Bivariate Analysis of Extreme Precipitation Using Copula Functions in Arid and Semi-Arid Regions

This study analyzed extreme precipitation events, using daily rainfall data for 1966–2015. A Mann–Kendall trend test was used to evaluate trends in precipitation, copula functions were applied compute the joint return periods of and univariate bivariate distributions determine risk. The results showed that decrease consecutive wet days (CWD) significant west northwest Iran, while dry (CDD) index increasing therein. on more than 90th percentile (P90) very annual number with less threshold (D90) indices followed similar patterns, no most parts but at several stations north, west, northwest, their decline extreme. Furthermore, increase D10 (annual threshold) P10 (total a year) regions including areas, also part center. More 50 percent Iran experienced low risk level, period events (CWD, CDD) 27.5 years, (D10, D90), (P10, P90), P10) pairs 100 years Iran. Due drought increased. Based changes recent findings this will be useful copula-based frequency analysis under changing environment regional global scales.