Feng Ying, Shi Peng, Qu Simin, Mou Shiyu, Chen Chen, Dong Fengcheng
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China.
College of Hydrology and Water Resources, Hohai University, Nanjing, 210098, China.
Sci Rep. 2020 Feb 25;10(1):3395. doi: 10.1038/s41598-020-60264-3.
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.
干流与其支流洪水流量的同时出现可能导致灾难性洪水。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同时发生风险。使用非平稳多变量模型计算考虑洪水发生日期和洪水量级的同时发生概率，并与平稳模型的概率进行比较。此外，基于Copula理论的“最可能”设计用于提供最可能的洪水同时发生情景。选取淮河和洪河作为案例研究。结果表明，洪水同时发生的最高概率出现在7月中旬。两条河流洪水量级的边缘分布是非平稳的，对于洪水量级的相依结构，时变Copula比平稳Copula拟合得更好。考虑给定洪水量级的年同时发生概率和“最可能”设计，平稳模型可能在湿润年份低估洪水同时发生的风险，而在干旱年份高估这种风险。因此，在气候变化情景下有必要使用非平稳模型。
