Comparison of Machine Learning and Empirical Methods for Data-Efficient Estimation of Reference Evapotranspiration in a Semiarid Region

Abstract

AbstractAccurate estimation of reference evapotranspiration (ET0) is critical for efficient irrigation planning and water resource management, particularly in semiarid regions where meteorological data are limited. This study compares the performance of ...Practical ApplicationsThis study presents a practical solution for regions with limited weather data by showing how ML can accurately estimate reference ET0, a key factor in managing water for agriculture, drought planning, and irrigation. Traditional ...