Topographic wetness index (TWI) is used as a proxy for soil moisture, but how well it performs ac... more Topographic wetness index (TWI) is used as a proxy for soil moisture, but how well it performs across varying timescales and methods of calculation is not well understood. To assess the effectiveness of TWI, we examined spatial correlations between in situ soil volumetric water content (VWC) and TWI values over 5 years in soils at 42 locations in an agroforestry catena in Fayetteville, Arkansas, USA. We calculated TWI 546 ways using different flow algorithms and digital elevation model (DEM) preparations. We found that most TWI algorithms performed poorly on DEMs that were not first filtered or resampled, but DEM filtration and resampling (collectively called generalization) greatly improved the TWI performance. Seasonal variation of soil moisture influenced TWI performance which was best when conditions were not saturated and not dry. Pearson correlation coefficients between TWI and grand mean VWC for the 5-year measurement period ranged from 0.18 to 0.64 on generalized DEMs and 0....
This dataset provides two sets of estimates of soil organic carbon (SOC) and uncertainties as kg ... more This dataset provides two sets of estimates of soil organic carbon (SOC) and uncertainties as kg SOC/m2 in the 0-30 cm topsoil layer at 250-m resolution across Mexico and the conterminous USA (CONUS). The first set of SOC estimates, 1991-2010, were derived using multi-source SOC field data and multiple environmental variables representative of the soil forming environment coupled with a machine learning approach (e.g., simulated annealing) and regression tree ensemble modeling for optimized SOC prediction. Predictions of SOC and uncertainty based on multiple bulk density pedotransfer functions are also included. A second set of SOC estimates and uncertainties, 2009-2011, were derived from two fully independent validation field datasets from across both countries. Note that the same environmental variables and modeling approach as used for the first estimates were applied to these independent datasets for the purpose of assessing the models' sensitivity to multiple SOC data sources. The SOC field data for the first set of estimates are provided and the other data sources are referenced.
Core Ideas Topographic variation influenced soil nutrient distribution in a silvopasture system. ... more Core Ideas Topographic variation influenced soil nutrient distribution in a silvopasture system. High‐resolution digital maps of soil nutrients were generated. Terrain attributes identified topographic functional units as management zones. Level of soil nutrients in topographic functional units were different. Topography plays a crucial role in spatial distribution of nutrients in soils; however, studies to quantify topographic influence on soil nutrient distribution from a silvopasture system are mostly lacking. To address this question, a 4.3‐ha silvopasture site in northwest Arkansas was selected and a total of 51 topsoil (0–15 cm thickness) samples were collected and analyzed for primary (total N [TN], P, K), secondary (Ca, Mg, S), and micronutrients (Fe, Zn, Cu, Mn, B, Na). Topographic information was acquired from 12 terrain attributes derived from a 1‐m digital elevation model. The prediction model was based on random forest. Results showed TN, S, and P were best predicted, w...
SummaryStatistical validation of spatial predictions of soil properties requires assessment of er... more SummaryStatistical validation of spatial predictions of soil properties requires assessment of errors against measured values. The objective of this study was to assess the size of errors in the measurement of soil pH from different sources in the United States of America national databases and implications of the size of errors for prediction, validation and management decision making under uncertain conditions. Error sources included measurement methods, laboratory conditions, pedotransfer functions, database manipulations, location accuracy, and spatial and polygon methods of interpolation. The databases consisted of measured soil pH values from the US National Cooperative Soil Survey Characterization Database (NCSS–SCDB) and estimated values from US Soil Survey Geographic (SSURGO) and State Soil Geographic (STATSGO2) databases. The degree of agreement between measurement methods ranged from poor to substantial, with Lin's concordance correlation coefficients (ρc) varying fro...
