A Comparative Study of Evapotranspiration Calculated from Remote Sensing and Meteorological Data for Gaya District, India

Abstract

A study on evapotranspiration for wheat was conducted in the two-year Rabi season crop from November, 2017 to April, 2018 and from November, 2018 to April 2019 at Gaya District, Bihar. Spatio-temporal information on actual evapotranspiration (ETa) helps users to better understand evaporative depletion and to establish links between land use, water allocation, and water use. The Surface Energy Balance Algorithm for Land (SEBAL) was adopted for the Gaya District, employing the essential adaptations for local soil and meteorological conditions. AOI images were used to retrieve the needed of spectral data. The results have been compared to the in-situ measurements of CROPWAT Model, Makkink Model (MM) and remote sensing SEBAL model. A precise and uniform assessment of reference crop evapotranspiration (ETo) is required due to its crucial role in estimating the crop water needs in irrigated agriculture. The aim of this work was to estimate evapotranspiration (ETc) in a semi-arid environment using freely accessible earth observation datasets and a regionally distributed crop coefficient (Kc). Based on a regionally distributed crop coefficient (Kc), the SEBAL and Makkink models were used to anticipate the actual evapotranspiration (ETc). The Makkink model fared adequately when compared to the standard Penman-Monteith model estimate (R2=0.88), according to statistical tests for model comparison. Analysis also demonstrates distributed actual evapotranspiration from the Penman-Monteith model and actual evapotranspiration based on the Makkink model with R2 = 0.76, respectively. The result implies that the Penman-Monteith model-based ETo and Makkink model estimations of ETo are very similar. ETc estimated by SEBAL was also compared with PM ETc with the help of crop coefficient. Additionally, the validation of model’s was performed with the analysis of correlation between models ETc and district level wheat production and area under crop of two years. The results of this analysis outline that water availability and good amount of rainfall gives higher wheat yield and resulted into more etc.