DayCent model simulations for estimating soil carbon dynamics and greenhouse gas fluxes from agricultural production systems

USDA-ARS?s Scientific Manuscript database

DayCent is a biogeochemical model of intermediate complexity used to simulate carbon, nutrient, and greenhouse gas fluxes for crop, grassland, forest, and savanna ecosystems. Model inputs include: soil texture and hydraulic properties, current and historical land use, vegetation cover, daily maximum...

A complex permittivity model for field estimation of soil water contents using time domain reflectometry

USDA-ARS?s Scientific Manuscript database

Accurate electromagnetic sensing of soil water contents (') under field conditions is complicated by the dependence of permittivity on specific surface area, temperature, and apparent electrical conductivity, all which may vary across space or time. We present a physically-based mixing model to pred...

Pier and contraction scour prediction in cohesive soils at selected bridges in Illinois

USGS Publications Warehouse

Straub, Timothy D.; Over, Thomas M.

2010-01-01

This report presents the results of testing the Scour Rate In Cohesive Soils-Erosion Function Apparatus (SRICOS-EFA) method for estimating scour depth of cohesive soils at 15 bridges in Illinois. The SRICOS-EFA method for complex pier and contraction scour in cohesive soils has two primary components. The first component includes the calculation of the maximum contraction and pier scour (Zmax). The second component is an integrated approach that considers a time factor, soil properties, and continued interaction between the contraction and pier scour (SRICOS runs). The SRICOS-EFA results were compared to scour prediction results for non-cohesive soils based on Hydraulic Engineering Circular No. 18 (HEC-18). On average, the HEC-18 method predicted higher scour depths than the SRICOS-EFA method. A reduction factor was determined for each HEC-18 result to make it match the maximum of three types of SRICOS run results. The unconfined compressive strength (Qu) for the soil was then matched with the reduction factor and the results were ranked in order of increasing Qu. Reduction factors were then grouped by Qu and applied to each bridge site and soil. These results, and comparison with the SRICOS Zmax calculation, show that less than half of the reduction-factor method values were the lowest estimate of scour; whereas, the Zmax method values were the lowest estimate for over half. A tiered approach to predicting pier and contraction scour was developed. There are four levels to this approach numbered in order of complexity, with the fourth level being a full SRICOS-EFA analysis. Levels 1 and 2 involve the reduction factors and Zmax calculation, and can be completed without EFA data. Level 3 requires some surrogate EFA data. Levels 3 and 4 require streamflow for input into SRICOS. Estimation techniques for both EFA surrogate data and streamflow data were developed.

Evaluating the biological activity of oil-polluted soils using a complex index

NASA Astrophysics Data System (ADS)

Kabirov, R. R.; Kireeva, N. A.; Kabirov, T. R.; Dubovik, I. Ye.; Yakupova, A. B.; Safiullina, L. M.

2012-02-01

A complex index characterizing the biological activity of soils (BAS) is suggested. It is based on an estimate of the level of activity of catalase; the number of heterotrophic and hydrocarbon oxidizing microorganisms, microscopic fungi, algae, and cyanobacteria; and the degree of development of higher plants and insects in the studied soil. The data on using the BAS coefficient for evaluating the efficiency of rehabilitation measures for oil-polluted soils are given. Such measures included introducing the following biological preparations: Lenoil based on a natural consortium of microorganisms Bacillus brevis and Arthrobacter sp.; the Azolen biofertilizer with complex action based on Azotobacter vinelandii; the Belvitamil biopreparation, which is the active silt of pulp and paper production; and a ready-mixed industrial association of aerobic and anaerobic microorganisms that contains hydrocarbon oxidizing microorganisms of the Arthrobacter, Bacillus, Candida, Desulfovibrio, and Pseudomonas genera.

Estimating Children’s Soil/Dust Ingestion Rates through Retrospective Analyses of Blood Lead Biomonitoring from the Bunker Hill Superfund Site in Idaho

PubMed Central

von Lindern, Ian; Spalinger, Susan; Stifelman, Marc L.; Stanek, Lindsay Wichers; Bartrem, Casey

2016-01-01

Background: Soil/dust ingestion rates are important variables in assessing children’s health risks in contaminated environments. Current estimates are based largely on soil tracer methodology, which is limited by analytical uncertainty, small sample size, and short study duration. Objectives: The objective was to estimate site-specific soil/dust ingestion rates through reevaluation of the lead absorption dose–response relationship using new bioavailability data from the Bunker Hill Mining and Metallurgical Complex Superfund Site (BHSS) in Idaho, USA. Methods: The U.S. Environmental Protection Agency (EPA) in vitro bioavailability methodology was applied to archived BHSS soil and dust samples. Using age-specific biokinetic slope factors, we related bioavailable lead from these sources to children’s blood lead levels (BLLs) monitored during cleanup from 1988 through 2002. Quantitative regression analyses and exposure assessment guidance were used to develop candidate soil/dust source partition scenarios estimating lead intake, allowing estimation of age-specific soil/dust ingestion rates. These ingestion rate and bioavailability estimates were simultaneously applied to the U.S. EPA Integrated Exposure Uptake Biokinetic Model for Lead in Children to determine those combinations best approximating observed BLLs. Results: Absolute soil and house dust bioavailability averaged 33% (SD ± 4%) and 28% (SD ± 6%), respectively. Estimated BHSS age-specific soil/dust ingestion rates are 86–94 mg/day for 6-month- to 2-year-old children and 51–67 mg/day for 2- to 9-year-old children. Conclusions: Soil/dust ingestion rate estimates for 1- to 9-year-old children at the BHSS are lower than those commonly used in human health risk assessment. A substantial component of children’s exposure comes from sources beyond the immediate home environment. Citation: von Lindern I, Spalinger S, Stifelman ML, Stanek LW, Bartrem C. 2016. Estimating children’s soil/dust ingestion rates through retrospective analyses of blood lead biomonitoring from the Bunker Hill Superfund Site in Idaho. Environ Health Perspect 124:1462–1470; http://dx.doi.org/10.1289/ehp.1510144 PMID:26745545

Application of the two-source energy balance model to partition evapotranspiration in an arid wine vineyard

NASA Astrophysics Data System (ADS)

Kool, Dilia; Kustas, William P.; Agam, Nurit

2016-04-01

The partitioning of evapotranspiration (ET) into transpiration (T), a productive water use, and soil water evaporation (E), which is generally considered a water loss, is highly relevant to agriculture in the light of increasing desertification and water scarcity. This task is challenged by the complexity of soil and plant interactions, coupled with changes in atmospheric and soil water content conditions. Many of the processes controlling water/energy exchange are not adequately modeled. The two-source energy balance model (TSEB) was evaluated and adapted for independent E and T estimations in an isolated drip-irrigated wine vineyard in the arid Negev desert. The TSEB model estimates ET by computing vegetation and soil energy fluxes using remotely sensed composite surface temperature, local weather data (solar radiation, air temperature and humidity, and wind speed), and vegetation metrics (row spacing, canopy height and width, and leaf area). The soil and vegetation energy fluxes are computed numerically using a system of temperature gradient and resistance equations; where soil and canopy temperatures are derived from the composite surface temperature. For estimation of ET, the TSEB model has been shown to perform well for various agricultural crops under a wide range of environmental conditions, but validation of T and E fluxes is limited to one study in a well-watered cotton crop. Extending the TSEB approach to water-limited vineyards demands careful consideration regarding how the complex canopy structure of vineyards will influence the accuracy of the partitioning between E and T. Data for evaluation of the TSEB model were collected over a season (bud break till harvest). Composite, canopy, and soil surface temperatures were measured using infrared thermometers. The composite vegetation and soil surface energy fluxes were assessed using independent measurements of net radiation, and soil, sensible and latent heat flux. The below canopy energy balance was assessed at the dry midrow position as well as the wet irrigated position directly underneath the vine row, where net radiation and soil heat flux were measured, sensible heat flux was computed indirectly, and E was calculated as the residual. While the below canopy energy balance approach used in this study allowed continuous assessment of E at daily intervals, instantaneous E fluxes could not be assessed due to vertical variability in shading below the canopy. Seasonal partitioning indicated that total E amounted to 9-11% of ET. Initial evaluation of the TSEB model indicated that discrepancies between modeled and measured fluxes can largely be attributed to net radiation partitioning. In addition, large diurnal variation at the soil surface requires adaptation of the soil heat flux formulations. Improved estimation of energy fluxes by accounting for the relatively complex canopy structure of vineyards will be highlighted.

Incorporating soil variability in continental soil water modelling: a trade-off between data availability and model complexity

NASA Astrophysics Data System (ADS)

Peeters, L.; Crosbie, R. S.; Doble, R.; van Dijk, A. I. J. M.

2012-04-01

Developing a continental land surface model implies finding a balance between the complexity in representing the system processes and the availability of reliable data to drive, parameterise and calibrate the model. While a high level of process understanding at plot or catchment scales may warrant a complex model, such data is not available at the continental scale. This data sparsity is especially an issue for the Australian Water Resources Assessment system, AWRA-L, a land-surface model designed to estimate the components of the water balance for the Australian continent. This study focuses on the conceptualization and parametrization of the soil drainage process in AWRA-L. Traditionally soil drainage is simulated with Richards' equation, which is highly non-linear. As general analytic solutions are not available, this equation is usually solved numerically. In AWRA-L however, we introduce a simpler function based on simulation experiments that solve Richards' equation. In the simplified function soil drainage rate, the ratio of drainage (D) over storage (S), decreases exponentially with relative water content. This function is controlled by three parameters, the soil water storage at field capacity (SFC), the drainage fraction at field capacity (KFC) and a drainage function exponent (β). [ ] D- -S- S = KF C exp - β (1 - SFC ) To obtain spatially variable estimates of these three parameters, the Atlas of Australian Soils is used, which lists soil hydraulic properties for each soil profile type. For each soil profile type in the Atlas, 10 days of draining an initially fully saturated, freely draining soil is simulated using HYDRUS-1D. With field capacity defined as the volume of water in the soil after 1 day, the remaining parameters can be obtained by fitting the AWRA-L soil drainage function to the HYDRUS-1D results. This model conceptualisation fully exploits the data available in the Atlas of Australian Soils, without the need to solve the non-linear Richards' equation for each time-step. The spatial distribution of long term recharge and baseflow obtained with a 30 year simulation of historic data using this parameterisation, corresponds well with the spatial patterns of groundwater recharge inferred from field measurements.

Concentrations, profiles, and estimated human exposures for polychlorinated dibenzo-p-dioxins and dibenzofurans from electronic waste recycling facilities and a chemical industrial complex in Eastern China

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

Ma, J.; Kannan, K.; Cheng, J.

2008-11-15

Electronic shredder waste and dust from e-waste facilities, and leaves and surface soil collected in the vicinity of a large scale e-waste recycling facility in Taizhou, Eastern China, were analyzed for total dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) including 2,3,7,8-substituted congeners. We also determined PCDD/Fs in surface agricultural soils from several provinces in China for comparison with soils from e-waste facilities. Concentrations of total PCDD/Fs were high in all of the matrices analyzed and ranged from 30.9 to 11,400 pg/g for shredder waste, 3460 to 9820 pg/g dry weight for leaves, 2560 to 148,000 pg/g dry weight for workshop-floor dust, and 854more » to 10200 pg/g dry weight for soils. We also analyzed surface soils from a chemical industrial complex (a coke-oven plant, a coal-fired power plant, and a chlor-alkali plant) in Shanghai. Concentrations of total PCDD/Fs in surface soil from the chemical industrial complex were lower than the concentrations found in soils from e-waste recycling plants, but higher than the concentrations found in agricultural soils. Agricultural soils from six cities in China contained low levels of total PCDD/Fs. Profiles of dioxin toxic equivalents (TEQs) of 2,3,7,8-PCDD/Fs in soils from e-waste facilities in Taizhou differed from the profiles found in agricultural soils. The estimated daily intakes of TEQs of PCDD/Fs via soil/dust ingestion and dermal exposure were 2 orders of magnitude higher in people at e-waste recycling facilities than in people at the chemical industrial site, implying greater health risk for humans from dioxin exposures at e-waste recycling facilities. The calculated TEQ exposures for e-waste workers from dust and soil ingestion alone were 2-3 orders of magnitude greater than the exposures from soils in reference locations. 37 refs., 1 fig., 2 tabs.« less

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

PubMed

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data

PubMed Central

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures. PMID:26901763

TEMPERATURE SENSITIVITY OF SOIL RESPIRATION AND ITS EFFECTS ON ECOSYSTEM CARBON BUDGET: NONLINEARITY BEGETS SURPRISES. (R827676)

EPA Science Inventory

Nonlinearity is a salient feature in all complex systems, and it certainly characterizes biogeochemical cycles in ecosystems across a wide range of scales. Soil carbon emission is a major source of uncertainty in estimating the terrestrial carbon budget at the ecosystem level ...

Identifying hydrological pre-conditions and rainfall triggers of slope failures for 2014 storm events in the Ialomita Subcarpathians, Romania

NASA Astrophysics Data System (ADS)

Chitu, Zenaida; Bogaard, Thom; Busuioc, Aristita; Burcea, Sorin; Adler, Mary-Jeanne; Sandric, Ionut

2015-04-01

Like in many parts of the world, in Romania, landslides represent recurrent phenomena that produce numerous damages to infrastructure every few years. Various studies on landslide occurrence in the Curvature Subcarpathians reveal that rainfall represents the most important triggering factor for landslides. Depending on rainfall characteristics and environmental factors different types of landslides were recorded in the Ialomita Subcarpathians: slumps, earthflows and complex landslides. This area, located in the western part of Curvature Subcarpathians, is characterized by a very complex geology whose main features are represented by the nappes system, the post tectonic covers, the diapirism phenomena and vertical faults. This work aims to investigate hydrological pre-conditions and rainfall characteristics which triggered slope failures in 2014 in the Ialomita Subcarpathians, Romania. Hydrological pre-conditions were investigated by means of water balance analysis and low flow techniques, while spatial and temporal patterns of rainfalls were estimated using radar data and six rain gauges. Additionally, six soil moisture stations that are fitted with volumetric soil moisture sensors and temperature soil sensors were used to estimate the antecedent soil moisture conditions.

Estimation of soil sorption coefficients of veterinary pharmaceuticals from soil properties.

PubMed

ter Laak, Thomas L; Gebbink, Wouter A; Tolls, Johannes

2006-04-01

Environmental exposure assessment of veterinary pharmaceuticals requires estimating the sorption to soil. Soil sorption coefficients of three common, ionizable, antimicrobial agents (oxytetracycline [OTC], tylosin [TYL], and sulfachloropyridazine [SCP]) were studied in relation to the soil properties of 11 different soils. The soil sorption coefficient at natural pH varied from 950 to 7,200, 10 to 370, and 0.4 to 35 L/kg for OTC, TYL, and SCP, respectively. The variation increased by almost two orders of magnitude for OTC and TYL when pH was artificially adjusted. Separate soil properties (pH, organic carbon content, clay content, cation-exchange capacity, aluminum oxyhydroxide content, and iron oxyhydroxide content) were not able to explain more than half the variation observed in soil sorption coefficients. This reflects the complexity of the sorbent-sorbate interactions. Partial-least-squares (PLS) models, integrating all the soil properties listed above, were able to explain as much as 78% of the variation in sorption coefficients. The PLS model was able to predict the sorption coefficient with an accuracy of a factor of six. Considering the pH-dependent speciation, species-specific PLS models were developed. These models were able to predict species-specific sorption coefficients with an accuracy of a factor of three to four. However, the species-specific sorption models did not improve the estimation of sorption coefficients of species mixtures, because these models were developed with a reduced data set at standardized aqueous concentrations. In conclusion, pragmatic approaches like PLS modeling might be suitable to estimate soil sorption for risk assessment purposes.

Mapping Soil Surface Macropores Using Infrared Thermography: An Exploratory Laboratory Study

PubMed Central

de Lima, João L. M. P.; Abrantes, João R. C. B.; Silva, Valdemir P.; de Lima, M. Isabel P.; Montenegro, Abelardo A. A.

2014-01-01

Macropores and water flow in soils and substrates are complex and are related to topics like preferential flow, nonequilibrium flow, and dual-continuum. Hence, the quantification of the number of macropores and the determination of their geometry are expected to provide a better understanding on the effects of pores on the soil's physical and hydraulic properties. This exploratory study aimed at evaluating the potential of using infrared thermography for mapping macroporosity at the soil surface and estimating the number and size of such macropores. The presented technique was applied to a small scale study (laboratory soil flume). PMID:25371915

Estimating Soil and Root Parameters of Biofuel Crops using a Hydrogeophysical Inversion

NASA Astrophysics Data System (ADS)

Kuhl, A.; Kendall, A. D.; Van Dam, R. L.; Hyndman, D. W.

2017-12-01

Transpiration is the dominant pathway for continental water exchange to the atmosphere, and therefore a crucial aspect of modeling water balances at many scales. The root water uptake dynamics that control transpiration are dependent on soil water availability, as well as the root distribution. However, the root distribution is determined by many factors beyond the plant species alone, including climate conditions and soil texture. Despite the significant contribution of transpiration to global water fluxes, modelling the complex critical zone processes that drive root water uptake remains a challenge. Geophysical tools such as electrical resistivity (ER), have been shown to be highly sensitive to water dynamics in the unsaturated zone. ER data can be temporally and spatially robust, covering large areas or long time periods non-invasively, which is an advantage over in-situ methods. Previous studies have shown the value of using hydrogeophysical inversions to estimate soil properties. Others have used hydrological inversions to estimate both soil properties and root distribution parameters. In this study, we combine these two approaches to create a coupled hydrogeophysical inversion that estimates root and retention curve parameters for a HYDRUS model. To test the feasibility of this new approach, we estimated daily water fluxes and root growth for several biofuel crops at a long-term ecological research site in Southwest Michigan, using monthly ER data from 2009 through 2011. Time domain reflectometry data at seven depths was used to validate modeled soil moisture estimates throughout the model period. This hydrogeophysical inversion method shows promise for improving root distribution and transpiration estimates across a wide variety of settings.

Improvment of the Trapezoid Method Using Raw Landsat Image Digital Count Data for Soil Moisture Estimation in the Texas (usa) High Plains

NASA Astrophysics Data System (ADS)

Shafian, S.; Maas, S. J.

2015-12-01

Variations in soil moisture strongly affect surface energy balances, regional runoff, land erosion and vegetation productivity (i.e., potential crop yield). Hence, the estimation of soil moisture is very valuable in the social, economic, humanitarian (food security) and environmental segments of society. Extensive efforts to exploit the potential of remotely sensed observations to help quantify this complex variable are ongoing. This study aims at developing a new index, the Thermal Ground cover Moisture Index (TGMI), for estimating soil moisture content. This index is based on empirical parameterization of the relationship between raw image digital count (DC) data in the thermal infrared spectral band and ground cover (determined from raw image digital count data in the red and near-infrared spectral bands).The index uses satellite-derived information only, and the potential for its operational application is therefore great. This study was conducted in 18 commercial agricultural fields near Lubbock, TX (USA). Soil moisture was measured in these fields over two years and statistically compared to corresponding values of TGMI determined from Landsat image data. Results indicate statistically significant correlations between TGMI and field measurements of soil moisture (R2 = 0.73, RMSE = 0.05, MBE = 0.17 and AAE = 0.049), suggesting that soil moisture can be estimated using this index. It was further demonstrated that maps of TGMI developed from Landsat imagery could be constructed to show the relative spatial distribution of soil moisture across a region.

Remote sensing-based estimation of annual soil respiration at two contrasting forest sites

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

Huang, Ni; Gu, Lianhong; Black, T. Andrew

Here, soil respiration (R s), an important component of the global carbon cycle, can be estimated using remotely sensed data, but the accuracy of this technique has not been thoroughly investigated. In this study, we proposed a methodology for the remote estimation of annual R s at two contrasting FLUXNET forest sites (a deciduous broadleaf forest and an evergreen needleleaf forest). A version of the Akaike's information criterion was used to select the best model from a range of models for annual R s estimation based on the remotely sensed data products from the Moderate Resolution Imaging Spectroradiometer and root-zonemore » soil moisture product derived from assimilation of the NASA Advanced Microwave Scanning Radiometer soil moisture products and a two-layer Palmer water balance model. We found that the Arrhenius-type function based on nighttime land surface temperature (LST-night) was the best model by comprehensively considering the model explanatory power and model complexity at the Missouri Ozark and BC-Campbell River 1949 Douglas-fir sites.« less

SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS

NASA Astrophysics Data System (ADS)

Pellarin, Thierry; Brocca, Luca; Crow, Wade; Kerr, Yann; Massari, Christian; Román-Cascón, Carlos; Fernández, Diego

2017-04-01

Recent studies have demonstrated the usefulness of soil moisture retrieved from satellite for improving rainfall estimations of satellite based precipitation products (SBPP). The real-time version of these products are known to be biased from the real precipitation observed at the ground. Therefore, the information contained in soil moisture can be used to correct the inaccuracy and uncertainty of these products, since the value and behavior of this soil variable preserve the information of a rain event even for several days. In this work, we take advantage of the soil moisture data from the Soil Moisture and Ocean Salinity (SMOS) satellite, which provides information with a quite appropriate temporal and spatial resolution for correcting rainfall events. Specifically, we test and compare the ability of three different methodologies for this aim: 1) SM2RAIN, which directly relate changes in soil moisture to rainfall quantities; 2) The LMAA methodology, which is based on the assimilation of soil moisture in two models of different complexity (see EGU2017-5324 in this same session); 3) The SMART method, based on the assimilation of soil moisture in a simple hydrological model with a different assimilation/modelling technique. The results are tested for 6 years over 10 sites around the world with different features (land surface, rainfall climatology, orography complexity, etc.). These preliminary and promising results are shown here for the first time to the scientific community, as also the observed limitations of the different methodologies. Specific remarks on the technical configurations, filtering/smoothing of SMOS soil moisture or re-scaling techniques are also provided from the results of different sensitivity experiments.

Biodegradation kinetics for pesticide exposure assessment.

PubMed

Wolt, J D; Nelson, H P; Cleveland, C B; van Wesenbeeck, I J

2001-01-01

Understanding pesticide risks requires characterizing pesticide exposure within the environment in a manner that can be broadly generalized across widely varied conditions of use. The coupled processes of sorption and soil degradation are especially important for understanding the potential environmental exposure of pesticides. The data obtained from degradation studies are inherently variable and, when limited in extent, lend uncertainty to exposure characterization and risk assessment. Pesticide decline in soils reflects dynamically coupled processes of sorption and degradation that add complexity to the treatment of soil biodegradation data from a kinetic perspective. Additional complexity arises from study design limitations that may not fully account for the decline in microbial activity of test systems, or that may be inadequate for considerations of all potential dissipation routes for a given pesticide. Accordingly, kinetic treatment of data must accommodate a variety of differing approaches starting with very simple assumptions as to reaction dynamics and extending to more involved treatments if warranted by the available experimental data. Selection of the appropriate kinetic model to describe pesticide degradation should rely on statistical evaluation of the data fit to ensure that the models used are not overparameterized. Recognizing the effects of experimental conditions and methods for kinetic treatment of degradation data is critical for making appropriate comparisons among pesticide biodegradation data sets. Assessment of variability in soil half-life among soils is uncertain because for many pesticides the data on soil degradation rate are limited to one or two soils. Reasonable upper-bound estimates of soil half-life are necessary in risk assessment so that estimated environmental concentrations can be developed from exposure models. Thus, an understanding of the variable and uncertain distribution of soil half-lives in the environment is necessary to estimate bounding values. Statistical evaluation of measures of central tendency for multisoil kinetic studies shows that geometric means better represent the distribution in soil half-lives than do the arithmetic or harmonic means. Estimates of upper-bound soil half-life values based on the upper 90% confidence bound on the geometric mean tend to accurately represent the upper bound when pesticide degradation rate is biologically driven but appear to overestimate the upper bound when there is extensive coupling of biodegradation with sorptive processes. The limited data available comparing distribution in pesticide soil half-lives between multisoil laboratory studies and multilocation field studies suggest that the probability density functions are similar. Thus, upper-bound estimates of pesticide half-life determined from laboratory studies conservatively represent pesticide biodegradation in the field environment for the purposes of exposure and risk assessment. International guidelines and approaches used for interpretations of soil biodegradation reflect many common elements, but differ in how the source and nature of variability in soil kinetic data are considered. Harmonization of approaches for the use of soil biodegradation data will improve the interpretative power of these data for the purposes of exposure and risk assessment.

Soil: A Public Health Threat or Savior

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

IL Pepper; CP Gerba; DT Newby

Soil is the most complicated biomaterial on the planet due to complex soil architecture and billions of soil microbes with extreme biotic diversity. Soil is potentially a source of human pathogens, which can be defined as geo-indigenous, geo-transportable, or geotreatable. Such pathogens cumulatively can and do result in multiple human fatalities annually. A striking example is Helminths, with current infections worldwide estimated to be around two billion. However, soil can also be a source of antibiotics and other natural products that enhance human health. Soilborne antibiotics are used to treat human infections, but can also result in antibiotic-resistant bacteria. Naturalmore » products isolated from soil resulted in 60% of new cancer drugs between the period 1983–1994. Soils are also crucial to human health through their impact on human nutrition. Finally, from a global perspective, soils are vital to the future well-being of nations through their impact on climate change and global warming. A critical review of soil with respect to public health leads to the conclusion that overall soil is a public health savior. The value of soil using a systems approach is estimated to be $20 trillion, and is by far the most valuable ecosystem in the world.« less

Ecological risk assessment on heavy metals in soils: Use of soil diffuse reflectance mid-infrared Fourier-transform spectroscopy

PubMed Central

Wang, Cheng; Li, Wei; Guo, Mingxing; Ji, Junfeng

2017-01-01

The bioavailability of heavy metals in soil is controlled by their concentrations and soil properties. Diffuse reflectance mid-infrared Fourier-transform spectroscopy (DRIFTS) is capable of detecting specific organic and inorganic bonds in metal complexes and minerals and therefore, has been employed to predict soil composition and heavy metal contents. The present study explored the potential of DRIFTS for estimating soil heavy metal bioavailability. Soil and corresponding wheat grain samples from the Yangtze River Delta region were analyzed by DRIFTS and chemical methods. Statistical regression analyses were conducted to correlate the soil spectral information to the concentrations of Cd, Cr, Cu, Zn, Pb, Ni, Hg and Fe in wheat grains. The principal components in the spectra influencing soil heavy metal bioavailability were identified and used in prediction model construction. The established soil DRIFTS-based prediction models were applied to estimate the heavy metal concentrations in wheat grains in the mid-Yangtze River Delta area. The predicted heavy metal concentrations of wheat grain were highly consistent with the measured levels by chemical analysis, showing a significant correlation (r2 > 0.72) with acceptable root mean square error RMSE. In conclusion, DRIFTS is a promising technique for assessing the bioavailability of soil heavy metals and related ecological risk. PMID:28198802

An empirical model for the complex dielectric permittivity of soils as a function of water content

NASA Technical Reports Server (NTRS)

Wang, J. R.; Chmugge, T. J.

1978-01-01

The recent measurements on the dielectric properties of soils shows that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value of transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of ths soil-water mixtures. The relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.

Plant-beneficial elements status assessment in soil-plant system in the vicinity of a chemical industry complex: shedding light on forage grass safety issues.

PubMed

Anjum, Naser A; Duarte, Armando C; Pereira, Eduarda; Ahmad, Iqbal

2015-02-01

Human health is closely linked with soils via plants, grazers, or plant-based products. This study estimated plant-beneficial elements (macronutrients: K, P; secondary macronutrients: Ca, Mg; micronutrients: Mo, Mn, Na, Ni, Se) in both soils and shoots of two forage grass species (Eriophorum angustifolium and Lolium perenne) prevalent in the vicinity of a chemical industry complex (Estarreja, Portugal). Both soils and plants from the chemical industrial areas exhibited differential concentrations of the studied elements. In soils, the role of contamination was evidenced as insignificant in context of its impact on all the tested macro and secondary macronutrients except P, and micronutrients such as Mo and Ni. In forage grass plant shoots, the role of contamination was evidenced as insignificant in relation to its impact on all the tested macro and secondary macronutrients except K. Between the two forage grass plants, high Se-harboring L. perenne cannot be recommended for its use as animal feed.

Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Higgins, Chad W.; Still, Christopher J.; Good, Stephen P.

2018-06-01

Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash-Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from < 1 to 15 %. The parameter identifiability was not significantly improved in the more complex seasonal model; however, small differences in parameter values indicate that the annual model may have absorbed dry season dynamics. Parameter estimates were most constrained for scales and locations at which soil water dynamics are more sensitive to the fitted ecohydrological parameters of interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in ecohydrology and provides a simple framework to obtain scale- and site-specific analytical descriptions of soil moisture dynamics consistent with soil moisture observations.

Ground-Based Passive Microwave Remote Sensing Observations of Soil Moisture at S and L Band with Insight into Measurement Accuracy

NASA Technical Reports Server (NTRS)

Laymon, Charles A.; Crosson, William L.; Jackson, Thomas J.; Manu, Andrew; Tsegaye, Teferi D.; Soman, V.; Arnold, James E. (Technical Monitor)

2001-01-01

Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.

Complex conductivity of oil-contaminated clayey soils

NASA Astrophysics Data System (ADS)

Deng, Yaping; Shi, Xiaoqing; Revil, André; Wu, Jichun; Ghorbani, A.

2018-06-01

Spectral induced polarization (SIP) is considered as a promising tool in environmental investigations. However, few works have done regarding the electrical signature of oil contamination of clayey soils upon induced polarization. Laboratory column experiments plus one sandbox experiment are conducted in this study to investigate the performances of the SIP method in oil-contaminated soils. First, a total of 12 soils are investigated to reveal the influences of water and soil properties on the saturation dependence of the complex conductivity below 100 Hz. Results show that the magnitude of the complex conductivity consistently decreases with decreasing water saturation for all soils samples. The saturation n and quadrature conductivity p exponents tend to increase slightly with increasing water salinity when using a linear conductivity model. The saturation exponent increases marginally with the cation exchange capacity (CEC) and the specific surface area (Ssp) while the quadrature conductivity exponent exhibits a relatively stronger dependence on both CEC and Ssp. For the low CEC soil samples (normally ≤10 meq/100 g), the quadrature conductivity exponent p correlates well with the saturation exponent n using the relationship p = n-1. SIP method is further applied in a sandbox experiment to estimate the saturation distribution and total volume of the oil. Results demonstrate that the SIP method has a great potential for mapping the organic contaminant plume and quantifying the oil volume.

Estimating Prion Adsorption Capacity of Soil by BioAssay of Subtracted Infectivity from Complex Solutions (BASICS)

PubMed Central

Wyckoff, A. Christy; Lockwood, Krista L.; Meyerett-Reid, Crystal; Michel, Brady A.; Bender, Heather; VerCauteren, Kurt C.; Zabel, Mark D.

2013-01-01

Prions, the infectious agent of scrapie, chronic wasting disease and other transmissible spongiform encephalopathies, are misfolded proteins that are highly stable and resistant to degradation. Prions are known to associate with clay and other soil components, enhancing their persistence and surprisingly, transmissibility. Currently, few detection and quantification methods exist for prions in soil, hindering an understanding of prion persistence and infectivity in the environment. Variability in apparent infectious titers of prions when bound to soil has complicated attempts to quantify the binding capacity of soil for prion infectivity. Here, we quantify the prion adsorption capacity of whole, sandy loam soil (SLS) typically found in CWD endemic areas in Colorado; and purified montmorillonite clay (Mte), previously shown to bind prions, by BioAssay of Subtracted Infectivity in Complex Solutions (BASICS). We incubated prion positive 10% brain homogenate from terminally sick mice infected with the Rocky Mountain Lab strain of mouse-adapted prions (RML) with 10% SLS or Mte. After 24 hours samples were centrifuged five minutes at 200×g and soil-free supernatant was intracerebrally inoculated into prion susceptible indicator mice. We used the number of days post inoculation to clinical disease to calculate the infectious titer remaining in the supernatant, which we subtracted from the starting titer to determine the infectious prion binding capacity of SLS and Mte. BASICS indicated SLS bound and removed ≥ 95% of infectivity. Mte bound and removed lethal doses (99.98%) of prions from inocula, effectively preventing disease in the mice. Our data reveal significant prion-binding capacity of soil and the utility of BASICS to estimate prion loads and investigate persistence and decomposition in the environment. Additionally, since Mte successfully rescued the mice from prion disease, Mte might be used for remediation and decontamination protocols. PMID:23484043

Estimating prion adsorption capacity of soil by BioAssay of Subtracted Infectivity from Complex Solutions (BASICS).

PubMed

Wyckoff, A Christy; Lockwood, Krista L; Meyerett-Reid, Crystal; Michel, Brady A; Bender, Heather; VerCauteren, Kurt C; Zabel, Mark D

2013-01-01

Prions, the infectious agent of scrapie, chronic wasting disease and other transmissible spongiform encephalopathies, are misfolded proteins that are highly stable and resistant to degradation. Prions are known to associate with clay and other soil components, enhancing their persistence and surprisingly, transmissibility. Currently, few detection and quantification methods exist for prions in soil, hindering an understanding of prion persistence and infectivity in the environment. Variability in apparent infectious titers of prions when bound to soil has complicated attempts to quantify the binding capacity of soil for prion infectivity. Here, we quantify the prion adsorption capacity of whole, sandy loam soil (SLS) typically found in CWD endemic areas in Colorado; and purified montmorillonite clay (Mte), previously shown to bind prions, by BioAssay of Subtracted Infectivity in Complex Solutions (BASICS). We incubated prion positive 10% brain homogenate from terminally sick mice infected with the Rocky Mountain Lab strain of mouse-adapted prions (RML) with 10% SLS or Mte. After 24 hours samples were centrifuged five minutes at 200 × g and soil-free supernatant was intracerebrally inoculated into prion susceptible indicator mice. We used the number of days post inoculation to clinical disease to calculate the infectious titer remaining in the supernatant, which we subtracted from the starting titer to determine the infectious prion binding capacity of SLS and Mte. BASICS indicated SLS bound and removed ≥ 95% of infectivity. Mte bound and removed lethal doses (99.98%) of prions from inocula, effectively preventing disease in the mice. Our data reveal significant prion-binding capacity of soil and the utility of BASICS to estimate prion loads and investigate persistence and decomposition in the environment. Additionally, since Mte successfully rescued the mice from prion disease, Mte might be used for remediation and decontamination protocols.

Automated image processing of Landsat II digital data for watershed runoff prediction

NASA Technical Reports Server (NTRS)

Sasso, R. R.; Jensen, J. R.; Estes, J. E.

1977-01-01

Digital image processing of Landsat data from a 230 sq km area was examined as a possible means of generating soil cover information for use in the watershed runoff prediction of Kern County, California. The soil cover information included data on brush, grass, pasture lands and forests. A classification accuracy of 94% for the Landsat-based soil cover survey suggested that the technique could be applied to the watershed runoff estimate. However, problems involving the survey of complex mountainous environments may require further attention

Estimation of soil cation exchange capacity using Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS)

NASA Astrophysics Data System (ADS)

Emamgolizadeh, S.; Bateni, S. M.; Shahsavani, D.; Ashrafi, T.; Ghorbani, H.

2015-10-01

The soil cation exchange capacity (CEC) is one of the main soil chemical properties, which is required in various fields such as environmental and agricultural engineering as well as soil science. In situ measurement of CEC is time consuming and costly. Hence, numerous studies have used traditional regression-based techniques to estimate CEC from more easily measurable soil parameters (e.g., soil texture, organic matter (OM), and pH). However, these models may not be able to adequately capture the complex and highly nonlinear relationship between CEC and its influential soil variables. In this study, Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) were employed to estimate CEC from more readily measurable soil physical and chemical variables (e.g., OM, clay, and pH) by developing functional relations. The GEP- and MARS-based functional relations were tested at two field sites in Iran. Results showed that GEP and MARS can provide reliable estimates of CEC. Also, it was found that the MARS model (with root-mean-square-error (RMSE) of 0.318 Cmol+ kg-1 and correlation coefficient (R2) of 0.864) generated slightly better results than the GEP model (with RMSE of 0.270 Cmol+ kg-1 and R2 of 0.807). The performance of GEP and MARS models was compared with two existing approaches, namely artificial neural network (ANN) and multiple linear regression (MLR). The comparison indicated that MARS and GEP outperformed the MLP model, but they did not perform as good as ANN. Finally, a sensitivity analysis was conducted to determine the most and the least influential variables affecting CEC. It was found that OM and pH have the most and least significant effect on CEC, respectively.

Soil Moisture Estimate under Forest using a Semi-empirical Model at P-Band

NASA Astrophysics Data System (ADS)

Truong-Loi, M.; Saatchi, S.; Jaruwatanadilok, S.

2013-12-01

In this paper we show the potential of a semi-empirical algorithm to retrieve soil moisture under forests using P-band polarimetric SAR data. In past decades, several remote sensing techniques have been developed to estimate the surface soil moisture. In most studies associated with radar sensing of soil moisture, the proposed algorithms are focused on bare or sparsely vegetated surfaces where the effect of vegetation can be ignored. At long wavelengths such as L-band, empirical or physical models such as the Small Perturbation Model (SPM) provide reasonable estimates of surface soil moisture at depths of 0-5cm. However for densely covered vegetated surfaces such as forests, the problem becomes more challenging because the vegetation canopy is a complex scattering environment. For this reason there have been only few studies focusing on retrieving soil moisture under vegetation canopy in the literature. Moghaddam et al. developed an algorithm to estimate soil moisture under a boreal forest using L- and P-band SAR data. For their studied area, double-bounce between trunks and ground appear to be the most important scattering mechanism. Thereby, they implemented parametric models of radar backscatter for double-bounce using simulations of a numerical forest scattering model. Hajnsek et al. showed the potential of estimating the soil moisture under agricultural vegetation using L-band polarimetric SAR data and using polarimetric-decomposition techniques to remove the vegetation layer. Here we use an approach based on physical formulation of dominant scattering mechanisms and three parameters that integrates the vegetation and soil effects at long wavelengths. The algorithm is a simplification of a 3-D coherent model of forest canopy based on the Distorted Born Approximation (DBA). The simplified model has three equations and three unknowns, preserving the three dominant scattering mechanisms of volume, double-bounce and surface for three polarized backscattering coefficients: σHH, σVV and σHV. The inversion process, which is not an ill-posed problem, uses the non-linear optimization method of Levenberg-Marquardt and estimates the three model parameters: vegetation aboveground biomass, average soil moisture and surface roughness. The model analytical formulation will be first recalled and sensitivity analyses will be shown. Then some results obtained with real SAR data will be presented and compared to ground estimates.

Bioavailability of xenobiotics in the soil environment.

PubMed

Katayama, Arata; Bhula, Raj; Burns, G Richard; Carazo, Elizabeth; Felsot, Allan; Hamilton, Denis; Harris, Caroline; Kim, Yong-Hwa; Kleter, Gijs; Koedel, Werner; Linders, Jan; Peijnenburg, J G M Willie; Sabljic, Aleksandar; Stephenson, R Gerald; Racke, D Kenneth; Rubin, Baruch; Tanaka, Keiji; Unsworth, John; Wauchope, R Donald

2010-01-01

It is often presumed that all chemicals in soil are available to microorganisms, plant roots, and soil fauna via dermal exposure. Subsequent bioaccumulation through the food chain may then result in exposure to higher organisms. Using the presumption of total availability, national governments reduce environmental threshold levels of regulated chemicals by increasing guideline safety margins. However, evidence shows that chemical residues in the soil environment are not always bioavailable. Hence, actual chemical exposure levels of biota are much less than concentrations present in soil would suggest. Because "bioavailability" conveys meaning that combines implications of chemical sol persistency, efficacy, and toxicity, insights on the magnitude of a chemicals soil bioavailability is valuable. however, soil bioavailability of chemicals is a complex topic, and is affected by chemical properties, soil properties, species exposed, climate, and interaction processes. In this review, the state-of-art scientific basis for bioavailability is addressed. Key points covered include: definition, factors affecting bioavailability, equations governing key transport and distributive kinetics, and primary methods for estimating bioavailability. Primary transport mechanisms in living organisms, critical to an understanding of bioavailability, also presage the review. Transport of lipophilic chemicals occurs mainly by passive diffusion for all microorganisms, plants, and soil fauna. Therefore, the distribution of a chemical between organisms and soil (bioavailable proportion) follows partition equilibrium theory. However, a chemical's bioavailability does not always follow partition equilibrium theory because of other interactions with soil, such as soil sorption, hysteretic desorption, effects of surfactants in pore water, formation of "bound residue", etc. Bioassays for estimating chemical bioavailability have been introduced with several targeted endpoints: microbial degradation, uptake by higher plants and soil fauna, and toxicity to organisms. However, there bioassays are often time consuming and laborious. Thus, mild extraction methods have been employed to estimate bioavailability of chemicals. Mild methods include sequential extraction using alcohols, hexane/water, supercritical fluids (carbon dioxide), aqueous hydroxypropyl-beta-cyclodextrin extraction, polymeric TENAX beads extraction, and poly(dimethylsiloxane)-coated solid-phase microextraction. It should be noted that mild extraction methods may predict bioavailability at the moment when measurements are carried out, but not the changes in bioavailability that may occur over time. Simulation models are needed to estimate better bioavailability as a function of exposure time. In the past, models have progressed significantly by addressing each group of organisms separately: microbial degradation, plant uptake via evapotranspiration processes, and uptake of soil fauna in their habitat. This approach has been used primarily because of wide differences in the physiology and behaviors of such disparate organisms. However, improvement of models is badly needed, Particularly to describe uptake processes by plant and animals that impinge on bioavailability. Although models are required to describe all important factors that may affect chemical bioavailability to individual organisms over time (e.g., sorption/desorption to soil/sediment, volatilization, dissolution, aging, "bound residue" formation, biodegradation, etc.), these models should be simplified, when possible, to limit the number of parameters to the practical minimum. Although significant scientific progress has been made in understanding the complexities in specific methodologies dedicated to determining bioavailability, no method has yet emerged to characterized bioavailability across a wide range of chemicals, organisms, and soils/sediments. The primary aim in studying bioavailability is to define options for addressing bioremediation or environmental toxicity (risk assessment), and that is unlikely to change. Because of its importance in estimating research is needed to more comprehensively address the key environmental issue of "bioavailability of chemicals in soil/sediment."

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.

Underestimation of boreal soil carbon stocks by mathematical soil carbon models linked to soil nutrient status

NASA Astrophysics Data System (ADS)

Ťupek, Boris; Ortiz, Carina A.; Hashimoto, Shoji; Stendahl, Johan; Dahlgren, Jonas; Karltun, Erik; Lehtonen, Aleksi

2016-08-01

Inaccurate estimate of the largest terrestrial carbon pool, soil organic carbon (SOC) stock, is the major source of uncertainty in simulating feedback of climate warming on ecosystem-atmosphere carbon dioxide exchange by process-based ecosystem and soil carbon models. Although the models need to simplify complex environmental processes of soil carbon sequestration, in a large mosaic of environments a missing key driver could lead to a modeling bias in predictions of SOC stock change.We aimed to evaluate SOC stock estimates of process-based models (Yasso07, Q, and CENTURY soil sub-model v4) against a massive Swedish forest soil inventory data set (3230 samples) organized by a recursive partitioning method into distinct soil groups with underlying SOC stock development linked to physicochemical conditions.For two-thirds of measurements all models predicted accurate SOC stock levels regardless of the detail of input data, e.g., whether they ignored or included soil properties. However, in fertile sites with high N deposition, high cation exchange capacity, or moderately increased soil water content, Yasso07 and Q models underestimated SOC stocks. In comparison to Yasso07 and Q, accounting for the site-specific soil characteristics (e. g. clay content and topsoil mineral N) by CENTURY improved SOC stock estimates for sites with high clay content, but not for sites with high N deposition.Our analysis suggested that the soils with poorly predicted SOC stocks, as characterized by the high nutrient status and well-sorted parent material, indeed have had other predominant drivers of SOC stabilization lacking in the models, presumably the mycorrhizal organic uptake and organo-mineral stabilization processes. Our results imply that the role of soil nutrient status as regulator of organic matter mineralization has to be re-evaluated, since correct SOC stocks are decisive for predicting future SOC change and soil CO2 efflux.

Field-scale soil moisture space-time geostatistical modeling for complex Palouse landscapes in the inland Pacific Northwest

NASA Astrophysics Data System (ADS)

Chahal, M. K.; Brown, D. J.; Brooks, E. S.; Campbell, C.; Cobos, D. R.; Vierling, L. A.

2012-12-01

Estimating soil moisture content continuously over space and time using geo-statistical techniques supports the refinement of process-based watershed hydrology models and the application of soil process models (e.g. biogeochemical models predicting greenhouse gas fluxes) to complex landscapes. In this study, we model soil profile volumetric moisture content for five agricultural fields with loess soils in the Palouse region of Eastern Washington and Northern Idaho. Using a combination of stratification and space-filling techniques, we selected 42 representative and distributed measurement locations in the Cook Agronomy Farm (Pullman, WA) and 12 locations each in four additional grower fields that span the precipitation gradient across the Palouse. At each measurement location, soil moisture was measured on an hourly basis at five different depths (30, 60, 90, 120, and 150 cm) using Decagon 5-TE/5-TM soil moisture sensors (Decagon Devices, Pullman, WA, USA). This data was collected over three years for the Cook Agronomy Farm and one year for each of the grower fields. In addition to ordinary kriging, we explored the correlation of volumetric water content with external, spatially exhaustive indices derived from terrain models, optical remote sensing imagery, and proximal soil sensing data (electromagnetic induction and VisNIR penetrometer)

A genetic-algorithm approach for assessing the liquefaction potential of sandy soils

NASA Astrophysics Data System (ADS)

Sen, G.; Akyol, E.

2010-04-01

The determination of liquefaction potential is required to take into account a large number of parameters, which creates a complex nonlinear structure of the liquefaction phenomenon. The conventional methods rely on simple statistical and empirical relations or charts. However, they cannot characterise these complexities. Genetic algorithms are suited to solve these types of problems. A genetic algorithm-based model has been developed to determine the liquefaction potential by confirming Cone Penetration Test datasets derived from case studies of sandy soils. Software has been developed that uses genetic algorithms for the parameter selection and assessment of liquefaction potential. Then several estimation functions for the assessment of a Liquefaction Index have been generated from the dataset. The generated Liquefaction Index estimation functions were evaluated by assessing the training and test data. The suggested formulation estimates the liquefaction occurrence with significant accuracy. Besides, the parametric study on the liquefaction index curves shows a good relation with the physical behaviour. The total number of misestimated cases was only 7.8% for the proposed method, which is quite low when compared to another commonly used method.

Using global sensitivity analysis to understand higher order interactions in complex models: an application of GSA on the Revised Universal Soil Loss Equation (RUSLE) to quantify model sensitivity and implications for ecosystem services management in Costa Rica

NASA Astrophysics Data System (ADS)

Fremier, A. K.; Estrada Carmona, N.; Harper, E.; DeClerck, F.

2011-12-01

Appropriate application of complex models to estimate system behavior requires understanding the influence of model structure and parameter estimates on model output. To date, most researchers perform local sensitivity analyses, rather than global, because of computational time and quantity of data produced. Local sensitivity analyses are limited in quantifying the higher order interactions among parameters, which could lead to incomplete analysis of model behavior. To address this concern, we performed a GSA on a commonly applied equation for soil loss - the Revised Universal Soil Loss Equation. USLE is an empirical model built on plot-scale data from the USA and the Revised version (RUSLE) includes improved equations for wider conditions, with 25 parameters grouped into six factors to estimate long-term plot and watershed scale soil loss. Despite RUSLE's widespread application, a complete sensitivity analysis has yet to be performed. In this research, we applied a GSA to plot and watershed scale data from the US and Costa Rica to parameterize the RUSLE in an effort to understand the relative importance of model factors and parameters across wide environmental space. We analyzed the GSA results using Random Forest, a statistical approach to evaluate parameter importance accounting for the higher order interactions, and used Classification and Regression Trees to show the dominant trends in complex interactions. In all GSA calculations the management of cover crops (C factor) ranks the highest among factors (compared to rain-runoff erosivity, topography, support practices, and soil erodibility). This is counter to previous sensitivity analyses where the topographic factor was determined to be the most important. The GSA finding is consistent across multiple model runs, including data from the US, Costa Rica, and a synthetic dataset of the widest theoretical space. The three most important parameters were: Mass density of live and dead roots found in the upper inch of soil (C factor), slope angle (L and S factor), and percentage of land area covered by surface cover (C factor). Our findings give further support to the importance of vegetation as a vital ecosystem service provider - soil loss reduction. Concurrent, progress is already been made in Costa Rica, where dam managers are moving forward on a Payment for Ecosystem Services scheme to help keep private lands forested and to improve crop management through targeted investments. Use of complex watershed models, such as RUSLE can help managers quantify the effect of specific land use changes. Moreover, effective land management of vegetation has other important benefits, such as bundled ecosystem services (e.g. pollination, habitat connectivity, etc) and improvements of communities' livelihoods.

Agricultural soil greenhouse gas emissions: a review of national inventory methods.

PubMed

Lokupitiya, Erandathie; Paustian, Keith

2006-01-01

Parties to the United Nations Framework Convention on Climate Change (UNFCCC) are required to submit national greenhouse gas (GHG) inventories, together with information on methods used in estimating their emissions. Currently agricultural activities contribute a significant portion (approximately 20%) of global anthropogenic GHG emissions, and agricultural soils have been identified as one of the main GHG source categories within the agricultural sector. However, compared to many other GHG sources, inventory methods for soils are relatively more complex and have been implemented only to varying degrees among member countries. This review summarizes and evaluates the methods used by Annex 1 countries in estimating CO2 and N2O emissions in agricultural soils. While most countries utilize the Intergovernmental Panel on Climate Change (IPCC) default methodology, several Annex 1 countries are developing more advanced methods that are tailored for specific country circumstances. Based on the latest national inventory reporting, about 56% of the Annex 1 countries use IPCC Tier 1 methods, about 26% use Tier 2 methods, and about 18% do not estimate or report N2O emissions from agricultural soils. More than 65% of the countries do not report CO2 emissions from the cultivation of mineral soils, organic soils, or liming, and only a handful of countries have used country-specific, Tier 3 methods. Tier 3 methods usually involve process-based models and detailed, geographically specific activity data. Such methods can provide more robust, accurate estimates of emissions and removals but require greater diligence in documentation, transparency, and uncertainty assessment to ensure comparability between countries. Availability of detailed, spatially explicit activity data is a major constraint to implementing higher tiered methods in many countries.

Stable isotopic constraints on global soil organic carbon turnover

NASA Astrophysics Data System (ADS)

Wang, Chao; Houlton, Benjamin Z.; Liu, Dongwei; Hou, Jianfeng; Cheng, Weixin; Bai, Edith

2018-02-01

Carbon dioxide release during soil organic carbon (SOC) turnover is a pivotal component of atmospheric CO2 concentrations and global climate change. However, reliably measuring SOC turnover rates on large spatial and temporal scales remains challenging. Here we use a natural carbon isotope approach, defined as beta (β), which was quantified from the δ13C of vegetation and soil reported in the literature (176 separate soil profiles), to examine large-scale controls of climate, soil physical properties and nutrients over patterns of SOC turnover across terrestrial biomes worldwide. We report a significant relationship between β and calculated soil C turnover rates (k), which were estimated by dividing soil heterotrophic respiration rates by SOC pools. ln( - β) exhibits a significant linear relationship with mean annual temperature, but a more complex polynomial relationship with mean annual precipitation, implying strong-feedbacks of SOC turnover to climate changes. Soil nitrogen (N) and clay content correlate strongly and positively with ln( - β), revealing the additional influence of nutrients and physical soil properties on SOC decomposition rates. Furthermore, a strong (R2 = 0.76; p < 0.001) linear relationship between ln( - β) and estimates of litter and root decomposition rates suggests similar controls over rates of organic matter decay among the generalized soil C stocks. Overall, these findings demonstrate the utility of soil δ13C for independently benchmarking global models of soil C turnover and thereby improving predictions of multiple global change influences over terrestrial C-climate feedback.

Selective Separation and Determination of Heavy Metals (Cd, Pb, Cr) Speciation Forms from Hortic Antrosols

NASA Astrophysics Data System (ADS)

Bulgariu, D.; Bulgariu, L.

2009-04-01

The speciation, inter-phases distribution and biodisponibility of heavy metals in soils represent one of main problem of environmental geochemistry and agro-chemistry. This problem is very important in case of hortic antrosols (soils from glasshouses) for the elimination of agricultural products (fruits, vegetables) contamination with heavy metals. In soils from glass houses, the speciation and inter-phases distribution processes of heavy metals have a particular dynamic, different in comparison with those from non-protected soils. The predominant distribution forms of heavy metals in such soils types are: complexes with low mass organic molecules, organic-mineral complexes, complexes with inorganic ligands (hydroxide-complexes, carbonate-complexes, sulphate-complexes, etc.) and basic salts. All of these have high stabilities in conditions of soils from glass houses, and in consequence, the separation and determination of speciation forms (which is directly connected with biodisponibility of heavy metals) by usual methods id very difficult and has a high uncertain degree. In this study is presented an original method for the selective separation and differentiation of speciation forms of heavy metals from glass houses soils, which is based by the combination of solid-liquid sequential extraction (SPE) with the extraction in aqueous polymer-inorganic salt two-phase systems (ABS). The soil samples used for this study have been sampled from three different locations (glass houses from Iasi, Barlad and Bacau - Romania) where the vegetables cultivation have bee performed by three different technologies. In this way was estimated the applicability and the analytical limits of method proposed by as, in function of the chemical-mineralogical and physical-chemical characteristics of soils. As heavy metals have been studied cadmium, lead and chromium, all being known for their high toxicity. The procedure used for the selective separation and differentiation of speciation forms of heavy metals from glass houses soils has two main steps: (i) non-destructive separation of chemical-mineralogical associations and aggregates from soils samples - for this the separation method with heavy liquids (bromophorme) and isodynamic magnetic method have been used; (ii) sequential extraction of heavy metals from soil fractions separated in the first step, by using combined SPE-ABS procedure. For the preparation of combined extraction systems was used polyethylene glycol (with different molecular mass: 2000, 4000 and 8000). As phase-forming inorganic salts and as selective extracting agents we have used different usual inorganic reagents. The type and concentration of phase-forming salts have been selected in function of, both nature of extracted heavy metals and chemical-mineralogical characteristics of soil samples. The experimental parameters investigated in this study are: molecular mass of polyethylene glycol and the concentration of polymeric solutions, nature and concentration of phase-forming salts, nature and concentration of extracting agents, pH in extraction system phase, type of extracted heavy metals, type of speciation forms of heavy metals and their concentrations. All these factors can influence significantly the efficiency and the selectivity of separation process. The experimental results have indicate that the combined SPE-ABS extraction systems have better separation efficiency, in comparison with traditional SPE systems and ca realized a accurate discrimination between speciation forms of heavy metals from soils. Under these conditions, the estimation of inter-phases distribution and biodisponibility of heavy metals has a high precision. On the other hand, when the combined SPE-ABS systems are used, the concomitant extraction of the elements from the same geochemical association with studied heavy metals (inevitable phenomena in case of separation by SPE procedures) is significant diminished. This increases the separation selectivity and facilitated the more accurate determination of speciation forms concentration. By adequate selection of extraction conditions can be realized the selective separation of organic-mineral complexes, which will permit to perform detailed studies about the structure and chemical composition of these. Acknowledgments The authors would like to acknowledge the financial support from Romanian Ministry of Education and Research (Project PNCDI 2-D5 no. 51045/07).

Complex Adaptive Systems, soil degradation and land sensitivity to desertification: A multivariate assessment of Italian agro-forest landscape.

PubMed

Salvati, Luca; Mavrakis, Anastasios; Colantoni, Andrea; Mancino, Giuseppe; Ferrara, Agostino

2015-07-15

Degradation of soils and sensitivity of land to desertification are intensified in last decades in the Mediterranean region producing heterogeneous spatial patterns determined by the interplay of factors such as climate, land-use changes, and human pressure. The present study hypothesizes that rising levels of soil degradation and land sensitivity to desertification are reflected into increasingly complex (and non-linear) relationships between environmental and socioeconomic variables. To verify this hypothesis, the Complex Adaptive Systems (CAS) framework was used to explore the spatiotemporal dynamics of eleven indicators derived from a standard assessment of soil degradation and land sensitivity to desertification in Italy. Indicators were made available on a detailed spatial scale (773 agricultural districts) for various years (1960, 1990, 2000 and 2010) and analyzed through a multi-dimensional exploratory data analysis. Our results indicate that the number of significant pair-wise correlations observed between indicators increased with the level of soil and land degradation, although with marked differences between northern and southern Italy. 'Fast' and 'slow' factors underlying soil and land degradation, and 'rapidly-evolving' or 'locked' agricultural districts were identified according to the rapidity of change estimated for each of the indicators studied. In southern Italy, 'rapidly-evolving' districts show a high level of soil degradation and land sensitivity to desertification during the whole period of investigation. On the contrary, those districts in northern Italy are those experiencing a moderate soil degradation and land sensitivity to desertification with the highest increase in the level of sensitivity over time. The study framework contributes to the assessment of complex local systems' dynamics in affluent but divided countries. Results may inform thematic strategies for the mitigation of land and soil degradation in the framework of action plans to combat desertification. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparison of evaporative fluxes from porous surfaces resolved by remotely sensed and in-situ temperature and soil moisture data

NASA Astrophysics Data System (ADS)

Wallen, B.; Trautz, A.; Smits, K. M.

2014-12-01

The estimation of evaporation has important implications in modeling climate at the regional and global scale, the hydrological cycle and estimating environmental stress on agricultural systems. In field and laboratory studies, remote sensing and in-situ techniques are used to collect thermal and soil moisture data of the soil surface and subsurface which is then used to estimate evaporative fluxes, oftentimes using the sensible heat balance method. Nonetheless, few studies exist that compare the methods due to limited data availability and the complexity of many of the techniques, making it difficult to understand flux estimates. This work compares different methods used to quantify evaporative flux based on remotely sensed and in-situ temperature and soil moisture data. A series of four laboratory experiments were performed under ambient and elevated air temperature conditions with homogeneous and heterogeneous soil configurations in a small two-dimensional soil tank interfaced with a small wind tunnel apparatus. The soil tank and wind tunnel were outfitted with a suite of sensors that measured soil temperature (surface and subsurface), air temperature, soil moisture, and tank weight. Air and soil temperature measurements were obtained using infrared thermography, heat pulse sensors and thermistors. Spatial and temporal thermal data were numerically inverted to obtain the evaporative flux. These values were then compared with rates of mass loss from direct weighing of the samples. Results demonstrate the applicability of different methods under different surface boundary conditions; no one method was deemed most applicable under every condition. Infrared thermography combined with the sensible heat balance method was best able to determine evaporative fluxes under stage 1 conditions while distributed temperature sensing combined with the sensible heat balance method best determined stage 2 evaporation. The approaches that appear most promising for determining the surface energy balance incorporates soil moisture rate of change over time and atmospheric conditions immediately above the soil surface. An understanding of the fidelity regarding predicted evaporation rates based upon stages of evaporation enables a more deliberate selection of the suite of sensors required for data collection.

Contemporary overview of soil creep phenomenon

NASA Astrophysics Data System (ADS)

Kaczmarek, Łukasz; Dobak, Paweł

2017-06-01

Soil creep deformation refers to phenomena which take place in many areas and research in this field of science is rich and constantly developing. The article presents an analysis of the literature on soil creep phenomena. In light of the complexity of the issues involved and the wide variety of perspectives taken, this attempt at systematization seeks to provide a reliable review of current theories and practical approaches concerning creep deformation. The paper deals with subjects such as definition of creep, creep genesis, basic description of soil creep dynamics deformation, estimation of creep capabilities, various fields of creep occurrence, and an introduction to creep modeling. Furthermore, based on this analysis, a new direction for research is proposed.

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review

PubMed Central

Zhang, Dianjun; Zhou, Guoqing

2016-01-01

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research. PMID:27548168

Estimation of Soil Moisture from Optical and Thermal Remote Sensing: A Review.

PubMed

Zhang, Dianjun; Zhou, Guoqing

2016-08-17

As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research.

Experimental considerations in metal mobilization from soil by chelating ligands: The influence of soil-solution ratio and pre-equilibration - A case study on Fe acquisition by phytosiderophores.

PubMed

Schenkeveld, W D C; Kimber, R L; Walter, M; Oburger, E; Puschenreiter, M; Kraemer, S M

2017-02-01

The efficiency of chelating ligands in mobilizing metals from soils and sediments is generally examined under conditions remote from those under which they are exuded or applied in the field. This may lead to incorrect estimations of the mobilizing efficiency. The aim of this study was to establish the influence of the soil solution ratio (SSR) and pre-equilibration with electrolyte solution on metal mobilization and metal displacement. For this purpose a series of interaction experiments with a calcareous clay soil and a biogenic chelating agent, the phytosiderophore 2'-deoxymugineic acid (DMA) were carried out. For a fixed ligand concentration, the SSR had a strong influence on metal mobilization and displacement. Metal complexation was faster at higher SSR. Reactive pools of metals that were predominantly mobilized at SSR 6 (in this case Cu), became depleted at SSR 0.1, whereas metals that were marginally mobilized at SSR 6, were dominantly mobilized at SSR 0.1 (in this case Fe), because of large soil reactive pools. For a fixed "amount of ligand"-to-"amount of soil"-ratio, metal complexation scaled linearly with the SSR. The efficiency of ligands in mobilizing metals under field conditions can be predicted with batch experiments, as long as the ligand-to-soil-ratio is matched. In most previously reported studies this criterion was not met. Equivalent metal-complex concentrations under field conditions can be back-calculated using adsorption isotherms for the respective metal-complexes. Drying and dry storage created labile pools of Fe, Cu and Zn, which were rapidly mobilized upon addition of DMA solution to dry soil. Pre-equilibration decreased these labile pools, leading to smaller concentrations of these metals during initial mobilization, but did not reduce the lag time between ligand addition and onset of microbial degradation of the metal-complexes. Hence SSR and pre-equilibration should be carefully considered when testing the metal mobilizing efficiency of chelating ligands. Copyright © 2016. Published by Elsevier B.V.

Soil characteristics of landslides on Mount Elgon (Uganda): implications for estimating their age

NASA Astrophysics Data System (ADS)

Van Eynde, Elise; Dondeyne, Stefaan; Isabirye, Moses; Deckers, Jozef; Poesen, Jean

2017-04-01

The slopes of Mount Elgon, a complex volcano at the border between Uganda and Kenya, are frequently affected by landslides with disastrous effects on the livelihood of its population. Since local people greatly depend on the land for crop production, we examined if and how fast physico-chemical characteristics in landslide scars recover. A chronosequence of 18 landslides covering a period of 103 years was sampled in order to explore differences between topsoil within and outside landslide scars. For each landslide, two topsoil samples were taken within the landslide and two in nearby undisturbed soils to compare their physico-chemical characteristics. No differences were found for available P, Ca2+, Mg2+ content or for the fine earth texture. Recent landslides had however lower content of soil organic carbon (OC) and K+, and higher content of rock fragments and Na+ than the adjacent soils. Soil OC content increased significantly with age and reached levels of the corresponding undisturbed soils after ca. 60 years. Older landslides had even higher OC contents than soils adjacent to the landslide. Hence landslide scars act as local carbon sink. We suggest that the occurrence of rock fragments in the topsoil is a useful indicator for mapping past landslides. Moreover, the difference in soil OC content between landslide scars and adjacent soil could be used for estimating the age of landslides in data-poor regions.

Superfund Record of Decision (EPA Region 9): Watkins-Johnson (Stewart Division), Scotts Valley, California (first remedial action), Final report, June 29, 1990

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

Not Available

The Watkins-Johnson site is an active research and development, manufacturing, and industrial complex in Santa Cruz County, five miles north of Santa Cruz, California. The Watkins-Johnson Company has owned and operated the complex since 1963, conducting such activities as: metal machining, degreasing, metal plating, and photo laboratory activities. During these activities, a variety of organics, inorganics and metals were used. The primary contaminants of concern affecting the soil and ground water are VOCs including PCE and TCE, and metals including silver. The selected remedial action for the site includes soil vapor (vacuum) extraction with pretreatment of extracted vapors using GACmore » prior to ambient discharge; capping and grading contaminated soil areas to minimize the potential for mobilization of soil contaminants to the ground water; installing infiltration leachfields to prevent offsite migration of ground water contaminants in the perched zone; installing gravity drains to transfer the contaminated ground water from the perched zone to the regional aquifer zone for subsequent extraction; ground water pumping and onsite treatment to remove contamination from both the perched and regional zones using GAC adsorption with offsite regeneration of spent carbon. The estimated present worth cost for this remedial action is $2,156,243, which includes an estimated annual O and M cost of $167,820.« less

Concentrations, profiles, and estimated human exposures for polychlorinated dibenzo-p-dioxins and dibenzofurans from electronic waste recycling facilities and a chemical industrial complex in Eastern China.

PubMed

Ma, Jing; Kannan, Kurunthachalam; Cheng, Jinping; Horii, Yuichi; Wu, Qian; Wang, Wenhua

2008-11-15

Environmental pollution arising from electronic waste (e-waste) disposal and recycling has received considerable attention in recent years. Treatment, at low temperatures, of e-wastes that contain polyvinylchloride and related polymers can release polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). Although several studies have reported trace metals and polybrominated diphenyl ethers (PBDEs) released from e-waste recycling operations, environmental contamination and human exposure to PCDD/Fs from e-waste recycling operations are less well understood. In this study, electronic shredder waste and dust from e-waste facilities, and leaves and surface soil collected in the vicinity of a large scale e-waste recycling facility in Taizhou, Eastern China, were analyzed for total PCDD/ Fs including 2,3,7,8-substituted congeners. We also determined PCDD/Fs in surface agricultural soils from several provinces in China for comparison with soils from e-waste facilities. Concentrations of total PCDD/Fs were high in all of the matrices analyzed and ranged from 30.9 to 11400 pg/g for shredder waste, 3460 to 9820 pg/g dry weight for leaves, 2560 to 148000 pg/g dry weight for workshop-floor dust, and 854 to 10200 pg/g dry weight for soils. We also analyzed surface soils from a chemical industrial complex (a coke-oven plant, a coal-fired power plant, and a chlor-alkali plant) in Shanghai. Concentrations of total PCDD/Fs in surface soil (44.5-531 pg/g dry wt) from the chemical industrial complex were lower than the concentrations found in soils from e-waste recycling plants, but higher than the concentrations found in agricultural soils. Agricultural soils from six cities in China contained low levels (3.44-33.8 pg/g dry wt) of total PCDD/Fs. Profiles of dioxin toxic equivalents (TEQs) of 2,3,7,8-PCDD/Fs in soils from e-waste facilities in Taizhou differed from the profiles found in agricultural soils. The estimated daily intakes of TEQs of PCDD/ Fs via soil/dust ingestion and dermal exposure (2.3 and 0.363 pg TEQ/kg bw/day for children and adults, respectively) were 2 orders of magnitude higher in people at e-waste recycling facilities than in people at the chemical industrial site (0.021 and 0.0053 pg TEQ/kg bw/day for children and adults, respectively), implying greater health risk for humans from dioxin exposures at e-waste recycling facilities. The calculated TEQ exposures for e-waste workers from dust and soil ingestion alone were 2-3 orders of magnitude greater than the exposures from soils in reference locations.

Investigating local controls on temporal stability of soil water content using sensor network data and an inverse modeling approach

NASA Astrophysics Data System (ADS)

Qu, W.; Bogena, H. R.; Huisman, J. A.; Martinez, G.; Pachepsky, Y. A.; Vereecken, H.

2013-12-01

Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and temporal stability presents substantial interest. The objective of this work was to assess the effect of soil hydraulic parameters on the temporal stability. The inverse modeling based on large observed time series SWC with in-situ sensor network was used to estimate the van Genuchten-Mualem (VGM) soil hydraulic parameters in a small grassland catchment located in western Germany. For the inverse modeling, the shuffled complex evaluation (SCE) optimization algorithm was coupled with the HYDRUS 1D code. We considered two cases: without and with prior information about the correlation between VGM parameters. The temporal stability of observed SWC was well pronounced at all observation depths. Both the spatial variability of SWC and the robustness of temporal stability increased with depth. Calibrated models both with and without prior information provided reasonable correspondence between simulated and measured time series of SWC. Furthermore, we found a linear relationship between the mean relative difference (MRD) of SWC and the saturated SWC (θs). Also, the logarithm of saturated hydraulic conductivity (Ks), the VGM parameter n and logarithm of α were strongly correlated with the MRD of saturation degree for the prior information case, but no correlation was found for the non-prior information case except at the 50cm depth. Based on these results we propose that establishing relationships between temporal stability and spatial variability of soil properties presents a promising research avenue for a better understanding of the controls on soil moisture variability. Correlation between Mean Relative Difference of soil water content (or saturation degree) and inversely estimated soil hydraulic parameters (log10(Ks), log10(α), n, and θs) at 5-cm, 20-cm and 50-cm depths. Solid circles represent parameters estimated by using prior information; open circles represent parameters estimated without using prior information.

Daily estimates of soil ingestion in children.

PubMed Central

Stanek, E J; Calabrese, E J

1995-01-01

Soil ingestion estimates play an important role in risk assessment of contaminated sites, and estimates of soil ingestion in children are of special interest. Current estimates of soil ingestion are trace-element specific and vary widely among elements. Although expressed as daily estimates, the actual estimates have been constructed by averaging soil ingestion over a study period of several days. The wide variability has resulted in uncertainty as to which method of estimation of soil ingestion is best. We developed a methodology for calculating a single estimate of soil ingestion for each subject for each day. Because the daily soil ingestion estimate represents the median estimate of eligible daily trace-element-specific soil ingestion estimates for each child, this median estimate is not trace-element specific. Summary estimates for individuals and weeks are calculated using these daily estimates. Using this methodology, the median daily soil ingestion estimate for 64 children participating in the 1989 Amherst soil ingestion study is 13 mg/day or less for 50% of the children and 138 mg/day or less for 95% of the children. Mean soil ingestion estimates (for up to an 8-day period) were 45 mg/day or less for 50% of the children, whereas 95% of the children reported a mean soil ingestion of 208 mg/day or less. Daily soil ingestion estimates were used subsequently to estimate the mean and variance in soil ingestion for each child and to extrapolate a soil ingestion distribution over a year, assuming that soil ingestion followed a log-normal distribution. Images Figure 1. Figure 2. Figure 3. Figure 4. PMID:7768230

The effect of measured and estimated soil hydraulic properties on simulated water regime in the analysis of grapevine adaptability to future climate

NASA Astrophysics Data System (ADS)

Bonfante, Antonello; Alfieri, Silvia Maria; Agrillo, Antonietta; Dragonetti, Giovanna; Mileti, Antonio; Monaco, Eugenia; De Lorenzi, Francesca

2013-04-01

In the last years many research works have been addressed to evaluate the impact of future climate on crop productivity and plant water use at different spatial scales (global, regional, field) by means of simulation models of agricultural crop systems. Most of these approaches use estimated soil hydraulic properties, through pedotransfer functions (PTF). This choice is related to soil data availability: soil data bases lack measured soil hydraulic properties, but generally they contain information that allow the application of PTF . Although the reliability of the predicted future climate scenarios cannot be immediately validated, we address to evaluate the effects of a simplification of the soil system by using PTF. Thus we compare simulations performed with measured soil hydraulic properties versus simulations carried out with estimated properties. The water regimes resulting from the two procedures are evaluated with respect to crop adaptability to future climate. In particular we will examine if the two procedures bring about different seasonal and spatial variations in the soil water regime patterns, and if these patterns influence adaptation options. The present case study uses the agro-hydrological model SWAP (soil-water-atmosphere and plant) and studies future adaptability of grapevine. The study area is a viticultural area of Southern Italy (Valle Telesina, BN) devoted to the production of high quality wines (DOC and DOCG), and characterized by a complex geomorphology and pedology. The future climate scenario (2021-2050) was constructed applying statistical downscaling techniques to GCMs scenarios. The moisture regime for 25 soils of the selected study area was calculated by means of SWAP model, using both measured and estimated soil hydraulic properties. In the simulation, the upper boundary conditions were derived from the regional climate scenarios. Unit gradient in soil water potential was set as lower boundary condition. Crop-specific input data and model parameters were estimated on the basis of scientific literature and assumed to be generically representative of the species. From the output of the simulation runs, the relative evapotranspiration deficit (or Crop Water Stress Index - CWSI) of the soil units was calculated. Since CWSI is considered an important indicator of the qualitative grapevine responses, its pattern in both simulation procedures has been evaluated. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Cancer risk assessment of polycyclic aromatic hydrocarbon contaminated soils determined using bioassay-derived levels of benzo[a]pyrene equivalents.

PubMed

Lemieux, Christine L; Long, Alexandra S; Lambert, Iain B; Lundstedt, Staffan; Tysklind, Mats; White, Paul A

2015-02-03

Here we evaluate the excess lifetime cancer risk (ELCR) posed by 10 PAH-contaminated soils using (i) the currently advocated, targeted chemical-specific approach that assumes dose additivity for carcinogenic PAHs and (ii) a bioassay-based approach that employs the in vitro mutagenic activity of the soil fractions to determine levels of benzo[a]pyrene equivalents and, by extension, ELCR. Mutagenic activity results are presented in our companion paper.1 The results show that ELCR values for the PAH-containing fractions, determined using the chemical-specific approach, are generally (i.e., 8 out of 10) greater than those calculated using the bioassay-based approach; most are less than 5-fold greater. Only two chemical-specific ELCR estimates are less than their corresponding bioassay-derived values; differences are less than 10%. The bioassay-based approach, which permits estimation of ELCR without a priori knowledge of mixture composition, proved to be a useful tool to evaluate the chemical-specific approach. The results suggest that ELCR estimates for complex PAH mixtures determined using a targeted, chemical-specific approach are reasonable, albeit conservative. Calculated risk estimates still depend on contentious PEFs and cancer slope factors. Follow-up in vivo mutagenicity assessments will be required to validate the results and their relevance for human health risk assessment of PAH-contaminated soils.

The Effects of Wideband Complex Electromagnetic Properties of Soils on Geophysical Sensor Performance

NASA Astrophysics Data System (ADS)

North, Ryan Elliot

Common near-surface geophysical methods such as time domain electromagnetic induction (TDEM) metal detectors and ground penetrating radar (GPR) suffer performance degradation as a function of site specific complex electromagnetic soil properties (permittivity, permeability and conductivity). Knowledge of these soil properties from the kHz to the GHz frequency range can be used to predict and improve sensor performance. A prototype permittivity probe was used to measure the complex permittivity and conductivity of the soil and calculate the GPR velocity and attenuation of the from the in-situ measurements. The prototype probe was capable of accurately predicting the GPR velocities when compared with the GPR measurement and could easily predict the attenuation which is difficult to determine from actual GPR data. Unfortunately the prototype probe here has one primarily deficiency which is the assumption that the soils where it is used are non-magnetic. To illustrate the problems with using this probe in magnetic soils I made soil analogues from commercially available magnetite and crushed silica powder then measured them using a common open ended coaxial probe followed by measurements with coaxial air- line fixture which can also calculate magnetic properties. The calculated permittivities are up to twice as high when measured with the coaxial probe as they are when measured with a coaxial airline fixture which will lead to incorrect estimates of GPR velocity and attenuation. To address the performance issues of metal detectors in magnetically viscous soils I created a magnetically viscous soil analogue that could be used in mine detection training lanes instead of importing soil from sites exhibiting magnetic viscosity. Five commercially available iron oxide nano-powders were tested as additives to create the soil analogues by measuring the magnetic viscosity of these iron oxides with a new prototype instrument and compared them to samples of magnetically viscous soils collected at sites around the world. Three of the iron oxides exhibited comparable magnetic viscosities to the naturally occurring soil samples. One was selected to make a soil analogue by mixing it with crushed silica. The resulting magnetic susceptibilities compared favorably with those of the natural soil samples.

