize socio-ecological benefits and avoid trade-offs such as between urban infill development and urban green protection. This place-based study can be regarded as a stepping stone on how to develop systemic strategies by considering different spatial sub-targets and socio-ecological systems. - Highlights: • Urban soil sealing management is spatially complex. • The legal-planning strategy supports a systemic sealing management. • Urban green infrastructure protection should be in the management focus. • Soil protection requires policies from higher levels of government. • A systemic urban soil sealing monitoring concept is needed.« less

Proximal soil sensing: global perspective

USDA-ARS?s Scientific Manuscript database

As a result of a number of naturally occurring processes and cultural practices, the characteristics of soils demonstrate substantial spatial heterogeneity that affects current land use. From infrastructure development to agriculture, spatial variability in soils must be taken into account in order ...

Reconciling spatial and temporal soil moisture effects on afternoon rainfall

PubMed Central

Guillod, Benoit P.; Orlowsky, Boris; Miralles, Diego G.; Teuling, Adriaan J.; Seneviratne, Sonia I.

2015-01-01

Soil moisture impacts on precipitation have been strongly debated. Recent observational evidence of afternoon rain falling preferentially over land parcels that are drier than the surrounding areas (negative spatial effect), contrasts with previous reports of a predominant positive temporal effect. However, whether spatial effects relating to soil moisture heterogeneity translate into similar temporal effects remains unknown. Here we show that afternoon precipitation events tend to occur during wet and heterogeneous soil moisture conditions, while being located over comparatively drier patches. Using remote-sensing data and a common analysis framework, spatial and temporal correlations with opposite signs are shown to coexist within the same region and data set. Positive temporal coupling might enhance precipitation persistence, while negative spatial coupling tends to regionally homogenize land surface conditions. Although the apparent positive temporal coupling does not necessarily imply a causal relationship, these results reconcile the notions of moisture recycling with local, spatially negative feedbacks. PMID:25740589

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies ergodicity and quasi-stationarity assumptions, required for geostatistical analysis. The semivariograms examinations revealed that spatial dependences occurring in the surface soil moisture distributions for the selected area were more or less 200 km. The exception was the driest of the studied days, when the spatial correlations of soil moisture were not disturbed for a long time by any rainfall. Spatial correlation length on that day was about 400 km. Because of zonal character of frost, the spatial dependences in the examined surface soil moisture distributions during freezing/thawing found to be disturbed. Probably, the amount of water remains the same, but it is not detected by SMOS, hence analysing dielectric constant instead of soil moisture would be more appropriate. Some spatial relations of soil moisture and freezing distribution with existing maps of soil granulometric fractions and soil specific surface area for Poland have also been found. The work was partially funded under the ELBARA_PD (Penetration Depth) project No. 4000107897/13/NL/KML. ELBARA_PD project is funded by the Government of Poland through an ESA (European Space Agency) Contract under the PECS (Plan for European Cooperating States).

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

DTIC Science & Technology

2010-01-25

2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

Structure, variation, and assembly of the root-associated microbiomes of rice

PubMed Central

Edwards, Joseph; Johnson, Cameron; Santos-Medellín, Christian; Lurie, Eugene; Podishetty, Natraj Kumar; Bhatnagar, Srijak; Eisen, Jonathan A.; Sundaresan, Venkatesan

2015-01-01

Plants depend upon beneficial interactions between roots and microbes for nutrient availability, growth promotion, and disease suppression. High-throughput sequencing approaches have provided recent insights into root microbiomes, but our current understanding is still limited relative to animal microbiomes. Here we present a detailed characterization of the root-associated microbiomes of the crop plant rice by deep sequencing, using plants grown under controlled conditions as well as field cultivation at multiple sites. The spatial resolution of the study distinguished three root-associated compartments, the endosphere (root interior), rhizoplane (root surface), and rhizosphere (soil close to the root surface), each of which was found to harbor a distinct microbiome. Under controlled greenhouse conditions, microbiome composition varied with soil source and genotype. In field conditions, geographical location and cultivation practice, namely organic vs. conventional, were factors contributing to microbiome variation. Rice cultivation is a major source of global methane emissions, and methanogenic archaea could be detected in all spatial compartments of field-grown rice. The depth and scale of this study were used to build coabundance networks that revealed potential microbial consortia, some of which were involved in methane cycling. Dynamic changes observed during microbiome acquisition, as well as steady-state compositions of spatial compartments, support a multistep model for root microbiome assembly from soil wherein the rhizoplane plays a selective gating role. Similarities in the distribution of phyla in the root microbiomes of rice and other plants suggest that conclusions derived from this study might be generally applicable to land plants. PMID:25605935

Soil organic carbon dynamics as related to land use history in the northwestern Great Plains

USGS Publications Warehouse

Tan, Z.; Liu, S.; Johnston, C.A.; Loveland, Thomas R.; Tieszen, L.L.; Liu, J.; Kurtz, R.

2005-01-01

Strategies for mitigating the global greenhouse effect must account for soil organic carbon (SOC) dynamics at both spatial and temporal scales, which is usually challenging owing to limitations in data and approach. This study was conducted to characterize the SOC dynamics associated with land use change history in the northwestern Great Plains ecoregion. A sampling framework (40 sample blocks of 10 × 10 km2 randomly located in the ecoregion) and the General Ensemble Biogeochemical Modeling System (GEMS) were used to quantify the spatial and temporal variability in the SOC stock from 1972 to 2001. Results indicate that C source and sink areas coexisted within the ecoregion, and the SOC stock in the upper 20-cm depth increased by 3.93 Mg ha−1 over the 29 years. About 17.5% of the area was evaluated as a C source at 122 kg C ha−1 yr−1. The spatial variability of SOC stock was attributed to the dynamics of both slow and passive fractions, while the temporal variation depended on the slow fraction only. The SOC change at the block scale was positively related to either grassland proportion or negatively related to cropland proportion. We concluded that the slow C pool determined whether soils behaved as sources or sinks of atmospheric CO2, but the strength depended on antecedent SOC contents, land cover type, and land use change history in the ecoregion.

Using Electromagnetic Induction Technique to Detect Hydropedological Dynamics: Principles and Applications

NASA Astrophysics Data System (ADS)

Zhu, Qing; Liao, Kaihua; Doolittle, James; Lin, Henry

2014-05-01

Hydropedological dynamics including soil moisture variation, subsurface flow, and spatial distributions of different soil properties are important parameters in ecological, environmental, hydrological, and agricultural modeling and applications. However, technical gap exists in mapping these dynamics at intermediate spatial scale (e.g., farm and catchment scales). At intermediate scales, in-situ monitoring provides detailed data, but is restricted in number and spatial coverage; while remote sensing provides more acceptable spatial coverage, but has comparatively low spatial resolution, limited observation depths, and is greatly influenced by the surface condition and climate. As a non-invasive, fast, and convenient geophysical tool, electromagnetic induction (EMI) measures soil apparent electrical conductivity (ECa) and has great potential to bridge this technical gap. In this presentation, principles of different EMI meters are briefly introduced. Then, case studies of using repeated EMI to detect spatial distributions of subsurface convergent flow, soil moisture dynamics, soil types and their transition zones, and different soil properties are presented. The suitability, effectiveness, and accuracy of EMI are evaluated for mapping different hydropedological dynamics. Lastly, contributions of different hydropedological and terrain properties on soil ECa are quantified under different wetness conditions, seasons, and land use types using Classification and Regression Tree model. Trend removal and residual analysis are then used for further mining of EMI survey data. Based on these analyses, proper EMI survey designs and data processing are proposed.

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments.

PubMed

Krami, Loghman Khoda; Amiri, Fazel; Sefiyanian, Alireza; Shariff, Abdul Rashid B Mohamed; Tabatabaie, Tayebeh; Pradhan, Biswajeet

2013-12-01

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF(G)) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF(G) techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF(G) technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.

Characterization of anthropogenic impacts in a large urban center by examining the spatial distribution of halogenated flame retardants.

