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HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling
C Wade Ross1, Lara Prihodko2, Julius Anchang1
1New Mexico State University, Department of Plant and Environmental Sciences, Las Cruces, New Mexico 88003, USA.
Scientific Data
|May 16, 2018
Summary
A new global dataset of Hydrologic Soil Groups (HSGs) has been developed, offering high-resolution runoff potential data. This resource is crucial for improving rainfall runoff modeling and flood risk assessments worldwide.
Area of Science:
- Earth Science
- Hydrology
- Soil Science
Background:
- Hydrologic Soil Groups (HSGs) are essential for the USDA curve-number (CN) method of rainfall runoff estimation.
- Existing HSG data lacks the spatial resolution and global consistency required for large-scale modeling.
Purpose of the Study:
- To develop a globally consistent, high-resolution gridded dataset of HSGs.
- To provide a data product suitable for regional and global hydrological and biogeographical analyses.
Main Methods:
- Developed a globally consistent dataset defining HSGs using soil texture, bedrock depth, and groundwater data.
- The dataset, HYSOGs250m, provides runoff potential at a 250m spatial resolution.
Main Results:
- The global distribution of soil runoff potential is predominantly moderately high, followed by moderately low, high, and low.
- Low runoff potential (sandy) soils are concentrated in the Sahara and Arabian Deserts.
- High runoff potential soils are prevalent in tropical and subtropical regions.
Conclusions:
- The HYSOGs250m dataset offers a significant advancement for hydrological modeling and environmental research.
- Applications include improved CN-based runoff modeling, flood risk assessment, and vegetation distribution analysis.
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