Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA
A satellite-based vegetation index model that tracks daily crop growth and evapotranspiration (ETc) is developed, tested, and validated over irrigated farms in Yuma irrigation districts of Arizona and California. Model inputs are remotely sensed normalized difference vegetation index (NDVI) images,...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-12-01
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| Series: | Agricultural Water Management |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S037837742300447X |
| _version_ | 1797430029766885376 |
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| author | Andrew N. French Charles A. Sanchez Troy Wirth Andrew Scott John W. Shields Eduardo Bautista Mazin N. Saber Elzbieta Wisniewski Mohammadreza R. Gohardoust |
| author_facet | Andrew N. French Charles A. Sanchez Troy Wirth Andrew Scott John W. Shields Eduardo Bautista Mazin N. Saber Elzbieta Wisniewski Mohammadreza R. Gohardoust |
| author_sort | Andrew N. French |
| collection | DOAJ |
| description | A satellite-based vegetation index model that tracks daily crop growth and evapotranspiration (ETc) is developed, tested, and validated over irrigated farms in Yuma irrigation districts of Arizona and California. Model inputs are remotely sensed normalized difference vegetation index (NDVI) images, crop type maps, and local weather. The utility and novelty of the model is a more accurate assessment of ETc than currently provided by the US Bureau of Reclamation’s evapotranspiration modeling system. The model analyzes NDVI time series data from the European Space Agency’s Sentinel-2 satellites using the Google Earth Engine, constructs FAO-56 style crop growth stages from NDVI, and then estimates daily ETc using pre-defined crop coefficients (Kc) and grass reference evapotranspiration (ETos). Four crops were selected to test and evaluate model performance: short-season broccoli, mid-season cotton and wheat, and perennial alfalfa. Comparison of model results showed that Reclamation reports overestimate alfalfa and wheat ETc by 21–25%, cotton ETc by 6%, and underestimate broccoli ETc by 21%. Variability resolved by the model ranged 6–18% of median total ETc. Comparison of model results with those obtained from 13 eddy covariance sites showed validation discrepancies ranging 1–14%: average total actual ETc differences were 12, − 14, 78, and 87 mm/season, respectively, for alfalfa, broccoli, cotton, and wheat. The wide availability of Sentinel-2 data, collected every 5 days or less, and the rapid processing via Google Earth Engine make the vegetation index model implementation fast and practical. Its accuracy and ability to resolve ETc for every field would benefit the Reclamation water accounting system and provide valuable consumptive water use data for any Colorado River stakeholder. |
| first_indexed | 2024-03-09T09:21:46Z |
| format | Article |
| id | doaj.art-0c7c1854261a42e1bfdf76890ae27797 |
| institution | Directory Open Access Journal |
| issn | 1873-2283 |
| language | English |
| last_indexed | 2024-03-09T09:21:46Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Agricultural Water Management |
| spelling | doaj.art-0c7c1854261a42e1bfdf76890ae277972023-12-02T06:58:39ZengElsevierAgricultural Water Management1873-22832023-12-01290108582Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USAAndrew N. French0Charles A. Sanchez1Troy Wirth2Andrew Scott3John W. Shields4Eduardo Bautista5Mazin N. Saber6Elzbieta Wisniewski7Mohammadreza R. Gohardoust8US Department of Agriculture, ARS, Maricopa, AZ USA; Corresponding author.University of Arizona, Maricopa, AZ, USAUS Bureau of Reclamation, Boulder City, NV, USAUS Bureau of Reclamation, Boulder City, NV, USAUS Bureau of Reclamation, Boulder City, NV, USAUS Department of Agriculture, ARS, Maricopa, AZ USAUniversity of Arizona, Maricopa, AZ, USAUS Department of Agriculture, ARS, Maricopa, AZ USAUniversity of Arizona, Maricopa, AZ, USAA satellite-based vegetation index model that tracks daily crop growth and evapotranspiration (ETc) is developed, tested, and validated over irrigated farms in Yuma irrigation districts of Arizona and California. Model inputs are remotely sensed normalized difference vegetation index (NDVI) images, crop type maps, and local weather. The utility and novelty of the model is a more accurate assessment of ETc than currently provided by the US Bureau of Reclamation’s evapotranspiration modeling system. The model analyzes NDVI time series data from the European Space Agency’s Sentinel-2 satellites using the Google Earth Engine, constructs FAO-56 style crop growth stages from NDVI, and then estimates daily ETc using pre-defined crop coefficients (Kc) and grass reference evapotranspiration (ETos). Four crops were selected to test and evaluate model performance: short-season broccoli, mid-season cotton and wheat, and perennial alfalfa. Comparison of model results showed that Reclamation reports overestimate alfalfa and wheat ETc by 21–25%, cotton ETc by 6%, and underestimate broccoli ETc by 21%. Variability resolved by the model ranged 6–18% of median total ETc. Comparison of model results with those obtained from 13 eddy covariance sites showed validation discrepancies ranging 1–14%: average total actual ETc differences were 12, − 14, 78, and 87 mm/season, respectively, for alfalfa, broccoli, cotton, and wheat. The wide availability of Sentinel-2 data, collected every 5 days or less, and the rapid processing via Google Earth Engine make the vegetation index model implementation fast and practical. Its accuracy and ability to resolve ETc for every field would benefit the Reclamation water accounting system and provide valuable consumptive water use data for any Colorado River stakeholder.http://www.sciencedirect.com/science/article/pii/S037837742300447XCrop evapotranspirationSentinel-2Google Earth EngineLower Colorado RiverNDVI |
| spellingShingle | Andrew N. French Charles A. Sanchez Troy Wirth Andrew Scott John W. Shields Eduardo Bautista Mazin N. Saber Elzbieta Wisniewski Mohammadreza R. Gohardoust Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA Agricultural Water Management Crop evapotranspiration Sentinel-2 Google Earth Engine Lower Colorado River NDVI |
| title | Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA |
| title_full | Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA |
| title_fullStr | Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA |
| title_full_unstemmed | Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA |
| title_short | Remote sensing of evapotranspiration for irrigated crops at Yuma, Arizona, USA |
| title_sort | remote sensing of evapotranspiration for irrigated crops at yuma arizona usa |
| topic | Crop evapotranspiration Sentinel-2 Google Earth Engine Lower Colorado River NDVI |
| url | http://www.sciencedirect.com/science/article/pii/S037837742300447X |
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