Rahimzadegan et al. (2026) Satellite-based mapping of evapotranspiration, water stress, and crop productivity in mixed irrigated–rainfed agricultural watersheds of central minnesota

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-10-07
• Authors: Majid Rahimzadegan, David J. MULLA, Bryan Runck, Vasudha Sharma
• DOI: 10.1016/j.agwat.2026.110830

Research Groups

• Department of Soil, Water and Climate, University of Minnesota
• GEMS Informatics Center, University of Minnesota

Short Summary

This study applied a Google Earth Engine–based Surface Energy Balance Algorithm for Land (SEBAL) framework to estimate actual crop evapotranspiration under non-standard conditions (ETₐ), water stress index (WSI), and crop productivity across two central Minnesota watersheds during 2021–2024.

Objective

• To develop an integrated remote-sensing framework to quantify ETₐ, water stress, yield, and crop water productivity at the watershed scale.
• To evaluate the performance of SEBAL against OpenET geeSEBAL and field water-balance ETₐ estimates in humid agricultural watersheds.

Study Configuration

• Spatial Scale: 30 m spatial resolution across two agricultural watersheds in central Minnesota: the Sauk River Watershed and the Clearwater–Elk River Watershed.
• Temporal Scale: 2021–2024 growing seasons.

Methodology and Data

• Models used: Surface Energy Balance Algorithm for Land (SEBAL) framework.
• Data sources: Landsat 8 and 9 imagery, PRISM climate normals, soil texture information from the SSURGO database, and meteorological observations from Becker and Westport agricultural weather stations.

Main Results

• SEBAL-derived ETₐ showed strong consistency with OpenET geeSEBAL product (R = 0.87–0.97) and moderate agreement with independent field water-balance ETₐ (R = 0.74–0.75; NSE = 0.53–0.54).
• Clearwater–Elk exhibited a stronger irrigation signal, whereas Sauk showed higher growing-season water stress.
• Yield disaggregation showed strong agreement with observed field-scale patterns for corn (R = 0.91; NSE = 0.81), while soybean showed high correlation but more modest predictive efficiency (R = 0.80; NSE = 0.42).

Contributions

• This study provides an integrated framework to evaluate ETₐ, water stress, yield, and crop productivity at the watershed scale in humid agricultural regions.
• The results highlight the importance of considering both canopy vigor and moisture conditions when estimating crop yields.

Funding

• This research was funded by [project/program name] with reference code [reference code].

Citation

@article{Rahimzadegan2026Satellitebased,
  author = {Rahimzadegan, Majid and MULLA, David J. and Runck, Bryan and Sharma, Vasudha},
  title = {Satellite-based mapping of evapotranspiration, water stress, and crop productivity in mixed irrigated–rainfed agricultural watersheds of central minnesota},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110830},
  url = {https://doi.org/10.1016/j.agwat.2026.110830}
}