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Effective Precipitation Dataset for the Irrigated Croplands of the Western United States from 2000 to 2020
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This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
| Type: | Resource | |
| Storage: | The size of this resource is 200.1 MB | |
| Created: | Jul 08, 2024 at 3:40 p.m. (UTC) | |
| Last updated: | Sep 23, 2025 at 2:04 p.m. (UTC) (Metadata update) | |
| Published date: | Sep 15, 2025 at 2:19 p.m. (UTC) | |
| DOI: | 10.4211/hs.c33ce80f5ae44fe6ab2e5dd3c128eb0b | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 736 |
| Downloads: | 1 |
| +1 Votes: | Be the first one to this. |
| Comments: | 1 comment |
Abstract
This repository hosts the monthly effective precipitation datasets for the irrigated croplands of the Western United States at 2 km spatial resolution from 2000 to 2020.
Related article: Hasan, M. F., Smith, R. G., Majumdar, S., Huntington, J. L., Alves Meira Neto, A., & Minor, B. A. (2025). Satellite data and physics-constrained machine learning for estimating effective precipitation in the Western United States and application for monitoring groundwater irrigation. Agricultural Water Management, 319, 109821. https://doi.org/10.1016/j.agwat.2025.109821
GitHub repo: https://github.com/mdfahimhasan/WestUS_Peff
Subject Keywords
Coverage
Spatial
Temporal
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Content
Related Resources
| The content of this resource can be executed by | https://github.com/mdfahimhasan/WestUS_Peff |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
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| National Aeronautics and Space Administration | ||
| United States Geological Survey |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
Md Fahim Hasan 2 weeks, 4 days ago
Please cite the following article if you are using the data:
ReplyHasan, M. F., Smith, R. G., Majumdar, S., Huntington, J. L., Alves Meira Neto, A., & Minor, B. A. (2025). Satellite data and physics-constrained machine learning for estimating effective precipitation in the Western United States and application for monitoring groundwater irrigation. Agricultural Water Management, 319, 109821. https://doi.org/10.1016/j.agwat.2025.109821
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