PubMed

Wei, Yan-Li; Bao, Lian-Jun; Wu, Chen-Chou; Zeng, Eddy Y

2016-08-01

Anthropogenic impacts have continuously intensified in mega urban centers with increasing urbanization and growing population. The spatial distribution pattern of such impacts can be assessed with soil halogenated flame retardants (HFRs) as HFRs are mostly derived from the production and use of various consumer products. In the present study, soil samples were collected from the Pearl River Delta (PRD), a large urbanized region in southern China, and its surrounding areas and analyzed for a group of HFRs, i.e., polybrominated diphenyl ethers (PBDEs), decabromodiphenyl ethane, bis(hexachlorocyclopentadieno)cyclooctane (DP) and hexabromobenzene. The sum concentrations of HFRs and PBDEs were in the ranges of 0.66-6500 and 0.37-5700 (mean: 290 and 250) ng g(-1) dry weight, respectively, around the middle level of the global range. BDE-209 was the predominant compound likely due to the huge amounts of usage and its persistence. The concentrations of HFRs were greater in the land-use types of residency, industry and landfill than in agriculture, forestry and drinking water source, and were also greater in the central PRD than in its surrounding areas. The concentrations of HFRs were moderately significantly (r(2) = 0.32-0.57; p < 0.05) correlated with urbanization levels, population densities and gross domestic productions in fifteen administrative districts. The spatial distribution of DP isomers appeared to be stereoselective as indicated by the similarity in the spatial patterns for the ratio of anti-DP versus the sum of DP isomers (fanti-DP) and DP concentrations. Finally, the concentrations of HFRs sharply decreased with increasing distance from an e-waste recycling site, indicating that e-waste derived HFRs largely remained in local soil. Copyright © 2016 Elsevier Ltd. All rights reserved.

Land cover heterogeneity and soil respiration in a west Greenland tundra landscape

NASA Astrophysics Data System (ADS)

Bradley-Cook, J. I.; Burzynski, A.; Hammond, C. R.; Virginia, R. A.

2011-12-01

Multiple direct and indirect pathways underlie the association between land cover classification, temperature and soil respiration. Temperature is a main control of the biological processes that constitute soil respiration, yet the effect of changing atmospheric temperatures on soil carbon flux is unresolved. This study examines associations amongst land cover, soil carbon characteristics, soil respiration, and temperature in an Arctic tundra landscape in western Greenland. We used a 1.34 meter resolution multi-spectral WorldView2 satellite image to conduct an unsupervised multi-staged ISODATA classification to characterize land cover heterogeneity. The four band image was taken on July 10th, 2010, and captures an 18 km by 15 km area in the vicinity of Kangerlussuaq. The four major terrestrial land cover classes identified were: shrub-dominated, graminoid-dominated, mixed vegetation, and bare soil. The bare soil class was comprised of patches where surface soil has been deflated by wind and ridge-top fellfield. We hypothesize that soil respiration and soil carbon storage are associated with land cover classification and temperature. We set up a hierarchical field sampling design to directly observe spatial variation between and within land cover classes along a 20 km temperature gradient extending west from Russell Glacier on the margin of the Greenland Ice Sheet. We used the land cover classification map and ground verification to select nine sites, each containing patches of the four land cover classes. Within each patch we collected soil samples from a 50 cm pit, quantified vegetation, measured active layer depth and determined landscape characteristics. From a subset of field sites we collected additional 10 cm surface soil samples to estimate soil heterogeneity within patches and measured soil respiration using a LiCor 8100 Infrared Gas Analyzer. Soil respiration rates varied with land cover classes, with values ranging from 0.2 mg C/m^2/hr in the bare soil class to over 5 mg C/m^2/hr in the graminoid-dominated class. These findings suggest that shifts in land cover vegetation types, especially soil and vegetation loss (e.g. from wind deflation), can alter landscape soil respiration. We relate soil respiration measurements to soil, vegetation, and permafrost characteristics to understand how ecosystem properties and processes vary at the landscape scale. A long-term goal of this research is to develop a spatially explicit model of soil organic matter, soil respiration, and temperature sensitivity of soil carbon dynamics for a western Greenland permafrost tundra ecosystems.

Strategies Influencing Spatial Heterogeneity of Microbial Life in a Soil Lysimeter

NASA Astrophysics Data System (ADS)

Sengupta, A.; Neilson, J. W.; Meira, A.; Wang, Y.; Meza, M.; Chorover, J.; Maier, R. M.; Troch, P. A. A.

2016-12-01

Soil microorganisms are critical drivers of biogeochemical processes. These microbes, in conjunction with their physical and chemical environment, contribute to ecosystem functioning and services of the landscape, have a profound impact on soil formation, and are of particular importance in oligotrophic environments; ecosystems that are characterized by low biotic diversity due to extremely low nutrient levels. Here, we present a study of microbial heterogeneity in a soil lysimeter under incipient conditions. The key questions asked were: 1) what is the spatial heterogeneity of microbes over a new and evolving landscape with inherent oligotrophic conditions, and 2) can patterns in diversity translate to patterns in microbe-mediated weathering processes and soil formation? We hypothesized that stratification of environmental conditions, brought about by varying water potential, flow paths, and redox conditions, will drive the heterogeneity of microbial life in a sub-meter scale. A suite of traditional and current microbiological tools were employed to study community characteristics. These included isolation on R2A media, quantitative polymerase chain reactions targeted at 16S rRNA bacterial and archaeal genes, and 18S fungal genes, and iTAG phylogenetic gene amplification. Illumina Mi-Seq platform generated sequences were analyzed using various bioinformatics pipelines to identify community patterns, classify microbial metabolic functions, and identify variables affecting the community dynamics. Numerous phyla (Verrucomicrobia, Actinobacteria, Planctomycetes, Proteobacteria, and Euryarchaeota) were identified. The surface layer had distinctly different distribution of communities compared to the other layers. Metabolically heterogeneous groups were found with respect to depth, with metabolic functions further confirmed by predictive functional profiling of the microbial communities. Therefore, despite being highly oligotrophic, the system was rich in species and functional diversity. Alongside physical and chemical data, the patterns observed in spatial and functional heterogeneity of microbes under incipient conditions is unique, and allows us to predict strategies undertaken by these microbes to survive in, and influence their oligotrophic environments.

Acoustic Determination of Near-Surface Soil Properties

DTIC Science & Technology

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

Distributions of ectomycorrhizal and foliar endophytic fungal communities associated with Pinus ponderosa along a spatially constrained elevation gradient.

PubMed

Bowman, Elizabeth A; Arnold, A Elizabeth

2018-04-01

Understanding distributions of plant-symbiotic fungi is important for projecting responses to environmental change. Many coniferous trees host ectomycorrhizal fungi (EM) in association with roots and foliar endophytic fungi (FE) in leaves. We examined how EM and FE associated with Pinus ponderosa each vary in abundance, diversity, and community structure over a spatially constrained elevation gradient that traverses four plant communities, 4°C in mean annual temperature, and 15 cm in mean annual precipitation. We sampled 63 individuals of Pinus ponderosa in 10 sites along a 635 m elevation gradient that encompassed a geographic distance of 9.8 km. We used standard methods to characterize each fungal group (amplified and sequenced EM from root tips; isolated and sequenced FE from leaves). Abundance and diversity of EM were similar across sites, but community composition and distributions of the most common EM differed with elevation (i.e., with climate, soil chemistry, and plant communities). Abundance and composition of FE did not differ with elevation, but diversity peaked in mid-to-high elevations. Our results suggest relatively tight linkages between EM and climate, soil chemistry, and plant communities. That FE appear less linked with these factors may speak to limitations of a culture-based approach, but more likely reflects the small spatial scale encompassed by our study. Future work should consider comparable methods for characterizing these functional groups, and additional transects to understand relationships of EM and FE to environmental factors that are likely to shift as a function of climate change. © 2018 Botanical Society of America.

Analysis of Factors Influencing Soil Salinity, Acidity, and Arsenic Concentration in a Polder in Southwest Bangladesh

NASA Astrophysics Data System (ADS)

Ayers, J. C.; Patton, B.; Fry, D. C.; Goodbred, S. L., Jr.

