Fitting statistical probability distribution for evaporation in western Brazil

Abstract

This study aims to find evaporation (ETo) probabilities for the central west region of Brazil, including Campo Grande, Cuiabá, Goiânia and Brasilia. In this case, a maximum likelihood estimation was used for the probability distributions adjusting to the monthly ETo from 1960 to 2020. The work estimates three probability distributions, including the Generalized Extreme Values (GEV), Gumbel (GUM) and Log-Normal (LN). The Kolmogorov-Smirnov test, the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the root mean square error (RMSE) and the coefficient of determination (R2) were applied to measure the quality of the adjustment. The evapotranspiration forecasts were made for the return periods of 10, 30, 50, and 100 years. The GEV and GUM distributions are advised for use during the summer. Altering LN distribution to a sequence of ETo throughout the winter months is the best option. Moreover, deforestation, combustion, extensive fires, aerosol pollutants, and climate change are the primary causes of excessive ETo in the area under study.