Modeling Extreme Precipitation Data in a Mining Area

Abstract

In recent decades, extreme precipitation events have increased in frequency and intensity in Greece and across regions of the Mediterranean, with significant environmental and socioeconomic impacts. Therefore, extensive statistical analysis of the extreme rainfall characteristics on a dense temporal scale is crucial for areas with important economic activity. For this reason, this paper uses the daily precipitation measurements of four meteorological stations in a mining area of northeastern Chalkidiki peninsula from 2006 to 2021. Three statistical approaches were carried out to develop the best-fitting probability distribution for annual extreme precipitation conditions, using the maximum likelihood method for parameter estimation: the block maxima of the generalized extreme value (GEV) distribution and the peak over threshold of the generalized Pareto distribution (GPD) based on extreme value theory (EVT), and the gamma distribution. Based upon this fitting distribution procedure, return periods for the extreme precipitation values were calculated. Results indicate that EVT distributions satisfactorily fit extreme precipitation, with GPD being the most appropriate, and lead to similar conclusions regarding extreme events.