Predicting Future Flood Risks in the Face of Climate Change: A Frequency Analysis Perspective

The frequency analysis of maximum flows represents a direct method to predict future flood risks in the face of climate change. Thus, the correct use of the tools (probability distributions and methods of estimating their parameters) necessary to carry out such analyzes is required to avoid possible...

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Bibliographic Details
Published inWater (Basel) Vol. 15; no. 22; p. 3883
Main Authors Anghel, Cristian Gabriel, Ilinca, Cornel
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2023
Subjects
Case studies
Distribution (Probability theory)
flood
frequency analysis
Global temperature changes
linear moments
Maximum likelihood method
Parameter estimation
Precipitation
Probability
risks
Rivers
Skewness
statistical distributions
Romania
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Summary:The frequency analysis of maximum flows represents a direct method to predict future flood risks in the face of climate change. Thus, the correct use of the tools (probability distributions and methods of estimating their parameters) necessary to carry out such analyzes is required to avoid possible negative consequences. This article presents four probability distributions from the generalized Beta families, using the L- and LH-moments method as parameter estimation. New elements are presented regarding the applicability of Dagum, Paralogistic, Inverse Paralogistic and the four-parameter Burr distributions in the flood frequency analysis. The article represents the continuation of the research carried out in the Faculty of Hydrotechnics, being part of larger and more complex research with the aim of developing a normative regarding flood frequency analysis using these methods. According to the results obtained, among the four analyzed distributions, the Burr distribution was found to be the best fit model because the theoretical values of the statistical indicators calibrated the corresponding values of the observed data. Considering the existence of more rigorous selection criteria, it is recommended to use these methods in the frequency analysis.
ISSN:2073-4441
2073-4441
DOI:10.3390/w15223883