Scientific Data · 2018 · 270 citations · 15 references
Natural ResourcesEarth SciencesHydrologyCatchment HydrologyHydrologic ModelingSoil ScienceHillslope HydrologyHydrologic AnalysisRainfall-runoff AnalysisRainfall-runoff ModelingRainfall-runoff RelationshipsSurface RunoffBedrock DepthGlobal Soil GridsRunoff EstimationRunoff ModelingSoil Texture AnalysisSoil Texture DistributionSurface Runoff ModelingSurface Runoff Potential
Hydrologic soil groups (HSGs) are a fundamental component of the USDA curve-number (CN) method for estimation of rainfall runoff; yet these data are not readily available in a format or spatial-resolution suitable for regional- and global-scale modeling applications. We developed a globally consistent, gridded dataset defining HSGs from soil texture, bedrock depth, and groundwater. The resulting data product-HYSOGs250m-represents runoff potential at 250 m spatial resolution. Our analysis indicates that the global distribution of soil is dominated by moderately high runoff potential, followed by moderately low, high, and low runoff potential. Low runoff potential, sandy soils are found primarily in parts of the Sahara and Arabian Deserts. High runoff potential soils occur predominantly within tropical and sub-tropical regions. No clear pattern could be discerned for moderately low runoff potential soils, as they occur in arid and humid environments and at both high and low elevations. Potential applications of this data include CN-based runoff modeling, flood risk assessment, and as a covariate for biogeographical analysis of vegetation distributions.
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SoilGrids250m: Global gridded soil information based on machine learning
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