Closing the water balance with cosmic-ray soil moisture measurements and assessing their relation to evapotranspiration in two semiarid watersheds

NASA Astrophysics Data System (ADS)

Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.

2016-01-01

Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate-scale soil moisture estimates from the cosmic-ray neutron sensing (CRNS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRNS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower, and runoff flumes used to close the water balance. We found a very good agreement between the CRNS method and the distributed sensor network (root mean square error (RMSE) of 0.009 and 0.013 m3 m-3 at SRER and JER, respectively) at the hourly timescale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was also obtained in soil moisture changes estimated from the CRNS and watershed water balance methods (RMSE of 0.001 and 0.082 m3 m-3 at SRER and JER, respectively), with deviations due to bypassing of the CRNS measurement depth during large rainfall events. Once validated, the CRNS soil moisture estimates were used to investigate hydrological processes at the footprint scale at each site. Through the computation of the water balance, we showed that drier-than-average conditions at SRER promoted plant water uptake from deeper soil layers, while the wetter-than-average period at JER resulted in percolation towards deeper soils. The CRNS measurements were then used to quantify the link between evapotranspiration and soil moisture at a commensurate scale, finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US.

Selective determination of heavy metals (Cd, Pb, Cr) speciation forms from hortic anthrosols

NASA Astrophysics Data System (ADS)

Bulgariu, Dumitru; Bulgariu, Laura; Filipov, Feodor; Astefanei, Dan; Stoleru, Vasile

2010-05-01

In soils from glass houses, the speciation and inter-phases distribution processes of heavy metals have a particular dynamic, different in comparison with those from non-protected soils. The predominant distribution forms of heavy metals in such soils types are: complexes with low mass organic molecules, organic-mineral complexes, complexes with inorganic ligands (hydroxide-complexes, carbonate-complexes, sulphate-complexes, etc.) and basic salts. All of these have high stabilities in conditions of soils from glass houses, and in consequence, the separation and determination of speciation forms (which is directly connected with biodisponibility of heavy metals) by usual methods id very difficult and has a high uncertain degree. In this study is presented an original method for the selective separation and differentiation of speciation forms of heavy metals from glass houses soils, which is based by the combination of solid-liquid sequential extraction (SPE) with the extraction in aqueous polymer-inorganic salt two-phase systems (ABS). The soil samples used for this study have been sampled from three different locations (glass houses from Iasi, Barlad and Bacau - Romania) where the vegetables cultivation have been performed by three different technologies. In this way was estimated the applicability and the analytical limits of method proposed by as, in function of the chemical-mineralogical and physical-chemical characteristics of soils. As heavy metals have been studied cadmium, lead and chromium, all being known for their high toxicity. The procedure used for the selective separation and differentiation of speciation forms of heavy metals from glass houses soils has two main steps: (i) non-destructive separation of chemical-mineralogical associations and aggregates from soils samples - for this the separation method with heavy liquids (bromophorme) and isodynamic magnetic method have been used; (ii) sequential extraction of heavy metals from soil fractions separated in the first step, by using combined SPE-ABS procedure. For the preparation of combined extraction systems was used polyethylene glycol (with different molecular mass: 2000, 4000 and 8000). As phase-forming inorganic salts and as selective extracting agents we have used different usual inorganic reagents. The type and concentration of phase-forming salts have been selected in function of, both nature of extracted heavy metals and chemical-mineralogical characteristics of soil samples. The experimental parameters investigated in this study are: molecular mass of polyethylene glycol and the concentration of polymeric solutions, nature and concentration of phase-forming salts, nature and concentration of extracting agents, pH in extraction system phase, type of extracted heavy metals, type of speciation forms of heavy metals and their concentrations. All these factors can influence significantly the efficiency and the selectivity of separation process. The experimental results have indicate that the combined SPE-ABS extraction systems have better separation efficiency, in comparison with traditional SPE systems and ca realized a accurate discrimination between speciation forms of heavy metals from soils. Under these conditions, the estimation of inter-phases distribution and biodisponibility of heavy metals has a high precision. On the other hand, when the combined SPE-ABS systems are used, the concomitant extraction of the elements from the same geochemical association with studied heavy metals (inevitable phenomena in case of separation by SPE procedures) is significant diminished. This increases the separation selectivity and facilitated the more accurate determination of speciation forms concentration. By adequate selection of extraction conditions can be realized the selective separation of organic-mineral complexes, which will permit to perform detailed studies about the structure and chemical composition of these. Acknowledgments The authors would like to acknowledge the financial support from Romanian Ministry of Education and Research (Project PNCDI 2-D5 no. 51045/07 and project PNCDI 2 - D5 no. 52-141 / 2008).

Reduction of Topographic Effect for Curve Number Estimated from Remotely Sensed Imagery

NASA Astrophysics Data System (ADS)

Zhang, Wen-Yan; Lin, Chao-Yuan

2016-04-01

The Soil Conservation Service Curve Number (SCS-CN) method is commonly used in hydrology to estimate direct runoff volume. The CN is the empirical parameter which corresponding to land use/land cover, hydrologic soil group and antecedent soil moisture condition. In large watersheds with complex topography, satellite remote sensing is the appropriate approach to acquire the land use change information. However, the topographic effect have been usually found in the remotely sensed imageries and resulted in land use classification. This research selected summer and winter scenes of Landsat-5 TM during 2008 to classified land use in Chen-You-Lan Watershed, Taiwan. The b-correction, the empirical topographic correction method, was applied to Landsat-5 TM data. Land use were categorized using K-mean classification into 4 groups i.e. forest, grassland, agriculture and river. Accuracy assessment of image classification was performed with national land use map. The results showed that after topographic correction, the overall accuracy of classification was increased from 68.0% to 74.5%. The average CN estimated from remotely sensed imagery decreased from 48.69 to 45.35 where the average CN estimated from national LULC map was 44.11. Therefore, the topographic correction method was recommended to normalize the topographic effect from the satellite remote sensing data before estimating the CN.

A comparison of groundwater recharge estimation methods in a semi-arid, coastal avocado and citrus orchard (Ventura County, California)

NASA Astrophysics Data System (ADS)

Grismer, Mark E.; Bachman, S.; Powers, T.

2000-10-01

We assess the relative merits of application of the most commonly used field methods (soil-water balance (SWB), chloride mass balance (CMB) and soil moisture monitoring (NP)) to determine recharge rates in micro-irrigated and non-irrigated areas of a semi-arid coastal orchard located in a relatively complex geological environment.Application of the CMB method to estimate recharge rates was difficult owing to the unusually high, variable soil-water chloride concentrations. In addition, contrary to that expected, the chloride concentration distribution at depths below the root zone in the non-irrigated soil profiles was greater than that in the irrigated profiles. The CMB method severely underestimated recharge rates in the non-irrigated areas when compared with the other methods, although the CMB method estimated recharge rates for the irrigated areas, that were similar to those from the other methods, ranging from 42 to 141 mm/year.The SWB method, constructed for a 15-year period, provided insight into the recharge process being driven by winter rains rather than summer irrigation and indicated an average rate of 75 mm/year and 164 mm/year for the 1984 - 98 and 1996 - 98 periods, respectively. Assuming similar soil-water holding capacity, these recharge rates applied to both irrigated and non-irrigated areas. Use of the long period of record was important because it encompassed both drought and heavy rainfall years. Successful application of the SWB method, however, required considerable additional field measurements of orchard ETc, soil-water holding capacity and estimation of rainfall interception - runoff losses.Continuous soil moisture monitoring (NP) was necessary to identify both daily and seasonal seepage processes to corroborate the other recharge estimates. Measured recharge rates during the 1996 - 1998 period in both the orchards and non-irrigated site averaged 180 mm/year. The pattern of soil profile drying during the summer irrigation season, followed by progressive wetting during the winter rainy season was observed in both irrigated and non-irrigated soil profiles, confirming that groundwater recharge was rainfall driven and that micro-irrigation did not predispose the soil profile to excess rainfall recharge. The ability to make this recharge assessment, however, depended on making multiple field measurements associated with all three methods, suggesting that any one should not be used alone.

Computation of European carbon balance components through synergistic use of CARBOEUROPE eddy covariance, MODIS remote sensing data and advanced ecosystem and statistical modeling

NASA Astrophysics Data System (ADS)

Reichstein, M.; Dinh, N.; Running, S.; Seufert, G.; Tenhunen, J.; Valentini, R.

2003-04-01

Here we present spatially distributed bottom-up estimates of European carbon balance components for the year 2001, that stem from a newly built modeling system that integrates CARBOEUROPE eddy covariance CO_2 exchange data, remotely sensed vegetation properties via the MODIS-Terra sensor, European-wide soils data, and a suite of carbon balance models of different complexity. These estimates are able to better constrain top-down atmospheric-inversion carbon balance estimates within the dual-constraint approach for estimating continental carbon balances. The models that are used to calculate gross primary production (GPP) include a detailed layered canopy model with Farquhar-type photosynthesis (PROXELNEE), sun-shade big-leaf formulations operating at a daily time-step and a simple radiation-use efficiency model. These models are parameterized from eddy covariance data through inverse estimation techniques. Also for the estimation of soil and ecosystem respiration (Rsoil, Reco) we profit from a large data set of eddy covariance and soil chamber measurements, that enables us to the parameterize and validate a recently developed semi-empirical model, that includes a variable temperature sensitivity of respiration. As the outcome of the modeling system we present the most likely daily to annual numbers of carbon balance components (GPP, Reco, Rsoil), but we also issue a thorough analysis of biases and uncertainties in carbon balance estimates that are introduced through errors in the meteorological and remote sensing input data and through uncertainties in the model parameterization. In particular, we analyze 1) the effect of cloud contamination of the MODIS data, 2) the sensitivity to the land-use classification (Corine versus MODIS), 3) the effect of different soil parameterizations as derived from new continental-scale soil maps, and 4) the necessity to include soil drought effects into models of GPP and respiration. While the models describe the eddy covariance data quite well with r^2 values always greater than 0.7, there are still uncertainties in the European carbon balance estimate that exceed 0.3 PgC/yr. In northern (boreal) regions the carbon balance estimate is very much contingent on a high-quality filling of cloud contaminated remote sensing data, while in the southern (Mediterranean) regions a correct description of the soil water holding capacity is crucial. A major source of uncertainty also still is the estimation of heterotrophic respiration at continental scales. Consequently more spatial surveys on soil carbon stocks, turnover and history are needed. The study demonstrates that both, the inclusion of considerable geo-biological variability into a carbon balance modeling system, a high-quality cloud screening and gap-filling of the MODIS remote sensing data, and a correct description of soil drought effects are mandatory for realistic bottom-up estimates of European carbon balance components.

Assessing the radar rainfall estimates in watershed-scale water quality model

USDA-ARS?s Scientific Manuscript database

Watershed-scale water quality models are effective science-based tools for interpreting change in complex environmental systems that affect hydrology cycle, soil erosion and nutrient fate and transport in watershed. Precipitation is one of the primary input data to achieve a precise rainfall-runoff ...

Pedotransfer Functions in Earth System Science: Challenges and Perspectives

NASA Astrophysics Data System (ADS)

Van Looy, Kris; Bouma, Johan; Herbst, Michael; Koestel, John; Minasny, Budiman; Mishra, Umakant; Montzka, Carsten; Nemes, Attila; Pachepsky, Yakov A.; Padarian, José; Schaap, Marcel G.; Tóth, Brigitta; Verhoef, Anne; Vanderborght, Jan; van der Ploeg, Martine J.; Weihermüller, Lutz; Zacharias, Steffen; Zhang, Yonggen; Vereecken, Harry

2017-12-01

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

Compact polarimetric synthetic aperture radar for monitoring soil moisture condition

NASA Astrophysics Data System (ADS)

Merzouki, A.; McNairn, H.; Powers, J.; Friesen, M.

2017-12-01

Coarse resolution soil moisture maps are currently operationally delivered by ESA's SMOS and NASA's SMAP passive microwaves sensors. Despite this evolution, operational soil moisture monitoring at the field scale remains challenging. A number of factors contribute to this challenge including the complexity of the retrieval that requires advanced SAR systems with enhanced temporal revisit capabilities. Since the launch of RADARSAT-2 in 2007, Agriculture and Agri-Food Canada (AAFC) has been evaluating the accuracy of these data for estimating surface soil moisture. Thus, a hybrid (multi-angle/multi-polarization) retrieval approach was found well suited for the planned RADARSAT Constellation Mission (RCM) considering the more frequent relook expected with the three satellite configuration. The purpose of this study is to evaluate the capability of C-band CP data to estimate soil moisture over agricultural fields, in anticipation of the launch of RCM. In this research we introduce a new CP approach based on the IEM and simulated RCM CP mode intensities from RADARSAT-2 images acquired at different dates. The accuracy of soil moisture retrieval from the proposed multi-polarization and hybrid methods will be contrasted with that from a more conventional quad-pol approach, and validated against in situ measurements by pooling data collected over AAFC test sites in Ontario, Manitoba and Saskatchewan, Canada.

High resolution modelling of soil moisture patterns with TerrSysMP: A comparison with sensor network data

NASA Astrophysics Data System (ADS)

Gebler, S.; Hendricks Franssen, H.-J.; Kollet, S. J.; Qu, W.; Vereecken, H.

2017-04-01

The prediction of the spatial and temporal variability of land surface states and fluxes with land surface models at high spatial resolution is still a challenge. This study compares simulation results using TerrSysMP including a 3D variably saturated groundwater flow model (ParFlow) coupled to the Community Land Model (CLM) of a 38 ha managed grassland head-water catchment in the Eifel (Germany), with soil water content (SWC) measurements from a wireless sensor network, actual evapotranspiration recorded by lysimeters and eddy covariance stations and discharge observations. TerrSysMP was discretized with a 10 × 10 m lateral resolution, variable vertical resolution (0.025-0.575 m), and the following parameterization strategies of the subsurface soil hydraulic parameters: (i) completely homogeneous, (ii) homogeneous parameters for different soil horizons, (iii) different parameters for each soil unit and soil horizon and (iv) heterogeneous stochastic realizations. Hydraulic conductivity and Mualem-Van Genuchten parameters in these simulations were sampled from probability density functions, constructed from either (i) soil texture measurements and Rosetta pedotransfer functions (ROS), or (ii) estimated soil hydraulic parameters by 1D inverse modelling using shuffle complex evolution (SCE). The results indicate that the spatial variability of SWC at the scale of a small headwater catchment is dominated by topography and spatially heterogeneous soil hydraulic parameters. The spatial variability of the soil water content thereby increases as a function of heterogeneity of soil hydraulic parameters. For lower levels of complexity, spatial variability of the SWC was underrepresented in particular for the ROS-simulations. Whereas all model simulations were able to reproduce the seasonal evapotranspiration variability, the poor discharge simulations with high model bias are likely related to short-term ET dynamics and the lack of information about bedrock characteristics and an on-site drainage system in the uncalibrated model. In general, simulation performance was better for the SCE setups. The SCE-simulations had a higher inverse air entry parameter resulting in SWC dynamics in better correspondence with data than the ROS simulations during dry periods. This illustrates that small scale measurements of soil hydraulic parameters cannot be transferred to the larger scale and that interpolated 1D inverse parameter estimates result in an acceptable performance for the catchment.

New approaches to the estimation of the geosystem properties transformation in technogenesis

NASA Astrophysics Data System (ADS)

Sarapulova, G.; Fedotov, K.

2013-03-01

A new approach to the estimation of environmental situation of the urbanized territories of a large city is offered. The approach is based on a complex of physical and chemical parameters adequately describing transformation of soil properties, with the use of landscape-geochemical method and GIS technologies. The pollution of soil horizons by heavy metals (HM) and mineral oil (MO) in a zone of influence of dangerous industrial objects exceeds by orders the maximum permissible concentration (MPC). Sharp deterioration of a nitric and carbon mode, increase of the alkalinity and the decrease in buffer activity of ground were revealed. The dynamics of technogenic streams and aureole of the contaminants migration in soils can result not only in the further transformation of their properties, but in closing the migration cycles of MO and HM. As a rule this is accompanied by the formation of secondary local sites of toxic substances accumulation and abnormal geochemical fields - laterally technogenic module. The revision of approaches to the analysis of soils under technogenesis and the development of new system of ecological monitoring represent a challenging goal.

Polybrominated dibenzo-p-dioxins/dibenzofurans and polybrominated diphenyl ethers in soil, vegetation, workshop-floor dust, and electronic shredder residue from an electronic waste recycling facility and in soils from a chemical industrial complex in eastern China

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

Jing Ma; Rudolf Addink; Sehun Yun

2009-10-01

In this study, 11 2,3,7,8-substituted PBDD/Fs and 10 polybrominated diphenyl ether (PBDE) congeners were determined in electronic shredder waste, workshop-floor dust, soil, and leaves (of plants on the grounds of the facility) from a large-scale electronic wastes (e-waste) recycling facility and in surface soil from a chemical-industrial complex (comprising a coke-oven plant, a coal-fired power plant, and a chlor-alkali plant) as well as agricultural areas in eastern China. Total PBDD/F concentrations in environmental samples were in the range of 113-818 pg/g dry wt (dw) for leaves, 392-18,500 pg/g dw for electronic shredder residues, 716-80,0000 pg/g dw for soil samples, andmore » 89,600-14,3000 pg/g dw for workshop-floor dust from the e-waste recycling facility and in a range from nondetect (ND) to 427 pg/g dw in soil from the chemical-industrial complex. The highest mean concentrations of total PBDD/Fs were found in soil samples and workshop-floor dust from the e-waste recycling facility. The dioxin-like toxic equivalent (measured as TEQ) concentrations of PBDD/Fs were greater than the TEQs of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) reported in our previous study for the same set of samples. The concentrations of PBDFs were several orders of magnitude higher than the concentrations of PBDDs in samples from the e-waste facility or from soil from the chemical-industrial complex. A significant correlation was found between the concentrations of {Sigma}PBDD/Fs and {Sigma}PBDEs (r = 0.769, p < 0.01) and between SPBDD/Fs and the previously reported SPCDD/F concentrations (r = 0.805, p < 0.01). The estimated daily human intakes of TEQs contributed by PBDD/Fs via soil/dust ingestion and dermal exposures in e-waste recycling facilities were higher than the intakes of TEQs contributed by PCDD/Fs, calculated in our previous study. 45 refs., 2 figs., 2 tabs.« less

Evaluating the importance of characterizing soil structure and horizons in parameterizing a hydrologic process model

USGS Publications Warehouse

Mirus, Benjamin B.

2015-01-01

Incorporating the influence of soil structure and horizons into parameterizations of distributed surface water/groundwater models remains a challenge. Often, only a single soil unit is employed, and soil-hydraulic properties are assigned based on textural classification, without evaluating the potential impact of these simplifications. This study uses a distributed physics-based model to assess the influence of soil horizons and structure on effective parameterization. This paper tests the viability of two established and widely used hydrogeologic methods for simulating runoff and variably saturated flow through layered soils: (1) accounting for vertical heterogeneity by combining hydrostratigraphic units with contrasting hydraulic properties into homogeneous, anisotropic units and (2) use of established pedotransfer functions based on soil texture alone to estimate water retention and conductivity, without accounting for the influence of pedon structures and hysteresis. The viability of this latter method for capturing the seasonal transition from runoff-dominated to evapotranspiration-dominated regimes is also tested here. For cases tested here, event-based simulations using simplified vertical heterogeneity did not capture the state-dependent anisotropy and complex combinations of runoff generation mechanisms resulting from permeability contrasts in layered hillslopes with complex topography. Continuous simulations using pedotransfer functions that do not account for the influence of soil structure and hysteresis generally over-predicted runoff, leading to propagation of substantial water balance errors. Analysis suggests that identifying a dominant hydropedological unit provides the most acceptable simplification of subsurface layering and that modified pedotransfer functions with steeper soil-water retention curves might adequately capture the influence of soil structure and hysteresis on hydrologic response in headwater catchments.

Speciation and isotopic exchangeability of nickel in soil solution.

PubMed

Nolan, Annette L; Ma, Yibing; Lombi, Enzo; McLaughlin, Mike J

2009-01-01

Knowledge of trace metal speciation in soil pore waters is important in addressing metal bioavailability and risk assessment of contaminated soils. In this study, free Ni(2+) activities were determined in pore waters of long-term Ni-contaminated soils using a Donnan dialysis membrane technique. The pore water free Ni(2+) concentration as a percentage of total soluble Ni ranged from 21 to 80% (average 53%), and the average amount of Ni bound to dissolved organic matter estimated by Windermere Humic Aqueous Model VI was < or = 17%. These data indicate that complexed forms of Ni can constitute a significant fraction of total Ni in solution. Windermere Humic Aqueous Model VI provided reasonable estimates of free Ni(2+) fractions in comparison to the measured fractions (R(2) = 0.83 with a slope of 1.0). Also, the isotopically exchangeable pools (E value) of soil Ni were measured by an isotope dilution technique using water extraction, with and without resin purification, and 0.1 mol L(-1) CaCl(2) extraction, and the isotopic exchangeability of Ni species in soil water extracts was investigated. The concentrations of isotopically non-exchangeable Ni in water extracts were <9% of total water soluble Ni concentrations for all soils. The resin E values expressed as a percentage of the total Ni concentrations in soil showed that the labile Ni pool ranged from 0.9 to 32.4% (average 12.4%) of total soil Ni. Therefore the labile Ni pool in these well-equilibrated contaminated soils appears to be relatively small in relation to total Ni concentrations.

Extension of coupled multispecies metal transport and speciation (TRANSPEC) model to soil.

PubMed

Bhavsar, Satyendra P; Gandhi, Nilima; Diamond, Miriam L

2008-01-01

Atmospheric deposition of metals emitted from mining operations has raised metal concentrations in the surrounding soils. This repository may be remobilized and act as a source of metals to nearby surface aquatic systems. It is important to understand metal dynamics and the impact of various chemistry and fate parameters on metal movement in the soil environment in order to evaluate risk associated with metals in terrestrial ecosystems and accurately establish critical discharge limits that are protective of aquatic biota. Here we extend our previously developed coupled multispecies metal fate-TRANsport and SPECiation/complexation (TRANSPEC) model, which was applicable to surface aquatic systems. The extended TRANSPEC, termed TRANSPEC-II, estimates the partition coefficient, K(d), between the soil-solid and -soluble phases using site-specific data and a semi-empirical regression model obtained from literature. A geochemical model calculates metal and species fractions in the dissolved and colloidal phases of the soil solution. The multispecies fugacity/aquivalence based fate-transport model then estimates inter-media transport rates such as leaching from soil, soil runoff, and water-sediment exchanges of each metal species. The model is illustratively applied to Ni in the Kelly Lake watershed (Sudbury, Ontario, Canada), where several mining operations are located. The model results suggest that the current atmospheric fallout supplies only 4% of Ni removed from soil through soil runoff and leaching. Soil runoff contributes about 20% of Ni entering into Kelly Lake with the rest coming from other sources. Leaching to groundwater, apart from runoff, is also a major loss process for Ni in the soil. A sensitivity analysis indicates that raising soil pH to above 6 may substantially reduce metal runoff and improve water quality of nearby water bodies that are impacted by runoff.

Investigation of mesoscale precipitation processes in the Carolinas using a radar-based climatology

NASA Astrophysics Data System (ADS)

Boyles, Ryan Patrick

The complex topography, shoreline, soils, and land use patterns makes the Carolinas a unique location to study mesoscale processes. Using gage-calibrated radar estimates and a series of numerical model simulations, warm season mesoscale precipitation patterns are analyzed over the Carolinas. Gage-calibrated radar precipitation estimates are compared with surface gage observations. Stage IV estimates generally compared better than Stage II estimates, but some Stage II and Stage IV estimates have gross errors during autumn, winter, and spring seasons. Analysis of days when sea breeze is observed suggests that sea breeze induced precipitation occurs on nearly 40% of days in June, July, and August, but only 18% in May and 6% of days in April. Precipitation on days with sea breeze convection can contribute to over 50% of seasonal precipitation. Rainfall associated with sea breeze is generally maximized along east-facing shores 10-20 km inland, and minimized along south-facing shores in North Carolina. The shape of the shoreline along Cape Fear is associated with a local precipitation maximum that may be caused by the convergence of two sea breeze fronts from the south and east shores. Differential heating associated with contrasting soils along the Carolina Sandhills is suggested as a mechanism for enhancement in local precipitation. A high-resolution summer precipitation climatology suggests that precipitation is enhanced along the Sandhills region in both wet and dry years. Analysis of four numerical simulations suggests that contrasts in soils over the Carolinas Sandhills dominates over vegetation contrasts to produce heat flux gradients and a convergence zone along the sand-to-clay transition. Orographically induced precipitation is consistently observed in the summer, and appears to be isolated along windward slopes at 20km--40km from the ridge line. Amounts over external ridges are generally 50-100% higher than amounts observed over the foothills. Precipitation amounts over interior ridges and valleys are lower than observed on exterior ridges and are similar to values observed over the foothills. When compared with Stage IV estimates, the PRISM (Precipitation-elevation Regressions on Independent Slopes Model) method for estimating precipitation in complex terrain appears to largely over-estimate precipitation amounts over the interior ridges.

Antecedent wetness conditions based on ERS scatterometer data

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2009-01-01

SummarySoil moisture is widely recognized as a key parameter in environmental processes mainly for the role of rainfall partitioning into runoff and infiltration. Therefore, for storm rainfall-runoff modeling the estimation of the antecedent wetness conditions ( AWC) is one of the most important aspect. In this context, this study investigates the potential of scatterometer on board of the ERS satellites for the assessment of wetness conditions in three Tiber sub-catchments (Central Italy), of which one includes an experimental area for soil moisture monitoring. The satellite soil moisture data are taken from the ERS/METOP soil moisture archive. First, the scatterometer-derived soil wetness index ( SWI) data are compared with two on-site soil moisture data sets acquired by different methodologies on areas of different extension ranging from 0.01 km 2 to ˜60 km 2. Moreover, the reliability of SWI to estimate the AWC at a catchment scale is investigated considering the relationship between SWI and the soil potential maximum retention parameter, S, of the Soil Conservation Service-Curve Number (SCS-CN) method for abstraction. Several flood events occurred from 1992 to 2005 are selected for this purpose. Specifically, the performance of the SWI for S estimation is compared with two antecedent precipitation indices ( API) and one base flow index ( BFI). The S values obtained through the observed direct runoff volume and rainfall depth are used as benchmark. Results show the great reliability of the SWI for the estimation of wetness conditions both at the plot and catchment scale despite the complex orography of the investigated areas. As far as the comparison with on site soil moisture data set is concerned, the SWI is found quite reliable in representing the soil moisture at layer depth of 15 cm, with a mean correlation coefficient equal to 0.81. The characteristic time length parameter variations, as expected, is depended on soil type, with values in accordance with previous studies. In terms of AWC assessment at catchment scale, based on selected flood events, the SWI is found highly correlated with the observed maximum potential retention of the SCS-CN method with a correlation coefficient R equal to -0.90. Besides, SWI in representing the AWC of the three investigated catchments, outperformed both API indices, poorly representative of AWC, and BFI. Finally, the classical SCS-CN method applied for direct runoff depth estimation, where S is assessed by SWI, provided good performance with a percentage error not exceeding ˜25% for 80% of investigated rainfall-runoff events.

An integrated soil-crop system model for water and nitrogen management in North China

PubMed Central

Liang, Hao; Hu, Kelin; Batchelor, William D.; Qi, Zhiming; Li, Baoguo

2016-01-01

An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China. PMID:27181364

Soil moisture sensors for continuous monitoring

USGS Publications Warehouse

Amer, Saud A.; Keefer, T. O.; Weltz, M.A.; Goodrich, David C.; Bach, Leslie

1995-01-01

Certain physical and chemical properties of soil vary with soil water content. The relationship between these properties and water content is complex and involves both the pore structure and constituents of the soil solution. One of the most economical techniques to quantify soil water content involves the measurement of electrical resistance of a dielectric medium that is in equilibrium with the soil water content. The objective of this research was to test the reliability and accuracy of fiberglass soil-moisture electrical resistance sensors (ERS) as compared to gravimetric sampling and Time Domain Reflectometry (TDR). The response of the ERS was compared to gravimetric measurements at eight locations on the USDA-ABS Walnut Gulch Experimental Watershed. The comparisons with TDR sensors were made at three additional locations on the same watershed. The high soil rock content (>45 percent) at seven locations resulted in consistent overestimation of soil water content by the ERS method. Where rock content was less than 10 percent, estimation of soil water was within 5 percent of the gravimetric soil water content. New methodology to calibrate the ERS sensors for rocky soils will need to be developed before soil water content values can be determined with these sensors. (KEY TERMS: soil moisture; soil water; infiltration; instrumentation; soil moisture sensors.)

Safety assessment of a shallow foundation using the random finite element method

NASA Astrophysics Data System (ADS)

Zaskórski, Łukasz; Puła, Wojciech

2015-04-01

A complex structure of soil and its random character are reasons why soil modeling is a cumbersome task. Heterogeneity of soil has to be considered even within a homogenous layer of soil. Therefore an estimation of shear strength parameters of soil for the purposes of a geotechnical analysis causes many problems. In applicable standards (Eurocode 7) there is not presented any explicit method of an evaluation of characteristic values of soil parameters. Only general guidelines can be found how these values should be estimated. Hence many approaches of an assessment of characteristic values of soil parameters are presented in literature and can be applied in practice. In this paper, the reliability assessment of a shallow strip footing was conducted using a reliability index β. Therefore some approaches of an estimation of characteristic values of soil properties were compared by evaluating values of reliability index β which can be achieved by applying each of them. Method of Orr and Breysse, Duncan's method, Schneider's method, Schneider's method concerning influence of fluctuation scales and method included in Eurocode 7 were examined. Design values of the bearing capacity based on these approaches were referred to the stochastic bearing capacity estimated by the random finite element method (RFEM). Design values of the bearing capacity were conducted for various widths and depths of a foundation in conjunction with design approaches DA defined in Eurocode. RFEM was presented by Griffiths and Fenton (1993). It combines deterministic finite element method, random field theory and Monte Carlo simulations. Random field theory allows to consider a random character of soil parameters within a homogenous layer of soil. For this purpose a soil property is considered as a separate random variable in every element of a mesh in the finite element method with proper correlation structure between points of given area. RFEM was applied to estimate which theoretical probability distribution fits the empirical probability distribution of bearing capacity basing on 3000 realizations. Assessed probability distribution was applied to compute design values of the bearing capacity and related reliability indices β. Conducted analysis were carried out for a cohesion soil. Hence a friction angle and a cohesion were defined as a random parameters and characterized by two dimensional random fields. A friction angle was described by a bounded distribution as it differs within limited range. While a lognormal distribution was applied in case of a cohesion. Other properties - Young's modulus, Poisson's ratio and unit weight were assumed as deterministic values because they have negligible influence on the stochastic bearing capacity. Griffiths D. V., & Fenton G. A. (1993). Seepage beneath water retaining structures founded on spatially random soil. Géotechnique, 43(6), 577-587.

Aggregate stability as an indicator of soil erodibility and soil physical quality: review and perspectives

NASA Astrophysics Data System (ADS)

Le Bissonnais, Yves; Chenu, Claire; Darboux, Frédéric; Duval, Odile; Legout, Cédric; Leguédois, Sophie; Gumiere, Silvio

2010-05-01

Aggregate breakdown due to water and rain action may cause surface crusting, slumping, a reduction of infiltration and interrill erosion. Aggregate stability determines the capacity of aggregates to resist the effects of water and rainfall. In this paper, we evaluated and reviewed the relevance of an aggregate stability measurement to characterize soil physical properties as well as to analyse the processes involved in these properties. Stability measurement assesses the sensitivity of soil aggregates to various basic disaggregation mechanisms such as slaking, differential swelling, dispersion and mechanical breakdown. It has been showed that aggregate size distributions of structural stability tests matched the size distributions of eroded aggregates under rainfall simulations and that erosion amount was well predicted using aggregate stability indexes. It means stability tests could be used to estimate both the erodibility and the size fractions that are available for crust formation and erosion processes. Several studies showed that organic matter was one of the main soil properties affecting soil stability. However, it has also been showed that aggregate stability of a given soil could vary within a year or between years. The factors controlling such changes have still to be specified. Aggregate stability appears therefore as a complex property, depending both on permanent soil characteristics and on dynamic factors such as the crusting stage, the climate and the biological activity. Despite, and may be, because of this complexity, aggregate stability seems an integrative and powerful indicator of soil physical quality. Future research efforts should look at the causes of short-term changes of structural stability, in order to fully understand all its aspects.

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

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

Van Looy, Kris; Bouma, Johan; Herbst, Michael

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less

Pedotransfer Functions in Earth System Science: Challenges and Perspectives: PTFs in Earth system science perspective

DOE PAGES

Van Looy, Kris; Bouma, Johan; Herbst, Michael; ...

2017-12-28

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. Here in this article, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscalingmore » techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration, and organic carbon content, root density, and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.« less

Phytoremediation of Cu and Zn by vetiver grass in mine soils amended with humic acids.

PubMed

Vargas, Carmen; Pérez-Esteban, Javier; Escolástico, Consuelo; Masaguer, Alberto; Moliner, Ana

2016-07-01

Phytoremediation of contaminated mine soils requires the use of fast-growing, deep-rooted, high-biomass, and metal-tolerant plants with the application of soil amendments that promote metal uptake by plants. A pot experiment was performed to evaluate the combined use of vetiver grass (Chrysopogon zizanioides) and humic acid for phytoremediation of Cu and Zn in mine soils. Vetiver plants were grown in soil samples collected from two mine sites of Spain mixed with a commercial humic acid derived from leonardite at doses of 0, 2, 10, and 20 g kg(-1). Plant metal concentrations and biomass were measured and metal bioavailability in soils was determined by a low molecular weight organic acid extraction. Results showed that humic acid addition decreased organic acid-extractable metals in soil. Although this extraction method is used to estimate bioavailability of metals, it was not a good estimator under these conditions due to competition with the strong chelators in the added humic acid. High doses of humic acid also promoted root growth and increased Cu concentrations in plants due to formation of soluble metal-organic complexes, which enhanced removal of this metal from soil and its accumulation in roots. Although humic acid was not able to improve Zn uptake, it managed to reduce translocation of Zn and Cu to aerial parts of plants. Vetiver resulted unsuitable for phytoextraction, but our study showed that the combined use of this species with humic acid at 10-20 g kg(-1) could be an effective strategy for phytostabilization of mine soils.

[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

PubMed

Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua

2015-08-01

Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

Soil Organic Carbon Sequestration by Tillage and Crop Rotation: A Global Data Analysis

DOE Data Explorer

West, Tristram O. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Post, Wilfred M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2002-01-01

Changes in agricultural management can potentially increase the accumulation rate of soil organic carbon (SOC), thereby sequestering CO2 from the atmosphere. This study was conducted to quantify potential soil carbon (C) sequestration rates for different crops in response to decreasing tillage intensity or enhancing rotation complexity, and to estimate the duration of time over which sequestration may occur. Analyses of C sequestration rates were completed using a global database of 67 long-term agricultural experiments, consisting of 276 paired treatments. Results indicate, on average, that a change from conventional tillage (CT) to no-till (NT) can sequester 57 ± 14 g C m^–2 yr^–1, excluding wheat (Triticum aestivum L.)-fallow systems which may not result in SOC accumulation with a change from CT to NT. Enhancing rotation complexity can sequester an average 14 ± 11 g C m^–2 yr^–1, excluding a change from continuous corn (Zea mays L.) to corn-soybean (Glycine max L.) which may not result in a significant accumulation of SOC. Carbon sequestration rates, with a change from CT to NT, can be expected to peak in 5-10 yr with SOC reaching a new equilibrium in 15-20 yr. Following initiation of an enhancement in rotation complexity, SOC may reach a new equilibrium in approximately 40-60 yr. Carbon sequestration rates, estimated for a number of individual crops and crop rotations in this study, can be used in spatial modeling analyses to more accurately predict regional, national, and global C sequestration potentials.

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Treesearch

Taehee Hwang; Conghe Song; James Vose; Lawrence Band

2011-01-01

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology...

Determination of soil degradation from flooding for estimating ecosystem services in Slovakia

NASA Astrophysics Data System (ADS)

Hlavcova, Kamila; Szolgay, Jan; Karabova, Beata; Kohnova, Silvia

2015-04-01

Floods as natural hazards are related to soil health, land-use and land management. They not only represent threats on their own, but can also be triggered, controlled and amplified by interactions with other soil threats and soil degradation processes. Among the many direct impacts of flooding on soil health, including soil texture, structure, changes in the soil's chemical properties, deterioration of soil aggregation and water holding capacity, etc., are soil erosion, mudflows, depositions of sediment and debris. Flooding is initiated by a combination of predispositive and triggering factors and apart from climate drivers it is related to the physiographic conditions of the land, state of the soil, land use and land management. Due to the diversity and complexity of their potential interactions, diverse methodologies and approaches are needed for describing a particular type of event in a specific environment, especially in ungauged sites. In engineering studies and also in many rainfall-runoff models, the SCS-CN method has remained widely applied for soil and land use-based estimations of direct runoff and flooding potential. The SCS-CN method is an empirical rainfall-runoff model developed by the USDA Natural Resources Conservation Service (formerly called the Soil Conservation Service or SCS). The runoff curve number (CN) is based on the hydrological soil characteristics, land use, land management and antecedent saturation conditions of soil. Since the method and curve numbers were derived on the basis of an empirical analysis of rainfall-runoff events from small catchments and hillslope plots monitored by the USDA, the use of the method for the conditions of Slovakia raises uncertainty and can cause inaccurate results in determining direct runoff. The objective of the study presented (also within the framework of the EU-FP7 RECARE Project) was to develop the SCS - CN methodology for the flood conditions in Slovakia (and especially for the RECARE pilot site of Myjava), with an emphasis on the determination of soil degradation from flooding for estimating ecosystem services. The parameters of the SCS-CN methodology were regionalised empirically based on actual rainfall and discharge measurements. Since there has been no appropriate methodology provided for the regionalisation of SCS-CN method parameters in Slovakia, such as runoff curve numbers and initial abstraction coefficients (λ), the work presented is important for the correct application of the SCS-CN method in our conditions.

Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.

NASA Astrophysics Data System (ADS)

Nair, A. S.; Indu, J.

2017-12-01

Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb assimilation. The results indicate an improvement in Tb simulations based on the multi polarization difference index approach with a correlation of 0.81 (figure 1b (e)) and bias of < 5 K with respect to the SMOS Tb.

An index for plant water deficit based on root-weighted soil water content

NASA Astrophysics Data System (ADS)

Shi, Jianchu; Li, Sen; Zuo, Qiang; Ben-Gal, Alon

2015-03-01

Governed by atmospheric demand, soil water conditions and plant characteristics, plant water status is dynamic, complex, and fundamental to efficient agricultural water management. To explore a centralized signal for the evaluation of plant water status based on soil water status, two greenhouse experiments investigating the effect of the relative distribution between soil water and roots on wheat and rice were conducted. Due to the significant offset between the distributions of soil water and roots, wheat receiving subsurface irrigation suffered more from drought than wheat under surface irrigation, even when the arithmetic averaged soil water content (SWC) in the root zone was higher. A significant relationship was found between the plant water deficit index (PWDI) and the root-weighted (rather than the arithmetic) average SWC over root zone. The traditional soil-based approach for the estimation of PWDI was improved by replacing the arithmetic averaged SWC with the root-weighted SWC to take the effect of the relative distribution between soil water and roots into consideration. These results should be beneficial for scheduling irrigation, as well as for evaluating plant water consumption and root density profile.

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

Visualising the equilibrium distribution and mobility of organic contaminants in soil using the chemical partitioning space.

PubMed

Wong, Fiona; Wania, Frank

2011-06-01

Assessing the behaviour of organic chemicals in soil is a complex task as it is governed by the physical chemical properties of the chemicals, the characteristics of the soil as well as the ambient conditions of the environment. The chemical partitioning space, defined by the air-water partition coefficient (K(AW)) and the soil organic carbon-water partition coefficient (K(OC)), was employed to visualize the equilibrium distribution of organic contaminants between the air-filled pores, the pore water and the solid phases of the bulk soil and the relative importance of the three transport processes removing contaminants from soil (evaporation, leaching and particle erosion). The partitioning properties of twenty neutral organic chemicals (i.e. herbicides, pharmaceuticals, polychlorinated biphenyls and volatile chemicals) were estimated using poly-parameter linear free energy relationships and superimposed onto these maps. This allows instantaneous estimation of the equilibrium phase distribution and mobility of neutral organic chemicals in soil. Although there is a link between the major phase and the dominant transport process, such that chemicals found in air-filled pore space are subject to evaporation, those in water-filled pore space undergo leaching and those in the sorbed phase are associated with particle erosion, the partitioning coefficient thresholds for distribution and mobility can often deviate by many orders of magnitude. In particular, even a small fraction of chemical in pore water or pore air allows for evaporation and leaching to dominate over solid phase transport. Multiple maps that represent soils that differ in the amount and type of soil organic matter, water saturation, temperature, depth of surface soil horizon, and mineral matters were evaluated.

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

Solubility enhancement of seven metal contaminants using carboxymethyl-β-cyclodextrin (CMCD)

NASA Astrophysics Data System (ADS)

Skold, Magnus E.; Thyne, Geoffrey D.; Drexler, John W.; McCray, John E.

2009-07-01

Carboxymethyl-β-cyclodextrin (CMCD) has been suggested as a complexing agent for remediation of sites co-contaminated with metals and organic pollutants. As part of an attempt to construct a geochemical complexation model for metal-CMCD interactions, conditional formation constants for the complexes between CMCD and 7 metal ions (Ba, Ca, Cd, Ni, Pb, Sr, and Zn) are estimated from experimental data. Stable metal concentrations were reached after approximately 1 day and estimated logarithmic conditional formation constants range from - 3.2 to - 5.1 with confidence intervals within ± 0.08 log units. Experiments performed at 10 °C and 25 °C show that temperature affects the solubility of the metal salts but the strength of CMCD-metal complexes are not affected by this temperature variation. The conditional stability constants and complexation model presented in this work can be used to screen CMCD as a potential remediation agent for clean-up of contaminated soil and groundwater.

Variation in Soil Respiration across Soil and Vegetation Types in an Alpine Valley

PubMed Central

Rubin, Aurélie

2016-01-01

Background and Aims Soils of mountain regions and their associated plant communities are highly diverse over short spatial scales due to the heterogeneity of geological substrates and highly dynamic geomorphic processes. The consequences of this heterogeneity for biogeochemical transfers, however, remain poorly documented. The objective of this study was to quantify the variability of soil-surface carbon dioxide efflux, known as soil respiration (Rs), across soil and vegetation types in an Alpine valley. To this aim, we measured Rs rates during the peak and late growing season (July-October) in 48 plots located in pastoral areas of a small valley of the Swiss Alps. Findings Four herbaceous vegetation types were identified, three corresponding to different stages of primary succession (Petasition paradoxi in pioneer conditions, Seslerion in more advanced stages and Poion alpinae replacing the climactic forests), as well as one (Rumicion alpinae) corresponding to eutrophic grasslands in intensively grazed areas. Soils were developed on calcareous alluvial and colluvial fan deposits and were classified into six types including three Fluvisols grades and three Cambisols grades. Plant and soil types had a high level of co-occurrence. The strongest predictor of Rs was soil temperature, yet we detected additional explanatory power of sampling month, showing that temporal variation was not entirely reducible to variations in temperature. Vegetation and soil types were also major determinants of Rs. During the warmest month (August), Rs rates varied by over a factor three between soil and vegetation types, ranging from 2.5 μmol m-2 s-1 in pioneer environments (Petasition on Very Young Fluvisols) to 8.5 μmol m-2 s-1 in differentiated soils supporting nitrophilous species (Rumicion on Calcaric Cambisols). Conclusions Overall, this study provides quantitative estimates of spatial and temporal variability in Rs in the mountain environment, and demonstrates that estimations of soil carbon efflux at the watershed scale in complex geomorphic terrain have to account for soil and vegetation heterogeneity. PMID:27685955

Fate of carbon in Alaskan Landscapes Project: database for soils from eddy covariance tower sites, Delta Junction, AK

USGS Publications Warehouse

King, Stagg; Harden, Jennifer; Manies, Kristen L.; Munster, Jennie; White, L. Douglas

2002-01-01

Soils in Alaska, and in high latitude terrestrial ecosystems in general, contain significant amounts of organic carbon, most of which is believed to have accumulated since the start of the Holocene about 10 ky before present. High latitude soils are estimated to contain 30-40% of terrestrial soil carbon (Melillo et al., 1995; McGuire and Hobbie, 1997), or ~ 300-400 Gt C (Gt = 1015 g), which equals about half of the current atmospheric burden of carbon. Boreal forests in particular are estimated to have more soil carbon than any other terrestrial biome (Post et al., 1982; Chapin and Matthews, 1993). The relations among net primary production, soil carbon storage, recurrent fire disturbance, nutrients, the hydrologic cycle, permafrost and geomorphology are poorly understood in boreal forest. Fire disturbance has been suggested to play a key role in the interactions among the complex biogeochemical processes influencing carbon storage in boreal forest soils (Harden et al., 2000; Zhuang et al., 2002). There has been an observed increase in fire disturbance in North American boreal black spruce (Picea mariana) forests in recent decades (Murphy et al., 1999; Kasichke et al., 2000), concurrent with increases in Alaskan boreal and arctic surface temperatures and warming of permafrost (Osterkamp and Romanofsky, 1999). Understanding the role of fire in long term carbon storage and how recent changes in fire frequency and severity may influence future high latitude soil carbon pools is necessary for those working to understand or mitigate the effects of global climate change.

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2013-10-01

Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater level dynamics were not adequately reproduced and the predicted spatial patterns of soil saturation did not correspond to the patterns estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a more complex model. Especially high spatial resolution and very detailed process representations at the boundary between the unsaturated and the saturated zone are expected to be crucial. The data needed for such a detailed model are not generally available. The high computational demand and the complex model setup would require more resources than the direct identification of saturated areas in the field. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

Polybrominated dibenzo-p-dioxins/ dibenzofurans and polybrominated diphenyl ethers in soil, vegetation, workshop-floor dust, and electronic shredder residue from an electronic waste recycling facility and in soils from a chemical industrial complex in eastern China.

PubMed

Ma, Jing; Addink, Rudolf; Yun, Sehun; Cheng, Jinping; Wang, Wenhua; Kannan, Kurunthachalam

2009-10-01

The formation and release of polybrominated dibenzo-p-dioxins and dibenzofurans (PBDD/Fs) from the incineration of electronic wastes (e-waste) that contain brominated flame retardants (BFRs) are a concern. However, studies on the determination of PBDD/Fs in environmental samples collected from e-waste recycling facilities are scarce. In this study, 11 2,3,7,8-substituted PBDD/Fs and 10 polybrominated diphenyl ether (PBDE) congeners were determined in electronic shredder waste, workshop-floor dust soil, and leaves (of plants on the grounds of the facility) from a large-scale e-waste recycling facility and in surface soil from a chemical-industrial complex (comprising a coke-oven plant, a coal-fired power plant, and a chlor-alkali plant) as well as agricultural areas in eastern China. Total PBDD/F concentrations in environmental samples were in the range of 113-818 pg/g dry wt (dw) for leaves, 392-18500 pg/g dw for electronic shredder residues, 716-800000 pg/g dw for soil samples, and 89600-pg/g dw for workshop-floor dust from the e-waste recycling facility and in a range from nondetect (ND) to 427 pg/g dw in soil from the chemical-industrial complex. The highest mean concentrations of total PBDD/Fs were found in soil samples and workshop-floor dust from the e-waste recycling facility. The dioxin-like toxic equivalent (measured as TEQ) concentrations of PBDD/Fs were greater than the TEQs of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) reported in our previous study for the same set of samples. The concentrations of PBDFs were several orders of magnitude higher than the concentrations of PBDDs in samples from the e-waste facility or from soil from the chemical-industrial complex. A significant correlation was found between the concentrations of sigmaPBDD/Fs and sigmaPBDEs (r = 0.769, p < 0.01) and between sigmaPBDD/Fs and the previously reported sigmaPCDD/F concentrations (r = 0.805, p < 0.01). The estimated daily human intakes of TEQs contributed by PBDD/Fs via soil/dust ingestion and dermal exposures in e-waste recycling facilities were higher than the intakes of TEQs contributed by PCDD/ Fs, calculated in our previous study.

Above- and below-ground methane fluxes and methanotrophic activity in a landfill-cover soil

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

Schroth, M.H., E-mail: martin.schroth@env.ethz.ch; Eugster, W.; Gomez, K.E.

2012-05-15

Highlights: Black-Right-Pointing-Pointer We quantify above- and below-ground CH{sub 4} fluxes in a landfill-cover soil. Black-Right-Pointing-Pointer We link methanotrophic activity to estimates of CH{sub 4} loading from the waste body. Black-Right-Pointing-Pointer Methane loading and emissions are highly variable in space and time. Black-Right-Pointing-Pointer Eddy covariance measurements yield largest estimates of CH{sub 4} emissions. Black-Right-Pointing-Pointer Potential methanotrophic activity is high at a location with substantial CH{sub 4} loading. - Abstract: Landfills are a major anthropogenic source of the greenhouse gas methane (CH{sub 4}). However, much of the CH{sub 4} produced during the anaerobic degradation of organic waste is consumed by methanotrophic microorganismsmore » during passage through the landfill-cover soil. On a section of a closed landfill near Liestal, Switzerland, we performed experiments to compare CH{sub 4} fluxes obtained by different methods at or above the cover-soil surface with below-ground fluxes, and to link methanotrophic activity to estimates of CH{sub 4} ingress (loading) from the waste body at selected locations. Fluxes of CH{sub 4} into or out of the cover soil were quantified by eddy-covariance and static flux-chamber measurements. In addition, CH{sub 4} concentrations at the soil surface were monitored using a field-portable FID detector. Near-surface CH{sub 4} fluxes and CH{sub 4} loading were estimated from soil-gas concentration profiles in conjunction with radon measurements, and gas push-pull tests (GPPTs) were performed to quantify rates of microbial CH{sub 4} oxidation. Eddy-covariance measurements yielded by far the largest and probably most representative estimates of overall CH{sub 4} emissions from the test section (daily mean up to {approx}91,500 {mu}mol m{sup -2} d{sup -1}), whereas flux-chamber measurements and CH{sub 4} concentration profiles indicated that at the majority of locations the cover soil was a net sink for atmospheric CH{sub 4} (uptake up to -380 {mu}mol m{sup -2} d{sup -1}) during the experimental period. Methane concentration profiles also indicated strong variability in CH{sub 4} loading over short distances in the cover soil, while potential methanotrophic activity derived from GPPTs was high (v{sub max} {approx} 13 mmol L{sup -1}(soil air) h{sup -1}) at a location with substantial CH{sub 4} loading. Our results provide a basis to assess spatial and temporal variability of CH{sub 4} dynamics in the complex terrain of a landfill-cover soil.« less

Mechanistic modeling of reactive soil nitrogen emissions across agricultural management practices

NASA Astrophysics Data System (ADS)

Rasool, Q. Z.; Miller, D. J.; Bash, J. O.; Venterea, R. T.; Cooter, E. J.; Hastings, M. G.; Cohan, D. S.

2017-12-01

The global reactive nitrogen (N) budget has increased by a factor of 2-3 from pre-industrial levels. This increase is especially pronounced in highly N fertilized agricultural regions in summer. The reactive N emissions from soil to atmosphere can be in reduced (NH3) or oxidized (NO, HONO, N2O) forms, depending on complex biogeochemical transformations of soil N reservoirs. Air quality models like CMAQ typically neglect soil emissions of HONO and N2O. Previously, soil NO emissions estimated by models like CMAQ remained parametric and inconsistent with soil NH3 emissions. Thus, there is a need to more mechanistically and consistently represent the soil N processes that lead to reactive N emissions to the atmosphere. Our updated approach estimates soil NO, HONO and N2O emissions by incorporating detailed agricultural fertilizer inputs from EPIC, and CMAQ-modeled N deposition, into the soil N pool. EPIC addresses the nitrification, denitrification and volatilization rates along with soil N pools for agricultural soils. Suitable updates to account for factors like nitrite (NO2-) accumulation not addressed in EPIC, will also be made. The NO and N2O emissions from nitrification and denitrification are computed mechanistically using the N sub-model of DAYCENT. These mechanistic definitions use soil water content, temperature, NH4+ and NO3- concentrations, gas diffusivity and labile C availability as dependent parameters at various soil layers. Soil HONO emissions found to be most probable under high NO2- availability will be based on observed ratios of HONO to NO emissions under different soil moistures, pH and soil types. The updated scheme will utilize field-specific soil properties and N inputs across differing manure management practices such as tillage. Comparison of the modeled soil NO emission rates from the new mechanistic and existing schemes against field measurements will be discussed. Our updated framework will help to predict the diurnal and daily variability of different reactive N emissions (NO, HONO, N2O) with soil temperature, moisture and N inputs.

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

USDA-ARS?s Scientific Manuscript database

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Emergent relation between surface vapor conductance and relative humidity profiles yields evaporation rates from weather data

NASA Astrophysics Data System (ADS)

Salvucci, Guido D.; Gentine, Pierre

2013-04-01

The ability to predict terrestrial evapotranspiration (E) is limited by the complexity of rate-limiting pathways as water moves through the soil, vegetation (roots, xylem, stomata), canopy air space, and the atmospheric boundary layer. The impossibility of specifying the numerous parameters required to model this process in full spatial detail has necessitated spatially upscaled models that depend on effective parameters such as the surface vapor conductance (Csurf). Csurf accounts for the biophysical and hydrological effects on diffusion through the soil and vegetation substrate. This approach, however, requires either site-specific calibration of Csurf to measured E, or further parameterization based on metrics such as leaf area, senescence state, stomatal conductance, soil texture, soil moisture, and water table depth. Here, we show that this key, rate-limiting, parameter can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and E. The relation is that the vertical variance of the relative humidity profile is less than would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. It is found to hold over a wide range of climate conditions (arid-humid) and limiting factors (soil moisture, leaf area, energy). With this relation, estimates of E and Csurf can be obtained globally from widely available meteorological measurements, many of which have been archived since the early 1900s. In conjunction with precipitation and stream flow, long-term E estimates provide insights and empirical constraints on projected accelerations of the hydrologic cycle.

Emergent relation between surface vapor conductance and relative humidity profiles yields evaporation rates from weather data.

PubMed

Salvucci, Guido D; Gentine, Pierre

2013-04-16

The ability to predict terrestrial evapotranspiration (E) is limited by the complexity of rate-limiting pathways as water moves through the soil, vegetation (roots, xylem, stomata), canopy air space, and the atmospheric boundary layer. The impossibility of specifying the numerous parameters required to model this process in full spatial detail has necessitated spatially upscaled models that depend on effective parameters such as the surface vapor conductance (C(surf)). C(surf) accounts for the biophysical and hydrological effects on diffusion through the soil and vegetation substrate. This approach, however, requires either site-specific calibration of C(surf) to measured E, or further parameterization based on metrics such as leaf area, senescence state, stomatal conductance, soil texture, soil moisture, and water table depth. Here, we show that this key, rate-limiting, parameter can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and E. The relation is that the vertical variance of the relative humidity profile is less than would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. It is found to hold over a wide range of climate conditions (arid-humid) and limiting factors (soil moisture, leaf area, energy). With this relation, estimates of E and C(surf) can be obtained globally from widely available meteorological measurements, many of which have been archived since the early 1900s. In conjunction with precipitation and stream flow, long-term E estimates provide insights and empirical constraints on projected accelerations of the hydrologic cycle.

Geochemical and thermodynamic specificity of volcanic, hydrothermal and soil aerosols

NASA Astrophysics Data System (ADS)

Mukhamadiyarova, Renata V.; Alekhin, Yury V.; Karpov, Gennady A.; Makarova, Marina A.

2010-05-01

On the basis of element composition analyses results (ICP-MS) of hydrothermal and soil aerosols condensates, and also results of diagnostics of ultradisperse phases by means of power dispersive x-ray spectrometers features of phase and microelement composition of issue aerosols are discussed. Our researches of streams of polyelement issue from a soil cover and specificity of structure of volcanic aerosols have led us to a conclusion that is geochemistry area practically is not developed in the relation of microelement migration in lithosphere - atmosphere. Nanoaerosol particles (0,001 - 1 microns) submit to laws of gas dynamics and in fluid streams are steady enough. Experimental researches of polyelement emission streams from soils and low-temperature microelements migration have allowed to detail the reasons of rather high values of the soil issue. Complexity of authentic definition of forms of carrying over, structure and dispersion of particles of the gas phase emitting from a soil cover, is substantially connected with absence of methodically well-founded receptions of selection of water condensates, free from aerosol components, and methods of their reliable division in a stationary stage of processes of issue and condensation. Reception of the information on factors of distribution of metals between pore solutions, true gas complexes and mineral phases of soils, an estimation of a role gas electrophoresis at transition to molecular cluster and to water colloid aerosols (0.1 microns and less) have allowed us to clear up estimations of streams of soil issue. The differentiation of a multicomponent gas phase in near surface conditions at powerful Tolbachinsky eruption (PTE) 1975 - 1976 to formation of many native metals - gold, silver, copper, lead, bismuth, tungsten, numerous intermetallic compounds. In eruption ashes of Kamchatka volcanoes - Karymsky, Bezymyanny, Kljuchevskoy and Shivelutch we found not only iron oxides but also numerous grains of native metals - Fe, Al, Zn, Cu. Geochemical specificity of aerosol carrying over in eruption columns at volcanic eruptions, often consists in high cleanliness individual many native metals allocations from typical elements - impurity. Presence of tungsten allocations without molybdenum and similar examples for other metals force to assume presence of the specific gas complexes which stability sharply changes at variations of pressure and temperatures in eruption columns at eruptions. Our analysis has shown that for a role of such forms of carrying over can apply metals carbonyls, widely used at reception of especially pure substances. These covalent compounds with formally 0-valency Me in a complex kernel contain variable quantity of groups CO in ligand parts and always complete the electronic cover to a cover of following inert gas, i.e. have in external sphere 4, 5, 6 groups CO, that together with the big distinctions in dependences of constants of formation on temperature their disintegration does non-simultaneous. The thermodynamical description superfluous components fugacity for aerosol systems is developed.

Using remote sensing and GIS techniques to estimate discharge and recharge fluxes for the Death Valley regional groundwater flow system, USA

USGS Publications Warehouse

D'Agnese, F. A.; Faunt, C.C.; Turner, A.K.; ,

1996-01-01

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were used to calculate discharge volumes for these area. An empirical method of groundwater recharge estimation was modified to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

[Effects of soil data and map scale on assessment of total phosphorus storage in upland soils.

PubMed

Li, Heng Rong; Zhang, Li Ming; Li, Xiao di; Yu, Dong Sheng; Shi, Xue Zheng; Xing, Shi He; Chen, Han Yue

2016-06-01

Accurate assessment of total phosphorus storage in farmland soils is of great significance to sustainable agricultural and non-point source pollution control. However, previous studies haven't considered the estimation errors from mapping scales and various databases with different sources of soil profile data. In this study, a total of 393×10 4 hm 2 of upland in the 29 counties (or cities) of North Jiangsu was cited as a case for study. Analysis was performed of how the four sources of soil profile data, namely, "Soils of County", "Soils of Prefecture", "Soils of Province" and "Soils of China", and the six scales, i.e. 1:50000, 1:250000, 1:500000, 1:1000000, 1:4000000 and1:10000000, used in the 24 soil databases established for the four soil journals, affected assessment of soil total phosphorus. Compared with the most detailed 1:50000 soil database established with 983 upland soil profiles, relative deviation of the estimates of soil total phosphorus density (STPD) and soil total phosphorus storage (STPS) from the other soil databases varied from 4.8% to 48.9% and from 1.6% to 48.4%, respectively. The estimated STPD and STPS based on the 1:50000 database of "Soils of County" and most of the estimates based on the databases of each scale in "Soils of County" and "Soils of Prefecture" were different, with the significance levels of P＜0.001 or P＜0.05. Extremely significant differences (P＜0.001) existed between the estimates based on the 1:50000 database of "Soils of County" and the estimates based on the databases of each scale in "Soils of Province" and "Soils of China". This study demonstrated the significance of appropriate soil data sources and appropriate mapping scales in estimating STPS.

Simulating Soil C Stock with the Process-based Model CQESTR

NASA Astrophysics Data System (ADS)

Gollany, H.; Liang, Y.; Rickman, R.; Albrecht, S.; Follett, R.; Wilhelm, W.; Novak, J.; Douglas, C.

2009-04-01

The prospect of storing carbon (C) in soil, as soil organic matter (SOM), provides an opportunity for agriculture to contribute to the reduction of carbon dioxide in the atmosphere while enhancing soil properties. Soil C models are useful for examining the complex interactions between crop, soil management practices and climate and their effects on long-term carbon storage or loss. The process-based carbon model CQESTR, pronounced ‘sequester,' was developed by USDA-ARS scientists at the Columbia Plateau Conservation Research Center, Pendleton, Oregon, USA. It computes the rate of biological decomposition of crop residues or organic amendments as they convert to SOM. CQESTR uses readily available field-scale data to assess long-term effects of cropping systems or crop residue removal on SOM accretion/loss in agricultural soil. Data inputs include weather, above- ground and below-ground biomass additions, N content of residues and amendments, soil properties, and management factors such as tillage and crop rotation. The model was calibrated using information from six long-term experiments across North America (Florence, SC, 19 yrs; Lincoln, NE, 26 yrs; Hoytville, OH, 31 yrs; Breton, AB, 60 yrs; Pendleton, OR, 76 yrs; and Columbia, MO, >100 yrs) having a range of soil properties and climate. CQESTR was validated using data from several additional long-term experiments (8 - 106 yrs) across North America having a range of SOM (7.3 - 57.9 g SOM/kg). Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites resulted in a linear relationship with an r2 of 0.95 (P < 0.0001) and a 95% confidence interval of 4.3 g SOM/kg. Estimated SOC values from CQESTR and IPCC (the Intergovernmental Panel on Climate Change) were compared to observed values in three relatively long-term experiments (20 - 24 years). At one site, CQESTR and IPCC estimates of SOC stocks were within 5% of each other for three rotations. At a second site, decreasing tillage intensity increased SOC stocks for winter wheat-fallow rotation for both observed and estimated values by CQESTR and IPCC. At the third site, CQESTR simulated an increase in SOC stocks with increased fertility levels, while IPCC estimates of SOC stocks did not reflect an increase. The CQESTR model successfully predicts SOM dynamics from various management practices and offers the potential for C sequestration planning for C credits or to guide crop residue removal for bio-energy production without degrading the soil resource, environmental quality, or productivity.

[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.

[Complexes of soil micromycetes in the area of the influence of the Chernobyl Atomic Electric Power Station].

PubMed

Zhdanova, N N; Vasilevskaia, A I; Artyshkova, L V; Gavriliuk, V I; Lashko, T N; Sadovnikov, Iu S

1991-01-01

Complexes of soil micromycetes in the Chernobyl 30-km zone of the Ukrainian Polesye were studied for 1986-1989 with regard for such ecological parameters as the level of radiation contamination, a particular observation site, depth of soil horizon and season. As a result of the study correlation pleiads of soil micromycete complexes have been revealed with their structure and fungal genera characteristic of such complexes determined. The overwhelming majority of correlation pleiads of fungal complexes are attributed to complex-organized ones and this indicated high radioresistance of mycobiota in the studied, soils. Melanine-containing genera of fungi rank among the first in formation of correlation pleiads of soil micromycete complexes.

Soils as relative-age dating tools

USGS Publications Warehouse

Markewich, Helaine Walsh; Pavich, Milan J.; Wysocki, Douglas A.

2017-01-01

Soils develop at the earth's surface via multiple processes that act through time. Precluding burial or disturbance, soil genetic horizons form progressively and reflect the balance among formation processes, surface age, and original substrate composition. Soil morphology provides a key link between process and time (soil age), enabling soils to serve as both relative and numerical dating tools for geomorphic studies and landscape evolution. Five major factors define the contemporary state of all soils: climate, organisms, topography, parent material, and time. Soils developed on similar landforms and parent materials within a given landscape comprise what we term a soil/landform/substrate complex. Soils on such complexes that differ in development as a function of time represent a soil chronosequence. In a soil chronosequence, time constitutes the only independent formation factor; the other factors act through time. Time dictates the variations in soil development or properties (field or laboratory measured) on a soil/landform/substrate complex. Using a dataset within the chronosequence model, we can also formulate various soil development indices based upon one or a combination of soil properties, either for individual soil horizons or for an entire profile. When we evaluate soil data or soil indices mathematically, the resulting equation creates a chronofunction. Chronofunctions help quantify processes and mechanisms involved in soil development, and relate them mathematically to time. These rigorous kinds of comparisons among and within soil/landform complexes constitute an important tool for relative-age dating. After determining one or more absolute ages for a soil/landform complex, we can calculate quantitative soil formation, and or landform-development rates. Multiple dates for several complexes allow rate calculations for soil/landform-chronosequence development and soil-chronofunction calibration.

Understanding the effect of watershed characteristic on the runoff using SCS curve number

NASA Astrophysics Data System (ADS)

Damayanti, Frieta; Schneider, Karl

2015-04-01

Runoff modeling is a key component in watershed management. The temporal course and amount of runoff is a complex function of a multitude of parameters such as climate, soil, topography, land use, and water management. Against the background of the current rapid environmental change, which is due to both i) man-made changes (e.g. urban development, land use change, water management) as well as ii) changes in the natural systems (e.g. climate change), understanding and predicting the impacts of these changes upon the runoff is very important and affects the wellbeing of many people living in the watershed. A main tool for predictions is hydrologic models. Particularly process based models are the method of choice to assess the impact of land use and climate change. However, many regions which experience large changes in the watersheds can be described as rather data poor, which limits the applicability of such models. This is particularly also true for the Telomoyo Watershed (545 km2) which is located in southern part of Central Java province. The average annual rainfall of the study area reaches 2971 mm. Irrigated paddy field are the dominating land use (35%), followed by built-up area and dry land agriculture. The only available soil map is the FAO soil digital map of the world, which provides rather general soil information. A field survey accompanied by a lab analysis 65 soil samples of was carried out to provide more detailed soil texture information. The soil texture map is a key input in the SCS method to define hydrological soil groups. In the frame of our study on 'Integrated Analysis on Flood Risk of Telomoyo Watershed in Response to the Climate and Land Use Change' funded by the German Academic Exchange service (DAAD) we analyzed the sensitivity of the modeled runoff upon the choice of the method to estimate the CN values using the SCS-CN method. The goal of this study is to analyze the impact of different data sources on the curve numbers and the estimated runoff. CN values were estimated using the field measurements of soil textures for different combinations of land use and topography. To transfer the local soil texture measurements to the watershed domain a statistical analysis using the frequency distribution of the measured soil textures is applied and used to derive the effective CN value for a given land use, topography and soil texture combination. Since the curve numbers change as a function of parameter combinations, the effect of different methods to estimate the curve number upon the runoff is analyzed and compared to the straight forward method of using the data from the FAO soil map.

Simulating grazing practices in a complete livestock system model: estimating soil carbon storage and greenhouse gas emissions in grazed versus un-grazed agroecosystems using the Manure-DNDC model

NASA Astrophysics Data System (ADS)

Campbell, E. E.; Dorich, C.; Contosta, A.; Varner, R. K.

2017-12-01

In livestock agroecosystems, the combined contributions of enteric fermentation, manure management, and livestock grazing and/or feed production play an important role in agroecosystem carbon (C) storage and GHG losses, with complete livestock system models acting as important tools to evaluate the full impacts of these complex systems. The Manure-DeNitrification-DeComposition (DNDC) model is one such example, simulating impacts on C and nitrogen cycling, estimating methane, carbon dioxide, nitrous oxide, and ammonium dynamics in fields, manure storage, and enteric emissions. This allows the evaluation of differences in GHG and soil C impacts between conventional and organic dairy production systems, which differ in their use of grazed pasture versus confined feeding operations. However, Manure-DNDC has received limited testing in representing variations in grazed pasture management (i.e. intensive rotational grazing versus standard grazing practices). Using a set of forage biomass, soil C, and GHG emissions data collected at four sites across New England, we parameterized and validated Manure-DNDC estimations of GHG emissions and soil C in grazed versus un-grazed systems. Soil observations from these sites showed little effect from grazing practices, but larger soil carbon differences between farms. This may be due to spatial variation in SOC, making it difficult to measure and model, or due to controls of edaphic properties that make management moot. However, to further address these questions, model development will be needed to improve Manure-DNDC simulation of rotational grazing, as high stocking density grazing over short periods resulted in forage not re-growing sufficiently within the model. Furthermore, model simulations did not account for variation in interactions between livestock and soil given variability in field microclimates, perhaps requiring simulations that divide a single field into multiple paddocks to move towards more accurate evaluation of grazing management used in dairy operations in cool season pastures.

[Humus composition of black soil and its organo-mineral complexes under different fertility level].

PubMed

Zhao, Lanpo; Wang, Jie; Liu, Jingshuan; Liu, Shuxia; Wang, Yanling; Wang, Hongbin; Zhang, Zhidan

2005-01-01

Determinations by Kumada method showed that with the improvement of black soil fertility, the free and combined humus contents in soil and its different size organo-mineral complexes increased, but the humification degree of free humus decreased, which was more obvious in silt and fine sand size complexes. The organic carbon content in complexes, humus extraction rate, free humus content, and humification degree of free humic acid decreased with the increasing particle size of complexes. All free humic acids in fertile soil were Rp type, while in unfertile soil, they were Rp and B type. With the increasing particle size of complexes, the type of free humic acids changed in the sequence A type (clay)-->B type (silt)-->Rp type (fine sand). Combined form humic acid mainly belonged to A type, no matter what particle size the complex was. The improvement of soil fertility could make the humification degree of free humus in soil and its complexes decrease, and furthermore, result in type change. In black soil, the type change of free humic acid mainly occurred in silt size complex, and that of combined form humic acid mainly occurred in fine sand size complex.

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.

CONSERVB: A numerical method to compute soil water content and temperature profiles under a bare surface

NASA Technical Reports Server (NTRS)

Vanbavel, C. H. M.; Lascano, R. J.

1982-01-01

A comprehensive, yet fairly simple model of water disposition in a bare soil profile under the sequential impact of rain storms and other atmospheric influences, as they occur from hour to hour is presented. This model is intended mostly to support field studies of soil moisture dynamics by our current team, to serve as a background for the microwave measurements, and, eventually, to serve as a point of departure for soil moisture predictions for estimates based in part upon airborne measurements. The main distinction of the current model is that it accounts not only for the moisture flow in the soil-atmosphere system, but also for the energy flow and, hence, calculates system temperatures. Also, the model is of a dynamic nature, capable of supporting any required degree of resolution in time and space. Much critical testing of the sample is needed before the complexities of the hydrology of a vegetated surface can be related meaningfully to microwave observations.

Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.

PubMed

Youssef, Noha H; Elshahed, Mostafa S

2008-09-01

Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.

A Unified Experimental Approach for Estimation of Irrigationwater and Nitrate Leaching in Tree Crops

NASA Astrophysics Data System (ADS)

Hopmans, J. W.; Kandelous, M. M.; Moradi, A. B.

2014-12-01

Groundwater quality is specifically vulnerable in irrigated agricultural lands in California and many other(semi-)arid regions of the world. The routine application of nitrogen fertilizers with irrigation water in California is likely responsible for the high nitrate concentrations in groundwater, underlying much of its main agricultural areas. To optimize irrigation/fertigation practices, it is essential that irrigation and fertilizers are applied at the optimal concentration, place, and time to ensure maximum root uptake and minimize leaching losses to the groundwater. The applied irrigation water and dissolved fertilizer, as well as root growth and associated nitrate and water uptake, interact with soil properties and fertilizer source(s) in a complex manner that cannot easily be resolved. It is therefore that coupled experimental-modeling studies are required to allow for unraveling of the relevant complexities that result from typical field-wide spatial variations of soil texture and layering across farmer-managed fields. We present experimental approaches across a network of tree crop orchards in the San Joaquin Valley, that provide the necessary soil data of soil moisture, water potential and nitrate concentration to evaluate and optimize irrigation water management practices. Specifically, deep tensiometers were used to monitor in-situ continuous soil water potential gradients, for the purpose to compute leaching fluxes of water and nitrate at both the individual tree and field scale.

Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing

NASA Technical Reports Server (NTRS)

Vandegriend, A. A.; Oneill, P. E.

1986-01-01

Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

Estimated Annual Net Change in Soil Carbon per US County, 1990-2004

DOE Data Explorer

West, Tristram O.; Brandt, Craig C.; Wilson, Bradly S.; Hellwinckel, Chap M.; Tyler, Donald D.; Marland, Gregg; De La Torre Ugarte, Daniel D.; Larson, James A.; Nelson, Richard G.

2008-01-01

These data represent the estimated net change (Megagram per year) in soil carbon due to changes in the crop type and tillage intensity. Estimated accumulation of soil carbon under Conservation Reserve Program (CRP)lands is included in these estimates. Negative values represent a net flux from the atmosphere to the soil; positive values represent a net flux from the soil to the atmosphere. As such, soil carbon sequestration is represented here as a negative value.

"LOVE TO HATE" pesticides: felicity or curse for the soil microbial community? An FP7 IAPP Marie Curie project aiming to establish tools for the assessment of the mechanisms controlling the interactions of pesticides with soil microorganisms.

PubMed

Karpouzas, D G; Tsiamis, G; Trevisan, M; Ferrari, F; Malandain, C; Sibourg, O; Martin-Laurent, F

2016-09-01

Pesticides end up in soil where they interact with soil microorganisms in various ways. On the Yin Side of the interaction, pesticides could exert toxicity on soil microorganisms, while on the Yang side of interaction, pesticides could be used as energy source by a fraction of the soil microbial community. The LOVE TO HATE project is an IAPP Marie Curie project which aims to study these complex interactions of pesticides with soil microorganisms and provide novel tools which will be useful both for pesticide regulatory purposes and agricultural use. On the Yin side of the interactions, a new regulatory scheme for assessing the soil microbial toxicity of pesticides will be proposed based on the use of advanced standardized tools and a well-defined experimental tiered scheme. On the Yang side of the interactions, advanced molecular tools like amplicon sequencing and functional metagenomics will be applied to define microbes that are involved in the rapid transformation of pesticides in soils and isolate novel pesticide biocatalysts. In addition, a functional microarray has been designed to estimate the biodegradation genetic potential of the microbial community of agricultural soils for a range of pesticide groups.

