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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
Projects
Soil
Spatial Extent

N: 83.9997 S: -56.0008 E: 180 W: -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)
Concept ID
C2216864285-ORNL_CLOUD
Data State
COMPLETE
Number of Files/Granules
1
Processing Level
3
Published
Updated
Science Keywords
Runoff ,
Soil Texture

Citation

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

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: 2026-10-08

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Publications Citing This Dataset

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Title Authors Year Referenced Datasets
Assessing Precipitation Effectiveness in the Context of Drought
  • Ford, Trent W., Quiring, Steven M., Teleubay, Zhanassyl, Straus, Katie, Zhang, Zhengxing
Hybrid defences for flash-flood resilience: multi-scenario assessment of grey and nature-based solutions in Indonesia's watershed
  • Hidayah, Entin, Dhokhikah, Yeny, Sulistyowati, Hari, Soetjipto, Jojok Widodo, Widodo, Joko, Gunawan, Alexander Agung Santoso, Herawati, Henny, Azmeri, Azmeri, Juliastuti, Juliastuti
How do international boundary river dynamics affect riparian land? Insights from the China-Russia Ussuri River
  • Huang, Sijing, Lu, Shengquan, Wu, Bin, Zhang, Wenzhu
Flood-sensitive land take (FSL) analysis: A new way to read how urban
  • Azadgar, Anahita, Benedini, Andrea, Salata, Stefano, Lacoere, Peter, Badach, Joanna, Nyka, Lucyna
Flood Hazard Assessment Under Subsidence-Influenced Terrain Using Deformation-Adjusted DEM in an Oil and Gas Field
  • Al Sulaimani, Mohammed, Abdalla, Rifaat, El-Diasty, Mohammed, Al Abri, Amani, El-Ghali, Mohamed A. K., Tabook, Ahmed
GCN10: An MPI-parallelized framework for processing global curve number
  • Azzam, Muhammad Abdullah, Cho, Huidae
GEMS-GER: a machine learning benchmark dataset of long-term groundwater levels in Germany with meteorological forcings and site-specific environmental ...
  • Ohmer, Marc, Liesch, Tanja, Habbel, Bastian, Heudorfer, Benedikt, Gomez, Mariana, Clos, Patrick, Nolscher, Maximilian, Broda, Stefan
The potential of green infrastructure in urban pluvial flood mitigationa scenario-based modelling study in Berlin
  • Dobkowitz, Sophia, De Vos, Leon Frederik, Jarajapu, Deva Charan, Lindenlaub, Sarah, Samprogna Mohor, Guilherme, Seleem, Omar, Bronstert, Axel
Role of nutrient and runoff retention in reducing nutrient export and runoff: a comprehensive framework for sustainable basin-scale water management
  • Shifaw, Eshetu, Vilas, Cesar, Corzo, Alfonso, Papaspyrou, Sokratis
A bayesian framework for dynamic monthly curve number conditioning using
  • Parisay, Zahra, Mirdashtvan, Mahsa, Abdollahi, Khodayar, Sheikh, Vahedberdi
Afforestation priority for multiple objectives at national scale: Italy as a case study
  • Gibertini, Chiara, Rossi, Lorenzo M. W., Cislaghi, Alessio, Galimberti, Susanna, Marchetti, Simone, Marchi, Maurizio, Pastore, Maria C., Pimentel, Luis, Salbitano, Fabio, Shamir, Livia, Vacchiano, Giorgio
Generating High-Resolution DEMs from Two Different Resolution Data for 2D Flood Mapping.
  • Hidayah, Entin, Widiarti, Wiwik Yunarni, Wiyono, Retno Utami Agung, Dhokhikah, Yeny, Lee, Wei Koon, Yusop, Zulkifli, Putra, Santosa Sandy
Global spatially detailed water footprint of crop production over five
  • Demeke, Betelhem W., Mekonnen, Mesfin M., Brauman, Kate A., Magliocca, Nicholas, Moradkhani, Hamid
Effects of River Channel Structural Modifications on High-Flow Characteristics Using 2D Rain-on-Grid HEC-RAS Modelling: A Case of Chongwe River Catchment in Zambia
  • Mudenda, Frank, M. Mwangi, Hosea, Gathenya, John M., Maina, Caroline W.
Effects of green infrastructure composition and configuration on runoff
  • Liu, Ling, Chen, Zhaofang, Lu, Xinghao, Wang, Yuncai
Evaluating urban flood risk and retention potential using InVEST-UFRM: a case study from Gurugram, India
  • Sehrawat, Simran, Shekhar, Sulochana
Predicting LULC Changes and Assessing their Impact on Surface Runoff
  • Riche, Abdelkader, Drias, Ammar, Ricci, Riccardo, Souissi, Boularbah, Melgani, Farid
Intercomparison of regional flood frequency estimation procedures in
  • Diop, Serigne Bassirou, Tramblay, Yves, Bodian, Ansoumana, Dieppois, Bastien, Ouarda, Taha B. M. J.
Multilevel Flood Susceptibility Mapping by Fuzzy Sets, Analytical
  • Gorsevski, Pece V., Milevski, Ivica
Nonlinear responses and differentiated pathways of driving mechanisms underlying the spatiotemporal evolution of water retention in the Qinba Mountains
  • Zhang, Jinxia, Zhang, Jiaqi, Liu, Zhao, Li, Duofen, Sun, Xudong
Deep learning-based aided spatial mapping of local scale hydrologic soil
  • Faouzi, Elhousna, Arioua, Abdelkrim, Hssaisoune, Mohammed, Houmma, Ismaguil Hanade, Brahim, Yassine Ait, Ismail, Karaoui, Arshad, Arfan, Bouchaou, Lhoussaine
Land use change as a driver of hydrological ecosystem services in the
  • Obateru, Rotimi Oluseyi
Land use/Land cover control on groundwater recharge: A multi-method
  • Lweendo, Muumbe K., Mapani, Benjamin, Banda, Kawawa, Adelabu, Samuel, Bassukas, Dimitrios, Kulls, Christoph
Natural climate change and social population ageing reconstruct the flood risk gap between inland and coastal cities in China
  • Gu, Xinyue, Liu, Xinhu, Long, Zhiyong, Duan, Huanfeng, Liu, Xintao
Feasibility of pumped hydro energy storage in arid climate using GIS and
  • Badi, Shima Hassan, Alamailes, Abubaker A., Maitieg, Abduladim, Talhey, Mohamed A.
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