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oa Flood Frequency Analysis: Selection of Distribution Functions for Modelling Extreme Floods on Mountain Rivers
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 18th International Conference Monitoring of Geological Processes and Ecological Condition of the Environment, Apr 2025, Volume 2025, p.1 - 5
Abstract
The most catastrophic floods in Ukraine occur in mountainous regions, where forecasting them based on existing global climate and hydrological models is ineffective. One of the alternative methods of Flood frequency analysis is the selection and use of the most suitable theoretical distributions for further modeling of extreme water flows, the so-called Peaks Above Threshold (POT). The research was carried out on the example of the Opir River (Carpathian Mountains, Ukraine) based on daily observations of water flow over a multi-year period (1961–2020). 10 theoretical distributions were examined using the Chi-square, Kolmogorov-Smirnov, Anderson-Darling criteria.The GEV distribution gave best goodness-of-fit values than other distributions. Based on the GEV distribution function, a statistical model was constructed, the parameters of which were estimated using the Monte Carlo method. The resulting model was used to simulate extreme floods on the Opir River. Two simulation procedures were performed using the Monte Carlo method to generate random data from the best fitting distributions while ignoring the correlations between variables and the Iman Conover method to generate random data from the best fitting distributions while preserving the rank correlation structure. An analysis of the obtained models shows that in the range of percentiles 0-60%, the model built using the Iman Conover methods demonstrates the best agreement of the simulated POT values. In the range of percentiles 60–80%, the model built by the Monte Carlo method demonstrates the best coincidence.