Nonlinear Spectral Mixture Modeling to Estimate Water-Ice Abundance of Martian Regolith

NASA Astrophysics Data System (ADS)

Gyalay, Szilard; Chu, Kathryn; Zeev Noe Dobrea, Eldar

2017-10-01

We present a novel technique to estimate the abundance of water-ice in the Martian permafrost using Phoenix Surface Stereo Imager multispectral data. In previous work, Cull et al. (2010) estimated the abundance of water-ice in trenches dug by the Mars Phoenix lander by modeling the spectra of the icy regolith using the radiative transfer methods described in Hapke (2008) with optical constants for Mauna Kea palagonite (Clancy et al., 1995) as a substitute for unknown Martian regolith optical constants. Our technique, which uses the radiative transfer methods described in Shkuratov et al. (1999), seeks to eliminate the uncertainty that stems from not knowing the composition of the Martian regolith by using observations of the Martian soil before and after the water-ice has sublimated away. We use observations of the desiccated regolith sample to estimate its complex index of refraction from its spectrum. This removes any a priori assumptions of Martian regolith composition, limiting our free parameters to the estimated real index of refraction of the dry regolith at one specific wavelength, ice grain size, and regolith porosity. We can then model mixtures of regolith and water-ice, fitting to the original icy spectrum to estimate the ice abundance. To constrain the uncertainties in this technique, we performed laboratory measurements of the spectra of known mixtures of water-ice and dry soils as well as those of soils after desiccation with controlled viewing geometries. Finally, we applied the technique to Phoenix Surface Stereo Imager observations and estimated water-ice abundances consistent with pore-fill in the near-surface ice. This abundance is consistent with atmospheric diffusion, which has implications to our understanding of the history of water-ice on Mars and the role of the regolith at high latitudes as a reservoir of atmospheric H2O.

Integrative assessment of the effects produced by Ag nanoparticles at different levels of biological complexity in Eisenia fetida maintained in two standard soils (OECD and LUFA 2.3).

PubMed

Garcia-Velasco, N; Peña-Cearra, A; Bilbao, E; Zaldibar, B; Soto, M

2017-08-01

There is a potential risk to increase the release of silver nanoparticles (Ag NPs) into the environment: For instance. in soils receiving sludge models estimate 0.007 mg Ag NPs kg -1 that will annually increase due to sludge or sludge incineration residues land-disposal. Thus, the concern about the hazards of nanosilver to soils and soil invertebrates is growing. Studies performed up to now have been focused in traditional endpoints, used limit range concentrations and employed different soil types that differ in physico-chemical characteristics. Presently, effects of Ag NPs have been measured at different levels of biological complexity in Eisenia fetida, exposed for 3 and 14 d to high but sublethal (50 mg Ag NPs kg -1 ) and close to modeled environmental concentrations (0.05 mg Ag NPs kg -1 ). Since characteristics of the exposure matrix may limit the response of the organisms to these concentrations, experiments were carried out in OECD and LUFA soils, the most used standard soils. High concentrations of Ag NPs increased catalase activity and DNA damage in OECD soils after 14 d while in LUFA 2.3 soils produced earlier effects (weight loss, decrease in cell viability and increase in catalase activity at day 3). At day 14, LUFA 2.3 (low clay and organic matter-OM-) could have provoked starvation of earthworms, masking Ag NPs toxicity. The concentration close to modeled environmental concentrations produced effects uniquely in LUFA 2.3 soil. Accurate physico-chemical characteristics of the standard soils are crucial to assess the toxicity exerted by Ag NPs in E. fetida since low clay and OM contents can be considered toxicity enhancers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Projecting the release of carbon from permafrost soils using a perturbed physics ensemble modelling approach

NASA Astrophysics Data System (ADS)

MacDougall, Andrew; Knutti, Reto

2016-04-01

The soils of the northern hemisphere permafrost region are estimated to contain 1100 to 1500 Pg of carbon. A substantial fraction of this carbon has been frozen and therefore protected from microbial decay for millennia. As anthropogenic climate warming progresses permafrost soils are expected to thaw. Here we conduct perturbed physics experiments on a climate model of intermediate complexity, with an improved permafrost carbon module, to estimate with formal uncertainty bounds the release of carbon from permafrost soils by year 2100 and 2300. We estimate that by year 2100 the permafrost region may release between 56 (13 to 118)Pg C under Representative Concentration Pathway (RCP) 2.6 and 102 (27 to 199) Pg C under RCP 8.5, with substantially more to be released under each scenario by 2300. A subset of 25 model variants is projected 8000 years into the future under continued RCP 4.5 and 8.5 forcing. Under the high forcing scenario the permafrost carbon pool decays away over several thousand years. Under the moderate forcing scenario a remnant near-surface permafrost region persists in the High-Arctic, which develops a large permafrost carbon pool, leading to a global recovery of the pool beginning in mid third millennium of the common era. Overall our simulations suggest that the permafrost carbon cycle feedback to climate change will make a significant but not cataclysmic contribution to climate change over the next centuries and millennia.

Profile soil property estimation using a VIS-NIR-EC-force probe

USDA-ARS?s Scientific Manuscript database

Combining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. ...

Comparing the performance of coupled soil-vegetation-atmosphere models at two contrasting field sites in South-West Germany

NASA Astrophysics Data System (ADS)

Gayler, S.; Wöhling, T.; Priesack, E.; Wizemann, H.-D.; Wulfmeyer, V.; Ingwersen, J.; Streck, T.

2012-04-01

The soil moisture, the energy balance at the land surface and the state of the lower atmosphere are closely linked by complex feedback processes. The vegetation acts as the interface between soil and atmosphere and plays an important role in this coupled system. Consequently, a consistent description of the fluxes of water, energy and carbon is a prerequisite for analyzing many problems in soil-, plant- and atmospheric research. To better understand the complex interplay of the involved processes, many numerical and physics-based soil-plant-atmosphere simulation models were developed during the last decades. As these models have been developed for different purposes, the degree of complexity in describing individual feedback processes can vary considerably. In models designed to predict soil moisture, for example, plants are often sufficiently represented by a simple sink term. If these models are calibrated, sometimes only one state variable and the corresponding calibration data type is used, e.g. soil water contents or pressure heads. In this case, vegetation properties and feedbacks between soil moisture, plant growth and stomatal conductivity are neglected to a large extent. Some crop models, in turn, pay little attention to modeling soil water transport. In a coupled soil-vegetation-atmosphere model, however, the interface between soil and atmosphere has to be consistent in all directions. As different data types such as soil moisture, leaf area development and evapotranspiration may contain contrasting information about the system under consideration, the fitting of such a model to a single data type may result in a poor agreement to another data type. The trade-off between the fittings to different data types can thereby be caused by structural inadequacies in the model or by errors in input and calibration data. In our study, we compare the Community Land Model CLM (version 3.5, offline mode) with different agricultural crop models to analyze the adequacy of their structural complexity on two winter wheat research fields under different climate in South-West Germany. We investigate the ability of the models to simultaneously fit measured soil water contents, leaf area development and actual evapotranspiration rates from eddy-covariance measurements. The calibration of the models is performed in a multi-criteria context using three objective functions, which describe the discrepancy between measurements and simulations of the three data types. We use the AMALGAM evolutionary search algorithm to simultaneously estimate the most important plant and soil hydraulic parameters. The results show that the trade-off in fitting soil moisture, leaf area development and evapotranspiration can be quite large for those models that represent plant processes by simple concepts. However, these trade-offs are smaller for the more mechanistic plant growth models, so that it can be expected that these optimized mechanistic models will provide the basis for improved simulations of land-surface-atmosphere feedback processes.

Closing the water balance with cosmic-ray soil moisture measurements and assessing their spatial variability within two semiarid watersheds

NASA Astrophysics Data System (ADS)

Schreiner-McGraw, A. P.; Vivoni, E. R.; Mascaro, G.; Franz, T. E.

2015-06-01

Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate scale soil moisture estimates from the cosmic-ray sensing (CRS) method are evaluated for two semiarid ecosystems in the southwestern United States: a mesquite savanna at the Santa Rita Experimental Range (SRER) and a mixed shrubland at the Jornada Experimental Range (JER). Evaluations of the CRS method are performed for small watersheds instrumented with a distributed sensor network consisting of soil moisture sensor profiles, an eddy covariance tower and runoff flumes used to close the water balance. We found an excellent agreement between the CRS method and the distributed sensor network (RMSE of 0.009 and 0.013 m3 m-3 at SRER and JER) at the hourly time scale over the 19-month study period, primarily due to the inclusion of 5 cm observations of shallow soil moisture. Good agreement was obtained in soil moisture changes estimated from the CRS and watershed water balance methods (RMSE = 0.001 and 0.038 m3 m-3 at SRER and JER), with deviations due to bypassing of the CRS measurement depth during large rainfall events. This limitation, however, was used to show that drier-than-average conditions at SRER promoted plant water uptake from deeper layers, while the wetter-than-average period at JER resulted in leakage towards deeper soils. Using the distributed sensor network, we quantified the spatial variability of soil moisture in the CRS footprint and the relation between evapotranspiration and soil moisture, in both cases finding similar predictive relations at both sites that are applicable to other semiarid ecosystems in the southwestern US. Furthermore, soil moisture spatial variability was related to evapotranspiration in a manner consistent with analytical relations derived using the CRS method, opening up new possibilities for understanding land-atmosphere interactions.

Modeling runoff and sediment yield from a terraced watershed using WEPP

Treesearch

Mary Carla McCullough; Dean E. Eisenhauer; Michael G. Dosskey

2008-01-01

The watershed version of WEPP (Water Erosion Prediction Project) was used to estimate 50-year runoff and sediment yields for a 291 ha watershed in eastern Nebraska that is 90% terraced and which has no historical gage data. The watershed has a complex matrix of elements, including terraced and non-terraced subwatersheds, multiple combinations of soils and land...

A surface complexation and ion exchange model of Pb and Cd competitive sorption on natural soils

NASA Astrophysics Data System (ADS)

Serrano, Susana; O'Day, Peggy A.; Vlassopoulos, Dimitri; García-González, Maria Teresa; Garrido, Fernando

2009-02-01

The bioavailability and fate of heavy metals in the environment are often controlled by sorption reactions on the reactive surfaces of soil minerals. We have developed a non-electrostatic equilibrium model (NEM) with both surface complexation and ion exchange reactions to describe the sorption of Pb and Cd in single- and binary-metal systems over a range of pH and metal concentration. Mineralogical and exchange properties of three different acidic soils were used to constrain surface reactions in the model and to estimate surface densities for sorption sites, rather than treating them as adjustable parameters. Soil heterogeneity was modeled with >FeOH and >SOH functional groups, representing Fe- and Al-oxyhydroxide minerals and phyllosilicate clay mineral edge sites, and two ion exchange sites (X - and Y -), representing clay mineral exchange. An optimization process was carried out using the entire experimental sorption data set to determine the binding constants for Pb and Cd surface complexation and ion exchange reactions. Modeling results showed that the adsorption of Pb and Cd was distributed between ion exchange sites at low pH values and specific adsorption sites at higher pH values, mainly associated with >FeOH sites. Modeling results confirmed the greater tendency of Cd to be retained on exchange sites compared to Pb, which had a higher affinity than Cd for specific adsorption on >FeOH sites. Lead retention on >FeOH occurred at lower pH than for Cd, suggesting that Pb sorbs to surface hydroxyl groups at pH values at which Cd interacts only with exchange sites. The results from the binary system (both Pb and Cd present) showed that Cd retained in >FeOH sites decreased significantly in the presence of Pb, while the occupancy of Pb in these sites did not change in the presence of Cd. As a consequence of this competition, Cd was shifted to ion exchange sites, where it competes with Pb and possibly Ca (from the background electrolyte). Sorption on >SOH functional groups increased with increasing pH but was small compared to >FeOH sites, with little difference between single- and binary-metal systems. Model reactions and conditional sorption constants for Pb and Cd sorption were tested on a fourth soil that was not used for model optimization. The same reactions and constants were used successfully without adjustment by estimating surface site concentrations from soil mineralogy. The model formulation developed in this study is applicable to acidic mineral soils with low organic matter content. Extension of the model to soils of different composition may require selection of surface reactions that account for differences in clay and oxide mineral composition and organic matter content.

Comparison of field and laboratory VNIR spectroscopy for profile soil property estimation

USDA-ARS?s Scientific Manuscript database

In-field, in-situ data collection with soil sensors has potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate important soil properties, such as soil carbon, nitrogen, water content, and texture. Most pre...

Estimation of soil profile physical and chemical properties using a VIS-NIR-EC-force probe

USDA-ARS?s Scientific Manuscript database

Combining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. ...

Spectrometry of Pasture Condition and Biogeochemistry in the Central Amazon

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Townsend, Alan R.; Bustamante, Mercedes M. C.

1999-01-01

Regional analyses of Amazon cattle pasture biogeochemistry are difficult due to the complexity of human, edaphic, biotic and climatic factors and persistent cloud cover in satellite observations. We developed a method to estimate key biophysical properties of Amazon pastures using hyperspectral reflectance data and photon transport inverse modeling. Remote estimates of live and senescent biomass were strongly correlated with plant-available forms of soil phosphorus and calcium. These results provide a basis for monitoring pasture condition and biogeochemistry in the Amazon Basin using spaceborne hyperspectral sensors.

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

NASA Astrophysics Data System (ADS)

Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

2018-04-01

As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.

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.

Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown

PubMed Central

Ymeti, Irena; van der Werff, Harald; Shrestha, Dhruba Pikha; Jetten, Victor G.; Lievens, Caroline; van der Meer, Freek

2017-01-01

Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing–thawing cycles are the cause of soil aggregate breakdown. PMID:28556803

Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown.

PubMed

Ymeti, Irena; van der Werff, Harald; Shrestha, Dhruba Pikha; Jetten, Victor G; Lievens, Caroline; van der Meer, Freek

2017-05-30

Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing-thawing cycles are the cause of soil aggregate breakdown.

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

NASA Astrophysics Data System (ADS)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

[Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.

PubMed

Wang, Min Zheng; Zhou, Guang Sheng

2016-06-01

Soil moisture is an important component of the soil-vegetation-atmosphere continuum (SPAC). It is a key factor to determine the water status of terrestrial ecosystems, and is also the main source of water supply for crops. In order to estimate soil moisture at different soil depths at a station scale, based on the energy balance equation and the water deficit index (WDI), a soil moisture estimation model was established in terms of the remote sensing data (the normalized difference vegetation index and surface temperature) and air temperature. The soil moisture estimation model was validated based on the data from the drought process experiment of summer maize (Zea mays) responding to different irrigation treatments carried out during 2014 at Gucheng eco-agrometeorological experimental station of China Meteorological Administration. The results indicated that the soil moisture estimation model developed in this paper was able to evaluate soil relative humidity at different soil depths in the summer maize field, and the hypothesis was reasonable that evapotranspiration deficit ratio (i.e., WDI) linearly depended on soil relative humidity. It showed that the estimation accuracy of 0-10 cm surface soil moisture was the highest (R 2 =0.90). The RMAEs of the estimated and measured soil relative humidity in deeper soil layers (up to 50 cm) were less than 15% and the RMSEs were less than 20%. The research could provide reference for drought monitoring and irrigation management.

Fe-C interactions and soil organic matter stability in two tropical soils of contrasting parent materials

NASA Astrophysics Data System (ADS)

Coward, E.; Thompson, A.; Plante, A. F.

2014-12-01

The long residence time of soil organic matter (SOM) is a dynamic property, reflecting the diversity of stabilization mechanisms active within the soil matrix. Climate and ecosystem properties act at the broadest scale, while biochemical recalcitrance, physical occlusion and mineral association drive stability at the microscale. Increasing evidence suggests that the stability of SOM is dominated by organo-mineral interactions. However, the 2:1 clays that provide much of the stabilization capacity in temperate soils are typically absent in tropical soils due to weathering. In contrast, these soils may contain an abundance of iron and aluminium oxides and oxyhydroxides, known as short-range-order (SRO) minerals. These SRO minerals are capable of SOM stabilization through adsorption or co-precipitation, a faculty largely enabled by their high specific surface area (SSA). As such, despite their relatively small mass, SRO minerals may contribute substantially to the SOM stabilization capacity of tropical soils. The objective of this work is to characterize and quantify these Fe-C interactions. Surface (0-20 cm) soil samples were taken from 20 quantitative soil pits dug within the Luquillo Critical Zone Observatory in northeast Puerto Rico. Soils were stratified across granodiorite and volcaniclastic parent materials. Four extraction procedures were used to isolate three different forms of Fe-C interactions: sodium pyrophosphate to isolate organo-metallic complexes, hydroxylamine and oxalate to isolate SRO Fe- and Al-hydroxides, and dithionite to isolate crystalline Fe-oxyhydroxides. Extracts were analysed for DOC and Fe and Al concentrations to estimate the amount of SOM associated with each mineral type. Soils were subjected to SSA and solid-phase C analyses before and after extraction to determine the contribution of the various Fe mineral types to soil SSA, and therefore to potential stabilization capacity through organo-mineral complexation. Preliminary results suggest that extracts from granodiorite parent material contain on average twice the Fe than those from volcaniclastic parent material. The removal of SRO minerals reduced SSA in both soil types, and appear to contribute substantially to SOM stabilization compared to the bulk mineral matrix.

Scaling up carbonyl sulfide (COS) fluxes from leaf and soil to the canopy

NASA Astrophysics Data System (ADS)

Yang, Fulin; Yakir, Dan

2016-04-01

Carbonyl sulfide (COS) with atmospheric concentrations around 500 ppt is an analog of CO2 which can potentially serve as powerful and much needed tracer of photosynthetic CO2 uptake, and global gross primary production (GPP). However, questions remain regarding the application of this approach due to uncertainties in the contributions of different ecosystem components to the canopy scale fluxes of COS. We used laser quantum cascade spectroscopy in combination with soil and branch chambers, and eddy covariance measurements of net ecosystem exchange fluxes of COS and CO2 (NEE) in citrus orchard during the driest summer month to test our ability to integrate the chamber measurements into the ecosystem fluxes. The results indicated that: 1) Soil fluxes showed clear gradient from continuous uptake under the trees in wet soil of up to -4 pmol m-2s-1 (CO2 emission of ~0.5 umol m-2s-1) to emission in dry hot and exposed soil between rows of trees of up to +3 pmol m-2s-1 (CO2 emission of ~11 umol m-2s-1). In all cases a clear correlation between fluxes and soil temperature was observed. 2) At the leaf scale, midday uptake was ~5.5 pmol m-2s-1 (CO2 uptake of ~1.8 umol m-2s-1). Some nighttime COS uptake was observed in the citrus leaves consistent with nocturnal leaf stomatal conductance. Leaf relative uptake (LRU) of COS vs. CO2 was not constant over the diurnal cycle, but showed exponential correlation with photosynthetically active radiation (PAR) during the daytime. 3) At the canopy scale mid-day summer flux reached -12.0 pmol m-2s-1 (NEE ~6 umol m-2s-1) with the diurnal patterns of COS fluxes following those of CO2 fluxes during the daytime, but with small COS uptake fluxes maintained also during the night when significant CO2 emission fluxes were observed. The canopy-scale fluxes always indicated COS uptake, irrespective of the soil emission effects. GPP estimates were consistent with conventional indirect estimates based on NEE and nocturnal measurements. Scaling up from soil and leaf chamber to canopy scale was possible by estimating LAI, and differential consideration of soil surface components (shaded vs. exposed fractions). 4) Diurnal changes in the atmospheric concentrations of COS and CO2 above the canopy showed complex patterns with opposite trends after sunrise that could be explain by the development of the planetary boundary layer 5) COS-based estimate of GPP can be improved by adopting light dependent LRU, around the mean value of ~1.6, and correcting for soil COS fluxes based on soil temperature and canopy cover estimates, and coupled COS/CO2 concentration measurements provide useful information on boundary layer dynamics.

The hidden ecological resource of andic soils in mountain ecosystems: evidence from Italy

NASA Astrophysics Data System (ADS)

Terribile, Fabio; Iamarino, Michela; Langella, Giuliano; Manna, Piero; Mileti, Florindo Antonio; Vingiani, Simona; Basile, Angelo

2018-01-01

Andic soils have unique morphological, physical, and chemical properties that induce both considerable soil fertility and great vulnerability to land degradation. Moreover, they are the most striking mineral soils in terms of large organic C storage and long C residence time. This is especially related to the presence of poorly crystalline clay minerals and metal-humus complexes. Recognition of andic soils is then very important.Here we attempt to show, through a combined analysis of 35 sampling points chosen in accordance to specific physical and vegetation rules, that some andic soils have an utmost ecological importance.More specifically, in Italian non-volcanic mountain ecosystems ( > 600 m a.s.l.) combining low slope (< 21 %) and highly active green biomass (high NDVI values) and in agreement to recent findings, we found the widespread occurrence of andic soils having distinctive physical and hydrological properties including low bulk density and remarkably high water retention. Most importantly, we report a demonstration of the ability of these soils to affect ecosystem functions by analysing their influence on the timescale acceleration of photosynthesis estimated by NDVI measurements.Our results are hoped to be a starting point for better understanding of the ecological importance of andic soils and also possibly to better consider pedological information in C balance calculations.

Macroscopic behavior and fluctuation-dissipation response of stochastic ecohydrological systems

NASA Astrophysics Data System (ADS)

Porporato, A. M.

2017-12-01

The coupled dynamics of water, carbon and nutrient cycles in ecohydrological systems is forced by unpredictable and intermittent hydroclimatic fluctuations at different time scales. While modeling and long-term prediction of these complex interactions often requires a probabilistic approach, the resulting stochastic equations however are only solvable in special cases. To obtain information on the behavior of the system one typically has to resort to approximation methods. Here we discuss macroscopic equations for the averages and fluctuation-dissipation estimates for the general correlations between the forcing and the ecohydrological response for the soil moisture-plant biomass interaction and the problem of primary salinization and nitrogen retention in soils.

Antecedent Wetness Conditions based on ERS scatterometer data in support to rainfall-runoff modeling

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.

2009-04-01

Despite of its small volume compared to other components of the hydrologic cycle, the soil moisture is of fundamental importance to many hydrological, meteorological, biological and biogeochemical processes. For storm rainfall-runoff modeling the estimation of the Antecedent Wetness Conditions (AWC) is one of the most important issues to determine the hydrological response. In this context, this study investigates the potential of the scatterometer on board of the ERS satellites for the assessment of soil wetness conditions at two different scales. The satellite soil moisture data set, available from 1992, is downloaded from the ERS/METOP Soil Moisture archive located at http://www.ipf.tuwien.ac.at/radar/index.php?go=ascat. At the local scale, the scatterometer-derived soil wetness index (SWI) data (Wagner, W., Lemoine, G., and Rott, H., 1999. A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data. Remote Sensing of Environment, 70, 191-207) have been compared with two in-situ soil moisture data sets. At the catchment scale, the reliability of the SWI to estimate the AWC has been tested considering its relationship with the soil potential maximum retention parameter, S, of the Soil Conservation Service-Curve Number (SCS-CN) method for abstraction. The parameter S has been derived by considering several flood events occurred from 1992 to 2005 in different catchments of central Italy. The performance of two Antecedent Precipitation Indices (API) and one Base Flow Index (BFI), usually employed in the hydrological practice for the AWC assessment, have been compared with the SWI. The obtained results show a high accuracy of the SWI for the estimation of wetness conditions both at the local and catchment scale despite of the complex orography of the investigated areas (Brocca, L., Melone, F., Moramarco, T., Morbidelli, R., 2009. Antecedent wetness conditions based on ERS scatterometer data. Journal of Hydrology, 364 (1-2), 73-87). At the local scale, the SWI has been found quite reliable in representing the soil moisture at layer depth of 15 cm with average correlation coefficient equal to 0.81 and a root mean square error of ~ 0.04 m3/m3. In terms of AWC assessment at the catchment scale, the SWI has been found highly correlated with the observed S parameter with correlation coefficient equal to -0.90. Besides, SWI outperformed both API indices, poorly representative of AWC, and BFI. The methodology delineated in this study can be considered as a simple and entirely new approach to validate the remotely sensed soil moisture estimates at the catchment scale, mainly for coarse resolution sensors as scatterometers and radiometers. The obtained results indirectly reveal the usefulness of the SWI both for flood forecasting applications and for prediction in ungauged basins. Moreover, the correlation of in-situ soil moisture measurements with the SWI reveals the potential of scatterometer data, particularly considering the higher spatial resolution provided by the successor of ERS scatterometer, the Advanced Scatterometer, ASCAT, on board of the meteorological operational platforms, METOP.

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.

Estimating soil matric potential in Owens Valley, California

USGS Publications Warehouse

Sorenson, Stephen K.; Miller, Reuben F.; Welch, Michael R.; Groeneveld, David P.; Branson, Farrel A.

1989-01-01

Much of the floor of Owens Valley, California, is covered with alkaline scrub and alkaline meadow plant communities, whose existence is dependent partly on precipitation and partly on water infiltrated into the rooting zone from the shallow water table. The extent to which these plant communities are capable of adapting to and surviving fluctuations in the water table depends on physiological adaptations of the plants and on the water content, matric potential characteristics of the soils. Two methods were used to estimate soil matric potential in test sites in Owens Valley. The first, the filter-paper method, uses water content of filter papers equilibrated to water content of soil samples taken with a hand auger. The previously published calibration relations used to estimate soil matric potential from the water content of the filter papers were modified on the basis of current laboratory data. The other method of estimating soil matric potential was a modeling approach based on data from this and previous investigations. These data indicate that the base-10 logarithm of soil matric potential is a linear function of gravimetric soil water content for a particular soil. The slope and intercepts of this function vary with the texture and saturation capacity of the soil. Estimates of soil water characteristic curves were made at two sites by averaging the gravimetric soil water content and soil matric potential values from multiple samples at 0.1-m depth intervals derived by using the hand auger and filter-paper method and entering these values in the soil water model. The characteristic curves then were used to estimate soil matric potential from estimates of volumetric soil water content derived from neutron-probe readings. Evaluation of the modeling technique at two study sites indicated that estimates of soil matric potential within 0.5 pF units of the soil matric potential value derived by using the filter-paper method could be obtained 90 to 95 percent of the time in soils where water content was less than field capacity. The greatest errors occurred at depths where there was a distinct transition between soils of different textures.

Dynamics of Zn in an urban wetland soil-plant system: Coupling isotopic and EXAFS approaches

NASA Astrophysics Data System (ADS)

Aucour, Anne-Marie; Bedell, Jean-Philippe; Queyron, Marine; Magnin, Valérie; Testemale, Denis; Sarret, Géraldine

2015-07-01

Plants play a key role in the stabilization of metals in contaminated environments. Studies have been performed on Zn uptake and storage mechanisms, mainly for Zn hyperaccumulating plants, though less is known about Zn stabilization in the rhizosphere of non-accumulating plants. This study was focused on the dynamics of Zn in a whole soil-litter-plant system and the processes controlling Zn mobilization and stabilization. The site studied was an infiltration basin receiving urban stormwater, in which Phalaris arundinacea (reed canary grass) developed spontaneously. A combination of chemical extractions (CaCl2, DTPA), EXAFS spectroscopy and Zn stable isotope measurements was applied for the water inlet, soil, plant organs and decaying biomass. Zn speciation changed from the water inlet to the soil. In the soil, Zn was present as Zn-layered double hydroxide (Zn-LDH), tetrahedral and octahedral sorbed Zn species. The formation of Zn-LDH participates in Zn stabilization. Tetrahedral Zn species, which were partly DTPA exchangeable, were enriched in heavy isotopes, whereas octahedral Zn (Zn-LDH and sorbed species) were enriched in light isotopes. Based on a linear model between δ66Zn and Zn speciation, δ66Zn for pure tetrahedral and octahedral end-members were estimated at ca. 0.33‰ and 0.04‰, respectively. In the plant, a mixture of octahedral Zn (attributed to aqueous Zn-organic acid complexes present in the symplasm), and tetrahedral Zn (attributed to apoplasmic Zn-cell wall complexes) was observed in all organs. Large enrichment in light isotopes from the soil to the plant Δ66Zn (of ca. -0.6‰) was observed. The stem was enriched in light isotopes versus roots and, to a lesser extent, versus leaves. The results suggest that Zn was taken up via a low-affinity transport system and that Zn was sequestrated in the stem symplasm after transit through leaves. Finally, intense Zn exchanges were observed between the decaying biomass and the soil, with the sorption of heavy Zn from the soil to cell wall remains and release of light Zn to the soil. Overall, this study provides a complete overview of Zn cycling in an urban wetland soil-plant system, and describes several changes in Zn speciation with Zn isotopic fractionation processes in a complex system.

Global distribution of plant-extractable water capacity of soil

USGS Publications Warehouse

Dunne, K.A.; Willmott, C.J.

1996-01-01

Plant-extractable water capacity of soil is the amount of water that can be extracted from the soil to fulfill evapotranspiration demands. It is often assumed to be spatially invariant in large-scale computations of the soil-water balance. Empirical evidence, however, suggests that this assumption is incorrect. In this paper, we estimate the global distribution of the plant-extractable water capacity of soil. A representative soil profile, characterized by horizon (layer) particle size data and thickness, was created for each soil unit mapped by FAO (Food and Agriculture Organization of the United Nations)/Unesco. Soil organic matter was estimated empirically from climate data. Plant rooting depths and ground coverages were obtained from a vegetation characteristic data set. At each 0.5?? ?? 0.5?? grid cell where vegetation is present, unit available water capacity (cm water per cm soil) was estimated from the sand, clay, and organic content of each profile horizon, and integrated over horizon thickness. Summation of the integrated values over the lesser of profile depth and root depth produced an estimate of the plant-extractable water capacity of soil. The global average of the estimated plant-extractable water capacities of soil is 8??6 cm (Greenland, Antarctica and bare soil areas excluded). Estimates are less than 5, 10 and 15 cm - over approximately 30, 60, and 89 per cent of the area, respectively. Estimates reflect the combined effects of soil texture, soil organic content, and plant root depth or profile depth. The most influential and uncertain parameter is the depth over which the plant-extractable water capacity of soil is computed, which is usually limited by root depth. Soil texture exerts a lesser, but still substantial, influence. Organic content, except where concentrations are very high, has relatively little effect.

Comparative approaches from empirical to mechanistic simulation modelling in Land Evaluation studies

NASA Astrophysics Data System (ADS)

Manna, P.; Basile, A.; Bonfante, A.; Terribile, F.

2009-04-01

The Land Evaluation (LE) comprise the evaluation procedures to asses the attitudes of the land to a generic or specific use (e.g. biomass production). From local to regional and national scale the approach to the land use planning should requires a deep knowledge of the processes that drive the functioning of the soil-plant-atmosphere system. According to the classical approaches the assessment of attitudes is the result of a qualitative comparison between the land/soil physical properties and the land use requirements. These approaches have a quick and inexpensive applicability; however, they are based on empirical and qualitative models with a basic knowledge structure specifically built for a specific landscape and for the specific object of the evaluation (e.g. crop). The outcome from this situation is the huge difficulties in the spatial extrapolation of the LE results and the rigidity of the system. Modern techniques instead, rely on the application of mechanistic and quantitative simulation modelling that allow a dynamic characterisation of the interrelated physical and chemical processes taking place in the soil landscape. Moreover, the insertion of physical based rules in the LE procedure may make it less difficult in terms of both extending spatially the results and changing the object (e.g. crop species, nitrate dynamics, etc.) of the evaluation. On the other side these modern approaches require high quality and quantity of input data that cause a significant increase in costs. In this scenario nowadays the LE expert is asked to choose the best LE methodology considering costs, complexity of the procedure and benefits in handling a specific land evaluation. In this work we performed a forage maize land suitability study by comparing 9 different methods having increasing complexity and costs. The study area, of about 2000 ha, is located in North Italy in the Lodi plain (Po valley). The range of the 9 employed methods ranged from standard LE approaches to the extensive use of simulation modelling (SWAP and CropSyst), using as data input pre-existing soil information (soil map 1:50000) and also hydraulic properties measured as well estimated by PTF. The comparison between the different methods was based on both cost and predictive ability of each of the methods. The latter was evaluated by comparison to the estimate of forage maize biomass obtained by using locally tested remote sensing measurements. Statistical indexes like correlation, relative variance and ANOVA test were applied. As expected, higher method complexity corresponds to higher quality/quantity of input parameters and as consequence higher costs. Generally, results show that more complex methods gave better results in terms of their predictive ability and those operating on measurements gave better performance than those operating on PTF. Moreover, the best predictive results were obtained abandoning the support of the soil mapping units, incrementing dramatically the number of sampling and analysis and applying the simulation modelling on real benchmark soils rather than averaging more soils observations. Keywords: Land Evaluation, simulation modelling, CropSyst, SWAP, NDVI.

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Geographic considerations for fire management in the Eastern United States: geomorphology and topography, soils, and climate

Treesearch

Barton D. Clinton; James M. Vose; Erika C. Cohen

2012-01-01

Across the Eastern United States, there is on average an estimated 36 MT ha–1 (16 tons ac–1) of dead woody fuel (Chojnacky and others 2004). Variations in fuel type, size, and flammability make the selection of treatment options critical for effective fuels management. The region is a complex landscape characterized by...

Response of stress indicators and growth parameters of Tibouchina pulchra Cogn. exposed to air and soil pollution near the industrial complex of Cubatão, Brazil.

PubMed

Klumpp, G; Furlan, C M; Domingos, M; Klumpp, A

2000-01-31

The present study was performed in the vicinity of the industrial complex of Cubatão, São Paulo, Brazil, in order to evaluate the response of 'manaca da serra' Tibouchina pulchra Cogn. (Melastomataceae), a common species of secondary Atlantic Rain Forest vegetation, to the impact of complex air pollution. Emphasis was given to changes of biochemical parameters such as ascorbic acid concentration, peroxidase activity, contents of water-soluble thiols, pH of leaf extract and buffering capacity. These plant factors are often used as early indicators of air pollution stress. Field experiments included sampling of leaves from mature trees in areas with different air pollution load (passive monitoring), exposure of saplings cultivated in uniform soil at these areas (active monitoring) and a study on the combined effects of contaminated soil and air pollution. In general, metabolic response of saplings was more accentuated than that of mature trees. Leaf extract pH and buffering capacity showed no or only small alterations in plants exposed to industrial emissions. In contrast, air pollution resulted in a distinct decrease in ascorbic acid contents and an increase in peroxidase activity and thiol concentrations in leaves. Cultivation of saplings in soil types from contaminated regions frequently caused the same modifications or enhanced the effects produced by air pollution. Growth analysis of exposed saplings demonstrated that a change of the relationship between above-ground and below-ground plant parts was the most obvious effect of air pollution and soil contamination. The experiments showed that even T. pulchra, a species considered resistant to air pollution, suffers metabolic disturbances by the present ambient air and soil quality. Although biochemical and physiological alterations were not related to a certain air pollution type, they could be used to estimate the overall pollution load and to map zones with different air quality.

Evaluation of the environmental impact of Brownfield remediation options: comparison of two life cycle assessment-based evaluation tools.

PubMed

Cappuyns, Valérie; Kessen, Bram

2012-01-01

The choice between different options for the remediation of a contaminated site traditionally relies on economical, technical and regulatory criteria without consideration of the environmental impact of the soil remediation process itself. In the present study, the environmental impact assessment of two potential soil remediation techniques (excavation and off-site cleaning and in situ steam extraction) was performed using two life cycle assessment (LCA)-based evaluation tools, namely the REC (risk reduction, environmental merit and cost) method and the ReCiPe method. The comparison and evaluation of the different tools used to estimate the environmental impact of Brownfield remediation was based on a case study which consisted of the remediation of a former oil and fat processing plant. For the environmental impact assessment, both the REC and ReCiPe methods result in a single score for the environmental impact of the soil remediation process and allow the same conclusion to be drawn: excavation and off-site cleaning has a more pronounced environmental impact than in situ soil remediation by means of steam extraction. The ReCiPe method takes into account more impact categories, but is also more complex to work with and needs more input data. Within the routine evaluation of soil remediation alternatives, a detailed LCA evaluation will often be too time consuming and costly and the estimation of the environmental impact with the REC method will in most cases be sufficient. The case study worked out in this paper wants to provide a basis for a more sounded selection of soil remediation technologies based on a more detailed assessment of the secondary impact of soil remediation.

Vs30 mapping at selected sites within the Greater Accra Metropolitan Area

NASA Astrophysics Data System (ADS)

Nortey, Grace; Armah, Thomas K.; Amponsah, Paulina

2018-06-01

A large part of Accra is underlain by a complex distribution of shallow soft soils. Within seismically active zones, these soils hold the most potential to significantly amplify seismic waves and cause severe damage, especially to structures sited on soils lacking sufficient stiffness. This paper presents preliminary site classification for the Greater Accra Metropolitan Area of Ghana (GAMA), using experimental data from two-dimensional (2-D) Multichannel Analysis of Surface Wave (MASW) technique. The dispersive characteristics of fundamental mode Rayleigh type surface waves were utilized for imaging the shallow subsurface layers (approx. up to 30 m depth) by estimating the 1D (depth) and 2D (depth and surface location) shear wave velocities at 5 selected sites. The average shear wave velocity for 30 m depth (Vs30), which is critical in evaluating the site response of the upper 30 m, was estimated and used for the preliminary site classification of the GAM area, as per NEHRP (National Earthquake Hazards Reduction Program). Based on the Vs30 values obtained in the study, two common site types C, and D corresponding to shallow (>6 m < 30 m) weathered rock and deep (up 30 m thick) stiff soils respectively, have been identified within the study area. Lower velocity profiles are inferred for the residual soils (sandy to silty clays), derived from the Accraian Formation that lies mainly within Accra central. Stiffer soil sites lie to the north of Accra, and to the west near Nyanyano. The seismic response characteristics over the residual soils in the GAMA have become apparent using the MASW technique. An extensive site effect map and a more robust probabilistic seismic hazard analysis can now be efficiently built for the metropolis, by considering the site classes and design parameters obtained from this study.

Relevant role of dissolved humic matter in phosphorus bioavailability in natural and agronomical ecosystems through the formation of Humic-(Metal)-Phosphate complexes

NASA Astrophysics Data System (ADS)

Baigorri, Roberto; Urrutia, Óscar; Erro, Javier; Pazos-Pérez, Nicolás; María García-Mina, José

2016-04-01

Natural Organic Matter (NOM) and the NOM fraction present in soil solution (dissolved organic matter: DOM) are currently considered as fundamental actors in soil fertility and crop mineral nutrition. Indeed, decreases in crop yields as well as soil erosion are closely related to low values of NOM and, in fact, the use of organic amendments as both soil improvers and plant growth enhancers is very usual in countries with soils poor in NOM. This role of NOM (and DOM) seems to be associated with the presence of bio-transformed organic molecules (humic substances) with high cation chelating-complexing ability. In fact, bioavailable micronutrients with metallic character in soil solutions of alkaline and calcareous soils are forming stable complexes with DOM. This beneficial action of DOM also concerns other plant nutrients such as inorganic phosphate (Pi). Among the different mechanisms involved in the beneficial action of DOM on P bioavailability, the possible formation of poly-nuclear complexes including stable chemical bonds between negative binding sites in humic substances and Pi through metal bridges in soil solution might be relevant, especially in acidic soils. In fact, several studies have proven that these complexes can be obtained in the laboratory and are very efficient in prevent Pi soil fixation and improve Pi root uptake. However, clear experimental evidence about their presence in soil solutions of natural and agronomical soil ecosystems has not published yet. We present here experimental results supporting the real presence of stable Pi-metal-Humic (PMH) complexes in the soil solution of several acidic soils. The study is based on the physico-chemical characterization (31P-NMR, FTIR, TEM-EDAX, ICP-OES) of the DOM fraction isolated by ultrafiltration from the soil solution of several representative acidic soils. In average, more than 60 % of Pi was found in the soil solution humic fraction forming stable humic-metal (Fe, Al) complexes.

Experimental study of the complex resistivity and dielectric constant of chrome-contaminated soil

NASA Astrophysics Data System (ADS)

Liu, Haorui; Yang, Heli; Yi, Fengyan

2016-08-01

Heavy metals such as arsenic and chromium often contaminate soils near industrialized areas. Soil samples, made with different water content and chromate pollutant concentrations, are often needed to test soil quality. Because complex resistivity and complex dielectric characteristics of these samples need to be measured, the relationship between these measurement results and chromium concentration as well as water content was studied. Based on soil sample observations, the amplitude of the sample complex resistivity decreased with an increase of contamination concentration and water content. The phase of complex resistivity takes on a tendency of initially decrease, and then increase with the increasing of contamination concentration and water content. For a soil sample with the same resistivity, the higher the amplitude of complex resistivity, the lower the water content and the higher the contamination concentration. The real and imaginary parts of the complex dielectric constant increase with an increase in contamination concentration and water content. Note that resistivity and complex resistivity methods are necessary to adequately evaluate pollution at various sites.

Estimating soil matric potential in Owens Valley, California

USGS Publications Warehouse

Sorenson, Stephen K.; Miller, R.F.; Welch, M.R.; Groeneveld, D.P.; Branson, F.A.

1988-01-01

Much of the floor of the Owens Valley, California, is covered with alkaline scrub and alkaline meadow plant communities, whose existence is dependent partly on precipitation and partly on water infiltrated into the rooting zone from the shallow water table. The extent to which these plant communities are capable of adapting to and surviving fluctuations in the water table depends on physiological adaptations of the plants and on the water content, matric potential characteristics of the soils. Two methods were used to estimate soil matric potential in test sites in Owens Valley. The first was the filter-paper method, which uses water content of filter papers equilibrated to water content of soil samples taken with a hand auger. The other method of estimating soil matric potential was a modeling approach based on data from this and previous investigations. These data indicate that the base 10 logarithm of soil matric potential is a linear function of gravimetric soil water content for a particular soil. Estimates of soil water characteristic curves were made at two sites by averaging the gravimetric soil water content and soil matric potential values from multiple samples at 0.1 m depths derived by using the hand auger and filter paper method and entering these values in the soil water model. The characteristic curves then were used to estimate soil matric potential from estimates of volumetric soil water content derived from neutron-probe readings. Evaluation of the modeling technique at two study sites indicated that estimates of soil matric potential within 0.5 pF units of the soil matric potential value derived by using the filter paper method could be obtained 90 to 95% of the time in soils where water content was less than field capacity. The greatest errors occurred at depths where there was a distinct transition between soils of different textures. (Lantz-PTT)

The seed bank longevity index revisited: limited reliability evident from a burial experiment and database analyses.

PubMed

Saatkamp, Arne; Affre, Laurence; Dutoit, Thierry; Poschlod, Peter

2009-09-01

Seed survival in the soil contributes to population persistence and community diversity, creating a need for reliable measures of soil seed bank persistence. Several methods estimate soil seed bank persistence, most of which count seedlings emerging from soil samples. Seasonality, depth distribution and presence (or absence) in vegetation are then used to classify a species' soil seed bank into persistent or transient, often synthesized into a longevity index. This study aims to determine if counts of seedlings from soil samples yield reliable seed bank persistence estimates and if this is correlated to seed production. Seeds of 38 annual weeds taken from arable fields were buried in the field and their viability tested by germination and tetrazolium tests at 6 month intervals for 2.5 years. This direct measure of soil seed survival was compared with indirect estimates from the literature, which use seedling emergence from soil samples to determine seed bank persistence. Published databases were used to explore the generality of the influence of reproductive capacity on seed bank persistence estimates from seedling emergence data. There was no relationship between a species' soil seed survival in the burial experiment and its seed bank persistence estimate from published data using seedling emergence from soil samples. The analysis of complementary data from published databases revealed that while seed bank persistence estimates based on seedling emergence from soil samples are generally correlated with seed production, estimates of seed banks from burial experiments are not. The results can be explained in terms of the seed size-seed number trade-off, which suggests that the higher number of smaller seeds is compensated after germination. Soil seed bank persistence estimates correlated to seed production are therefore not useful for studies on population persistence or community diversity. Confusion of soil seed survival and seed production can be avoided by separate use of soil seed abundance and experimental soil seed survival.

Use of physically-based models and Soil Taxonomy to identify soil moisture classes: Problems and proposals

NASA Astrophysics Data System (ADS)

Bonfante, A.; Basile, A.; de Mascellis, R.; Manna, P.; Terribile, F.

2009-04-01

Soil classification according to Soil Taxonomy include, as fundamental feature, the estimation of soil moisture regime. The term soil moisture regime refers to the "presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year". In the classification procedure, defining of the soil moisture control section is the primary step in order to obtain the soil moisture regimes classification. Currently, the estimation of soil moisture regimes is carried out through simple calculation schemes, such as Newhall and Billaux models, and only in few cases some authors suggest the use of different more complex models (i.e., EPIC) In fact, in the Soil Taxonomy, the definition of the soil moisture control section is based on the wetting front position in two different conditions: the upper boundary is the depth to which a dry soil will be moistened by 2.5 cm of water within 24 hours and the lower boundary is the depth to which a dry soil will be moistened by 7.5 cm of water within 48 hours. Newhall, Billaux and EPIC models don't use physical laws to describe soil water flows, but they use a simple bucket-like scheme where the soil is divided into several compartments and water moves, instantly, only downward when the field capacity is achieved. On the other side, a large number of one-dimensional hydrological simulation models (SWAP, Cropsyst, Hydrus, MACRO, etc..) are available, tested and successfully used. The flow is simulated according to pressure head gradients through the numerical solution of the Richard's equation. These simulation models can be fruitful used to improve the study of soil moisture regimes. The aims of this work are: (i) analysis of the soil moisture control section concept by a physically based model (SWAP); (ii) comparison of the classification obtained in five different Italian pedoclimatic conditions (Mantova and Lodi in northern Italy; Salerno, Benevento and Caserta in southern Italy) applying the classical models (Newhall e Billaux) and the physically-based models (CropSyst e SWAP), The results have shown that the Soil Taxonomy scheme for the definition of the soil moisture regime is unrealistic for the considered Mediterranean soil hydrological conditions. In fact, the same classifications arise irrespective of the soil type. In this respect some suggestions on how modified the section control boundaries were formulated. Keywords: Soil moisture regimes, Newhall, Swap, Soil Taxonomy

Effect of land use change on the carbon cycle in Amazon soils

NASA Technical Reports Server (NTRS)

Trumbore, Susan E.; Davidson, Eric A.

1994-01-01

The overall goal of this study was to provide a quantitative understanding of the cycling of carbon in the soils associated with deep-rooting Amazon forests. In particular, we wished to apply the understanding gained by answering two questions: (1) what changes will accompany the major land use change in this region, the conversion of forest to pasture? and (2) what is the role of carbon stored deeper than one meter in depth in these soils? To construct carbon budgets for pasture and forest soils we combined the following: measurements of carbon stocks in above-ground vegetation, root biomass, detritus, and soil organic matter; rates of carbon inputs to soil and detrital layers using litterfall collection and sequential coring to estimate fine root turnover; C-14 analyses of fractionated SOM and soil CO2 to estimate residence times; C-13 analyses to estimate C inputs to pasture soils from C-4 grasses; soil pCO2, volumetric water content, and radon gradients to estimate CO2 production as a function of soil depth; soil respiration to estimate total C outputs; and a model of soil C dynamics that defines SOM fractions cycling on annual, decadal, and millennial time scales.

High resolution digital soil mapping as a future instrument for developing sustainable landuse strategies

NASA Astrophysics Data System (ADS)

Gries, Philipp; Funke, Lisa-Marie; Baumann, Frank; Schmidt, Karsten; Behrens, Thorsten; Scholten, Thomas

2016-04-01

Climate change, increase in population and intensification of land use pose a great challenge for sustainable handling of soils. Intelligent landuse systems are able to minimize and/or avoid soil erosion and loss of soil fertility. A successful application of such systems requires area-wide soil information with high resolution. Containing three consecutive steps, the project INE-2-H („innovative sustainable landuse") at the University of Tuebingen is about creating high-resolution soil information using Digital Soil Mapping (DSM) techniques to develop sustainable landuse strategies. Input data includes soil data from fieldwork (texture and carbon content), the official digital soil and geological map (1:50.000) as well as a wide selection of local, complex and combined terrain parameters. First, soil maps have been created using the DSM approach and Random Forest (RF). Due to high resolution (10x10 m pixels), those maps show a more detailed spatial variability of soil information compared to the official maps used. Root mean square errors (RMSE) of the modelled maps vary from 2.11 % to 6.87 % and the coefficients of determination (R²) go from 0.42 to 0.68. Second, soil erosion potentials have been estimated according to the Universal Soil Loss Equation (USLE). Long-term average annual soil loss ranges from 0.56 to 24.23 [t/ha/a]. Third, combining high-resolution erosion potentials with expert-knowledge of local farmers will result in a landuse system adapted to local conditions. This system will include sustainable strategies reducing soil erosion and conserving soil fertility.

Progress Towards Identifying and Quantifying the Organic Ice Nucleating Particles in Soils and Aerosols

NASA Astrophysics Data System (ADS)

Hill, T. C. J.; DeMott, P. J.; Fröhlich-Nowoisky, J.; Tobo, Y.; Suski, K. J.; Levin, E. J.; Kreidenweis, S. M.; Franc, G. D.

2014-12-01

Soil and plant surfaces emit ice nucleating particles (INP) to the atmosphere, especially when disturbed by wind, harvesting, rain or fire. Organic (biogenic) INP are abundant in most soils and dominate the population that nucleate >-15°C. For example, the sandy topsoil of sagebrush shrubland, a widespread ecotype prone to wind erosion after fire, contains ~106 organic INP g-1 at -6°C. The relevance of organic INP may also extend to colder temperatures than previously thought: Particles of soil organic matter (SOM) have been shown to be more important than mineral particles for the ice nucleating ability of agricultural soil dusts to -34°C. While the abundance of ice nucleation active (INA) bacteria on plants has been established, the identity of the organic INP in and emitted by soils remains a 40-year-old mystery. The need to understand their production and release is highlighted by recent findings that INA bacteria (measured with qPCR) account for few, if any, of the warm-temperature organic INP that predominate in boundary layer aerosols and snow; organic INP lofted with soil dusts seem a likely source. The complexity of SOM hinders its investigation. It contains decomposing plant materials, a diverse microbial and microfaunal community, humus, and inert organic matter. All are biochemically complex and all may contain ice nucleating constituents, either by design or by chance. Indeed the smoothness of the INP temperature spectra of soils is indicative of numerous, overlapping distributions of INP. We report recent progress in identifying and quantifying the organic INP in soils and boundary layer aerosols representative of West Central U.S. ecosystems, and how their characteristics may affect their dispersal. Chemical, enzymatic and DNA-based tests were used to assess contributions of INP from plant tissues, INA bacteria, INA fungi, organic crystals, monolayers of aliphatic alcohols, carbohydrates, and humic substances, while heat- and peroxide-based tests were used to estimate total organic INP abundance.

Projecting the release of carbon from permafrost soils using a perturbed parameter ensemble modelling approach

NASA Astrophysics Data System (ADS)

MacDougall, Andrew H.; Knutti, Reto

2016-04-01

The soils of the northern hemispheric permafrost region are estimated to contain 1100 to 1500 Pg of carbon. A substantial fraction of this carbon has been frozen and therefore protected from microbial decay for millennia. As anthropogenic climate warming progresses much of this permafrost is expected to thaw. Here we conduct perturbed model experiments on a climate model of intermediate complexity, with an improved permafrost carbon module, to estimate with formal uncertainty bounds the release of carbon from permafrost soils by the year 2100 and 2300 CE. We estimate that by year 2100 the permafrost region may release between 56 (13 to 118) Pg C under Representative Concentration Pathway (RCP) 2.6 and 102 (27 to 199) Pg C under RCP 8.5, with substantially more to be released under each scenario by the year 2300. Our analysis suggests that the two parameters that contribute most to the uncertainty in the release of carbon from permafrost soils are the size of the non-passive fraction of the permafrost carbon pool and the equilibrium climate sensitivity. A subset of 25 model variants are integrated 8000 years into the future under continued RCP forcing. Under the moderate RCP 4.5 forcing a remnant near-surface permafrost region persists in the high Arctic, eventually developing a new permafrost carbon pool. Overall our simulations suggest that the permafrost carbon cycle feedback to climate change will make a significant contribution to climate change over the next centuries and millennia, releasing a quantity of carbon 3 to 54 % of the cumulative anthropogenic total.

Complex of solonetzes and vertic chestnut soils in the manych-gudilo depression

NASA Astrophysics Data System (ADS)

Kovda, I. V.; Morgun, E. P.; Il'ina, L. P.

2013-01-01

Morphological, physicochemical, and isotopic properties of a two-member soil complex developed under dry steppe have been studied in the central part of the Manych Depression. The soils are formed on chocolate-colored clayey sediments, and have pronounced microrelief and the complex vegetation pattern. A specific feature of the studied soil complex is the inverse position of its components: vertic chestnut soil occupies the microhigh, while solonetz is in the microlow. The formation of such complexes is explained by the biological factor, i.e., by the destruction of the solonetzic horizon under the impact of vegetation and earth-burrowing animals with further transformation under steppe plants and dealkalinization of the soil in the microhighs. The manifestation of vertic features and shrink-swell process in soils of the complex developing in dry steppe are compared with those in the vertic soils of the Central Pre-Caucasus formed under more humid environment. It is supposed that slickensides in the investigated vertic chestnut soil are relict feature inherited from the former wetter stage of the soil development and are subjected to a gradual degradation at present. In the modern period, vertic processes are weak and cannot be distinctly diagnosed. However, their activation may take place upon an increase of precipitation or the rise in the groundwater level.

Assessment of agronomic homogeneity and compatibility of soils in the Vladimir Opolie region

NASA Astrophysics Data System (ADS)

Shein, E. V.; Kiryushin, V. I.; Korchagin, A. A.; Mazirov, M. A.; Dembovetskii, A. V.; Il'in, L. I.

2017-10-01

Complexes of gray forest soils of different podzolization degrees with the participation of gray forest podzolized soils with the second humus horizon play a noticeable role in the soil cover patterns of Vladimir Opolie. The agronomic homogeneity and agronomic compatibility of gray forest soils in automorphic positions ("plakor" sites) were assessed on the test field of the Vladimir Agricultural Research Institute. The term "soil homogeneity" implies in our study the closeness of crop yield estimates (scores) for the soil polygons; the term "soil compatibility" implies the possibility to apply the same technologies in the same dates for different soil polygons within a field. To assess the agronomic homogeneity and compatibility of soils, the statistical analysis of the yields of test crop (oats) was performed, and the spatial distribution of the particular parameters of soil hydrothermic regime was studied. The analysis of crop yields showed their high variability: the gray forest soils on microhighs showed the minimal potential fertility, and the maximal fertility was typical of the soils with the second humus horizon in microlows. Soils also differed significantly in their hydrothermic regime, as the gray forest soils with the second humus horizon were heated and cooled slower than the background gray forest soils; their temperature had a stronger lag effect and displayed a narrower amplitude in seasonal fluctuations; and these soils were wetter during the first weeks (40 days) of the growing season. Being colder and wetter, the soils with the second humus horizons reached their physical ripeness later than the gray forest soils. Thus, the soil cover of the test plot in the automorphic position is heterogeneous; from the agronomic standpoint, its components are incompatible.

Enhancing soil moisture monitoring via cosmic-ray neutron sensing in farmlands by combining field site tests with an uncertainty analysis

NASA Astrophysics Data System (ADS)

Oswald, S. E.; Scheiffele, L. M.; Baroni, G.; Ingwersen, J.; Schrön, M.

2017-12-01

One application of Cosmic-Ray Neutron Sensing (CRNS) is to investigate soil moisture on agricultural fields during the crop season. This fully employs the non-invasive character of CRNS without interference with agricultural practices of the farmland. The changing influence of vegetation on CRNS has to be dealt with as well as spatio-temporal influences, e.g. by irrigation or harvest. Previous work revealed that the CRNS signal on farmland shows complex and non-unique response because of the hydrogen pools in different depths and distances. This creates a challenge for soil moisture estimation and subsequent use for irrigation management or hydrological modelling. Thus, a special aim of our study was to assess the uncertainty of CRNS in cropped fields and to identify underlying causes of uncertainty. We have applied CRNS at two field sites during the growing season that were accompanied by intensive measurements of soil moisture, vegetation parameters, and irrigation events. Sources of uncertainty were identified from the experimental data. A Monte Carlo approach was used to propagate these uncertainties to CRNS soil moisture estimations. In addition, a sensitivity analysis was performed to identify the most important factors explaining this uncertainty. Results showed that CRNS soil moisture compares well to the soil moisture network when the point values were converted to weighted water content with all hydrogen pools included. However, when considered as a stand-alone method to retrieve volumetric soil moisture, the performance decreased. The support volume including its penetration depth showed also a considerable uncertainty, especially in relatively dry soil moisture conditions. Of seven factors analyzed, actual soil moisture profile, bulk density, incoming neutron correction and calibrated parameter N0 were found to play an important role. One possible improvement could be a simple correction factor based on independent data of soil moisture profiles to better account for the sensitivity of the CRNS signal to the upper soil layers. This is an important step to improve the method for validation of remote sensing products or agricultural water management and establish CRNS as an applied monitoring tool on farmland.

Estimation of soil saturated hydraulic conductivity by artificial neural networks ensemble in smectitic soils

NASA Astrophysics Data System (ADS)

Sedaghat, A.; Bayat, H.; Safari Sinegani, A. A.

2016-03-01

The saturated hydraulic conductivity ( K s ) of the soil is one of the main soil physical properties. Indirect estimation of this parameter using pedo-transfer functions (PTFs) has received considerable attention. The Purpose of this study was to improve the estimation of K s using fractal parameters of particle and micro-aggregate size distributions in smectitic soils. In this study 260 disturbed and undisturbed soil samples were collected from Guilan province, the north of Iran. The fractal model of Bird and Perrier was used to compute the fractal parameters of particle and micro-aggregate size distributions. The PTFs were developed by artificial neural networks (ANNs) ensemble to estimate K s by using available soil data and fractal parameters. There were found significant correlations between K s and fractal parameters of particles and microaggregates. Estimation of K s was improved significantly by using fractal parameters of soil micro-aggregates as predictors. But using geometric mean and geometric standard deviation of particles diameter did not improve K s estimations significantly. Using fractal parameters of particles and micro-aggregates simultaneously, had the most effect in the estimation of K s . Generally, fractal parameters can be successfully used as input parameters to improve the estimation of K s in the PTFs in smectitic soils. As a result, ANNs ensemble successfully correlated the fractal parameters of particles and micro-aggregates to K s .

Estimating phosphorus availability for microbial growth in an emerging landscape

USGS Publications Warehouse

Schmidt, S.K.; Cleveland, C.C.; Nemergut, D.R.; Reed, S.C.; King, A.J.; Sowell, P.

2011-01-01

Estimating phosphorus (P) availability is difficult—particularly in infertile soils such as those exposed after glacial recession—because standard P extraction methods may not mimic biological acquisition pathways. We developed an approach, based on microbial CO2 production kinetics and conserved carbon:phosphorus (C:P) ratios, to estimate the amount of P available for microbial growth in soils and compared this method to traditional, operationally-defined indicators of P availability. Along a primary succession gradient in the High Andes of Perú, P additions stimulated the growth-related (logistic) kinetics of glutamate mineralization in soils that had been deglaciated from 0 to 5 years suggesting that microbial growth was limited by soil P availability. We then used a logistic model to estimate the amount of C incorporated into biomass in P-limited soils, allowing us to estimate total microbial P uptake based on a conservative C:P ratio of 28:1 (mass:mass). Using this approach, we estimated that there was < 1 μg/g of microbial-available P in recently de-glaciated soils in both years of this study. These estimates fell well below estimates of available soil P obtained using traditional extraction procedures. Our results give both theoretical and practical insights into the kinetics of C and P utilization in young soils, as well as show changes in microbial P availability during early stages of soil development.

Remote sensing-based estimation of annual soil respiration at two contrasting forest sites

NASA Astrophysics Data System (ADS)

Huang, Ni; Gu, Lianhong; Black, T. Andrew; Wang, Li; Niu, Zheng

2015-11-01

Soil respiration (Rs), an important component of the global carbon cycle, can be estimated using remotely sensed data, but the accuracy of this technique has not been thoroughly investigated. In this study, we proposed a methodology for the remote estimation of annual Rs at two contrasting FLUXNET forest sites (a deciduous broadleaf forest and an evergreen needleleaf forest). A version of the Akaike's information criterion was used to select the best model from a range of models for annual Rs estimation based on the remotely sensed data products from the Moderate Resolution Imaging Spectroradiometer and root-zone soil moisture product derived from assimilation of the NASA Advanced Microwave Scanning Radiometer soil moisture products and a two-layer Palmer water balance model. We found that the Arrhenius-type function based on nighttime land surface temperature (LST-night) was the best model by comprehensively considering the model explanatory power and model complexity at the Missouri Ozark and BC-Campbell River 1949 Douglas-fir sites. In addition, a multicollinearity problem among LST-night, root-zone soil moisture, and plant photosynthesis factor was effectively avoided by selecting the LST-night-driven model. Cross validation showed that temporal variation in Rs was captured by the LST-night-driven model with a mean absolute error below 1 µmol CO2 m-2 s-1 at both forest sites. An obvious overestimation that occurred in 2005 and 2007 at the Missouri Ozark site reduced the evaluation accuracy of cross validation because of summer drought. However, no significant difference was found between the Arrhenius-type function driven by LST-night and the function considering LST-night and root-zone soil moisture. This finding indicated that the contribution of soil moisture to Rs was relatively small at our multiyear data set. To predict intersite Rs, maximum leaf area index (LAImax) was used as an upscaling factor to calibrate the site-specific reference respiration rates. Independent validation demonstrated that the model incorporating LST-night and LAImax efficiently predicted the spatial and temporal variabilities of Rs. Based on the Arrhenius-type function using LST-night as an input parameter, the rates of annual C release from Rs were 894-1027 g C m-2 yr-1 at the BC-Campbell River 1949 Douglas-fir site and 818-943 g C m-2 yr-1 at the Missouri Ozark site. The ratio between annual Rs estimates based on remotely sensed data and the total annual ecosystem respiration from eddy covariance measurements fell within the range reported in previous studies. Our results demonstrated that estimating annual Rs based on remote sensing data products was possible at deciduous and evergreen forest sites.

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.

Parameterization models for pesticide exposure via crop consumption.

PubMed

Fantke, Peter; Wieland, Peter; Juraske, Ronnie; Shaddick, Gavin; Itoiz, Eva Sevigné; Friedrich, Rainer; Jolliet, Olivier

2012-12-04

An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces, overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role for fruit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the framework's physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption. All parametric models can be easily implemented into existing assessment frameworks.

Assessing quality of citizen scientists’ soil texture estimates to evaluate land potential

USDA-ARS?s Scientific Manuscript database

Texture influences nearly all soil processes and is often the most measured parameter in soil science. Estimating soil texture is a universal and fundamental practice applied by resource scientists to classify and understand the behavior and management of soil systems. While trained soil scientist c...

Global distribution of soil organic carbon, based on the Harmonized World Soil Database - Part 1: Masses and frequency distribution of SOC stocks for the tropics, permafrost regions, wetlands, and the world

NASA Astrophysics Data System (ADS)

Köchy, M.; Hiederer, R.; Freibauer, A.

2014-09-01

The global soil organic carbon (SOC) mass is relevant for the carbon cycle budget. We review current estimates of soil organic carbon stocks (mass/area) and mass (stock × area) in wetlands, permafrost and tropical regions and the world in the upper 1 m of soil. The Harmonized World Soil Database (HWSD) v.1.2 provides one of the most recent and coherent global data sets of SOC, giving a total mass of 2476 Pg. Correcting the HWSD's bulk density of organic soils, especially Histosols, results in a mass of 1062 Pg. The uncertainty of bulk density of Histosols alone introduces a range of -56 to +180 Pg for the estimate of global SOC in the top 1 m, larger than estimates of global soil respiration. We report the spatial distribution of SOC stocks per 0.5 arc minutes, the areal masses of SOC and the quantiles of SOC stocks by continents, wetland types, and permafrost types. Depending on the definition of "wetland", wetland soils contain between 82 and 158 Pg SOC. Incorporating more detailed estimates for permafrost from the Northern Circumpolar Soil Carbon Data Base (496 Pg SOC) and tropical peatland carbon, global soils contain 1324 Pg SOC in the upper 1 m including 421 Pg in tropical soils, whereof 40 Pg occur in tropical wetlands. Global SOC amounts to just under 3000 Pg when estimates for deeper soil layers are included. Variability in estimates is due to variation in definitions of soil units, differences in soil property databases, scarcity of information about soil carbon at depths > 1 m in peatlands, and variation in definitions of "peatland".

A time-series approach to estimating soil moisture from vegetated surfaces using L-band radar backscatter

USDA-ARS?s Scientific Manuscript database

Many previous studies have shown the sensitivity of radar backscatter to surface soil moisture content, particularly at L-band. Moreover, the estimation of soil moisture from radar for bare soil surfaces is well-documented, but estimation underneath a vegetation canopy remains unsolved. Vegetation s...

Reassessment of soil erosion on the Chinese loess plateau: were rates overestimated?

NASA Astrophysics Data System (ADS)

Zhao, Jianlin; Govers, Gerard

2014-05-01

Several studies have estimated regional soil erosion rates (rill and interrill erosion) on the Chinese loess plateau using an erosion model such as the RUSLE (e.g. Fu et al., 2011; Sun et al., 2013). However, the question may be asked whether such estimates are realistic: studies have shown that the use of models for large areas may lead to significant overestimations (Quinton et al., 2010). In this study, soil erosion rates on the Chinese loess plateau were reevaluated by using field measured soil erosion data from erosion plots (216 plots and 1380 plot years) in combination with a careful extrapolation procedure. Data analysis showed that the relationship between slope and erosion rate on arable land could be well described by erosion-slope relationships reported in the literature (Nearing, 1997). The increase of average erosion rate with slope length was clearly degressive, as could be expected from earlier research. However, for plots with permanent vegetation (grassland, shrub, forest) no relationship was found between erosion rates and slope gradient and/or slope length. This is important, as it implies that spatial variations of erosion on permanently vegetated areas cannot be modeled using topographical functions derived from observations on arable land. Application of relationships developed for arable land will lead to a significant overestimation of soil erosion rates. Based on our analysis we estimate the total soil erosion rate in the Chinese Loess plateau averages ca. 6.78 t ha-1 yr-1 for the whole loess plateau, resulting in a total sediment mobilisation of ca. 0.38 Gt yr-1. Erosion rates on arable land average ca. 15.10 t ha-1 yr-1. These estimates are 2 to 3 times lower than previously published estimates. The main reason why previous estimates are likely to be too high is that the values of (R)USLE parameters such as K, P and LS factor were overestimated. Overestimations of the K factor are due to the reliance of nomograph calculations, resulting in significantly higher erodibility values than those obtained from field data. Overestimations of the P and LS factors are mainly due to the fact that erosion control measures such as terracing are not accounted for and that erroneous scaling functions are used on permanently vegetated areas. Our findings have not only important implications with respect to the mobilization of sediments by agricultural erosion: we will also need to reassess the impact of erosion on biogeochemicaly cycling and crop productivity. Fu, B., Liu, Y., Lü, Y., He, C., Zeng, Y., & Wu, B. (2011). Assessing the soil erosion control service of ecosystems change in the Loess Plateau of China. Ecological Complexity, 8(4), 284-293. doi:10.1016/j.ecocom.2011.07.003 Nearing, M. A. (1997). A single, continuous function for slope steepness influence on soil loss. Soil Science Society of American Journal, 61(3), 917-919. Quinton, J. N., Govers, G., Van Oost, K., & Bardgett, R. D. (2010). The impact of agricultural soil erosion on biogeochemical cycling. Nature Geoscience, 3(5), 311-314. doi:10.1038/ngeo838 Sun, W., Shao, Q., & Liu, J. (2013). Soil erosion and its response to the changes of precipitation and vegetation cover on the Loess Plateau. Journal of Geographical Sciences, 23(6), 1091-1106. doi:10.1007/s11442-013-1065-z

Negative soil moisture-precipitation feedback in dry and wet regions.

PubMed

Yang, Lingbin; Sun, Guoqing; Zhi, Lu; Zhao, Jianjun

2018-03-05

Soil moisture-precipitation (SM-P) feedback significantly influences the terrestrial water and energy cycles. However, the sign of the feedback and the associated physical mechanism have been debated, leaving a research gap regarding global water and climate changes. Based on Koster's framework, we estimate SM-P feedback using satellite remote sensing and ground observation data sets. Methodologically, the sign of the feedback is identified by the correlation between monthly soil moisture and next-month precipitation. The physical mechanism is investigated through coupling precipitation and soil moisture (P-SM), soil moisture ad evapotranspiration (SM-E) and evapotranspiration and precipitation (E-P) correlations. Our results demonstrate that although positive SM-P feedback is predominant over land, non-negligible negative feedback occurs in dry and wet regions. Specifically, 43.75% and 40.16% of the negative feedback occurs in the arid and humid climate zones. Physically, negative SM-P feedback depends on the SM-E correlation. In dry regions, evapotranspiration change is soil moisture limited. In wet regions, evapotranspiration change is energy limited. We conclude that the complex SM-E correlation results in negative SM-P feedback in dry and wet regions, and the cause varies based on the environmental and climatic conditions.

Complexity in Soil Systems: What Does It Mean and How Should We Proceed?

NASA Astrophysics Data System (ADS)

Faybishenko, B.; Molz, F. J.; Brodie, E.; Hubbard, S. S.

2015-12-01

The complex soil systems approach is needed fundamentally for the development of integrated, interdisciplinary methods to measure and quantify the physical, chemical and biological processes taking place in soil, and to determine the role of fine-scale heterogeneities. This presentation is aimed at a review of the concepts and observations concerning complexity and complex systems theory, including terminology, emergent complexity and simplicity, self-organization and a general approach to the study of complex systems using the Weaver (1948) concept of "organized complexity." These concepts are used to provide understanding of complex soil systems, and to develop experimental and mathematical approaches to soil microbiological processes. The results of numerical simulations, observations and experiments are presented that indicate the presence of deterministic chaotic dynamics in soil microbial systems. So what are the implications for the scientists who wish to develop mathematical models in the area of organized complexity or to perform experiments to help clarify an aspect of an organized complex system? The modelers have to deal with coupled systems having at least three dependent variables, and they have to forgo making linear approximations to nonlinear phenomena. The analogous rule for experimentalists is that they need to perform experiments that involve measurement of at least three interacting entities (variables depending on time, space, and each other). These entities could be microbes in soil penetrated by roots. If a process being studied in a soil affects the soil properties, like biofilm formation, then this effect has to be measured and included. The mathematical implications of this viewpoint are examined, and results of numerical solutions to a system of equations demonstrating deterministic chaotic behavior are also discussed using time series and the 3D strange attractors.

Ultrasound Algorithm Derivation for Soil Moisture Content Estimation

NASA Technical Reports Server (NTRS)

Belisle, W.R.; Metzl, R.; Choi, J.; Aggarwal, M. D.; Coleman, T.

1997-01-01

Soil moisture content can be estimated by evaluating the velocity at which sound waves travel through a known volume of solid material. This research involved the development of three soil algorithms relating the moisture content to the velocity at which sound waves moved through dry and moist media. Pressure and shear wave propagation equations were used in conjunction with soil property descriptions to derive algorithms appropriate for describing the effects of moisture content variation on the velocity of sound waves in soils with and without complete soil pore water volumes, An elementary algorithm was used to estimate soil moisture contents ranging from 0.08 g/g to 0.5 g/g from sound wave velocities ranging from 526 m/s to 664 m/s. Secondary algorithms were also used to estimate soil moisture content from sound wave velocities through soils with pores that were filled predominantly with air or water.

Estimating Sources and Sinks of Methane from Soils in the Contiguous United States (CONUS)

NASA Astrophysics Data System (ADS)

Shu, S.; Jain, A. K.; Kheshgi, H. S.

2017-12-01

The global methane (CH4) budget estimated based on state-of-the-art models remains highly uncertain. Sources and sinks of CH4 from soils, including wetlands, are the most important source of uncertainty. Soils are estimated to account for about 45% of global CH4 emissions. At the same time oxidation of CH4 by soils is a significant sink, representing about 10% of the total sink. However, most regional and global scale modeling studies of soil CH4 fluxes have ignored the sink through soil oxidation and the source of CH4 emissions from the wet soils with shallow water tables. In this study, we link a bottom-up soil gas diffusion and CH4 biogeochemistry model to a land surface model, ISAM, to calculate the sources, emissions from both wetlands and non-wetlands, and sinks, soil oxidation, of CH4 from soils for the CONUS over the period 1900-2100. The newly developed soil CH4 model framework consists of a gas diffusion module with the vertically resolved soil hydrology (depth up to 3.5 m soil) and soil organic carbon (SOC) and CH4 biogeochemistry module. SOC profile is estimated by modeling vertical soil mixing and thus can represent the deep SOC content and estimate CH4 production from the deep non-wetland soil. For the diffusion calculations, we separately consider both the dissolved and gaseous O2 and CH4 at each soil layer. For CH4 biogeochemistry, we parameterize the production, soil oxidation, ebullition and aerenchyma transportation of CH4 for both seasonal/permanent wetland and wet soil. The SWAMP inundated fraction dataset with 8-day temporal resolution is incorporated to prescribe the extent of permanent and seasonal wetland extent for the recent decade. The model is first evaluated using a compilation of published CH4 site measurement data for CONUS. We then perform two different model experiments: 1) forced by the CRUNCEP climate data from 1900 to 2010 to estimate the contemporary CH4 emission and 2) forced by a climate projection of IPCC's highest representative concentration pathway (RCP8.5) from 2011 to 2100. Our study shows that soil oxidation has an important role attenuating the estimated natural CH4 source. We also find a wetter and warmer climate affects the dry soil CH4 sink and wet soil CH4 emissions and increases the estimated CH4 source over the CONUS.

Sorption of citalopram, irbesartan and fexofenadine in soils: Estimation of sorption coefficients from soil properties.

PubMed

Klement, Aleš; Kodešová, Radka; Bauerová, Martina; Golovko, Oksana; Kočárek, Martin; Fér, Miroslav; Koba, Olga; Nikodem, Antonín; Grabic, Roman

2018-03-01

The sorption of 3 pharmaceuticals, which may exist in 4 different forms depending on the solution pH (irbesartan in cationic, neutral and anionic, fexofenadine in cationic, zwitter-ionic and anionic, and citalopram cationic and neutral), in seven different soils was studied. The measured sorption isotherms were described by Freundlich equations, and the sorption coefficients, K F (for the fixed n exponent for each compound), were related to the soil properties to derive relationships for estimating the sorption coefficients from the soil properties (i.e., pedotransfer rules). The largest sorption was obtained for citalopram (average K F value for n = 1 was 1838 cm 3  g -1 ) followed by fexofenadine (K F  = 35.1 cm 3/n μg 1-1/n g -1 , n = 1.19) and irbesartan (K F  = 3.96 cm 3/n μg 1-1/n g -1 , n = 1.10). The behavior of citalopram (CIT) in soils was different than the behaviors of irbesartan (IRB) and fexofenadine (FEX). Different trends were documented according to the correlation coefficients between the K F values for different compounds (R IRB,FEX  = 0.895, p-value<0.01; R IRB,CIT  = -0.835, p-value<0.05; R FEX,CIT  = -0.759, p-value<0.05) and by the reverse relationships between the K F values and soil properties in the pedotransfer functions. While the K F value for citalopram was positively related to base cation saturation (BCS) or sorption complex saturation (SCS) and negatively correlated to the organic carbon content (Cox), the K F values of irbesartan and fexofenadine were negatively related to BCS, SCS or the clay content and positively related to Cox. The best estimates were obtained by combining BCS and Cox for citalopram (R 2  = 93.4), SCS and Cox for irbesartan (R 2  = 96.3), and clay content and Cox for fexofenadine (R 2  = 82.9). Copyright © 2017 Elsevier Ltd. All rights reserved.

Wood ash application increases pH but does not harm the soil mesofauna.

