A comparative study of probability distribution models for flood discharge estimation

Due to climate change, floods have been more frequent in recent years. Estimating the flood discharge as a result of flood frequency analysis is very substantial to make necessary preparations for possible floods. Data covering 36 years were collected from different stream gauging stations (SGS No: D17A016 and EIEI 1731) in Eastern Mediterranean Basin. With these data, flood discharge values were computed for return periods of 2, 5, 10, 25, 50, 100, 200, 500 and 1000 years. Normal, Log-Normal, Gumbel, Pearson Type III and Log-Pearson Type III statistical distribution methods were used. Kolmogorov-Smirnov (K-S) and Chi-square goodness-of-fit tests were performed to determine which distribution fitted the flood discharge the best. The study showed that the highest flood discharge among the probability distributions for both SGSs came from the Log-Normal distribution, and the lowest discharge was calculated with the Normal distribution. The K-S tests showed that all probability distributions conformed to the 20% significance level. For SGS D17A016, the flood values calculated with Log-Normal distribution were compatible with a 90% confidence interval according to the Chi-square test. Flood values obtained with the other distributions were found within the 10% significance level. In the Chi-square test for SGS EIEI-1731, all probability distributions fell within a 10% significance.