We are in the process of migrating all NASA Earth science data sites into Earthdata from now until end of 2026. Not all NASA Earth science data and resources will appear here until then. Thank you for your patience as we make this transition.Read about the Web Unification Project
Error message
The submitted value 10 in the Items element is not allowed.
Description
This dataset - HYSOGs250m - represents a globally consistent, gridded dataset of hydrologic soil groups (HSGs) with a geographical resolution of 1/480 decimal degrees, corresponding to a projected resolution of approximately 250-m. These data were developed to support USDA-based curve-number runoff modeling at regional and continental scales. Classification of HSGs was derived from soil texture classes and depth to bedrock provided by the Food and Agriculture Organization soilGrids250m system.
Product Summary
Platforms
MODELS
Instruments
Computer
Spatial Extent
N: 83.9997S: -56.0008E: 180W: -180
Location
GLOBAL
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
2017-01-01 to 2017-11-28
Data Partner
THE OAK RIDGE NATIONAL LABORATORY (ORNL) DISTRIBUTED ACTIVE ARCHIVE CENTER (DAAC) (ORNL_DAAC)
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
Copy Citation
Citation Copied
Ross, C. W., Prihodko, L., Anchang, J. Y., Kumar, S. S., Ji, W., & Hanan, N. P. (2018). Global Hydrologic Soil Groups (HYSOGs250m) for Curve Number-Based Runoff Modeling (Version 1). ORNL Distributed Active Archive Center. https://doi.org/10.3334/ORNLDAAC/1566 Date Accessed: 2026-05-16
Ross, C.W., L. Prihodko, J.Y. Anchang, S.S. Kumar, W. Ji, and N.P. Hanan. “Global Hydrologic Soil Groups (HYSOGs250m) for Curve Number-Based Runoff Modeling.” ORNL Distributed Active Archive Center, January 1, 2018. doi:10.3334/ORNLDAAC/1566. Date Accessed: 2026-05-16
Ross, C. W., et al. Global Hydrologic Soil Groups (HYSOGs250m) for Curve Number-Based Runoff Modeling. 1, ORNL Distributed Active Archive Center, 1 Jan. 2018, doi:10.3334/ORNLDAAC/1566. Date Accessed: 2026-05-16
Hsu, ShengKai, Emmett, Bryan D, Haafke, Alexandria, CostaNeto, Germano, Schulz, Aimee J, Lepak, Nicholas, La, Thuy, AuBuchonElder, Taylor M, Hale, Charles O, Raglin, Sierra S, OjedaRivera, Jonathan O, Kent, Angela D, Kellogg, Elizabeth A, Romay, M. Cinta, Buckler, Edward S