HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling

Scientific Data
C Wade RossNiall P Hanan

Abstract

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.

References

Feb 23, 2013·Science·Y FanG Miguez-Macho
Feb 17, 2017·PloS One·Tomislav HenglBas Kempen

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Citations

Jan 16, 2019·Scientific Data·F NardiS Grimaldi
May 23, 2020·Science·Joel Podgorski, Michael Berg
Aug 14, 2019·Scientific Data·Hadi H JaafarNaji El Beyrouthy
May 2, 2020·Frontiers in Environmental Science·Joseph SpruceVenkat Lakshmi
Nov 16, 2018·The Science of the Total Environment·Baijing CaoBrian F Walters
Nov 27, 2019·The Science of the Total Environment·C Wade RossXiong Xiong
Mar 20, 2021·The Science of the Total Environment·Sarfaraz AlamSanjay K Mohanty
Jun 28, 2021·The Science of the Total Environment·Abdelrazek ElnasharRobert Duerler
Dec 18, 2021·The Science of the Total Environment·Josias da Silva CruzJosé Francisco de Oliveira Júnior

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Software Mentioned

HYSOGs250m
textStack
raster
hsgStack
R environment

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