2017-12-01

Soil samples were collected on Polder 32 in the coastal zone of SW Bangladesh in wet (October) and dry (May) seasons from 2013-2017 and analyzed to characterize the problems of soil salinization and arsenic contamination and identify their causes. Soils are entisols formed from recently deposited, predominantly silt-sized sediments with low carbon concentrations typical of the local mangrove forests. Soluble (DI extract) arsenic concentrations were below the Government of Bangladesh limit of 50 ppb for drinking water. Soil acidity and extract arsenic concentrations exhibit spatial variation but no consistent trends. In October soil extract As is higher and S and pH are lower than in May. These observations suggest that wet season rainwater oxidizes pyrite, reducing soil S and releasing H+, causing pH to decrease. Released iron is oxidized to form Hydrous Ferric Oxyhydroxides (HFOs), which sorb As and increase extractable As in wet season soils. Changes in pH are small due to pH buffering by soil carbonates. Soil and rice paddy water salinities are consistently higher in May than October, reaching levels in May that reduce rice yields. Rice grown in paddies should be unaffected by salt concentrations in the wet season, while arsenic concentrations in soil may be high enough to cause unsafe As levels in produced rice.

A spatial approach to environmental risk assessment of PAH contamination.

PubMed

Bengtsson, Göran; Törneman, Niklas

2009-01-01

The extent of remediation of contaminated industrial sites depends on spatial heterogeneity of contaminant concentration and spatially explicit risk characterization. We used sequential Gaussian simulation (SGS) and indicator kriging (IK) to describe the spatial distribution of polycyclic aromatic hydrocarbons (PAHs), pH, electric conductivity, particle aggregate distribution, water holding capacity, and total organic carbon, and quantitative relations among them, in a creosote polluted soil in southern Sweden. The geostatistical analyses were combined with risk analyses, in which the total toxic equivalent concentration of the PAH mixture was calculated from the soil concentrations of individual PAHs and compared with ecotoxicological effect concentrations and regulatory threshold values in block sizes of 1.8 x 1.8 m. Most PAHs were spatially autocorrelated and appeared in several hot spots. The risk calculated by SGS was more confined to specific hot spot areas than the risk calculated by IK, and 40-50% of the site had PAH concentrations exceeding the threshold values with a probability of 80% and higher. The toxic equivalent concentration of the PAH mixture was dependent on the spatial distribution of organic carbon, showing the importance of assessing risk by a combination of measurements of PAH and organic carbon concentrations. Essentially, the same risk distribution pattern was maintained when Monte Carlo simulations were used for implementation of risk in larger (5 x 5 m), economically more feasible remediation blocks, but a smaller area became of great concern for remediation when the simulations included PAH partitioning to two separate sources, creosote and natural, of organic matter, rather than one general.

Spatial distribution of grape root borer (Lepidoptera: Sesiidae) infestations in Virginia vineyards and implications for sampling.

PubMed

Rijal, J P; Brewster, C C; Bergh, J C

2014-06-01

Grape root borer, Vitacea polistiformis (Harris) (Lepidoptera: Sesiidae) is a potentially destructive pest of grape vines, Vitis spp. in the eastern United States. After feeding on grape roots for ≍2 yr in Virginia, larvae pupate beneath the soil surface around the vine base. Adults emerge during July and August, leaving empty pupal exuviae on or protruding from the soil. Weekly collections of pupal exuviae from an ≍1-m-diameter weed-free zone around the base of a grid of sample vines in Virginia vineyards were conducted in July and August, 2008-2012, and their distribution was characterized using both nonspatial (dispersion) and spatial techniques. Taylor's power law showed a significant aggregation of pupal exuviae, based on data from 19 vineyard blocks. Combined use of geostatistical and Spatial Analysis by Distance IndicEs methods indicated evidence of an aggregated pupal exuviae distribution pattern in seven of the nine blocks used for those analyses. Grape root borer pupal exuviae exhibited spatial dependency within a mean distance of 8.8 m, based on the range values of best-fitted variograms. Interpolated and clustering index-based infestation distribution maps were developed to show the spatial pattern of the insect within the vineyard blocks. The temporal distribution of pupal exuviae showed that the majority of moths emerged during the 3-wk period spanning the third week of July and the first week of August. The spatial distribution of grape root borer pupal exuviae was used in combination with temporal moth emergence patterns to develop a quantitative and efficient sampling scheme to assess infestations.

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.

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.

Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees

NASA Astrophysics Data System (ADS)

Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung

2017-04-01

Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.

Proposal for a Spatial Organization Model in Soil Science (The Example of the European Communities Soil Map).

ERIC Educational Resources Information Center

King, D.; And Others

1994-01-01

Discusses the computational problems of automating paper-based spatial information. A new relational structure for soil science information based on the main conceptual concepts used during conventional cartographic work is proposed. This model is a computerized framework for coherent description of the geographical variability of soils, combined…

Assessing heterogeneity in soil nitrogen cycling: a plot-scale approach

Treesearch

Peter Baas; Jacqueline E. Mohan; David Markewitz; Jennifer D. Knoepp

2014-01-01

The high level of spatial and temporal heterogeneity in soil N cycling processes hinders our ability to develop an ecosystem-wide understanding of this cycle. This study examined how incorporating an intensive assessment of spatial variability for soil moisture, C, nutrients, and soil texture can better explain ecosystem N cycling at the plot scale. Five sites...

Spatial Variability of Grapevine Bud Burst Percentage and Its Association with Soil Properties at Field Scale

PubMed Central

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

Soil cover patterns and dynamics impact on GHG fluxes in RF native and man-changed ecosystems

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Nesterova, Olga

2017-04-01

The increased soil spatial-temporal variability is mutual feature for most mature natural and particularly man-changed terrestrial ecosystems in Central and Far-East regions of Russia with soil cover strongly pronounced bioclimatic zoning and landscape-geomorphologic differentiation. Soil cover patterns (SCP) detailed morphogenetic analysis and typification is useful tool for soil forming and degradation processes quantitative evaluation, land ecological state and functional quality quantitative assessment. Quantitative analysis and functional-ecological interpretation of representative SCP spatial variability is especially important for environmentally friendly and demand-driven land-use planning and decision making. The carried out 33-years region- and local-scale researches of the wide zonal-provincial set of representative ecosystems and SCP with different types and history of land-use (forest, meadow-steppe, agricultural and recreational ones) give us the interregional multi-factorial matrix of elementary soil cover patterns (ESCP) with different land-use practices and history, soil-geomorphologic features, environmental and microclimate conditions. Succession process-based analysis of modern evolution of man-changed and natural soils and ESCP essentially increases accuracy of quantitative assessments of dominant soil forming and degradation processes rate and potential, their influence on land and soil cover quality and ecosystem services. Their results allow developing the regional and landscape adapted versions of automated land evaluation systems and land-use DSS. The validation and ranging of the limiting factors of ESCP regulation and develop¬ment, ecosystem principal services (with especial attention on greenhouse gases emissions, soil carbon dynamics and sequestration potential, biodiversity and productivity, hydrological regimes and geomorphologic stabilization), land functional qualities and agroecological state have been done for dominating and most dynamical components of ESCP regional-typological forms - with application of regional/local GIS, ESCP mapping, kriging, correlation tree models and adapted to region DSS. Key-site monitoring results and regional generalized data showed 1-1.5 % Corg lost during last 50 years period, active processes of CO2, CH4 and N2O emission (2-4-time variability in frame of one farm and of one vegetation season) and humus redistribution throw soil profile and soil cover patterns. Forest-steppe Chernozem ecosystems are usually characterized by more stable SCP than forest or steppe ones. The ratio between erosive and biological losses in humus supplies is estimated as fifty-fifty with strong spatial varia¬bility due to slope and land-use parameters. These problem agroecological situations can be essentially improved by climate-smart agriculture practice development with DSS-based landscape-adaptive land-use systems and organic farming stimulation with environmentally friendly technologies, adapted to conditions of concrete agrolandscapes in Central and Far-East Russia.

Forest soil chemistry and terrain attributes in a Catskills watershed

USGS Publications Warehouse

Johnson, C.E.; Ruiz-Mendez, J. J.; Lawrence, G.B.

2000-01-01

Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pH(w), effective cation-exchange capacity (CEC(e)), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pH(w) together explained 33 to 66% of the variation in exchangeable bases and CEC(e). Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CEC(e) (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CEC(e) occupied by H explained 44% of the variation in pH(w). Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pHw, effective cation-exchange capacity (CECe), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pHw together explained 33 to 66% of the variation in exchangeable bases and CECe. Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CECe (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CECe occupied by H explained 44% of the variation in pHw. Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.

Demonstration to characterize watershed runoff potential by microwave techniques

NASA Technical Reports Server (NTRS)

Blanchard, B. J.