PubMed

Qin, Jiayi; Hovmand, Mads Frederik; Ekelund, Flemming; Rønn, Regin; Christensen, Søren; Groot, Gerard Arjen de; Mortensen, Louise Hindborg; Skov, Simon; Krogh, Paul Henning

2017-05-01

Application of bioash from biofuel combustion to soil supports nutrient recycling, but may have unwanted and detrimental ecotoxicological side-effects, as the ash is a complex mixture of compounds that could affect soil invertebrates directly or through changes in their food or habitat conditions. To examine this, we performed laboratory toxicity studies of the effects of wood-ash added to an agricultural soil and the organic horizon of a coniferous plantation soil with the detrivore soil collembolans Folsomia candida and Onychiurus yodai, the gamasid predaceous mite Hypoaspis aculeifer, and the enchytraeid worm Enchytraeus crypticus. We used ash concentrations spanning 0-75 g kg -1 soil. As ash increases pH we compared bioash effects with effects of calcium hydroxide, Ca(OH) 2 , the main liming component of ash. Only high ash concentrations above 15 g kg -1 agricultural soil or 17 t ha -1 had significant effects on the collembolans. The wood ash neither affected H. aculeifer nor E. crypticus. The estimated osmolalities of Ca(OH) 2 and the wood ash were similar at the LC 50 concentration level. We conclude that short-term chronic effects of wood ash differ among different soil types, and osmotic stress is the likely cause of effects while high pH and heavy metals is of minor importance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Carbon sequestration potential of coastal wetland soils of Veracruz, Mexico

NASA Astrophysics Data System (ADS)

Fuentes-Romero, Elisabeth; García-Calderón, Norma Eugenia; Ikkonen, Elena; García-Varela, Kl

2014-05-01

Tropical coastal wetlands, including rainforests and mangrove ecosystems play an increasingly important ecological and economic role in the tropical coastal area of the State of Veracruz /Mexico. However, soil processes in these environments, especially C-turnover rates are largely unknown until today. Therefore, we investigated CO2 and CH4 emissions together with gains and losses of organic C in the soils of two different coastal ecosystems in the "Natural Protected Area Cienaga del Fuerte (NPACF)" near Tecolutla, in the State of Veracruz. The research areas were an artificially introduced grassland (IG) and a wetland rainforest (WRF). The gas emissions from the soil surfaces were measured by a static chamber array, the soil organic C was analysed in soil profiles distributed in the two areas, humic substances were characterized and C budget was calculated. The soils in both areas acted as carbon sinks, but the soils of the WRF sequestered more C than those of the IG, which showed a higher gas emission rate and produced more dissolved organic carbon. The gas emission measurements during the dry and the rainy seasons allowed for estimating the possible influence of global warming on gas fluxes from the soils of the two different ecological systems, which show in the WRF a quite complex spatial emission pattern during the rainy season in contrast to a more continuous emission pattern in the IG plots

Using satellite image data to estimate soil moisture

NASA Astrophysics Data System (ADS)

Chuang, Chi-Hung; Yu, Hwa-Lung

2017-04-01

Soil moisture is considered as an important parameter in various study fields, such as hydrology, phenology, and agriculture. In hydrology, soil moisture is an significant parameter to decide how much rainfall that will infiltrate into permeable layer and become groundwater resource. Although soil moisture is a critical role in many environmental studies, so far the measurement of soil moisture is using ground instrument such as electromagnetic soil moisture sensor. Use of ground instrumentation can directly obtain the information, but the instrument needs maintenance and consume manpower to operation. If we need wide range region information, ground instrumentation probably is not suitable. To measure wide region soil moisture information, we need other method to achieve this purpose. Satellite remote sensing techniques can obtain satellite image on Earth, this can be a way to solve the spatial restriction on instrument measurement. In this study, we used MODIS data to retrieve daily soil moisture pattern estimation, i.e., crop water stress index (cwsi), over the year of 2015. The estimations are compared with the observations at the soil moisture stations from Taiwan Bureau of soil and water conservation. Results show that the satellite remote sensing data can be helpful to the soil moisture estimation. Further analysis can be required to obtain the optimal parameters for soil moisture estimation in Taiwan.

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

NASA Technical Reports Server (NTRS)

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

Two methods are described which are used to estimate soil moisture remotely using the 0.4- to 14.0 micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

NASA Technical Reports Server (NTRS)

Blanchard, M. B.; Greeley, R.; Goettelman, R.

1974-01-01

Two methods are used to estimate soil moisture remotely using the 0.4- to 14.0-micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

Tundra fire disturbance homogonizes belowground food web structure, function and dynamics

NASA Astrophysics Data System (ADS)

Moore, J. C.; Pressler, Y.; Koltz, A.; Asmus, A.; Simpson, R.

2016-12-01

Tundra fires on Alaska's North Slope are on the rise due to increased lightning strikes since 2000. On July 16, 2007 lightning ignited the Anaktuvuk River fire, burning a 40-by-10 mile swath of tundra about 24 miles north of Toolik Field Station. The fire burned 401 square miles, was visible from space, and released more than 2.3 million tons of carbon into the atmosphere. A large amount of the organic layer of the soil was burned, changing the over all composition of the site and exposing deeper soil horizons. Due to fundamental transitions in soil characteristics and vegetation we hypothesized that the belowground food web community would be affected both in terms of biomass and location within the soil profile. Microbial biomass was reduced with burn severity. In the lower organic horizon there was a significant reduction in fungal biomass but we did not observe this effect in the upper organic soil. We did not observe a significant effect of burn severity on individual group biomass within higher trophic levels. Canonical Discriminant Analysis using the biomass estimates of the functional groups in the food webs found that the webs are becoming increasingly homogenized in the severely burned site compared to the moderately burned and unburned sites. The unburned soils differed significantly from soil at both burn sites; the greatest effects on food web structure were at the lower organic depth, whereas. We modeled the effects of the fire on soil organic matter processing rates and energy flow through the three food webs. The model estimated a decrease in C and N mineralization with fire severity, due in large part to the loss of organic material. While the organic horizon at the unburned site had 12 times greater C and N mineralization than the mineral soils, we observed little to no difference in C and N mineralization between the organic and mineral soil horizons in the moderately and severely burned sites. Our results show that the fire significantly altered the trophic structure of the soil food web, with loss of trophic complexity with increasing fire severity, which correlated strongly with C and N processing and food web stability.

Adaptive data-driven models for estimating carbon fluxes in the Northern Great Plains

USGS Publications Warehouse

Wylie, B.K.; Fosnight, E.A.; Gilmanov, T.G.; Frank, A.B.; Morgan, J.A.; Haferkamp, Marshall R.; Meyers, T.P.

2007-01-01

Rangeland carbon fluxes are highly variable in both space and time. Given the expansive areas of rangelands, how rangelands respond to climatic variation, management, and soil potential is important to understanding carbon dynamics. Rangeland carbon fluxes associated with Net Ecosystem Exchange (NEE) were measured from multiple year data sets at five flux tower locations in the Northern Great Plains. These flux tower measurements were combined with 1-km2 spatial data sets of Photosynthetically Active Radiation (PAR), Normalized Difference Vegetation Index (NDVI), temperature, precipitation, seasonal NDVI metrics, and soil characteristics. Flux tower measurements were used to train and select variables for a rule-based piece-wise regression model. The accuracy and stability of the model were assessed through random cross-validation and cross-validation by site and year. Estimates of NEE were produced for each 10-day period during each growing season from 1998 to 2001. Growing season carbon flux estimates were combined with winter flux estimates to derive and map annual estimates of NEE. The rule-based piece-wise regression model is a dynamic, adaptive model that captures the relationships of the spatial data to NEE as conditions evolve throughout the growing season. The carbon dynamics in the Northern Great Plains proved to be in near equilibrium, serving as a small carbon sink in 1999 and as a small carbon source in 1998, 2000, and 2001. Patterns of carbon sinks and sources are very complex, with the carbon dynamics tilting toward sources in the drier west and toward sinks in the east and near the mountains in the extreme west. Significant local variability exists, which initial investigations suggest are likely related to local climate variability, soil properties, and management.

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-09-01

The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

Stochastic error model corrections to improve the performance of bottom-up precipitation products for hydrologic applications

NASA Astrophysics Data System (ADS)

Maggioni, V.; Massari, C.; Ciabatta, L.; Brocca, L.

2016-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning, and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. However, uncertainties in the SM2RAIN product are still not well known and could represent a limitation in utilizing this dataset for hydrological applications. Therefore, quantifying the uncertainty associated with SM2RAIN is necessary for enabling its use. The study is conducted over the Italian territory for a 5-yr period (2010-2014). A number of satellite precipitation error properties, typically used in error modeling, are investigated and include probability of detection, false alarm rates, missed events, spatial correlation of the error, and hit biases. After this preliminary uncertainty analysis, the potential of applying the stochastic rainfall error model SREM2D to correct SM2RAIN and to improve its performance in hydrologic applications is investigated. The use of SREM2D for characterizing the error in precipitation by SM2RAIN would be highly useful for the merging and the integration steps in its algorithm, i.e., the merging of multiple soil moisture derived products (e.g., SMAP, SMOS, ASCAT) and the integration of soil moisture derived and state of the art satellite precipitation products (e.g., GPM IMERG).

Estimating Soil Cation Exchange Capacity from Soil Physical and Chemical Properties

NASA Astrophysics Data System (ADS)

Bateni, S. M.; Emamgholizadeh, S.; Shahsavani, D.

2014-12-01

The soil Cation Exchange Capacity (CEC) is an important soil characteristic that has many applications in soil science and environmental studies. For example, CEC influences soil fertility by controlling the exchange of ions in the soil. Measurement of CEC is costly and difficult. Consequently, several studies attempted to obtain CEC from readily measurable soil physical and chemical properties such as soil pH, organic matter, soil texture, bulk density, and particle size distribution. These studies have often used multiple regression or artificial neural network models. Regression-based models cannot capture the intricate relationship between CEC and soil physical and chemical attributes and provide inaccurate CEC estimates. Although neural network models perform better than regression methods, they act like a black-box and cannot generate an explicit expression for retrieval of CEC from soil properties. In a departure with regression and neural network models, this study uses Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) to estimate CEC from easily measurable soil variables such as clay, pH, and OM. CEC estimates from GEP and MARS are compared with measurements at two field sites in Iran. Results show that GEP and MARS can estimate CEC accurately. Also, the MARS model performs slightly better than GEP. Finally, a sensitivity test indicates that organic matter and pH have respectively the least and the most significant impact on CEC.

Cost-effective sampling of ¹³⁷Cs-derived net soil redistribution: part 1--estimating the spatial mean across scales of variation.

PubMed

Li, Y; Chappell, A; Nyamdavaa, B; Yu, H; Davaasuren, D; Zoljargal, K

2015-03-01

The (137)Cs technique for estimating net time-integrated soil redistribution is valuable for understanding the factors controlling soil redistribution by all processes. The literature on this technique is dominated by studies of individual fields and describes its typically time-consuming nature. We contend that the community making these studies has inappropriately assumed that many (137)Cs measurements are required and hence estimates of net soil redistribution can only be made at the field scale. Here, we support future studies of (137)Cs-derived net soil redistribution to apply their often limited resources across scales of variation (field, catchment, region etc.) without compromising the quality of the estimates at any scale. We describe a hybrid, design-based and model-based, stratified random sampling design with composites to estimate the sampling variance and a cost model for fieldwork and laboratory measurements. Geostatistical mapping of net (1954-2012) soil redistribution as a case study on the Chinese Loess Plateau is compared with estimates for several other sampling designs popular in the literature. We demonstrate the cost-effectiveness of the hybrid design for spatial estimation of net soil redistribution. To demonstrate the limitations of current sampling approaches to cut across scales of variation, we extrapolate our estimate of net soil redistribution across the region, show that for the same resources, estimates from many fields could have been provided and would elucidate the cause of differences within and between regional estimates. We recommend that future studies evaluate carefully the sampling design to consider the opportunity to investigate (137)Cs-derived net soil redistribution across scales of variation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

NASA Technical Reports Server (NTRS)

Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

2014-01-01

Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data.

PubMed

Adachi, Minaco; Ito, Akihiko; Yonemura, Seiichiro; Takeuchi, Wataru

2017-09-15

Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr -1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q 10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q 10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or <1.0) because of the low seasonal variation in soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimates of amounts of soil removal for clean-up of transuranics at NAEG offsite safety-shot sites

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

Kinnison, R.R.; Gilbert, R.O.

Rough estimates are given for the amount of soil removal necessary to decontaminate five representative safety-shot areas. In order to decontaminate to levels of less than 160 pCi /sup 239/Pu per gram of surface soil, it is estimated that over one-half million tons of soil would have to be removed from the five areas. This is a preliminary estimate based on summary data and concentration contour maps readily available in NAEG publications. More accurate estimates could be obtained by applying Kriging techniques to available soil data if the need arises. The inclusion of /sup 241/Am and /sup 238/Pu activities domore » not significantly increase the soil tonnage estimates obtained for /sup 239/ /sup 240/Pu because of their relatively small contributions to total transuranic activity. The magnitude of the errors inherent in our use of summary data to obtain rough estimates also suggests that a revision of the tonnage estimates for /sup 239/ /sup 240/Pu to include /sup 241/Am and /sup 238/Pu is not warranted.« less

Application of IEM model on soil moisture and surface roughness estimation

NASA Technical Reports Server (NTRS)

Shi, Jiancheng; Wang, J. R.; Oneill, P. E.; Hsu, A. Y.; Engman, E. T.

1995-01-01

Monitoring spatial and temporal changes of soil moisture are of importance to hydrology, meteorology, and agriculture. This paper reports a result on study of using L-band SAR imagery to estimate soil moisture and surface roughness for bare fields. Due to limitations of the Small Perturbation Model, it is difficult to apply this model on estimation of soil moisture and surface roughness directly. In this study, we show a simplified model derived from the Integral Equation Model for estimation of soil moisture and surface roughness. We show a test of this model using JPL L-band AIRSAR data.

Estimation of soil organic partition coefficients: from retention factors measured by soil column chromatography with water as eluent.

PubMed

Xu, Feng; Liang, Xinmiao; Lin, Bingcheng; Schramm, Karl-Werner; Kettrup, Antonius

2002-08-30

The retention factors (k) of 104 hydrophobic organic chemicals (HOCs) were measured in soil column chromatography (SCC) over columns filled with three naturally occurring reference soils and eluted with Milli-Q water. A novel method for the estimation of soil organic partition coefficient (Koc) was developed based on correlations with k in soil/water systems. Strong log Koc versus log k correlations (r>0.96) were found. The estimated Koc values were in accordance with the literature values with a maximum deviation of less than 0.4 log units. All estimated Koc values from three soils were consistent with each other. The SCC approach is promising for fast screening of a large number of chemicals in their environmental applications.

Subsurface cadmium loss from a stony soil-effect of cow urine application.

PubMed

Gray, Colin William; Chrystal, Jane Marie; Monaghan, Ross Martin; Cavanagh, Jo-Anne

2017-05-01

Cadmium (Cd) losses in subsurface flow from stony soils that have received cow urine are potentially important, but poorly understood. This study investigated Cd loss from a soil under a winter dairy-grazed forage crop that was grazed either conventionally (24 h) or with restricted grazing (6 h). This provided an opportunity to test the hypothesis that urine inputs could increase Cd concentrations in drainage. It was thought this would be a result of cow urine either (i) enhancing dissolved organic carbon (DOC) concentrations via an increase in soil pH, resulting in the formation of soluble Cd-organic carbon complexes and, or (ii) greater inputs of chloride (Cl) via cow urine, promoting the formation of soluble Cd-Cl complexes. Cadmium concentrations in subsurface flow were generally low, with a spike above the water quality guidelines for a month after the 24-h grazing. Cadmium fluxes were on average 0.30 g Cd ha -1  year -1 (0.27-0.32 g Cd ha -1  year -1 ), in line with previous estimates for agricultural soils. The mean Cd concentration in drainage from the 24-h grazed plots was significantly higher (P < 0.05) than 6-h plots. No increase in DOC concentrations between the treatments was found. However, Cl concentrations in drainage were significantly higher (P < 0.001) from the 24-h than the 6-h grazed treatment plots, and positively correlated with Cd concentrations, and therefore, a possible mechanism increasing Cd mobility in soil. Further study is warranted to confirm the mechanisms involved and quantities of Cd lost from other systems.

Productivity of aboveground coarse wood biomass and stand age related to soil hydrology of Amazonian forests in the Purus-Madeira interfluvial area

NASA Astrophysics Data System (ADS)

Cintra, B. B. L.; Schietti, J.; Emillio, T.; Martins, D.; Moulatlet, G.; Souza, P.; Levis, C.; Quesada, C. A.; Schöngart, J.

2013-04-01

The ongoing demand for information on forest productivity has increased the number of permanent monitoring plots across the Amazon. Those plots, however, do not comprise the whole diversity of forest types in the Amazon. The complex effects of soil, climate and hydrology on the productivity of seasonally waterlogged interfluvial wetland forests are still poorly understood. The presented study is the first field-based estimate for tree ages and wood biomass productivity in the vast interfluvial region between the Purus and Madeira rivers. We estimate stand age and wood biomass productivity by a combination of tree-ring data and allometric equations for biomass stocks of eight plots distributed along 600 km in the Purus-Madeira interfluvial area that is crossed by the BR-319 highway. We relate stand age and wood biomass productivity to hydrological and edaphic conditions. Mean productivity and stand age were 5.6 ± 1.1 Mg ha-1 yr-1 and 102 ± 18 yr, respectively. There is a strong relationship between tree age and diameter, as well as between mean diameter increment and mean wood density within a plot. Regarding the soil hydromorphic properties we find a positive correlation with wood biomass productivity and a negative relationship with stand age. Productivity also shows a positive correlation with the superficial phosphorus concentration. In addition, superficial phosphorus concentration increases with enhanced soil hydromorphic condition. We raise three hypotheses to explain these results: (1) the reduction of iron molecules on the saturated soils with plinthite layers close to the surface releases available phosphorous for the plants; (2) the poor structure of the saturated soils creates an environmental filter selecting tree species of faster growth rates and shorter life spans and (3) plant growth on saturated soil is favored during the dry season, since there should be low restrictions for soil water availability.

Electrokinetic treatment of an agricultural soil contaminated with heavy metals.

PubMed

Figueroa, Arylein; Cameselle, Claudio; Gouveia, Susana; Hansen, Henrik K

2016-07-28

The high organic matter content in agricultural soils tends to complex and retain contaminants such as heavy metals. Electrokinetic remediation was tested in an agricultural soil contaminated with Co(+2), Zn(+2), Cd(+2), Cu(+2), Cr(VI), Pb(+2) and Hg(+2). The unenhanced electrokinetic treatment was not able to remove heavy metals from the soil due to the formation of precipitates in the alkaline environment in the soil section close to the cathode. Moreover, the interaction between metals and organic matter probably limited metal transportation under the effect of the electric field. Citric acid and ethylenediaminetetraacetic acid (EDTA) were used in the catholyte as complexing agents in order to enhance the extractability and removal of heavy metals from soil. These complexing agents formed negatively charged complexes that migrated towards the anode. The acid front electrogenerated at the anode favored the dissolution of heavy metals that were transported towards the cathode. The combined effect of the soil pH and the complexing agents resulted in the accumulation of heavy metals in the center of the soil specimen.

Development of partial rock veneers by root throw in a subalpine setting

USGS Publications Warehouse

Osterkamp, W.R.; Toy, T.J.; Lenart, M.T.

2006-01-01

Rock veneers stabilize hillslope surfaces, occur especially in areas of immature soil, and form through a variety of process sets that includes root throw. Near Westcliffe, Colorado, USA, data were collected from a 20 ?? 500 m transect on the east slope of the Sangre de Cristo Mountains. Ages of pit/mound complexes with rock fragments exposed at the surface by root throw ranged from recent (freshly toppled tree) to unknown (complete tree decay). Calculations based on dimensions of the pit/mound complexes, estimated time of free topppling, sizes of exposed rock fragments, and percentage rock covers at pit/mound complexes, as well as within the transect area, indicate that recent rates of root throw have resulted in only partial rock veneering since late Pleistocene deglaciation. Weathering of rock fragments prevent development of an extensive rock veneer and causes a balance, achieved within an estimated 700 years, between the rates of rock-fragment exposure by root throw and clast disintegration by chemical reduction. The estimated rate of rock-fragment reduction accounts for part of the fluvial sediment yields observed for forested subalpine areas of western North America. Copyright ?? 2005 John Wiley & Sons, Ltd.

Dominant controls of transpiration along a hillslope transect inferred from ecohydrological measurements and thermodynamic limits

NASA Astrophysics Data System (ADS)

Renner, Maik; Hassler, Sibylle K.; Blume, Theresa; Weiler, Markus; Hildebrandt, Anke; Guderle, Marcus; Schymanski, Stanislaus J.; Kleidon, Axel

2016-05-01

We combine ecohydrological observations of sap flow and soil moisture with thermodynamically constrained estimates of atmospheric evaporative demand to infer the dominant controls of forest transpiration in complex terrain. We hypothesize that daily variations in transpiration are dominated by variations in atmospheric demand, while site-specific controls, including limiting soil moisture, act on longer timescales. We test these hypotheses with data of a measurement setup consisting of five sites along a valley cross section in Luxembourg. Both hillslopes are covered by forest dominated by European beech (Fagus sylvatica L.). Two independent measurements are used to estimate stand transpiration: (i) sap flow and (ii) diurnal variations in soil moisture, which were used to estimate the daily root water uptake. Atmospheric evaporative demand is estimated through thermodynamically constrained evaporation, which only requires absorbed solar radiation and temperature as input data without any empirical parameters. Both transpiration estimates are strongly correlated to atmospheric demand at the daily timescale. We find that neither vapor pressure deficit nor wind speed add to the explained variance, supporting the idea that they are dependent variables on land-atmosphere exchange and the surface energy budget. Estimated stand transpiration was in a similar range at the north-facing and the south-facing hillslopes despite the different aspect and the largely different stand composition. We identified an inverse relationship between sap flux density and the site-average sapwood area per tree as estimated by the site forest inventories. This suggests that tree hydraulic adaptation can compensate for heterogeneous conditions. However, during dry summer periods differences in topographic factors and stand structure can cause spatially variable transpiration rates. We conclude that absorption of solar radiation at the surface forms a dominant control for turbulent heat and mass exchange and that vegetation across the hillslope adjusts to this constraint at the tree and stand level. These findings should help to improve the description of land-surface-atmosphere exchange at regional scales.

Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-03-01

The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

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...

Maximum Entropy Production Modeling of Evapotranspiration Partitioning on Heterogeneous Terrain and Canopy Cover: advantages and limitations.

NASA Astrophysics Data System (ADS)

Gutierrez-Jurado, H. A.; Guan, H.; Wang, J.; Wang, H.; Bras, R. L.; Simmons, C. T.

2015-12-01

Quantification of evapotranspiration (ET) and its partition over regions of heterogeneous topography and canopy poses a challenge using traditional approaches. In this study, we report the results of a novel field experiment design guided by the Maximum Entropy Production model of ET (MEP-ET), formulated for estimating evaporation and transpiration from homogeneous soil and canopy. A catchment with complex terrain and patchy vegetation in South Australia was instrumented to measure temperature, humidity and net radiation at soil and canopy surfaces. Performance of the MEP-ET model to quantify transpiration and soil evaporation was evaluated during wet and dry conditions with independently and directly measured transpiration from sapflow and soil evaporation using the Bowen Ratio Energy Balance (BREB). MEP-ET transpiration shows remarkable agreement with that obtained through sapflow measurements during wet conditions, but consistently overestimates the flux during dry periods. However, an additional term introduced to the original MEP-ET model accounting for higher stomatal regulation during dry spells, based on differences between leaf and air vapor pressure deficits and temperatures, significantly improves the model performance. On the other hand, MEP-ET soil evaporation is in good agreement with that from BREB regardless of moisture conditions. The experimental design allows a plot and tree scale quantification of evaporation and transpiration respectively. This study confirms for the first time that the MEP-ET originally developed for homogeneous open bare soil and closed canopy can be used for modeling ET over heterogeneous land surfaces. Furthermore, we show that with the addition of an empirical function simulating the plants ability to regulate transpiration, and based on the same measurements of temperature and humidity, the method can produce reliable estimates of ET during both wet and dry conditions without compromising its parsimony.

Soil hydraulic material properties and layered architecture from time-lapse GPR

NASA Astrophysics Data System (ADS)

Jaumann, Stefan; Roth, Kurt

2018-04-01

Quantitative knowledge of the subsurface material distribution and its effective soil hydraulic material properties is essential to predict soil water movement. Ground-penetrating radar (GPR) is a noninvasive and nondestructive geophysical measurement method that is suitable to monitor hydraulic processes. Previous studies showed that the GPR signal from a fluctuating groundwater table is sensitive to the soil water characteristic and the hydraulic conductivity function. In this work, we show that the GPR signal originating from both the subsurface architecture and the fluctuating groundwater table is suitable to estimate the position of layers within the subsurface architecture together with the associated effective soil hydraulic material properties with inversion methods. To that end, we parameterize the subsurface architecture, solve the Richards equation, convert the resulting water content to relative permittivity with the complex refractive index model (CRIM), and solve Maxwell's equations numerically. In order to analyze the GPR signal, we implemented a new heuristic algorithm that detects relevant signals in the radargram (events) and extracts the corresponding signal travel time and amplitude. This algorithm is applied to simulated as well as measured radargrams and the detected events are associated automatically. Using events instead of the full wave regularizes the inversion focussing on the relevant measurement signal. For optimization, we use a global-local approach with preconditioning. Starting from an ensemble of initial parameter sets drawn with a Latin hypercube algorithm, we sequentially couple a simulated annealing algorithm with a Levenberg-Marquardt algorithm. The method is applied to synthetic as well as measured data from the ASSESS test site. We show that the method yields reasonable estimates for the position of the layers as well as for the soil hydraulic material properties by comparing the results to references derived from ground truth data as well as from time domain reflectometry (TDR).

Modelling Soil Heat and Water Flow as a Coupled Process in Land Surface Models

NASA Astrophysics Data System (ADS)

García González, Raquel; Verhoef, Anne; Vidale, Pier Luigi; Braud, Isabelle

2010-05-01

To improve model estimates of soil water and heat flow by land surface models (LSMs), in particular in the first few centimetres of the near-surface soil profile, we have to consider in detail all the relevant physical processes involved (see e.g. Milly, 1982). Often, thermal and iso-thermal vapour fluxes in LSMs are neglected and the simplified Richard's equation is used as a result. Vapour transfer may affect the water fluxes and heat transfer in LSMs used for hydrometeorological and climate simulations. Processes occurring in the top 50 cm soil may be relevant for water and heat flux dynamics in the deeper layers, as well as for estimates of evapotranspiration and heterotrophic respiration, or even for climate and weather predictions. Water vapour transfer, which was not incorporated in previous versions of the MOSES/JULES model (Joint UK Land Environment Simulator; Cox et al., 1999), has now been implemented. Furthermore, we also assessed the effect of the soil vertical resolution on the simulated soil moisture and temperature profiles and the effect of the processes occurring at the upper boundary, mainly in terms of infiltration rates and evapotranspiration. SiSPAT (Simple Soil Plant Atmosphere Transfer Model; Braud et al., 1995) was initially used to quantify the changes that we expect to find when we introduce vapour transfer in JULES, involving parameters such as thermal vapour conductivity and diffusivity. Also, this approach allows us to compare JULES to a more complete and complex numerical model. Water vapour flux varied with soil texture, depth and soil moisture content, but overall our results suggested that water vapour fluxes change temperature gradients in the entire soil profile and introduce an overall surface cooling effect. Increasing the resolution smoothed and reduced temperature differences between liquid (L) and liquid/vapour (LV) simulations at all depths, and introduced a temperature increase over the entire soil profile. Thermal gradients rather than soil water potential gradients seem to cause temporal and spatial (vertical) soil temperature variability. We conclude that a multi-soil layer configuration may improve soil water dynamics, heat transfer and coupling of these processes, as well as evapotranspiration estimates and land surface-atmosphere coupling. However, a compromise should be reached between numerical and process-simulation aspects. References: Braud I., A.C. Dantas-Antonino, M. Vauclin, J.L. Thony and P. Ruelle, 1995b: A Simple Soil Plant Atmo- sphere Transfer model (SiSPAT), Development and field verification, J. Hydrol, 166: 213-250 Cox, P.M., R.A. Betts, C.B. Bunton, R.L.H. Essery, P.R. Rowntree, and J. Smith (1999), The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Clim. Dyn., 15, 183-203. Milly, P.C.D., 1982. Moisture and heat transport in hysteric inhomogeneous porous media: a matric head- based formulation and a numerical model, Water Resour. Res., 18:489-498

Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

2016-01-01

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

Using Remotely Sensed Soil Moisture to Estimate Fire Risk in Tropical Peatlands

NASA Astrophysics Data System (ADS)

Dadap, N.; Cobb, A.; Hoyt, A.; Harvey, C. F.; Konings, A. G.

2017-12-01

Tropical peatlands in Equatorial Asia have become more vulnerable to fire due to deforestation and peatland drainage over the last 30 years. In these regions, water table depth has been shown to play an important role in mediating fire risk as it serves as a proxy for peat moisture content. However, water table depth observations are sparse and expensive. Soil moisture could provide a more direct indicator of fire risk than water table depth. In this study, we use new soil moisture retrievals from the Soil Moisture Active Passive (SMAP) satellite to demonstrate that - contrary to popular wisdom - remotely sensed soil moisture observations are possible over most Southeast Asian peatlands. Soil moisture estimation in this region was previously thought to be impossible over tropical peatlands because of dense vegetation cover. We show that vegetation density is sufficiently low across most Equatorial Asian peatlands to allow soil moisture estimation, and hypothesize that deforestation and other anthropogenic changes in land cover have combined to reduce overall vegetation density sufficient to allow soil moisture estimation. We further combine burned area estimates from the Global Fire Emissions Database and SMAP soil moisture retrievals to show that soil moisture provides a strong signal for fire risk in peatlands, with fires occurring at a much greater rate over drier soils. We will also develop an explicit fire risk model incorporating soil moisture with additional climatic, land cover, and anthropogenic predictor variables.

Microbial soil community analyses for forensic science: Application to a blind test.

PubMed

Demanèche, Sandrine; Schauser, Leif; Dawson, Lorna; Franqueville, Laure; Simonet, Pascal

2017-01-01

Soil complexity, heterogeneity and transferability make it valuable in forensic investigations to help obtain clues as to the origin of an unknown sample, or to compare samples from a suspect or object with samples collected at a crime scene. In a few countries, soil analysis is used in matters from site verification to estimates of time after death. However, up to date the application or use of soil information in criminal investigations has been limited. In particular, comparing bacterial communities in soil samples could be a useful tool for forensic science. To evaluate the relevance of this approach, a blind test was performed to determine the origin of two questioned samples (one from the mock crime scene and the other from a 50:50 mixture of the crime scene and the alibi site) compared to three control samples (soil samples from the crime scene, from a context site 25m away from the crime scene and from the alibi site which was the suspect's home). Two biological methods were used, Ribosomal Intergenic Spacer Analysis (RISA), and 16S rRNA gene sequencing with Illumina Miseq, to evaluate the discriminating power of soil bacterial communities. Both techniques discriminated well between soils from a single source, but a combination of both techniques was necessary to show that the origin was a mixture of soils. This study illustrates the potential of applying microbial ecology methodologies in soil as an evaluative forensic tool. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Organic matter and salinity modify cadmium soil (phyto)availability.

PubMed

Filipović, Lana; Romić, Marija; Romić, Davor; Filipović, Vilim; Ondrašek, Gabrijel

2018-01-01

Although Cd availability depends on its total concentration in soil, it is ultimately defined by the processes which control its mobility, transformations and soil solution speciation. Cd mobility between different soil fractions can be significantly affected by certain pedovariables such as soil organic matter (SOM; over formation of metal-organic complexes) and/or soil salinity (over formation of metal-inorganic complexes). Phytoavailable Cd fraction may be described as the proportion of the available Cd in soil which is actually accessible by roots and available for plant uptake. Therefore, in a greenhouse pot experiment Cd availability was observed in the rhizosphere of faba bean exposed to different levels of SOM, NaCl salinity (50 and 100mM) and Cd contamination (5 and 10mgkg -1 ). Cd availability in soil does not linearly follow its total concentration. Still, increasing soil Cd concentration may lead to increased Cd phytoavailability if the proportion of Cd 2+ pool in soil solution is enhanced. Reduced Cd (phyto)availability by raised SOM was found, along with increased proportion of Cd-DOC complexes in soil solution. Data suggest decreased Cd soil (phyto)availability with the application of salts. NaCl salinity affected Cd speciation in soil solution by promoting the formation of CdCl n 2-n complexes. Results possibly suggest that increased Cd mobility in soil does not result in its increased availability if soil adsorption capacity for Cd has not been exceeded. Accordingly, chloro-complex possibly operated just as a Cd carrier between different soil fractions and resulted only in transfer between solid phases and not in increased (phyto)availability. Copyright © 2017 Elsevier Inc. All rights reserved.

Estimation of soil clay and organic matter using two quantitative methods (PLSR and MARS) based on reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Nawar, Said; Buddenbaum, Henning; Hill, Joachim

2014-05-01

A rapid and inexpensive soil analytical technique is needed for soil quality assessment and accurate mapping. This study investigated a method for improved estimation of soil clay (SC) and organic matter (OM) using reflectance spectroscopy. Seventy soil samples were collected from Sinai peninsula in Egypt to estimate the soil clay and organic matter relative to the soil spectra. Soil samples were scanned with an Analytical Spectral Devices (ASD) spectrometer (350-2500 nm). Three spectral formats were used in the calibration models derived from the spectra and the soil properties: (1) original reflectance spectra (OR), (2) first-derivative spectra smoothened using the Savitzky-Golay technique (FD-SG) and (3) continuum-removed reflectance (CR). Partial least-squares regression (PLSR) models using the CR of the 400-2500 nm spectral region resulted in R2 = 0.76 and 0.57, and RPD = 2.1 and 1.5 for estimating SC and OM, respectively, indicating better performance than that obtained using OR and SG. The multivariate adaptive regression splines (MARS) calibration model with the CR spectra resulted in an improved performance (R2 = 0.89 and 0.83, RPD = 3.1 and 2.4) for estimating SC and OM, respectively. The results show that the MARS models have a great potential for estimating SC and OM compared with PLSR models. The results obtained in this study have potential value in the field of soil spectroscopy because they can be applied directly to the mapping of soil properties using remote sensing imagery in arid environment conditions. Key Words: soil clay, organic matter, PLSR, MARS, reflectance spectroscopy.

Estimates of soil ingestion by wildlife

USGS Publications Warehouse

Beyer, W.N.; Connor, E.E.; Gerould, S.

1994-01-01

Many wildlife species ingest soil while feeding, but ingestion rates are known for only a few species. Knowing ingestion rates may be important for studies of environmental contaminants. Wildlife may ingest soil deliberately, or incidentally, when they ingest soil-laden forage or animals that contain soil. We fed white-footed mice (Peromyscus leucopus) diets containing 0-15% soil to relate the dietary soil content to the acid-insoluble ash content of scat collected from the mice. The relation was described by an equation that required estimates of the percent acid-insoluble ash content of the diet, digestibility of the diet, and mineral content of soil. We collected scat from 28 wildlife species by capturing animals, searching appropriate habitats for scat, or removing material from the intestines of animals collected for other purposes. We measured the acid-insoluble ash content of the scat and estimated the soil content of the diets by using the soil-ingestion equation. Soil ingestion estimates should be considered only approximate because they depend on estimated rather than measured digestibility values and because animals collected from local populations at one time of the year may not represent the species as a whole. Sandpipers (Calidris spp.), which probe or peck for invertebrates in mud or shallow water, consumed sediments at a rate of 7-30% of their diets. Nine-banded armadillo (Dasypus novemcinctus, soil = 17% of diet), American woodcock (Scolopax minor, 10%), and raccoon (Procyon lotor, 9%) had high rates of soil ingestion, presumably because they ate soil organisms. Bison (Bison bison, 7%), black-tailed prairie dog (Cynomys ludovicianus, 8%), and Canada geese (Branta canadensis, 8%) consumed soil at the highest rates among the herbivores studied, and various browsers studied consumed little soil. Box turtle (Terrapene carolina, 4%), opossum (Didelphis virginiana, 5%), red fox (Vulpes vulpes, 3%), and wild turkey (Meleagris gallopavo, 9%) consumed soil at intermediate rates. Ingested soil may be the principal means of exposure to some environmental contaminants or the principal source of certain minerals. Soil-ingestion estimates may be required for risk assessments of wildlife inhabiting contaminated sites and for computing budgets of those nutrients associated mainly with soil.

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Garcia, Matthew E.; Mocko, David M.; Tischler, Michael A.; Moran, M. Susan; Thoma, D. P.

2007-01-01

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Estimation of effective soil hydraulic properties at field scale via ground albedo neutron sensing

NASA Astrophysics Data System (ADS)

Rivera Villarreyes, C. A.; Baroni, G.; Oswald, S. E.

2012-04-01

Upscaling of soil hydraulic parameters is a big challenge in hydrological research, especially in model applications of water and solute transport processes. In this contest, numerous attempts have been made to optimize soil hydraulic properties using observations of state variables such as soil moisture. However, in most of the cases the observations are limited at the point-scale and then transferred to the model scale. In this way inherent small-scale soil heterogeneities and non-linearity of dominate processes introduce sources of error that can produce significant misinterpretation of hydrological scenarios and unrealistic predictions. On the other hand, remote-sensed soil moisture over large areas is also a new promising approach to derive effective soil hydraulic properties over its observation footprint, but it is still limited to the soil surface. In this study we present a new methodology to derive soil moisture at the intermediate scale between point-scale observations and estimations at the remote-sensed scale. The data are then used for the estimation of effective soil hydraulic parameters. In particular, ground albedo neutron sensing (GANS) was used to derive non-invasive soil water content in a footprint of ca. 600 m diameter and a depth of few decimeters. This approach is based on the crucial role of hydrogen compared to other landscape materials as neutron moderator. As natural neutron measured aboveground depends on soil water content, the vertical footprint of the GANS method, i.e. its penetration depth, does also. Firstly, this study was designed to evaluate the dynamics of GANS vertical footprint and derive a mathematical model for its prediction. To test GANS-soil moisture and its penetration depth, it was accompanied by other soil moisture measurements (FDR) located at 5, 20 and 40 cm depths over the GANS horizontal footprint in a sunflower field (Brandenburg, Germany). Secondly, a HYDRUS-1D model was set up with monitored values of crop height and meteorological variables as input during a four-month period. Parameter estimation (PEST) software was coupled to HYDRUS-1D in order to calibrate soil hydraulic properties based on soil water content data. Thirdly, effective soil hydraulic properties were derived from GANS-soil moisture. Our observations show the potential of GANS to compensate the lack of information at the intermediate scale, soil water content estimation and effective soil properties. Despite measurement volumes, GANS-derived soil water content compared quantitatively to FDRs at several depths. For one-hour estimations, root mean square error was estimated as 0.019, 0.029 and 0.036 m3/m3 for 5 cm, 20 cm and 40 cm depths, respectively. In the context of soil hydraulic properties, this first application of GANS method succeed and its estimations were comparable to those derived by other approaches.

Geomorphic controls of soil spatial complexity in a primeval mountain forest in the Czech Republic

NASA Astrophysics Data System (ADS)

Daněk, Pavel; Šamonil, Pavel; Phillips, Jonathan D.

2016-11-01

Soil diversity and complexity is influenced by a variety of factors, and much recent research has been focused on interpreting or modeling complexity based on soil-topography relationships, and effects of biogeomorphic processes. We aimed to (i) describe local soil diversity in one of the oldest forest reserves in Europe, (ii) employ existing graph theory concepts in pedocomplexity calculation and extend them by a novel approach based on hypothesis testing and an index measuring graph sequentiality (the extent to which soils have gradual vs. abrupt variations in underlying soil factors), and (iii) reveal the main sources of pedocomplexity, with a particular focus on geomorphic controls. A total of 954 soil profiles were described and classified to soil taxonomic units (STU) within a 46 ha area. We analyzed soil diversity using the Shannon index, and soil complexity using a novel graph theory approach. Pairwise tests of observed adjacencies, spectral radius and a newly proposed sequentiality index were used to describe and quantify the complexity of the spatial pattern of STUs. This was then decomposed into the contributions of three soil factor sequences (SFS), (i) degree of weathering and leaching processes, (ii) hydromorphology, and (iii) proportion of rock fragments. Six Reference Soil Groups and 37 second-level soil units were found. A significant portion of pedocomplexity occurred at distances shorter than the 22 m spacing of neighbouring soil profiles. The spectral radius (an index of complexity) of the pattern of soil spatial adjacency was 14.73, to which the individual SFS accounted for values of 2.0, 8.0 and 3.5, respectively. Significant sequentiality was found for degree of weathering and hydromorphology. Exceptional overall pedocomplexity was particularly caused by enormous spatial variability of soil wetness, representing a crucial soil factor sequence in the primeval forest. Moreover, the soil wetness gradient was partly spatially correlated with the gradient of soil weathering and leaching, suggesting synergistic influences of topography, climate, (hydro)geology and biomechanical and biochemical effects of individual trees. The pattern of stony soils, random in most respects, resulted probably from local geology and quaternary biogeomorphological processes. Thus, while geomorphology is the primary control over a very locally complex soil pattern, microtopography and local disturbances, mostly related to the effects of individual trees, are also critical. Considerable local pedodiversity seems to be an important component of the dynamics of old-growth mixed temperate mountain forests, with implications for decreasing pedodiversity in managed forests and deforested areas.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

Spatial gradient of human health risk from exposure to trace elements and radioactive pollutants in soils at the Puchuncaví-Ventanas industrial complex, Chile.

PubMed

Salmani-Ghabeshi, S; Palomo-Marín, M R; Bernalte, E; Rueda-Holgado, F; Miró-Rodríguez, C; Cereceda-Balic, F; Fadic, X; Vidal, V; Funes, M; Pinilla-Gil, E

2016-11-01

The Punchuncaví Valley in central Chile, heavily affected by a range of anthropogenic emissions from a localized industrial complex, has been studied as a model environment for evaluating the spatial gradient of human health risk, which are mainly caused by trace elemental pollutants in soil. Soil elemental profiles in 121 samples from five selected locations representing different degrees of impact from the industrial source were used for human risk estimation. Distance to source dependent cumulative non-carcinogenic hazard indexes above 1 for children (max 4.4 - min 1.5) were found in the study area, ingestion being the most relevant risk pathway. The significance of health risk differences within the study area was confirmed by statistical analysis (ANOVA and HCA) of individual hazard index values at the five sampling locations. As was the dominant factor causing unacceptable carcinogenic risk levels for children (<10 -4 ) at the two sampling locations which are closer to the industrial complex, whereas the risk was just in the tolerable range (10 -6 - 10 -4 ) for children and adults in the rest of the sampling locations at the study area. Furthermore, we assessed gamma ray radiation external hazard indexes and annual effective dose rate from the natural radioactivity elements ( 226 Ra, 232 Th and 40 K) levels in the surface soils of the study area. The highest average values for the specific activity of 232 Th (31 Bq kg -1 ), 40 K (615 Bq kg - 1 ), and 226 Ra (25 Bq kg -1 ) are lower than limit recommended by OECD, so no significant radioactive risk was detected within the study area. In addition, no significant variability of radioactive risk was observed among sampling locations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

2017-12-01

Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

Assessing and monitoring soil erosion and land degradation in Malta

NASA Astrophysics Data System (ADS)

Symeonakis, Elias; Brearley, James

2017-04-01

The United Nations Convention to Combat Desertification (UNCCD) identifies the Mediterranean as one of the most seriously affected by land degradation and desertification (LDD) regions in the World. LDD is a complex process related with a multitude of biogeographical and socioeconomic parameters and is often assessed using proxies or indicators. One of the most important indicators of LDD is soil erosion. Here, we assess the evolution of soil erosion and LDD in the Mediterranean islands of Malta between 1986 and 2002. Soil erosion is estimated using the Revised Soil Loss Equation (RUSLE). For the assessment of LDD, we employ a modification of the Environmentally Sensitive Area Index (ESAI) methodology with Landsat imagery and ancillary GIS datasets. We incorporate 4 vegetation-related indicators, 3 climate-related, 5 soil-related and 3 socio-economic ones in the final assessment of the evolution of LDD. Results show that there has been an increase in soil erosion rates and in the sensitivity to LDD in the areas of San Pawl il-Bahar and Il-Mizieb most likely due to the transition from agricultural use to Mediterranean shrubs. Also, almost the entire country is flagged as belonging to the 'Fragile' and 'Critical' ESAI classes. It is clear that soil erosion and LDD mitigation measures are necessary, especially in the most critical (i.e. 'C3') areas which occupy 10% of Malta.

The BonaRes Centre - A virtual institute for soil research in the context of a sustainable bio-economy

NASA Astrophysics Data System (ADS)

Wollschläger, Ute; Helming, Katharina; Heinrich, Uwe; Bartke, Stephan; Kögel-Knabner, Ingrid; Russell, David; Eberhardt, Einar; Vogel, Hans-Jörg

2016-04-01

Fertile soils are central resources for the production of biomass and provision of food and energy. A growing world population and latest climate targets lead to an increasing demand for both, food and bio-energy, which require preserving and improving the long-term productivity of soils as a bio-economic resource. At the same time, other soil functions and ecosystem services need to be maintained. To render soil management sustainable, we need to establish a scientific knowledge base about complex soil system processes that allows for the development of model tools to quantitatively predict the impact of a multitude of management measures on soil functions. This, finally, will allow for the provision of site-specific options for sustainable soil management. To face this challenge, the German Federal Ministry of Education and Research recently launched the funding program "Soil as a Natural Resource for the Bio-Economy - BonaRes". In a joint effort, ten collaborative projects and the coordinating BonaRes Centre are engaged to close existing knowledge gaps for a profound and systemic understanding of soil functions and their sensitivity to soil management. This presentation provides an overview of the concept of the BonaRes Centre which is responsible for i) setting up a comprehensive data base for soil-related information, ii) the development of model tools aiming to estimate the impact of different management measures on soil functions, and iii) establishing a web-based portal providing decision support tools for a sustainable soil management. A specific focus of the presentation will be laid on the so-called "knowledge-portal" providing the infrastructure for a community effort towards a comprehensive meta-analysis on soil functions as a basis for future model developments.

Healthy soils healthy people: Unraveling the complexity

USDA-ARS?s Scientific Manuscript database

The linkage between soil and human health is undoubtedly a complex and multidisciplinary issue. The recognition that soil can influence human health is not a novelty; it has been recognized scientifically for decades. However, the advancement in understanding soil health/quality has renewed interest...

Assessment of Bioavailable Concentrations of Germanium and Rare Earth Elements in the Rhizosphere of White Lupin (Lupinus albus L.)

NASA Astrophysics Data System (ADS)

Wiche, Oliver; Fischer, Ronny; Moschner, Christin; Székely, Balázs

2015-04-01

Concentrations of Germanium (Ge) and Rare Earth Elements in soils are estimated at 1.5 mg kg -1 (Ge), 25 mg kg -1 (La) and 20 mg kg -1 (Nd), which are only roughly smaller than concentrations of Pb and Zn. Germanium and rare earth elements are thus not rare but widely dispersed in soils and therefore up to date, only a few minable deposits are available. An environmental friendly and cost-effective way for Ge and rare earth element production could be phytomining. However, the most challenging part of a phytomining of these elements is to increase bioavailable concentrations of the elements in soils. Recent studies show, that mixed cultures with white lupine or other species with a high potential to mobilize trace metals in their rhizosphere due to an acidification of the soil and release of organic acids in the root zone could be a promising tool for phytomining. Complexation of Ge and rare earth elements by organic acids might play a key role in controlling bioavailability to plants as re-adsorption on soil particles and precipitation is prevented and thus, concentrations in the root zone of white lupine increase. This may also allow the complexes to diffuse along a concentration gradient to the roots of mixed culture growing species leading to enhanced plant uptake. However, to optimize mixed cultures it would be interesting to know to which extend mobilization of trace metals is dependent from chemical speciation of elements in soil due to the interspecific interaction of roots. A method for the identification of complexes of germanium and rare earth elements with organic acids, predominantly citric acid in the rhizosphere of white lupine was developed and successfully tested. The method is based on coupling of liquid chromatography with ICP-MS using a zic-philic column (SeQuant). As a preliminary result, we were able to show that complexes of germanium with citric acid exist in the rhizosphere of white lupin, what may contribute to the bioavailability of this element. These studies have been carried out in the framework of the PhytoGerm project, financed by the Federal Ministry of Education and Research, Germany. The authors are grateful to students and laboratory assistants contributing in the field work and sample preparation.

On soil textural classifications and soil-texture-based estimations

NASA Astrophysics Data System (ADS)

Ángel Martín, Miguel; Pachepsky, Yakov A.; García-Gutiérrez, Carlos; Reyes, Miguel

2018-02-01

The soil texture representation with the standard textural fraction triplet sand-silt-clay is commonly used to estimate soil properties. The objective of this work was to test the hypothesis that other fraction sizes in the triplets may provide a better representation of soil texture for estimating some soil parameters. We estimated the cumulative particle size distribution and bulk density from an entropy-based representation of the textural triplet with experimental data for 6240 soil samples. The results supported the hypothesis. For example, simulated distributions were not significantly different from the original ones in 25 and 85 % of cases when the sand-silt-clay and very coarse+coarse + medium sand - fine + very fine sand - silt+clay were used, respectively. When the same standard and modified triplets were used to estimate the average bulk density, the coefficients of determination were 0.001 and 0.967, respectively. Overall, the textural triplet selection appears to be application and data specific.

The inconvenient truth about eddy covariance flux partitioning and implications for global carbon cycle estimates

NASA Astrophysics Data System (ADS)

Wohlfahrt, Georg; Galvagno, Marta

2016-04-01

Ecosystem respiration (ER) and gross primary productivity (GPP) are key carbon cycle concepts. Global estimates of ER and GPP are largely based on measurements of the net ecosystem CO2 exchange by means of the eddy covariance method from which ER and GPP are inferred using so-called flux partitioning algorithms. Using a simple two-source model of ecosystem respiration, consisting of an above-ground respiration source driven by simulated air temperature and a below-ground respiration source driven by simulated soil temperature, we demonstrate that the two most popular flux partitioning algorithms are unable to provide unbiased estimates of daytime ER (ignoring any reduction of leaf mitochondrial respiration) and thus GPP. The bias is demonstrated to be either positive or negative and to depend in a complex fashion on the driving temperature, the ratio of above- to below-ground respiration, the respective temperature sensitivities, the soil depth where the below-ground respiration source originates from (and thus phase and amplitude of soil vs. surface temperature) and day length. The insights from the modeling analysis are subject to a reality check using direct measurements of ER at a grassland where measurements of ER were conducted both during night and day using automated opaque chambers. Consistent with the modeling analysis we find that using air temperature to extrapolate from nighttime to daytime conditions overestimates daytime ER (by 20% or ca. 65 gC m-2 over a 100 day study period), while soil temperature results in an underestimation (by 4% or 12 gC m-2). We conclude with practical recommendations for eddy covariance flux partitioning in the context of the FLUXNET project.

Generating large-scale estimates from sparse, in-situ networks: multi-scale soil moisture modeling at ARS watersheds for NASA’s soil moisture active passive (SMAP) calibration/validation mission

USDA-ARS?s Scientific Manuscript database

NASA’s SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networ...

Soil Bulk Density by Soil Type, Land Use and Data Source: Putting the Error in SOC Estimates

NASA Astrophysics Data System (ADS)

Wills, S. A.; Rossi, A.; Loecke, T.; Ramcharan, A. M.; Roecker, S.; Mishra, U.; Waltman, S.; Nave, L. E.; Williams, C. O.; Beaudette, D.; Libohova, Z.; Vasilas, L.

2017-12-01

An important part of SOC stock and pool assessment is the assessment, estimation, and application of bulk density estimates. The concept of bulk density is relatively simple (the mass of soil in a given volume), the specifics Bulk density can be difficult to measure in soils due to logistical and methodological constraints. While many estimates of SOC pools use legacy data in their estimates, few concerted efforts have been made to assess the process used to convert laboratory carbon concentration measurements and bulk density collection into volumetrically based SOC estimates. The methodologies used are particularly sensitive in wetlands and organic soils with high amounts of carbon and very low bulk densities. We will present an analysis across four database measurements: NCSS - the National Cooperative Soil Survey Characterization dataset, RaCA - the Rapid Carbon Assessment sample dataset, NWCA - the National Wetland Condition Assessment, and ISCN - the International soil Carbon Network. The relationship between bulk density and soil organic carbon will be evaluated by dataset and land use/land cover information. Prediction methods (both regression and machine learning) will be compared and contrasted across datasets and available input information. The assessment and application of bulk density, including modeling, aggregation and error propagation will be evaluated. Finally, recommendations will be made about both the use of new data in soil survey products (such as SSURGO) and the use of that information as legacy data in SOC pool estimates.

Validation of Soil Water Content Estimation Method on Agricultural Regions in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Kim, M.

2016-12-01

The continuous water stress caused by decrease of soil water has a direct influence to the crop growth in a upland crop area. The agricultural drought is occured if water requirement is not supplied timely in crop growh process. It is more important to understand the soil characteristics for high accuracy soil moisture estimation because of the soil water contents largely depends on soil properties. The RDA(Rural Development Administration) has provided real-time soil moisture observations corrected for 71 points in the South Korea. In this study, we developed a soil water content estimation method that considered soil hydraulic parameters for the observation points of soil water content in agricultural regions operated by the RDA. SWAP(Soil-Water-Atmosphere-Plant) model was used in the estimation of soil water contents. The soil hydraulic parameters that is the input data of the SWAP model were estimated using the ROSETTA model developed by the U.S. Department of Agriculture(USDA). Meteorological data observed from AWS(Automatic Weather Station) were used including daily maximum temperature(°), daily minimum temperature(°), relative humidity(%), solar radiation, wind speed and precipitation data. We choosed 56 stations there are no missing of meteorological data and have soil physical properties. For the verification of soil water content estimation method, we used Haenam KoFlux observation data that are observed long-term soil water contents over 2009-2015(2014 missing) years. In the case of 2015, there are good reproducibility between observation of soil water contents and results of SWAP model simulation with R2=0.72, RMSE=0.026 and TCC=0.849. In the case of precipitation event, the simulation results were slightly overestimated more than observation. However there are good reproducibility in the case of soil water reduction due to continuous non-precipitation periods. We have simulated the soil water contents of the 56 stations that being operated in the RDA from 4 January 2015 to 31 October 2015 using the SWAP model. The environmental setting of SWAP modle according to the station applied it equally. The results showed a significant difference to the reproducibility according to the observation station.

Towards a model-based inventory of soil organic carbon in agricultural soils for the Swiss greenhouse gas reporting

NASA Astrophysics Data System (ADS)

Staudt, K.; Leifeld, J.; Bretscher, D.; Fuhrer, J.

2012-04-01

The Swiss inventory submission under the United Nations Framework Convention on Climate Change (UNFCCC) reports on changes in soil organic carbon stocks under different land-uses and land-use changes. The approach currently employed for cropland and grassland soils combines Tier 1 and Tier 2 methods and is considered overly simplistic. As the UNFCC encourages countries to develop Tier 3 methods for national greenhouse gas reporting, we aim to build up a model-based inventory of soil organic carbon in agricultural soils in Switzerland. We conducted a literature research on currently employed higher-tier methods using process-based models in four countries: Denmark, Sweden, Finland and the USA. The applied models stem from two major groups differing in complexity - those belonging to the group of general ecosystem models that include a plant-growth submodel, e.g. Century, and those that simulate soil organic matter turnover but not plant-growth, e.g. ICBM. For the latter group, carbon inputs to the soil from plant residues and roots have to be determined separately. We will present some aspects of the development of a model-based inventory of soil organic carbon in agricultural soils in Switzerland. Criteria for model evaluation are, among others, modeled land-use classes and land-use changes, spatial and temporal resolution, and coverage of relevant processes. For model parameterization and model evaluation at the field scale, data from several long-term agricultural experiments and monitoring sites in Switzerland is available. A subsequent regional application of a model requires the preparation of regional input data for the whole country - among others spatio-temporal meteorological data, agricultural and soil data. Following the evaluation of possible models and of available data, preference for application in the Swiss inventory will be given to simpler model structures, i.e. models without a plant-growth module. Thus, we compared different allometric relations for the estimation of plant carbon inputs to the soil from yield data that are usually provided with the models. Calculated above- and below-ground carbon inputs vary substantially between methods and exhibit different sensitivities to yield data. As a benchmark, inputs to the soil from above- and below-ground crop residues are calculated with the IPCC default method. Furthermore, the suitability of these estimation methods for Swiss conditions is tested.

Exploring the Impact of Different Input Data Types on Soil Variable Estimation Using the ICRAF-ISRIC Global Soil Spectral Database.

PubMed

Aitkenhead, Matt J; Black, Helaina I J

2018-02-01

Using the International Centre for Research in Agroforestry-International Soil Reference and Information Centre (ICRAF-ISRIC) global soil spectroscopy database, models were developed to estimate a number of soil variables using different input data types. These input types included: (1) site data only; (2) visible-near-infrared (Vis-NIR) diffuse reflectance spectroscopy only; (3) combined site and Vis-NIR data; (4) red-green-blue (RGB) color data only; and (5) combined site and RGB color data. The models produced variable estimation accuracy, with RGB only being generally worst and spectroscopy plus site being best. However, we showed that for certain variables, estimation accuracy levels achieved with the "site plus RGB input data" were sufficiently good to provide useful estimates (r 2  > 0.7). These included major elements (Ca, Si, Al, Fe), organic carbon, and cation exchange capacity. Estimates for bulk density, contrast-to-noise (C/N), and P were moderately good, but K was not well estimated using this model type. For the "spectra plus site" model, many more variables were well estimated, including many that are important indicators for agricultural productivity and soil health. Sum of cation, electrical conductivity, Si, Ca, and Al oxides, and C/N ratio were estimated using this approach with r 2 values > 0.9. This work provides a mechanism for identifying the cost-effectiveness of using different model input data, with associated costs, for estimating soil variables to required levels of accuracy.

Global spatiotemporal distribution of soil respiration modeled using a global database

NASA Astrophysics Data System (ADS)

Hashimoto, S.; Carvalhais, N.; Ito, A.; Migliavacca, M.; Nishina, K.; Reichstein, M.

2015-07-01

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration data set, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5°and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95 % confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. The estimates are based on a semi-empirical model parameterized with over one thousand data points. Our analysis indicates that the climate controls on soil respiration may translate into an increasing trend in global soil respiration and our analysis emphasizes the relevance of the soil carbon flux from soil to the atmosphere in response to climate change. Further approaches should additionally focus on climate controls in soil respiration in combination with changes in vegetation dynamics and soil carbon stocks, along with their effects on the long temporal dynamics of soil respiration. We expect that these spatiotemporal estimates will provide a benchmark for future studies and also help to constrain process-oriented models.

Application of Multitemporal Remotely Sensed Soil Moisture for the Estimation of Soil Physical Properties

NASA Technical Reports Server (NTRS)

Mattikalli, N. M.; Engman, E. T.; Jackson, T. J.; Ahuja, L. R.

1997-01-01

This paper demonstrates the use of multitemporal soil moisture derived from microwave remote sensing to estimate soil physical properties. The passive microwave ESTAR instrument was employed during June 10-18, 1992, to obtain brightness temperature (TB) and surface soil moisture data in the Little Washita watershed, Oklahoma. Analyses of spatial and temporal variations of TB and soil moisture during the dry-down period revealed a direct relationship between changes in T and soil moisture and soil physical (viz. texture) and hydraulic (viz. saturated hydraulic conductivity, K(sat)) properties. Statistically significant regression relationships were developed for the ratio of percent sand to percent clay (RSC) and K(sat), in terms of change components of TB and surface soil moisture. Validation of results using field measured values and soil texture map indicated that both RSC and K(sat) can be estimated with reasonable accuracy. These findings have potential applications of microwave remote sensing to obtain quick estimates of the spatial distributions of K(sat), over large areas for input parameterization of hydrologic models.

Comparative estimation and assessment of initial soil moisture conditions for Flash Flood warning in Saxony

NASA Astrophysics Data System (ADS)

Luong, Thanh Thi; Kronenberg, Rico; Bernhofer, Christian; Janabi, Firas Al; Schütze, Niels

2017-04-01

Flash Floods are known as highly destructive natural hazards due to their sudden appearance and severe consequences. In Saxony/Germany flash floods occur in small and medium catchments of low mountain ranges which are typically ungauged. Besides rainfall and orography, pre-event moisture is decisive, as it determines the available natural retention in the catchment. The Flash Flood Guidance concept according to WMO and Prof. Marco Borga (University of Padua) will be adapted to incorporate pre-event moisture in real-time flood forecast within the ESF EXTRUSO project (SAB-Nr. 100270097). To arrive at pre-event moisture for the complete area of the low mountain range with flash flood potential, a widely applicable, accurate but yet simple approach is needed. Here, we use radar precipitation as input time series, detailed orographic, land-use and soil information and a lumped parameter model to estimate the overall catchment soil moisture and potential retention. When combined with rainfall forecast and its intrinsic uncertainty, the approach allows to find the point in time when precipitation exceeds the retention potential of the catchment. Then, spatially distributed and complex hydrological modeling and additional measurements can be initiated. Assuming reasonable rainfall forecasts of 24 to 48hrs, this part can start up to two days in advance of the actual event. The lumped-parameter model BROOK90 is used and tested for well observed catchments. First, physical meaningful parameters (like albedo or soil porosity) a set according to standards and second, "free" parameters (like percentage of lateral flow) were calibrated objectively by PEST (Model-Independent Parameter Estimation and Uncertainty Analysis) with the target on evapotranspiration and soil moisture which both have been measured at the study site Anchor Station Tharandt in Saxony/Germany. Finally, first results are presented for the Wernersbach catchment in Tharandt forest for main flood events in the 50-year gauging period since 1968.

Smart Fluids in Hydrology: Use of Non-Newtonian Fluids for Pore Structure Characterization

NASA Astrophysics Data System (ADS)

Abou Najm, M. R.; Atallah, N. M.; Selker, J. S.; Roques, C.; Stewart, R. D.; Rupp, D. E.; Saad, G.; El-Fadel, M.

2015-12-01

Classic porous media characterization relies on typical infiltration experiments with Newtonian fluids (i.e., water) to estimate hydraulic conductivity. However, such experiments are generally not able to discern important characteristics such as pore size distribution or pore structure. We show that introducing non-Newtonian fluids provides additional unique flow signatures that can be used for improved pore structure characterization while still representing the functional hydraulic behavior of real porous media. We present a new method for experimentally estimating the pore structure of porous media using a combination of Newtonian and non-Newtonian fluids. The proposed method transforms results of N infiltration experiments using water and N-1 non-Newtonian solutions into a system of equations that yields N representative radii (Ri) and their corresponding percent contribution to flow (wi). This method allows for estimating the soil retention curve using only saturated experiments. Experimental and numerical validation comparing the functional flow behavior of different soils to their modeled flow with N representative radii revealed the ability of the proposed method to represent the water retention and infiltration behavior of real soils. The experimental results showed the ability of such fluids to outsmart Newtonian fluids and infer pore size distribution and unsaturated behavior using simple saturated experiments. Specifically, we demonstrate using synthetic porous media that the use of different non-Newtonian fluids enables the definition of the radii and corresponding percent contribution to flow of multiple representative pores, thus improving the ability of pore-scale models to mimic the functional behavior of real porous media in terms of flow and porosity. The results advance the knowledge towards conceptualizing the complexity of porous media and can potentially impact applications in fields like irrigation efficiencies, vadose zone hydrology, soil-root-plant continuum, carbon sequestration into geologic formations, soil remediation, petroleum reservoir engineering, oil exploration and groundwater modeling.

Estimated stocks of circumpolar permafrost carbon with quantified uncertainty ranges and identified data gaps

DOE PAGES

Hugelius, Gustaf; Strauss, J.; Zubrzycki, S.; ...

2014-12-01

Soils and other unconsolidated deposits in the northern circumpolar permafrost region store large amounts of soil organic carbon (SOC). This SOC is potentially vulnerable to remobilization following soil warming and permafrost thaw, but SOC stock estimates were poorly constrained and quantitative error estimates were lacking. This study presents revised estimates of permafrost SOC stocks, including quantitative uncertainty estimates, in the 0–3 m depth range in soils as well as for sediments deeper than 3 m in deltaic deposits of major rivers and in the Yedoma region of Siberia and Alaska. Revised estimates are based on significantly larger databases compared tomore » previous studies. Despite this there is evidence of significant remaining regional data gaps. Estimates remain particularly poorly constrained for soils in the High Arctic region and physiographic regions with thin sedimentary overburden (mountains, highlands and plateaus) as well as for deposits below 3 m depth in deltas and the Yedoma region. While some components of the revised SOC stocks are similar in magnitude to those previously reported for this region, there are substantial differences in other components, including the fraction of perennially frozen SOC. Upscaled based on regional soil maps, estimated permafrost region SOC stocks are 217 ± 12 and 472 ± 27 Pg for the 0–0.3 and 0–1 m soil depths, respectively (±95% confidence intervals). Storage of SOC in 0–3 m of soils is estimated to 1035 ± 150 Pg. Of this, 34 ± 16 Pg C is stored in poorly developed soils of the High Arctic. Based on generalized calculations, storage of SOC below 3 m of surface soils in deltaic alluvium of major Arctic rivers is estimated as 91 ± 52 Pg. In the Yedoma region, estimated SOC stocks below 3 m depth are 181 ± 54 Pg, of which 74 ± 20 Pg is stored in intact Yedoma (late Pleistocene ice- and organic-rich silty sediments) with the remainder in refrozen thermokarst deposits. Total estimated SOC storage for the permafrost region is ∼1300 Pg with an uncertainty range of ∼1100 to 1500 Pg. Of this, ∼500 Pg is in non-permafrost soils, seasonally thawed in the active layer or in deeper taliks, while ∼800 Pg is perennially frozen. In conclusion, this represents a substantial ∼300 Pg lowering of the estimated perennially frozen SOC stock compared to previous estimates.« less

Characterization of tillage effects on soil permeability using different measures of macroporosity derived from tension infiltrometry

NASA Astrophysics Data System (ADS)

Bodner, G.; Schwen, A.; Scholl, P.; Kammerer, G.; Buchan, G.; Kaul, H.-P.; Loiskandl, W.

2010-05-01

Soil macroporosity is a highly dynamic property influenced by environmental factors, such as raindrop impact, wetting-drying and freezing-thawing cycles, soil biota and plant roots, as well as agricultural management measures. Macroporosity represents an important indicator of soil physical quality, particularly in relation to the site specific water transmission properties, and can be used as a sensitive measure to assess soil structural degradation. Its quantification is also required for the parameterization of dual porosity models that are frequently used in environmental impact studies on erosion and solute (pesticide, nitrate) leaching. The importance of soil macroporosity for the water transport properties of the soil and its complexity due to high spatio-temporal heterogeneity make its quantitative assessment still a challenging task. Tension infiltrometers have been shown to be adequate measurement devices to obtain data in the near-saturated range of water flow where structural (macro)pores are dominating the transport process. Different methods have been used to derive water transmission characteristics from tension infiltrometer measurements. Moret and Arrúe (2007) differentiated between using a minimum equivalent capillary pore radius and a flow weighted mean pore radius to obtain representative macropore flow properties from tension infiltrometer data. Beside direct approaches based on Wooding's equation, also inverse methods have been applied to obtain soil hydraulic properties (Šimůnek et al. 1998). Using a dual porosity model in the inverse procedure allows estimating parameters in the dynamic near-saturated range by numerical optimization to the infiltration measurements, while fixing parameters in the more stable textural range of small pores using e.g. pressure plate data or even pedotransfer functions. The present work presents a comparison of quantitative measures of soil macroporosity derived from tension infiltrometer data by different approaches (direct vs. inverse evaluation, capillary vs. flow weighted pore radius). We will show the influence of the distinct evaluation procedures on the resulting effective macroporosity, as well as on the relationships between macropore radius and hydraulic conductivity (Moret and Arrúe, 2007) and pore fraction respectively (Carey et al., 2007). The infiltration measurements used in this study were obtained in a long-term tillage trial located in the semi-arid region of Eastern Austria. Measurements were taken five times over the vegetation period, starting immediately after tillage until harvest of the winter wheat crop. Three tillage systems were evaluated, being conventional tillage with plough, minimum tillage with chisel and no-tillage. Additional to infiltration measurements, also soil water content was monitored continuously by a capacitance probe in all three replicates of each tillage treatment in 10, 20 and 40 cm soil depth. Water content time series are used to derive flow velocity in the wet range by cross-correlation analysis (Wu et al., 1997). This effective parameter of water transmission will then be compared to the flow behaviour expected from the characterization of soil macroporosity. We will show that mainly in no-tillage systems large macropores contribute essentially to flow and therefore the decision on pore measure and evaluation procedure to be used leads to substantial differences. For a detailed comparison of tillage effects on soil hydraulic properties it is therefore essential to analyse the contribution of different tension infiltrometry based evaluation methods to explain effective water transmission through the complex porous network of the soil. References Carey, S.K., Quinton, W.L., Goeller, N.T. 2007. Field and laboratory estimates of pore size properties and hydraulic characteristics for subarctic organic soils. Hydrol. Process. 21, 2560-2571. Moret, D., Arrúe, J.L. 2007. Characterizing soil water conducting macro- and mesoporosity as influences by tillage using tension infiltrmetry. Soil Sci. Soc. Am. J. 71, 500-506. Šimůnek, J., Wang Dong, Shouse, P. J., van Genuchten, M. T. 1998. Analysis of field tension disc infiltrometer data by parameter estimation. Int. Agrophys. 12. 167-180. Wu, L., Jury, W.A., Chang, A.C. 1997. Time series analysis of field-measured watr content of a sandy soil. Soil Sci. Soc. Am. J. 61. 742-745.

Impacts of different types of measurements on estimating unsaturated flow parameters

NASA Astrophysics Data System (ADS)

Shi, Liangsheng; Song, Xuehang; Tong, Juxiu; Zhu, Yan; Zhang, Qiuru

2015-05-01

This paper assesses the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

NASA Astrophysics Data System (ADS)

Shi, L.

2015-12-01

This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Linking annual N2O emission in organic soils to mineral nitrogen input as estimated by heterotrophic respiration and soil C/N ratio.

PubMed

Mu, Zhijian; Huang, Aiying; Ni, Jiupai; Xie, Deti

2014-01-01

Organic soils are an important source of N2O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N2O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO2 flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO2 and N2O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N2O fluxes, whereas CO2 flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N2O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N2O flux. Our proposed approach, which uses the product of soil-derived CO2 flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N2O fluxes from organic soils, although some further enhancements may be warranted.

Global distribution of soil organic carbon - Part 1: Masses and frequency distributions of SOC stocks for the tropics, permafrost regions, wetlands, and the world

NASA Astrophysics Data System (ADS)

Köchy, M.; Hiederer, R.; Freibauer, A.

2015-04-01

The global soil organic carbon (SOC) mass is relevant for the carbon cycle budget and thus atmospheric carbon concentrations. We review current estimates of SOC stocks and mass (stock × area) in wetlands, permafrost and tropical regions and the world in the upper 1 m of soil. The Harmonized World Soil Database (HWSD) v.1.2 provides one of the most recent and coherent global data sets of SOC, giving a total mass of 2476 Pg when using the original values for bulk density. Adjusting the HWSD's bulk density (BD) of soil high in organic carbon results in a mass of 1230 Pg, and additionally setting the BD of Histosols to 0.1 g cm-3 (typical of peat soils), results in a mass of 1062 Pg. The uncertainty in BD of Histosols alone introduces a range of -56 to +180 Pg C into the estimate of global SOC mass in the top 1 m, larger than estimates of global soil respiration. We report the spatial distribution of SOC stocks per 0.5 arcminutes; the areal masses of SOC; and the quantiles of SOC stocks by continents, wetland types, and permafrost types. Depending on the definition of "wetland", wetland soils contain between 82 and 158 Pg SOC. With more detailed estimates for permafrost from the Northern Circumpolar Soil Carbon Database (496 Pg SOC) and tropical peatland carbon incorporated, global soils contain 1325 Pg SOC in the upper 1 m, including 421 Pg in tropical soils, whereof 40 Pg occurs in tropical wetlands. Global SOC amounts to just under 3000 Pg when estimates for deeper soil layers are included. Variability in estimates is due to variation in definitions of soil units, differences in soil property databases, scarcity of information about soil carbon at depths > 1 m in peatlands, and variation in definitions of "peatland".

Use of modeled and satelite soil moisture to estimate soil erosion in central and southern Italy.

NASA Astrophysics Data System (ADS)

Termite, Loris Francesco; Massari, Christian; Todisco, Francesca; Brocca, Luca; Ferro, Vito; Bagarello, Vincenzo; Pampalone, Vincenzo; Wagner, Wolfgang

2016-04-01

This study presents an accurate comparison between two different approaches aimed to enhance accuracy of the Universal Soil Loss Equation (USLE) in estimating the soil loss at the single event time scale. Indeed it is well known that including the observed event runoff in the USLE improves its soil loss estimation ability at the event scale. In particular, the USLE-M and USLE-MM models use the observed runoff coefficient to correct the rainfall erosivity factor. In the first case, the soil loss is linearly dependent on rainfall erosivity, in the second case soil loss and erosivity are related by a power law. However, the measurement of the event runoff is not straightforward or, in some cases, possible. For this reason, the first approach used in this study is the use of Soil Moisture For Erosion (SM4E), a recent USLE-derived model in which the event runoff is replaced by the antecedent soil moisture. Three kinds of soil moisture datasets have been separately used: the ERA-Interim/Land reanalysis data of the European Centre for Medium-range Weather Forecasts (ECMWF); satellite retrievals from the European Space Agency - Climate Change Initiative (ESA-CCI); modeled data using a Soil Water Balance Model (SWBM). The second approach is the use of an estimated runoff rather than the observed. Specifically, the Simplified Continuous Rainfall-Runoff Model (SCRRM) is used to derive the runoff estimates. SCRMM requires soil moisture data as input and at this aim the same three soil moisture datasets used for the SM4E have been separately used. All the examined models have been calibrated and tested at the plot scale, using data from the experimental stations for the monitoring of the erosive processes "Masse" (Central Italy) and "Sparacia" (Southern Italy). Climatic data and runoff and soil loss measures at the event time scale are available for the period 2008-2013 at Masse and for the period 2002-2013 at Sparacia. The results show that both the approaches can provide better results than the USLE. Specifically, the SM4E model has proven to be particularly effective at Masse, providing the best soil loss estimations, especially when the modeled soil moisture is used. In this case, the RSR index (ratio between the Root Mean Square Error and the Observed Standard deviation) is equal to 0.94. Instead, the SCRRM is able to better estimate the event runoff at Sparacia than at Masse, thus resulting in good performances of the USLE-derived models using the estimated runoff; however, even at Sparacia the SM4E with modeled soil moisture gives the better soil loss estimates, with RSR = 0.54. These results open an interesting scenario in the use of empirical models to determine soil loss at a large scale, since soil moisture is a not only a simple in situ measurement, but only a widely available information on a global scale from remote sensing.

