Extreme value theory (EVT) is a statistical method that is concerned with the analysis of the extreme values of a distribution. EVT is often used to model the behavior of rare and extreme events, such as floods caused by extreme rainfall phenomena. There are two methods for identifying the movement of extreme values, namely Block Maxima (BM) and Peaks over Threshold (POT). The Generalized Extreme Value (GEV) distribution has three parameters and is used to model the distribution of extreme values using the BM method. On the other hand, the classic method of EVT does not capture uncertainty in the data. The Bayesian method is one of the statistical methods that can use information from data and prior knowledge. This research aims to model EVT-BM using a Bayesian approach for rainfall data at eleven weather stations in Jawa Timur. The result shows that all rainfall distributions at different weather conditions have a value of the parameter shape equal to 0, which implies a Weibull distribution. This paper also provides return level of 6 months, 2, 5, and 10 years respectively.
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