Abstract

Evapotranspiration (ET), a complex mechanism in the hydrological cycle, influences runoff, which in turn influences how much water is required for irrigation. There are many techniques available to calculate of the reference evapotranspiration (ETo). Unfortunately, most efficient reference evapotranspiration approaches are parameter-rich models, making them unsuitable for use in data-scarce locations. On the other hand, accuracy and reliability of simple ETo models vary widely according to regional climate conditions. The purpose of this study was to assess the effectiveness of two temperature-based and three radiation-based simple ET methods in estimating ET algorithms used to forecast the wheat crop for the years 2017–2018 in Gaya District, Bihar. The performance was measured by comparing the temperature and radiation-based method with the parameter intensive Penman-Monteith method. Comparative evaluation of two method (radiation and temperature) was performed through statistical tests, and it was found that the (R2 = 1 and R2 = 0.98) and RMSE = 0.84. The study found that ETo values calculated from the six methods were highly correlated (Pearson correlation coefficient 0.84 to 0.99). Through data analysis for model comparison, it was found that the Radiation method performed satisfactorily when compared to the standard Penman-Monteith model estimate (R2 = 0.94). However, multivariate statistical testing revealed that the ETo readings obtained using various techniques differed significantly from one another. In comparison to radiation-based ETo approaches, temperature-based ETo techniques showed greater disparities. The Priestley-Taylor, Turc, and Jensen-Haise methods all outperformed the other ETo methods in general. When estimating ETo in this study region, it was discovered that radiation-based approaches performed better than temperature-based methods.

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