Frequency analysis of nonstationary annual maximum flood series using the time‐varying two‐component mixture distributions |
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| Authors: | Lei Yan Lihua Xiong Dedi Liu Tiesong Hu Chong‐Yu Xu |
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| Affiliation: | 1. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China;2. Department of Geosciences, University of Oslo, Oslo, Norway |
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| Abstract: | The most popular practice for analysing nonstationarity of flood series is to use a fixed single‐type probability distribution incorporated with the time‐varying moments. However, the type of probability distribution could be both complex because of distinct flood populations and time‐varying under changing environments. To allow the investigation of this complex nature, the time‐varying two‐component mixture distributions (TTMD) method is proposed in this study by considering the time variations of not only the moments of its component distributions but also the weighting coefficients. Having identified the existence of mixed flood populations based on circular statistics, the proposed TTMD was applied to model the annual maximum flood series of two stations in the Weihe River basin, with the model parameters calibrated by the meta‐heuristic maximum likelihood method. The performance of TTMD was evaluated by different diagnostic plots and indexes and compared with stationary single‐type distributions, stationary mixture distributions and time‐varying single‐type distributions. The results highlighted the advantages of TTMD with physically‐based covariates for both stations. Besides, the optimal TTMD models were considered to be capable of settling the issue of nonstationarity and capturing the mixed flood populations satisfactorily. Copyright © 2016 John Wiley & Sons, Ltd. |
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| Keywords: | flood frequency analysis nonstationarity time‐varying two‐component mixture distributions (TTMD) time‐varying moments circular statistics the Weihe River |
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