Soils have critical relevance to global issues, such as food and water security, climate regulati... more Soils have critical relevance to global issues, such as food and water security, climate regulation, sustainable energy, desertification and biodiversity protec-tion. As a consequence, soil is becoming one of the top priorities for the global environmental policy agenda. Conventional soil maps suffer from large limita-tions, i.e. most of them are static and often obsolete, are often generated at coarse scale, and can be uneasy to handle. Digital Soil Mapping has been developed as a solution to generate high-resolution maps of soil properties over large areas. Two projects, GlobalSoilMap and SoilGrids, presently aim at delivering the first generation of global, high-resolution soil property fine grids. In this paper, we briefly describe the GlobalSoilMap history, its present status and present achievements, and illustrate some of these with (mainly) French examples. At given moment there is still an enormous potential for forthcoming research and for delivering products more helpful ...
Abstract Predicting soil property distribution from a catena in the digital environment has been ... more Abstract Predicting soil property distribution from a catena in the digital environment has been explored by many researchers with only slightly better than modest results. In this study, the landform recognition algorithm “geomorphons” in the GRASS GIS environment was explored to determine if this landscape model could improve predictions of soil properties. For 74 borings on the Wabash glacial moraine in Wells County, Indiana, measurements were made for: A horizon thickness, depth to chroma 2 features, effervescence, dense glacial till, carbonate concretions, and autochthonous platy structure. A digital elevation model (DEM) generated from light detection and ranging (LiDAR) data was used for the study site. The geomorphons algorithm was used to generate 10 original landforms: “flat”, “footslope”, “summit”, “ridge”, “shoulder”, “spur”, “slope”, “hollow”, “valley”, and “depression” that were aggregated to new landforms coinciding with slope positions: “toeslope”, “footslope”, “backslope”, “shoulder”, “summit”, and “depression” recognized by soil surveyors. Linear Discriminant Analysis (LDA) and Multinomial Logistics Regression Analysis (MLR) were used to aggregate the measured soil properties into the landform groups. The aggregation of geomorphons groups improved the MRL predictions to 83% accuracy. Also, the aggregation of geomorphons to five landforms to predict soil property distribution on the landscape gave promising results for the low-relief and relatively flat area of northeast Indiana. To test if the true mean value of each soil property for each landform was reliable for generalizing population characteristics, relative standard error (RSE) was calculated as a proportion of standard error to population mean from a bootstrap estimation. The range of RSE values for all soil properties and landforms was between ~ 0.7% and ~ 19%. Since the estimates of the measured soil properties all have RSE values of less than 25%, they can be considered reliable.
Core Ideas Saturated hydraulic conductivity (Ksat) was measured with different methods. Ksat was ... more Core Ideas Saturated hydraulic conductivity (Ksat) was measured with different methods. Ksat was upscaled from point to catchment to watershed scales. Upscaled Ksat predicted streamflow at a large watershed without model calibration. A soil system approach was used to successfully upscale Ksat for streamflow predictions Successful hydrological model predictions depend on appropriate framing of scale and the spatial‐temporal accuracy of input parameters describing soil hydraulic properties. Saturated soil hydraulic conductivity (Ksat) is one of the most important properties influencing water movement through soil under saturated conditions. It is also one of the most expensive to measure and is highly variable. The objectives of this research were (i) to assess the ability of Amoozemeters, wells, piezometers, and flumes to accurately represent Ksat at a small catchment scale and (ii) to extrapolate Ksat to a larger watershed based on available soil data and soil landscape models for ...
The Chaoyang profile represents a rare multi-period, continuous and complete sequence of aeolian ... more The Chaoyang profile represents a rare multi-period, continuous and complete sequence of aeolian paleo-deposits with a stable sedimentary origin and multi-stage paleoclimatic cycles. Benchmark profiles including soil types at different pedogenic stages can be used for the recognition and classification of paleosols and paleoclimate reconstruction. The loess–paleosol sequence benchmark profile (LBP) is also helpful in comparing the results of paleoenvironment reconstruction from different ecological regions. In this study, a loess–paleosol profile derived from thick loess in Chaoyang city of Liaoning province, Northeast China, was investigated as a well-preserved LBP that included various paleosol types. To determine the nature and origin of the Chaoyang profile, the geographic, stratigraphic and morphological characteristics were described in the field. Bulk samples from 42 horizons were collected for chemical and physical analysis, and sub-sampling of 946 samples at 2 cm intervals ...
