A globally consistent, gridded dataset for curve-number-based runoff ...
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HYSOGs250m: A globally consistent, gridded dataset for curve-number-based runoff modeling with hydrologic soil groups C. Wade Ross1, Lara Prihodko2, Julius Anchang1, Wenjie Ji1, Sanath Kumar1, Niall P. Hanan1 1New Mexico State University, Department of Plant and Environmental Sciences 2New Mexico State University, Department of Animal and Range Sciences
Overview
Soil texture
Depth to groundwater table
Depth to bedrock
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. To fill this gap, we developed a globally consistent, gridded dataset defining HSGs according to the USDA-NRCS National Engineering Handbook specifications.
0.
7
80
(cm)
≤ 50 cm C l
The resulting data product—HYSOGs250m—represents runoff potential at 250 m spatial resolution (Ross et. al, 2018).
Materials and methods HYSOGs250m was developed by incorporating soil texture classes (Hengl et al., 2017), depth to bedrock (Hengl et al., 2017), and depth to groundwater table (Fan et al., 2013). Conceptual workflow.
Hydrologic soil groups A
a) b) c) d) e)
Soils were represented to 1 m depth using six soilGrids (textStack). HSGs were classified according to Table 1 at each gridcell and depth (hsgStack). The least transmissive layer was used to classify HSGs for the entire pedon (maxHSG). Shallow soils (“R”, depth to bedrock
