Abstract

Evapotranspiration is a complex process in the hydrological cycle that influences the quantity of surface and groundwater. This study strives to evaluate potential evapotranspiration (PET) estimating models, modeling, and project potential evapotranspiration under climate scenarios. For models evaluation, the modified Hargreaves???Samani, Thornthwait, and Blaney???Criddle were evaluated against the FAO 56 Penman???Monteith method using the relative error (Re), normalized root-mean-squared error, and Pearson correlation (r). Multiple linear regression technique has been used to develop a PET estimation model using six climate parameters (minimum and maximum temperatures, relative humidity, wind speed, solar radiation, and sun hours). Outputs of 17 global climate models ensemble were used for RCP 4.5 and 8.5 emission scenarios to predict future PET. The correlation of climate parameters with PET reveals solar radiation, and Tmax had strong correlation (r) (0.73 and 0.8) at Shola Gebeya and (0.65 and 0.8) at Aleltu Agriculture, respectively, than other considered parameters. The models evaluation shows the modified Hargreaves???Samani equation performed better than others at both Shola Gebeya and Aleltu Agriculture stations. The result of multiple linear regression model shows the input variables used in the modeling were sufficient, implying that this model can be successfully used in estimating PET. Overall, the estimated PET using the multiple linear regression models under RCP 4.5 and 8.5 emission scenarios shows an increasing trend???this is pillar information for the water users in the study catchment.

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