Topographic wetness index (TWI) is used as a proxy for soil moisture, but how well it performs ac... more Topographic wetness index (TWI) is used as a proxy for soil moisture, but how well it performs across varying timescales and methods of calculation is not well understood. To assess the effectiveness of TWI, we examined spatial correlations between in situ soil volumetric water content (VWC) and TWI values over 5 years in soils at 42 locations in an agroforestry catena in Fayetteville, Arkansas, USA. We calculated TWI 546 ways using different flow algorithms and digital elevation model (DEM) preparations. We found that most TWI algorithms performed poorly on DEMs that were not first filtered or resampled, but DEM filtration and resampling (collectively called generalization) greatly improved the TWI performance. Seasonal variation of soil moisture influenced TWI performance which was best when conditions were not saturated and not dry. Pearson correlation coefficients between TWI and grand mean VWC for the 5-year measurement period ranged from 0.18 to 0.64 on generalized DEMs and 0....
This dataset provides two sets of estimates of soil organic carbon (SOC) and uncertainties as kg ... more This dataset provides two sets of estimates of soil organic carbon (SOC) and uncertainties as kg SOC/m2 in the 0-30 cm topsoil layer at 250-m resolution across Mexico and the conterminous USA (CONUS). The first set of SOC estimates, 1991-2010, were derived using multi-source SOC field data and multiple environmental variables representative of the soil forming environment coupled with a machine learning approach (e.g., simulated annealing) and regression tree ensemble modeling for optimized SOC prediction. Predictions of SOC and uncertainty based on multiple bulk density pedotransfer functions are also included. A second set of SOC estimates and uncertainties, 2009-2011, were derived from two fully independent validation field datasets from across both countries. Note that the same environmental variables and modeling approach as used for the first estimates were applied to these independent datasets for the purpose of assessing the models' sensitivity to multiple SOC data sources. The SOC field data for the first set of estimates are provided and the other data sources are referenced.
Core Ideas Topographic variation influenced soil nutrient distribution in a silvopasture system. ... more Core Ideas Topographic variation influenced soil nutrient distribution in a silvopasture system. High‐resolution digital maps of soil nutrients were generated. Terrain attributes identified topographic functional units as management zones. Level of soil nutrients in topographic functional units were different. Topography plays a crucial role in spatial distribution of nutrients in soils; however, studies to quantify topographic influence on soil nutrient distribution from a silvopasture system are mostly lacking. To address this question, a 4.3‐ha silvopasture site in northwest Arkansas was selected and a total of 51 topsoil (0–15 cm thickness) samples were collected and analyzed for primary (total N [TN], P, K), secondary (Ca, Mg, S), and micronutrients (Fe, Zn, Cu, Mn, B, Na). Topographic information was acquired from 12 terrain attributes derived from a 1‐m digital elevation model. The prediction model was based on random forest. Results showed TN, S, and P were best predicted, w...
SummaryStatistical validation of spatial predictions of soil properties requires assessment of er... more SummaryStatistical validation of spatial predictions of soil properties requires assessment of errors against measured values. The objective of this study was to assess the size of errors in the measurement of soil pH from different sources in the United States of America national databases and implications of the size of errors for prediction, validation and management decision making under uncertain conditions. Error sources included measurement methods, laboratory conditions, pedotransfer functions, database manipulations, location accuracy, and spatial and polygon methods of interpolation. The databases consisted of measured soil pH values from the US National Cooperative Soil Survey Characterization Database (NCSS–SCDB) and estimated values from US Soil Survey Geographic (SSURGO) and State Soil Geographic (STATSGO2) databases. The degree of agreement between measurement methods ranged from poor to substantial, with Lin's concordance correlation coefficients (ρc) varying fro...
