Multivariate Modeling Of Flood Characteristics Using Vine Copulas
| Autor: | Muhammet Nuri Ispirli, Faruk Gürbüz, Fatih Tosunoglu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Global and Planetary Change
Multivariate statistics 0208 environmental biotechnology Copula (linguistics) Univariate Tail dependence Soil Science Geology 02 engineering and technology 010501 environmental sciences 01 natural sciences Pollution 020801 environmental engineering Vine copula Joint probability distribution Statistics Generalized extreme value distribution Environmental Chemistry 0105 earth and related environmental sciences Earth-Surface Processes Water Science and Technology Weibull distribution Mathematics |
| Popis: | Vine copulas provide a great deal of flexibility in modeling complex dependence structures between the variables. In spite of its importance, very limited attention has been paid in hydrology field. In the present study, multivariate modelling of flood characteristics was performed using traditional Archimedean and Elliptical and Vine copulas. In the first phase, flood characteristics [peak (Q), volume (V) and duration (D)] were computed from daily streamflow of 18 stations located in the Euphrates River Basin, Turkey. Based on various model selection criteria, the gamma and Weibull distributions for Q series, the logistic and generalized extreme value distributions for V series and the logistic, log-logistic and generalized extreme value distributions for D series were mostly found to be the best appropriate univariate models. In the second phase, the considered copulas were evaluated for modeling joint distribution of flood Q–V–D triplets at each station. On evaluating their performance by various copula selection methods, graphical procedures and tail dependence analysis, the Vine copulas have been identified as the most valid models. In last phase, conditional and joint return periods of different flood Q, V and D combinations were estimated and the spatial distribution of the return periods were drawn using Geographic Information Systems tool. |
| Databáze: | OpenAIRE |
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