1977-01-01

Characteristics such as storage capacity of the soil, volume of storage in vegetative matter, and volume of storage available in local depressions are expressed in empirical watershed runoff equations as one or more coefficients. Conventional techniques for estimating coefficients representing the spatial distribution of these characteristics over a watershed drainage area are subjective and produce significant errors. Characteristics of the wear surface are described as a single coefficient called the curve number.

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

Spatial interpolation quality assessments for soil sensor transect datasets

USDA-ARS?s Scientific Manuscript database

Near-ground geophysical soil sensors provide extremely valuable information for precision agriculture applications. Indeed, their readings can be used as proxy for many soil parameters. Typically, leave-one-out (loo) cross-validation (CV) of spatial interpolation of sensor data returns overly optimi...

Temporal and spatial variation of groundwater in quantity and quality in sand dune at coastal region, Kamisu city, central Japan.

NASA Astrophysics Data System (ADS)

Umei, Yohei; Tsujimura, Maki; Sakakibara, Koichi; Watanabe, Yasuto; Minema, Motomitsu

2016-04-01

The role of groundwater in integrated water management has become important in recent 10 years, though the surface water is the major source of drinking water in Japan. Especially, it is remarked that groundwater recharge changed due to land cover change under the anthropogenic and climatic condition factors. Therefore, we need to investigate temporal and spatial variation of groundwater in quantity and quality focusing on the change during recent 10-20 years in specific region. We performed research on groundwater level and quality in sand dune at coastal region facing Pacific Ocean, Kamisu city, Ibaraki Prefecture, which have been facing environmental issues, such as land cover change due to soil mining for construction and urbanization. We compared the present situation of groundwater with that in 2000 using existed data to clarify the change of groundwater from 2000 to 2015. The quality of water is dominantly characterized by Ca2+-HCO3- in both 2000 and 2015, and nitrate was not observed in 2015, though it was detected in some locations in 2000. This may be caused by improvement of the domestic wastewater treatment. The topography of groundwater table was in parallel with that of ground surface in 2015, same as that in 2000. However, a depletion of groundwater table was observed in higher elevation area in 2015 as compared with that in 2000, and this area corresponds to the locations where the land cover has changed due to soil mining and urbanization between 2015 and 2000. In the region of soil mining, the original soil is generally replaced by impermeable soil after mining, and this may cause a decrease of percolation and net groundwater recharge, thus the depletion of groundwater table occurred after the soil mining.

BOREAS TGB-5 Biogenic Soil Emissions of NO and N2O

NASA Technical Reports Server (NTRS)

Levine, J. S.; Winstead, E. L.; Parsons, D. A. B.; Scholes, M. C.; Cofer, W. R.; Cahoon, D. R.; Sebacher, D. I.; Scholes, R. J.; Hall, Forrest G. (Editor); Conrad, Sara K. (Editor)

2000-01-01

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB)-5 team made several measurements of trace gas concentrations and fluxes at various NSA sites. This data set contains biogenic soil emissions of nitric oxide and nitrous oxide that were measured over a wide range of spatial and temporal site parameters. Since very little is known about biogenic soil emissions of nitric oxide and nitrous oxide from the boreal forest, the goal of the measurements was to characterize the biogenic soil fluxes of nitric oxide and nitrous oxide from black spruce and jack pine areas in the boreal forest. The diurnal variation and monthly variation of the emissions was examined as well as the impact of wetting through natural or artificial means. Temporally, the data cover mid-August 1993, June to August 1994, and mid-July 1995. The data are provided in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884).

Characteristics of organic soil in black spruce forests: Implications for the application of land surface and ecosystem models in cold regions

USGS Publications Warehouse

Yi, S.; Manies, K.; Harden, J.; McGuire, A.D.

2009-01-01

Soil organic layers (OL) play an important role in landatmosphere exchanges of water, energy and carbon in cold environments. The proper implementation of OL in land surface and ecosystem models is important for predicting dynamic responses to climate warming. Based on the analysis of OL samples of black spruce (Picea mariana), we recommend that implementation of OL for cold regions modeling: (1) use three general organic horizon types (live, fibrous, and amorphous) to represent vertical soil heterogeneity; (2) implement dynamics of OL over the course of disturbance, as there are significant differences of OL thickness between young and mature stands; and (3) use two broad drainage classes to characterize spatial heterogeneity, as there are significant differences in OL thickness between dry and wet sites. Implementation of these suggestions into models has the potential to substantially improve how OL dynamics influence variability in surface temperature and soil moisture in cold regions. Copyright 2009 by the American Geophys.ical Union.

High fragility of the soil organic C pools in mangrove forests.

PubMed

Otero, X L; Méndez, A; Nóbrega, G N; Ferreira, T O; Santiso-Taboada, M J; Meléndez, W; Macías, F

2017-06-15

Mangrove forests play an important role in biogeochemical cycle of C, storing large amounts of organic carbon. However, these functions can be controlled by the high spatial heterogeneity of these intertidal environments. In this study were performed an intensive sampling characterizing mangrove soils under different type of vegetation (Rhizophora/Avicennia/dead mangrove) in the Venezuelan coast. The soils were anoxic, with a pH~7; however other soil parameters varied widely (e.g., clay, organic carbon). Dead mangrove area showed a significant lower amounts of total organic carbon (TOC) (6.8±2.2%), in comparison to the well-preserved mangrove of Avicennia or Rhizophora (TOC=17-20%). Our results indicate that 56% of the TOC was lost within a period of 10years and we estimate that 11,219kgm -2 of CO 2 was emitted as a result of the mangrove death. These results represent an average emission rate of 11.2±19.17tCO 2 ha -1 y -1 . Copyright © 2017 Elsevier Ltd. All rights reserved.

Highly spatially- and seasonally-resolved predictive contamination maps for persistent organic pollutants: development and validation.

PubMed

Ballabio, Cristiano; Guazzoni, Niccoló; Comolli, Roberto; Tremolada, Paolo

2013-08-01

A reliable spatial assessment of the POPs contamination in soils is essential for burden studies and flux evaluations. Soil characteristics and properties vary enormously even within small spatial scale and over time; therefore soil capacity of accumulating POPs varies greatly. In order to include this very high spatial and temporal variability, models can be used for assessing soil accumulation capacity in a specific time and space and, from it, the spatial distribution and temporal trends of POPs concentrations. In this work, predictive contamination maps of the accumulation capacity of soils were developed at a space resolution of 1×1m with a time frame of one day, in a study area located in the central Alps. Physical algorithms for temperature and organic carbon estimation along the soil profile and across the year were fitted to estimate the horizontal, vertical and seasonal distribution of the contamination potential for PCBs in soil (Ksa maps). The resulting maps were cross-validated with an independent set of PCB contamination data, showing very good agreement (e.g. for CB-153, R(2)=0.80, p-value≤2.2·10(-06)). Slopes of the regression between predicted Ksa and experimental concentrations were used to map the soil contamination for the whole area, taking into account soil characteristics and temperature conditions. These maps offer the opportunity to evaluate burden (concentration maps) and fluxes (emission maps) with highly resolved temporal and spatial detail. In addition, in order to explain the observed low autumn PCB concentrations in soil related to the high Ksa values of this period, a dynamic model of seasonal variation of soil concentrations was developed basing on rate parameters fitted on measured concentrations. The model was able to describe, at least partially, the observed different behavior between the quite rapid discharge phase in summer and the slow recharge phase in autumn. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques.

PubMed

Chen, Tao; Niu, Rui-qing; Wang, Yi; Li, Ping-xiang; Zhang, Liang-pei; Du, Bo

2011-08-01

Soil conservation planning often requires estimates of the spatial distribution of soil erosion at a catchment or regional scale. This paper applied the Revised Universal Soil Loss Equation (RUSLE) to investigate the spatial distribution of annual soil loss over the upper basin of Miyun reservoir in China. Among the soil erosion factors, which are rainfall erosivity (R), soil erodibility (K), slope length (L), slope steepness (S), vegetation cover (C), and support practice factor (P), the vegetative cover or C factor, which represents the effects of vegetation canopy and ground covers in reducing soil loss, has been one of the most difficult to estimate over broad geographic areas. In this paper, the C factor was estimated based on back propagation neural network and the results were compared with the values measured in the field. The correlation coefficient (r) obtained was 0.929. Then the C factor and the other factors were used as the input to RUSLE model. By integrating the six factor maps in geographical information system (GIS) through pixel-based computing, the spatial distribution of soil loss over the upper basin of Miyun reservoir was obtained. The results showed that the annual average soil loss for the upper basin of Miyun reservoir was 9.86 t ha(-1) ya(-1) in 2005, and the area of 46.61 km(2) (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.9% very low, 21.89% low, 6.18% moderate, 2.89% severe, and 1.84% very severe. Thus, by using RUSLE in a GIS environment, the spatial distribution of water erosion can be obtained and the regions which susceptible to water erosion and need immediate soil conservation planning and application over the upper watershed of Miyun reservoir in China can be identified.

