Abstract

Several phenomena have been studied to gain knowledge of their average values. However, for some phenomena, it is more relevant to study their extreme values, such as dam resistance, air humidity, wind speed, among others. Consequently, studies aimed at identifying asymptotic distributions of extreme values have been conducted to derive a distribution that does not depend on the sample's distribution. In this way, disasters in the most diverse sectors can be avoided. In this study, daily precipitation data from the city of Belo Horizonte between January 1, 1970, and December 31, 2024, were modeled. The maximum precipitation values for each year were selected, resulting in 55 observations. The dataset was obtained from the Meteorological Database for Teaching and Research (BDMEP). The Generalized Extreme Value (GEV) distribution was fitted to estimate the return levels for extreme precipitation over short, medium, and long-term periods, specifically 10, 25, 50, and 100 years. The location, scale, and shape parameters of the GEV distribution were estimated using the maximum likelihood method. However, due to the nonlinearity of the equations, the Newton-Raphson numerical method was applied. The results indicated that precipitation levels are expected to reach 132 mm in 10 years, 156 mm in 25 years, 175 mm in 50 years, and 195 mm in 100 years. In light of these findings, public policies should be implemented to prevent floods, landslides, epidemics, and economic losses in industrial, agricultural, and livestock sectors in the state capital and neighboring cities.

Keywords

• Modeling
• Return
• Rain
• Climate forecast

References

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