Using Copula functions to predict climatic change impacts on floods in river source regions

作者：Tingxing Chen, Haishen Lyu, Robert Horton, Yonghua Zhu, Rensheng Chen, Ming-yue Sun, Mingwen Liu, Yu Lin · 发表于：Advances in Climate Change Research · 年份：2024 · DOI：10.1016/j.accre.2024.04.006 · 被引用次数：10 · 研究领域：Hydrology and Drought Analysis、Hydrology and Watershed Management Studies、Flood Risk Assessment and Management

Flood frequency in river source regions is significantly affected by rainfall and snowmelt as part of climatic changes. A traditional univariate flood frequency analysis cannot reflect the complexity of floods, and when used in isolation, it can only underestimate flood risk. For effective flood prevention and mitigation, it is essential to consider the combined effects of precipitation and snowmelt. Copula functions can effectively quantify the joint distribution relationship between floods and their associated variables without restrictions on their distribution characteristics. This study uses copula functions to consider a multivariate probability distribution model of flood peak flow (Q) with cumulative snowmelt (CSm) and cumulative precipitation (CPr) for the Hutubi River basin located in northern Xinjiang, China. The joint frequencies of rainfall and snowmelt floods are predicted using copula models based on the Coupled Model Intercomparison Project Phase 6 data. The results show that Q has a significant positive correlation with 24-d CSm (r = 0.559, p = 0.002) and 23-d CPr (r = 0.965, p < 0.05). Flood frequency will increase in the future, and mid- (2050‒2074) and long-term (2075‒2099) floods will be more severe than those in the near-term (2025‒2049). The probability of flood occurrence is higher under the SSP2-4.5 and SSP1-2.6 scenarios than under SSP5-8.5. Precipitation during the historical period (1990–2014) led to extreme floods, and increasing future precipitat...