Abstract
The Von Mises distribution and the Pearson Type III distribution are used to describe the occurrence dates and magnitudes of annual maximum flood series, respectively. A bivariate joint distribution is developed based on Gumbel Archimedean copula. A modified inference functions for margins (MIFM) method is used to establish the marginal distribution and joint distributions with an incorporation of historical information. The conditional probabilities of flood volumes, given the flood occurrence dates (or peak discharge exceeding various values), are derived. A boundary identification method is developed to define the feasible ranges of flood peaks and volumes suitable for combination. Two combination methods, i.e., the equivalent frequency combination (EFC) method and the conditional expectation combination (CEC) method, for estimating unique bivariate flood quantiles are also proposed. The case study shows that the bivariate joint distribution can well fit both occurrence dates and magnitudes of annual maximum flood series, which can extract more flood information and provide an alternative way to conduct the multivariate frequency analysis.
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Chen, L., Guo, S. (2019). Copula-Based Flood Frequency Analysis. In: Copulas and Its Application in Hydrology and Water Resources. Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-13-0574-0_3
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DOI: https://doi.org/10.1007/978-981-13-0574-0_3
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