Objective regional frequency analysis of extreme precipitation in Sicily, Italy

Abstract

The extreme events have large impacts on society and are likely to increase under climate change. For design and management decisions, particularly around hydraulic infrastructures, accurate estimates of precipitation magnitudes are needed at different durations. In this paper, the regional frequency analysis has been implemented and applied to precipitation data recorded in Sicily, Italy. Annual maximum series for rainfall durations of 1, 3, 6, 12 and 24 h provided by about 130 rain gauges were used. The Regional Frequency Analysis (RFA) has been used to identify the homogeneous regions using Principal Component Analysis (PCA) followed by a clustering analysis, through k-means, aimed to identify regional groups. Two regional probability distributions have been used in order to derive the Depth-Duration Frequency (DDF) curves: lognormal distribution with three parameters (GNO) and generalized extreme value distribution (GEV). The regional parameters of these distributions were estimated using the L-moment ratios approach while the relative bias and relative RMSE have been calculated using a simulation study of regional L-moment algorithm for the assessment of the accuracy.