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1篇 您的检索式:作者名="Xinjun Tu"
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1Joint probability analysis of water and sediment and predicting sediment load based on copula function显示文摘The Jinsha River comprises the upper reaches of the Yangtze River,which is the river section with the highest sediment content.Monitoring of sediment transport in the Jinsha River is done to the guarantee for the normal operation of the Three Gorges Reservoir.In the current study,a copula function was used to do a joint probability analysis of the water and sediment in the Jinsha River Basin(JRB),further a sediment load prediction model based on the copula function also was constructed.The results show that the average annual flow from 2001 to 2018 at the outlet of the Jinsha River(Yibin station)is about60.43 billion m^(3),and the average annual sediment load is about 58.82 million t.The linear correlation coefficient between annual flow and annual sediment load is 0.28.The best marginal distribution for annual flow and sediment load is Pearson Type Three(PE3)and Generalized Normal(GNO),respectively,and the best fit for the combined distribution of the two variables is the Frank copula function.The synchronous probability of water and sediment occurrence is 0.459,and the asynchronous probability is0.541.Based on the copula prediction model,the sediment load can be effectively simulated,and the correlation coefficient between the simulated sequence and the measured sequence reached 0.93.The current study provides important significance for the analysis of water and sediment in the JRB,which is beneficial to the management of Three Gorges Reservoir sediment discharge in the upstream and downstream.Haoyu Jin Xiaohong Chen Ruida Zhong Yingjie Pan Tongtiegang Zhao Zhiyong Liu Xinjun Tu 2022International Journal of Sediment Research2022,37,5:0
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