Water budget-based evapotranspiration product captures natural and human-caused variability

Water budget-based evapotranspiration product captures natural and human-caused variability. Goswami, S., Rajendra Ternikar, C., Kandala, R., Pillai, N. S, Kumar Yadav, V., Abhishek, Joseph, J., Ghosh, S., & Dutt Vishwakarma, B. Environmental Research Letters, 19(9):094034, September, 2024.

Paper doi abstract bibtex

Abstract Evapotranspiration ( ET ) is one of the most important yet highly uncertain components of the water cycle. Available modeled ET products do not necessarily agree with each other at various spatiotemporal scales, either due to limitations on input data and/or due to model assumptions and simplifications. Therefore, using the water budget equation to estimate ET has gained attention. However, numerous water budget combinations with large uncertainties are available, which increases ambiguity in choosing the best ET estimate. Here, the Kalman filter is employed to ingest 96 water budget-based ET estimates, and produce a global ET product with uncertainty \textless 2 mm month −1 , and capture the general spatiotemporal pattern of ET and the inter-annual variability over all continents. Since the water budget includes storage changes due to human interventions, our ET estimates are superior over regions with strong irrigation signals, such as the Ganges basin. We verify our claim by using a modified variable infiltration capacity model that also simulates irrigation activities. Our ET estimates have a global mean positive trend of 0.18 ± 0.02 mm yr −1 with larger regional variations, which we discuss.

@article{goswami_water_2024,
	title = {Water budget-based evapotranspiration product captures natural and human-caused variability},
	volume = {19},
	issn = {1748-9326},
	url = {https://iopscience.iop.org/article/10.1088/1748-9326/ad63bd},
	doi = {10.1088/1748-9326/ad63bd},
	abstract = {Abstract
            
              Evapotranspiration (
              ET
              ) is one of the most important yet highly uncertain components of the water cycle. Available modeled
              ET
              products do not necessarily agree with each other at various spatiotemporal scales, either due to limitations on input data and/or due to model assumptions and simplifications. Therefore, using the water budget equation to estimate
              ET
              has gained attention. However, numerous water budget combinations with large uncertainties are available, which increases ambiguity in choosing the best
              ET
              estimate. Here, the Kalman filter is employed to ingest 96 water budget-based
              ET
              estimates, and produce a global
              ET
              product with uncertainty
              
                
                  
                
                
                  
                    
                      {\textless}
                    
                    2
                  
                
              
               mm month
              −1
              , and capture the general spatiotemporal pattern of
              ET
              and the inter-annual variability over all continents. Since the water budget includes storage changes due to human interventions, our
              ET
              estimates are superior over regions with strong irrigation signals, such as the Ganges basin. We verify our claim by using a modified variable infiltration capacity model that also simulates irrigation activities. Our
              ET
              estimates have a global mean positive trend of
              
                
                  
                
                
                  
                    0.18
                    
                    ±
                    
                    0.02
                  
                
              
              mm yr
              −1
              with larger regional variations, which we discuss.},
	number = {9},
	urldate = {2025-02-14},
	journal = {Environmental Research Letters},
	author = {Goswami, Shubham and Rajendra Ternikar, Chirag and Kandala, Rajsekhar and Pillai, Netra S and Kumar Yadav, Vivek and {Abhishek} and Joseph, Jisha and Ghosh, Subimal and Dutt Vishwakarma, Bramha},
	month = sep,
	year = {2024},
	pages = {094034},
}

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Therefore, using the water budget equation to estimate ET has gained attention. However, numerous water budget combinations with large uncertainties are available, which increases ambiguity in choosing the best ET estimate. Here, the Kalman filter is employed to ingest 96 water budget-based ET estimates, and produce a global ET product with uncertainty \\textless 2 mm month −1 , and capture the general spatiotemporal pattern of ET and the inter-annual variability over all continents. Since the water budget includes storage changes due to human interventions, our ET estimates are superior over regions with strong irrigation signals, such as the Ganges basin. We verify our claim by using a modified variable infiltration capacity model that also simulates irrigation activities. 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Available modeled\n ET\n products do not necessarily agree with each other at various spatiotemporal scales, either due to limitations on input data and/or due to model assumptions and simplifications. Therefore, using the water budget equation to estimate\n ET\n has gained attention. However, numerous water budget combinations with large uncertainties are available, which increases ambiguity in choosing the best\n ET\n estimate. Here, the Kalman filter is employed to ingest 96 water budget-based\n ET\n estimates, and produce a global\n ET\n product with uncertainty\n \n \n \n \n \n \n \n {\\textless}\n \n 2\n \n \n \n mm month\n −1\n , and capture the general spatiotemporal pattern of\n ET\n and the inter-annual variability over all continents. Since the water budget includes storage changes due to human interventions, our\n ET\n estimates are superior over regions with strong irrigation signals, such as the Ganges basin. 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