Soils have critical relevance to global issues, such as food and water security, climate regulati... more Soils have critical relevance to global issues, such as food and water security, climate regulation, sustainable energy, desertification and biodiversity protec-tion. As a consequence, soil is becoming one of the top priorities for the global environmental policy agenda. Conventional soil maps suffer from large limita-tions, i.e. most of them are static and often obsolete, are often generated at coarse scale, and can be uneasy to handle. Digital Soil Mapping has been developed as a solution to generate high-resolution maps of soil properties over large areas. Two projects, GlobalSoilMap and SoilGrids, presently aim at delivering the first generation of global, high-resolution soil property fine grids. In this paper, we briefly describe the GlobalSoilMap history, its present status and present achievements, and illustrate some of these with (mainly) French examples. At given moment there is still an enormous potential for forthcoming research and for delivering products more helpful ...
Abstract Predicting soil property distribution from a catena in the digital environment has been ... more Abstract Predicting soil property distribution from a catena in the digital environment has been explored by many researchers with only slightly better than modest results. In this study, the landform recognition algorithm “geomorphons” in the GRASS GIS environment was explored to determine if this landscape model could improve predictions of soil properties. For 74 borings on the Wabash glacial moraine in Wells County, Indiana, measurements were made for: A horizon thickness, depth to chroma 2 features, effervescence, dense glacial till, carbonate concretions, and autochthonous platy structure. A digital elevation model (DEM) generated from light detection and ranging (LiDAR) data was used for the study site. The geomorphons algorithm was used to generate 10 original landforms: “flat”, “footslope”, “summit”, “ridge”, “shoulder”, “spur”, “slope”, “hollow”, “valley”, and “depression” that were aggregated to new landforms coinciding with slope positions: “toeslope”, “footslope”, “backslope”, “shoulder”, “summit”, and “depression” recognized by soil surveyors. Linear Discriminant Analysis (LDA) and Multinomial Logistics Regression Analysis (MLR) were used to aggregate the measured soil properties into the landform groups. The aggregation of geomorphons groups improved the MRL predictions to 83% accuracy. Also, the aggregation of geomorphons to five landforms to predict soil property distribution on the landscape gave promising results for the low-relief and relatively flat area of northeast Indiana. To test if the true mean value of each soil property for each landform was reliable for generalizing population characteristics, relative standard error (RSE) was calculated as a proportion of standard error to population mean from a bootstrap estimation. The range of RSE values for all soil properties and landforms was between ~ 0.7% and ~ 19%. Since the estimates of the measured soil properties all have RSE values of less than 25%, they can be considered reliable.
Core Ideas Saturated hydraulic conductivity (Ksat) was measured with different methods. Ksat was ... more Core Ideas Saturated hydraulic conductivity (Ksat) was measured with different methods. Ksat was upscaled from point to catchment to watershed scales. Upscaled Ksat predicted streamflow at a large watershed without model calibration. A soil system approach was used to successfully upscale Ksat for streamflow predictions Successful hydrological model predictions depend on appropriate framing of scale and the spatial‐temporal accuracy of input parameters describing soil hydraulic properties. Saturated soil hydraulic conductivity (Ksat) is one of the most important properties influencing water movement through soil under saturated conditions. It is also one of the most expensive to measure and is highly variable. The objectives of this research were (i) to assess the ability of Amoozemeters, wells, piezometers, and flumes to accurately represent Ksat at a small catchment scale and (ii) to extrapolate Ksat to a larger watershed based on available soil data and soil landscape models for ...
The Chaoyang profile represents a rare multi-period, continuous and complete sequence of aeolian ... more The Chaoyang profile represents a rare multi-period, continuous and complete sequence of aeolian paleo-deposits with a stable sedimentary origin and multi-stage paleoclimatic cycles. Benchmark profiles including soil types at different pedogenic stages can be used for the recognition and classification of paleosols and paleoclimate reconstruction. The loess–paleosol sequence benchmark profile (LBP) is also helpful in comparing the results of paleoenvironment reconstruction from different ecological regions. In this study, a loess–paleosol profile derived from thick loess in Chaoyang city of Liaoning province, Northeast China, was investigated as a well-preserved LBP that included various paleosol types. To determine the nature and origin of the Chaoyang profile, the geographic, stratigraphic and morphological characteristics were described in the field. Bulk samples from 42 horizons were collected for chemical and physical analysis, and sub-sampling of 946 samples at 2 cm intervals ...
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