Estimation of the water retention curve from the soil hydraulic conductivity and sorptivity in an upward infiltration process

NASA Astrophysics Data System (ADS)

Moret-Fernández, David; Angulo, Marta; Latorre, Borja; González-Cebollada, César; López, María Victoria

2017-04-01

Determination of the saturated hydraulic conductivity, Ks, and the α and n parameters of the van Genuchten (1980) water retention curve, θ(h), are fundamental to fully understand and predict soil water distribution. This work presents a new procedure to estimate the soil hydraulic properties from the inverse analysis of a single cumulative upward infiltration curve followed by an overpressure step at the end of the wetting process. Firstly, Ks is calculated by the Darcy's law from the overpressure step. The soil sorptivity (S) is then estimated using the Haverkamp et al., (1994) equation. Next, a relationship between α and n, f(α,n), is calculated from the estimated Sand Ks. The α and n values are finally obtained by the inverse analysis of the experimental data after applying the f(α,n) relationship to the HYDRUS-1D model. The method was validated on theoretical synthetic curves for three different soils (sand, loam and clay), and subsequently tested on experimental sieved soils (sand, loam, clay loam and clay) of known hydraulic properties. A robust relationship was observed between the theoretical α and nvalues (R2 > 0.99) of the different synthetic soils and those estimated from inverse analysis of the upward infiltration curve. Consistent results were also obtained for the experimental soils (R2 > 0.85). These results demonstrated that this technique allowed accurate estimates of the soil hydraulic properties for a wide range of textures, including clay soils.

Soil profile property estimation with field and laboratory VNIR spectroscopy

USDA-ARS?s Scientific Manuscript database

Diffuse reflectance spectroscopy (DRS) soil sensors have the potential to provide rapid, high-resolution estimation of multiple soil properties. Although many studies have focused on laboratory-based visible and near-infrared (VNIR) spectroscopy of dried soil samples, previous work has demonstrated ...

Extrapolating existing soil organic carbon data to estimate soil organic carbon stocks below 20 cm

Treesearch

An-Min Wu; Cinzia Fissore; Charles H. Perry; An-Min Wu; Brent Dalzell; Barry T. Wilson

2015-01-01

Estimates of forest soil organic carbon stocks across the US are currently developed from expert opinion in STATSGO/SSURGO and linked to forest type. The results are reported to the US EPA as the official United States submission to the UN Framework Convention on Climate Change. Beginning in 2015, however, estimates of soil organic carbon (SOC) stocks will be based on...

An empirical method to estimate shear wave velocity of soils in the New Madrid seismic zone

USGS Publications Warehouse

Wei, B.-Z.; Pezeshk, S.; Chang, T.-S.; Hall, K.H.; Liu, Huaibao P.

1996-01-01

In this study, a set of charts are developed to estimate shear wave velocity of soils in the New Madrid seismic zone (NMSZ), using the standard penetration test (SPT) N values and soil depths. Laboratory dynamic test results of soil samples collected from the NMSZ showed that the shear wave velocity of soils is related to the void ratio and the effective confining pressure applied to the soils. The void ratio of soils can be estimated from the SPT N values and the effective confining pressure depends on the depth of soils. Therefore, the shear wave velocity of soils can be estimated from the SPT N value and the soil depth. To make the methodology practical, two corrections should be made. One is that field SPT N values of soils must be adjusted to an unified SPT N??? value to account the effects of overburden pressure and equipment. The second is that the effect of water table to effective overburden pressure of soils must be considered. To verify the methodology, shear wave velocities of five sites in the NMSZ are estimated and compared with those obtained from field measurements. The comparison shows that our approach and the field tests are consistent with an error of less than of 15%. Thus, the method developed in this study is useful for dynamic study and practical designs in the NMSZ region. Copyright ?? 1996 Elsevier Science Limited.

Habitat complexity influences fine scale hydrological processes and the incidence of stormwater runoff in managed urban ecosystems.

PubMed

Ossola, Alessandro; Hahs, Amy Kristin; Livesley, Stephen John

2015-08-15

Urban ecosystems have traditionally been considered to be pervious features of our cities. Their hydrological properties have largely been investigated at the landscape scale and in comparison with other urban land use types. However, hydrological properties can vary at smaller scales depending upon changes in soil, surface litter and vegetation components. Management practices can directly and indirectly affect each of these components and the overall habitat complexity, ultimately affecting hydrological processes. This study aims to investigate the influence that habitat components and habitat complexity have upon key hydrological processes and the implications for urban habitat management. Using a network of urban parks and remnant nature reserves in Melbourne, Australia, replicate plots representing three types of habitat complexity were established: low-complexity parks, high-complexity parks, and high-complexity remnants. Saturated soil hydraulic conductivity in low-complexity parks was an order of magnitude lower than that measured in the more complex habitat types, due to fewer soil macropores. Conversely, soil water holding capacity in low-complexity parks was significantly higher compared to the two more complex habitat types. Low-complexity parks would generate runoff during modest precipitation events, whereas high-complexity parks and remnants would be able to absorb the vast majority of rainfall events without generating runoff. Litter layers on the soil surface would absorb most of precipitation events in high-complexity parks and high-complexity remnants. To minimize the incidence of stormwater runoff from urban ecosystems, land managers could incrementally increase the complexity of habitat patches, by increasing canopy density and volume, preserving surface litter and maintaining soil macropore structure. Copyright © 2015 Elsevier Ltd. All rights reserved.

Technogenic contaminations of the soil-plant cover in the Primorsky Krai, Russia

NASA Astrophysics Data System (ADS)

Molchanova, Inna; Pozolotina, Vera; Mikhailovskaya, Ludmila; Antonova, Elena; Zhuravlev, Yury; Timofeeva, Yana; Burdukovsky, Maxim

2013-04-01

All economical development of the countries carries out monitoring as with the aim to estimate impact of the industrial enterprises and nuclear-energetic complexes as consequences of the nuclear accidents. The investigation the region of the Far East due to proximity to epicentre of accident on Fukushima-1 NPP is of a great interest. The aim of this work are radioecological investigations and estimate technogenic load on the ecosystems of tightly populated plots of the shore zone of the Vladivostok region. Eight plots were located on the investigated territory. The tree fall, forest litters and soils were sampling from the profile cuts of layer by layer, up to 20 cm. The artificial radionuclides (Sr-90 and Cs-134,137), as heavy metals and microelements (Co, Cu, Zn, Pb and Mn) content in the prepared samples was determined. The stock of Sr-90 fluctuates from 0.3 to 1.3 kBq/m2 and Cs-137 was from 0.4 to 3.0 kBq/m2 in the examined soils. On the whole, the level of the radionuclides content in the soil cover is within the limits of the background that was formed in the belt between 50° and 60° of northern latitude. The presence in investigated samples of Cs-134 indicates to contribution of accidental fallout of Fukushima-1 into contamination of the components of the natural ecosystems. In a year's time after the accident the stock of this isotope in the soils was 0.01-0.20 kBq/m^2. It is by factor of 10-100 lower than the stock of Cs-137. Taking into account that the ratio Cs-134/Cs-137 on the moment of accident was equal to unity (1:1). It can be estimated the quantity of Cs-137 entering into environment during post - accident period. This quantity was an average 0.03-0.30 kBq/m2 (with correction on radionuclides decay). The observation for the state of the soil cover includes the estimate of the level and peculiarities of distribution in the soils of heavy metals and microelements. Their content in the soils is formed from Clarke number and additional industrial gas-aerosol fallout. The analysis of a large volume data permitted to calculate the maximal level of the elements content in a soil under influence only natural factors. It was established, that maximal content of Co, Zn, Mn in these soils exceed of their Clarke's numbers. Minimal elements content was found for a tree fall. As a rule, this content is by factor of 10-100 lower than the Clarke values. Maximal concentration is in the soil layer. At the same time the additional technogenic fall-out produces the double increasing of the content of Cu and Pb in the soil layer. For the rest elements the concentrations increased on 8-32%. Acknowledgements. This work was supported by the grant for integrative research between the Ural and Far Eastern Branches of the Russian Academy of Sciences (12-C-4-1001).

Spatial and Temporal Influences on Carbon Storage in Hydric Soils of the Conterminous United States

NASA Astrophysics Data System (ADS)

Sundquist, E. T.; Ackerman, K.; Bliss, N.; Griffin, R.; Waltman, S.; Windham-Myers, L.

2016-12-01

Defined features of hydric soils persist over extensive areas of the conterminous United States (CUS) long after their hydric formation conditions have been altered by historical changes in land and water management. These legacy hydric features may represent previous wetland environments in which soil carbon storage was significantly higher before the influence of human activities. We hypothesize that historical alterations of hydric soil carbon storage can be approximated using carefully selected estimates of carbon storage in currently identified hydric soils. Using the Soil Survey Geographic (SSURGO) database, we evaluate carbon storage in identified hydric soil components that are subject to discrete ranges of current or recent conditions of flooding, ponding, and other indicators of hydric and non-hydric soil associations. We check our evaluations and, where necessary, adjust them using independently published soil data. We compare estimates of soil carbon storage under various hydric and non-hydric conditions within proximal landscapes and similar biophysical settings and ecosystems. By combining these setting- and ecosystem-constrained comparisons with the spatial distribution and attributes of wetlands in the National Wetlands Inventory, we impute carbon storage estimates for soils that occur in current wetlands and for hydric soils that are not associated with current wetlands. Using historical data on land use and water control structures, we map the spatial and temporal distribution of past changes in land and water management that have affected hydric soils. We combine these maps with our imputed carbon storage estimates to calculate ranges of values for historical and present-day carbon storage in hydric soils throughout the CUS. These estimates may provide useful constraints for projections of potential carbon storage in hydric soils under future conditions.

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.

Passive Microwave Remote Sensing of Soil Moisture

NASA Technical Reports Server (NTRS)

Njoku, Eni G.; Entekhabi, Dara

1996-01-01

Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive Microwave soil moisture sensors currently considered for space operation are in the range 10-20 km. The most useful frequency range for soil moisture sensing is 1-5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

Projecting the release of carbon from permafrost soils using a perturbed physics ensemble

NASA Astrophysics Data System (ADS)

MacDougall, A. H.; Knutti, R.

2015-12-01

The soils of the Northern Hemisphere permafrost region are estimated to contain 1100 to 1500 Pg of carbon (Pg C). A substantial fraction of this carbon has been frozen and therefore protected from microbial decay for millennia. As anthropogenic climate warming progresses much of this permafrost is expected to thaw. Here we conduct perturbed physics experiments on a climate model of intermediate complexity, with an improved permafrost carbon module, to estimate with formal uncertainty bounds the release of carbon from permafrost soils by year 2100 and 2300. We estimate that by 2100 the permafrost region may release between 56 (13 to 118) Pg C under Representative Concentration Pathway (RCP) 2.6 and 102 (27 to 199) Pg C under RCP 8.5, with substantially more to be released under each scenario by year 2300. A subset of 25 model variants were projected 8000 years into the future under continued RCP 4.5 and 8.5 forcing. Under the high forcing scenario the permafrost carbon pool decays away over several thousand years. Under the moderate scenario forcing a remnant near-surface permafrost region persists in the high Arctic which develops a large permafrost carbon pool, leading to global recovery of the pool beginning in mid third millennium of the common era (CE). Overall our simulations suggest that the permafrost carbon cycle feedback to climate change will make a significant but not cataclysmic contribution to climate change over the next centuries and millennia.

Effect of climate change on the irrigation and discharge scheme for winter wheat in Huaibei Plain, China

NASA Astrophysics Data System (ADS)

Zhu, Y.; Ren, L.; Lü, H.

2017-12-01

On the Huaibei Plain of Anhui Province, China, winter wheat (WW) is the most prominent crop. The study area belongs to transitional climate, with shallow water table. The original climate change is complex, in addition, global warming make the climate change more complex. The winter wheat growth period is from October to June, just during the rainless season, the WW growth always depends on part of irrigation water. Under such complex climate change, the rainfall varies during the growing seasons, and water table elevations also vary. Thus, water tables supply variable moisture change between soil water and groundwater, which impact the irrigation and discharge scheme for plant growth and yield. In Huaibei plain, the environmental pollution is very serious because of agricultural use of chemical fertilizer, pesticide, herbicide and etc. In order to protect river water and groundwater from pollution, the irrigation and discharge scheme should be estimated accurately. Therefore, determining the irrigation and discharge scheme for winter wheat under climate change is important for the plant growth management decision-making. Based on field observations and local weather data of 2004-2005 and 2005-2006, the numerical model HYDRUS-1D was validated and calibrated by comparing simulated and measured root-zone soil water contents. The validated model was used to estimate the irrigation and discharge scheme in 2010-2090 under the scenarios described by HadCM3 (1970 to 2000 climate states are taken as baselines) with winter wheat growth in an optimum state indicated by growth height and LAI.

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.

Sensible heat balance estimates of transient soil ice contents for freezing and thawing conditions

USDA-ARS?s Scientific Manuscript database

Soil ice content is an important component for winter soil hydrology. The sensible heat balance (SHB) method using measurements from heat pulse probes (HPP) is a possible way to determine transient soil ice content. In a previous study, in situ soil ice contents estimates with the SHB method were in...

Relation between L-band soil emittance and soil water content

NASA Technical Reports Server (NTRS)

Stroosnijder, L.; Lascano, R. J.; Van Bavel, C. H. M.; Newton, R. W.

1986-01-01

An experimental relation between soil emittance (E) at L-band and soil surface moisture content (M) is compared with a theoretical one. The latter depends on the soil dielectric constant, which is a function of both soil moisture content and of soil texture. It appears that a difference of 10 percent in the surface clay content causes a change in the estimate of M on the order of 0.02 cu m/cu m. This is based on calculations with a model that simulates the flow of water and energy, in combination with a radiative transfer model. It is concluded that an experimental determination of the E-M relation for each soil type is not required, and that a rough estimate of the soil texture will lead to a sufficiently accurate estimate of soil moisture from a general, theoretical relationship obtained by numerical simulation.

Measuring the electrical properties of soil using a calibrated ground-coupled GPR system

USGS Publications Warehouse

Oden, C.P.; Olhoeft, G.R.; Wright, D.L.; Powers, M.H.

2008-01-01

Traditional methods for estimating vadose zone soil properties using ground penetrating radar (GPR) include measuring travel time, fitting diffraction hyperbolae, and other methods exploiting geometry. Additional processing techniques for estimating soil properties are possible with properly calibrated GPR systems. Such calibration using ground-coupled antennas must account for the effects of the shallow soil on the antenna's response, because changing soil properties result in a changing antenna response. A prototype GPR system using ground-coupled antennas was calibrated using laboratory measurements and numerical simulations of the GPR components. Two methods for estimating subsurface properties that utilize the calibrated response were developed. First, a new nonlinear inversion algorithm to estimate shallow soil properties under ground-coupled antennas was evaluated. Tests with synthetic data showed that the inversion algorithm is well behaved across the allowed range of soil properties. A preliminary field test gave encouraging results, with estimated soil property uncertainties (????) of ??1.9 and ??4.4 mS/m for the relative dielectric permittivity and the electrical conductivity, respectively. Next, a deconvolution method for estimating the properties of subsurface reflectors with known shapes (e.g., pipes or planar interfaces) was developed. This method uses scattering matrices to account for the response of subsurface reflectors. The deconvolution method was evaluated for use with noisy data using synthetic data. Results indicate that the deconvolution method requires reflected waves with a signal/noise ratio of about 10:1 or greater. When applied to field data with a signal/noise ratio of 2:1, the method was able to estimate the reflection coefficient and relative permittivity, but the large uncertainty in this estimate precluded inversion for conductivity. ?? Soil Science Society of America.

Estimation of soil profile properties using field and laboratory VNIR spectroscopy

USDA-ARS?s Scientific Manuscript database

Diffuse reflectance spectroscopy (DRS) soil sensors have the potential to provide rapid, high-resolution estimation of multiple soil properties. Although many studies have focused on laboratory-based visible and near-infrared (VNIR) spectroscopy of dried soil samples, previous work has demonstrated ...

Estimation of soil-soil solution distribution coefficient of radiostrontium using soil properties.

PubMed

Ishikawa, Nao K; Uchida, Shigeo; Tagami, Keiko

2009-02-01

We propose a new approach for estimation of soil-soil solution distribution coefficient (K(d)) of radiostrontium using some selected soil properties. We used 142 Japanese agricultural soil samples (35 Andosol, 25 Cambisol, 77 Fluvisol, and 5 others) for which Sr-K(d) values had been determined by a batch sorption test and listed in our database. Spearman's rank correlation test was carried out to investigate correlations between Sr-K(d) values and soil properties. Electrical conductivity and water soluble Ca had good correlations with Sr-K(d) values for all soil groups. Then, we found a high correlation between the ratio of exchangeable Ca to Ca concentration in water soluble fraction and Sr-K(d) values with correlation coefficient R=0.72. This pointed us toward a relatively easy way to estimate Sr-K(d) values.

Non-destructive estimates of soil carbonic anhydrase activity and associated soil water oxygen isotope composition

NASA Astrophysics Data System (ADS)

Jones, Sam P.; Ogée, Jérôme; Sauze, Joana; Wohl, Steven; Saavedra, Noelia; Fernández-Prado, Noelia; Maire, Juliette; Launois, Thomas; Bosc, Alexandre; Wingate, Lisa

2017-12-01

The contribution of photosynthesis and soil respiration to net land-atmosphere carbon dioxide (CO2) exchange can be estimated based on the differential influence of leaves and soils on budgets of the oxygen isotope composition (δ18O) of atmospheric CO2. To do so, the activity of carbonic anhydrases (CAs), a group of enzymes that catalyse the hydration of CO2 in soils and plants, needs to be understood. Measurements of soil CA activity typically involve the inversion of models describing the δ18O of CO2 fluxes to solve for the apparent, potentially catalysed, rate of CO2 hydration. This requires information about the δ18O of CO2 in isotopic equilibrium with soil water, typically obtained from destructive, depth-resolved sampling and extraction of soil water. In doing so, an assumption is made about the soil water pool that CO2 interacts with, which may bias estimates of CA activity if incorrect. Furthermore, this can represent a significant challenge in data collection given the potential for spatial and temporal variability in the δ18O of soil water and limited a priori information with respect to the appropriate sampling resolution and depth. We investigated whether we could circumvent this requirement by inferring the rate of CO2 hydration and the δ18O of soil water from the relationship between the δ18O of CO2 fluxes and the δ18O of CO2 at the soil surface measured at different ambient CO2 conditions. This approach was tested through laboratory incubations of air-dried soils that were re-wetted with three waters of different δ18O. Gas exchange measurements were made on these soils to estimate the rate of hydration and the δ18O of soil water, followed by soil water extraction to allow for comparison. Estimated rates of CO2 hydration were 6.8-14.6 times greater than the theoretical uncatalysed rate of hydration, indicating that CA were active in these soils. Importantly, these estimates were not significantly different among water treatments, suggesting that this represents a robust approach to assay the activity of CA in soil. As expected, estimates of the δ18O of the soil water that equilibrates with CO2 varied in response to alteration to the δ18O of soil water. However, these estimates were consistently more negative than the composition of the soil water extracted by cryogenic vacuum distillation at the end of the gas measurements with differences of up to -3.94 ‰ VSMOW-SLAP. These offsets suggest that, at least at lower water contents, CO2-H2O isotope equilibration primarily occurs with water pools that are bound to particle surfaces and are depleted in 18O compared to bulk soil water.

Classification and modelling of non-extractable residue (NER) formation from xenobiotics in soil - a synthesis

NASA Astrophysics Data System (ADS)

Kaestner, Matthias; Nowak, Karolina; Miltner, Anja; Trapp, Stefan; Schaeffer, Andreas

2014-05-01

This presentation provides a comprehensive overview about the formation of non-extractable residues (NER) from organic pesticides and contaminants in soil and tries classifying the different types. Anthropogenic organic chemicals are deliberately (e.g. pesticides) or unintentionally (e.g. polyaromatic hydrocarbons [PAH], chlorinated solvents, pharmaceuticals) released in major amounts to nearly all compartments of the environment. Soils and sediments as complex matrices provide a wide variety of binding sites and are the major sinks for these compounds. Many of the xenobiotics entering soil undergo turnover processes and can be volatilised, leached to the groundwater, degraded by microorganisms or taken up and enriched by living organisms. Xenobiotic NER may be derived from parent compounds and primary metabolites that are sequestered (sorbed or entrapped) within the soil organic matter (type I NER) or can be covalently bound (type II NER). Especially type I NER may pose a considerably environmental risk of potential release. However, NER resulting from productive biodegradation, which means the conversion of carbon (or nitrogen) from the compounds into microbial biomass molecules during microbial degradation (type III, bioNER), do not pose any risk. Experimental and analytical approaches to clearly distinguish between the types are provided and a model to prospectively estimate their fate in soil is proposed.

Solid-phase cadmium speciation in soil using L3-edge XANES spectroscopy with partial least-squares regression.

PubMed

Siebers, Nina; Kruse, Jens; Eckhardt, Kai-Uwe; Hu, Yongfeng; Leinweber, Peter

2012-07-01

Cadmium (Cd) has a high toxicity and resolving its speciation in soil is challenging but essential for estimating the environmental risk. In this study partial least-square (PLS) regression was tested for its capability to deconvolute Cd L(3)-edge X-ray absorption near-edge structure (XANES) spectra of multi-compound mixtures. For this, a library of Cd reference compound spectra and a spectrum of a soil sample were acquired. A good coefficient of determination (R(2)) of Cd compounds in mixtures was obtained for the PLS model using binary and ternary mixtures of various Cd reference compounds proving the validity of this approach. In order to describe complex systems like soil, multi-compound mixtures of a variety of Cd compounds must be included in the PLS model. The obtained PLS regression model was then applied to a highly Cd-contaminated soil revealing Cd(3)(PO(4))(2) (36.1%), Cd(NO(3))(2)·4H(2)O (24.5%), Cd(OH)(2) (21.7%), CdCO(3) (17.1%) and CdCl(2) (0.4%). These preliminary results proved that PLS regression is a promising approach for a direct determination of Cd speciation in the solid phase of a soil sample.

Methodology for estimating soil carbon for the forest carbon budget model of the United States, 2001

Treesearch

L. S. Heath; R. A. Birdsey; D. W. Williams

2002-01-01

The largest carbon (C) pool in United States forests is the soil C pool. We present methodology and soil C pool estimates used in the FORCARB model, which estimates and projects forest carbon budgets for the United States. The methodology balances knowledge, uncertainties, and ease of use. The estimates are calculated using the USDA Natural Resources Conservation...

[Estimation of organic matter content of north fluvo-aquic soil based on the coupling model of wavelet transform and partial least squares].

PubMed

Wang, Yan-Cang; Yang, Gui-Jun; Zhu, Jin-Shan; Gu, Xiao-He; Xu, Peng; Liao, Qin-Hong

2014-07-01

For improving the estimation accuracy of soil organic matter content of the north fluvo-aquic soil, wavelet transform technology is introduced. The soil samples were collected from Tongzhou district and Shunyi district in Beijing city. And the data source is from soil hyperspectral data obtained under laboratory condition. First, discrete wavelet transform efficiently decomposes hyperspectral into approximate coefficients and detail coefficients. Then, the correlation between approximate coefficients, detail coefficients and organic matter content was analyzed, and the sensitive bands of the organic matter were screened. Finally, models were established to estimate the soil organic content by using the partial least squares regression (PLSR). Results show that the NIR bands made more contributions than the visible band in estimating organic matter content models; the ability of approximate coefficients to estimate organic matter content is better than that of detail coefficients; The estimation precision of the detail coefficients fir soil organic matter content decreases with the spectral resolution being lower; Compared with the commonly used three types of soil spectral reflectance transforms, the wavelet transform can improve the estimation ability of soil spectral fir organic content; The accuracy of the best model established by the approximate coefficients or detail coefficients is higher, and the coefficient of determination (R2) and the root mean square error (RMSE) of the best model for approximate coefficients are 0.722 and 0.221, respectively. The R2 and RMSE of the best model for detail coefficients are 0.670 and 0.255, respectively.

Neural Network-Based Retrieval of Surface and Root Zone Soil Moisture using Multi-Frequency Remotely-Sensed Observations

NASA Astrophysics Data System (ADS)

Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre

2017-04-01

Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.

Long-term monitoring of temperature in the subsoil using Fiber Optic Distributed Sensing

NASA Astrophysics Data System (ADS)

Susanto, Kusnahadi; Malet, Jean-Philippe; Gance, Julien; Marc, Vincent

2017-04-01

Monitoring changes in soil water content in the vadose zone of soils is a great importance for various hydrological, agronomical, ecological and environmental studies. By using soil temperature measurements with Fiber-Optic Distributed Temperature Sensing (FO-DTS), we can indirectly document soil water changes at high spatial and temporal frequency. In this research, we installed an observatory of soil temperature on a representative black marl slope of the long-term Draix-Bléone hydrological observatory (South French Alps, Réseau de Basins-Versants / RBV). A 350 m long reinforced fiber optic cable was buried at 0.05, 0.10 and 0.15 m of depths and installed at the soil surface. The total length of the monitored profile is 60 m, and it three different soil units consisting of argillaceous weathered black marls, silty colluvium under grass and silty colluvium under forest. Soil temperature is measured every 6 minutes at a spatial resolution of 0.50 m using a double-ended configuration. Both passive and active (heating of the FO) is used to document soil water changes. We present the analysis of a period of 6 months of temperature measurements (January-July 2016). Changes in soil temperature at various temporal scales (rainfall event, season) and for the three units are discussed. These changes indicate different processes of water infiltration at different velocities in relation to the presence of roots and the soil permeability. We further test several inversion strategies to estimate soil water content from the thermal diffusivity of the soils using simple and more complex thermal models. Some limitations of using this indirect technique for long-term monitoring are also presented. The work is supported by the research project HYDROSLIDE and the large infrastructure project CRITEX funded by the French Research Agency (ANR).

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.

Establishing a tracer-based sediment budget to preserve wetlands in Mediterranean mountain agroecosystems (NE Spain).

PubMed

Navas, Ana; López-Vicente, Manuel; Gaspar, Leticia; Palazón, Leticia; Quijano, Laura

2014-10-15

Mountain wetlands in Mediterranean regions are particularly threatened in agricultural environments due to anthropogenic activity. An integrated study of source-to-sink sediment fluxes was carried out in an agricultural catchment that holds a small permanent lake included in the European NATURA 2000 Network. More than 1000 yrs of human intervention and the variety of land uses pose a substantial challenge when attempting to estimate sediment fluxes which is the first requirement to protect fragile wetlands. To date, there have been few similar studies and those that have been carried out have not addressed such complex terrain. Geostatistical interpolation and GIS tools were used to derive the soil spatial redistribution from point (137)Cs inventories, and to establish the sediment budget in a catchment located in the Southern Pyrenees. The soil redistribution was intense and soil erosion predominated over soil deposition. On the areas that maintained natural vegetation the median soil erosion and deposition rates were moderate, ranging from 2.6 to 6 Mg ha yr(-1) and 1.5 to 2.1 Mg ha yr(-1), respectively. However, in cultivated fields both erosion and deposition were significantly higher (ca. 20 Mg ha yr(-1)), and the maximum rates were always associated with tillage practices. Farming activities in the last part of the 20th century intensified soil erosion, as evidenced by the 1963 (137)Cs peaks in the lake cores and estimates from the sediment budget indicated a net deposition of 671 Mg yr(-1). Results confirm a siltation risk for the lake and provide a foundation for designing management plans to preserve this threatened wetland. This comprehensive approach provides information useful for understanding processes that influence the patterns and rates of soil transfer and deposition within fragile Mediterranean mountain wetlands subjected to climate and anthropogenic stresses. Copyright © 2014 Elsevier B.V. All rights reserved.

Fire intensity drives post-fire temporal pattern of soil carbon accumulation in Australian fire-prone forests.

PubMed

Sawyer, Robert; Bradstock, Ross; Bedward, Michael; Morrison, R John

2018-01-01

The impact of fire on global C cycles is considerable but complex. Nevertheless, studies on patterns of soil C accumulation following fires of differing intensity over time are lacking. Our study utilised 15 locations last burnt by prescribed fire (inferred low intensity) and 18 locations last burnt by wildfire (inferred high intensity), with time since fire (TSF) up to 43years, in a homogenous forest type in south eastern Australia. Following a stratified approach to mineral soil sampling, the soil % total C (% C Tot ) and % recalcitrant pyrogenic C (% RPC), were estimated. Generalised additive models indicated increases in % C Tot at TSF >30years in sites last burnt by wildfire. Estimates in sites last subjected to prescribed fire however, remained constant across the TSF chronosequence. There was no significant difference in % C Tot between the different fire types for the first 20years after fire. In the first 10years after wildfires, % RPC was elevated, declining to a minimum at ca. TSF 25years. After prescribed fires, % RPC was unaffected by TSF. Differences in response of % C Tot and % RPC to fire type may reflect the strength of stimulation of early successional processes and extent of charring. The divergent response to fire type in % C Tot was apparent at TSF longer than the landscape average fire return interval (i.e., 15 to 20years). Thus, any attempt to increase C sequestration in soils would require long-term exclusion of fire. Conversely, increased fire frequency is likely to have negligible impact on soil C stocks in these forests. Further investigation of the effects of fire frequency, fire intensity combinations and interaction of fire with other disturbances will enhance prediction of the likely impact of imposed or climatically induced changes to fire regimes on soil C. Copyright © 2017 Elsevier B.V. All rights reserved.

Modelling pesticide volatilization after soil application using the mechanistic model Volt'Air

NASA Astrophysics Data System (ADS)

Bedos, Carole; Génermont, Sophie; Le Cadre, Edith; Garcia, Lucas; Barriuso, Enrique; Cellier, Pierre

Volatilization of pesticides participates in atmospheric contamination and affects environmental ecosystems including human welfare. Modelling at relevant time and spatial scales is needed to better understand the complex processes involved in pesticide volatilization. Volt'Air-Pesticides has been developed following a two-step procedure to study pesticide volatilization at the field scale and at a quarter time step. Firstly, Volt'Air-NH 3 was adapted by extending the initial transfer of solutes to pesticides and by adding specific calculations for physico-chemical equilibriums as well as for the degradation of pesticides in soil. Secondly, the model was evaluated in terms of 3 pesticides applied on bare soil (atrazine, alachlor, and trifluralin) which display a wide range of volatilization rates. A sensitivity analysis confirmed the relevance of tuning to K h. Then, using Volt'Air-Pesticides, environmental conditions and emission fluxes of the pesticides were compared to fluxes measured under 2 environmental conditions. The model fairly well described water temporal dynamics, soil surface temperature, and energy budget. Overall, Volt'Air-Pesticides estimates of the order of magnitude of the volatilization flux of all three compounds were in good agreement with the field measurements. The model also satisfactorily simulated the decrease in the volatilization rate of the three pesticides during night-time as well as the decrease in the soil surface residue of trifluralin before and after incorporation. However, the timing of the maximum flux rate during the day was not correctly described, thought to be linked to an increased adsorption under dry soil conditions. Thanks to Volt'Air's capacity to deal with pedo-climatic conditions, several existing parameterizations describing adsorption as a function of soil water content could be tested. However, this point requires further investigation. Practically speaking, Volt'Air-Pesticides can be a useful tool to make decision about agricultural practices such as incorporation or for the estimation of overall pesticide volatilization rates, and it holds promise for time specific dynamics.

Spatiotemporal variability of water and energy fluxes: TERENO- prealpine hydrometeorological data analysis and inverse modeling with GEOtop and PEST

NASA Astrophysics Data System (ADS)

Soltani, M.; Kunstmann, H.; Laux, P.; Mauder, M.

2016-12-01

In mountainous and prealpine regions echohydrological processes exhibit rapid changes within short distances due to the complex orography and strong elevation gradients. Water- and energy fluxes between the land surface and the atmosphere are crucial drivers for nearly all ecosystem processes. The aim of this research is to analyze the variability of surface water- and energy fluxes by both comprehensive observational hydrometeorological data analysis and process-based high resolution hydrological modeling for a mountainous and prealpine region in Germany. We particularly focus on the closure of the observed energy balance and on the added value of energy flux observations for parameter estimation in our hydrological model (GEOtop) by inverse modeling using PEST. Our study area is the catchment of the river Rott (55 km2), being part of the TERENO prealpine observatory in Southern Germany, and we focus particularly on the observations during the summer episode May to July 2013. We present the coupling of GEOtop and the parameter estimation tool PEST, which is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. Estimation of the surface energy partitioning during the data analysis process revealed that the latent heat flux was considered as the main consumer of available energy. The relative imbalance was largest during nocturnal periods. An energy imbalance was observed at the eddy-covariance site Fendt due to either underestimated turbulent fluxes or overestimated available energy. The calculation of the simulated energy and water balances for the entire catchment indicated that 78% of net radiation leaves the catchment as latent heat flux, 17% as sensible heat, and 5% enters the soil in the form of soil heat flux. 45% of the catchment aggregated precipitation leaves the catchment as discharge and 55% as evaporation. Using the developed GEOtop-PEST interface, the hydrological model is calibrated by comparing simulated and observed discharge, soil moisture and -temperature, sensible-, latent-, and soil heat fluxes. A reasonable quality of fit could be achieved. Uncertainty- and covariance analyses are performed, allowing the derivation of confidence intervals for all estimated parameters.

BOREAS TGB-12 Soil Carbon and Flux Data of NSA-MSA in Raster Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David E. (Editor); Rapalee, Gloria; Davidson, Eric; Harden, Jennifer W.; Trumbore, Susan E.; Veldhuis, Hugo

2000-01-01

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites. This data set provides: (1) estimates of soil carbon stocks by horizon based on soil survey data and analyses of data from individual soil profiles; (2) estimates of soil carbon fluxes based on stocks, fire history, drain-age, and soil carbon inputs and decomposition constants based on field work using radiocarbon analyses; (3) fire history data estimating age ranges of time since last fire; and (4) a raster image and an associated soils table file from which area-weighted maps of soil carbon and fluxes and fire history may be generated. This data set was created from raster files, soil polygon data files, and detailed lab analysis of soils data that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. Also used were soils data from Susan Trumbore and Jennifer Harden (BOREAS TGB-12). The binary raster file covers a 733-km 2 area within the NSA-MSA.

A new estimation of global soil greenhouse gas fluxes using a simple data-oriented model.

PubMed

Hashimoto, Shoji

2012-01-01

Soil greenhouse gas fluxes (particularly CO(2), CH(4), and N(2)O) play important roles in climate change. However, despite the importance of these soil greenhouse gases, the number of reports on global soil greenhouse gas fluxes is limited. Here, new estimates are presented for global soil CO(2) emission (total soil respiration), CH(4) uptake, and N(2)O emission fluxes, using a simple data-oriented model. The estimated global fluxes for CO(2) emission, CH(4) uptake, and N(2)O emission were 78 Pg C yr(-1) (Monte Carlo 95% confidence interval, 64-95 Pg C yr(-1)), 18 Tg C yr(-1) (11-23 Tg C yr(-1)), and 4.4 Tg N yr(-1) (1.4-11.1 Tg N yr(-1)), respectively. Tropical regions were the largest contributor of all of the gases, particularly the CO(2) and N(2)O fluxes. The soil CO(2) and N(2)O fluxes had more pronounced seasonal patterns than the soil CH(4) flux. The collected estimates, including both the previous and the present estimates, demonstrate that the means of the best estimates from each study were 79 Pg C yr(-1) (291 Pg CO(2) yr(-1); coefficient of variation, CV = 13%, N = 6) for CO(2), 21 Tg C yr(-1) (29 Tg CH(4) yr(-1); CV = 24%, N = 24) for CH(4), and 7.8 Tg N yr(-1) (12.2 Tg N(2)O yr(-1); CV = 38%, N = 11) for N(2)O. For N(2)O, the mean of the estimates that was calculated by excluding the earliest two estimates was 6.6 Tg N yr(-1) (10.4 Tg N(2)O yr(-1); CV = 22%, N = 9). The reported estimates vary and have large degrees of uncertainty but their overall magnitudes are in general agreement. To further minimize the uncertainty of soil greenhouse gas flux estimates, it is necessary to build global databases and identify key processes in describing global soil greenhouse gas fluxes.

A New Estimation of Global Soil Greenhouse Gas Fluxes Using a Simple Data-Oriented Model

PubMed Central

Hashimoto, Shoji

2012-01-01

Soil greenhouse gas fluxes (particularly CO2, CH4, and N2O) play important roles in climate change. However, despite the importance of these soil greenhouse gases, the number of reports on global soil greenhouse gas fluxes is limited. Here, new estimates are presented for global soil CO2 emission (total soil respiration), CH4 uptake, and N2O emission fluxes, using a simple data-oriented model. The estimated global fluxes for CO2 emission, CH4 uptake, and N2O emission were 78 Pg C yr−1 (Monte Carlo 95% confidence interval, 64–95 Pg C yr−1), 18 Tg C yr−1 (11–23 Tg C yr−1), and 4.4 Tg N yr−1 (1.4–11.1 Tg N yr−1), respectively. Tropical regions were the largest contributor of all of the gases, particularly the CO2 and N2O fluxes. The soil CO2 and N2O fluxes had more pronounced seasonal patterns than the soil CH4 flux. The collected estimates, including both the previous and the present estimates, demonstrate that the means of the best estimates from each study were 79 Pg C yr−1 (291 Pg CO2 yr−1; coefficient of variation, CV = 13%, N = 6) for CO2, 21 Tg C yr−1 (29 Tg CH4 yr−1; CV = 24%, N = 24) for CH4, and 7.8 Tg N yr−1 (12.2 Tg N2O yr−1; CV = 38%, N = 11) for N2O. For N2O, the mean of the estimates that was calculated by excluding the earliest two estimates was 6.6 Tg N yr−1 (10.4 Tg N2O yr−1; CV = 22%, N = 9). The reported estimates vary and have large degrees of uncertainty but their overall magnitudes are in general agreement. To further minimize the uncertainty of soil greenhouse gas flux estimates, it is necessary to build global databases and identify key processes in describing global soil greenhouse gas fluxes. PMID:22876295

A statistical method for estimating rates of soil development and ages of geologic deposits: A design for soil-chronosequence studies

USGS Publications Warehouse

Switzer, P.; Harden, J.W.; Mark, R.K.

1988-01-01

A statistical method for estimating rates of soil development in a given region based on calibration from a series of dated soils is used to estimate ages of soils in the same region that are not dated directly. The method is designed specifically to account for sampling procedures and uncertainties that are inherent in soil studies. Soil variation and measurement error, uncertainties in calibration dates and their relation to the age of the soil, and the limited number of dated soils are all considered. Maximum likelihood (ML) is employed to estimate a parametric linear calibration curve, relating soil development to time or age on suitably transformed scales. Soil variation on a geomorphic surface of a certain age is characterized by replicate sampling of soils on each surface; such variation is assumed to have a Gaussian distribution. The age of a geomorphic surface is described by older and younger bounds. This technique allows age uncertainty to be characterized by either a Gaussian distribution or by a triangular distribution using minimum, best-estimate, and maximum ages. The calibration curve is taken to be linear after suitable (in certain cases logarithmic) transformations, if required, of the soil parameter and age variables. Soil variability, measurement error, and departures from linearity are described in a combined fashion using Gaussian distributions with variances particular to each sampled geomorphic surface and the number of sample replicates. Uncertainty in age of a geomorphic surface used for calibration is described using three parameters by one of two methods. In the first method, upper and lower ages are specified together with a coverage probability; this specification is converted to a Gaussian distribution with the appropriate mean and variance. In the second method, "absolute" older and younger ages are specified together with a most probable age; this specification is converted to an asymmetric triangular distribution with mode at the most probable age. The statistical variability of the ML-estimated calibration curve is assessed by a Monte Carlo method in which simulated data sets repeatedly are drawn from the distributional specification; calibration parameters are reestimated for each such simulation in order to assess their statistical variability. Several examples are used for illustration. The age of undated soils in a related setting may be estimated from the soil data using the fitted calibration curve. A second simulation to assess age estimate variability is described and applied to the examples. ?? 1988 International Association for Mathematical Geology.

Geometric factor and influence of sensors in the establishment of a resistivity-moisture relation in soil samples

NASA Astrophysics Data System (ADS)

López-Sánchez, M.; Mansilla-Plaza, L.; Sánchez-de-laOrden, M.

2017-10-01

Prior to field scale research, soil samples are analysed on a laboratory scale for electrical resistivity calibrations. Currently, there are a variety of field instruments to estimate the water content in soils using different physical phenomena. These instruments can be used to develop moisture-resistivity relationships on the same soil samples. This assures that measurements are performed on the same material and under the same conditions (e.g., humidity and temperature). A geometric factor is applied to the location of electrodes, in order to calculate the apparent electrical resistivity of the laboratory test cells. This geometric factor can be determined in three different ways: by means of the use of an analytical approximation, laboratory trials (experimental approximation), or by the analysis of a numerical model. The first case, the analytical approximation, is not appropriate for complex cells or arrays. And both, the experimental and numerical approximation can lead to inaccurate results. Therefore, we propose a novel approach to obtain a compromise solution between both techniques, providing a more precise determination of the geometrical factor.

Infiltration into soils: Conceptual approaches and solutions

NASA Astrophysics Data System (ADS)

Assouline, Shmuel

2013-04-01

Infiltration is a key process in aspects of hydrology, agricultural and civil engineering, irrigation design, and soil and water conservation. It is complex, depending on soil and rainfall properties and initial and boundary conditions within the flow domain. During the last century, a great deal of effort has been invested to understand the physics of infiltration and to develop quantitative predictors of infiltration dynamics. Jean-Yves Parlange and Wilfried Brutsaert have made seminal contributions, especially in the area of infiltration theory and related analytical solutions to the flow equations. This review retraces the landmark discoveries and the evolution of the conceptual approaches and the mathematical solutions applied to the problem of infiltration into porous media, highlighting the pivotal contributions of Parlange and Brutsaert. A historical retrospective of physical models of infiltration is followed by the presentation of mathematical methods leading to analytical solutions of the flow equations. This review then addresses the time compression approximation developed to estimate infiltration at the transition between preponding and postponding conditions. Finally, the effects of special conditions, such as the presence of air and heterogeneity in soil properties, on infiltration are considered.

Deposition parameterizations for the Industrial Source Complex (ISC3) model

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

Wesely, Marvin L.; Doskey, Paul V.; Shannon, J. D.

2002-06-01

Improved algorithms have been developed to simulate the dry and wet deposition of hazardous air pollutants (HAPs) with the Industrial Source Complex version 3 (ISC3) model system. The dry deposition velocities (concentrations divided by downward flux at a specified height) of the gaseous HAPs are modeled with algorithms adapted from existing dry deposition modules. The dry deposition velocities are described in a conventional resistance scheme, for which micrometeorological formulas are applied to describe the aerodynamic resistances above the surface. Pathways to uptake at the ground and in vegetative canopies are depicted with several resistances that are affected by variations inmore » air temperature, humidity, solar irradiance, and soil moisture. The role of soil moisture variations in affecting the uptake of gases through vegetative plant leaf stomata is assessed with the relative available soil moisture, which is estimated with a rudimentary budget of soil moisture content. Some of the procedures and equations are simplified to be commensurate with the type and extent of information on atmospheric and surface conditions available to the ISC3 model system user. For example, standardized land use types and seasonal categories provide sets of resistances to uptake by various components of the surface. To describe the dry deposition of the large number of gaseous organic HAPS, a new technique based on laboratory study results and theoretical considerations has been developed providing a means of evaluating the role of lipid solubility in uptake by the waxy outer cuticle of vegetative plant leaves.« less

Determination of the distribution coefficient (log Kd) of oxytetracycline, tylosin A, olaquindox and metronidazole in manure.

PubMed

Loke, Marie-Louise; Tjørnelund, Jette; Halling-Sørensen, Bent

2002-07-01

Olaquindox (log Kow = -2.3) and metronidazole (log Kow = -0.1) both have low tendencies to sorp to particles in manure. This corresponds with the negative log Kow values of these antibiotics. Tylosin (log Kow = 1.63) and oxytetracycline (log Kow = -1.12) sorp relatively strongly to the manure particles and have log Kd values between 1.5 and 2.0. The tendency to bind to manure was ranked after increasing binding as follows: metronidazole < olaquindox < tylosin A and oxytetracycline. This order of ranking is consistent with results of sorption in soil. Our experiments illustrate that for some antibacterial agents estimation of the partitioning coefficients, Kd, cannot be made from Kow and f(oc) alone. Sorption of oxytetracycline to manure is much higher than expected from the negative log Kow value of the compound. It is believed that sorption of oxytetracycline to manure is influenced by ionic binding to divalent metal ions as such Mg2+ and Ca2+ as well as other charged compounds in the matrix. Binding of oxytetracycline to soil is stronger than the binding to manure. This is most likely due to the strong mineral related metal complexes formed between soil, metal ion and oxytetracycline. These complexes are not known to exist in manure. The relatively strong sorption of tylosin A to manure corresponds with data found for soil sorption of tylosin. Tylosin has a log Kow value of 2.5, thus it is not surprising that this drug binds strongly to manure.

An Isotopic Exchange Kinetic Model to Assess the Speciation of Metal Available Pool in Soil: The Case of Nickel.

PubMed

Zelano, I O; Sivry, Y; Quantin, C; Gélabert, A; Maury, A; Phalyvong, K; Benedetti, M F

2016-12-06

In this study an innovative approach is proposed to predict the relative contribution of each mineral phase to the total metal availability in soils, which, in other words, could be called the available metal fractionation. Through the use of isotopic exchange kinetics (IEK) performed on typical Ni bearing phases (i.e., two types of serpentines, chlorite, smectite, goethite, and hematite) the isotopic exchange and metal-solid interaction processes are connected, considering both the thermodynamic and kinetic aspects. Results of Ni IEK experiments on mineral phases are fitted with a pseudo-first order kinetic model. For each Ni bearing phase, this allows to (i) determine the number and size of exchangeable pools (E Ni(i) ), (ii) assess their corresponding kinetic constants (k (i) ), and (iii) discuss the mechanism of Ni isotopic exchange at mineral surfaces. It is shown that all the phases investigated, with the only exception of hematite, present at least two distinct reactive pools with significantly different k (i) values. Results suggest also that metal involved in outer-sphere complexes would display isotopic exchange between 100 and 1000 times faster than metal involved in inner-sphere complexes, and that the presence of high and low affinity sites may influence the rate of isotopic exchange up to 1 order of magnitude. Moreover, the method developed represents a tool to predict and estimate Ni mobility and availability in natural soil samples on the basis of soil mineral composition, providing information barely obtained with other techniques.

A Method for a Multi-Platform Approach to Generate Gridded Surface Evaporation

NASA Astrophysics Data System (ADS)

Badger, A.; Livneh, B.; Small, E. E.; Abolafia-Rosenzweig, R.

2017-12-01

Evapotranspiration is an integral component of the surface water balance. While there are many estimates of evapotranspiration, there are fewer estimates that partition evapotranspiration into evaporation and transpiration components. This study aims to generate a CONUS-scale, observationally-based soil evaporation dataset by using the time difference of surface soil moisture by Soil Moisture Active Passive (SMAP) satellite with adjustments for transpiration and a bottom flux out of the surface layer. In concert with SMAP, the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite, North American Land Data Assimilation Systems (NLDAS) and the Hydrus-1D model are used to fully analyze the surface water balance. A biome specific estimate of the total terrestrial ET is calculated through a variation of the Penman-Monteith equation with NLDAS forcing and NLDAS Noah Model output for meteorological variables. A root density restriction and SMAP-based soil moisture restriction are applied to obtain terrestrial transpiration estimates. By forcing Hydrus-1D with NLDAS meteorology and our terrestrial transpiration estimates, an estimate of the flux between the soil surface and root zone layers (qbot) will dictate the proportion of water that is available for soil evaporation. After constraining transpiration and the bottom flux from the surface layer, we estimate soil evaporation as the residual of the surface water balance. Application of this method at Fluxnet sites shows soil evaporation estimates of approximately 0­3 mm/day and less than ET estimates. Expanding this methodology to produce a gridded product for CONUS, and eventually a global-scale product, will enable a better understanding of water balance processes and contribute a dataset to validate land-surface model's surface flux processes.

The assessment of spatial distribution of soil salinity risk using neural network.

PubMed

Akramkhanov, Akmal; Vlek, Paul L G

2012-04-01

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.

Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

NASA Astrophysics Data System (ADS)

Legates, David R.; Junghenn, Katherine T.

2018-04-01

Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.

Linking Annual N2O Emission in Organic Soils to Mineral Nitrogen Input as Estimated by Heterotrophic Respiration and Soil C/N Ratio

PubMed Central

Mu, Zhijian; Huang, Aiying; Ni, Jiupai; Xie, Deti

2014-01-01

Organic soils are an important source of N2O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N2O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO2 flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO2 and N2O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N2O fluxes, whereas CO2 flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N2O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N2O flux. Our proposed approach, which uses the product of soil-derived CO2 flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N2O fluxes from organic soils, although some further enhancements may be warranted. PMID:24798347

Calibrating a Soil-Vegetation-Atmosphere system with a genetical algorithm

NASA Astrophysics Data System (ADS)

Schneider, S.; Jacques, D.; Mallants, D.

2009-04-01

Accuracy of model prediction is well known for being very sensitive to the quality of the calibration of the model. It is also known that quantifying soil hydraulic parameters in a Soil-Vegetation-Atmosphere (SVA) system is a highly non-linear parameter estimation problem, and that robust methods are needed to avoid the optimization process to lead to non-optimal parameters. Evolutionary algorithms and specifically genetic algorithms (GAs) are very well suited for those complex parameter optimization problems. The SVA system in this study concerns a pine stand on a heterogeneous sandy soil (podzol) in the north of Belgium (Campine region). Throughfall and other meteorological data and water contents at different soil depths have been recorded during one year at a daily time step. The water table level, which is varying between 95 and 170 cm, has been recorded with a frequency of 0.5 hours. Based on the profile description, four soil layers have been distinguished in the podzol and used for the numerical simulation with the hydrus1D model (Simunek and al., 2005). For the inversion procedure the MYGA program (Yedder, 2002), which is an elitism GA, was used. Optimization was based on the water content measurements realized at the depths of 10, 20, 40, 50, 60, 70, 90, 110, and 120 cm to estimate parameters describing the unsaturated hydraulic soil properties of the different soil layers. Comparison between the modeled and measured water contents shows a good similarity during the simulated year. Impacts of short and intensive events (rainfall) on the water content of the soil are also well reproduced. Errors on predictions are on average equal to 5%, which is considered as a good result. A. Ben Haj Yedder. Numerical optimization and optimal control : (molecular chemistry applications). PhD thesis, Ecole Nationale des Ponts et Chaussées, 2002. Šimůnek, J., M. Th. van Genuchten, and M. Šejna, The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat, and multiple solutes in variably saturated media. Version 3.0, HYDRUS Software Series 1, Department of Environmental Sciences, University of California Riverside, Riverside, CA, 270 pp., 2005.

Modern soil system constraints on reconstructing deep-time atmospheric CO2

NASA Astrophysics Data System (ADS)

Montañez, Isabel P.

2013-01-01

Paleosol carbonate-based estimates of paleo-atmospheric CO2 play a prominent role in constraining radiative-forcing and climate sensitivity in the deep-time. Large uncertainty in paleo-CO2 estimates made using the paleosol-carbonate CO2-barometer, however, arises primarily from their sensitivity to soil-respired CO2 (S(z)). This parameter is poorly constrained due to a paucity of soil CO2 measurements during carbonate formation in modern soils and a lack of widely applicable proxies of paleo-soil CO2. Here the δ13C values of carbonate and soil organic matter (SOM) pairs from 130 Holocene soils are applied to a two-component CO2-mixing equation to define soil order-specific ranges of soil CO2 applicable for constraining S(z) in their corresponding paleosol analogs. Equilibrium carbonate-SOM pairs, characterized by Δ13Ccarb-SOM values of 12.2-15.8‰, define a mean effective fractionation of 14.1‰ and overall inferred total soil CO2 contents during calcite formation of <1000-10,000 ppmv. For those Aridisols and Alfisols, characterized by a net soil-moisture deficit, and their paleosol analogs (Calcisols and Argillisols), a best estimate of S(z) during calcite formation is 1500-2000 ppmv (range of 500-2500 ppmv). Overall higher values (2000-5000 ppmv) are indicated by the subset of these soils characterized by higher moisture content and productivity. Near atmospheric levels (400 ± 200 ppmv) of estimated S(z) are indicated by immature soils, recording their low soil productivity. Vertisols define the largest range in total soil CO2 (<1000 to >25,000 ppmv) reflecting their seasonally driven dynamic hydrochemistry. A S(z) range of 1000-10,000 ppmv is suggested for paleo-Vertisols for which calcite precipitation can be constrained to have occurred in an open system with two-component CO2 mixing, with a best estimate of 2000 ppmv ± 1000 ppmv appropriate for paleo-Vertisols for which evidence of protracted water saturation is lacking. Mollisol pairs define a best estimate of S(z) of 2500 ppmv (range of 600-4000 ppmv) for late Cretaceous and Cenozoic analogs. Non-equilibrium pairs with Δ13C values >16‰ make up 51% of the dataset, lending support to the hypothesis that pedogenic carbonate precipitation occurs during periods of low productivity in a soil atmosphere with a large component of atmospheric CO2. Predictable scaling between estimated soil CO2 and the difference in δ13C between measured pedogenic carbonate and that predicted to have formed from soil-respired CO2 (inferred from measured SOM) can be used to further constrain appropriate ranges of S(z) for reconstruction of paleo-atmospheric pCO2. Soil CO2 estimates are poorly correlated to mean annual precipitation likely reflecting that for carbonate-bearing soils, where moisture limits CO2 production, total soil CO2 is most strongly influenced by actual evapotranspiration.

a Review of Late Holocene Fluvial Systems in the Karst Maya Lowlands with Focus on the Rio Bravo, Belize

NASA Astrophysics Data System (ADS)

Beach, T.; Luzzadder-Beach, S.; Krause, S.; Doyle, C.

2015-12-01

The Maya Lowlands is mostly an internally draining karst region with about 400 m of regional relief. Fluvial and fluviokarst systems drain the edges of this landscape either from low limestone uplands or igneous and metamorphic complexes. Thus far most fluvial research has focused around archaeology projects, and here we review the extant research conducted across the region and new research on the transboundary Rio Bravo watershed of Belize and Guatemala. The Rio Bravo drains a largely old growth tropical forest today, but was partly deforested around ancient Maya cities and farms from 3,000 to 1000 BP. Several studies estimate that 30 to 40 percent of forest survived through the Maya period. Work here has focused on soils and sediment movement along slope catenas, in floodplain sites, and on contributions from groundwater with high dissolved loads of sulfate and calcium. We review radiocarbon dates and present new dates and soil stratigraphy from these sequences to date slope and floodplain movement, and we estimate ancient land use from carbon isotopic and pollen evidence. Aggradation in this watershed occurred by flooding, gypsum precipitation, upland erosion, and ancient Maya canal building and filling for wetland farming. Soil erosion and aggradation started at least by 3,000 BP and continued through the ancient Maya period, though reduced locally by soil conservation, post urban construction, and source reduction, especially in Maya Classic period from 1700 to 1000 BP.

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.

Estimating effective roughness parameters of the L-MEB model for soil moisture retrieval using passive microwave observations from SMAPVEX12

USDA-ARS?s Scientific Manuscript database

Although there have been efforts to improve existing soil moisture retrieval algorithms, the ability to estimate soil moisture from passive microwave observations is still hampered by problems in accurately modeling the observed microwave signal. This paper focuses on the estimation of effective sur...

Does plant architectural complexity increase with increasing habitat complexity? A test with a pioneer shrub in the Brazilian Cerrado.

PubMed

Silveira, F A O; Oliveira, E G

2013-05-01

Understanding variation in plant traits in heterogeneous habitats is important to predict responses to changing environments, but trait-environment associations are poorly known along ecological gradients. We tested the hypothesis that plant architectural complexity increases with habitat complexity along a soil fertility gradient in a Cerrado (Neotropical savanna) area in southeastern Brazil. Plant architecture and productivity (estimated as the total number of healthy infructescences) of Miconia albicans (SW.) Triana were examined in three types of vegetation which together form a natural gradient of increasing soil fertility, tree density and canopy cover: grasslands (campo sujo, CS), shrublands (cerrado sensu strico, CE) and woodlands (cerradão, CD). As expected, plants growing at the CS were shorter and had a lower branching pattern, whereas plants at the CD were the tallest. Unexpectedly, however, CD plants did not show higher architectural complexity compared to CE plants. Higher architectural similarity between CE and CD plants compared to similarity between CS and CE plants suggests reduced expression of functional architectural traits under shade. Plants growing at the CE produced more quaternary shoots, leading to a larger number of infructescences. This higher plant productivity in CE indicates that trait variation in ecological gradients is more complex than previously thought. Nematode-induced galls accounted for fruit destruction in 76.5% infructescences across physiognomies, but percentage of attack was poorly related to architectural variables. Our data suggest shade-induced limitation in M. albicans architecture, and point to complex phenotypic variation in heterogeneous habitats in Neotropical savannas.

[Quantitative estimation of vegetation cover and management factor in USLE and RUSLE models by using remote sensing data: a review].

PubMed

Wu, Chang-Guang; Li, Sheng; Ren, Hua-Dong; Yao, Xiao-Hua; Huang, Zi-Jie

2012-06-01

Soil loss prediction models such as universal soil loss equation (USLE) and its revised universal soil loss equation (RUSLE) are the useful tools for risk assessment of soil erosion and planning of soil conservation at regional scale. To make a rational estimation of vegetation cover and management factor, the most important parameters in USLE or RUSLE, is particularly important for the accurate prediction of soil erosion. The traditional estimation based on field survey and measurement is time-consuming, laborious, and costly, and cannot rapidly extract the vegetation cover and management factor at macro-scale. In recent years, the development of remote sensing technology has provided both data and methods for the estimation of vegetation cover and management factor over broad geographic areas. This paper summarized the research findings on the quantitative estimation of vegetation cover and management factor by using remote sensing data, and analyzed the advantages and the disadvantages of various methods, aimed to provide reference for the further research and quantitative estimation of vegetation cover and management factor at large scale.

Regionalising MUSLE factors for application to a data-scarce catchment

NASA Astrophysics Data System (ADS)

Gwapedza, David; Slaughter, Andrew; Hughes, Denis; Mantel, Sukhmani

2018-04-01

The estimation of soil loss and sediment transport is important for effective management of catchments. A model for semi-arid catchments in southern Africa has been developed; however, simplification of the model parameters and further testing are required. Soil loss is calculated through the Modified Universal Soil Loss Equation (MUSLE). The aims of the current study were to: (1) regionalise the MUSLE erodibility factors and; (2) perform a sensitivity analysis and validate the soil loss outputs against independently-estimated measures. The regionalisation was developed using Geographic Information Systems (GIS) coverages. The model was applied to a high erosion semi-arid region in the Eastern Cape, South Africa. Sensitivity analysis indicated model outputs to be more sensitive to the vegetation cover factor. The simulated soil loss estimates of 40 t ha-1 yr-1 were within the range of estimates by previous studies. The outcome of the present research is a framework for parameter estimation for the MUSLE through regionalisation. This is part of the ongoing development of a model which can estimate soil loss and sediment delivery at broad spatial and temporal scales.

Method comparison for forest soil carbon and nitrogen estimates in the Delaware River basin

Treesearch

B. Xu; Yude Pan; A.H. Johnson; A.F. Plante

2016-01-01

The accuracy of forest soil C and N estimates is hampered by forest soils that are rocky, inaccessible, and spatially heterogeneous. A composite coring technique is the standard method used in Forest Inventory and Analysis, but its accuracy has been questioned. Quantitative soil pits provide direct measurement of rock content and soil mass from a larger, more...

Improvement in estimation of soil water deficit by integrating airborne imagery data into a soil water balance modelents into a soil water

USDA-ARS?s Scientific Manuscript database

In this paper, an approach that integrates airborne imagery data as inputs was used to improve the estimation of soil water deficit (SWD) for maize and sunflower grown under full and deficit irrigation treatments. The proposed model was applied to optimize the maximum total available soil water (TAW...

Carbon to organic matter ratios for soils in Rocky Mountain coniferous forests

Treesearch

Theresa B. Jain; Russell T. Graham; David L. Adams

1997-01-01

Vegetation type, soils, climate, and conversion ratios influence estimates of terrestrial C. Our objectives were to (i) determine carbon to organic matter (C/OM) ratios for brown cubical rotten wood, litter, surface humus, soil wood, and mineral soils; (ii) evaluate the validity of using 0.58 and 0.50 ratios for estimating C in mineral and organic soil components,...

The effect of compost on carbon cycling in soil

NASA Astrophysics Data System (ADS)

Singer, E.; Woyke, T.

2013-12-01

Rangelands cover an estimated 40-70% of global landmass, approximately one-third of the landmass of the United States and half of California. The soils of this vast land area has high carbon (C) storage capacity, which makes it an important target ecosystem for the mitigation of greenhouse gas emission and effects on climate change, in particular under land management techniques that favor increased C sequestration rates. While microbial communities are key players in the processes responsible for C storage and loss in soils, we have barely shed light on these highly complex processes in part due to the tremendous and seemingly intractable diversity of microbes, largely uncultured, that inhabit soil ecosystems. In our study, we compare Mediterranean grassland soil plots that were amended with greenwaste of various C:N ratios and biochar in a single event. Monthly subsampling of control and amended plots over the course of three months was performed in depth increments of 0-12 cm and 12-24 cm. We present data on greenhouse gas emissions and budgets of carbon, nitrogen, phosphorus, and micronutrients in dependence of amendment types and seasonality. Changes in the active members of the soil microbial community were assessed using a novel approach combining flow cytometry and metagenomic sequencing disclosing 'who does what'. This is the first study revealing the nature of actively metabolizing microbial community members linked to the geochemical characteristics of compost-amended soil.

Determination of nitrogen balance in agroecosystems.

PubMed

Sainju, Upendra M

2017-01-01

Nitrogen balance in agroecosystems provides a quantitative framework of N inputs and outputs and retention in the soil that examines the sustainability of agricultural productivity and soil and environmental quality. Nitrogen inputs include N additions from manures and fertilizers, atmospheric depositions including wet and dry depositions, irrigation water, and biological N fixation. Nitrogen outputs include N removal in crop grain and biomass and N losses through leaching, denitrification, volatilization, surface runoff, erosion, gas emissions, and plant senescence. Nitrogen balance, which is the difference between N inputs and outputs, can be reflected in changes in soil total (organic + inorganic) N during the course of the experiment duration due to N immobilization and mineralization. While increased soil N retention and mineralization can enhance crop yields and decrease N fertilization rate, reduced N losses through N leaching and gas emissions (primarily NH 4 and NO x emissions, out of which N 2 O is a potent greenhouse gas) can improve water and air quality. •This paper discusses measurements and estimations (for non-measurable parameters due to complexity) of all inputs and outputs of N as well as changes in soil N storage during the course of the experiment to calculate N balance.•The method shows N flows, retention in the soil, and losses to the environment from agroecosystems.•The method can be used to measure agroecosystem performance and soil and environmental quality from agricultural practices.

The effect of compost on carbon cycling and the active soil microbiota

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

Singer, Esther; Woyke, Tanja; Ryals, Rebecca

2014-09-02

Rangelands cover an estimated 40-70percent of global landmass, approximately one-third of the landmass of the United States and half of California. The soils of this vast land area has high carbon (C) storage capacity, which makes it an important target ecosystem for the mitigation of greenhouse gas emission and effects on climate change, in particular under land management techniques that favor increased C sequestration rates. While microbial communities are key players in the processes responsible for C storage and loss in soils, we have barely shed light on these highly complex processes in part due to the tremendous and seeminglymore » intractable diversity of microbes, largely uncultured, that inhabit soil ecosystems. In our study, we compare Mediterranean grassland soil plots that were amended with greenwaste compost in a single event 6 years ago. Subsampling of control and amended plots was performed in depth increments of 0-10 cm. We present data on greenhouse gas emissions and budgets of carbon, nitrogen, phosphorus, and micronutrients in dependence of compost amendment. Changes in the active members of the soil microbial community were assessed using a novel approach combining flow cytometry and 16S tag sequencing disclosing who is active. This is the first study revealing the nature of actively metabolizing microbial community members linked to the geochemical characteristics of compost-amended soil.« less

Linking soil type and rainfall characteristics towards estimation of surface evaporative capacitance

NASA Astrophysics Data System (ADS)

Or, D.; Bickel, S.; Lehmann, P.

2017-12-01

Separation of evapotranspiration (ET) to evaporation (E) and transpiration (T) components for attribution of surface fluxes or for assessment of isotope fractionation in groundwater remains a challenge. Regional estimates of soil evaporation often rely on plant-based (Penman-Monteith) ET estimates where is E is obtained as a residual or a fraction of potential evaporation. We propose a novel method for estimating E from soil-specific properties, regional rainfall characteristics and considering concurrent internal drainage that shelters soil water from evaporation. A soil-dependent evaporative characteristic length defines a depth below which soil water cannot be pulled to the surface by capillarity; this depth determines the maximal soil evaporative capacitance (SEC). The SEC is recharged by rainfall and subsequently emptied by competition between drainage and surface evaporation (considering canopy interception evaporation). We show that E is strongly dependent on rainfall characteristics (mean annual, number of storms) and soil textural type, with up to 50% of rainfall lost to evaporation in loamy soil. The SEC concept applied to different soil types and climatic regions offers direct bounds on regional surface evaporation independent of plant-based parameterization or energy balance calculations.

Proxies for soil organic carbon derived from remote sensing

NASA Astrophysics Data System (ADS)

Rasel, S. M. M.; Groen, T. A.; Hussin, Y. A.; Diti, I. J.

2017-07-01

The possibility of carbon storage in soils is of interest because compared to vegetation it contains more carbon. Estimation of soil carbon through remote sensing based techniques can be a cost effective approach, but is limited by available methods. This study aims to develop a model based on remotely sensed variables (elevation, forest type and above ground biomass) to estimate soil carbon stocks. Field observations on soil organic carbon, species composition, and above ground biomass were recorded in the subtropical forest of Chitwan, Nepal. These variables were also estimated using LiDAR data and a WorldView 2 image. Above ground biomass was estimated from the LiDAR image using a novel approach where the image was segmented to identify individual trees, and for these trees estimates of DBH and Height were made. Based on AIC (Akaike Information Criterion) a regression model with above ground biomass derived from LiDAR data, and forest type derived from WorldView 2 imagery was selected to estimate soil organic carbon (SOC) stocks. The selected model had a coefficient of determination (R2) of 0.69. This shows the scope of estimating SOC with remote sensing derived variables in sub-tropical forests.

Quantifying the Complex Hydrologic Response of a Desert Ephemeral Wash

DTIC Science & Technology

2011-04-19

who graduated during this period and will receive scholarships or fellowships for further studies in science, mathematics, engineering or technology...precipitation, soil moisture response, 5 and evaporative losses across variable terrain provides an opportunity to improve water balance estimates for...threshold of +/- 0.5 o C for Oceanic Nino Index (ONI). (Source: NOAA /CPC, 2010) Year DJF JFM FMA MAM AMJ MJJ JJA JAS ASO SON OND NDJ 2005 0.7 0.5 0.4 0.4

Measuring organic matter in Everglades wetlands and the Everglades Agricultural Area

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

Wright, Alan L.; Hanlon, Edward A.

Here, organic matter is a complex material that represents the long-term decay products from plants and other organisms in the soil. When organic matter is allowed to build up in a soil, the soil color at the surface usually turns a darker color, often with a red or brown hue. Typically in Florida mineral soils, organic matter content is quite low, within the range of 1 to 5%. However, in some soils that remain flooded for most of the year, organic matter can build up with time and actually become the soil. Such is the case for the organic soils,more » or histosols, found in southern Florida. These organic soils comprise much of the Water Conservation Areas, Everglades National Park (ENP), Big Cypress Basin, and the Everglades Agricultural Area (EAA). It is important to document organic matter accumulation in the Everglades to gauge the effectiveness of wetland creation and succession. For the EAA, the drained soils lose organic matter due to oxidation, so measurement of the organic matter content of these soils over the course of time indicates the oxidation potential and mineral incorporation from bedrock. Due to the wide diversity of soil types and methods of measuring soil organic matter, there is a need to devise a more universal method applicable to many types of histosols in south Florida. The intent of this publication is: 1.To describe a simple laboratory method for determining the organic matter content of the organic soils of southern Florida and demonstrate the importance of using this new procedure for improved accuracy and precision; 2.To utilize this updated laboratory procedure for field sites across Everglades wetlands and the EAA; and 3. To recommend this procedure be used by growers, state and federal agencies, and university and agency researchers dealing with the management of organic soils in southern Florida. Growers can use this improvement to organic matter measurement to keep lab testing costs low while getting a better, more quantitative estimate of organic carbon (organic matter) for decisions regarding pesticide applications and estimated contribution of nutrients released from the organic matter in their fields. Restoration efforts in the Everglades wetlands can be better documented with the lower cost, but now equally as useful, LOI test for organic carbon. Improvements to soil organic matter coupled with other measurements of biological health of the system can be documented with less work using the adjusted LOI calculations.« less

Soil texture analysis revisited: Removal of organic matter matters more than ever

PubMed Central

Schjønning, Per; Watts, Christopher W.; Christensen, Bent T.; Munkholm, Lars J.

2017-01-01

Exact estimates of soil clay (<2 μm) and silt (2–20 μm) contents are crucial as these size fractions impact key soil functions, and as pedotransfer concepts based on clay and silt contents are becoming increasingly abundant. We examined the effect of removing soil organic matter (SOM) by H2O2 before soil dispersion and determination of clay and silt. Soil samples with gradients in SOM were retrieved from three long-term field experiments each with uniform soil mineralogy and texture. For soils with less than 2 g C 100 g-1 minerals, clay estimates were little affected by SOM. Above this threshold, underestimation of clay increased dramatically with increasing SOM content. Silt contents were systematically overestimated when SOM was not removed; no lower SOM threshold was found for silt, but the overestimation was more pronounced for finer textured soils. When exact estimates of soil particles <20 μm are needed, SOM should always be removed before soil dispersion. PMID:28542416

Soil texture analysis revisited: Removal of organic matter matters more than ever.

PubMed

Jensen, Johannes Lund; Schjønning, Per; Watts, Christopher W; Christensen, Bent T; Munkholm, Lars J

2017-01-01

Exact estimates of soil clay (<2 μm) and silt (2-20 μm) contents are crucial as these size fractions impact key soil functions, and as pedotransfer concepts based on clay and silt contents are becoming increasingly abundant. We examined the effect of removing soil organic matter (SOM) by H2O2 before soil dispersion and determination of clay and silt. Soil samples with gradients in SOM were retrieved from three long-term field experiments each with uniform soil mineralogy and texture. For soils with less than 2 g C 100 g-1 minerals, clay estimates were little affected by SOM. Above this threshold, underestimation of clay increased dramatically with increasing SOM content. Silt contents were systematically overestimated when SOM was not removed; no lower SOM threshold was found for silt, but the overestimation was more pronounced for finer textured soils. When exact estimates of soil particles <20 μm are needed, SOM should always be removed before soil dispersion.

Estimating surface soil moisture from SMAP observations using a neural network technique

USDA-ARS?s Scientific Manuscript database

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to June 2016 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observ...

Precipitation estimation using L-Band and C-Band soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterome...

Hillslope soil erosion estimated from aerosol concentrations, North Halawa Valley, Oahu, Hawaii

USGS Publications Warehouse

Hill, B.R.; Fuller, C.C.; DeCarlo, E.H.

1997-01-01

Concentrations of aerosolic quartz and 137Cs were used to estimate rates of hillslope soil erosion during 1990-91 in the North Halawa Valley on the island of Oahu, Hawaii. Fluvial transport of quartz was estimated to be 6.1 Mg in 1990 and 14.9 Mg in 1991. Fluvial transport of 137Cs from North Halawa Valley was estimated to be 1.29 ?? 109 pCi in 1991. Results were used with quartz contents, 137Cs activities, and bulk densities of hillslope soils to compute rates of basinwide hillslope soil erosion ranging from 0.1 to 0.3 mm yr-1. These rates are within the range of previous estimates of denudation computed for drainage basins on Oahu. The aerosol-concentration approach, therefore, is a useful method for assessing basinwide soil erosion.

Adapting FAO-56 Spreadsheet Program to estimate olive orchard transpiration fluxes under soil water stress condition

NASA Astrophysics Data System (ADS)

Rallo, G.; Provenzano, G.; Manzano-Juárez, J.

2012-04-01

In the Mediterranean environment, where the period of crops growth does not coincide with the rainy season, the crop is subject to water stress periods that may be amplified with improper irrigation management. Agro-hydrological models can be considered an economic and simple tool to optimize irrigation water use, mainly when water represents a limiting factor for crop production. In the last two decades, agro-hydrological physically based models have been developed to simulate mass and energy exchange processes in the soil-plant-atmosphere system (Feddes et al., 1978; Bastiaanssen et al., 2007). Unfortunately these models, although very reliable, as a consequence of the high number of required variables and the complex computational analysis, cannot often be used. Therefore, simplified agro-hydrological models may represent an useful and simple tool for practical irrigation scheduling. The main objective of the work is to assess, for an olive orchard, the suitability of FAO-56 spreadsheet agro-hydrological model to estimate a long time series of field transpiration, soil water content and crop water stress dynamic. A modification of the spreadsheet is suggested in order to adapt the simulations to a crop tolerant to water stress. In particular, by implementing a new crop water stress function, actual transpiration fluxes and an ecophysiological stress indicator, i. e. the relative transpiration, are computed in order to evaluate a plant-based irrigation scheduling parameter. Validation of the proposed amendment is carried out by means of measured sap fluxes, measured on different plants and up-scaled to plot level. Spatial and temporal variability of soil water contents in the plot was measured, at several depths, using the Diviner 2000 capacitance probe (Sentek Environmental Technologies, 2000) and TDR-100 (Campbell scientific, Inc.) system. The detailed measurements of soil water content, allowed to explore the high spatial variability of soil water content due to the combined effect of the punctual irrigation and the non-uniform root density distribution. A further validation of the plant-based irrigation-timing indicator will be carried out by considering another ecophysiological stress variable like the predawn leaf water potential. Accuracy of the model output was assessed using the Mean Absolute Difference, the Root Mean Square Difference and the efficiency index of Nash and Sutcliffe. Experimental data, recorded during three years of field observation, allowed, with a great level of detail, to investigate on the dynamic of water fluxes from the soil to atmosphere as well as to validate the proposed amendment of the FAO-56 spreadsheet. The modified model simulated with a satisfactory approximation the measured values of average soil water content in the root zone, with error of estimation equal to about 2.0%. These differences can be considered acceptable for practical applications taking into account the intrinsic variability of the data especially in the soil moisture point measurements. An error less than 1 mm was calculated in the daily transpiration estimation. A good performance was observed in the estimation of the cumulate transpiration fluxes.

Challenges in Developing Models Describing Complex Soil Systems

NASA Astrophysics Data System (ADS)

Simunek, J.; Jacques, D.

2014-12-01

Quantitative mechanistic models that consider basic physical, mechanical, chemical, and biological processes have the potential to be powerful tools to integrate our understanding of complex soil systems, and the soil science community has often called for models that would include a large number of these diverse processes. However, once attempts have been made to develop such models, the response from the community has not always been overwhelming, especially after it discovered that these models are consequently highly complex, requiring not only a large number of parameters, not all of which can be easily (or at all) measured and/or identified, and which are often associated with large uncertainties, but also requiring from their users deep knowledge of all/most of these implemented physical, mechanical, chemical and biological processes. Real, or perceived, complexity of these models then discourages users from using them even for relatively simple applications, for which they would be perfectly adequate. Due to the nonlinear nature and chemical/biological complexity of the soil systems, it is also virtually impossible to verify these types of models analytically, raising doubts about their applicability. Code inter-comparisons, which is then likely the most suitable method to assess code capabilities and model performance, requires existence of multiple models of similar/overlapping capabilities, which may not always exist. It is thus a challenge not only to developed models describing complex soil systems, but also to persuade the soil science community in using them. As a result, complex quantitative mechanistic models are still an underutilized tool in soil science research. We will demonstrate some of the challenges discussed above on our own efforts in developing quantitative mechanistic models (such as HP1/2) for complex soil systems.

