Assessing Flood Risk: LH-Moments Method and Univariate Probability Distributions in Flood Frequency Analysis

• Published in: Water (Basel) Vol. 15; no. 19; p. 3510
• Main Authors: Ilinca, Cornel, Stanca, Stefan Ciprian, Anghel, Cristian Gabriel
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2023
• Subjects: Distribution (Probability theory); Floods; frequency analysis; linear moments; log-logistic; Maximum likelihood method; Methods; Parameter estimation; parameters; Pareto; Probability; Rayleigh; Skewness; Romania
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w15193510

This study examines all of the equations necessary to derive the parameters for seven probability distributions of three parameters typically used in flood frequency research, namely the Pearson III (PE3), the generalized extreme value (GEV), the Weibull (W3), the log-normal (LN3), the generalized Pareto Type II (PG), the Rayleigh (RY) and the log-logistic (LL3) distributions, using the higher-order linear moments method (LH-moments). The analysis represents the expansion of previous research whose results were presented in previous materials, and is part of hydrological research aimed at developing a standard for calculating maximum flows based on L-moments and LH-moments. The given methods for calculating the parameters of the examined distributions are used to calculate the maximum flows on Romania’s Prigor River. For both methods, the criterion for selecting the most suitable distribution is represented by the diagram of the L-skewness–L-kurtosis and LH-skewness–LH-kurtosis. The results for Prigor River show that the PG distribution is the best model for the L-moments method, the theoretical values of the statistical indicators being 0.399 and 0.221. The RY distribution is the best model for the LH-moments technique, with values of 0.398 and 0.192 for the two statistical indicators.