Soil erosion and sediment yield and their relationships with vegetation cover in upper stream of the Yellow River.

PubMed

Ouyang, Wei; Hao, Fanghua; Skidmore, Andrew K; Toxopeus, A G

2010-12-15

Soil erosion is a significant concern when considering regional environmental protection, especially in the Yellow River Basin in China. This study evaluated the temporal-spatial interaction of land cover status with soil erosion characteristics in the Longliu Catchment of China, using the Soil and Water Assessment Tool (SWAT) model. SWAT is a physical hydrological model which uses the RUSLE equation as a sediment algorithm. Considering the spatial and temporal scale of the relationship between soil erosion and sediment yield, simulations were undertaken at monthly and annual temporal scales and basin and sub-basin spatial scales. The corresponding temporal and spatial Normalized Difference Vegetation Index (NDVI) information was summarized from MODIS data, which can integrate regional land cover and climatic features. The SWAT simulation revealed that the annual soil erosion and sediment yield showed similar spatial distribution patterns, but the monthly variation fluctuated significantly. The monthly basin soil erosion varied from almost no erosion load to 3.92 t/ha and the maximum monthly sediment yield was 47,540 tones. The inter-annual simulation focused on the spatial difference and relationship with the corresponding vegetation NDVI value for every sub-basin. It is concluded that, for this continental monsoon climate basin, the higher NDVI vegetation zones prevented sediment transport, but at the same time they also contributed considerable soil erosion. The monthly basin soil erosion and sediment yield both correlated with NDVI, and the determination coefficients of their exponential correlation model were 0.446 and 0.426, respectively. The relationships between soil erosion and sediment yield with vegetation NDVI indicated that the vegetation status has a significant impact on sediment formation and transport. The findings can be used to develop soil erosion conservation programs for the study area. Copyright © 2010 Elsevier B.V. All rights reserved.

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Spatial heterogeneity distribution of soil total nitrogen and total phosphorus in the Yaoxiang watershed in a hilly area of northern China based on geographic information system and geostatistics.

PubMed

Liu, Yu; Gao, Peng; Zhang, Liyong; Niu, Xiang; Wang, Bing

2016-10-01

Soil total nitrogen (STN) and total phosphorus (STP) are important indicators of soil nutrients and the important indexes of soil fertility and soil quality evaluation. Using geographic information system (GIS) and geostatistics, the spatial heterogeneity distribution of STN and STP in the Yaoxiang watershed in a hilly area of northern China was studied. The results showed that: (1) The STN and STP contents showed a declining trend with the increase in soil depth; the variation coefficients ( C v ) of STN and STP in the 0- to 10-cm soil layer (42.25% and 14.77%, respectively) were higher than in the 10- to 30-cm soil layer (28.77% and 11.60%, respectively). Moreover, the C v of STN was higher than that of STP. (2) The maximum C 0 /( C 0  +  C 1 ) of STN and STP in the soil layers was less than 25%, this indicated that a strong spatial distribution autocorrelation existed for STN and STP; and the STP showed higher intensity and more stable variation than the STN. (3) From the correlation analysis, we concluded that the topographic indexes such as elevation and slope direction all influenced the spatial distribution of STN and STP (correlation coefficients were 0.688 and 0.518, respectively). (4) The overall distribution of STN and STP in the Yaoxiang watershed decreased from the northwest to the southeast. This variation trend was similar to the watershed DEM trend and was significantly influenced by vegetation and topographic factors. These results revealed the spatial heterogeneity distribution of STN and STP, and addressed the influences of forest vegetation coverage, elevation, and other topographic factors on the spatial distribution of STN and STP at the watershed scale.

Archaeal ammonia oxidizers respond to soil factors at smaller spatial scales than the overall archaeal community does in a high Arctic polar oasis.

PubMed

Banerjee, Samiran; Kennedy, Nabla; Richardson, Alan E; Egger, Keith N; Siciliano, Steven D

2016-06-01

Archaea are ubiquitous and highly abundant in Arctic soils. Because of their oligotrophic nature, archaea play an important role in biogeochemical processes in nutrient-limited Arctic soils. With the existing knowledge of high archaeal abundance and functional potential in Arctic soils, this study employed terminal restriction fragment length polymorphism (t-RFLP) profiling and geostatistical analysis to explore spatial dependency and edaphic determinants of the overall archaeal (ARC) and ammonia-oxidizing archaeal (AOA) communities in a high Arctic polar oasis soil. ARC communities were spatially dependent at the 2-5 m scale (P < 0.05), whereas AOA communities were dependent at the ∼1 m scale (P < 0.0001). Soil moisture, pH, and total carbon content were key edaphic factors driving both the ARC and AOA community structure. However, AOA evenness had simultaneous correlations with dissolved organic nitrogen and mineral nitrogen, indicating a possible niche differentiation for AOA in which dry mineral and wet organic soil microsites support different AOA genotypes. Richness, evenness, and diversity indices of both ARC and AOA communities showed high spatial dependency along the landscape and resembled scaling of edaphic factors. The spatial link between archaeal community structure and soil resources found in this study has implications for predictive understanding of archaea-driven processes in polar oases.

[Spatial variability of surface soil nutrients in the landslide area of Beichuan County, South- west China, after 5 · 12 Wenchuan Earthquake].

PubMed

Mai, Ji-shan; Zhao, Ting-ning; Zheng, Jiang-kun; Shi, Chang-qing

2015-12-01

Based on grid sampling and laboratory analysis, spatial variability of surface soil nutrients was analyzed with GS⁺ and other statistics methods on the landslide area of Fenghuang Mountain, Leigu Town, Beichuan County. The results showed that except for high variability of available phosphorus, other soil nutrients exhibited moderate variability. The ratios of nugget to sill of the soil available phosphorus and soil organic carbon were 27.9% and 28.8%, respectively, showing moderate spatial correlation, while the ratios of nugget to sill of the total nitrogen (20.0%), total phosphorus (24.3%), total potassium (11.1%), available nitrogen (11.2%), and available potassium (22.7%) suggested strong spatial correlation. The total phosphorus had the maximum range (1232.7 m), followed by available nitrogen (541.27 m), total nitrogen (468.35 m), total potassium (136.0 m), available potassium (128.7 m), available phosphorus (116.6 m), and soil organic carbon (93.5 m). Soil nutrients had no significant variation with the increase of altitude, but gradually increased from the landslide area, the transition area, to the little-impacted area. The total and available phosphorus contents of the landslide area decreased by 10.3% and 79.7% compared to that of the little-impacted area, respectively. The soil nutrient contents in the transition area accounted for 31.1%-87.2% of that of the little-impacted area, with the nant reason for the spatial variability of surface soil nutrients.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harden, Jennifer W.; Hugelius, Gustaf; Ahlstrom, Anders

Here, soil organic matter supports the Earth’s ability to sustain terrestrial ecosystems, provide food and fiber, and retain the largest pool of actively cycling carbon (C). Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance land productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerablemore » to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well-established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of soil organic matter and C and their management for sustained production and climate regulation.« less

Impact of biological soil crusts and desert plants on soil microfaunal community composition

USGS Publications Warehouse

Darby, B.J.; Neher, D.A.; Belnap, J.

