Some best-fit probability distributions for at-site flood frequency analysis of the Ume River

Abstract

At-site flood frequency analysis is a direct method of flood estimation at a given site. The choice of an appropriate probability distribution and parameter estimation method plays a vital role in at-site frequency analysis. In the current article, flood frequency analysis is carried out at five gauging sites of the Ume River in Sweden. Generalised extreme value, three-parameter log-normal, generalised logistic and Gumbel distributions are fitted to the annual maximum peak flow data. The L-moment and the maximum likelihood methods are used to estimate the parameters of the distributions. Based on different goodness-of-fit tests and accuracy measures, the three-parameter log-normal distribution has been identified as the best-fitted distribution by using the L-moments method of estimation for gauging sites Harrsele Krv, Gardiken and Överuman Nedre. The generalised extreme value distribution with the L-moments estimation provided the best fit to maximum annual streamflow at gauging sites Solberg and Stornorrfors Krv. Finally, the best-fitted distribution for each gauging site is used to predict the maximum flow of water for return periods of 5, 10, 25, 50, 100, 200, 500, and 1000 years.