Estimation of available water capacity components of two-layered soils using crop model inversion: Effect of crop type and water regime

NASA Astrophysics Data System (ADS)

Sreelash, K.; Buis, Samuel; Sekhar, M.; Ruiz, Laurent; Kumar Tomer, Sat; Guérif, Martine

2017-03-01

Characterization of the soil water reservoir is critical for understanding the interactions between crops and their environment and the impacts of land use and environmental changes on the hydrology of agricultural catchments especially in tropical context. Recent studies have shown that inversion of crop models is a powerful tool for retrieving information on root zone properties. Increasing availability of remotely sensed soil and vegetation observations makes it well suited for large scale applications. The potential of this methodology has however never been properly evaluated on extensive experimental datasets and previous studies suggested that the quality of estimation of soil hydraulic properties may vary depending on agro-environmental situations. The objective of this study was to evaluate this approach on an extensive field experiment. The dataset covered four crops (sunflower, sorghum, turmeric, maize) grown on different soils and several years in South India. The components of AWC (available water capacity) namely soil water content at field capacity and wilting point, and soil depth of two-layered soils were estimated by inversion of the crop model STICS with the GLUE (generalized likelihood uncertainty estimation) approach using observations of surface soil moisture (SSM; typically from 0 to 10 cm deep) and leaf area index (LAI), which are attainable from radar remote sensing in tropical regions with frequent cloudy conditions. The results showed that the quality of parameter estimation largely depends on the hydric regime and its interaction with crop type. A mean relative absolute error of 5% for field capacity of surface layer, 10% for field capacity of root zone, 15% for wilting point of surface layer and root zone, and 20% for soil depth can be obtained in favorable conditions. A few observations of SSM (during wet and dry soil moisture periods) and LAI (within water stress periods) were sufficient to significantly improve the estimation of AWC components. These results show the potential of crop model inversion for estimating the AWC components of two-layered soils and may guide the sampling of representative years and fields to use this technique for mapping soil properties that are relevant for distributed hydrological modelling.

Pore-water chemistry explains zinc phytotoxicity in soil.

PubMed

Kader, Mohammed; Lamb, Dane T; Correll, Ray; Megharaj, Mallavarapu; Naidu, Ravi

2015-12-01

Zinc (Zn) is a widespread soil contaminant arising from a numerous anthropogenic sources. However, adequately predicting toxicity of Zn to ecological receptors remains difficult due to the complexity of soil characteristics. In this study, we examined solid-solution partitioning using pore-water data and toxicity of Zn to cucumber (Cucumis sativus L.) in spiked soils. Pore-water effective concentration (ECx, x=10%, 20% and 50% reduction) values were negatively related to pH, indicating lower Zn pore water concentration were needed to cause phytotoxicity at high pH soils. Total dissolved zinc (Znpw) and free zinc (Zn(2+)) in soil-pore water successfully described 78% and 80.3% of the variation in relative growth (%) in the full dataset. When the complete data set was used (10 soils), the estimated EC50pw was 450 and 79.2 µM for Znpw and Zn(2+), respectively. Total added Zn, soil pore water pH (pHpw) and dissolve organic carbon (DOC) were the best predictors of Znpw and Zn(2+) in pore-water. The EC10 (total loading) values ranged from 179 to 5214 mg/kg, depending on soil type. Only pH measurements in soil were related to ECx total Zn data. The strongest relationship to ECx overall was pHca, although pHw and pHpw were in general related to Zn ECx. Similarly, when a solution-only model was used to predict Zn in shoot, DOC was negatively related to Zn in shoot, indicating a reduction in uptake/ translocation of Zn from solution with increasing DOC. Copyright © 2015 Elsevier Inc. All rights reserved.

Electrokinetic-Fenton technology for the remediation of hydrocarbons historically polluted sites.

PubMed

Sandu, Ciprian; Popescu, Marius; Rosales, Emilio; Bocos, Elvira; Pazos, Marta; Lazar, Gabriel; Sanromán, M Angeles

2016-08-01

The feasibility of the electrokinetic-Fenton technology coupled with surfactants in the treatment of real historically hydrocarbons polluted soils has been studied. The characterisation of these soils from Spain and Romania was performed and identified as diesel and diesel-motor oil spillages, respectively. Moreover, the ageing of the spillages produced by the soil contamination was estimated showing the historical pollution of the sites (around 11 and 20 years for Romanian and Spanish soils, respectively). An ex-situ electrochemical treatment was performed to evaluate the adequacy of surfactants for the degradation of the hydrocarbons present in the soils. It was found an enhancement in the solubilisation and removal of TPHs with percentages increasing from 25.7 to 81.8% by the presence of Tween 80 for Spanish soil and from 15.1% to 71.6% for Triton X100 in Romanian soil. Therefore, the viability of coupling enhanced electrokinetic and Fenton remediation was evaluated through a simulated in-situ treatment at laboratory scale. The results demonstrated that the addition of the selected surfactants improved the solubilisation of the hydrocarbons and influenced the electroosmotic flow with a slight decrease. The efficiency of the treatment increased for both considered soil samples and a significant degradation level of the hydrocarbons compounds was observed. Buffering of pH coupled with the addition of a complexing agent showed to be important in the treatment process, facilitating the conditions for the degradation reactions that take place into the soil matrix. The results demonstrated the effectiveness of the selected techniques for remediation of the investigated soils. Copyright © 2016 Elsevier Ltd. All rights reserved.

Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model

NASA Astrophysics Data System (ADS)

Exbrayat, J.-F.; Pitman, A. J.; Abramowitz, G.

2014-03-01

Recent studies have identified the first-order parameterization of microbial decomposition as a major source of uncertainty in simulations and projections of the terrestrial carbon balance. Here, we use a reduced complexity model representative of the current state-of-the-art parameterization of soil organic carbon decomposition. We undertake a systematic sensitivity analysis to disentangle the effect of the time-invariant baseline residence time (k) and the sensitvity of microbial decomposition to temperature (Q10) on soil carbon dynamics at regional and global scales. Our simulations produce a range in total soil carbon at equilibrium of ~ 592 to 2745 Pg C which is similar to the ~ 561 to 2938 Pg C range in pre-industrial soil carbon in models used in the fifth phase of the Coupled Model Intercomparison Project. This range depends primarily on the value of k, although the impact of Q10 is not trivial at regional scales. As climate changes through the historical period, and into the future, k is primarily responsible for the magnitude of the response in soil carbon, whereas Q10 determines whether the soil remains a sink, or becomes a source in the future mostly by its effect on mid-latitudes carbon balance. If we restrict our simulations to those simulating total soil carbon stocks consistent with observations of current stocks, the projected range in total soil carbon change is reduced by 42% for the historical simulations and 45% for the future projections. However, while this observation-based selection dismisses outliers it does not increase confidence in the future sign of the soil carbon feedback. We conclude that despite this result, future estimates of soil carbon, and how soil carbon responds to climate change should be constrained by available observational data sets.

Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model

NASA Astrophysics Data System (ADS)

Exbrayat, J.-F.; Pitman, A. J.; Abramowitz, G.

2014-12-01

Recent studies have identified the first-order representation of microbial decomposition as a major source of uncertainty in simulations and projections of the terrestrial carbon balance. Here, we use a reduced complexity model representative of current state-of-the-art models of soil organic carbon decomposition. We undertake a systematic sensitivity analysis to disentangle the effect of the time-invariant baseline residence time (k) and the sensitivity of microbial decomposition to temperature (Q10) on soil carbon dynamics at regional and global scales. Our simulations produce a range in total soil carbon at equilibrium of ~ 592 to 2745 Pg C, which is similar to the ~ 561 to 2938 Pg C range in pre-industrial soil carbon in models used in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). This range depends primarily on the value of k, although the impact of Q10 is not trivial at regional scales. As climate changes through the historical period, and into the future, k is primarily responsible for the magnitude of the response in soil carbon, whereas Q10 determines whether the soil remains a sink, or becomes a source in the future mostly by its effect on mid-latitude carbon balance. If we restrict our simulations to those simulating total soil carbon stocks consistent with observations of current stocks, the projected range in total soil carbon change is reduced by 42% for the historical simulations and 45% for the future projections. However, while this observation-based selection dismisses outliers, it does not increase confidence in the future sign of the soil carbon feedback. We conclude that despite this result, future estimates of soil carbon and how soil carbon responds to climate change should be more constrained by available data sets of carbon stocks.

Methodological Approaches toward Chemico-Biological Diagnostics of the State of Soils in Technogenically Transformed Territories

NASA Astrophysics Data System (ADS)

Fokina, A. I.; Dabakh, E. V.; Domracheva, L. I.; Skugoreva, S. G.; Lyalina, E. I.; Ashikhmina, T. Ya.; Zykova, Yu. N.; Leonova, K. A.

2018-05-01

The comprehensive diagnostics of the state of soils in the impact zone of thermal power station (TPS-5) in the city of Kirov was performed on the basis of the soil chemical analyses and the study of biota response to the loads at different organization levels. The chemical analyses attested to a satisfactory state of the soils. However, the use of soil cyanobacteria and bird's-foot trefoil ( Lótus corniculátus) as test objects showed the toxicity of studied soil samples. The toxicity of the samples was judged from the bioindication effects of cyanophytization and melanization of soil microbial complexes. The obtained results demonstrated that at relatively low concentrations of total and mobile heavy metal compounds in the soil samples, their amount released into the tested soil water (1: 4) extract exceeded the limit allowable for normal functioning of living organisms. For the first time, the express cyanobacterial tetrazole-topographic method of biotesting was applied in the geoecological study to estimate the toxicity of the soil samples. The results obtained with the help of traditional and express methods proved to be comparable. The express-method was sufficiently sensitive and efficient. It allowed the determination of the samples' toxicity in five hours, i.e., four to five times faster than the traditional technique. An inverse relationship between the number of viable cells of cyanobacteria (as judged from the inclusion of formazan crystals) and the concentration of lead ions in the tested soil extracts was found. This finding can be considered a prerequisite for further study and application of the express method in the practice of geoecological monitoring. Our study demonstrated the necessity of a comprehensive approach for the assessment of the real ecological state of soils in the investigated impact zone of the thermal power station.

The effect of organic contaminants on the spectral induced polarization response of porous media - mechanistic approach

NASA Astrophysics Data System (ADS)

Schwartz, N.; Huisman, J. A.; Furman, A.

2012-12-01

In recent years, there is a growing interest in using geophysical methods in general and spectral induced polarization (SIP) in particular as a tool to detect and monitor organic contaminants within the subsurface. The general idea of the SIP method is to inject alternating current through a soil volume and to measure the resultant potential in order to obtain the relevant soil electrical properties (e.g. complex impedance, complex conductivity/resistivity). Currently, a complete mechanistic understanding of the effect of organic contaminants on the SIP response of soil is still absent. In this work, we combine laboratory experiments with modeling to reveal the main processes affecting the SIP signature of soil contaminated with organic pollutant. In a first set of experiments, we investigate the effect of non-aqueous phase liquids (NAPL) on the complex conductivity of unsaturated porous media. Our results show that addition of NAPL to the porous media increases the real component of the soil electrical conductivity and decreases the polarization of the soil (imaginary component of the complex conductivity). Furthermore, addition of NAPL to the soil resulted in an increase of the electrical conductivity of the soil solution. Based on these results, we suggest that adsorption of NAPL to the soil surface, and exchange process between polar organic compounds in the NAPL and inorganic ions in the soil are the main processes affecting the SIP signature of the contaminated soil. To further support our hypothesis, the temporal change of the SIP signature of a soil as function of a single organic cation concentration was measured. In addition to the measurements of the soil electrical properties, we also measured the effect of the organic cation on the chemical composition of both the bulk and the surface of the soil. The results of those experiments again showed that the electrical conductivity of the soil increased with increasing contaminant concentration. In addition, direct evidence showed that the organic cation was adsorbed on the soil surface and exchanged with inorganic ions that usually exist in soil. This experiment confirmed that adsorption to the soil surface and the associated release of inorganic ions is the main mechanism affecting the complex conductivity of the contaminated porous media. Furthermore, our results show that adsorption of organic ions to the soil surface resulted in a decrease of the soil polarization. Using a chemical complexation model of the soil surface and a model for the polarization of the Stern layer, we were able to show that the decrease in the polarization of the soil can be related to the decrease in the surface site density of inorganic ions, and that the contribution of the soil-organic complexes to the polarization of the soil is negligible. We attribute this to the strong interaction between polar organic compounds and soil which results in a significant decrease in the mobility of the organic compounds in the Stern layer. The results of this work are essential to better interpret SIP signatures of soil contaminated with organic contaminants.

Soil moisture data as a constraint for groundwater recharge estimation

NASA Astrophysics Data System (ADS)

Mathias, Simon A.; Sorensen, James P. R.; Butler, Adrian P.

2017-09-01

Estimating groundwater recharge rates is important for water resource management studies. Modeling approaches to forecast groundwater recharge typically require observed historic data to assist calibration. It is generally not possible to observe groundwater recharge rates directly. Therefore, in the past, much effort has been invested to record soil moisture content (SMC) data, which can be used in a water balance calculation to estimate groundwater recharge. In this context, SMC data is measured at different depths and then typically integrated with respect to depth to obtain a single set of aggregated SMC values, which are used as an estimate of the total water stored within a given soil profile. This article seeks to investigate the value of such aggregated SMC data for conditioning groundwater recharge models in this respect. A simple modeling approach is adopted, which utilizes an emulation of Richards' equation in conjunction with a soil texture pedotransfer function. The only unknown parameters are soil texture. Monte Carlo simulation is performed for four different SMC monitoring sites. The model is used to estimate both aggregated SMC and groundwater recharge. The impact of conditioning the model to the aggregated SMC data is then explored in terms of its ability to reduce the uncertainty associated with recharge estimation. Whilst uncertainty in soil texture can lead to significant uncertainty in groundwater recharge estimation, it is found that aggregated SMC is virtually insensitive to soil texture.

Estimating Rangeland Forage Production Using Remote Sensing Data from a Small Unmanned Aerial System (sUAS)

NASA Astrophysics Data System (ADS)

Liu, H.; Jin, Y.; Devine, S.; Dahlgren, R. A.; Covello, S.; Larsen, R.; O'Geen, A. T.

2017-12-01

California rangelands cover 23 million hectares and support a $3.4 billion annual cattle industry. Rangeland forage production varies appreciably from year-to-year and across short distances on the landscape. Spatially explicit and near real-time information on forage production at a high resolution is critical for effective rangeland management, especially during an era of climatic extremes. We here integrated a multispectral MicaSense RedEdge camera with a 3DR solo quad-copter and acquired time-series images during the 2017 growing season over a topographically complex 10-hectare rangeland in San Luis Obispo County, CA. Soil moisture and temperature sensors were installed at 16 landscape positions, and vegetation clippings were collected at 36 plots to quantify forage dry biomass. We built four centimeter-level models for forage production mapping using time series of sUAS images and ground measurements of forage biomass and soil temperature and moisture. The biophysical model based on Monteith's eco-physiological plant growth theory estimated forage production reasonably well with a coefficient of determination (R2) of 0.86 and a root-mean-square error (RMSE) of 424 kg/ha when the soil parameters were included, and a R2 of 0.79 and a RMSE of 510 kg/ha when only remote sensing and topographical variables were included. We built two empirical models of forage production using a stepwise variable selection technique, one with soil variables. Results showed that cumulative absorbed photosynthetically active radiation (APAR) and elevation were the most important variables in both models, explaining more than 40% of the spatio-temporal variance in forage production. Soil moisture accounted for an additional 29% of the variance. Illumination condition was selected as a proxy for soil moisture in the model without soil variables, and accounted for 18% of the variance. We applied the remote sensing-based models to map daily forage production at 30-cm resolution for the whole study area during the 2017 growing season. The forage maps captured similar seasonal and spatial patterns of forage production as ground measured dry biomass. This study demonstrated a near real-time monitoring tool for ranchers to estimate forage production with sUAS technology and improved watershed-scale rangeland management.

Soil ingestion rates for children under 3 years old in Taiwan.

PubMed

Chien, Ling-Chu; Tsou, Ming-Chien; Hsi, Hsing-Cheng; Beamer, Paloma; Bradham, Karen; Hseu, Zeng-Yei; Jien, Shih-Hao; Jiang, Chuen-Bin; Dang, Winston; Özkaynak, Halûk

2017-01-01

Soil and dust ingestion rates by children are among the most critical exposure factors in determining risks to children from exposures to environmental contaminants in soil and dust. We believe this is the first published soil ingestion study for children in Taiwan using tracer element methodology. In this study, 66 children under 3 years of age were enrolled from Taiwan. Three days of fecal samples and a 24-h duplicate food sample were collected. The soil and household dust samples were also collected from children's homes. Soil ingestion rates were estimated based on silicon (Si) and titanium (Ti). The average soil ingestion rates were 9.6±19.2 mg/day based on Si as a tracer. The estimated soil ingestion rates based on Si did not have statistically significant differences by children's age and gender, although the average soil ingestion rates clearly increased as a function of children's age category. The estimated soil ingestion rates based on Si was significantly and positively correlated with the sum of indoor and outdoor hand-to-mouth frequency rates. The average soil ingestion rates based on Si were generally lower than the results from previous studies for the US children. Ti may not be a suitable tracer for estimating soil ingestion rates in Taiwan because the Ti dioxide is a common additive in food. To the best of our knowledge, this is the first study that investigated the correlations between soil ingestion rates and mouthing behaviors in Taiwan or other parts of Asia. It is also the first study that could compare available soil ingestion data from different countries and/or different cultures. The hand-to-mouth frequency and health habits are important to estimate the soil ingestion exposure for children. The results in this study are particularly important when assessing children's exposure and potential health risk from nearby contaminated soils in Taiwan.

Frozen peatlands: carbon store and the climate change

NASA Astrophysics Data System (ADS)

Ogneva, Olga; Matyshak, George; Tarkhov, Matvey

2017-04-01

Peatlands soils in the northern permafrost region store approximately 40% of total Earth's soils carbon. These soils develop under the influence of cryogenic processes especially such as freeze-thaw and cryoturbations. Climate change predictions suggest that the frequency of soil freeze-thaw cycles (FTCs) will increase in cool temperate and other high-latitude regions. This trend may cause a response in organic matter decomposition rate - that will result in significant changes of greenhouse gases emission (CO2, CH4). For further predictions improvement of soils response to global climate changes it is necessary to estimate the impact of FTCs in permafrost soils on organic matter decomposition. We investigated the effects of FTCs on microbial biomass, basal respiration, metabolic quotient and dissolved organic matter (DOM) content (carbon - DOC and nitrogen - DON) in frozen peatlands soils by laboratory modelling experiment. Frozen peatlands from the north of Western Siberia in Nadym area (N65°19', E72°53'), in a zone of discontinuous permafrost were studied. The soil cover of these formations is represented by a complex of Typic Histoturbels (Turbic Cryosol) and Typic Historthels (Cryic Histosols). Peat profiles of both soil types were divided into horizons due to decomposition degree (from 15 to 55-60%), age (from 1000 to 5700 yrs) and botanic composition (oligotrophic, mesotrophic, eutrophic). During the experiment, first group of samples of peat horizons (field moisture content) were subjected for 10 times to 3-day FTCs at the temperature of -10 and +4 ° C. In the second group of peat samples were incubated at +4 ° C (with no freeze-thaw). It was established that all studied microbial properties were inversely proportional with decomposition degree of peat, except metabolic quotient. Our results illustrate that microbial activity, estimated by BR, shows resistance to FTCs and doesn't significantly differ after FTCs an average. Microbial biomass (carbon and nitrogen) as well as BR doesn't differ too. The most intensive response to FTCs shows DOM content value which was 1.5 times higher on average in samples after FTCs in comparison with control samples. We suppose that increase of FTCs frequency in soil will result in significant acceleration mineralization of peat. Because these processes exert disruptive effects on soil organic matter, provide converting carbon from pool into forms available for microbial communities, thus involving stored carbon into the carbon turnover.

Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery

NASA Astrophysics Data System (ADS)

Brook, Anna; Wittenberg, Lea

2015-04-01

Long-term environmental monitoring is addressed to identify physical and biological changes and progresses taking place in the ecosystem. This basic action of landscape monitoring is an essential part of the systematic long-term surveillance, aiming to evaluate, assess and predict the spatial change and progresses. Indeed, it provides a context for wide range of diverse studies and research frameworks from regional or global scale. Spatial-temporal trends and changes at various scales (massive to less certain) require establishing consistent baseline data over time. One of the spatial cases of landscape monitoring is dedicated to soil formation and pedological progresses. It is previously acknowledged that changes in soil affect the functionality of the environment, so monitoring changes recently become important cause considerable resources in areas such as environmental management, sustainability services, and protecting the environment healthy. Given the above, it can be concluded that monitoring changes in the base for sustainable development. The hydrological response of bare soils and watersheds in semiarid regions to intense rainfall events is known to be complex due to multiply physical and structural impacts and feedbacks. As a result, the comprehensive evaluations of mathematical models including detailed consideration of uncertainties in the modeling of hydrological and environmental systems are of increasing importance. The presented method incorporates means of remote sensing data, hydrological and climate data and implementing dedicated and integrative Monte Carlo Analysis Toolbox (MCAT) model for semiarid region. Complexity of practical models to represent spatial systems requires an extensive understanding of the spatial phenomena, while providing realistic balance of sensitivity and corresponding uncertainty levels. Nowadays a large number of dedicated mathematical models applied to assess environmental hydrological process. Among the most promising models is the MCAT, which is a MATLAB library of visual and numerical analysis tools for the evaluation of hydrological and environmental models. The model applied in this paper presents an innovative infrastructural system for predicting soil stability and erosion impacts. This integrated model is applicable to mixed areas with spatially varying soil properties, landscape, and land-cover characteristics. Data from a semiarid site in southern Israel was used to evaluate the model and analyze fundamental erosion mechanisms. The findings estimate the sensitivity of the suggested model to the physical parameters and encourage the use of hyperspectral remote sensing imagery (HSI). The proposed model is integrated according to the following stages: 1. The soil texture, aggregation, soil moisture estimated via airborne HSI data, including soil surface clay and calcium carbonate erosions; 2. The mechanical stability of soil assessed via pedo-transfer function corresponding to load dependent changes in soil physical properties due to pre-compression stress (set of equations study shear strength parameters take into account soil texture, aggregation, soil moisture and ecological soil variables); 3. The precipitation-related runoff model program (RMP) satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation; 4. The Monte Carlo Analysis Toolbox (MCAT), a library of visual and numerical analysis tools for the evaluation of hydrological and environmental models, is proposed as a tool for integrate all the approaches to an applicable model. The presented model overcomes the limitations of existing modeling methods by integrating physical data produced via HSI and yet stays generic in terms of space and time independency.

Soil mercury levels in the area surrounding the Cerro Prieto geothermal complex, MEXICO.

PubMed

Pastrana-Corral, M A; Wakida, F T; García-Flores, E; Rodriguez-Mendivil, D D; Quiñonez-Plaza, A; Piñon-Colin, T D J

2016-08-01

Even though geothermal energy is a renewable energy source that is seen as cost-effective and environmentally friendly, emissions from geothermal plants can impact air, soil, and water in the vicinity of geothermal power plants. The Cerro Prieto geothermal complex is located 30 km southeast of the city of Mexicali in the Mexican state of Baja California. Its installed electricity generation capacity is 720 MW, being the largest geothermal complex in Mexico. The objective of this study was to evaluate whether the emissions generated by the geothermal complex have increased the soil mercury concentration in the surrounding areas. Fifty-four surface soil samples were collected from the perimeter up to an approximate distance of 7660 m from the complex. Additionally, four soil depth profiles were performed in the vicinity of the complex. Mercury concentration in 69 % of the samples was higher than the mercury concentration found at the baseline sites. The mercury concentration ranged from 0.01 to 0.26 mg/kg. Our results show that the activities of the geothermal complex have led to an accumulation of mercury in the soil of the surrounding area. More studies are needed to determine the risk to human health and the ecosystems in the study area.

Rhizosphere Environment and Labile Phosphorus Release from Organic Waste-Amended Soils.

NASA Astrophysics Data System (ADS)

Dao, Thanh H.

2015-04-01

Crop residues and biofertilizers are primary sources of nutrients for organic crop production. However, soils treated with large amounts of nutrient-enriched manure have elevated phosphorus (P) levels in regions of intensive animal agriculture. Surpluses occurred in these amended soils, resulting in large pools of exchangeable inorganic P (Pi) and enzyme-labile organic P (Po) that averaging 30.9 and 68.2 mg kg-1, respectively. Organic acids produced during crop residue decomposition can promote the complexation of counter-ions and decouple and release unbound Pi from metal and alkali metal phosphates. Animal manure and cover crop residues also contain large amounts of soluble organic matter, and likely generate similar ligands. However, a high degree of heterogeneity in P spatial distribution in such amended fields, arising from variances in substrate physical forms ranging from slurries to dried solids, composition, and diverse application methods and equipment. Distinct clusters of Pi and Po were observed, where accumulation of the latter forms was associated with high soil microbial biomass C and reduced phosphomonoesterases' activity. Accurate estimates of plant requirements and lability of soil P pools, and real-time plant and soil P sensing systems are critical considerations to optimally manage manure-derived nutrients in crop production systems. An in situ X-ray fluorescence-based approach to sensing canopy and soil XRFS-P was developed to improve the yield-soil P relationship for optimal nutrient recommendations in addition to allowing in-the-field verification of foliar P status.

Iron clad wetlands: Soil iron-sulfur buffering determines coastal wetland response to salt water incursion

NASA Astrophysics Data System (ADS)

Schoepfer, Valerie A.; Bernhardt, Emily S.; Burgin, Amy J.

2014-12-01

Coastal freshwater wetland chemistry is rapidly changing due to increased frequency of salt water incursion, a consequence of global change. Seasonal salt water incursion introduces sulfate, which microbially reduces to sulfide. Sulfide binds with reduced iron, producing iron sulfide (FeS), recognizable in wetland soils by its characteristic black color. The objective of this study is to document iron and sulfate reduction rates, as well as product formation (acid volatile sulfide (AVS) and chromium reducible sulfide (CRS)) in a coastal freshwater wetland undergoing seasonal salt water incursion. Understanding iron and sulfur cycling, as well as their reduction products, allows us to calculate the degree of sulfidization (DOS), from which we can estimate how long soil iron will buffer against chemical effects of sea level rise. We show that soil chloride, a direct indicator of the degree of incursion, best predicted iron and sulfate reduction rates. Correlations between soil chloride and iron or sulfur reduction rates were strongest in the surface layer (0-3 cm), indicative of surface water incursion, rather than groundwater intrusion at our site. The interaction between soil moisture and extractable chloride was significantly related to increased AVS, whereas increased soil chloride was a stronger predictor of CRS. The current DOS in this coastal plains wetland is very low, resulting from high soil iron content and relatively small degree of salt water incursion. However, with time and continuous salt water exposure, iron will bind with incoming sulfur, creating FeS complexes, and DOS will increase.

Vegetation Influences on Long-Term Carbon Stabilization in Soils: a Coast Redwood-Prairie Comparison

NASA Astrophysics Data System (ADS)

Mambelli, S.; Burton, S. D.; McFarlane, K. J.; Torn, M. S.; Dawson, T. E.

2010-12-01

Complex interactions and feedbacks among soil, biota, climate, and parent material determine the long-term pathways and mechanisms of carbon persistence in soils. While it is well known that litter chemistry influences litter decay on annual-decadal timescales, its impact on long-term SOM storage is still under debate. We tested the role of the substrate available to decomposers in determining decomposition and sequestration of carbon by comparing two contrasting ecosystems representing end-members in terms of tissue lifespan and litter recalcitrance, an old-growth redwood forest and an adjacent tree-less prairie, at one site with identical climate, topography, and parent material. Solid-state CP MAS 13C NMR was applied to investigate the chemical structure of vegetation tissues (aboveground and belowground), and of soil fractions (particulate organic carbon free in the soil matrix and particulate organic carbon located inside soil aggregates, or free and occluded light fraction (LF), respectively) at different depths. In addition, the carbon stability of these soil density fractions was estimated based on radiocarbon modeling. Preliminary NMR results showed strong differences between redwood and prairie tissues, and between litters and surface soil fractions. On average, redwood litter contained more aromatic carbon (C and O substituted aryl C), more lipids (alkyl C) and fewer carbohydrates (O-alkyl C) than prairie litter. Under both vegetation types we found that the chemical structure changed consistently from litter to free LF, and from free LF to occluded LF. The alkyl C signal intensity increased, while the O-alkyl C fraction decreased, but more strongly at the redwood forest. The proportion of aromatic functional groups in the total organic matter (aromaticity) was always higher in the soil fractions compared with the original litters. Redwood soil fractions aromaticity was 0.32 (+80% from litter), while prairie soil fractions aromaticity varied from 0.17 (free LF) to 0.23 (occluded LF)(+40 and +90% from litter, respectively). The proportion of carbon in carbonyl groups (alkyl/O-alkyl ratio), an estimate of the degree of decomposition, increased from the free LF to the occluded LF at both ecosystems (0.30 to 0.75 in the redwood forest, 0.24 to 0.68 in the prairie, respectively). In summary, the similar decomposition stage of the redwood and prairie SOM and the higher aromaticity of the free LF in the redwood soil compared to the original litter suggest the preservation of recalcitrant redwood constituents but only in the free soil matrix. Further investigations at deeper soil depths are underway.

Correlation Between An In-vitro Method And An In-vivo Method In Assessing Bioavailable Arsenic In Two Pesticide-Amended Soils

NASA Astrophysics Data System (ADS)

Quazi, S.; Sarkar, D.; Sylvia, V.; Datta, R.

2006-05-01

Health risk assessment of Arsenic (As) enriched soil requires the estimation of bioavailable fraction of total metal. Research has been conducted to gain a better understanding of the relationship between metal availability and risk assessment. Some baseline risk assessments developed for contaminated sites have used the conservative assumption that all (i.e. 100%) of the As present in soils and wastes is bioavailable, due to tremendous cost associated with in-vivo bioavailability studies. This potentially overestimates the actual health risk, elevating the expenses associated with site cleanup. Health risk from direct exposure to soil-As via the hand-to-mouth exposure route is restricted only to those fractions of As in the soil that are available to the human gastrointestinal system. A reasonable approach is to develop in-vitro methods that simulate the complex and dynamic human gastrointestinal system and correlate well with the results of in-vivo method. Thus this study aims in addressing the potential of one such in-vitro method developed by our research group in assessing the bioavailability of soil-As. Two soils with drastically different chemical characteristics in regards to As reactivity (Immokalee-low As retention capacity; Millhopper-high As retention capacity) spiked with a pesticide (sodium arsenate) were used. Soils were amended at two rates representing concentrations typically found at Superfund sites: 675 and 1500 mg/kg of As. In-vitro bioavailability experiments were performed in order to obtain an estimate of the amount of As likely to be available in the human gastrointestinal system as well as the fraction potentially absorbed onto the intestinal linings. Following the in-vitro study selective in-vivo bioavailability studies using As-contaminated soils were conducted on male and female mice to validate the in-vitro results via comparison with the in-vivo data. Soils were administered orally to the BALB/c mice immediately after spiking. Treatments comprised of a soil group (As in soil), a positive control group (only As) and a negative control group (no soil, no As). Blood samples were collected at different time periods to determine As concentrations. Correlation between the in-vitro and in-vivo data was determined. Information obtained from this study will serve as the first step towards the future development of a semi-quantitative model for predicting bioavailable As. This in turn will result in designing appropriate, cost-effective remedial strategies for As contaminated sites. Keywords: Bioavailability, In-vitro, In-vivo, Arsenic, Soil, Risk Assessment

Reducing Contingency through Sampling at the Luckey FUSRAP Site - 13186

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

Frothingham, David; Barker, Michelle; Buechi, Steve

2013-07-01

Typically, the greatest risk in developing accurate cost estimates for the remediation of hazardous, toxic, and radioactive waste sites is the uncertainty in the estimated volume of contaminated media requiring remediation. Efforts to address this risk in the remediation cost estimate can result in large cost contingencies that are often considered unacceptable when budgeting for site cleanups. Such was the case for the Luckey Formerly Utilized Sites Remedial Action Program (FUSRAP) site near Luckey, Ohio, which had significant uncertainty surrounding the estimated volume of site soils contaminated with radium, uranium, thorium, beryllium, and lead. Funding provided by the American Recoverymore » and Reinvestment Act (ARRA) allowed the U.S. Army Corps of Engineers (USACE) to conduct additional environmental sampling and analysis at the Luckey Site between November 2009 and April 2010, with the objective to further delineate the horizontal and vertical extent of contaminated soils in order to reduce the uncertainty in the soil volume estimate. Investigative work included radiological, geophysical, and topographic field surveys, subsurface borings, and soil sampling. Results from the investigative sampling were used in conjunction with Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software to update the contaminated soil volume estimate for the site. This updated volume estimate was then used to update the project cost-to-complete estimate using the USACE Cost and Schedule Risk Analysis process, which develops cost contingencies based on project risks. An investment of $1.1 M of ARRA funds for additional investigative work resulted in a reduction of 135,000 in-situ cubic meters (177,000 in-situ cubic yards) in the estimated base volume estimate. This refinement of the estimated soil volume resulted in a $64.3 M reduction in the estimated project cost-to-complete, through a reduction in the uncertainty in the contaminated soil volume estimate and the associated contingency costs. (authors)« less

Remotely monitoring evaporation rate and soil water status using thermal imaging and "three-temperatures model (3T Model)" under field-scale conditions.

PubMed

Qiu, Guo Yu; Zhao, Ming

2010-03-01

Remote monitoring of soil evaporation and soil water status is necessary for water resource and environment management. Ground based remote sensing can be the bridge between satellite remote sensing and ground-based point measurement. The primary object of this study is to provide an algorithm to estimate evaporation and soil water status by remote sensing and to verify its accuracy. Observations were carried out in a flat field with varied soil water content. High-resolution thermal images were taken with a thermal camera; soil evaporation was measured with a weighing lysimeter; weather data were recorded at a nearby meteorological station. Based on the thermal imaging and the three-temperatures model (3T model), we developed an algorithm to estimate soil evaporation and soil water status. The required parameters of the proposed method were soil surface temperature, air temperature, and solar radiation. By using the proposed method, daily variation in soil evaporation was estimated. Meanwhile, soil water status was remotely monitored by using the soil evaporation transfer coefficient. Results showed that the daily variation trends of measured and estimated evaporation agreed with each other, with a regression line of y = 0.92x and coefficient of determination R(2) = 0.69. The simplicity of the proposed method makes the 3T model a potentially valuable tool for remote sensing.

When bulk density methods matter: Implications for estimating soil organic carbon pools in rocky soils

USDA-ARS?s Scientific Manuscript database

Resolving uncertainty in the carbon cycle is paramount to refining climate predictions. Soil organic carbon (SOC) is a major component of terrestrial C pools, and accuracy of SOC estimates are only as good as the measurements and assumptions used to obtain them. Dryland soils account for a substanti...

Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia

USDA-ARS?s Scientific Manuscript database

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...

Evaluation of HCMM data for assessing soil moisture and water table depth. [South Dakota

NASA Technical Reports Server (NTRS)

Moore, D. G.; Heilman, J. L.; Tunheim, J. A.; Westin, F. C.; Heilman, W. E.; Beutler, G. A.; Ness, S. D. (Principal Investigator)

1981-01-01

Soil moisture in the 0-cm to 4-cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop in eastern South Dakota. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the soil temperature. Corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. Shallow alluvial aquifers were located with HCMM predawn data. After correcting the data for vegetation differences, equations were developed for predicting water table depths within the aquifer. A finite difference code simulating soil moisture and soil temperature shows that soils with different moisture profiles differed in soil temperatures in a well defined functional manner. A significant surface thermal anomaly was found to be associated with shallow water tables.

Soil moisture estimation using reflected solar and emitted thermal infrared radiation

NASA Technical Reports Server (NTRS)

Jackson, R. D.; Cihlar, J.; Estes, J. E.; Heilman, J. L.; Kahle, A.; Kanemasu, E. T.; Millard, J.; Price, J. C.; Wiegand, C. L.

1978-01-01

Classical methods of measuring soil moisture such as gravimetric sampling and the use of neutron moisture probes are useful for cases where a point measurement is sufficient to approximate the water content of a small surrounding area. However, there is an increasing need for rapid and repetitive estimations of soil moisture over large areas. Remote sensing techniques potentially have the capability of meeting this need. The use of reflected-solar and emitted thermal-infrared radiation, measured remotely, to estimate soil moisture is examined.

Mouse Assay for Determination of Arsenic Bioavailability in Contaminated Soils

EPA Science Inventory

Background: Accurate assessment of human exposure estimates from arsenic-contaminated soils depends upon estimating arsenic (As) soil bioavailability. Development of bioavailability assays provides data needed for human health risk assessments and supports development and valida...

Estimation of bare soil evaporation using multifrequency airborne SAR

NASA Technical Reports Server (NTRS)

Soares, Joao V.; Shi, Jiancheng; Van Zyl, Jakob; Engman, E. T.

1992-01-01

It is shown that for homogeneous areas soil moisture can be derived from synthetic aperture radar (SAR) measurements, so that the use of microwave remote sensing can given realistic estimates of energy fluxes if coupled to a simple two-layer model repesenting the soil. The model simulates volumetric water content (Wg) using classical meterological data, provided that some of the soil thermal and hydraulic properties are known. Only four parameters are necessary: mean water content, thermal conductivity and diffusitivity, and soil resistance to evaporation. They may be derived if a minimal number of measured values of Wg and surface layer temperature (Tg) are available together with independent measurements of energy flux to compare with the estimated values. The estimated evaporation is shown to be realistic and in good agreement with drying stage theory in which the transfer of water in the soil is in vapor form.

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.

Using remote sensing and GIS techniques to estimate discharge and recharge. fluxes for the Death Valley regional groundwater flow system, USA

USGS Publications Warehouse

D'Agnese, F. A.; Faunt, C.C.; Keith, Turner A.

1996-01-01

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

Estimating soil hydraulic parameters from transient flow experiments in a centrifuge using parameter optimization technique

USGS Publications Warehouse

Šimůnek, Jirka; Nimmo, John R.

2005-01-01

A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time‐variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field.

Detection of soil erosion within pinyon-juniper woodlands using Thematic Mapper (TM) data

NASA Technical Reports Server (NTRS)

Price, Kevin P.

1993-01-01

Multispectral measurements collected by Landsat Thematic Mapper (TM) were correlated with field measurements, direct soil loss estimates, and Universal Soil Loss Equation (USLE) estimates to determine the sensitivity of TM data to varying degrees of soil erosion in pinyon-juniper woodland in central Utah. TM data were also evaluated as a predictor of the USLE Crop Management C factor for pinyon-juniper woodlands. TM spectral data were consistently better predictors of soil erosion factors than any combination of field factors. TM data were more sensitive to vegetation variations than the USLE C factor. USLE estimates showed low annual rates of erosion which varied little among the study sites. Direct measurements of rate of soil loss using the SEDIMENT (Soil Erosion DIrect measureMENT) technique, indicated high and varying rates of soil loss among the sites since tree establishment. Erosion estimates from the USLE and SEDIMENT methods suggest that erosion rates have been severe in the past, but because significant amounts of soil have already been eroded, and the surface is now armored by rock debris, present erosion rates are lower. Indicators of accelerated erosion were still present on all sites, however, suggesting that the USLE underestimated erosion within the study area.

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.

A comparison of the abilities of the USLE-M, RUSLE2 and WEPP to model event erosion from bare fallow areas.

PubMed

Kinnell, P I A

2017-10-15

Traditionally, the Universal Soil Loss Equation (USLE) and the revised version of it (RUSLE) have been applied to predicting the long term average soil loss produced by rainfall erosion in many parts of the world. Overtime, it has been recognized that there is a need to predict soil losses over shorter time scales and this has led to the development of WEPP and RUSLE2 which can be used to predict soil losses generated by individual rainfall events. Data currently exists that enables the RUSLE2, WEPP and the USLE-M to estimate historic soil losses from bare fallow runoff and soil loss plots recorded in the USLE database. Comparisons of the abilities of the USLE-M and RUSLE2 to estimate event soil losses from bare fallow were undertaken under circumstances where both models produced the same total soil loss as observed for sets of erosion events on 4 different plots at 4 different locations. Likewise, comparisons of the abilities of the USLE-M and WEPP to model event soil loss from bare fallow were undertaken for sets of erosion events on 4 plots at 4 different locations. Despite being calibrated specifically for each plot, WEPP produced the worst estimates of event soil loss for all the 4 plots. Generally, the USLE-M using measured runoff to calculate the product of the runoff ratio, storm kinetic energy and the maximum 30-minute rainfall intensity produced the best estimates. As to be expected, ability of the USLE-M to estimate event soil loss was reduced when runoff predicted by either RUSLE2 or WEPP was used. Despite this, the USLE-M using runoff predicted by WEPP estimated event soil loss better than WEPP. RUSLE2 also outperformed WEPP. Copyright © 2017 Elsevier B.V. All rights reserved.

Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff-erosion model in the Mamuaba catchment, Brazil.

PubMed

Marques da Silva, Richarde; Guimarães Santos, Celso Augusto; Carneiro de Lima Silva, Valeriano; Pereira e Silva, Leonardo

2013-11-01

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (<6 t ha(-1) year(-1)) and, in 20% of the catchment, the soil erosion was estimated to exceed > 12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.

Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

NASA Astrophysics Data System (ADS)

Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

2013-04-01

The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

Uncertainty in predicting soil hydraulic properties at the hillslope scale with indirect methods

NASA Astrophysics Data System (ADS)

Chirico, G. B.; Medina, H.; Romano, N.

2007-02-01

SummarySeveral hydrological applications require the characterisation of the soil hydraulic properties at large spatial scales. Pedotransfer functions (PTFs) are being developed as simplified methods to estimate soil hydraulic properties as an alternative to direct measurements, which are unfeasible for most practical circumstances. The objective of this study is to quantify the uncertainty in PTFs spatial predictions at the hillslope scale as related to the sampling density, due to: (i) the error in estimated soil physico-chemical properties and (ii) PTF model error. The analysis is carried out on a 2-km-long experimental hillslope in South Italy. The method adopted is based on a stochastic generation of patterns of soil variables using sequential Gaussian simulation, conditioned to the observed sample data. The following PTFs are applied: Vereecken's PTF [Vereecken, H., Diels, J., van Orshoven, J., Feyen, J., Bouma, J., 1992. Functional evaluation of pedotransfer functions for the estimation of soil hydraulic properties. Soil Sci. Soc. Am. J. 56, 1371-1378] and HYPRES PTF [Wösten, J.H.M., Lilly, A., Nemes, A., Le Bas, C., 1999. Development and use of a database of hydraulic properties of European soils. Geoderma 90, 169-185]. The two PTFs estimate reliably the soil water retention characteristic even for a relatively coarse sampling resolution, with prediction uncertainties comparable to the uncertainties in direct laboratory or field measurements. The uncertainty of soil water retention prediction due to the model error is as much as or more significant than the uncertainty associated with the estimated input, even for a relatively coarse sampling resolution. Prediction uncertainties are much more important when PTF are applied to estimate the saturated hydraulic conductivity. In this case model error dominates the overall prediction uncertainties, making negligible the effect of the input error.

Impact of Land Use Change to the Soil Erosion Estimation for Cultural Landscapes: Case Study of Paphos Disrict in Cyprus

NASA Astrophysics Data System (ADS)

Cuca, B.; Agapiou, A.

2017-05-01

In 2006 UNESCO report has identified soil loss as one of the main threats of climate change with possible impact to natural and cultural heritage. The study illustrated in this paper shows the results from geomatic perspective, applying an interdisciplinary approach undertaken in order to identify major natural hazards affecting cultural landscapes and archaeological heritage in rural areas in Cyprus. In particular, Earth Observation (EO) and ground-based methods were identified and applied for mapping, monitoring and estimation of the possible soil loss caused by soil erosion. Special attention was given to the land use/land cover factor (C) and its impact on the overall estimation of the soil-loss. Cover factor represents the effect of soil-disturbing activities, plants, crop sequence and productivity level, soil cover and subsurface bio-mass on soil erosion. Urban areas have a definite role in retarding the recharge process, leading to increased runoff and soil loss in the broader area. On the other hand, natural vegetation plays a predominant role in reducing water erosion. The land use change was estimated based on the difference of the NDVI value between Landsat 5 TM and Sentinel-2 data for the period between 1980s' until today. Cover factor was then estimated for both periods and significant land use changes were further examined in areas of significant cultural and natural landscape value. The results were then compared in order to study the impact of land use change on the soil erosion and hence on the soil loss rate in the selected areas.

Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

NASA Astrophysics Data System (ADS)

Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

2017-12-01

In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four times a day) data to verify the relation between the image hue and the soil moisture for reliable moisture estimated model. And it is better to use the digital single lens reflex camera to prevent the deformation of the image and to have a better auto exposure. Keywords: soil, moisture, remote sensing

Sediment composition for the assessment of water erosion and nonpoint source pollution in natural and fire-affected landscapes.

PubMed

Carkovic, Athena B; Pastén, Pablo A; Bonilla, Carlos A

2015-04-15

Water erosion is a leading cause of soil degradation and a major nonpoint source pollution problem. Many efforts have been undertaken to estimate the amount and size distribution of the sediment leaving the field. Multi-size class water erosion models subdivide eroded soil into different sizes and estimate the aggregate's composition based on empirical equations derived from agricultural soils. The objective of this study was to evaluate these equations on soil samples collected from natural landscapes (uncultivated) and fire-affected soils. Chemical, physical, and soil fractions and aggregate composition analyses were performed on samples collected in the Chilean Patagonia and later compared with the equations' estimates. The results showed that the empirical equations were not suitable for predicting the sediment fractions. Fine particles, including primary clay, primary silt, and small aggregates (<53 μm) were over-estimated, and large aggregates (>53 μm) and primary sand were under-estimated. The uncultivated and fire-affected soils showed a reduced fraction of fine particles in the sediment, as clay and silt were mostly in the form of large aggregates. Thus, a new set of equations was developed for these soils, where small aggregates were defined as particles with sizes between 53 μm and 250 μm and large aggregates as particles>250 μm. With r(2) values between 0.47 and 0.98, the new equations provided better estimates for primary sand and large aggregates. The aggregate's composition was also well predicted, especially the silt and clay fractions in the large aggregates from uncultivated soils (r(2)=0.63 and 0.83, respectively) and the fractions of silt in the small aggregates (r(2)=0.84) and clay in the large aggregates (r(2)=0.78) from fire-affected soils. Overall, these new equations proved to be better predictors for the sediment and aggregate's composition in uncultivated and fire-affected soils, and they reduce the error when estimating soil loss in natural landscapes. Copyright © 2015 Elsevier B.V. All rights reserved.

Iron and silicon isotope behaviour accompanying weathering in Icelandic soils, and the implications for iron export from peatlands

NASA Astrophysics Data System (ADS)

Opfergelt, S.; Williams, H. M.; Cornelis, J. T.; Guicharnaud, R. A.; Georg, R. B.; Siebert, C.; Gislason, S. R.; Halliday, A. N.; Burton, K. W.

2017-11-01

Incipient warming of peatlands at high latitudes is expected to modify soil drainage and hence the redox conditions, which has implications for Fe export from soils. This study uses Fe isotopes to assess the processes controlling Fe export in a range of Icelandic soils including peat soils derived from the same parent basalt, where Fe isotope variations principally reflect differences in weathering and drainage. In poorly weathered, well-drained soils (non-peat soils), the limited Fe isotope fractionation in soil solutions relative to the bulk soil (Δ57Fesolution-soil = -0.11 ± 0.12‰) is attributed to proton-promoted mineral dissolution. In the more weathered poorly drained soils (peat soils), the soil solutions are usually lighter than the bulk soil (Δ57Fesolution-soil = -0.41 ± 0.32‰), which indicates that Fe has been mobilised by reductive mineral dissolution and/or ligand-controlled dissolution. The results highlight the presence of Fe-organic complexes in solution in anoxic conditions. An additional constraint on soil weathering is provided by Si isotopes. The Si isotope composition of the soil solutions relative to the soil (Δ30Sisolution-soil = 0.92 ± 0.26‰) generally reflects the incorporation of light Si isotopes in secondary aluminosilicates. Under anoxic conditions in peat soils, the largest Si isotope fractionation in soil solutions relative to the bulk soil is observed (Δ30Sisolution-soil = 1.63 ± 0.40‰) and attributed to the cumulative contribution of secondary clay minerals and amorphous silica precipitation. Si supersaturation in solution with respect to amorphous silica is reached upon freezing when Al availability to form aluminosilicates is limited by the affinity of Al for metal-organic complexes. Therefore, the precipitation of amorphous silica in peat soils indirectly supports the formation of metal-organic complexes in poorly drained soils. These observations highlight that in a scenario of decreasing soil drainage with warming high latitude peatlands, Fe export from soils as Fe-organic complexes will increase, which in turn has implications for Fe transport in rivers, and ultimately the delivery of Fe to the oceans.

Worldwide organic soil carbon and nitrogen data

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

Zinke, P.J.; Stangenberger, A.G.; Post, W.M.

The objective of the research presented in this package was to identify data that could be used to estimate the size of the soil organic carbon pool under relatively undisturbed soil conditions. A subset of the data can be used to estimate amounts of soil carbon storage at equilibrium with natural soil-forming factors. The magnitude of soil properties so defined is a resulting nonequilibrium values for carbon storage. Variation in these values is due to differences in local and geographic soil-forming factors. Therefore, information is included on location, soil nitrogen content, climate, and vegetation along with carbon density and variation.

Carbon sequestration potential of soils in southeast Germany derived from stable soil organic carbon saturation.

PubMed

Wiesmeier, Martin; Hübner, Rico; Spörlein, Peter; Geuß, Uwe; Hangen, Edzard; Reischl, Arthur; Schilling, Bernd; von Lützow, Margit; Kögel-Knabner, Ingrid

2014-02-01

Sequestration of atmospheric carbon (C) in soils through improved management of forest and agricultural land is considered to have high potential for global CO2 mitigation. However, the potential of soils to sequester soil organic carbon (SOC) in a stable form, which is limited by the stabilization of SOC against microbial mineralization, is largely unknown. In this study, we estimated the C sequestration potential of soils in southeast Germany by calculating the potential SOC saturation of silt and clay particles according to Hassink [Plant and Soil 191 (1997) 77] on the basis of 516 soil profiles. The determination of the current SOC content of silt and clay fractions for major soil units and land uses allowed an estimation of the C saturation deficit corresponding to the long-term C sequestration potential. The results showed that cropland soils have a low level of C saturation of around 50% and could store considerable amounts of additional SOC. A relatively high C sequestration potential was also determined for grassland soils. In contrast, forest soils had a low C sequestration potential as they were almost C saturated. A high proportion of sites with a high degree of apparent oversaturation revealed that in acidic, coarse-textured soils the relation to silt and clay is not suitable to estimate the stable C saturation. A strong correlation of the C saturation deficit with temperature and precipitation allowed a spatial estimation of the C sequestration potential for Bavaria. In total, about 395 Mt CO2 -equivalents could theoretically be stored in A horizons of cultivated soils - four times the annual emission of greenhouse gases in Bavaria. Although achieving the entire estimated C storage capacity is unrealistic, improved management of cultivated land could contribute significantly to CO2 mitigation. Moreover, increasing SOC stocks have additional benefits with respect to enhanced soil fertility and agricultural productivity. © 2013 John Wiley & Sons Ltd.

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

Crop moisture estimation over the southern Great Plains with dual polarization 1.66 centimeter passive microwave data from Nimbus 7

NASA Technical Reports Server (NTRS)

Mcfarland, M. J.; Harder, P. H., II; Wilke, G. D.; Huebner, G. L., Jr.

1984-01-01

Moisture content of snow-free, unfrozen soil is inferred using passive microwave brightness temperatures from the scanning multichannel microwave radiometer (SMMR) on Nimbus-7. Investigation is restricted to the two polarizations of the 1.66 cm wavelength sensor. Passive microwave estimates of soil moisture are of two basic categories; those based upon soil emissivity and those based upon the polarization of soil emission. The two methods are compared and contrasted through the investigation of 54 potential functions of polarized brightness temperatures and, in some cases, ground-based temperature measurements. Of these indices, three are selected for the estimated emissivity, the difference between polarized brightness temperatures, and the normalized polarization difference. Each of these indices is about equally effective for monitoring soil moisture. Using an antecedent precipitation index (API) as ground control data, temporal and spatial analyses show that emissivity data consistently give slightly better soil moisture estimates than depolarization data. The difference, however, is not statistically significant. It is concluded that polarization data alone can provide estimates of soil moisture in areas where the emissivity cannot be inferred due to nonavailability of surface temperature data.

Improved exposure estimation in soil screening and cleanup criteria for volatile organic chemicals.

PubMed

DeVaull, George E

2017-09-01

Soil cleanup criteria define acceptable concentrations of organic chemical constituents for exposed humans. These criteria sum the estimated soil exposure over multiple pathways. Assumptions for ingestion, dermal contact, and dust exposure generally presume a chemical persists in surface soils at a constant concentration level for the entire exposure duration. For volatile chemicals, this is an unrealistic assumption. A calculation method is presented for surficial soil criteria that include volatile depletion of chemical for these uptake pathways. The depletion estimates compare favorably with measured concentration profiles and with field measurements of soil concentration. Corresponding volatilization estimates compare favorably with measured data for a wide range of volatile and semivolatile chemicals, including instances with and without the presence of a mixed-chemical residual phase. Selected examples show application of the revised factors in estimating screening levels for benzene in surficial soils. Integr Environ Assess Manag 2017;13:861-869. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Inducing in situ, nonlinear soil response applying an active source

USGS Publications Warehouse

Johnson, P.A.; Bodin, P.; Gomberg, J.; Pearce, F.; Lawrence, Z.; Menq, F.-Y.

2009-01-01

[1] It is well known that soil sites have a profound effect on ground motion during large earthquakes. The complex structure of soil deposits and the highly nonlinear constitutive behavior of soils largely control nonlinear site response at soil sites. Measurements of nonlinear soil response under natural conditions are critical to advancing our understanding of soil behavior during earthquakes. Many factors limit the use of earthquake observations to estimate nonlinear site response such that quantitative characterization of nonlinear behavior relies almost exclusively on laboratory experiments and modeling of wave propagation. Here we introduce a new method for in situ characterization of the nonlinear behavior of a natural soil formation using measurements obtained immediately adjacent to a large vibrator source. To our knowledge, we are the first group to propose and test such an approach. Employing a large, surface vibrator as a source, we measure the nonlinear behavior of the soil by incrementally increasing the source amplitude over a range of frequencies and monitoring changes in the output spectra. We apply a homodyne algorithm for measuring spectral amplitudes, which provides robust signal-to-noise ratios at the frequencies of interest. Spectral ratios are computed between the receivers and the source as well as receiver pairs located in an array adjacent to the source, providing the means to separate source and near-source nonlinearity from pervasive nonlinearity in the soil column. We find clear evidence of nonlinearity in significant decreases in the frequency of peak spectral ratios, corresponding to material softening with amplitude, observed across the array as the source amplitude is increased. The observed peak shifts are consistent with laboratory measurements of soil nonlinearity. Our results provide constraints for future numerical modeling studies of strong ground motion during earthquakes.

Hydrologic characterization of desert soils with varying degrees of pedogenesis: 2. Inverse modeling for eff ective properties

USGS Publications Warehouse

Mirus, B.B.; Perkins, K.S.; Nimmo, J.R.; Singha, K.

2009-01-01

To understand their relation to pedogenic development, soil hydraulic properties in the Mojave Desert were investi- gated for three deposit types: (i) recently deposited sediments in an active wash, (ii) a soil of early Holocene age, and (iii) a highly developed soil of late Pleistocene age. Eff ective parameter values were estimated for a simplifi ed model based on Richards' equation using a fl ow simulator (VS2D), an inverse algorithm (UCODE-2005), and matric pressure and water content data from three ponded infi ltration experiments. The inverse problem framework was designed to account for the eff ects of subsurface lateral spreading of infi ltrated water. Although none of the inverse problems converged on a unique, best-fi t parameter set, a minimum standard error of regression was reached for each deposit type. Parameter sets from the numerous inversions that reached the minimum error were used to develop probability distribu tions for each parameter and deposit type. Electrical resistance imaging obtained for two of the three infi ltration experiments was used to independently test fl ow model performance. Simulations for the active wash and Holocene soil successfully depicted the lateral and vertical fl uxes. Simulations of the more pedogenically developed Pleistocene soil did not adequately replicate the observed fl ow processes, which would require a more complex conceptual model to include smaller scale heterogeneities. The inverse-modeling results, however, indicate that with increasing age, the steep slope of the soil water retention curve shitis toward more negative matric pressures. Assigning eff ective soil hydraulic properties based on soil age provides a promising framework for future development of regional-scale models of soil moisture dynamics in arid environments for land-management applications. ?? Soil Science Society of America.

Relative Bioavailability and Bioaccessability and Speciation of Arsenic in Contaminated Soils

EPA Science Inventory

Background: Assessment of soil arsenic (As) bioavailability may profoundly affect the extent of remediation required at contaminated sites by improving human exposure estimates. Because small adjustments in soil As bioavailability estimates can significantly alter risk assessment...

Nutrient Estimation Using Subsurface Sensing Methods

USDA-ARS?s Scientific Manuscript database

This report investigates the use of precision management techniques for measuring soil conductivity on feedlot surfaces to estimate nutrient value for crop production. An electromagnetic induction soil conductivity meter was used to collect apparent soil electrical conductivity (ECa) from feedlot p...

An objective analysis of the dynamic nature of field capacity

NASA Astrophysics Data System (ADS)

Twarakavi, Navin K. C.; Sakai, Masaru; Å Imå¯Nek, Jirka

2009-10-01

Field capacity is one of the most commonly used, and yet poorly defined, soil hydraulic properties. Traditionally, field capacity has been defined as the amount of soil moisture after excess water has drained away and the rate of downward movement has materially decreased. Unfortunately, this qualitative definition does not lend itself to an unambiguous quantitative approach for estimation. Because of the vagueness in defining what constitutes "drainage of excess water" from a soil, the estimation of field capacity has often been based upon empirical guidelines. These empirical guidelines are either time, pressure, or flux based. In this paper, we developed a numerical approach to estimate field capacity using a flux-based definition. The resulting approach was implemented on the soil parameter data set used by Schaap et al. (2001), and the estimated field capacity was compared to traditional definitions of field capacity. The developed modeling approach was implemented using the HYDRUS-1D software with the capability of simultaneously estimating field capacity for multiple soils with soil hydraulic parameter data. The Richards equation was used in conjunction with the van Genuchten-Mualem model to simulate variably saturated flow in a soil. Using the modeling approach to estimate field capacity also resulted in additional information such as (1) the pressure head, at which field capacity is attained, and (2) the drainage time needed to reach field capacity from saturated conditions under nonevaporative conditions. We analyzed the applicability of the modeling-based approach to estimate field capacity on real-world soils data. We also used the developed method to create contour diagrams showing the variation of field capacity with texture. It was found that using benchmark pressure heads to estimate field capacity from the retention curve leads to inaccurate results. Finally, a simple analytical equation was developed to predict field capacity from soil hydraulic parameter information. The analytical equation was found to be effective in its ability to predict field capacities.

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.

The distribution of soil phosphorus for global biogeochemical modeling

DOE PAGES

Yang, Xiaojuan; Post, Wilfred M.; Thornton, Peter E.; ...

2013-04-16

We discuss that phosphorus (P) is a major element required for biological activity in terrestrial ecosystems. Although the total P content in most soils can be large, only a small fraction is available or in an organic form for biological utilization because it is bound either in incompletely weathered mineral particles, adsorbed on mineral surfaces, or, over the time of soil formation, made unavailable by secondary mineral formation (occluded). In order to adequately represent phosphorus availability in global biogeochemistry–climate models, a representation of the amount and form of P in soils globally is required. We develop an approach that buildsmore » on existing knowledge of soil P processes and databases of parent material and soil P measurements to provide spatially explicit estimates of different forms of naturally occurring soil P on the global scale. We assembled data on the various forms of phosphorus in soils globally, chronosequence information, and several global spatial databases to develop a map of total soil P and the distribution among mineral bound, labile, organic, occluded, and secondary P forms in soils globally. The amount of P, to 50cm soil depth, in soil labile, organic, occluded, and secondary pools is 3.6 ± 3, 8.6 ± 6, 12.2 ± 8, and 3.2 ± 2 Pg P (Petagrams of P, 1 Pg = 1 × 10 15g) respectively. The amount in soil mineral particles to the same depth is estimated at 13.0 ± 8 Pg P for a global soil total of 40.6 ± 18 Pg P. The large uncertainty in our estimates reflects our limited understanding of the processes controlling soil P transformations during pedogenesis and a deficiency in the number of soil P measurements. In spite of the large uncertainty, the estimated global spatial variation and distribution of different soil P forms presented in this study will be useful for global biogeochemistry models that include P as a limiting element in biological production by providing initial estimates of the available soil P for plant uptake and microbial utilization.« less

Seasonal Variation in Soil Microbial Biomass, Bacterial Community Composition and Extracellular Enzyme Activity in Relation to Soil Respiration in a Northern Great Plains Grassland

NASA Astrophysics Data System (ADS)

Wilton, E.; Flanagan, L. B.

2014-12-01

Soil respiration rate is affected by seasonal changes in temperature and moisture, but is this a direct effect on soil metabolism or an indirect effect caused by changes in microbial biomass, bacterial community composition and substrate availability? In order to address this question, we compared continuous measurements of soil and plant CO2 exchange made with an automatic chamber system to analyses conducted on replicate soil samples collected on four dates during June-August. Microbial biomass was estimated from substrate-induced respiration rate, bacterial community composition was determined by 16S rRNA amplicon pyrosequencing, and β-1,4-N-acetylglucosaminidase (NAGase) and phenol oxidase enzyme activities were assayed fluorometrically or by absorbance measurements, respectively. Soil microbial biomass declined from June to August in strong correlation with a progressive decline in soil moisture during this time period. Soil bacterial species richness and alpha diversity showed no significant seasonal change. However, bacterial community composition showed a progressive shift over time as measured by Bray-Curtis dissimilarity. In particular, the change in community composition was associated with increasing relative abundance in the alpha and delta classes, and declining abundance of the beta and gamma classes of the Proteobacteria phylum during June-August. NAGase showed a progressive seasonal decline in potential activity that was correlated with microbial biomass and seasonal changes in soil moisture. In contrast, phenol oxidase showed highest potential activity in mid-July near the time of peak soil respiration and ecosystem photosynthesis, which may represent a time of high input of carbon exudates into the soil from plant roots. This input of exudates may stimulate the activity of phenol oxidase, a lignolytic enzyme involved in the breakdown of soil organic matter. These analyses indicated that seasonal change in soil respiration is a complex interaction between temporal changes in soil environmental factors and biological changes in the plant and microbial community that affect soil respiratory metabolism.

Estimating soil water content from ground penetrating radar coarse root reflections

NASA Astrophysics Data System (ADS)

Liu, X.; Cui, X.; Chen, J.; Li, W.; Cao, X.

2016-12-01

Soil water content (SWC) is an indispensable variable for understanding the organization of natural ecosystems and biodiversity. Especially in semiarid and arid regions, soil moisture is the plants primary source of water and largely determine their strategies for growth and survival, such as root depth, distribution and competition between them. Ground penetrating radar (GPR), a kind of noninvasive geophysical technique, has been regarded as an accurate tool for measuring soil water content at intermediate scale in past decades. For soil water content estimation with surface GPR, fixed antenna offset reflection method has been considered to have potential to obtain average soil water content between land surface and reflectors, and provide high resolution and few measurement time. In this study, 900MHz surface GPR antenna was used to estimate SWC with fixed offset reflection method; plant coarse roots (with diameters greater than 5 mm) were regarded as reflectors; a kind of advanced GPR data interpretation method, HADA (hyperbola automatic detection algorithm), was introduced to automatically obtain average velocity by recognizing coarse root hyperbolic reflection signals on GPR radargrams during estimating SWC. In addition, a formula was deduced to determine interval average SWC between two roots at different depths as well. We examined the performance of proposed method on a dataset simulated under different scenarios. Results showed that HADA could provide a reasonable average velocity to estimate SWC without knowledge of root depth and interval average SWC also be determined. When the proposed method was applied to estimation of SWC on a real-field measurement dataset, a very small soil water content vertical variation gradient about 0.006 with depth was captured as well. Therefore, the proposed method could be used to estimate average soil water content from ground penetrating radar coarse root reflections and obtain interval average SWC between two roots at different depths. It is very promising for measuring root-zone-soil-moisture and mapping soil moisture distribution around a shrub or even in field plot scale.

SMAP Level 4 Surface and Root Zone Soil Moisture

NASA Technical Reports Server (NTRS)

Reichle, R.; De Lannoy, G.; Liu, Q.; Ardizzone, J.; Kimball, J.; Koster, R.

2017-01-01

The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m(exp. 3)m(exp. -3), measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture.

Estimation of Compaction Parameters Based on Soil Classification

NASA Astrophysics Data System (ADS)

Lubis, A. S.; Muis, Z. A.; Hastuty, I. P.; Siregar, I. M.

2018-02-01

Factors that must be considered in compaction of the soil works were the type of soil material, field control, maintenance and availability of funds. Those problems then raised the idea of how to estimate the density of the soil with a proper implementation system, fast, and economical. This study aims to estimate the compaction parameter i.e. the maximum dry unit weight (γ dmax) and optimum water content (Wopt) based on soil classification. Each of 30 samples were being tested for its properties index and compaction test. All of the data’s from the laboratory test results, were used to estimate the compaction parameter values by using linear regression and Goswami Model. From the research result, the soil types were A4, A-6, and A-7 according to AASHTO and SC, SC-SM, and CL based on USCS. By linear regression, the equation for estimation of the maximum dry unit weight (γdmax *)=1,862-0,005*FINES- 0,003*LL and estimation of the optimum water content (wopt *)=- 0,607+0,362*FINES+0,161*LL. By Goswami Model (with equation Y=mLogG+k), for estimation of the maximum dry unit weight (γdmax *) with m=-0,376 and k=2,482, for estimation of the optimum water content (wopt *) with m=21,265 and k=-32,421. For both of these equations a 95% confidence interval was obtained.

Dual-core mass-balance approach for evaluating mercury and210Pb atmospheric fallout and focusing to lakes

USGS Publications Warehouse

Van Metre, P.C.; Fuller, C.C.

2009-01-01

Determining atmospheric deposition rates of mercury and other contaminants using lake sediment cores requires a quantitative understanding of sediment focusing. Here we present a novel approach that solves mass-balance equations for two cores algebraically to estimate contaminant contributions to sediment from direct atmospheric fallout and from watershed and in-lake focusing. The model is applied to excess 210Pb and Hg in cores from Hobbs Lake, a high-altitude lake in Wyoming. Model results for excess 210Pb are consistent with estimates of fallout and focusing factors computed using excess 210Pb burdens in lake cores and soil cores from the watershed and model results for Hg fallout are consistent with fallout estimated using the soil-core-based 210Pb focusing factors. The lake cores indicate small increases in mercury deposition beginning in the late 1800s and large increases after 1940, with the maximum at the tops of the cores of 16-20 ??g/m 2year. These results suggest that global Hg emissions and possibly regional emissions in the western United States are affecting the north-central Rocky Mountains. Hg fallout estimates are generally consistent with fallout reported from an ice core from the nearby Upper Fremont Glacier, but with several notable differences. The model might not work for lakes with complex geometries and multiple sediment inputs, but for lakes with simple geometries, like Hobbs, it can provide a quantitative approach for evaluating sediment focusing and estimating contaminant fallout.

Computational scheme for the prediction of metal ion binding by a soil fulvic acid

USGS Publications Warehouse

Marinsky, J.A.; Reddy, M.M.; Ephraim, J.H.; Mathuthu, A.S.

1995-01-01

The dissociation and metal ion binding properties of a soil fulvic acid have been characterized. Information thus gained was used to compensate for salt and site heterogeneity effects in metal ion complexation by the fulvic acid. An earlier computational scheme has been modified by incorporating an additional step which improves the accuracy of metal ion speciation estimates. An algorithm is employed for the prediction of metal ion binding by organic acid constituents of natural waters (once the organic acid is characterized in terms of functional group identity and abundance). The approach discussed here, currently used with a spreadsheet program on a personal computer, is conceptually envisaged to be compatible with computer programs available for ion binding by inorganic ligands in natural waters.

Soil CO2 concentrations and efflux dynamics of a tree island in the Pantanal wetland

NASA Astrophysics Data System (ADS)

Lathuillière, Michael J.; Pinto, Osvaldo B.; Johnson, Mark S.; Jassal, Rachhpal S.; Dalmagro, Higo J.; Leite, Nei K.; Speratti, Alicia B.; Krampe, Daniela; Couto, Eduardo G.

2017-08-01

The Pantanal is the largest tropical wetland on the planet, and yet little information is available on the biome's carbon cycle. We used an automatic station to measure soil CO2 concentrations and oxidation-reduction potential over the 2014 and 2015 flood cycles of a tree island in the Pantanal that is immune to inundation during the wetland's annual flooding. The soil CO2 concentration profile was then used to estimate soil CO2 efflux over the two periods. In 2014, subsurface soil saturation at 0.30 m depth created conditions in that layer that led to CO2 buildup close to 200,000 ppm and soil oxidation-reduction potential below -300 mV, conditions that were not repeated in 2015 due to annual variability in soil saturation at the site. Mean CO2 efflux over the 2015 flood cycle was 0.023 ± 0.103 mg CO2-C m-2 s-1 representing a total annual efflux of 593 ± 2690 mg CO2-C m-2 y-1. Unlike a nearby tree island site that experiences full inundation during the wet season, here the soil dried quickly following repeated rain events throughout the year, which led to the release of CO2 pulses from the soil. This study highlights not only the complexity and heterogeneity in the Pantanal's carbon balance based on differences in topography, flood cycles, and vegetation but also the challenges of applying the gradient method in the Pantanal due to deviations from steady state conditions.

Mechanisms for Reduction of Natural Waters Technogenic Pollution by Metals due to Complexions with Humus Substances (Zoning: Western Siberia and the European Territory of Russia)

NASA Astrophysics Data System (ADS)

Dinu, M. I.

2017-11-01

The article described the complexation of metal ions with humus substances in natural waters (small lakes). Humus substances as the major biochemical components of natural water have a significant impact on the forms and migration of metals and the toxicity of natural objects. This article presents the results of large-scale chemical experiments: the study of the structural features (zonal aspects) of humus substances extracted from soil and water natural climatic zones (more than 300 objects) in Russia (European Russia and West Siberia); the influence of structural features on the physic-chemical parameters of humus acids and, in particular, on their complexing ability. The functional specifics of humus matter extracted from soils is estimated using spectrometric techniques. The conditional stability constants for Fe(III), Cu(II), Pb(II), Cd(II), Zn(II), Ni(II), Co(II), Mn(II), Cr(III), Ca(II), Mg(II), Sr(II), and Al(III) are experimentally determined with the electrochemical, spectroscopic analysis methods. The activities of metals are classified according to their affinity to humus compounds in soils and water. The determined conditional stability constants of the complexes are tested by model experiments, and it is demonstrated that Fe and Al ions have higher conditional stability constants than the ions of alkali earth metals, Pb, Cu, and Zn. Furthermore, the influence of aluminium ions and iron on the complexation of copper and lead as well as the influence of lead and copper on complexation of cobalt and nickel have been identified. The metal forms in a large number of lakes are calculated basing on the experiments’ results. The main chemical mechanisms of the distribution of metals by forms in the water of the lakes in European Russia and West Siberia are described.

Isotopic Expression of Soil Denitrification across Gradients in Nitrogen and Carbon Availability

NASA Astrophysics Data System (ADS)

Walker, R.; Houlton, B. Z.; Perakis, S. S.

2016-12-01

Denitrification removes biologically available nitrogen (N) from ecosystems, making it an important control over the biosphere's N balance, with implications for air quality, human health and climate change. Despite its importance, estimates of the global soil denitrification flux remain highly uncertain. Major challenges lie in directly measuring the gaseous by-products of denitrification and scaling this complex microbial processes in both space and time. Process-based models constrained by empirical isotopic evidence have emerged as a method to help overcome these challenges. These models use the terrestrial 15N budget, along with soil moisture and N input data, to quantify denitrification fluxes and its gaseous forms, including NO, N2O and N2. However, the robustness of this method is limited by incomplete understanding of isotopic expression of denitrification and how it varies across known controls, such as carbon (C) and nitrate (NO3) availability. Here, we present a quantitative assessment of the isotope effect expression of in situ soil denitrification across gradients in N and C concentrations. This experiment tests the hypothesis that isotopic expression of soil denitrification (a kinetic process) increases with NO3 availability (reaction substrate) and decreases with increasing availability of organic C (electron donor). To test the impact of NO3 availability on the isotope effect of denitrification, field incubations experiments were conducted across a natural soil N gradient, ranging from 0.11 to 0.69% N. Similarly, the impact of electron donor availability was tested by conducting field incubations across a natural soil C gradient ranging from 1.94 to 11.60%. Data show that in lower N sites, the percent of NO3 consumed during the incubation was higher, while C availability neither affected the fraction of NO3 consumed nor the rate of consumption. These findings suggest that greater NO3 concentrations allow for greater isotope expression of denitrification in soil, supporting the working hypothesis. These results will be complemented by laboratory experiments in which NO3 concentration, C availability, and temperature are systematically varied. Future goals include the incorporation of these data into existing models to improve estimates of global N fluxes.

Using the Mehlich-3 Soil Test as an Inexpensive Screening Tool to Estimate Total and Bioaccessible Lead in Urban Soils

EPA Science Inventory

In cities nationwide, urban agriculture has been put on hold because of the high costs of soil testing for historical contaminants such as lead (Pb). The Mehlich-3 soil test is commonly used to determine plant available nutrients, is inexpensive, and has the potential to estimate...

Soil moisture and properties estimation by assimilating soil temperatures using particle batch smoother: A new perspective for DTS

NASA Astrophysics Data System (ADS)

Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.

2015-12-01

Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.