2010-01-01

Carbon and nitrogen are supplied by a variety of sources in the desert food web; both vascular and non-vascular plants and cyanobacteria supply carbon, and cyanobacteria and plant-associated rhizosphere bacteria are sources of biological nitrogen fixation. The objective of this study was to compare the relative influence of vascular plants and biological soil crusts on desert soil nematode and protozoan abundance and community composition. In the first experiment, biological soil crusts were removed by physical trampling. Treatments with crust removed had fewer nematodes and a greater relative ratio of bacterivores to microphytophages than treatments with intact crust. However, protozoa composition was similar with or without the presence of crusts. In a second experiment, nematode community composition was characterized along a spatial gradient away from stems of grasses or shrubs. Although nematodes generally occurred in increasing abundance nearer to plant stems, some genera (such as the enrichment-type Panagrolaimus) increased disproportionately more than others (such as the stress-tolerant Acromoldavicus). We propose that the impact of biological soil crusts and desert plants on soil microfauna, as reflected in the community composition of microbivorous nematodes, is a combination of carbon input, microclimate amelioration, and altered soil hydrology. ?? Springer Science + Business Media B.V. 2009.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

DOE PAGES

Harden, Jennifer W.; Hugelius, Gustaf; Ahlstrom, Anders; ...

2017-10-05

Here, soil organic matter supports the Earth’s ability to sustain terrestrial ecosystems, provide food and fiber, and retain the largest pool of actively cycling carbon (C). Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance land productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerablemore » to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well-established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of soil organic matter and C and their management for sustained production and climate regulation.« less

Induced polarization for characterizing and monitoring soil stabilization processes

NASA Astrophysics Data System (ADS)

Saneiyan, S.; Ntarlagiannis, D.; Werkema, D. D., Jr.

2017-12-01

Soil stabilization is critical in addressing engineering problems related to building foundation support, road construction and soil erosion among others. To increase soil strength, the stiffness of the soil is enhanced through injection/precipitation of a chemical agents or minerals. Methods such as cement injection and microbial induced carbonate precipitation (MICP) are commonly applied. Verification of a successful soil stabilization project is often challenging as treatment areas are spatially extensive and invasive sampling is expensive, time consuming and limited to sporadic points at discrete times. The geophysical method, complex conductivity (CC), is sensitive to mineral surface properties, hence a promising method to monitor soil stabilization projects. Previous laboratory work has established the sensitivity of CC on MICP processes. We performed a MICP soil stabilization projects and collected CC data for the duration of the treatment (15 days). Subsurface images show small, but very clear changes, in the area of MICP treatment; the changes observed fully agree with the bio-geochemical monitoring, and previous laboratory experiments. Our results strongly suggest that CC is sensitive to field MICP treatments. Finally, our results show that good quality data alone are not adequate for the correct interpretation of field CC data, at least when the signals are low. Informed data processing routines and the inverse modeling parameters are required to produce optimal results.

[Spatial variation of soil phosphorus in flooded area of the Yellow River based on GIS and geo-statistical methods: A case study in Zhoukou City, Henan, China.

PubMed

Jia, Zhen Yu; Zhang, Jun Hua; Ding, Sheng Yan; Feng, Shu; Xiong, Xiao Bo; Liang, Guo Fu

2016-04-22

Soil phosphorus is an important indicator to measure the soil fertility, because the content of soil phosphorus has an important effect on physical and chemical properties of soil, plant growth, and microbial activity in soil. In this study, the soil samples collecting and indoor analysis were conducted in Zhoukou City located in the flooded area of the Yellow River. By using GIS combined with geo-statistics, we tried to analyze the spatial variability and content distribution of soil total phosphorus (TP) and soil available phosphorus (AP) in the study area. Results showed that TP and AP of both soil layers (0-20 cm and 20-40 cm) were rich, and the contents of TP and AP in surface layer (0-20 cm) were higher than in the second layer (20-40 cm). TP and AP of both soil layers exhibited variation at medium level, and AP had varied much higher than TP. TP of both layers showed medium degree of anisotropy which could be well modeled by the Gaussian model. TP in the surface layer showed strong spatial correlation, but that of the second layer had medium spatial correlation. AP of both layers had a weaker scope in anisotropy which could be simulated by linear model, and both soil layers showed weaker spatial correlations. TP of both soil layers showed a slowly rising change from southwest to northeast of the study area, while it gradually declined from northwest to southeast. AP in soil surface layer exhibited an increase tendency firstly and then decrease from southwest to the northeast, while it decreased firstly and then increased from southeast to the northwest. AP in the second soil layer had an opposite change in the southwest to the northeast, while it showed continuously increasing tendency from northwest to the southeast. The contents of TP and AP in the surface layer presented high grades and the second layer of TP belonged to medium grade, but the second layer of AP was in a lower grade. The artificial factors such as land use type, cropping system, irrigation and fertilization were the main factors influencing the distribution and spatial variation of soil phosphorus in this area.

Fine-scale spatial distribution of orchid mycorrhizal fungi in the soil of host-rich grasslands.

PubMed

Voyron, Samuele; Ercole, Enrico; Ghignone, Stefano; Perotto, Silvia; Girlanda, Mariangela

2017-02-01

Mycorrhizal fungi are essential for the survival of orchid seedlings under natural conditions. The distribution of these fungi in soil can constrain the establishment and resulting spatial arrangement of orchids at the local scale, but the actual extent of occurrence and spatial patterns of orchid mycorrhizal (OrM) fungi in soil remain largely unknown. We addressed the fine-scale spatial distribution of OrM fungi in two orchid-rich Mediterranean grasslands by means of high-throughput sequencing of fungal ITS2 amplicons, obtained from soil samples collected either directly beneath or at a distance from adult Anacamptis morio and Ophrys sphegodes plants. Like ectomycorrhizal and arbuscular mycobionts, OrM fungi (tulasnelloid, ceratobasidioid, sebacinoid and pezizoid fungi) exhibited significant horizontal spatial autocorrelation in soil. However, OrM fungal read numbers did not correlate with distance from adult orchid plants, and several of these fungi were extremely sporadic or undetected even in the soil samples containing the orchid roots. Orchid mycorrhizal 'rhizoctonias' are commonly regarded as unspecialized saprotrophs. The sporadic occurrence of mycobionts of grassland orchids in host-rich stands questions the view of these mycorrhizal fungi as capable of sustained growth in soil. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.

Terrain and subsurface influences on runoff generation in a steep, deep, highly weathered system

NASA Astrophysics Data System (ADS)

Mallard, J. M.; McGlynn, B. L.; Richter, D. D., Jr.

2017-12-01

Our understanding of runoff generation in regions characterized by deep, highly weathered soils is incomplete, despite the prevalence occupation of these landscapes worldwide. To address this, we instrumented a first-order watershed in the Piedmont of South Carolina, USA, a region that extends east of the Appalachians from Maryland to Alabama, and home to some of the most rapid population growth in the country. Although regionally the relief is modest, the landscape is often highly dissected and local slopes can be steep and highly varied. The typical soils of the region are kaolinite dominated ultisols, with hydrologic properties controlled by argillic Bt horizons, often with >50% clay-size fraction. The humid subtropical climate creates relatively consistent precipitation intra-annually and seasonally variable energy availability. Consequently, the mixed deciduous and coniferous tree cover creates a strong evapotranspiration-mediated hydrologic dynamic. While moist soils and extended stream networks are typical from late fall through spring, relatively dry soils and contracting stream networks emerge in the summer and early fall. Here, we seek to elucidate the relative influence of the vertical soil and spatial terrain structure of this region on watershed hillslope hydrology and subsequent runoff generation. We installed a network of nested, shallow groundwater wells and soil water content probes within an ephemeral to first-order watershed to continuously measure soil and groundwater dynamics across soil horizons and landscape position. We also recorded local precipitation and discharge from this watershed. Most landscape positions exhibited minimal water table response to precipitation throughout dry summer periods, with infrequently observed responses rarely coincident with streamflow generation. In contrast, during the wetter late fall through early spring period, streamflow was driven by the interaction between transient perched water tables and topographically mediated redistribution of shallow groundwater downslope. Our findings suggest that understanding streamflow generation in regions possessing both complex terrain and complex vertical soil structure requires synchronous characterization of terrain mediated water redistribution and subsurface soil hydrology.

Synchrotron-based Infrared-microspectroscopy reveals the impact of land management on carbon storage in soil micro-aggregates

NASA Astrophysics Data System (ADS)

Hernandez-Soriano, Maria C.; Dalal, Ram C.; Menzies, Neal W.; Kopittke, Peter M.

