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Joint Dependence Between River Water Temperature, Air Temperature, and Discharge in the Yangtze River: The Role of the Three Gorges Dam
Author(s) -
Liu Zhiyong,
Chen Xiaohong,
Liu Feng,
Lin Kairong,
He Yanhu,
Cai Huayang
Publication year - 2018
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2018jd029078
Subject(s) - environmental science , three gorges , water level , bivariate analysis , yangtze river , hydrology (agriculture) , air temperature , joint (building) , joint probability distribution , atmospheric sciences , statistics , mathematics , geography , geology , geotechnical engineering , china , architectural engineering , cartography , archaeology , engineering
The water temperature of rivers is of considerable significance to freshwater ecosystems and human water use. In contrast to traditional regression models or other deterministic statistical models, we present a probabilistic approach to examine the joint dependence structures of water‐air temperature and water temperature‐discharge in the Yangtze River. Such dependence structures were built based on bivariate probabilistic models with well‐fitted marginal distributions of each variable. To investigate the stability of the dependence structures and the effects of the Three Gorges Dam (TGD), three stations (i.e., Cuntan, Yichang, and Datong) located in different sections of the river were involved in comparison between two periods, that is, pre‐TGD (1975–1987) and post‐TGD (2003–2014) periods (the dam began operating in 2003). Our results indicate that at the three stations the joint occurrence probabilities of the air‐water temperature events (e.g., the compound extreme events) tend to be lower for the second period. The dependence structures of water temperature and river discharge were stable between the two periods at the upstream station. For the downstream station relatively close to the TGD (Yichang station), a clear disturbance was observed in the dependence structures of water temperature‐discharge. In addition, relying on the established bivariate and trivariate dependence models, we further assessed the risk of different water temperature events under individual and coupled extreme conditions of air temperature and discharge. The trivariate model also revealed substantial changes in the probabilistic difference between the pre‐TGD and post‐TGD periods at Yichang station, indicating the impact from the TGD.