The use of a hydrological physically based model to evaluate the vine adaptability to future climate: the case study of a Protected Designation of Origin area (DOC and DOCG) of Southern Italy

NASA Astrophysics Data System (ADS)

Bonfante, Antonello; Basile, Angelo; Menenti, Massimo; Monaco, Eugenia; Alfieri, Silvia Maria; Manna, Piero; Langella, Giuliano; De Lorenzi, Francesca

2013-04-01

The quality of grape and wine is variety-specific and depends significantly on the pedoclimatic conditions, thus from the terroir characteristics. In viticulture the concept of terroir is known to be very complex. At present some changes are occurring in the studies of terroir. Their spatial analysis is improving by means of studies that account for the spatial distribution of solar radiation and of bioclimatic indexes. Moreover, simulation models are used to study the water flow in the soil-plant-atmosphere system in order to determine the water balance of vines as a function of i) soil physical properties, ii) climatic regime and iii) agro-ecosystems characteristics. The future climate evolution may endanger not only yield production (IPCC, 2007), but also its quality. The effects on quality may be relevant for grape production, since they can affect the sustainability of the cultivation of grape varieties in the areas where they are currently grown. This study addresses this question by evaluating the adaptive capacity of grape's cultivars in a 20000 ha viticultural area in the "Valle Telesina" (Campania Region, Southern Italy). This area has a long tradition in the production of high quality wines (DOC and DOCG) and it is characterized by a complex geomorphology with a large variability of soils and micro-climate. Two climate scenarios were considered: "past" (1961-1990) and "future" (2021-2050), the latter constructed applying statistical downscaling to GCMs scenarios. For each climate scenario the moisture regime of the soils of the study area was calculated by means of a simulation model of the soil-water-atmosphere system (SWAP). The hydrological model SWAP was applied to the representative soils of the entire area (47 soil units); the soil hydraulic properties were estimated (by means of pedo-transfer function HYPRES) and measured. Upper boundary conditions were derived from the climate scenarios. Unit gradient in soil water potential was set as lower boundary condition. Crop-specific input data and model parameters were estimated on the basis of scientific literature and assumed to be generically representative of the species. Synthetic indicators of the regimes (e.g. crop evapotranspiration deficit - CWSI, available soil water content, soil temperature) were calculated and compared with thermal and water requirements of a set of grape varieties, including the ones currently cultivated in the area. As a result of the comparison, most varieties resulted adaptable to the future climate. For some cultivars (i.e. Catalanesca) a significant increase of suitable area is foreseen; in other cases (i.e. Aglianico and Falanghina) a slight reduction will occur. Moreover for the most important varieties actually cultivated (e.g. Aglianico, Falanghina, etc.) an analysis on the expected spatial migration due to the climate change was performed. Finally, an analysis of CWSI during different crop phenological stages was performed for both climate periods . The time course of the moisture regime in different soils was thus described; this analysis allowed to identify the soils where the water regime can positively affect grape (and wine) quality . The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Seasonal Variations in Sugar Contents and Microbial Community Behavior in a Ryegrass Soil

NASA Astrophysics Data System (ADS)

Medeiros, P. M.; Fernandes, M. F.; Dick, R. P.; Simoneit, B. R.

2004-12-01

Soil is a complex mixture of numerous inorganic and organic constituents that vary in size, shape, chemical constitution and reactivity, and hosts numerous organisms. Total sugars have been estimated to constitute 10% (average) of soil organic matter, occurring in living and decaying organisms, as well as in extracellular materials. The role of sugars in soils is attributed to their influence on soil structure, chemical processes, plant nutrition and microbial activity. The sources of sugars in soils are: a) plants (the primary source); b) animals (the minor source), and c) microorganisms (fungi, bacteria, algae), which decompose the primary plant and animal material, and synthesize the major part of soil carbohydrates. A particular soil sample provides a momentary glimpse into a dynamic system (continuous addition, degradation and synthesis) that might, except for seasonal variations, be in equilibrium. The purpose of this study is to identify and quantify the major sugars in a grass soil and characterize the relationship between their concentration variations and soil microbial behavior over an annual cycle. Soil samples were collected monthly in a ryegrass field close to Corvallis, Oregon, and analyzed by gas chromatography-mass spectrometry as total silylated extracts for sugar composition, and by gas chromatography-flame ionization as fatty acid methyl esters derived from phospholipids and neutral lipids (PLFA and NLFA, respectively). The preliminary results of the first six-month experiment (from January to June, 2004) show that as the ambient temperatures increase the sugar concentrations (glucose, fructose, sucrose and trehalose) also tend to increase in the soil. A decrease is observed in March when precipitation was low during the whole month. The same trend is observed for the active biomass of fungi and bacteria estimated by their fatty acids derived from phospholipids. Fatty acids 18:2ω 6c and 18:3ω 6c are used as fungal biomarkers. Branched (15:0i, 15:0a, 16:0i) and monounsaturated fatty acids (16:1ω 7c) are used as biomarkers for gram-positive and gram-negative bacteria, respectively. The contents of 18:2ω 6c and 18:3ω 6c from neutral lipids, which are used as an index of fungal storage, have a significant increase in June, similarly to the disaccharide trehalose. This increase in fungal lipid storage may have occurred in response to the large input of detrital carbon into the soil from cutting the grass early in that month.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

Impact of soil properties on selected pharmaceuticals adsorption in soils

NASA Astrophysics Data System (ADS)

Kodesova, Radka; Kocarek, Martin; Klement, Ales; Fer, Miroslav; Golovko, Oksana; Grabic, Roman; Jaksik, Ondrej

2014-05-01

The presence of human and veterinary pharmaceuticals in the environment has been recognized as a potential threat. Pharmaceuticals may contaminate soils and consequently surface and groundwater. Study was therefore focused on the evaluation of selected pharmaceuticals adsorption in soils, as one of the parameters, which are necessary to know when assessing contaminant transport in soils. The goals of this study were: (1) to select representative soils of the Czech Republic and to measure soil physical and chemical properties; (2) to measure adsorption isotherms of selected pharmaceuticals; (3) to evaluate impact of soil properties on pharmaceutical adsorptions and to propose pedotransfer rules for estimating adsorption coefficients from the measured soil properties. Batch sorption tests were performed for 6 selected pharmaceuticals (beta blockers Atenolol and Metoprolol, anticonvulsant Carbamazepin, and antibiotics Clarithromycin, Trimetoprim and Sulfamethoxazol) and 13 representative soils (soil samples from surface horizons of 11 different soil types and 2 substrates). The Freundlich equations were used to describe adsorption isotherms. The simple correlations between measured physical and chemical soil properties (soil particle density, soil texture, oxidable organic carbon content, CaCO3 content, pH_H2O, pH_KCl, exchangeable acidity, cation exchange capacity, hydrolytic acidity, basic cation saturation, sorption complex saturation, salinity), and the Freundlich adsorption coefficients were assessed using Pearson correlation coefficient. Then multiple-linear regressions were applied to predict the Freundlich adsorption coefficients from measured soil properties. The largest adsorption was measured for Clarithromycin (average value of 227.1) and decreased as follows: Trimetoprim (22.5), Metoprolol (9.0), Atenolol (6.6), Carbamazepin (2.7), Sulfamethoxazol (1.9). Absorption coefficients for Atenolol and Metoprolol closely correlated (R=0.85), and both were also related to absorption coefficients of Carbamazepin (R=0.67 and 0.68). Positive correlation was found between Trimetoprim absorption coefficients and Atenolol, Metoprolol or Carbamazepin absorption coefficients. The negative relationship was found between absorption coefficients of Sulfomethoxazol and Clarithromycin (R=-0.80). Sulfamethoxazol absorption coefficient was negatively related to pH_H2O, pH_KCL or sorption complex saturation and positively to the hydrolytic acidity or exchangeable acidity. Trimetoprim absorption coefficient was positively related to the oxidable organic carbon content, cation exchange capacity, basic cation saturation or silt content and negatively to particle density or sand content. Clarithromycin absorption coefficient was positively related to pH_H2O, pH_KCL, CaCO3 content, basic cation saturation or sorption complex saturation and negatively to hydrolytic acidity or exchangeable acidity. Atenolol and Metoprolol absorption coefficients were positively related to the oxidable organic carbon content, cation exchange capacity, basic cation saturation, salinity, clay content or silt content, and negatively to the particle density or sand content. Finally Carbamazepin absorption coefficient was positively related to the oxidable organic carbon content, cation exchange capacity or basic cation saturation, and negatively to the particle density or sand content. Evaluated pedotransfer rules for different pharmaceuticals included different sets of soil properties. Absorption coefficients could be predicted from: the hydrolytic acidity (Sulfamethoxazol), the oxidable organic carbon content (Trimetoprim and Carbamazepin), the oxidable organic carbon content, hydrolytic acidity and cation exchange capacity (Clarithromycin), the basic cation saturation (Atenolol and Metoprolol). Acknowledgement: Authors acknowledge the financial support of the Czech Science Foundation (Project No. 13-12477S).

Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation

NASA Astrophysics Data System (ADS)

Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara

2018-03-01

The soil water content profile is often well correlated with the soil moisture state near the surface. They share mutual information such that analysis of surface-only soil moisture is, at times and in conjunction with precipitation information, reflective of deeper soil fluxes and dynamics. This study examines the characteristic length scale, or effective depth Δz, of a simple active hydrological control volume. The volume is described only by precipitation inputs and soil water dynamics evident in surface-only soil moisture observations. To proceed, first an observation-based technique is presented to estimate the soil moisture loss function based on analysis of soil moisture dry-downs and its successive negative increments. Then, the length scale Δz is obtained via an optimization process wherein the root-mean-squared (RMS) differences between surface soil moisture observations and its predictions based on water balance are minimized. The process is entirely observation-driven. The surface soil moisture estimates are obtained from the NASA Soil Moisture Active Passive (SMAP) mission and precipitation from the gauge-corrected Climate Prediction Center daily global precipitation product. The length scale Δz exhibits a clear east-west gradient across the contiguous United States (CONUS), such that large Δz depths (>200 mm) are estimated in wetter regions with larger mean precipitation. The median Δz across CONUS is 135 mm. The spatial variance of Δz is predominantly explained and influenced by precipitation characteristics. Soil properties, especially texture in the form of sand fraction, as well as the mean soil moisture state have a lesser influence on the length scale.

Using an integrated approach between hydrological and crop models to assess surface water balance in ungauged basin

NASA Astrophysics Data System (ADS)

Negm, Amro; D'Agostino, Daniela; Lamaddalena, Nicola; Bacchi, Baldassare; Iacobellis, Vito

2013-04-01

In the last decades hydrological models have been extensively used in research fields in order to improve water balance assessment and to support integrated water resources management by quantifying the soil-plant-atmosphere interface. Due to complexity of the physical system, the mathematical models can generally represent and simulate only the basic components of the system. On the other hand, calibration and validation processes of the hydrological models in ungauged basins are still complex tasks, due to the lack of reliable methods and the uncertainty in representing the hydrological processes and the physical features of a basin. Therefore, in order to practically apply model's results, there is a continuous needing to assess their accuracy through the calibration and validation processes at gauged sites. In this context, an integrated approach is presented that couples a semi-distributed hydrological model called Distributed model for Runoff, Evapotranspiration, and Antecedent soil Moisture simulation (DREAM) with the FAO's Crop Water Productivity Simulation Model (AQUACROP). DREAM uses rainfall, Leaf Area Index (LAI) and potential evapotranspiration as inputs and streamflow, infiltration, real evapotranspiration, subsurface flow and deep percolation as outputs. Soil moisture content is accounted for as an internal variable. The simulations were done for Lama San Giorgio, a basin located in a wadi area in the central part of Apulia region (Southern Italy) for the period 2001-2005 and the meadow is mainly covered by durum wheat. According to ACLA2 project survey (Caliandro et al., 2005), the depth of the soil upper layers is about 80 cm. Calibration and validation of the DREAM model were carried out by assessing an accurate estimation of soil water content using AQUACROP model which is a more detailed model in terms of soil water dynamics. Instead, one of the most significant features of DREAM model is the evaluation of lateral flow exchanges by means of a redistribution function weighted by the wetness index. The calibration process was done by adjusting a specific parameter of the water balance, the subsurface flow (through a subsurface flow coefficient C), by exploiting the results of soil moisture content provided by AQUACROP model. Then, the outputs of daily soil water content obtained by DREAM model were compared with the estimations of soil behaviour provided by the AQUACROP model. The simulations were done for a certain number of cells in the study area, for different years. The chosen factors were used to obtain an average value of C in time and space, which in this study is equal to 0.5. Finally, the results of the DREAM model in terms of evapotranspiration provided a satisfactory approximation of those obtained by AQUACROP model, while the Canopy Cover, an output of AQUACROP, was compared with the LAI used as input for the DREAM model.

A Long-term Forest Fertilization Experiment to Understand Ecosystem Responses to Atmospheric Nitrogen Deposition

NASA Astrophysics Data System (ADS)

Baron, J.; Advani, S. M.; Allen, J.; Boot, C.; Denef, K.; Denning, S.; Hall, E.; Moore, J. C.; Reuth, H.; Ryan, M. G.; Shaw, E.

2016-12-01

Long-term field experiments can reveal changes in ecosystem processes that may not be evident in short-term studies. Short-term measurements or experiments may have narrower objectives or unrealistic treatments in order to see a change, whereas long-term studies can reveal complex interactions that take longer to manifest. We report results from a long-term experiment (1996 to present) in subalpine forests to simulate the consequences of sustained atmospheric nitrogen (N) deposition. Loch Vale watershed in Rocky Mountain National Park, the location of the experiment, has received an order of magnitude greater atmospheric N deposition than estimated background since mid-20th Century. Augmenting that, in 1996 we began adding 25 kg NH4NO3 ha-1 yr-1 to three 30m x 30m old-growth Engelmann spruce and subalpine fir plots. Treated stands were matched by nearby controls. N addition caused rapid leaching of nitrate and cations from soils, and increased N mineralization and nitrification rates. These observations in the fertilized plots have been sustained over time. Soluble aluminum concentrations do not differ significantly between fertilized and control plots, but treated soils are now markedly more acidic (pH of 4.7) than original soil and controls (pH of 5.1); further acidification might increase aluminum leaching. Effects on soil carbon were complex, mediated by reductions in total microbial biomass, decreases in arbuscular mychorrizal and saprotropic fungi, and increased potential rates of N enzyme degrading activities. Initial soil C:N of 24 was lower than similar soils in low N deposition stands (C:N of 36). The C:N declined to 22 with treatment. Fertilized plots lost 11% soil C, but the mechanism is unclear. We did not measure changes in C inputs from litter, microbial biomass, or plant uptake, but there was no change in summer CO2 flux, measured in 2003, 2004, and 2014. Leaching of DOC from fertilized plots was elevated throughout the experiment, providing one pathway for C loss. The soil microfauna was dominated by nematodes; plant parasites and bacterial and fungal feeders were more abundant in fertilized plots than in controls, with fewer predaceous and omnivorous nematodes. Overall, N fertilization altered soil biogeochemical characteristics, soil food webs, and C cycling.

Evaluation of scour potential of cohesive soils : final report, August 2009.

DOT National Transportation Integrated Search

2009-08-01

Prediction of scour at bridge river crossings is an evolving process. Hydraulic models to estimate water velocity and, therefore, the shear stresses that erode soil are reasonably well developed. The weak link remains methods for estimating soil erod...

Estimating the Pollution Risk of Cadmium in Soil Using a Composite Soil Environmental Quality Standard

PubMed Central

Huang, Biao; Zhao, Yongcun

2014-01-01

Estimating standard-exceeding probabilities of toxic metals in soil is crucial for environmental evaluation. Because soil pH and land use types have strong effects on the bioavailability of trace metals in soil, they were taken into account by some environmental protection agencies in making composite soil environmental quality standards (SEQSs) that contain multiple metal thresholds under different pH and land use conditions. This study proposed a method for estimating the standard-exceeding probability map of soil cadmium using a composite SEQS. The spatial variability and uncertainty of soil pH and site-specific land use type were incorporated through simulated realizations by sequential Gaussian simulation. A case study was conducted using a sample data set from a 150 km2 area in Wuhan City and the composite SEQS for cadmium, recently set by the State Environmental Protection Administration of China. The method may be useful for evaluating the pollution risks of trace metals in soil with composite SEQSs. PMID:24672364

Inversely Estimating the Vertical Profile of the Soil CO2 Production Rate in a Deciduous Broadleaf Forest Using a Particle Filtering Method

PubMed Central

Sakurai, Gen; Yonemura, Seiichiro; Kishimoto-Mo, Ayaka W.; Murayama, Shohei; Ohtsuka, Toshiyuki; Yokozawa, Masayuki

2015-01-01

Carbon dioxide (CO2) efflux from the soil surface, which is a major source of CO2 from terrestrial ecosystems, represents the total CO2 production at all soil depths. Although many studies have estimated the vertical profile of the CO2 production rate, one of the difficulties in estimating the vertical profile is measuring diffusion coefficients of CO2 at all soil depths in a nondestructive manner. In this study, we estimated the temporal variation in the vertical profile of the CO2 production rate using a data assimilation method, the particle filtering method, in which the diffusion coefficients of CO2 were simultaneously estimated. The CO2 concentrations at several soil depths and CO2 efflux from the soil surface (only during the snow-free period) were measured at two points in a broadleaf forest in Japan, and the data were assimilated into a simple model including a diffusion equation. We found that there were large variations in the pattern of the vertical profile of the CO2 production rate between experiment sites: the peak CO2 production rate was at soil depths around 10 cm during the snow-free period at one site, but the peak was at the soil surface at the other site. Using this method to estimate the CO2 production rate during snow-cover periods allowed us to estimate CO2 efflux during that period as well. We estimated that the CO2 efflux during the snow-cover period (about half the year) accounted for around 13% of the annual CO2 efflux at this site. Although the method proposed in this study does not ensure the validity of the estimated diffusion coefficients and CO2 production rates, the method enables us to more closely approach the “actual” values by decreasing the variance of the posterior distribution of the values. PMID:25793387

Native Plant Uptake Model for Radioactive Waste Disposal Areas at the Nevada Test Site

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

BROWN,THERESA J.; WIRTH,SHARON

1999-09-01

This report defines and defends the basic framework, methodology, and associated input parameters for modeling plant uptake of radionuclides for use in Performance Assessment (PA) activities of Radioactive Waste Management Sites (RWMS) at the Nevada Test Site (NTS). PAs are used to help determine whether waste disposal configurations meet applicable regulatory standards for the protection of human health, the environment, or both. Plants adapted to the arid climate of the NTS are able to rapidly capture infiltrating moisture. In addition to capturing soil moisture, plant roots absorb nutrients, minerals, and heavy metals, transporting them within the plant to the above-groundmore » biomass. In this fashion, plant uptake affects the movement of radionuclides. The plant uptake model presented reflects rooting characteristics important to plant uptake, biomass turnover rates, and the ability of plants to uptake radionuclides from the soil. Parameters are provided for modeling plant uptake and estimating surface contaminant flux due to plant uptake under both current and potential future climate conditions with increased effective soil moisture. The term ''effective moisture'' is used throughout this report to indicate the soil moisture that is available to plants and is intended to be inclusive of all the variables that control soil moisture at a site (e.g., precipitation, temperature, soil texture, and soil chemistry). Effective moisture is a concept used to simplify a number of complex, interrelated soil processes for which there are too little data to model actual plant available moisture. The PA simulates both the flux of radionuclides across the land surface and the potential dose to humans from that flux. Surface flux is modeled here as the amount of soil contamination that is transferred from the soil by roots and incorporated into aboveground biomass. Movement of contaminants to the surface is the only transport mechanism evaluated with the model presented here. Parameters necessary for estimating surface contaminant flux due to native plants expected to inhabit the NTS RWMSS are developed in this report. The model is specific to the plant communities found at the NTS and is designed for both short-term (<1,000 years) and long-term (>1,000 years) modeling efforts. While the model has been crafted for general applicability to any NTS PA, the key radionuclides considered are limited to the transuranic (TRU) wastes disposed of at the NTS.« less

SAR-aided method for rural soil evaluation

NASA Astrophysics Data System (ADS)

Lay-Ekuakille, Aime; Dellisanti, Carmelo; Pelillo, Vincenza; Tralli, Francesco

2003-03-01

The principal land characteristics that can be estimated by means of airphoto interpretation are bedrock type, landform, soil texture, site drainage conditions, susceptibility to flooding, and depth of unconsolidated materials over bedrock. In addition, the slope of the land surface can be estimated by airphoto interpretation and measured by phptpgrammetric methods. The aim of this paper is to show an experimental use of satellite images in determining soil quality affected by anthropic activities as rock crushing, or scarifying. Scarifying activities began, in Murgia area, Apulia Region, Italy), as land improvement for agriculture uses. Scarifying is defined as loosening (the surface of soil) by using an agricultural tool or a machine with prongs. This kind of activity is facilitated by the availability, on the market, of scarifying machines and the objective is to get a stratum of agriculture-useful loose material on the soil surface. Apulia Region Government has permitted calcareous stone scarifying with Regional Law n.54 (August 31, 1981) according to National Law n.984 (Dicember 27,1977), that provides for encouraging to transform grazing in sown land in order to create new possibility of forage production to increase zootecnical facilities. We have used ERS-2/SAR images as contribution in the process of soil characterization.The area we have considered is in Puglia Region and is subject to soil transformation due to rocks crushed on land for agricultural facilities. European Union, through the same Apulia Region Government, has renewed funds for the improvement of meadow and grazing for an overall surface of 2000 hectares. In this way it is clear to understand the importance of qualitative and quantitative evaluation of rock crushing or scarifying by using airphoto interpretation. We have evaluated the soil quality by introducing a multicriteria, analysis by using a qualitative and quantitative methodology, so that it will be possible to prevent damages on soil, sub-soil and hydrology. Decision analysis in Impact assessment is a set of procedures for analyzing complex decision problems. The strategy is to divide the decision problem into small, understandable parts; analyze each part; and integrate the parts in a logical manner to produce a meaningful solution. The terms multicriteria decision making (MCDM) and multicriteria decision analysis (MCDA) are used interchangeably.

Characterization of Anaerobic Chemical Processes in Reservoirs: Problem Description and Conceptual Model Formulation.

DTIC Science & Technology

1981-04-01

also found that almost all the Fe in soil solution was complexed with organic mat- ter. The high degree of Fe complexing in soil solution was...range of pH, the potentials were in conformity with the theoretical slope of 0.06. 45. When a soil is submerged, soil solution concentrations of...Ponnanperuma 1972). Low temperatures lead to extensive accumula- tion of organic acids in the soil solution (International Rice Research Institute (IRRI) 1969

Alkanes as Components of Soil Hydrocarbon Status: Behavior and Indication Significance

NASA Astrophysics Data System (ADS)

Gennadiev, A. N.; Zavgorodnyaya, Yu. A.; Pikovskii, Yu. I.; Smirnova, M. A.

2018-01-01

Studies of soils on three key plots with different climatic conditions and technogenic impacts in Volgograd, Moscow, and Arkhangelsk oblasts have showed that alkanes in the soil exchange complex have some indication potential for the identification of soil processes. The following combinations of soil-forming factors and processes have been studied: (a) self-purification of soil after oil pollution; (b) accumulation of hydrocarbons coming from the atmosphere to soils of different land use patterns; and (c) changes in the soil hydrocarbon complex beyond the zone of technogenic impact due to the input of free hydrocarbon-containing gases. At the injection input of hydrocarbon pollutants, changes in the composition and proportions of alkanes allow tracing the degradation trend of pollutants in the soil from their initial content to the final stage of soil self-purification, when the background concentrations of hydrocarbons are reached. Upon atmospheric deposition of hydrocarbons onto the soil, from the composition and mass distribution of alkanes, conclusions can be drawn about the effect of toxicants on biogeochemical processes in the soil, including their manifestation under different land uses. Composition analysis of soil alkanes in natural landscapes can reveal signs of hydrocarbon emanation fluxes in soils. The indication potentials of alkanes in combination with polycyclic aromatic hydrocarbons and other components of soil hydrocarbon complex can also be used for the solution of other soil-geochemical problems.

Validating the use of 137Cs and 210Pbex measurements to estimate rates of soil loss from cultivated land in southern Italy.

PubMed

Porto, Paolo; Walling, Des E

2012-04-01

Soil erosion represents an important threat to the long-term sustainability of agriculture and forestry in many areas of the world, including southern Italy. Numerous models and prediction procedures have been developed to estimate rates of soil loss and soil redistribution, based on the local topography, hydrometeorology, soil type and land management. However, there remains an important need for empirical measurements to provide a basis for validating and calibrating such models and prediction procedures as well as to support specific investigations and experiments. In this context, erosion plots provide useful information on gross rates of soil loss, but are unable to document the efficiency of the onward transfer of the eroded sediment within a field and towards the stream system, and thus net rates of soil loss from larger areas. The use of environmental radionuclides, particularly caesium-137 ((137)Cs) and excess lead-210 ((210)Pb(ex)), as a means of estimating rates of soil erosion and deposition has attracted increasing attention in recent years and the approach has now been recognised as possessing several important advantages. In order to provide further confirmation of the validity of the estimates of longer-term erosion and soil redistribution rates provided by (137)Cs and (210)Pb(ex) measurements, there is a need for studies aimed explicitly at validating the results obtained. In this context, the authors directed attention to the potential offered by a set of small erosion plots located near Reggio Calabria in southern Italy, for validating estimates of soil loss provided by (137)Cs and (210)Pb(ex) measurements. A preliminary assessment suggested that, notwithstanding the limitations and constraints involved, a worthwhile investigation aimed at validating the use of (137)Cs and (210)Pb(ex) measurements to estimate rates of soil loss from cultivated land could be undertaken. The results demonstrate a close consistency between the measured rates of soil loss and the estimates provided by the (137)Cs and (210)Pb(ex) measurements and can therefore been seen as validating the use of these fallout radionuclides to document soil erosion rates in that environment. Further studies are clearly required to exploit other opportunities for validation in contrasting environments and under different land use conditions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Climatic variability of soil water in the American Midwest: Part 2. Spatio-temporal analysis

NASA Astrophysics Data System (ADS)

Georgakakos, Konstantine P.; Bae, Deg-Hyo

1994-11-01

A study of the model-estimated soil water, aggregated over three large drainage basins of the Midwestern USA, is reported. The basin areas are in the range from 2000 km 2 to 3500 km 2, and allow the study of mesoscale (1000-10000 km 2) soil water features. In each case, a conceptual hydrologic model was used to produce upper and lower soil water estimates that are consistent with the atmospheric forcing of daily precipitation, potential evapotranspiration and air temperature, and with the observed daily streamflow divergence over a 40 year period. It is shown that the water contents of the upper and lower soil reach peaks in different months, with the soil column being most saturated in June, when the area is prone to serious flooding. Temporal and spatial features of the variability of model-estimated soil water content are identified. The autocorrelation function of monthly averaged soil water shows that the upper soil water remains persistent for about a season, whereas the persistence of the lower soil water extends to several seasons. The soil water estimates of the three study basins exhibit strong similarities in annual cycles and interannual variability. It is shown that the frequency of significant positive (wet) soil water anomalies that extend over a 2° × 2° region is lower than that of significant negative (dry) ones of the same extent in this region of the USA.

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

Josephson, Walter S.

The 324 Building on the Hanford site played a key role in radiochemical and metallurgical research programs conducted by DOE. The B hot cell in the 324 Building was the site of high-level waste vitrification research. During clean-out operations in November 2009, a tear was noted in the stainless steel liner on the floor of B Cell. Exposure rate readings taken at various locations in the soil about 0.5 meters below B Cell reached 8,900 Roentgen (R) per hour, confirming the existence of a significant soil contamination field. The source of the radioactive material was likely a 510 L spillmore » from the Canister Fabrication Project, consisting of purified, concentrated Cs-137 and Sr-90 solutions totaling 48,000 TBq (1.3 MCi). MCNP modeling was used to estimate that the measured exposure rates were caused by 5,900 TBq (160 kCi) of Sr- 90 and Cs-137, although additional contamination was thought to exist deeper in the soil column. Two physical soil samples were obtained at different depths, which helped verify the contamination estimates. A detailed exposure rate survey inside B Cell was combined with additional MCNP modeling to estimate that an additional 1,700 TBq (460 kCi) is present just below the floor. Based on the results of the sampling campaign, it is likely that the radioactive material below B Cell is primarily consists of feed solutions from the FRG Canister Fabrication Project, and that it contains purified Sr-90 and Cs-137 with enough actinide carryover to make some of the soil transuranic. The close agreement between the Geoprobe calculations and the physical samples adds confidence that there are more than 3700 TBq (100,000 Ci) of Sr-90 and Cs-137 in the soil approximately 1 meter below the cell floor. The majority of the Cs-137 is contained in the first meter of soil, while significant Sr-90 contamination extends to 10 meters below the cell floor. It is also likely that an additional 15,000 TBq (400,000 Ci) of Cs-137 and Sr-90 activity is present directly below the floor of the cell, and that the residual activity inside the cell is only half of the previous estimates. However, the partitioning of activity between residuals in the cell and in the soil below the floor is much more uncertain than the activity calculations associated with the Geoprobe measurements. Taken together, the calculated soil activities represent about half of the spill associated with the FRG Canister Fabrication project. The remainder of the spill is believed to have remained in the cell, where the majority has been removed as part of cell cleanup activities. The magnitude of the soil contamination below 324 B Cell is sobering, and it represents one of the most challenging remediation activities in the DOE complex. Of course, safe remediation begins with a good understanding of the magnitude of the problem. As a result, additional modeling and cross-comparison efforts are planned for 2012. (authors)« less

Metal fate and partitioning in soils under bark beetle-killed trees.

PubMed

Bearup, Lindsay A; Mikkelson, Kristin M; Wiley, Joseph F; Navarre-Sitchler, Alexis K; Maxwell, Reed M; Sharp, Jonathan O; McCray, John E

2014-10-15

Recent mountain pine beetle infestation in the Rocky Mountains of North America has killed an unprecedented acreage of pine forest, creating an opportunity to observe an active re-equilibration in response to widespread land cover perturbation. This work investigates metal mobility in beetle-impacted forests using parallel rainwater and acid leaches to estimate solid-liquid partitioning coefficients and a complete sequential extraction procedure to determine how metals are fractionated in soils under trees experiencing different phases of mortality. Geochemical model simulations analyzed in consideration with experimental data provide additional insight into the mechanisms controlling metal complexation. Metal and base-cation mobility consistently increased in soils under beetle-attacked trees relative to soil under healthy trees. Mobility increases were more pronounced on south facing slopes and more strongly correlated to pH under attacked trees than under healthy trees. Similarly, soil moisture was significantly higher under dead trees, related to the loss of transpiration and interception. Zinc and cadmium content increased in soils under dead trees relative to living trees. Cadmium increases occurred predominantly in the exchangeable fraction, indicating increased mobilization potential. Relative increases of zinc were greatest in the organic fraction, the only fraction where increases in copper were observed. Model results reveal that increased organic complexation, not changes in pH or base cation concentrations, can explain the observed differences in metal partitioning for zinc, nickel, cadmium, and copper. Predicted concentrations would be unlikely to impair human health or plant growth at these sites; however, higher exchangeable metals under beetle-killed trees relative to healthy trees suggest a possible decline in riverine ecosystem health and water quality in areas already approaching criteria limits and drinking water standards. Impairment of water quality in important headwater streams from the increased potential for metal mobilization and storage will continue to change as beetle-killed trees decompose and forests begin to recover. Copyright © 2014 Elsevier B.V. All rights reserved.

A Subsurface Soil Composition and Physical Properties Experiment to Address Mars Regolith Stratigraphy

NASA Technical Reports Server (NTRS)

Richter, L.; Sims, M.; Economou, T.; Stoker, C.; Wright, I.; Tokano, T.

2004-01-01

Previous in-situ measurements of soil-like materials on the surface of Mars, in particular during the on-going Mars Exploration Rover missions, have shown complex relationships between composition, exposure to the surface environment, texture, and local rocks. In particular, a diversity in both compositional and physical properties could be established that is interpreted to be diagnostic of the complex geologic history of the martian surface layer. Physical and chemical properties vary laterally and vertically, providing insight into the composition of rocks from which soils derive, and environmental conditions that led to soil formation. They are central to understanding whether habitable environments existed on Mars in the distant past. An instrument the Mole for Soil Compositional Studies and Sampling (MOCSS) - is proposed to allow repeated access to subsurface regolith on Mars to depths of up to 1.5 meters for in-situ measurements of elemental composition and of physical and thermophysical properties, as well as for subsurface sample acquisition. MOCSS is based on the compact PLUTO (PLanetary Underground TOol) Mole system developed for the Beagle 2 lander and incorporates a small X-ray fluorescence spectrometer within the Mole which is a new development. Overall MOCSS mass is approximately 1.4 kilograms. Taken together, the MOCSS science data support to decipher the geologic history at the landing site as compositional and textural stratigraphy if they exist - can be detected at a number of places if the MOCSS were accommodated on a rover such as MSL. Based on uncovered stratigraphy, the regional sequence of depositional and erosional styles can be constrained which has an impact on understanding the ancient history of the Martian near-surface layer, considering estimates of Mars soil production rates of 0.5... 1.0 meters per billion years on the one hand and Mole subsurface access capability of approximately 1.5 meters. An overview of the MOCSS, XRS instrument accomodation and the impact that these instruments have on Mars science is discussed.

Chemical sensing thresholds for mine detection dogs

NASA Astrophysics Data System (ADS)

Phelan, James M.; Barnett, James L.

2002-08-01

Mine detection dogs have been found to be an effective method to locate buried landmines. The capabilities of the canine olfaction method are from a complex combination of training and inherent capacity of the dog for odor detection. The purpose of this effort was to explore the detection thresholds of a limited group of dogs that were trained specifically for landmine detection. Soils were contaminated with TNT and 2,4-DNT to develop chemical vapor standards to present to the dogs. Soils contained ultra trace levels of TNT and DNT, which produce extremely low vapor levels. Three groups of dogs were presented the headspace vapors from the contaminated soils in work environments for each dog group. One positive sample was placed among several that contained clean soils and, the location and vapor source (strength, type) was frequently changed. The detection thresholds for the dogs were determined from measured and extrapolated dilution of soil chemical residues and, estimated soil vapor values using phase partitioning relationships. The results showed significant variances in dog sensing thresholds, where some dogs could sense the lowest levels and others had trouble with even the highest source. The remarkable ultra-trace levels detectable by the dogs are consistent with the ultra-trace chemical residues derived from buried landmines; however, poor performance may go unnoticed without periodic challenge tests at levels consistent with performance requirements.

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.

Mean age distribution of inorganic soil-nitrogen

NASA Astrophysics Data System (ADS)

Woo, Dong K.; Kumar, Praveen

2016-07-01

Excess reactive nitrogen in soils of intensively managed landscapes 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 model to characterize the "age" of inorganic soil-nitrogen (nitrate, and ammonia/ammonium). We use the general theory of age, which provides an assessment of the time elapsed since inorganic nitrogen has been introduced into the soil system. We analyze a corn-corn-soybean rotation, common in the Midwest United States, as an example application. We observe two counter-intuitive results: (1) the mean nitrogen age in the topsoil layer is relatively high; and (2) mean nitrogen age is lower under soybean cultivation compared to corn although no fertilizer is applied for soybean cultivation. The first result can be explained by cation-exchange of ammonium that retards the leaching of nitrogen, resulting in an increase in the mean nitrogen age near the soil surface. The second result arises because the soybean utilizes the nitrogen fertilizer left from the previous year, thereby removing the older nitrogen and reducing mean nitrogen age. Estimating the mean nitrogen age can thus serve as an important tool to disentangle complex nitrogen dynamics by providing a nuanced characterization of the time scales of soil-nitrogen transformation and transport processes.

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

NASA Astrophysics Data System (ADS)

Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.

2017-02-01

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.

Input-decomposition balance of heterotrophic processes in a warm-temperate mixed forest in Japan

NASA Astrophysics Data System (ADS)

Jomura, M.; Kominami, Y.; Ataka, M.; Makita, N.; Dannoura, M.; Miyama, T.; Tamai, K.; Goto, Y.; Sakurai, S.

2010-12-01

Carbon accumulation in forest ecosystem has been evaluated using three approaches. One is net ecosystem exchange (NEE) estimated by tower flux measurement. The second is net ecosystem production (NEP) estimated by biometric measurements. NEP can be expressed as the difference between net primary production and heterotrophic respiration. NEP can also be expressed as the annual increment in the plant biomass (ΔW) plus soil (ΔS) carbon pools defined as follows; NEP = ΔW+ΔS The third approach needs to evaluate annual carbon increment in soil compartment. Soil carbon accumulation rate could not be measured directly in a short term because of the small amount of annual accumulation. Soil carbon accumulation rate can be estimated by a model calculation. Rothamsted carbon model is a soil organic carbon turnover model and a useful tool to estimate the rate of soil carbon accumulation. However, the model has not sufficiently included variations in decomposition processes of organic matters in forest ecosystems. Organic matter in forest ecosystems have a different turnover rate that creates temporal variations in input-decomposition balance and also have a large variation in spatial distribution. Thus, in order to estimate the rate of soil carbon accumulation, temporal and spatial variation in input-decomposition balance of heterotrophic processes should be incorporated in the model. In this study, we estimated input-decomposition balance and the rate of soil carbon accumulation using the modified Roth-C model. We measured respiration rate of many types of organic matters, such as leaf litter, fine root litter, twigs and coarse woody debris using a chamber method. We can illustrate the relation of respiration rate to diameter of organic matters. Leaf and fine root litters have no diameter, so assumed to be zero in diameter. Organic matters in small size, such as leaf and fine root litter, have high decomposition respiration. It could be caused by the difference in structure of organic matter. Because coarse woody debris has shape of cylinder, microbes decompose from the surface of it. Thus, respiration rate of coarse woody debris is lower than that of leaf and fine root litter. Based on this result, we modified Roth-C model and estimate soil carbon accumulation rate in recent years. Based on the results from a soil survey, the forest soil stored 30tC ha-1 in O and A horizon. We can evaluate the modified model using this result. NEP can be expressed as the annual increment in the plant biomass plus soil carbon pools. So if we can estimate NEP using this approach, then we can evaluate NEP estimated by micrometeorological and ecological approaches and reduce uncertainty of NEP estimation.

Comparison of DNDC and RZWQM2 for simulating hydrology and nitrogen dynamics in a corn-soybean system with a winter cover crop

NASA Astrophysics Data System (ADS)

Desjardins, R.; Smith, W.; Qi, Z.; Grant, B.; VanderZaag, A.

2017-12-01

Biophysical models are needed for assessing science-based mitigation options to improve the efficiency and sustainability of agricultural cropping systems. In order to account for trade-offs between environmental indicators such as GHG emissions, soil C change, and water quality it is important that models can encapsulate the complex array of interrelated biogeochemical processes controlling water, nutrient and energy flows in the agroecosystem. The Denitrification Decomposition (DNDC) model is one of the most widely used process-based models, and is arguably the most sophisticated for estimating GHG emissions and soil C&N cycling, however, the model simulates only simple cascade water flow. The purpose of this study was to compare the performance of DNDC to a comprehensive water flow model, the Root Zone Water Quality Model (RZWQM2), to determine which processes in DNDC may be limiting and recommend improvements. Both models were calibrated and validated for simulating crop biomass, soil hydrology, and nitrogen loss to tile drains using detailed observations from a corn-soybean rotation in Iowa, with and without cover crops. Results indicated that crop yields, biomass and the annual estimation of nitrogen and water loss to tiles drains were well simulated by both models (NSE > 0.6 in all cases); however, RZWQM2 performed much better for simulating soil water content, and the dynamics of daily water flow (DNDC: NSE -0.32 to 0.28; RZWQM2: NSE 0.34 to 0.70) to tile drains. DNDC overestimated soil water content near the soil surface and underestimated it deeper in the profile which was presumably caused by the lack of a root distribution algorithm, the inability to simulate a heterogeneous profile and lack of a water table. We recommend these improvements along with the inclusion of enhanced water flow and a mechanistic tile drainage sub-model. The accurate temporal simulation of water and N strongly impacts several biogeochemical processes.

Canadian Field Soils IV: Modeling Thermal Conductivity at Dryness and Saturation

NASA Astrophysics Data System (ADS)

Tarnawski, V. R.; McCombie, M. L.; Leong, W. H.; Coppa, P.; Corasaniti, S.; Bovesecchi, G.

2018-03-01

The thermal conductivity data of 40 Canadian soils at dryness (λ _{dry}) and at full saturation (λ _{sat}) were used to verify 13 predictive models, i.e., four mechanistic, four semi-empirical and five empirical equations. The performance of each model, for λ _{dry} and λ _{sat}, was evaluated using a standard deviation ( SD) formula. Among the mechanistic models applied to dry soils, the closest λ _{dry} estimates were obtained by MaxRTCM (it{SD} = ± 0.018 Wm^{-1}\\cdot K^{-1}), followed by de Vries and a series-parallel model (S-{\\vert }{\\vert }). Among the semi-empirical equations (deVries-ave, Advanced Geometric Mean Model (A-GMM), Chaudhary and Bhandari (C-B) and Chen's equation), the closest λ _{dry} estimates were obtained by the C-B model (± 0.022 Wm^{-1}\\cdot K^{-1}). Among the empirical equations, the top λ _{dry} estimates were given by CDry-40 (± 0.021 Wm^{-1}\\cdot K^{-1} and ± 0.018 Wm^{-1}\\cdot K^{-1} for18-coarse and 22-fine soils, respectively). In addition, λ _{dry} and λ _{sat} models were applied to the λ _{sat} database of 21 other soils. From all the models tested, only the maxRTCM and the CDry-40 models provided the closest λ _{dry} estimates for the 40 Canadian soils as well as the 21 soils. The best λ _{sat} estimates for the 40-Canadian soils and the 21 soils were given by the A-GMM and the S-{\\vert }{\\vert } model.

Estimating root-zone soil moisture in the West Africa Sahel using remotely sensed rainfall and vegetation

NASA Astrophysics Data System (ADS)

McNally, Amy L.

Agricultural drought is characterized by shortages in precipitation, large differences between actual and potential evapotranspiration, and soil water deficits that impact crop growth and pasture productivity. Rainfall and other agrometeorological gauge networks in Sub-Saharan Africa are inadequate for drought early warning systems and hence, satellite-based estimates of rainfall and vegetation greenness provide the main sources of information. While a number of studies have described the empirical relationship between rainfall and vegetation greenness, these studies lack a process based approach that includes soil moisture storage. In Chapters I and II, I modeled soil moisture using satellite rainfall inputs and developed a new method for estimating soil moisture with NDVI calibrated to in situ and microwave soil moisture observations. By transforming both NDVI and rainfall into estimates of soil moisture I was able to easily compare these two datasets in a physically meaningful way. In Chapter II, I also show how the new NDVI derived soil moisture can be assimilated into a water balance model that calculates an index of crop water stress. Compared to the analogous rainfall derived estimates of soil moisture and crop stress the NDVI derived estimates were better correlated with millet yields. In Chapter III, I developed a metric for defining growing season drought events that negatively impact millet yields. This metric is based on the data and models used in the Chapters I and II. I then use this metric to evaluate the ability of a sophisticated land surface model to detect drought events. The analysis showed that this particular land surface model's soil moisture estimates do have the potential to benefit the food security and drought early warning communities. With a focus on soil moisture, this dissertation introduced new methods that utilized a variety of data and models for agricultural drought monitoring applications. These new methods facilitate a more quantitative, transparent `convergence of evidence' approach to identifying agricultural drought events that lead to food insecurity. Ideally, these new methods will contribute to better famine early warning and the timely delivery of food aid to reduce the human suffering caused by drought.

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

NASA Astrophysics Data System (ADS)

Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.

2015-10-01

The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. Finally, by considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved.

Combined radar-radiometer surface soil moisture and roughness estimation

USDA-ARS?s Scientific Manuscript database

A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution rad...

Estimating mercury emissions resulting from wildfire in forests of the Western United States.

PubMed

Webster, Jackson P; Kane, Tyler J; Obrist, Daniel; Ryan, Joseph N; Aiken, George R

2016-10-15

Understanding the emissions of mercury (Hg) from wildfires is important for quantifying the global atmospheric Hg sources. Emissions of Hg from soils resulting from wildfires in the Western United States was estimated for the 2000 to 2013 period, and the potential emission of Hg from forest soils was assessed as a function of forest type and soil-heating. Wildfire released an annual average of 3100±1900kg-Hgy(-1) for the years spanning 2000-2013 in the 11 states within the study area. This estimate is nearly 5-fold lower than previous estimates for the study region. Lower emission estimates are attributed to an inclusion of fire severity within burn perimeters. Within reported wildfire perimeters, the average distribution of low, moderate, and high severity burns was 52, 29, and 19% of the total area, respectively. Review of literature data suggests that that low severity burning does not result in soil heating, moderate severity fire results in shallow soil heating, and high severity fire results in relatively deep soil heating (<5cm). Using this approach, emission factors for high severity burns ranged from 58 to 640μg-Hgkg-fuel(-1). In contrast, low severity burns have emission factors that are estimated to be only 18-34μg-Hgkg-fuel(-1). In this estimate, wildfire is predicted to release 1-30gHgha(-1) from Western United States forest soils while above ground fuels are projected to contribute an additional 0.9 to 7.8gHgha(-1). Land cover types with low biomass (desert scrub) are projected to release less than 1gHgha(-1). Following soil sources, fuel source contributions to total Hg emissions generally followed the order of duff>wood>foliage>litter>branches. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparative study of soil erodibility and critical shear stress between loess and purple soils

NASA Astrophysics Data System (ADS)

Xing, Hang; Huang, Yu-han; Chen, Xiao-yan; Luo, Bang-lin; Mi, Hong-xing

2018-03-01

Loess and purple soils are two very important cultivated soils, with the former in the loess region and the latter in southern sub-tropical region of China, featured with high-risks of erosion, considerable differences of soil structures due to differences in mineral and nutrient compositions. Study on soil erodibility (Kr) and critical shear stress (τc) of these two soils is beneficial to predict soil erosion with such models as WEPP. In this study, rill erosion experimental data sets of the two soils are used for estimating their Kr and τc before they are compared to understand their differences of rill erosion behaviors. The maximum detachment rates of the loess and purple soils are calculated under different hydrodynamic conditions (flow rates: 2, 4, 8 L/min; slope gradients: 5°, 10°, 15°, 20°, 25°) through analytical and numerical methods respectively. Analytical method used the derivative of the function between sediment concentration and rill length to estimate potential detachment rates, at the rill beginning. Numerical method estimated potential detachment rates with the experimental data, at the rill beginning and 0.5 m location. The Kr and τc of these two soils are determined by the linear equation based on experimental data. Results show that the methods could well estimate the Kr and τc of these two soils as they remain basically unchanged under different hydrodynamic conditions. The Kr value of loess soil is about twice of the purple soil, whereas the τc is about half of that. The numerical results have good correlations with the analytical values. These results can be useful in modeling rill erosion processes of loess and purple soils.

Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

2017-01-01

The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

Monitoring of Cr, Cu, Pb, V and Zn in polluted soils by laser induced breakdown spectroscopy (LIBS).

PubMed

Dell'Aglio, Marcella; Gaudiuso, Rosalba; Senesi, Giorgio S; De Giacomo, Alessandro; Zaccone, Claudio; Miano, Teodoro M; De Pascale, Olga

2011-05-01

Laser Induced Breakdown Spectroscopy (LIBS) is a fast and multi-elemental analytical technique particularly suitable for the qualitative and quantitative analysis of heavy metals in solid samples, including environmental ones. Although LIBS is often recognised in the literature as a well-established analytical technique, results about quantitative analysis of elements in chemically complex matrices such as soils are quite contrasting. In this work, soil samples of various origins have been analyzed by LIBS and data compared to those obtained by Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). The emission intensities of one selected line for each of the five analytes (i.e., Cr, Cu, Pb, V, and Zn) were normalized to the background signal, and plotted as a function of the concentration values previously determined by ICP-OES. Data showed a good linearity for all calibration lines drawn, and the correlation between ICP-OES and LIBS was confirmed by the satisfactory agreement obtained between the corresponding values. Consequently, LIBS method can be used at least for metal monitoring in soils. In this respect, a simple method for the estimation of the soil pollution degree by heavy metals, based on the determination of an anthropogenic index, was proposed and determined for Cr and Zn.

Estimation of CO2 diffusion coefficient at 0-10 cm depth in undisturbed and tilled soils

USDA-ARS?s Scientific Manuscript database

Diffusion coefficients (D) of CO2 at 0 – 10 cm layers in undisturbed and tilled soil conditions were estimated using Penman, Millington-Quirk, Ridgwell et al. (1999), Troeh et al., and Moldrup et al. models. Soil bulk density and volumetric soil water content ('v) at 0 – 10 cm were measured on April...

Using (137)Cs measurements to estimate soil erosion rates in the Pčinja and South Morava River Basins, southeastern Serbia.

PubMed

Petrović, Jelena; Dragović, Snežana; Dragović, Ranko; Đorđević, Milan; Đokić, Mrđan; Zlatković, Bojan; Walling, Desmond

2016-07-01

The need for reliable assessments of soil erosion rates in Serbia has directed attention to the potential for using (137)Cs measurements to derive estimates of soil redistribution rates. Since, to date, this approach has not been applied in southeastern Serbia, a reconnaissance study was undertaken to confirm its viability. The need to take account of the occurrence of substantial Chernobyl fallout was seen as a potential problem. Samples for (137)Cs measurement were collected from a zone of uncultivated soils in the watersheds of Pčinja and South Morava Rivers, an area with known high soil erosion rates. Two theoretical conversion models, the profile distribution (PD) model and diffusion and migration (D&M) model were used to derive estimates of soil erosion and deposition rates from the (137)Cs measurements. The estimates of soil redistribution rates derived by using the PD and D&M models were found to differ substantially and this difference was ascribed to the assumptions of the simpler PD model that cause it to overestimate rates of soil loss. The results provided by the D&M model were judged to more reliable. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale

NASA Astrophysics Data System (ADS)

Ibrahim, Hesham M.; Huggins, David R.

2011-07-01

SummarySpatio-temporal patterns of soil water are major determinants of crop yield potential in dryland agriculture and can serve as the basis for delineating precision management zones. Soil water patterns can vary significantly due to differences in seasonal precipitation, soil properties and topographic features. In this study we used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water at the Washington State University Cook Agronomy Farm (CAF) near Pullman, WA. During the period 1999-2006, the CAF was divided into three roughly equal blocks (A, B, and C), and soil water at 0.3 m intervals to a depth of 1.5 m measured gravimetrically at approximately one third of the 369 geo-referenced points on the 37-ha watershed. These data were combined with terrain attributes, soil bulk density and apparent soil conductivity (EC a). The first EOF generated from the three blocks explained 73-76% of the soil water variability. Field patterns of soil water based on EOF interpolation varied between wet and dry conditions during spring and fall seasons. Under wet conditions, elevation and wetness index were the dominant factors regulating the spatial patterns of soil water. As soil dries out during summer and fall, soil properties (EC a and bulk density) become more important in explaining the spatial patterns of soil water. The EOFs generated from block B, which represents average topographic and soil properties, provided better estimates of soil water over the entire watershed with larger Nash-Sutcliffe Coefficient of Efficiency (NSCE) values, especially when the first two EOFs were retained. Including more than the first two EOFs did not significantly increase the NSCE of soil water estimate. The EOF interpolation method to estimate soil water variability worked slightly better during spring than during fall, with average NSCE values of 0.23 and 0.20, respectively. The predictable patterns of stored soil water in the spring could serve as the basis for delineating precision management zones as yield potential is largely driven by water availability. The EOF-based method has the advantage of estimating the soil water variability based on soil water data from several measurement times, whereas in regression methods only soil water measurement at a single time are used. The EOF-based method can also be used to estimate soil water at any time other than measurement times, assuming the average soil water of the watershed is known at that time.

Evaluation of HCMM data for assessing soil moisture and water table depth

NASA Technical Reports Server (NTRS)

Moore, D. G.; Heilman, J. L.; Tunheim, J. A.; Westin, F. C.; Heilman, W. E.; Beutler, G. A.; Ness, S. D. (Principal Investigator)

1981-01-01

Data were analyzed for variations in eastern South Dakota. Soil moisture in the 0-4 cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop (% cover ranging from 30% to 90%) with an r squared = 0.81. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the 1-mm soil temperature, r squared = 0.88. The corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the 0-4 cm soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. HCMM data were used to estimate the soil moisture for four dates with an r squared = 0.55 after correction for crop conditions. Location of shallow alluvial aquifers could be accomplished with HCMM predawn data. After correction of HCMM day data for vegetation differences, equations were developed for predicting water table depths within the aquifer (r=0.8).

Estimating soil zinc concentrations using reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Sun, Weichao; Zhang, Xia

2017-06-01

Soil contamination by heavy metals has been an increasingly severe threat to nature environment and human health. Efficiently investigation of contamination status is essential to soil protection and remediation. Visible and near-infrared reflectance spectroscopy (VNIRS) has been regarded as an alternative for monitoring soil contamination by heavy metals. Generally, the entire VNIR spectral bands are employed to estimate heavy metal concentration, which lacks interpretability and requires much calculation. In this study, 74 soil samples were collected from Hunan Province, China and their reflectance spectra were used to estimate zinc (Zn) concentration in soil. Organic matter and clay minerals have strong adsorption for Zn in soil. Spectral bands associated with organic matter and clay minerals were used for estimation with genetic algorithm based partial least square regression (GA-PLSR). The entire VNIR spectral bands, the bands associated with organic matter and the bands associated with clay minerals were incorporated as comparisons. Root mean square error of prediction, residual prediction deviation, and coefficient of determination (R2) for the model developed using combined bands of organic matter and clay minerals were 329.65 mg kg-1, 1.96 and 0.73, which is better than 341.88 mg kg-1, 1.89 and 0.71 for the entire VNIR spectral bands, 492.65 mg kg-1, 1.31 and 0.40 for the organic matter, and 430.26 mg kg-1, 1.50 and 0.54 for the clay minerals. Additionally, in consideration of atmospheric water vapor absorption in field spectra measurement, combined bands of organic matter and absorption around 2200 nm were used for estimation and achieved high prediction accuracy with R2 reached 0.640. The results indicate huge potential of soil reflectance spectroscopy in estimating Zn concentrations in soil.

Chemical characterization of iron-mediated soil organic matter stabilization in tropical subsoils

NASA Astrophysics Data System (ADS)

Coward, E.; Plante, A. F.; Thompson, A.

2015-12-01

Tropical forest soils contribute disproportionately to the poorly-characterized and persistent deep soil carbon (C) pool. Highly-weathered and often extending one to two meters deep, these soils also contain an abundance of semicrystalline, Fe- and Al-containing short-range-order (SRO) minerals, metastable derivatives of framework silicate and ferromagnesian parent materials. SRO minerals are capable of soil organic matter (SOM) stabilization through sorption or co-precipitation, a faculty enhanced by their high specific surface area (SSA). As such, SRO-mediated organomineral associations may prove a critical, yet matrix-selective, driver of SOM stabilization capacity in tropical soils, particularly at depth. Surface (0-20 cm) and subsoil (50-80 cm) samples were taken from 20 quantitative soil pits dug in the Luquillo Critical Zone Observatory, located in northeast Puerto Rico. Soils were stratified across granodiorite and volcaniclastic parent materials, spanning primary mineral contents of 5 to 40%. Selective dissolution procedures were used to isolate distinct forms of Fe-C interactions: (1) sodium pyrophosphate to isolate organo-mineral complexes, (2) hydroxylamine and (3) oxalate to isolate SRO phases, and (4) inorganic dithionite to isolate crystalline Fe oxides. Extracts were analysed for dissolved organic C (DOC) and Fe and Al concentrations to estimate SOM associated with each mineral phase. Soils were also subjected to SSA analysis, 57Fe-Mössbauer spectroscopy and X-ray diffraction before and after extraction to determine the contribution of extracted mineral phases to SOM stabilization capacity. Preliminary results indicate a dominance of secondary (hydr)oxides and kaolin minerals in surface soils, strongly driven by parent material. With depth, however, we observe a marked shift towards SRO mineral phases across both parent materials, suggesting that SRO-mediated organomineral associations are significant contributors to observed C storage in tropical subsoils.

Assessment of soil health and fertility indicators with mobile phone imagery

NASA Astrophysics Data System (ADS)

Aitkenhead, Matt; Gwatkin, Richard; Coull, Malcolm; Donnelly, David

2015-04-01

Work on rapid soil assessment in the field has led to many hand-held sensors for soil monitoring (e.g. NIR, FTIR, XRF). Recent work by a research team at the James Hutton Institute has led to an integrated framework of mobile phones, apps and server-side processing. One example of this is the SOCIT app for estimating soil organic matter and carbon using geolocated mobile phone camera imagery. The SOCIT app is only applicable for agricultural soils in Scotland, and our intention is to expand this work both geographically and in functional ability. Ongoing work for the development of a prototype app for estimating soil characteristics across Europe using mobile phone imagery and the JRC LUCAS dataset will be described. Additionally, we will demonstrate recent work in estimating a number of soil health indicators from more detailed analysis of soil photographs. Accuracy levels achieved for estimating soil organic matter and organic carbon content, pH, structure, cation exchange capacity and texture vary and are not as good as those achieved with laboratory analysis, but are suitable for rapid field-based assessment. Issues relating to this work include colour stabilisation and calibration, integration with data on site characteristics, data processing, model development and the ethical use of data captured by others, and each of these topics will also be discussed.

Assessing NIR & MIR Spectral Analysis as a Method for Soil C Estimation Across a Network of Sampling Sites

NASA Astrophysics Data System (ADS)

Spencer, S.; Ogle, S.; Borch, T.; Rock, B.

2008-12-01

Monitoring soil C stocks is critical to assess the impact of future climate and land use change on carbon sinks and sources in agricultural lands. A benchmark network for soil carbon monitoring of stock changes is being designed for US agricultural lands with 3000-5000 sites anticipated and re-sampling on a 5- to10-year basis. Approximately 1000 sites would be sampled per year producing around 15,000 soil samples to be processed for total, organic, and inorganic carbon, as well as bulk density and nitrogen. Laboratory processing of soil samples is cost and time intensive, therefore we are testing the efficacy of using near-infrared (NIR) and mid-infrared (MIR) spectral methods for estimating soil carbon. As part of an initial implementation of national soil carbon monitoring, we collected over 1800 soil samples from 45 cropland sites in the mid-continental region of the U.S. Samples were processed using standard laboratory methods to determine the variables above. Carbon and nitrogen were determined by dry combustion and inorganic carbon was estimated with an acid-pressure test. 600 samples are being scanned using a bench- top NIR reflectance spectrometer (30 g of 2 mm oven-dried soil and 30 g of 8 mm air-dried soil) and 500 samples using a MIR Fourier-Transform Infrared Spectrometer (FTIR) with a DRIFT reflectance accessory (0.2 g oven-dried ground soil). Lab-measured carbon will be compared to spectrally-estimated carbon contents using Partial Least Squares (PLS) multivariate statistical approach. PLS attempts to develop a soil C predictive model that can then be used to estimate C in soil samples not lab-processed. The spectral analysis of soil samples either whole or partially processed can potentially save both funding resources and time to process samples. This is particularly relevant for the implementation of a national monitoring network for soil carbon. This poster will discuss our methods, initial results and potential for using NIR and MIR spectral approaches to either replace or augment traditional lab-based carbon analyses of soils.

Heat as a tracer to estimate dissolved organic carbon flux from a restored wetland

USGS Publications Warehouse

Burow, K.R.; Constantz, J.; Fujii, R.

2005-01-01

Heat was used as a natural tracer to characterize shallow ground water flow beneath a complex wetland system. Hydrogeologic data were combined with measured vertical temperature profiles to constrain a series of two-dimensional, transient simulations of ground water flow and heat transport using the model code SUTRA (Voss 1990). The measured seasonal temperature signal reached depths of 2.7 m beneath the pond. Hydraulic conductivity was varied in each of the layers in the model in a systematic manual calibration of the two-dimensional model to obtain the best fit to the measured temperature and hydraulic head. Results of a series of representative best-fit simulations represent a range in hydraulic conductivity values that had the best agreement between simulated and observed temperatures and that resulted in simulated pond seepage values within 1 order of magnitude of pond seepage estimated from the water budget. Resulting estimates of ground water discharge to an adjacent agricultural drainage ditch were used to estimate potential dissolved organic carbon (DOC) loads resulting from the restored wetland. Estimated DOC loads ranged from 45 to 1340 g C/(m2 year), which is higher than estimated DOC loads from surface water. In spite of the complexity in characterizing ground water flow in peat soils, using heat as a tracer provided a constrained estimate of subsurface flow from the pond to the agricultural drainage ditch. Copyright ?? 2005 National Ground Water Association.

Scale - dependent effects on the surface energy fluxes modelling in Iberian oak-savanna (dehesa) using the Two-Source Energy Balance (TSEB)

NASA Astrophysics Data System (ADS)

Andreu, Ana; Nieto, Hector; Gómez-Giráldez, Pedro; González-Dugo, Maria P.

2017-04-01

Iberian semi-arid oak-savannas (dehesas) are complex ecosystems where bare soil and different layers of vegetation (grass/scrubs/trees) are distributed following heterogeneous patterns. An assumption of the two source energy balance models is that the effective source/sink for turbulent flux exchange at the surface(canopy/soil) is described by a bulk radiometric surface temperature (TRAD) and resistance. Therefore, the agreement of the TRAD used as an input to these models, with the "bulk" concept (determined by the spatial resolution), will influence the final energy fluxes estimations. The representativeness of the field-ground measurements, the spatial resolution of sensors, the averaging and the up-scaling of TRAD and the ecosystem vegetation parameters, will be crucial for the precision of the results, more than in homogeneous landscapes. The aim of this study is to analyze the scale-effects derived from TSEB application, comparing the observed energy fluxes and the estimated ones obtained from multiple TRAD data sources of different nature: tree/grass/soil ground-based observations, tower footprint, hyperspectral reflectance imagery acquired with an airborne platform, medium (Landsat) and low spatial resolution satellite data (Sentinel 3, MODIS), and how the up-scaling of the vegetation structural characteristics contribute to the discrepancies. The study area selected for this purpose is a dehesa site (Santa Clotilde, Cordoba), which present canopy mosaics (oak, annual grasses and bushes) differing in phenology, physiology and functioning, and bare soil, all of them influencing the turbulent and radiative exchanges.

Expanded uncertainty estimation methodology in determining the sandy soils filtration coefficient

NASA Astrophysics Data System (ADS)

Rusanova, A. D.; Malaja, L. D.; Ivanov, R. N.; Gruzin, A. V.; Shalaj, V. V.

2018-04-01

The combined standard uncertainty estimation methodology in determining the sandy soils filtration coefficient has been developed. The laboratory researches were carried out which resulted in filtration coefficient determination and combined uncertainty estimation obtaining.

Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS.

PubMed

Markose, Vipin Joseph; Jayappa, K S

2016-04-01

Most of the mountainous regions in tropical humid climatic zone experience severe soil loss due to natural factors. In the absence of measured data, modeling techniques play a crucial role for quantitative estimation of soil loss in such regions. The objective of this research work is to estimate soil loss and prioritize the sub-watersheds of Kali River basin using Revised Universal Soil Loss Equation (RUSLE) model. Various thematic layers of RUSLE factors such as rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C), and support practice factor (P) have been prepared by using multiple spatial and non-spatial data sets. These layers are integrated in geographic information system (GIS) environment and estimated the soil loss. The results show that ∼42 % of the study area falls under low erosion risk and only 6.97 % area suffer from very high erosion risk. Based on the rate of soil loss, 165 sub-watersheds have been prioritized into four categories-very high, high, moderate, and low erosion risk. Anthropogenic activities such as deforestation, construction of dams, and rapid urbanization are the main reasons for high rate of soil loss in the study area. The soil erosion rate and prioritization maps help in implementation of a proper watershed management plan for the river basin.

Extension of the soil conservation service rainfall-runoff methodology for ungaged watersheds

DOT National Transportation Integrated Search

1981-07-01

The estimation of direct runoff for ungaged watersheds is a common problem in : engineering hydrology. The method of the Soil Conservation Services (SCS) is widely used due to its ease of application. Runoff estimates are based upon the soil types an...

Investigation of the applicability of intrusion technology to estimate the resilient modulus of subgrade soil.

DOT National Transportation Integrated Search

2000-04-01

An innovative and simple approach is presented for estimation of the resilient modulus of subgrade soils utilizing the cone penetration test. Field and laboratory testing programs were carried out at seven sites that comprise three common soil types ...

Remediation of lead-contaminated soil with non-toxic biodegradable natural ligands extracted from soybean.

PubMed

Lee, Yong-Woo; Kim, Chulsung

2012-01-01

Bench-scale soil washing studies were performed to evaluate the potential application of non-toxic, biodegradable extracted soybean-complexing ligands for the remediation of lead-contaminated soils. Results showed that, with extracted soybean-complexing ligands, lead solubility extensively increased when pH of the solution was higher than 6, and approximately 10% (500 mg/kg) of lead was removed from a rifle range soil. Two potential primary factors controlling the effectiveness of lead extraction from lead-contaminated soils with natural ligands are adsorption of extracted aqueous lead ions onto the ground soybean and the pH of the extraction solution. More complexing ligands were extracted from the ground soybean as the reaction pH increased. As a result, significantly higher lead extraction efficiency was observed under basic environments. In addition, less adsorption onto soybean was observed when the pH of the solution was higher than 7. Among two available Lewis base functional groups in the extracted soybean-complexing ligands such as carboxylate and the alpha-amino functional groups, the non-protonated alpha-amino functional groups may play an important role for the dissolution of lead from lead-contaminated soil through the formation of soluble lead--ligand complexes.

Estimating the spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing

NASA Astrophysics Data System (ADS)

Gao, Shengguo; Zhu, Zhongli; Liu, Shaomin; Jin, Rui; Yang, Guangchao; Tan, Lei

2014-10-01

Soil moisture (SM) plays a fundamental role in the land-atmosphere exchange process. Spatial estimation based on multi in situ (network) data is a critical way to understand the spatial structure and variation of land surface soil moisture. Theoretically, integrating densely sampled auxiliary data spatially correlated with soil moisture into the procedure of spatial estimation can improve its accuracy. In this study, we present a novel approach to estimate the spatial pattern of soil moisture by using the BME method based on wireless sensor network data and auxiliary information from ASTER (Terra) land surface temperature measurements. For comparison, three traditional geostatistic methods were also applied: ordinary kriging (OK), which used the wireless sensor network data only, regression kriging (RK) and ordinary co-kriging (Co-OK) which both integrated the ASTER land surface temperature as a covariate. In Co-OK, LST was linearly contained in the estimator, in RK, estimator is expressed as the sum of the regression estimate and the kriged estimate of the spatially correlated residual, but in BME, the ASTER land surface temperature was first retrieved as soil moisture based on the linear regression, then, the t-distributed prediction interval (PI) of soil moisture was estimated and used as soft data in probability form. The results indicate that all three methods provide reasonable estimations. Co-OK, RK and BME can provide a more accurate spatial estimation by integrating the auxiliary information Compared to OK. RK and BME shows more obvious improvement compared to Co-OK, and even BME can perform slightly better than RK. The inherent issue of spatial estimation (overestimation in the range of low values and underestimation in the range of high values) can also be further improved in both RK and BME. We can conclude that integrating auxiliary data into spatial estimation can indeed improve the accuracy, BME and RK take better advantage of the auxiliary information compared to Co-OK, and BME outperforms RK by integrating the auxiliary data in a probability form.

Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

NASA Astrophysics Data System (ADS)

Lu, Yang; Steele-Dunne, Susan C.; Farhadi, Leila; van de Giesen, Nick

2017-12-01

Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.

Vapor Intrusion Estimation Tool for Unsaturated Zone Contaminant Sources. User’s Guide

DTIC Science & Technology

2016-08-30

324449 Page Intentionally Left Blank iii Executive Summary Soil vapor extraction (SVE) is a prevalent remediation approach for volatile contaminants...strength and location, vadose zone transport, and a model for estimating movement of soil -gas vapor contamination into buildings. The tool may be...framework for estimating the impact of a vadose zone contaminant source on soil gas concentrations and vapor intrusion into a building

Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

NASA Astrophysics Data System (ADS)

Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

Analysis of the coexisting pathways for NO and N2O formation in Chernozem using the (15)N-tracer SimKIM-Advanced model.

PubMed

Stange, Claus Florian; Spott, Oliver; Russow, Rolf

2013-01-01

The nitrogen (N) cycle consists of a variety of microbial processes. These processes often occur simultaneously in soils, but respond differently to local environmental conditions due to process-specific biochemical restrictions (e.g. oxygen levels). Hence, soil nitrogen cycling (e.g. soil N gas production through nitrification and denitrification) is individually affected through these processes, resulting in the complex and highly dynamic behaviour of total soil N turnover. The development and application of methods that facilitate the quantification of individual contributions of coexisting processes is a fundamental prerequisite for (i) understanding the dynamics of soil N turnover and (ii) implementing these processes in ecosystem models. To explain the unexpected results of the triplet tracer experiment (TTE) of Russow et al. (Role of nitrite and nitric oxide in the processes of nitrification and denitrification in soil: results from (15)N tracer experiments. Soil Biol Biochem. 2009;41:785-795) the existing SimKIM model was extended to the SimKIM-Advanced model through the addition of three separate nitrite subpools associated with ammonia oxidation, oxidation of organic nitrogen (Norg), and denitrification, respectively. For the TTE, individual treatments with (15)N ammonium, (15)N nitrate, and (15)N nitrite were conducted under oxic, hypoxic, and anoxic conditions, respectively, to clarify the role of nitric oxide as a denitrification intermediate during N2O formation. Using a split nitrite pool, this analysis model explains the observed differences in the (15)N enrichments in nitric oxide (NO) and nitrous oxide (N2O) which occurred in dependence on different oxygen concentrations. The change from oxic over hypoxic to anoxic conditions only marginally increased the NO and N2O release rates (1.3-fold). The analysis using the model revealed that, under oxic and hypoxic conditions, Norg-based N2O production was the dominant pathway, contributing to 90 and 50 % of the total soil N2O release. Under anoxic conditions, denitrification was the dominant process for soil N2O release. The relative contribution of Norg to the total soil NO release was small. Ammonia oxidation served as the major pathway of soil NO release under oxic and hypoxic conditions, while denitrification was dominant under anoxic conditions. The model parameters for soil with moderate soil organic matter (SOM) content were not scalable to an additional data set for soil with higher SOM content, indicating a strong influence of SOM content on microbial N turnover. Thus, parameter estimation had to be re-calculated for these conditions, highlighting the necessity of individual soil-dependent parameter estimations.

Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER)

NASA Astrophysics Data System (ADS)

Wang, S. G.; Li, X.; Han, X. J.; Jin, R.

2010-06-01

Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Furthermore, retrieval of soil moisture using AIEM-like models is a classic example of the underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to directly obtain surface roughness information along with soil moisture from multi-angular ASAR images. The method first used a semi-empirical relationship that connects the roughness slope (Zs) and the difference in backscattering coefficient (Δσ) from ASAR data in different incidence angles, in combination with an optimal calibration form consisting of two roughness parameters (the standard deviation of surface height and the correlation length), to estimate the roughness parameters. The deduced surface roughness was then used in the AIEM model for the retrieval of soil moisture. An evaluation of the proposed method was performed in a grassland site in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It has demonstrated that the method is feasible to achieve reliable estimation of soil water content. The key challenge to surface soil moisture retrieval is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.

Parameter-induced uncertainty quantification of crop yields, soil N2O and CO2 emission for 8 arable sites across Europe using the LandscapeDNDC model

NASA Astrophysics Data System (ADS)

Santabarbara, Ignacio; Haas, Edwin; Kraus, David; Herrera, Saul; Klatt, Steffen; Kiese, Ralf

2014-05-01

When using biogeochemical models to estimate greenhouse gas emissions at site to regional/national levels, the assessment and quantification of the uncertainties of simulation results are of significant importance. The uncertainties in simulation results of process-based ecosystem models may result from uncertainties of the process parameters that describe the processes of the model, model structure inadequacy as well as uncertainties in the observations. Data for development and testing of uncertainty analisys were corp yield observations, measurements of soil fluxes of nitrous oxide (N2O) and carbon dioxide (CO2) from 8 arable sites across Europe. Using the process-based biogeochemical model LandscapeDNDC for simulating crop yields, N2O and CO2 emissions, our aim is to assess the simulation uncertainty by setting up a Bayesian framework based on Metropolis-Hastings algorithm. Using Gelman statistics convergence criteria and parallel computing techniques, enable multi Markov Chains to run independently in parallel and create a random walk to estimate the joint model parameter distribution. Through means distribution we limit the parameter space, get probabilities of parameter values and find the complex dependencies among them. With this parameter distribution that determines soil-atmosphere C and N exchange, we are able to obtain the parameter-induced uncertainty of simulation results and compare them with the measurements data.

A multi-year estimate of methane fluxes in Alaska from CARVE atmospheric observations

PubMed Central

Miller, Scot M.; Miller, Charles E.; Commane, Roisin; Chang, Rachel Y.-W.; Dinardo, Steven J.; Henderson, John M.; Karion, Anna; Lindaas, Jakob; Melton, Joe R.; Miller, John B.; Sweeney, Colm; Wofsy, Steven C.; Michalak, Anna M.

2016-01-01

Methane (CH4) fluxes from Alaska and other arctic regions may be sensitive to thawing permafrost and future climate change, but estimates of both current and future fluxes from the region are uncertain. This study estimates CH4 fluxes across Alaska for 2012–2014 using aircraft observations from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and a geostatistical inverse model (GIM). We find that a simple flux model based on a daily soil temperature map and a static map of wetland extent reproduces the atmospheric CH4 observations at the state-wide, multi-year scale more effectively than global-scale, state-of-the-art process-based models. This result points to a simple and effective way of representing CH4 flux patterns across Alaska. It further suggests that contemporary process-based models can improve their representation of key processes that control fluxes at regional scales, and that more complex processes included in these models cannot be evaluated given the information content of available atmospheric CH4 observations. In addition, we find that CH4 emissions from the North Slope of Alaska account for 24% of the total statewide flux of 1.74 ± 0.44 Tg CH4 (for May–Oct.). Contemporary global-scale process models only attribute an average of 3% of the total flux to this region. This mismatch occurs for two reasons: process models likely underestimate wetland area in regions without visible surface water, and these models prematurely shut down CH4 fluxes at soil temperatures near 0°C. As a consequence, wetlands covered by vegetation and wetlands with persistently cold soils could be larger contributors to natural CH4 fluxes than in process estimates. Lastly, we find that the seasonality of CH4 fluxes varied during 2012–2014, but that total emissions did not differ significantly among years, despite substantial differences in soil temperature and precipitation; year-to-year variability in these environmental conditions did not affect obvious changes in total CH4 fluxes from the state. PMID:28066129

A multi-year estimate of methane fluxes in Alaska from CARVE atmospheric observations.

PubMed

Miller, Scot M; Miller, Charles E; Commane, Roisin; Chang, Rachel Y-W; Dinardo, Steven J; Henderson, John M; Karion, Anna; Lindaas, Jakob; Melton, Joe R; Miller, John B; Sweeney, Colm; Wofsy, Steven C; Michalak, Anna M

2016-10-01

Methane (CH 4 ) fluxes from Alaska and other arctic regions may be sensitive to thawing permafrost and future climate change, but estimates of both current and future fluxes from the region are uncertain. This study estimates CH 4 fluxes across Alaska for 2012-2014 using aircraft observations from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and a geostatistical inverse model (GIM). We find that a simple flux model based on a daily soil temperature map and a static map of wetland extent reproduces the atmospheric CH 4 observations at the state-wide, multi-year scale more effectively than global-scale, state-of-the-art process-based models. This result points to a simple and effective way of representing CH 4 flux patterns across Alaska. It further suggests that contemporary process-based models can improve their representation of key processes that control fluxes at regional scales, and that more complex processes included in these models cannot be evaluated given the information content of available atmospheric CH 4 observations. In addition, we find that CH 4 emissions from the North Slope of Alaska account for 24% of the total statewide flux of 1.74 ± 0.44 Tg CH 4 ( for May-Oct.). Contemporary global-scale process models only attribute an average of 3% of the total flux to this region. This mismatch occurs for two reasons: process models likely underestimate wetland area in regions without visible surface water, and these models prematurely shut down CH 4 fluxes at soil temperatures near 0°C. As a consequence, wetlands covered by vegetation and wetlands with persistently cold soils could be larger contributors to natural CH 4 fluxes than in process estimates. Lastly, we find that the seasonality of CH 4 fluxes varied during 2012-2014, but that total emissions did not differ significantly among years, despite substantial differences in soil temperature and precipitation; year-to-year variability in these environmental conditions did not affect obvious changes in total CH 4 fluxes from the state.

