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Nonstationary flood coincidence risk analysis using time-varying copula functions.
Scientific Reports ( IF 3.8 ) Pub Date : 2020-02-25 , DOI: 10.1038/s41598-020-60264-3 Ying Feng 1, 2 , Peng Shi 1, 2 , Simin Qu 1, 2 , Shiyu Mou 1, 2 , Chen Chen 1, 2 , Fengcheng Dong 1, 2
Scientific Reports ( IF 3.8 ) Pub Date : 2020-02-25 , DOI: 10.1038/s41598-020-60264-3 Ying Feng 1, 2 , Peng Shi 1, 2 , Simin Qu 1, 2 , Shiyu Mou 1, 2 , Chen Chen 1, 2 , Fengcheng Dong 1, 2
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The coincidence of flood flows in a mainstream and its tributaries may lead to catastrophic floods. In this paper, we investigated the flood coincidence risk under nonstationary conditions arising from climate changes. The coincidence probabilities considering flood occurrence dates and flood magnitudes were calculated using nonstationary multivariate models and compared with those from stationary models. In addition, the "most likely" design based on copula theory was used to provide the most likely flood coincidence scenarios. The Huai River and Hong River were selected as case studies. The results show that the highest probabilities of flood coincidence occur in mid-July. The marginal distributions for the flood magnitudes of the two rivers are nonstationary, and time-varying copulas provide a better fit than stationary copulas for the dependence structure of the flood magnitudes. Considering the annual coincidence probabilities for given flood magnitudes and the "most likely" design, the stationary model may underestimate the risk of flood coincidence in wet years or overestimate this risk in dry years. Therefore, it is necessary to use nonstationary models in climate change scenarios.
中文翻译：
使用时变copula函数进行非平稳洪水重合风险分析。
主流及其支流中洪水的巧合可能会导致灾难性的洪水。在本文中，我们研究了气候变化引起的非平稳条件下的洪水重合风险。使用非平稳多元模型计算了考虑洪水发生日期和洪水幅度的重合概率，并将其与平稳模型相比较。此外，基于copula理论的“最可能”设计用于提供最可能的洪水重合情况。选择了淮河和洪河作为案例研究。结果表明，洪水重合的最高概率发生在7月中旬。两条河流的洪水幅度的边际分布是不稳定的，对于洪水幅度的依存结构，时变copula比固定copule更好。考虑到给定洪水幅度和“最可能”设计的年度重合概率，固定模型可能会低估雨季的洪水重合风险，或高估旱年的这种风险。因此，有必要在气候变化情景中使用非平稳模型。
更新日期：2020-02-25
中文翻译：
使用时变copula函数进行非平稳洪水重合风险分析。
主流及其支流中洪水的巧合可能会导致灾难性的洪水。在本文中，我们研究了气候变化引起的非平稳条件下的洪水重合风险。使用非平稳多元模型计算了考虑洪水发生日期和洪水幅度的重合概率，并将其与平稳模型相比较。此外，基于copula理论的“最可能”设计用于提供最可能的洪水重合情况。选择了淮河和洪河作为案例研究。结果表明，洪水重合的最高概率发生在7月中旬。两条河流的洪水幅度的边际分布是不稳定的，对于洪水幅度的依存结构，时变copula比固定copule更好。考虑到给定洪水幅度和“最可能”设计的年度重合概率，固定模型可能会低估雨季的洪水重合风险，或高估旱年的这种风险。因此，有必要在气候变化情景中使用非平稳模型。
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