Comparison of two methods of regional flood frequency analysis by using L-moments

Abstract

A regionalized relationship to estimate flood magnitudes for ungauged and poorly gauged catchments can be established using regional flood frequency analysis (RFFA). Comparison of index-flood and multiple-regression analyses based on L-moments was the main objective of this study. Factor analysis was applied to determine main variables influencing flood magnitude. Results showed that the main variables are perimeter, equivalent diameter, time of concentration, length of main waterway and area. The study area was divided into two regions based on the Ward’s method of clustering approach and site characteristics. The homogeneity test based on L-moments showed that two regions were acceptably homogeneous. Five distributions were fitted to the annual peak flood data of two homogeneous regions. Using the L-moment ratios and the Z-statistic criteria, generalized logistic (GLO) and generalized Pareto (GPA) distributions were identified for the first and second homogeneous regions respectively as the most robust distributions among five potential distributions. The relative root mean square error (RRMSE) measure was applied for evaluating the performance of the index-flood and the multiple-regression methods in comparison with the curve fitting (plotting position) method. In general, the index-flood method gives more reliable estimations for various flood magnitudes of different recurrence intervals.