Comparative Analysis of Remote sensing based evapotranspiration models for seasonal crops in desert environment

Abstract

Meticulous knowledge of evapotranspiration is vital for managing water resources. In this study, we used Landsat 8 to assess and evaluate four remote sensing-based energy balance models: SEBAL, SSEB, TSEB, and S-SEBI to predict evapotranspiration (ET) for seasonal crops in the desert environment. All models performed well in the prediction of spatial-temporal variation of ET. The actual ET of crops for different days of the year has been calculated using the Penman-Monteith equation and crop coefficients. The ET estimated for Kharif crops is higher than the Rabi crops. With different land cover, NDVI, and land surface temperature, the change of ET and transpiration is analysed. The seasonal transpiration is estimated using the trapezoidal and Gaussian fitting method. SSEB resulted in higher accuracy for Kharif crops, similarly TSEB model for Rabi crops. The spatiotemporal extent knowledge of ET can assist reservoir managers in allocating water for agriculture and other uses.