A simplified 137Cs transport model for estimating erosion rates in undisturbed soil.

PubMed

Zhang, Xinbao; Long, Yi; He, Xiubin; Fu, Jiexiong; Zhang, Yunqi

2008-08-01

(137)Cs is an artificial radionuclide with a half-life of 30.12 years which released into the environment as a result of atmospheric testing of thermo-nuclear weapons primarily during the period of 1950s-1970s with the maximum rate of (137)Cs fallout from atmosphere in 1963. (137)Cs fallout is strongly and rapidly adsorbed by fine particles in the surface horizons of the soil, when it falls down on the ground mostly with precipitation. Its subsequent redistribution is associated with movements of the soil or sediment particles. The (137)Cs nuclide tracing technique has been used for assessment of soil losses for both undisturbed and cultivated soils. For undisturbed soils, a simple profile-shape model was developed in 1990 to describe the (137)Cs depth distribution in profile, where the maximum (137)Cs occurs in the surface horizon and it exponentially decreases with depth. The model implied that the total (137)Cs fallout amount deposited on the earth surface in 1963 and the (137)Cs profile shape has not changed with time. The model has been widely used for assessment of soil losses on undisturbed land. However, temporal variations of (137)Cs depth distribution in undisturbed soils after its deposition on the ground due to downward transport processes are not considered in the previous simple profile-shape model. Thus, the soil losses are overestimated by the model. On the base of the erosion assessment model developed by Walling, D.E., He, Q. [1999. Improved models for estimating soil erosion rates from cesium-137 measurements. Journal of Environmental Quality 28, 611-622], we discuss the (137)Cs transport process in the eroded soil profile and make some simplification to the model, develop a method to estimate the soil erosion rate more expediently. To compare the soil erosion rates calculated by the simple profile-shape model and the simple transport model, the soil losses related to different (137)Cs loss proportions of the reference inventory at the Kaixian site of the Three Gorge Region, China are estimated by the two models. The over-estimation of the soil loss by using the previous simple profile-shape model obviously increases with the time period from the sampling year to the year of 1963 and (137)Cs loss proportion of the reference inventory. As to 20-80% of (137)Cs loss proportions of the reference inventory at the Kaixian site in 2004, the annual soil loss depths estimated by the new simplified transport process model are only 57.90-56.24% of the values estimated by the previous model.

Relative Bioavailability and Bioaccessability and Speciation of ...

EPA Pesticide Factsheets

Background: Assessment of soil arsenic (As) bioavailability may profoundly affect the extent of remediation required at contaminated sites by improving human exposure estimates. Because small adjustments in soil As bioavailability estimates can significantly alter risk assessments and remediation goals, convenient, rapid, reliable, and inexpensive tools are needed to determine soil As bioavailability. Objectives: We evaluated inexpensive methods for assessing As bioavailability in soil as a means to improve human exposure estimates and potentially reduce remediation costs. Methods: Nine soils from residential sites affected by mining or smelting activity and two National Institute of Standards and Technology standard reference materials were evaluated for As bioavailability, bioaccessibility, and speciation. Arsenic bioavailability was determined using an in vivo mouse model, and As bioaccessibility was determined using the Solubility/Bioavailability Research Consortium in vitro assay. Arsenic speciation in soil and selected soil physicochemical properties were also evaluated to determine whether these parameters could be used as predictors of As bio¬availability and bioaccessibility. Results: In the mouse assay, we compared bioavailabilities of As in soils with that for sodium arsenate. Relative bioavailabilities (RBAs) of soil As ranged from 11% to 53% (mean, 33%). In vitro soil As bioaccessibility values were strongly correlated with soil As RBAs (R

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Microwave remote sensing and its application to soil moisture detection

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Experimental measurements were utilized to demonstrate a procedure for estimating soil moisture, using a passive microwave sensor. The investigation showed that 1.4 GHz and 10.6 GHz can be used to estimate the average soil moisture within two depths; however, it appeared that a frequency less than 10.6 GHz would be preferable for the surface measurement. Average soil moisture within two depths would provide information on the slope of the soil moisture gradient near the surface. Measurements showed that a uniform surface roughness similar to flat tilled fields reduced the sensitivity of the microwave emission to soil moisture changes. Assuming that the surface roughness was known, the approximate soil moisture estimation accuracy at 1.4 GHz calculated for a 25% average soil moisture and an 80% degree of confidence, was +3% and -6% for a smooth bare surface, +4% and -5% for a medium rough surface, and +5.5% and -6% for a rough surface.

Effect of Climate Change on Soil Temperature in Swedish Boreal Forests

PubMed Central

Jungqvist, Gunnar; Oni, Stephen K.; Teutschbein, Claudia; Futter, Martyn N.

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions. PMID:24747938

Effect of climate change on soil temperature in Swedish boreal forests.

PubMed

Jungqvist, Gunnar; Oni, Stephen K; Teutschbein, Claudia; Futter, Martyn N

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions.

Aspergillus and Penicillium (Eurotiales: Trichocomaceae) in soils of the Brazilian tropical dry forest: diversity in an area of environmental preservation.

PubMed

Barbosa, Renan do Nascimento; Bezerra, Jadson Diogo Pereira; Costa, Phelipe Manoel Oller; de Lima-Júnior, Nelson Correia; Alves de Souza Galvão, Ivana Roberta Gomes; Alves dos Santos-Júnior, Anthony; Fernandes, Maria José; de Souza-Motta, Cristina Maria; Oliveira, Neiva Tinti

2016-03-01

Soil is a complex biological system that plays a key role for plants and animals, especially in dry forests such as the Caatinga. Fungi from soils, such as Aspergillus and Penicillium, can be used as bioindica- tors for biodiversity conservation. The aim of this study was to isolate and identify species of Aspergillus and Penicillium in soil, from the municipalities of Tupanatinga and Ibimirim, with dry forests, in the Catimbau National Park. Five collections were performed in each area during the drought season of 2012, totaling 25 soil samples per area. Fungi were isolated by suspending soil samples in sterile distilled water and plating on Sabouraud Agar media plus Chloramphenicol and Rose Bengal, and Glycerol Dicloran Agar. Isolates were identified by morphological taxonomy in the Culture Collection Laboratory and confirmed by sequencing of the Internal Transcribed Spacer of rDNA. A total of 42 species were identified, of which 22 belong to the genus Aspergillus and 20 to Penicillium. Penicillium isolates showed uniform distribution from the collecting area in Tupanatinga, and the evenness indices found were 0.92 and 0.88 in Tupanatinga and Ibimirim, respectively. Among isolates of Aspergillus evenness, the value found in Tupanatinga (0.85) was very close to that found in Ibimirim (0.86). High diversity and low dominance of fungi in soil samples was observed. These results con- tributed to the estimation of fungal diversity in dry environments of the Caatinga, where diversity is decreasing in soils that have undergone disturbance.

Determination of Nitroaromatic, Nitramine, and Nitrate Ester Explosives in Soils Using GC-ECD

DTIC Science & Technology

1999-08-01

for supplying soils from minefields; and Dr. Paul H. Miyares, CRREL, for HPLC analysis of Fort Leonard Wood soil extracts. ii CONTENTS P reface...42 ILLUSTRATIONS Figure 1. Correlation analysis of GC-ECD concentration (mg/kg) estimates with those from HPLC -UV...kg) estimates with those from HPLC -UV analysis using splits of the same acetonitrile extract from archived soils

Estimating soil labile organic carbon and potential turnover rates using a sequential fumigation–incubation procedure.

Treesearch

X.M. Zoua; H.H. Ruanc; Y. Fua; X.D. Yanga; L.Q. Sha

2005-01-01

Labile carbon is the fraction of soil organic carbon with most rapid turnover times and its oxidation drives the flux of CO2 between soils and atmosphere. Available chemical and physical fractionation methods for estimating soil labile organic carbon are indirect and lack a clear biological definition. We have modified the well-established Jenkinson and Powlson’s...

Development of a predictive model to estimate the effect of soil solarization on survival of soilborne inoculum of Phytophthora ramorum and Phytophthora pini

Treesearch

Fumiaki Funahashi; Jennifer L. Parke

2017-01-01

Soil solarization has been shown to be an effective tool to manage Phytophthora spp. within surface soils, but estimating the minimum time required to complete local eradication under variable weather conditions remains unknown. A mathematical model could help predict the effectiveness of solarization at different sites and soil depths....

HDMR methods to assess reliability in slope stability analyses

NASA Astrophysics Data System (ADS)

Kozubal, Janusz; Pula, Wojciech; Vessia, Giovanna

2014-05-01

Stability analyses of complex rock-soil deposits shall be tackled considering the complex structure of discontinuities within rock mass and embedded soil layers. These materials are characterized by a high variability in physical and mechanical properties. Thus, to calculate the slope safety factor in stability analyses two issues must be taken into account: 1) the uncertainties related to structural setting of the rock-slope mass and 2) the variability in mechanical properties of soils and rocks. High Dimensional Model Representation (HDMR) (Chowdhury et al. 2009; Chowdhury and Rao 2010) can be used to carry out the reliability index within complex rock-soil slopes when numerous random variables with high coefficient of variations are considered. HDMR implements the inverse reliability analysis, meaning that the unknown design parameters are sought provided that prescribed reliability index values are attained. Such approach uses implicit response functions according to the Response Surface Method (RSM). The simple RSM can be efficiently applied when less than four random variables are considered; as the number of variables increases, the efficiency in reliability index estimation decreases due to the great amount of calculations. Therefore, HDMR method is used to improve the computational accuracy. In this study, the sliding mechanism in Polish Flysch Carpathian Mountains have been studied by means of HDMR. The Southern part of Poland where Carpathian Mountains are placed is characterized by a rather complicated sedimentary pattern of flysh rocky-soil deposits that can be simplified into three main categories: (1) normal flysch, consisting of adjacent sandstone and shale beds of approximately equal thickness, (2) shale flysch, where shale beds are thicker than adjacent sandstone beds, and (3) sandstone flysch, where the opposite holds. Landslides occur in all flysch deposit types thus some configurations of possible unstable settings (within fractured rocky-soil masses) resulting in sliding mechanisms have been investigated in this study. The reliability indices values drawn from the HDRM method have been compared with conventional approaches as neural networks: the efficiency of HDRM is shown in the case studied. References Chowdhury R., Rao B.N. and Prasad A.M. 2009. High-dimensional model representation for structural reliability analysis. Commun. Numer. Meth. Engng, 25: 301-337. Chowdhury R. and Rao B. 2010. Probabilistic Stability Assessment of Slopes Using High Dimensional Model Representation. Computers and Geotechnics, 37: 876-884.

A global analysis of soil microbial biomass carbon, nitrogen and phosphorus in terrestrial ecosystems

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

Xu, Xiaofeng; Thornton, Peter E; Post, Wilfred M

2013-01-01

Soil microbes play a pivotal role in regulating land-atmosphere interactions; the soil microbial biomass carbon (C), nitrogen (N), phosphorus (P) and C:N:P stoichiometry are important regulators for soil biogeochemical processes; however, the current knowledge on magnitude, stoichiometry, storage, and spatial distribution of global soil microbial biomass C, N, and P is limited. In this study, 3087 pairs of data points were retrieved from 281 published papers and further used to summarize the magnitudes and stoichiometries of C, N, and P in soils and soil microbial biomass at global- and biome-levels. Finally, global stock and spatial distribution of microbial biomass Cmore » and N in 0-30 cm and 0-100 cm soil profiles were estimated. The results show that C, N, and P in soils and soil microbial biomass vary substantially across biomes; the fractions of soil nutrient C, N, and P in soil microbial biomass are 1.6% in a 95% confidence interval of (1.5%-1.6%), 2.9% in a 95% confidence interval of (2.8%-3.0%), and 4.4% in a 95% confidence interval of (3.9%-5.0%), respectively. The best estimates of C:N:P stoichiometries for soil nutrients and soil microbial biomass are 153:11:1, and 47:6:1, respectively, at global scale, and they vary in a wide range among biomes. Vertical distribution of soil microbial biomass follows the distribution of roots up to 1 m depth. The global stock of soil microbial biomass C and N were estimated to be 15.2 Pg C and 2.3 Pg N in the 0-30 cm soil profiles, and 21.2 Pg C and 3.2 Pg N in the 0-100 cm soil profiles. We did not estimate P in soil microbial biomass due to data shortage and insignificant correlation with soil total P and climate variables. The spatial patterns of soil microbial biomass C and N were consistent with those of soil organic C and total N, i.e. high density in northern high latitude, and low density in low latitudes and southern hemisphere.« less

Anthropogenic radionuclides for estimating rates of soil redistribution by wind

USDA-ARS?s Scientific Manuscript database

Erosion of soil by wind and water is a degrading process that affects millions of hectares worldwide. Atmospheric testing of nuclear weapons and the resulting fallout of anthropogenic radioisotopes, particularly Cesium 137, has made possible the estimation of mean soil redistribution rates. The pe...

Anthropogenic radioisotopes to estimate rates of soil redistribution by wind

USDA-ARS?s Scientific Manuscript database

Erosion of soil by wind and water is a degrading process that affects millions of hectares worldwide. Atmospheric testing of nuclear weapons and the resulting fallout of anthropogenic radioisotopes, particularly Cesium 137, has made possible the estimation of mean soil redistribution rates. The pe...

Improving root-zone soil moisture estimations using dynamic root growth and crop phenology

USDA-ARS?s Scientific Manuscript database

Water Energy Balance (WEB) Soil Vegetation Atmosphere Transfer (SVAT) modelling can be used to estimate soil moisture by forcing the model with observed data such as precipitation and solar radiation. Recently, an innovative approach that assimilates remotely sensed thermal infrared (TIR) observatio...

Fusion of spectral and electrochemical sensor data for estimating soil macronutrients

USDA-ARS?s Scientific Manuscript database

Rapid and efficient quantification of plant-available soil phosphorus (P) and potassium (K) is needed to support variable-rate fertilization strategies. Two methods that have been used for estimating these soil macronutrients are diffuse reflectance spectroscopy in visible and near-infrared (VNIR) w...

Synergistic method for boreal soil moisture and soil freeze retrievals using active and passive microwave instruments

NASA Astrophysics Data System (ADS)

Smolander, Tuomo; Lemmetyinen, Juha; Rautiainen, Kimmo; Schwank, Mike; Pulliainen, Jouni

2017-04-01

Soil moisture and soil freezing are important for diverse hydrological, biogeochemical, and climatological applications. They affect surface energy balance, surface and subsurface water flow, and exchange rates of carbon with the atmosphere. Soil freezing controls important biogeochemical processes, like photosynthetic activity of plants and microbial activity within soils. Permafrost covers approximately 24% of the land surface in the Northern Hemisphere and seasonal freezing occurs on approximately 51% of the area. The retrieval method presented is based on an inversion technique and applies a semiempirical backscattering model that describes the dependence of radar backscattering of forest as a function of stem volume, soil permittivity, the extinction coefficient of forest canopy, surface roughness, incidence angle, and radar frequency. It gives an estimate of soil permittivity using active microwave measurements. Applying a Bayesian assimilation scheme, it is also possible to use other soil permittivity retrievals to regulate this estimate to combine for example low resolution passive observations with high resolution active observations for a synergistic retrieval. This way the higher variance in the active retrieval can be constricted with the passive retrieval when at the same time the spatial resolution of the product is improved compared to the passive-only retrieval. The retrieved soil permittivity estimate can be used to detect soil freeze/thaw state by considering the soil to be frozen when the estimate is below a threshold value. The permittivity retrieval can also be used to estimate the relative moisture of the soil. The method was tested using SAR (Synthetic Aperture Radar) measurements from ENVISAT ASAR instrument for the years 2010-2012 and from Sentinel-1 satellite for the years 2015-2016 in Sodankylä area in Northern Finland. The synergistic method was tested combining the SAR measurements with a SMOS (Soil Moisture Ocean Salinity) radiometer based retrieval. The results were validated using in situ measurements from automatic soil state observation stations in Sodankylä calibration and validation (CAL-VAL) site, which is a reference site for several EO (Earth Observation) data products.

Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

NASA Astrophysics Data System (ADS)

Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

2017-03-01

Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.

Soil clay content controls the turnover of slow soil carbon across Chinese cropland

NASA Astrophysics Data System (ADS)

Feng, W.; Jiang, J.; Li, J.

2017-12-01

Improving the prediction of changes in global soil organic carbon (SOC) lies in accurate estimate of C inputs to soils and SOC turnover time. Since C inputs to soils in cropland can be estimated due to well documented data of crop yields, SOC turnover rate becomes critical for accurate prediction of changes in SOC. The laboratory incubation is widely used but cannot well represent the turnover of slow soil C that accounts for the majority of total SOC, while the long-term observation of temporal changes in SOC stock offers an opportunity to estimate the turnover of slow soil C. Using time series data of SOC stock of twenty long-term agricultural trials that have initiated since 1990 in China, we estimated SOC turnover rates based on changes in soil C pool size and aimed to identify the dominant controls on SOC turnover rate across Chinese cropland. We used the two-pool first-order kinetic soil C model and the inverse modeling with Markov chain the Monte Carlo algorithm, and estimated humification coefficient (h) of C inputs to soils, turnover rates of fast and slow soil C pools, and the transfer coefficient between these two soil C pools. The preliminary results show that the turnover rate of slow soil C is positively correlated with climate (i.e. mean annual temperature and precipitation) but negatively correlated with the clay content, demonstrating that the clay content is important in regulating SOC turnover rates. The ratio of humification coefficient to C turnover rate (h/k) that indicates soil C sequestration efficiency, is negatively correlated with climate and positively correlated with the clay content. In addition, the quantity of C inputs is correlated with h/k and the turnover rate of slow soil C, suggesting that the quantity of C inputs plays an important role in mediating C sequestration efficiency. Further results will inform us the main controls on SOC turnover in Chinese cropland. Keywords: SOC; turnover; long-term trial; temporal change; clay content; inverse modeling

Use of a (137)Cs re-sampling technique to investigate temporal changes in soil erosion and sediment mobilisation for a small forested catchment in southern Italy.

PubMed

Porto, Paolo; Walling, Des E; Alewell, Christine; Callegari, Giovanni; Mabit, Lionel; Mallimo, Nicola; Meusburger, Katrin; Zehringer, Markus

2014-12-01

Soil erosion and both its on-site and off-site impacts are increasingly seen as a serious environmental problem across the world. The need for an improved evidence base on soil loss and soil redistribution rates has directed attention to the use of fallout radionuclides, and particularly (137)Cs, for documenting soil redistribution rates. This approach possesses important advantages over more traditional means of documenting soil erosion and soil redistribution. However, one key limitation of the approach is the time-averaged or lumped nature of the estimated erosion rates. In nearly all cases, these will relate to the period extending from the main period of bomb fallout to the time of sampling. Increasing concern for the impact of global change, particularly that related to changing land use and climate change, has frequently directed attention to the need to document changes in soil redistribution rates within this period. Re-sampling techniques, which should be distinguished from repeat-sampling techniques, have the potential to meet this requirement. As an example, the use of a re-sampling technique to derive estimates of the mean annual net soil loss from a small (1.38 ha) forested catchment in southern Italy is reported. The catchment was originally sampled in 1998 and samples were collected from points very close to the original sampling points again in 2013. This made it possible to compare the estimate of mean annual erosion for the period 1954-1998 with that for the period 1999-2013. The availability of measurements of sediment yield from the catchment for parts of the overall period made it possible to compare the results provided by the (137)Cs re-sampling study with the estimates of sediment yield for the same periods. In order to compare the estimates of soil loss and sediment yield for the two different periods, it was necessary to establish the uncertainty associated with the individual estimates. In the absence of a generally accepted procedure for such calculations, key factors influencing the uncertainty of the estimates were identified and a procedure developed. The results of the study demonstrated that there had been no significant change in mean annual soil loss in recent years and this was consistent with the information provided by the estimates of sediment yield from the catchment for the same periods. The study demonstrates the potential for using a re-sampling technique to document recent changes in soil redistribution rates. Copyright © 2014. Published by Elsevier Ltd.

Linking soil moisture balance and source-responsive models to estimate diffuse and preferential components of groundwater recharge

USGS Publications Warehouse

Cuthbert, M.O.; Mackay, R.; Nimmo, J.R.

2012-01-01

Results are presented of a detailed study into the vadose zone and shallow water table hydrodynamics of a field site in Shropshire, UK. A conceptual model is developed and tested using a range of numerical models, including a modified soil moisture balance model (SMBM) for estimating groundwater recharge in the presence of both diffuse and preferential flow components. Tensiometry reveals that the loamy sand topsoil wets up via macropore flow and subsequent redistribution of moisture into the soil matrix. Recharge does not occur until near-positive pressures are achieved at the top of the sandy glaciofluvial outwash material that underlies the topsoil, about 1 m above the water table. Once this occurs, very rapid water table rises follow. This threshold behaviour is attributed to the vertical discontinuity in the macropore system due to seasonal ploughing of the topsoil, and a lower permeability plough/iron pan restricting matrix flow between the topsoil and the lower outwash deposits. Although the wetting process in the topsoil is complex, a SMBM is shown to be effective in predicting the initiation of preferential flow from the base of the topsoil into the lower outwash horizon. The rapidity of the response at the water table and a water table rise during the summer period while flow gradients in the unsaturated profile were upward suggest that preferential flow is also occurring within the outwash deposits below the topsoil. A variation of the source-responsive model proposed by Nimmo (2010) is shown to reproduce the observed water table dynamics well in the lower outwash horizon when linked to a SMBM that quantifies the potential recharge from the topsoil. The results reveal new insights into preferential flow processes in cultivated soils and provide a useful and practical approach to accounting for preferential flow in studies of groundwater recharge estimation.

A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Salvucci, G.

2012-12-01

Soil moisture influences many hydrological processes in the water and energy cycles, such as runoff generation, groundwater recharge, and evapotranspiration, and thus is important for climate modeling, water resources management, agriculture, and civil engineering. Large-scale estimates of soil moisture are produced almost exclusively from remote sensing, while validation of remotely sensed soil moisture has relied heavily on ground truthing, which is at an inherently smaller scale. Here we present a complementary method to determine the information content in different soil moisture products using only large-scale precipitation data (i.e. without modeling). This study builds on the work of Salvucci [2001], Saleem and Salvucci [2002], and Sun et al. [2011], in which precipitation was conditionally averaged according to soil moisture level, resulting in moisture-outflow curves that estimate the dependence of drainage, runoff, and evapotranspiration on soil moisture (i.e. sigmoidal relations that reflect stressed evapotranspiration for dry soils, roughly constant flux equal to potential evaporation minus capillary rise for moderately dry soils, and rapid drainage for very wet soils). We postulate that high quality satellite estimates of soil moisture, using large-scale precipitation data, will yield similar sigmoidal moisture-outflow curves to those that have been observed at field sites, while poor quality estimates will yield flatter, less informative curves that explain less of the precipitation variability. Following this logic, gridded ¼ degree NLDAS precipitation data were compared to three AMSR-E derived soil moisture products (VUA-NASA, or LPRM [Owe et al., 2001], NSIDC [Njoku et al., 2003], and NSIDC-LSP [Jones & Kimball, 2011]) for a period of nine years (2001-2010) across the contiguous United States. Gaps in the daily soil moisture data were filled using a multiple regression model reliant on past and future soil moisture and precipitation, and soil moisture was then converted to a ranked wetness index, in order to reconcile the wide range and magnitude of the soil moisture products. Generalized linear models were employed to fit a polynomial model to precipitation, given wetness index. Various measures of fit (e.g. log likelihood) were used to judge the amount of information in each soil moisture product, as indicated by the amount of precipitation variability explained by the fitted model. Using these methods, regional patterns appear in soil moisture product performance.

Estimation of p,p'-DDT degradation in soil by modeling and constraining hydrological and biogeochemical controls.

PubMed

Sanka, Ondrej; Kalina, Jiri; Lin, Yan; Deutscher, Jan; Futter, Martyn; Butterfield, Dan; Melymuk, Lisa; Brabec, Karel; Nizzetto, Luca

2018-08-01

Despite not being used for decades in most countries, DDT remains ubiquitous in soils due to its persistence and intense past usage. Because of this it is still a pollutant of high global concern. Assessing long term dissipation of DDT from this reservoir is fundamental to understand future environmental and human exposure. Despite a large research effort, key properties controlling fate in soil (in particular, the degradation half-life (τ soil )) are far from being fully quantified. This paper describes a case study in a large central European catchment where hundreds of measurements of p,p'-DDT concentrations in air, soil, river water and sediment are available for the last two decades. The goal was to deliver an integrated estimation of τ soil by constraining a state-of-the-art hydrobiogeochemical-multimedia fate model of the catchment against the full body of empirical data available for this area. The INCA-Contaminants model was used for this scope. Good predictive performance against an (external) dataset of water and sediment concentrations was achieved with partitioning properties taken from the literature and τ soil estimates obtained from forcing the model against empirical historical data of p,p'-DDT in the catchment multicompartments. This approach allowed estimation of p,p'-DDT degradation in soil after taking adequate consideration of losses due to runoff and volatilization. Estimated τ soil ranged over 3000-3800 days. Degradation was the most important loss process, accounting on a yearly basis for more than 90% of the total dissipation. The total dissipation flux from the catchment soils was one order of magnitude higher than the total current atmospheric input estimated from atmospheric concentrations, suggesting that the bulk of p,p'-DDT currently being remobilized or lost is essentially that accumulated over two decades ago. Copyright © 2018 Elsevier Ltd. All rights reserved.

Investigation of Methane and Soil Carbon Dynamics Using Near Surface Geophysical Methods at the Tanoma Educational Wetland Site, Tanoma, Pennsylvania

NASA Astrophysics Data System (ADS)

Seidel, A. D.; Mount, G.

2017-12-01

Studies to constrain methane budgets of Pennsylvania have sought to quantify the amount and rate of fugitive methane released during industrial natural gas development. However, contributions from other environmental systems such as artificial wetlands used to treat part of the 300 million gallons per day of acid mine drainage (AMD) are often not understated or not considered. The artificial wetlands are sources of both biogenic and thermogenic methane and are used to treat AMD which would otherwise flow untreated into Pennsylvania surface waters. Our research utilizes a combination of indirect non-invasive geophysical methods (ground penetrating radar, GPR) and the complex refractive index model, aerial imagery, and direct measurements (coring and gas traps) to estimate the contribution of biogenic methane from wetlands and legacy thermogenic methane from acid mine drainage from a flooded coal mine at an artificial wetland designed to treat these polluted waters at Tanoma, Pennsylvania. Our approach uses (3D) GPR surveys to define the thickness of the soil from the surface to the regolith-bedrock interface to create a volume model of potential biogenic gas stores. Velocity data derived from the GPR is then used to calculate the dielectric permittivity of the soil and then modeled for gas content when considering the saturation, porosity and amount of soil present. Depth-profile cores are extracted to confirm soil column interfaces and determine changes in soil carbon content. Comparisons of gas content are made with gas traps placed across the wetlands that measure the variability of gaseous methane released. In addition, methane dissolved in the waters from biogenic processes in the wetland and thermogenic processes underground are analyzed by a gas chromatograph to quantify those additions. In sum, these values can then be extrapolated to estimate carbon stocks in AMD areas such as those with similar water quality and vegetation types in the Appalachian region. This research demonstrates the ability of indirect geophysical methods and the CRIM petrophysical model to estimate methane gas fluxes and total carbon stocks within wetlands. This will be of assistance to understand the impact of methane released from naturally occurring sources and legacy coal mines, not only commercial extraction and distribution.

Geocryological hazards and destructive exogenic geological processes on lines of linear constructions of tundra and forest-tundra zones of Western Siberia

NASA Astrophysics Data System (ADS)

Ospennikov, E. N.; Hilimonjuk, V. Z.

2009-04-01

Economic development of northern oil-and gas-bearing regions, even by application of shift method, is accompanied by a construction of the linear transport systems including automobile- and railways. Construction of such roads is connected with the risks caused by the whole complex of hazards, defined by the environmental features of the region, including flat surface with strong marshiness, development of a peat, fine-grained and easily eroded friable sedimentations, as well as by complicated geocryological conditions. Geocryological conditions of Western Siberia area are characterized by a rather high heterogeneity. This implies the strong variability of permafrost soils distribution, their thickness and continuity, depths of seasonal thawing and frost penetration, and also intact development of geocryological processes and phenomena. Thermokarst, thermo erosion and thermo-abrasion develop in the natural conditions. These processes are caused by partial degradation of permafrost. A frost heave also occurs during their seasonal or long-term freezing. Failure of an environment, which is always peculiar to construction of the roads, causes reorganization of geocryological systems that is accompanied by occurrence of dangerous geocryological processes, such as technogenic thermokarst (with formation of various negative forms of a relief: from fine subsidence up to small and average sized lakes), frost heave ground (with formation frost mound in height up to 0,5 - 1,5 meters and more), thermal erosion (gullies and ravines with volume of the born material up to several thousand cubic meters). Development of these destructive processes in a road stripes leads to emergencies owing to deformations and destructions of an earthen cloth, and to failure of natural tundra and forest-tundra ecosystems. The methodical approaches based on typification and zoning of the area by its environmental complex have been developed for an estimation of geocryological hazards at linear construction. The estimation was carried out on the basis of the analysis, including features of geocryological processes development in natural conditions and certain types of geocryological conditions; character of the failures caused by construction and operation of roads; hazard severity of destructive processes for certain geotechnical systems of roads. Three categories of territories have been specified as a result on base of hazard severity: very complex, complex and simple. Very complex ones are characterized by close to 0 0C by average annual temperatures of soils, presence massive pore and it is repeated- wedge ices, a wide circulation it is high ice bearing ground and active modern development of processes thermokarst, thermo erosion and frost heave. Simple territories differ in low average annual temperatures of soils (below -4 0С), absence massive underground ices and weak development of geocryological processes. All other territories representing potential hazard at adverse change of an environment are classified as complex territories.

Soil Water Availability Modulation Over Estimated Relative Yield Losses in Wheat (Triticum aestivum L.) Due to Ozone Exposure

PubMed Central

De la Torre, Daniel; Sierra, Maria Jose

2007-01-01

The approach developed by Fuhrer in 1995 to estimate wheat yield losses induced by ozone and modulated by the soil water content (SWC) was applied to the data on Catalonian wheat yields. The aim of our work was to apply this approach and adjust it to Mediterranean environmental conditions by means of the necessary corrections. The main objective pursued was to prove the importance of soil water availability in the estimation of relative wheat yield losses as a factor that modifies the effects of tropospheric ozone on wheat, and to develop the algorithms required for the estimation of relative yield losses, adapted to the Mediterranean environmental conditions. The results show that this is an easy way to estimate relative yield losses just using meteorological data, without using ozone fluxes, which are much more difficult to calculate. Soil water availability is very important as a modulating factor of the effects of ozone on wheat; when soil water availability decreases, almost twice the amount of accumulated exposure to ozone is required to induce the same percentage of yield loss as in years when soil water availability is high. PMID:17619747

A new device to estimate abundance of moist-soil plant seeds

USGS Publications Warehouse

Penny, E.J.; Kaminski, R.M.; Reinecke, K.J.

2006-01-01

Methods to sample the abundance of moist-soil seeds efficiently and accurately are critical for evaluating management practices and determining food availability. We adapted a portable, gasoline-powered vacuum to estimate abundance of seeds on the surface of a moist-soil wetland in east-central Mississippi and evaluated the sampler by simulating conditions that researchers and managers may experience when sampling moist-soil areas for seeds. We measured the percent recovery of known masses of seeds by the vacuum sampler in relation to 4 experimentally controlled factors (i.e., seed-size class, sample mass, soil moisture class, and vacuum time) with 2-4 levels per factor. We also measured processing time of samples in the laboratory. Across all experimental factors, seed recovery averaged 88.4% and varied little (CV = 0.68%, n = 474). Overall, mean time to process a sample was 30.3 ? 2.5 min (SE, n = 417). Our estimate of seed recovery rate (88%) may be used to adjust estimates for incomplete seed recovery, or project-specific correction factors may be developed by investigators. Our device was effective for estimating surface abundance of moist-soil plant seeds after dehiscence and before habitats were flooded.

Soil Moisture or Groundwater?

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2017-12-01

Partitioning the vertically integrated water storage variations estimated from GRACE satellite data into the components of which it is comprised requires independent information. Land surface models, which simulate the transfer and storage of moisture and energy at the land surface, are often used to estimate water storage variability of snow, surface water, and soil moisture. To obtain an estimate of changes in groundwater, the estimates of these storage components are removed from GRACE data. Biases in the modeled water storage components are therefore present in the residual groundwater estimate. In this study, we examine how soil moisture variability, estimated using the Community Land Model (CLM), depends on the vertical structure of the model. We then explore the implications of this uncertainty in the context of estimating groundwater variations using GRACE data.

Generating a global soil evaporation dataset using SMAP soil moisture data to estimate components of the surface water balance

NASA Astrophysics Data System (ADS)

Carbone, E.; Small, E. E.; Badger, A.; Livneh, B.

2016-12-01

Evapotranspiration (ET) is fundamental to the water, energy and carbon cycles. However, our ability to measure ET and partition the total flux into transpiration and evaporation from soil is limited. This project aims to generate a global, observationally-based soil evaporation dataset (E-SMAP): using SMAP surface soil moisture data in conjunction with models and auxiliary observations to observe or estimate each component of the surface water balance. E-SMAP will enable a better understanding of water balance processes and contribute to forecasts of water resource availability. Here we focus on the flux between the soil surface and root zone layers (qbot), which dictates the proportion of water that is available for soil evaporation. Any water that moves from the surface layer to the root zone contributes to transpiration or groundwater recharge. The magnitude and direction of qbot are driven by gravity and the gradient in matric potential. We use a highly discretized Richards Equation-type model (e.g. Hydrus 1D software) with meteorological forcing from the North American Land Data Assimilation System (NLDAS) to estimate qbot. We verify the simulations using SMAP L4 surface and root zone soil moisture data. These data are well suited for evaluating qbot because they represent the most advanced estimate of the surface to root zone soil moisture gradient at the global scale. Results are compared with similar calculations using NLDAS and in situ soil moisture data. Preliminary calculations show that the greatest amount of variability between qbot determined from NLDAS, in situ and SMAP occurs directly after precipitation events. At these times, uncertainties in qbot calculations significantly affect E-SMAP estimates.

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Soil Moisture Estimate Under Forest Using a Semi-Empirical Model at P-Band

NASA Technical Reports Server (NTRS)

Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak

2013-01-01

Here we present the result of a semi-empirical inversion model for soil moisture retrieval using the three backscattering coefficients: sigma(sub HH), sigma(sub VV) and sigma(sub HV). In this paper we focus on the soil moisture estimate and use the biomass as an ancillary parameter estimated automatically from the algorithm and used as a validation parameter, We will first remind the model analytical formulation. Then we will sow some results obtained with real SAR data and compare them to ground estimates.

Estimation of soil loss by water erosion in the Chinese Loess Plateau using Universal Soil Loss Equation and GRACE

NASA Astrophysics Data System (ADS)

Schnitzer, S.; Seitz, F.; Eicker, A.; Güntner, A.; Wattenbach, M.; Menzel, A.

2013-06-01

For the estimation of soil loss by erosion in the strongly affected Chinese Loess Plateau we applied the Universal Soil Loss Equation (USLE) using a number of input data sets (monthly precipitation, soil types, digital elevation model, land cover and soil conservation measures). Calculations were performed in ArcGIS and SAGA. The large-scale soil erosion in the Loess Plateau results in a strong non-hydrological mass change. In order to investigate whether the resulting mass change from USLE may be validated by the gravity field satellite mission GRACE (Gravity Recovery and Climate Experiment), we processed different GRACE level-2 products (ITG, GFZ and CSR). The mass variations estimated in the GRACE trend were relatively close to the observed sediment yield data of the Yellow River. However, the soil losses resulting from two USLE parameterizations were comparatively high since USLE does not consider the sediment delivery ratio. Most eroded soil stays in the study area and only a fraction is exported by the Yellow River. Thus, the resultant mass loss appears to be too small to be resolved by GRACE.

Quantifying Contaminant Mass for the Feasibility Study of the DuPont Chambers Works FUSRAP Site - 13510

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

Young, Carl; Rahman, Mahmudur; Johnson, Ann

2013-07-01

The U.S. Army Corps of Engineers (USACE) - Philadelphia District is conducting an environmental restoration at the DuPont Chambers Works in Deepwater, New Jersey under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Discrete locations are contaminated with natural uranium, thorium-230 and radium-226. The USACE is proposing a preferred remedial alternative consisting of excavation and offsite disposal to address soil contamination followed by monitored natural attenuation to address residual groundwater contamination. Methods were developed to quantify the error associated with contaminant volume estimates and use mass balance calculations of the uranium plume to estimate the removal efficiency of the proposedmore » alternative. During the remedial investigation, the USACE collected approximately 500 soil samples at various depths. As the first step of contaminant mass estimation, soil analytical data was segmented into several depth intervals. Second, using contouring software, analytical data for each depth interval was contoured to determine lateral extent of contamination. Six different contouring algorithms were used to generate alternative interpretations of the lateral extent of the soil contamination. Finally, geographical information system software was used to produce a three dimensional model in order to present both lateral and vertical extent of the soil contamination and to estimate the volume of impacted soil for each depth interval. The average soil volume from all six contouring methods was used to determine the estimated volume of impacted soil. This method also allowed an estimate of a standard deviation of the waste volume estimate. It was determined that the margin of error for the method was plus or minus 17% of the waste volume, which is within the acceptable construction contingency for cost estimation. USACE collected approximately 190 groundwater samples from 40 monitor wells. It is expected that excavation and disposal of contaminated soil will remove the contaminant source zone and significantly reduce contaminant concentrations in groundwater. To test this assumption, a mass balance evaluation was performed to estimate the amount of dissolved uranium that would remain in the groundwater after completion of soil excavation. As part of this evaluation, average groundwater concentrations for the pre-excavation and post-excavation aquifer plume area were calculated to determine the percentage of plume removed during excavation activities. In addition, the volume of the plume removed during excavation dewatering was estimated. The results of the evaluation show that approximately 98% of the aqueous uranium would be removed during the excavation phase. The USACE expects that residual levels of contamination will remain in groundwater after excavation of soil but at levels well suited for the selection of excavation combined with monitored natural attenuation as a preferred alternative. (authors)« less

An improved Rosetta pedotransfer function and evaluation in earth system models

NASA Astrophysics Data System (ADS)

Zhang, Y.; Schaap, M. G.

2017-12-01

Soil hydraulic parameters are often difficult and expensive to measure, leading to the pedotransfer functions (PTFs) an alternative to predict those parameters. Rosetta (Schaap et al., 2001, denoted as Rosetta1) are widely used PTFs, which is based on artificial neural network (ANN) analysis coupled with the bootstrap re-sampling method, allowing the estimation of van Genuchten water retention parameters (van Genuchten, 1980, abbreviated here as VG), saturated hydraulic conductivity (Ks), as well as their uncertainties. We present an improved hierarchical pedotransfer functions (Rosetta3) that unify the VG water retention and Ks submodels into one, thus allowing the estimation of uni-variate and bi-variate probability distributions of estimated parameters. Results show that the estimation bias of moisture content was reduced significantly. Rosetta1 and Posetta3 were implemented in the python programming language, and the source code are available online. Based on different soil water retention equations, there are diverse PTFs used in different disciplines of earth system modelings. PTFs based on Campbell [1974] or Clapp and Hornberger [1978] are frequently used in land surface models and general circulation models, while van Genuchten [1980] based PTFs are more widely used in hydrology and soil sciences. We use an independent global scale soil database to evaluate the performance of diverse PTFs used in different disciplines of earth system modelings. PTFs are evaluated based on different soil characteristics and environmental characteristics, such as soil textural data, soil organic carbon, soil pH, as well as precipitation and soil temperature. This analysis provides more quantitative estimation error information for PTF predictions in different disciplines of earth system modelings.

An estimation of the main wetting branch of the soil water retention curve based on its main drying branch using the machine learning method

NASA Astrophysics Data System (ADS)

Lamorski, Krzysztof; Šimūnek, Jiří; Sławiński, Cezary; Lamorska, Joanna

2017-02-01

In this paper, we estimated using the machine learning methodology the main wetting branch of the soil water retention curve based on the knowledge of the main drying branch and other, optional, basic soil characteristics (particle size distribution, bulk density, organic matter content, or soil specific surface). The support vector machine algorithm was used for the models' development. The data needed by this algorithm for model training and validation consisted of 104 different undisturbed soil core samples collected from the topsoil layer (A horizon) of different soil profiles in Poland. The main wetting and drying branches of SWRC, as well as other basic soil physical characteristics, were determined for all soil samples. Models relying on different sets of input parameters were developed and validated. The analysis showed that taking into account other input parameters (i.e., particle size distribution, bulk density, organic matter content, or soil specific surface) than information about the drying branch of the SWRC has essentially no impact on the models' estimations. Developed models are validated and compared with well-known models that can be used for the same purpose, such as the Mualem (1977) (M77) and Kool and Parker (1987) (KP87) models. The developed models estimate the main wetting SWRC branch with estimation errors (RMSE = 0.018 m3/m3) that are significantly lower than those for the M77 (RMSE = 0.025 m3/m3) or KP87 (RMSE = 0. 047 m3/m3) models.

Operational Mapping of Soil Moisture Using Synthetic Aperture Radar Data: Application to the Touch Basin (France)

PubMed Central

Baghdadi, Nicolas; Aubert, Maelle; Cerdan, Olivier; Franchistéguy, Laurent; Viel, Christian; Martin, Eric; Zribi, Mehrez; Desprats, Jean François

2007-01-01

Soil moisture is a key parameter in different environmental applications, such as hydrology and natural risk assessment. In this paper, surface soil moisture mapping was carried out over a basin in France using satellite synthetic aperture radar (SAR) images acquired in 2006 and 2007 by C-band (5.3 GHz) sensors. The comparison between soil moisture estimated from SAR data and in situ measurements shows good agreement, with a mapping accuracy better than 3%. This result shows that the monitoring of soil moisture from SAR images is possible in operational phase. Moreover, moistures simulated by the operational Météo-France ISBA soil-vegetation-atmosphere transfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moisture estimates to validate its pertinence. The difference between ISBA simulations and radar estimates fluctuates between 0.4 and 10% (RMSE). The comparison between ISBA and gravimetric measurements of the 12 March 2007 shows a RMSE of about 6%. Generally, these results are very encouraging. Results show also that the soil moisture estimated from SAR images is not correlated with the textural units defined in the European Soil Geographical Database (SGDBE) at 1:1000000 scale. However, dependence was observed between texture maps and ISBA moisture. This dependence is induced by the use of the texture map as an input parameter in the ISBA model. Even if this parameter is very important for soil moisture estimations, radar results shown that the textural map scale at 1:1000000 is not appropriate to differentiate moistures zones. PMID:28903238

Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.

2014-12-01

NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each ­in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.

A Complex Inoculant of N2-Fixing, P- and K-Solubilizing Bacteria from a Purple Soil Improves the Growth of Kiwifruit (Actinidia chinensis) Plantlets

PubMed Central

Shen, Hong; He, Xinhua; Liu, Yiqing; Chen, Yi; Tang, Jianming; Guo, Tao

2016-01-01

Limited information is available if plant growth promoting bacteria (PGPB) can promote the growth of fruit crops through improvements in soil fertility. This study aimed to evaluate the capacity of PGPB, identified by phenotypic and 16S rRNA sequencing from a vegetable purple soil in Chongqing, China, to increase soil nitrogen (N), phosphorus (P), and potassium (K) availability and growth of kiwifruit (Actinidia chinensis). In doing so, three out of 17 bacterial isolates with a high capacity of N2-fixation (Bacillus amyloliquefaciens, XD-N-3), P-solubilization (B. pumilus, XD-P-1) or K-solubilization (B. circulans, XD-K-2) were mixed as a complex bacterial inoculant. A pot experiment then examined its effects of this complex inoculant on soil microflora, soil N2-fixation, P- and K-solubility and kiwifruit growth under four treatments. These treatments were (1) no-fertilizer and no-bacterial inoculant (Control), (2) no-bacterial inoculant and a full-rate of chemical NPK fertilizer (CF), (3) the complex inoculant (CI), and (4) a half-rate CF and full CI (1/2CF+CI). Results indicated that significantly greater growth of N2-fixing, P- and K-solubilizing bacteria among treatments ranked from greatest to least as under 1/2CF+CI ≈ CI > CF ≈ Control. Though generally without significant treatment differences in soil total N, P, or K, significantly greater soil available N, P, or K among treatments was, respectively, patterned as under 1/2CF+CI ≈ CI > CF ≈ Control, under 1/2CF+CI > CF > CI > Control or under 1/2CF+CI > CF ≈ CI > Control, indicating an improvement of soil fertility by this complex inoculant. In regards to plant growth, significantly greater total plant biomass and total N, P, and K accumulation among treatments were ranked as 1/2CF+CI ≈ CI > CF > Control. Additionally, significantly greater leaf polyphenol oxidase activity ranked as under CF > 1/2CF+CI ≈ Control ≈ CI, while leaf malondialdehyde contents as under Control > CI ≈ CF > 1/2CF+CI. In short, the applied complex inoculant is able to improve available soil N, P, and K and kiwifruit growth. These results demonstrate the potential of using a complex bacterial inoculant for promoting soil fertility and plant growth. PMID:27445991

A Complex Inoculant of N2-Fixing, P- and K-Solubilizing Bacteria from a Purple Soil Improves the Growth of Kiwifruit (Actinidia chinensis) Plantlets.

PubMed

Shen, Hong; He, Xinhua; Liu, Yiqing; Chen, Yi; Tang, Jianming; Guo, Tao

2016-01-01

Limited information is available if plant growth promoting bacteria (PGPB) can promote the growth of fruit crops through improvements in soil fertility. This study aimed to evaluate the capacity of PGPB, identified by phenotypic and 16S rRNA sequencing from a vegetable purple soil in Chongqing, China, to increase soil nitrogen (N), phosphorus (P), and potassium (K) availability and growth of kiwifruit (Actinidia chinensis). In doing so, three out of 17 bacterial isolates with a high capacity of N2-fixation (Bacillus amyloliquefaciens, XD-N-3), P-solubilization (B. pumilus, XD-P-1) or K-solubilization (B. circulans, XD-K-2) were mixed as a complex bacterial inoculant. A pot experiment then examined its effects of this complex inoculant on soil microflora, soil N2-fixation, P- and K-solubility and kiwifruit growth under four treatments. These treatments were (1) no-fertilizer and no-bacterial inoculant (Control), (2) no-bacterial inoculant and a full-rate of chemical NPK fertilizer (CF), (3) the complex inoculant (CI), and (4) a half-rate CF and full CI (1/2CF+CI). Results indicated that significantly greater growth of N2-fixing, P- and K-solubilizing bacteria among treatments ranked from greatest to least as under 1/2CF+CI ≈ CI > CF ≈ Control. Though generally without significant treatment differences in soil total N, P, or K, significantly greater soil available N, P, or K among treatments was, respectively, patterned as under 1/2CF+CI ≈ CI > CF ≈ Control, under 1/2CF+CI > CF > CI > Control or under 1/2CF+CI > CF ≈ CI > Control, indicating an improvement of soil fertility by this complex inoculant. In regards to plant growth, significantly greater total plant biomass and total N, P, and K accumulation among treatments were ranked as 1/2CF+CI ≈ CI > CF > Control. Additionally, significantly greater leaf polyphenol oxidase activity ranked as under CF > 1/2CF+CI ≈ Control ≈ CI, while leaf malondialdehyde contents as under Control > CI ≈ CF > 1/2CF+CI. In short, the applied complex inoculant is able to improve available soil N, P, and K and kiwifruit growth. These results demonstrate the potential of using a complex bacterial inoculant for promoting soil fertility and plant growth.

Estimating Infiltration Rates for a Loessal Silt Loam Using Soil Properties

Treesearch

M. Dean Knighton

1978-01-01

Soil properties were related to infiltration rates as measured by single-ringsteady-head infiltometers. The properties showing strong simple correlations were identified. Regression models were developed to estimate infiltration rate from several soil properties. The best model gave fair agreement to measured rates at another location.

AN IN VITRO GASTROINTESTINAL METHOD TO ESTIMATE BIOAVAILABLE ARSENIC IN CONTAMINATED SOILS AND SOLID MEDIA. (R825410)

EPA Science Inventory

A method was developed to simulate the human gastrointestinal environment and
to estimate bioavailability of arsenic in contaminated soil and solid media. In
this in vitro gastrointestinal (IVG) method, arsenic is sequentially extracted
from contaminated soil with ...

ESTIMATING ROOT RESPIRATION IN SPRUCE AND BEECH: DECREASES IN SOIL RESPIRATION FOLLOWING GIRDLING

EPA Science Inventory

A study was undertaken to follow seasonal fluxes of CO2 from soil and to estimate the contribution of autotrophic (root + mycorrhizal) to total soil respiration (SR) in a mixed stand of European beech (Fagus sylvatica) and Norway spruce (Picea abies) near Freising, Germany. Matu...

Comparison of corn transpiration, eddy covariance, and soil water loss

USDA-ARS?s Scientific Manuscript database

Stem flow gages are used to estimate plant transpiration, but only a few studies compare transpiration with other measures of soil water loss. The purpose of this study was to compare transpiration from stem flow measurements with soil water changes estimated by daily neutron probe readings. Monitor...

Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Pellarin, Thierry; Kerr, Yann; Crow, Wade; Cascon, Carlos; Ciabatta, Luca

2016-04-01

Recent advancements in the measurement of precipitation from space have provided estimates at scales that are commensurate with the needs of the hydrological and land-surface model communities. However, as demonstrated in a number of studies (Ebert et al. 2007, Tian et al. 2007, Stampoulis et al. 2012) satellite rainfall estimates are characterized by low accuracy in certain conditions and still suffer from a number of issues (e.g., bias) that may limit their utility in over-land applications (Serrat-Capdevila et al. 2014). In recent years many studies have demonstrated that soil moisture observations from ground and satellite sensors can be used for correcting satellite precipitation estimates (e.g. Crow et al., 2011; Pellarin et al., 2013), or directly estimating rainfall (SM2RAIN, Brocca et al., 2014). In this study, we carried out a detailed scientific analysis in which these three different methods are used for: i) estimating rainfall through satellite soil moisture observations (SM2RAIN, Brocca et al., 2014); ii) correcting rainfall through a Land surface Model Assimilation Algorithm (LMAA) (an improvement of a previous work of Crow et al. 2011 and Pellarin et al. 2013) and through the Soil Moisture Analysis Rainfall Tool (SMART, Crow et al. 2011). The analysis is carried within the ESA project "SMOS plus Rainfall" and involves 9 sites in Europe, Australia, Africa and USA containing high-quality hydrometeorological and soil moisture observations. Satellite soil moisture data from Soil Moisture and Ocean Salinity (SMOS) mission are employed for testing their potential in deriving a cumulated rainfall product at different temporal resolutions. The applicability and accuracy of the three algorithms is investigated also as a function of climatic and soil/land use conditions. A particular attention is paid to assess the expected limitations soil moisture based rainfall estimates such as soil saturation, freezing/snow conditions, SMOS RFI, irrigated areas, contribution of surface runoff and evapotranspiration, vegetation coverage, temporal sampling, and the assimilation/modelling approach. The 9 selected sites gather such potential problems which are shown and discussed at the conference. REFERENCES Ebert, E. E.; Janowiak, J. E.; Kidd, C. Comparison of Near-Real-Time Precipitation Estimates from Satellite Observations and Numerical Models. Bull. Am. Meteorol. Soc. 2007, 88, 47-64. Tian, Y.; Peters-Lidard, C. D.; Choudhury, B. J.; Garcia, M. Multitemporal Analysis of TRMM-Based Satellite Precipitation Products for Land Data Assimilation Applications. J. Hydrometeorol. 2007, 8, 1165-1183. Stampoulis, D.; Anagnostou, E. N. Evaluation of Global Satellite Rainfall Products over Continental Europe. J. Hydrometeorol. 2012, 13, 588-603. Serrat-Capdevila, A.; Valdes, J. B.; Stakhiv, E. Z. Water Management Applications for Satellite Precipitation Products: Synthesis and Recommendations. JAWRA J. Am. Water Resour. Assoc. 2014, 50, 509-525. Crow, W. T.; van den Berg, M. J.; Huffman, G. J.; Pellarin, T. Correcting rainfall using satellite-based surface soil moisture retrievals: The Soil Moisture Analysis Rainfall Tool (SMART). Water Resour. Res. 2011, 47, W08521. Pellarin, T.; Louvet, S.; Gruhier, C.; Quantin, G.; Legout, C. A simple and effective method for correcting soil moisture and precipitation estimates using AMSR-E measurements. Remote Sens. Environ. 2013, 136, 28-36. Brocca, L.; Ciabatta, L.; Massari, C.; Moramarco, T.; Hahn, S.; Hasenauer, S.; Kidd, R.; Dorigo, W.; Wagner, W.; Levizzani, V. Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data. J. Geophys. Res. Atmos. 2014, 119, 5128-5141.

Assessment of different methods to estimate heavy metal bioavailability in 30 contrasting Spanish and New Zealand soils

NASA Astrophysics Data System (ADS)

Soriano-Disla, J. M.; Speir, T. W.; Gómez, I.; Clucas, L. M.; McLaren, R. G.; Navarro-Pedreño, J.

2009-04-01

The accumulation of heavy metals in soil from different sources (atmospheric deposition, agricultural practices, urban-industrial activities, etc.) is of a great environmental concern because of metal persistence and toxicity. In this sense, there is a consensus in the literature that the estimation of the bioavailable heavy metals in soil is a preferable tool to determine potential risks from soil contamination than the total contents. However, controversy exists around the definition of an accurate and universal bioavailability estimator that is useful for soils with different properties, since many factors control this parameter. Thus, the main objective of this work was to compare the effectiveness of different methods to predict heavy metals plant uptake from soils with different properties and heavy metal contents. For the development of the present work, 30 contrasting soils from New Zealand and Spain were selected. Apart from the analysis of the basic soil properties, different methods to estimate heavy metal bioavailability were performed: total heavy metals, DTPA-extractable soil metals, diffusive gradient technique (DGT), and total heavy metals in soil solution. In these soils, a bioassay using wheat (Triticum aestivum) was carried out in a constant environment room for 25 days (12 hours photoperiod, day and night temperature of 20°C and 15°C respectively). After this time, the plants were divided in roots and shoots and heavy metal content was analysed in each part. Simple correlations were performed comparing the phytoavailable contents with the bioavailability estimated by the different methods. As expected, higher heavy metal concentrations were found in roots compared with shoots. Comparing the theoretical available heavy metals estimated by the different methods with the root and shoot uptake, better correlations were found with the root contents, thus, the discussion is based in the comparisons with the uptake by this part of the plant. According to the results, DTPA seemed to be the extractant that best estimated plant uptake (except for Cd, not estimated by any of the methods used). Similar good results were found using the total heavy metal contents, except for Ni and Zn. DGT also worked well, but its use for Pb is not advisable, since many values were below the detection level. The heavy metals in soil solution were less successful for predicting plant uptake. In general, the good results obtained for Cr and Zn seemed to be influenced by a few high values found in some soils. Taking this point into account, the soils with very high levels of these heavy metals were removed from the analysis and simple correlations were done again with the remaining soils having a lower range of these metals. For the case of Cr, four soils were removed (soils with ten times or more total Cr than the average of the others 26 samples) and three for the case of Zn (soils with two times or more total Zn than the average of the others 27 samples). After this, the correlations with total heavy metals and DTPA became very weak, being the heavy metals in soil solution for Cr, and DGT for Zn, the methods that best estimated the plant uptake of these metals. This work has proved the importance of careful revision of the data distribution, since good results can be influenced by just few samples with high values. In this sense and as a conclusion, DTPA and total heavy metals followed similar patterns and were good predictors of Cu and Pb uptake, and useful to distinguish between low and high values for Cr and Zn. On the other hand, DGT and heavy metals in soil solution showed a similar effectiveness to estimate Cu, Ni, Pb, Zn and Cr, but DGT presented, in general, higher correlation levels (except for Cr). Taking all of the results together, it seems that the most robust and efficient estimator for all metals studied (except Cd, impossible to predict with any of the methods used) was the DGT. Acknowledgements: Jose. M. Soriano-Disla gratefully acknowledges the Spanish Ministry of Innovation and Culture for a research fellowship (AP2005-0320).

An evaluation of soil chemistry in human cadaver decomposition islands: Potential for estimating postmortem interval (PMI).

PubMed

Fancher, J P; Aitkenhead-Peterson, J A; Farris, T; Mix, K; Schwab, A P; Wescott, D J; Hamilton, M D

2017-10-01

Soil samples from the Forensic Anthropology Research Facility (FARF) at Texas State University, San Marcos, TX, were analyzed for multiple soil characteristics from cadaver decomposition islands to a depth of 5centimeters (cm) from 63 human decomposition sites, as well as depths up to 15cm in a subset of 11 of the cadaver decomposition islands plus control soils. Postmortem interval (PMI) of the cadaver decomposition islands ranged from 6 to 1752 days. Some soil chemistry, including nitrate-N (NO 3 -N), ammonium-N (NH 4 -N), and dissolved inorganic carbon (DIC), peaked at early PMI values and their concentrations at 0-5cm returned to near control values over time likely due to translocation down the soil profile. Other soil chemistry, including dissolved organic carbon (DOC), dissolved organic nitrogen (DON), orthophosphate-P (PO 4 -P), sodium (Na + ), and potassium (K + ), remained higher than the control soil up to a PMI of 1752days postmortem. The body mass index (BMI) of the cadaver appeared to have some effect on the cadaver decomposition island chemistry. To estimate PMI using soil chemistry, backward, stepwise multiple regression analysis was used with PMI as the dependent variable and soil chemistry, body mass index (BMI) and physical soil characteristics such as saturated hydraulic conductivity as independent variables. Measures of soil parameters derived from predator and microbial mediated decomposition of human remains shows promise in estimating PMI to within 365days for a period up to nearly five years. This persistent change in soil chemistry extends the ability to estimate PMI beyond the traditionally utilized methods of entomology and taphonomy in support of medical-legal investigations, humanitarian recovery efforts, and criminal and civil cases. Copyright © 2017 Elsevier B.V. All rights reserved.

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle; Reichle, Rolf; Gruber, Alexander; Bechtold, Michel; Quets, Jan; Vrugt, Jasper; Wigneron, Jean-Pierre

2018-01-01

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.

Evaluating soil moisture and yield of winter wheat in the Great Plains using Landsat data

NASA Technical Reports Server (NTRS)

Heilman, J. L.; Kanemasu, E. T.; Bagley, J. O.; Rasmussen, V. P.

1977-01-01

Locating areas where soil moisture is limiting to crop growth is important for estimating winter-wheat yields on a regional basis. In the 1975-76 growing season, we evaluated soil-moisture conditions and winter-wheat yields for a five-state region of the Great Plains using Landsat estimates of leaf area index (LAI) and an evapotranspiration (ET) model described by Kanemasu et al (1977). Because LAI was used as an input, the ET model responded to changes in crop growth. Estimated soil-water depletions were high for the Nebraska Panhandle, southwestern Kansas, southeastern Colorado, and the Texas Panhandle. Estimated yields in five-state region ranged from 1.0 to 2.9 metric ton/ha.

A new approach to study cadmium complexes with oxalic acid in soil solution.

PubMed

Dytrtová, Jana Jaklová; Jakl, Michal; Sestáková, Ivana; Zins, Emilie-Laure; Schröder, Detlef; Navrátil, Tomáš

2011-05-05

This study presents a new analytical approach for the determination of heavy metals complexed to low-molecular-weight-organic acids in soil solutions, which combines the sensitivity of differential pulse anodic stripping voltammetry (DPASV) with the molecular insight gained by electrospray ionization mass spectrometry (ESI-MS). The combination of these analytical methods allows the investigation of such complexes in complex matrixes. On the voltammograms of the soil solutions, in addition to the expected complexes of oxalic acid with cadmium and lead, respectively, also peaks belonging to mixed complexes of cadmium, lead, and oxalic acid (OAH(2)) were observed. In order to verify the possible formation of complexes with OAH(2), aqueous solutions of OAH(2) with traces of Cd(II) were investigated as model systems. Signals corresponding to several distinct molecular complexes between cadmium and oxalic acid were detected in the model solutions using negative-ion ESI-MS, which follow the general formula [Cd(n)(X,Y)((2n+1))](-), where n is the number of cadmium atoms, X=Cl(-), and Y=OAH(-). Some of these complexes were also identified in the ESI mass spectra taken from the soil solutions. Copyright © 2011 Elsevier B.V. All rights reserved.

Living roots magnify the response of soil organic carbon decomposition to temperature in temperate grassland

PubMed Central

Hill, Paul W; Garnett, Mark H; Farrar, John; Iqbal, Zafar; Khalid, Muhammad; Soleman, Nawaf; Jones, Davey L

2015-01-01

Increasing atmospheric carbon dioxide (CO2) concentration is both a strong driver of primary productivity and widely believed to be the principal cause of recent increases in global temperature. Soils are the largest store of the world's terrestrial C. Consequently, many investigations have attempted to mechanistically understand how microbial mineralisation of soil organic carbon (SOC) to CO2 will be affected by projected increases in temperature. Most have attempted this in the absence of plants as the flux of CO2 from root and rhizomicrobial respiration in intact plant-soil systems confounds interpretation of measurements. We compared the effect of a small increase in temperature on respiration from soils without recent plant C with the effect on intact grass swards. We found that for 48 weeks, before acclimation occurred, an experimental 3 °C increase in sward temperature gave rise to a 50% increase in below ground respiration (ca. 0.4 kg C m−2; Q10 = 3.5), whereas mineralisation of older SOC without plants increased with a Q10 of only 1.7 when subject to increases in ambient soil temperature. Subsequent 14C dating of respired CO2 indicated that the presence of plants in swards more than doubled the effect of warming on the rate of mineralisation of SOC with an estimated mean C age of ca. 8 years or older relative to incubated soils without recent plant inputs. These results not only illustrate the formidable complexity of mechanisms controlling C fluxes in soils but also suggest that the dual biological and physical effects of CO2 on primary productivity and global temperature have the potential to synergistically increase the mineralisation of existing soil C. PMID:25351704

Effects of complex carbon addition to soil CO2 efflux and isotopic composition to soils near dead and live piñon pine trees

NASA Astrophysics Data System (ADS)

Powers, H.; McDowell, N.; Breecker, D. O.

2010-12-01

We test the hypothesis that soils collected near dead and living pinus edulous (piñon pine) trees should show a difference in their capacities to decompose complex carbon compounds. Since soils near dead trees have a large amount of cellulose and other complex carbon, the soil microbial community should be selected to metabolize cellulose. We collected soils from both live and dead piñon trees, added cellulose to half of the replicates, and placed them in microcosms for incubation. The microcosms were periodically sampled by a trace gas analyzer (TGA100, Campbell Scientific, USA) for CO2 concentration and δ13C and δ18O analysis. We found that CO2 evolution rates from live soils were significantly higher than rates from dead soils (1.1 and 0.6 ug CO2 g-1 soil s-1 respectively); soils with added cellulose displayed higher rates (1.1 and 0.8 and ug CO2 g-1 soil s-1). We did not see any significant differences in δ13C values between treatments, but there was a difference in δ18O between soils treated with cellulose and soils with no cellulose. Soils from both dead and live trees showed an increase in CO2 efflux when cellulose was added; however there was no distinguishable difference in efflux rate between live and dead soils in the cellulose added treatments.

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.

Late Pleistocene Environments of the Central Ukraine

NASA Astrophysics Data System (ADS)

Rousseau, Denis-Didier; Gerasimenko, Natalia; Matviischina, Zhanna; Kukla, George

2001-11-01

The Vyazivok loess sequence from the Dnieper Plain, Ukraine, documents regional environmental changes during the late Pleistocene and Holocene. Pedological and palynological analyses and low-field magnetic susceptibility document changes from dense temperate forest during the last interglacial maximum to open, harsh, loess-steppe during the latest Pleistocene. The Vyazivok section overlies hillwash derived from a lower Pleistocene terrace and consists of two stratified soil complexes (Kaydaky and Pryluky; marine isotope stage [MIS] 5 equivalent) separated by a layer of eolian dust (Tyasmyn silt). The lower soils in both complexes formed within forest. These soils are overlain by the Uday (MIS4) and Bug (MIS2) loess units, which are separated by boreal soils of the Vytachiv (MIS3) complex. The coldest conditions within the record occurred in the youngest loess. Holocene soils cap the Bug loess. The Vyazivok section shows remarkable similarities with other classical loess sequences in western Europe, the Czech Republic, and Austria. The Kaydaky, Pryluky, and Vytachiv deposits, correlate with the PKIII, PKII, and PKI soil complexes, respectively, of the Czech Republic. The Tyasmyn and Prylyky silt layers correspond to marker horizons from central Europe.

Soil carbon dynamics

NASA Astrophysics Data System (ADS)

Trumbore, Susan; Barbosa de Camargo, Plínio

The amount of organic carbon (C) stored in the upper meter of mineral soils in the Amazon Basin (˜40 Pg C) represents ˜3% of the estimated global store of soil carbon. Adding surface detrital C stocks and soil carbon deeper than 1 m can as much as quadruple this estimate. The potential for Amazon soil carbon to respond to changes in land use, climate, or atmospheric composition depends on the form and dynamics of soil carbon. Much (˜30% in the top ˜10 cm but >85% in soils to 1 m depth) of the carbon in mineral soils of the Oxisols and Ultisols that are the predominant soil types in the Amazon Basin is in forms that are strongly stabilized, with mean ages of centuries to thousands of years. Measurable changes in soil C stocks that accompany land use/land cover change occur in the upper meter of soil, although the presence of deep roots in forests systems drives an active C cycle at depths >1 m. Credible estimates of the potential for changes in Amazon soil C stocks with future land use and climate change are much smaller than predictions of aboveground biomass change. Soil organic matter influences fertility and other key soil properties, and thus is important independent of its role in the global C cycle. Most work on C dynamics is limited to upland soils, and more is needed to investigate C dynamics in poorly drained soils. Work is also needed to relate cycles of C with water, N, P, and other elements.

Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database (NDP-017) (2001 version of original 1985 data)

DOE Data Explorer

Olsen, Jerry S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Watts, Julia A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Allison, Linda J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2001-01-01

In 1980, this data base and the corresponding map were completed after more than 20 years of field investigations, consultations, and analyses of published literature. They characterize the use and vegetative cover of the Earth's land surface with a 0.5° × 0.5° grid. This world-ecosystem-complex data set and the accompanying map provide a current reference base for interpreting the role of vegetation in the global cycling of CO2 and other gases and a basis for improved estimates of vegetation and soil carbon, of natural exchanges of CO2, and of net historic shifts of carbon between the biosphere and the atmosphere.

Effects of Plutonium on Soil Microorganisms

PubMed Central

Wildung, Raymond E.; Garland, Thomas R.

1982-01-01

As a first phase in an investigation of the role of the soil microflora in Pu complex formation and solubilization in soil, the effects of Pu concentration, form, and specific activity on microbial types, colony-forming units, and CO2 evolution rate were determined in soils amended with C and N sources to optimize microbial activity. The effects of Pu differed with organism type and incubation time. After 30 days of incubation, aerobic sporeforming and anaerobic bacteria were significantly affected by soil Pu levels as low as 1 μg/g when Pu was added as the hydrolyzable 239Pu(NO3)4 (solubility, <0.1% in soil). Other classes of organisms, except the fungi, were significantly affected at soil Pu levels of 10 μg/g. Fungi were affected only at soil Pu levels of 180 μg/g. Soil CO2 evolution rate and total accumulated CO2 were affected by Pu only at the 180 μg/g level. Because of the possible role of resistant organisms in complex formation, the mechanisms of effects of Pu on the soil fungi were further evaluated. The effect of Pu on soil fungal colony-forming units was a function of Pu solubility in soil and Pu specific activity. When Pu was added in a soluble, complexed form [238Pu2(diethylenetriaminepentaacetate)3], effects occurred at Pu levels of 1 μg/g and persisted for at least 95 days. Toxicity was due primarily to radiation effects rather than to chemical effects, suggesting that, at least in the case of the fungi, formation of Pu complexes would result primarily from ligands associated with normal (in contrast to chemically-induced) biochemical pathways. PMID:16345947

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

2016-02-01

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

Soil Microbial Forensics.

PubMed

Santiago-Rodriguez, Tasha M; Cano, Raúl J

2016-08-01

Soil microbial forensics can be defined as the study of how microorganisms can be applied to forensic investigations. The field of soil microbial forensics is of increasing interest and applies techniques commonly used in diverse disciplines in order to identify microbes and determine their abundances, complexities, and interactions with soil and surrounding objects. Emerging new techniques are also providing insights into the complexity of microbes in soil. Soil may harbor unique microbes that may reflect specific physical and chemical characteristics indicating site specificity. While applications of some of these techniques in the field of soil microbial forensics are still in early stages, we are still gaining insight into how microorganisms may be more robustly used in forensic investigations.

Data compilation, synthesis, and calculations used for organic-carbon storage and inventory estimates for mineral soils of the Mississippi River Basin

USGS Publications Warehouse

Buell, Gary R.; Markewich, Helaine W.

2004-01-01

U.S. Geological Survey investigations of environmental controls on carbon cycling in soils and sediments of the Mississippi River Basin (MRB), an area of 3.3 x 106 square kilometers (km2), have produced an assessment tool for estimating the storage and inventory of soil organic carbon (SOC) by using soil-characterization data from Federal, State, academic, and literature sources. The methodology is based on the linkage of site-specific SOC data (pedon data) to the soil-association map units of the U.S. Department of Agriculture State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) digital soil databases in a geographic information system. The collective pedon database assembled from individual sources presently contains 7,321 pedon records representing 2,581 soil series. SOC storage, in kilograms per square meter (kg/m2), is calculated for each pedon at standard depth intervals from 0 to 10, 10 to 20, 20 to 50, and 50 to 100 centimeters. The site-specific storage estimates are then regionalized to produce national-scale (STATSGO) and county-scale (SSURGO) maps of SOC to a specified depth. Based on this methodology, the mean SOC storage for the top meter of mineral soil in the MRB is approximately 10 kg/m2, and the total inventory is approximately 32.3 Pg (1 petagram = 109 metric tons). This inventory is from 2.5 to 3 percent of the estimated global mineral SOC pool.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Boyles, Ryan

2016-12-01

Surface soil moisture is a critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purposes are sensors that are installed at depths of approximately 5 cm. There are however, sensor technologies and network designs that do not provide an estimate at this depth. If soil moisture estimates at deeper depths could be extrapolated to the near surface, in situ networks providing estimates at other depths would see their values enhanced. Soil moisture sensors from the U.S. Climate Reference Network (USCRN) were used to generate models of 5 cm soil moisture, with 10 cm soil moisture measurements and antecedent precipitation as inputs, via machine learning techniques. Validation was conducted with the available, in situ, 5 cm resources. It was shown that a 5 cm estimate, which was extrapolated from a 10 cm sensor and antecedent local precipitation, produced a root-mean-squared-error (RMSE) of 0.0215 m3/m3. Next, these machine-learning-generated 5 cm estimates were also compared to AMSR-E estimates at these locations. These results were then compared with the performance of the actual in situ readings against the AMSR-E data. The machine learning estimates at 5 cm produced an RMSE of approximately 0.03 m3/m3 when an optimized gain and offset were applied. This is necessary considering the performance of AMSR-E in locations characterized by high vegetation water contents, which are present across North Carolina. Lastly, the application of this extrapolation technique is applied to the ECONet in North Carolina, which provides a 10 cm depth measurement as its shallowest soil moisture estimate. A raw RMSE of 0.028 m3/m3 was achieved, and with a linear gain and offset applied at each ECONet site, an RMSE of 0.013 m3/m3 was possible.

Nutrient and Rainfall Additions Shift Phylogenetically Estimated Traits of Soil Microbial Communities.

PubMed

Gravuer, Kelly; Eskelinen, Anu

2017-01-01

Microbial traits related to ecological responses and functions could provide a common currency facilitating synthesis and prediction; however, such traits are difficult to measure directly for all taxa in environmental samples. Past efforts to estimate trait values based on phylogenetic relationships have not always distinguished between traits with high and low phylogenetic conservatism, limiting reliability, especially in poorly known environments, such as soil. Using updated reference trees and phylogenetic relationships, we estimated two phylogenetically conserved traits hypothesized to be ecologically important from DNA sequences of the 16S rRNA gene from soil bacterial and archaeal communities. We sampled these communities from an environmental change experiment in California grassland applying factorial addition of late-season precipitation and soil nutrients to multiple soil types for 3 years prior to sampling. Estimated traits were rRNA gene copy number, which contributes to how rapidly a microbe can respond to an increase in resources and may be related to its maximum growth rate, and genome size, which suggests the breadth of environmental and substrate conditions in which a microbe can thrive. Nutrient addition increased community-weighted mean estimated rRNA gene copy number and marginally increased estimated genome size, whereas precipitation addition decreased these community means for both estimated traits. The effects of both treatments on both traits were associated with soil properties, such as ammonium, available phosphorus, and pH. Estimated trait responses within several phyla were opposite to the community mean response, indicating that microbial responses, although largely consistent among soil types, were not uniform across the tree of life. Our results show that phylogenetic estimation of microbial traits can provide insight into how microbial ecological strategies interact with environmental changes. The method could easily be applied to any of the thousands of existing 16S rRNA sequence data sets and offers potential to improve our understanding of how microbial communities mediate ecosystem function responses to global changes.

Validating HYLARSMET: a Hydrologically Consistent Land Surface Model for Soil Moisture and Evapotranspiration Modelling over Southern Africa using Remote Sensing and Meteorological Data

NASA Astrophysics Data System (ADS)

Sinclair, Scott; Pegram, Geoff; Mengitsu, Michael; Everson, Colin

2015-04-01

Timeous knowledge of the spatial distribution of soil moisture and evapotranspiration over a large region in fine detail has great value for coping with two weather extremes: flash floods and droughts, since the state of the wetness of the land surface has a major impact on runoff response. Also, the ability to monitor the wetness of the soil and the actual evapotranspiration over large regions, without having to laboriously take expensive samples, is a bonus for agricultural managers who need to predict crop yields. We present samples of the daily national Soil Moisture and Evapotranspiration estimates on a grid of 7300 locations centred in 12 km squares, then move on to the results of a validation study for soil moisture and evapotranspiration estimated using the PyTOPKAPI hydrological model in Land Surface Modelling mode, a system called HYLARSMET. The HYLARSMET estimates are compared with detailed evapotranspiration and soil moisture measurements made at the Baynesfield experimental farm in the KwaZulu-Natal province of South Africa, run by the University of KZN. The HYLARSMET evapotranspiration estimates compared very well with the measured estimates for the two chosen crop types, in spite of the fact that the HYLARSMET estimates were not designed to explicitly account for the crop types at each site. The same seasonality effects were evident in all 3 estimates, and there was a stronger ET relationship between HYLARSMET and the Soybean site (Pearson r = 0.81) than for Maize, (r = 0.59). The soil moisture relationship was stronger between the two in situ measured estimates (r = 0.98 at 0.5 m depth) than it was between HYLARSMET and the field estimates (r about 0.52 in both cases). Overall there was a reasonably good relationship between HYLARSMET and the in situ measurements of ET and SM at each site, indicating the value of the modelling procedure.