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Exploring the Heterogenous Nature of Irrigated Winter Wheat and Potato Fields using an Experimental Water Stress Index and Vegetation Indices
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| Type: | Resource | |
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| Created: | Jun 02, 2026 at 8:13 p.m. (UTC) | |
| Last updated: | Jun 23, 2026 at 7:37 p.m. (UTC) | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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| Views: | 251 |
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Abstract
Growing competition for water has intensified the push for efficient irrigation management. As crop growth and soil properties vary at sub-field scales, irrigation management zones are developed and monitored using in situ data and vegetation indices (VIs). The latter has limited ability to capture plant water stress due to bare soil interference, crop-specific spectral differences, and a time lag between stress onset and phenological response to water stress. Remote sensing evapotranspiration (ET) data can supplement VIs to better characterize water stress. Here, we develop the Water Stress Index (WSI), a satellite-based index that identifies areas of water stress relative to the rest of the field over a selected period using an energy balance approach. The WSI is derived from ET and solar radiation data. An energy use proxy (latent heat flux from OpenET ensemble model) is subtracted from an energy availability proxy (LiDAR-derived and gridMET-modeled incoming solar radiation), producing a gridded map of relative water stress. The downscaled energy availability proxy provides field-scale variability that can be compared with high-resolution ET estimates more effectively than traditional, coarse-resolution products. The WSI is evaluated against in situ matric potential data and multi-season yield data. Results show the WSI consistently outperforms VIs and OpenET in describing end-of-season winter wheat yield. VIs outperform the WSI and OpenET for potatoes, which could be related to potatoes complex and rapid growth patterns. By leveraging energy balance concepts and accessible remote sensing products, the WSI offers an adaptable framework for identifying water-stressed areas in irrigated agricultural fields.
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| github Repository | This HydroShare Repository contains data needed to run python scripts associated with https://github.com/rpommer/RS-WSI |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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