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Full-Text Articles in Physical Sciences and Mathematics
Evaluation Of Evapotranspiration Estimates Using An Existing Hybrid Machine Learning Model In A Natural And A Managed Dryland Site, Katya Esquivel Herrera
Evaluation Of Evapotranspiration Estimates Using An Existing Hybrid Machine Learning Model In A Natural And A Managed Dryland Site, Katya Esquivel Herrera
Open Access Theses & Dissertations
Evapotranspiration (ET) is a critical component of the hydrologic cycle, encompassing both evaporative water loss from surfaces and transpiration through plant stomata. The environmental factors influencing ET include water and energy availability, atmospheric capacity for water uptake, and various meteorological variables. ET serves as a unique climate variable linking water, energy, and carbon cycles. In agroecosystems, accurate ET quantification is vital for optimizing water use efficiency, irrigation management, and crop yield. Traditional methods for ET estimation involve direct measurements and indirect models, with both presenting limitations.
Recent years have witnessed the integration of remote sensing and machine learning (ML) algorithms …