2015-04-01

Carbon stabilization in soil microaggregates results from chemical and biological processes that are highly sensitive to changes in land use. Indeed, such processes govern soil capability to store carbon, this being essential for soil health and productivity and to regulate emissions of soil organic carbon (SOC) as CO2. The identification of carbon functionalities using traditional mid-infrared analysis can be linked to carbon metabolism in soil but differences associated to land use are generally limited. The spatial resolution of synchrotron-based Infrared-microspectroscopy allows mapping microaggregate-associated forms of SOC because it has 1000 times higher brightness than a conventional thermal globar source. These maps can contribute to better understand molecular organization of SOC, physical protection in the soil particles and co-localization of carbon sources with microbial processes. Spatially-resolved analyses of carbon distribution in micro-aggregates (<200 μm diameter) have been conducted using FTIR microspectroscopy (Infrared Microspectroscopy beamline, Australian Synchrotron). Two soil types (Ferralsol and Vertisol, World Reference Base 2014) were collected from undisturbed areas and from a location(s) immediately adjacent which has a long history of agricultural use (>20 years). Soils were gently screened (250 μm) to obtain intact microaggregates which were humidified and frozen at -20°C, and sectioned (200 μm thickness) using a diamond knife and a cryo-ultramicrotome. The sections were placed between CaF2 windows and the spectra were acquired in transmission mode. The maps obtained (5 µm step-size over ca. 150 × 150 µm) revealed carbon distribution in microaggregates from soils under contrasting land management, namely undisturbed and cropping land. Accumulation of aromatic and carboxylic functions on specific spots and marginal co-localization with clays was observed, which suggests processes other than organo-mineral associations being responsible for carbon stabilization. A substantial decrease in carboxylic compounds was observed for agricultural soils. Clays were mostly co-localized with alkenes and polysaccharides, particularly in agricultural soils, likely due to enhanced microbial activity in those spots. Results will be linked to currently ongoing analysis of soil enzymes activities and characterization of dissolved organic carbon components. This novel methodological approach combines biological and chemical information on organic carbon dynamics in soil at a molecular level and will constitute a substantial advance towards understanding carbon storage in soil and the long term impact of land management.

Spatial distribution of Cd and Cu in soils in Shenyang Zhangshi Irrigation Area (SZIA), China*

PubMed Central

Sun, Li-na; Yang, Xiao-bo; Wang, Wen-qing; Ma, Li; Chen, Su

2008-01-01

Heavy metal contamination of soils, derived from sewage irrigation, mining and inappropriate utilization of various agrochemicals and pesticides, and so on, has been of wide concern in the last several decades. The Shenyang Zhangshi Irrigation Area (SZIA) in China is a representative area of heavy metal contamination of soils resulting from sewage irrigation for about 30 years. This study investigated the spatial distribution and temporal variation of soil cadmium (Cd) and copper (Cu) contamination in the SZIA. The soil samples were collected from the SZIA in 1990 and 2004; Cd and Cu in soils was analyzed and then the spatial distribution and temporal variation of Cd and Cu in soils were modeled using Kriging methods. The results show that long-term sewage irrigation had caused serious Cd and Cu contamination in soils. The mean and the maximum of soil Cd are markedly higher than the levels in second grade standard soil (LSGSS) in China, and the maximum of soil Cu is close to the LSGSS in China in 2004 and is more than the LSGSS in China in 1990. The contamination magnitude of soil Cd and the soil extent of Cd contamination had evidently increased since sewage irrigation ceased in 1992. The contamination magnitude of soil Cu and the soil extent of Cu contamination had evidently increased in topsoil, but obviously decresed in subsoil. The soil contamination of Cd and Cu was mainly related to Cd and Cu reactivation of contaminated sediments in Shenyang Xi River and the import of Cd and Cu during irrigation. The eluviation of Cd and Cu in contaminated topsoil with rainfall and irrigation water was another factor of temporal-spatial variability of Cd and Cu contamination in soils. PMID:18357631

In situ visualisation and characterisation of the capacity of highly reactive minerals to preserve soil organic matter (SOM) in colloids at submicron scale.

PubMed

Xiao, Jian; Wen, Yongli; Li, Huan; Hao, Jialong; Shen, Qirong; Ran, Wei; Mei, Xinlan; He, Xinhua; Yu, Guanghui

2015-11-01

Mineral-organo associations (MOAs) are a mixture of identifiable biopolymers associated with highly reactive minerals and microorganisms. However, the in situ characterization and correlation between soil organic matter (SOM) and highly reactive Al and Fe minerals are still unclear for the lack of technologies, particularly in the long-term agricultural soil colloids at submicron scale. We combined several novel techniques, including nano-scale secondary ion mass spectrometry (NanoSIMS), X-ray absorption near edge structure (XANES) and confocal laser scanning microscopy (CLSM) to characterise the capacity of highly reactive Al and Fe minerals to preserve SOM in Ferralic Cambisol in south China. Our results demonstrated that: (1) highly reactive minerals were strongly related to SOM preservation, while SOM had a more significant line correlation with the highly reactive Al minerals than the highly reactive Fe minerals, according to the regions of interest correlation analyses using NanoSIMS; (2) allophane and ferrihydrite were the potential mineral species to determine the SOM preservation capability, which was evaluated by the X-ray photoelectron spectroscopy (XPS) and Fe K-edge XANES spectroscopy techniques; and (3) soil organic biopolymers with dominant compounds, such as proteins, polysaccharides and lipids, were distributed at the rough and clustered surface of MOAs with high chemical and spatial heterogeneity according to the CLSM observation. Our results also promoted the understanding of the roles played by the highly reactive Al and Fe minerals in the spatial distribution of soil organic biopolymers and SOM sequestration. Copyright © 2015 Elsevier Ltd. All rights reserved.

Considerations for applying digital soil mapping to ecological sites

USDA-ARS?s Scientific Manuscript database

Recent advancements in the spatial prediction of soil properties are not currently being fully utilized for ecological studies. Linking digital soil mapping (DSM) with ecological sites (ES) has the potential to better land management decisions by improving spatial resolution and precision as well as...

Spatially enhanced passive microwave derived soil moisture: capabilities and opportunities

USDA-ARS?s Scientific Manuscript database

Low frequency passive microwave remote sensing is a proven technique for soil moisture retrieval, but its coarse resolution restricts the range of applications. Downscaling, otherwise known as disaggregation, has been proposed as the solution to spatially enhance these coarse resolution soil moistur...

Identifying the role of historical anthropogenic activities on urban soils: geochemical impact and city scale mapping

NASA Astrophysics Data System (ADS)

Le Guern, Cecile; Baudouin, Vivien; Conil, Pierre

2017-04-01

Recently, European cities have faced several changes including deindustrialization and population increase. To limit urban sprawl, urban densification is preferred. It conducts to (re)develop available areas such as brownfields. Although these areas can be attractive for housing due to their location (in proximity to the city centre or to a riverside), their soils and subsoils are often contaminated. They are therefore potentially harmful for human health and the environment, and potentially costly to remediate. Currently, in case of contamination suspicion, depth geochemical characterization of urban soil and subsoil are carried out at site scale. Nevertheless, large redevelopment project occur at quarter to city scale. It appears therefore useful to acquire the preliminary knowledge on the structure and quality of soil and subsoils, as well as on the potential sources of contamination at quarter to city scale. In the frame of the Ile de Nantes (France) redevelopment project, we considered more particularly anthropogenic deposits and former industrial activities as main sources of contamination linked to human activities. To face the low traceability of the use of anthropogenic deposits and the lack of synthesis of former industrial activities, we carried out a historical study, synthetizing the information spread in numerous archive documents to spatialize the extent of the deposits and of the former activities. In addition we developed a typology of made grounds according to their contamination potential to build a 3D geological model with a geochemical coherence. In this frame, we valorized existing borehole descriptions coming mainly from pollution diagnosis and geotechnical studies. We also developed a methodology to define urban baseline compatibility levels using the existing analytical data at depth from pollution diagnosis. These data were previously gathered in a local geodatabase towards with borehole descriptions (more than 2000 borehole descriptions, more than 1800 analyzed samples, almost 100 000 analyzed parameters). The potential quality of soil and subsoil was spatialized in 2D and 3D on the basis of anthropogenic deposits structure and typology as well as of the potential sources of contamination linked to former industrial activities. Volumes were also calculated to help the developer anticipating the management of excavated materials. Comparison with effective soil and subsoil quality (existing chemical data) shows fairly good anticipation of contamination problems, confirming the interest of spatializing the historical anthropogenic activities to anticipate the quality of urban soil and subsoil and guide city scale mapping. Urban geochemical compatibility levels will be used operationally to enhance the reuse of excavated materials. A better knowledge of soils and subsoils at depth is very useful to optimize urban redevelopment projects, anticipating contamination problems, and managing excavated materials (e.g. local reuse possibilities, disposal costs etc.). The potential economic, environmental and social consequences render it essential for urban sustainable development. 3D geochemical characterization of soil and subsoil for urban (re)development is an ambitious task. Rarely carried out until now, it needs improved development of acquisition, management, visualisation and use of data.

Soil erosion evolution and spatial correlation analysis in a typical karst geomorphology using RUSLE with GIS

NASA Astrophysics Data System (ADS)

Zeng, Cheng; Wang, Shijie; Bai, Xiaoyong; Li, Yangbing; Tian, Yichao; Li, Yue; Wu, Luhua; Luo, Guangjie

2017-07-01

Although some scholars have studied soil erosion in karst landforms, analyses of the spatial and temporal evolution of soil erosion and correlation analyses with spatial elements have been insufficient. The lack of research has led to an inaccurate assessment of environmental effects, especially in the mountainous area of Wuling in China. Soil erosion and rocky desertification in this area influence the survival and sustainability of a population of 0.22 billion people. This paper analyzes the spatiotemporal evolution of soil erosion and explores its relationship with rocky desertification using GIS technology and the revised universal soil loss equation (RUSLE). Furthermore, this paper analyzes the relationship between soil erosion and major natural elements in southern China. The results are as follows: (1) from 2000 to 2013, the proportion of the area experiencing micro-erosion and mild erosion was at increasing risk in contrast to areas where moderate and high erosion are decreasing. The area changes in this time sequence reflect moderate to high levels of erosion tending to convert into micro-erosion and mild erosion. (2) The soil erosion area on the slope, at 15-35°, accounted for 60.59 % of the total erosion area, and the corresponding soil erosion accounted for 40.44 %. (3) The annual erosion rate in the karst region decreased much faster than in the non-karst region. Soil erosion in all of the rock outcrop areas indicates an improving trend, and dynamic changes in soil erosion significantly differ among the various lithological distribution belts. (4) The soil erosion rate decreased in the rocky desertification regions, to below moderate levels, but increased in the severe rocky desertification areas. The temporal and spatial variations in soil erosion gradually decreased in the study area. Differences in the spatial distribution between lithology and rocky desertification induced extensive soil loss. As rocky desertification became worse, the erosion modulus decreased and the decreasing rate of annual erosion slowed.

Spatial and vertical distribution of soil physico-chemical properties and the content of heavy metals in the pedosphere in Poland

Treesearch

Marek Degorski

1998-01-01

The lithological and petrographical characteristics of soil pedogenesis was determined, and the spatial and vertical distribution of some soil physico-chemical properties (including heavy metal content) were studied along two transects in Poland. The genetic horizon for 22 soil profiles were described for particle size and petrographic composition, quartz grain...

Components of spatial and temporal soil variation at Canyonlands National Park: Implications for P dynamics and cheatgrass (Bromus tectorum) performance

Treesearch

Mark Miller; Jayne Belnap; Susan Beatty; Bruce Webb

2001-01-01

From January 1997 through October 1998, research was conducted at Canyonlands National Park to investigate soil traits responsible for distinct spatial patterns of cheatgrass (Bromus tectorum) occurrence. Field experiments were conducted at sites representing a broad range of soil conditions and cheatgrass abundances. Standard physicochemical soil measures in...

Spatial variation in soil biota mediates plant adaptation to a foliar pathogen.

PubMed

Mursinoff, Sini; Tack, Ayco J M

2017-04-01

Theory suggests that below-ground spatial heterogeneity may mediate host-parasite evolutionary dynamics and patterns of local adaptation, but this has rarely been tested in natural systems. Here, we test experimentally for the impact of spatial variation in the abiotic and biotic soil environment on the evolutionary outcome of the interaction between the host plant Plantago lanceolata and its specialist foliar pathogen Podosphaera plantaginis. Plants showed no adaptation to the local soil environment in the absence of natural enemies. However, quantitative, but not qualitative, plant resistance against local pathogens was higher when plants were grown in their local field soil than when they were grown in nonlocal field soil. This pattern was robust when extending the spatial scale beyond a single region, but disappeared with soil sterilization, indicating that soil biota mediated plant adaptation. We conclude that below-ground biotic heterogeneity mediates above-ground patterns of plant adaptation, resulting in increased plant resistance when plants are grown in their local soil environment. From an applied perspective, our findings emphasize the importance of using locally selected seeds in restoration ecology and low-input agriculture. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

Potential ecological risk assessment and predicting zinc accumulation in soils.

PubMed

Baran, Agnieszka; Wieczorek, Jerzy; Mazurek, Ryszard; Urbański, Krzysztof; Klimkowicz-Pawlas, Agnieszka

2018-02-01

The aims of this study were to investigate zinc content in the studied soils; evaluate the efficiency of geostatistics in presenting spatial variability of zinc in the soils; assess bioavailable forms of zinc in the soils and to assess soil-zinc binding ability; and to estimate the potential ecological risk of zinc in soils. The study was conducted in southern Poland, in the Malopolska Province. This area is characterized by a great diversity of geological structures and types of land use and intensity of industrial development. The zinc content was affected by soil factors, and the type of land use (arable lands, grasslands, forests, wastelands). A total of 320 soil samples were characterized in terms of physicochemical properties (texture, pH, organic C content, total and available Zn content). Based on the obtained data, assessment of the ecological risk of zinc was conducted using two methods: potential ecological risk index and hazard quotient. Total Zn content in the soils ranged from 8.27 to 7221 mg kg -1 d.m. Based on the surface semivariograms, the highest variability of zinc in the soils was observed from northwest to southeast. The point sources of Zn contamination were located in the northwestern part of the area, near the mining-metallurgical activity involving processing of zinc and lead ores. These findings were confirmed by the arrangement of semivariogram surfaces and bivariate Moran's correlation coefficients. The content of bioavailable forms of zinc was between 0.05 and 46.19 mg kg -1 d.m. (0.01 mol dm -3 CaCl 2 ), and between 0.03 and 71.54 mg kg -1 d.m. (1 mol dm -3 NH 4 NO 3 ). Forest soils had the highest zinc solubility, followed by arable land, grassland and wasteland. PCA showed that organic C was the key factor to control bioavailability of zinc in the soils. The extreme, very high and medium zinc accumulation was found in 69% of studied soils. There is no ecological risk of zinc to living organisms in the study area, and in 90% of the soils there were no potentially negative effects of zinc to ecological receptors.

Factors Driving Potential Ammonia Oxidation in Canadian Arctic Ecosystems: Does Spatial Scale Matter?

PubMed Central

Banerjee, Samiran

2012-01-01

Ammonia oxidation is a major process in nitrogen cycling, and it plays a key role in nitrogen limited soil ecosystems such as those in the arctic. Although mm-scale spatial dependency of ammonia oxidizers has been investigated, little is known about the field-scale spatial dependency of aerobic ammonia oxidation processes and ammonia-oxidizing archaeal and bacterial communities, particularly in arctic soils. The purpose of this study was to explore the drivers of ammonia oxidation at the field scale in cryosols (soils with permafrost within 1 m of the surface). We measured aerobic ammonia oxidation potential (both autotrophic and heterotrophic) and functional gene abundance (bacterial amoA and archaeal amoA) in 279 soil samples collected from three arctic ecosystems. The variability associated with quantifying genes was substantially less than the spatial variability observed in these soils, suggesting that molecular methods can be used reliably evaluate spatial dependency in arctic ecosystems. Ammonia-oxidizing archaeal and bacterial communities and aerobic ammonia oxidation were spatially autocorrelated. Gene abundances were spatially structured within 4 m, whereas biochemical processes were structured within 40 m. Ammonia oxidation was driven at small scales (<1m) by moisture and total organic carbon, whereas gene abundance and other edaphic factors drove ammonia oxidation at medium (1 to 10 m) and large (10 to 100 m) scales. In these arctic soils heterotrophs contributed between 29 and 47% of total ammonia oxidation potential. The spatial scale for aerobic ammonia oxidation genes differed from potential ammonia oxidation, suggesting that in arctic ecosystems edaphic, rather than genetic, factors are an important control on ammonia oxidation. PMID:22081570

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2012-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.