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In order to correct the bias produced by the evaluation result under the correlated criteria, we use the PCA method to eliminate the correlation that exists in the original criterion system. According to the principle that the contribution ratio of accumulative variance should be greater than 90%, we obtain two principal components, the first principal component Y1 and the second principal component Y2. The contribution ratio of accumulative variance reaches 96.7%, indicating that the two principal components preserve most of the information included in the original criterion system. As shown in Table 5, we obtain the loading matrix by varimax orthogonal rotation, and identify the meaning of the two principal components. Table 5 shows that the first principal component is highly correlated to the criteria that are used to assess the status of Shuangjiangkou reservoir (i.e., Zmax1, Ze1, Rv1), the criteria that are used to assess the status of Houziyan reservoir (i.e., Zmax2, Ze2, Rv2), and the criteria that are used to assess the status of Leshan city (i.e., T, W); the second principal component is highly correlated to the criteria that are used to assess the status of Pubugou reservoir (i.e., Zmax3, Ze3, Rv3) and Qmax.

Table 5

Loading matrix of the principal components

Principal component no.Zmax1Ze1Rv1Zmax2Ze2Rv2Zmax3Ze3Rv3QmaxTW
Y1 −0.99 −0.99 −0.99 0.99 0.99 0.99 0.02 −0.08 0.02 0.39 0.85 0.71 
Y2 −0.05 −0.05 −0.05 0.05 0.05 0.05 0.98 0.99 0.98 0.87 0.16 0.55 
Principal component no.Zmax1Ze1Rv1Zmax2Ze2Rv2Zmax3Ze3Rv3QmaxTW
Y1 −0.99 −0.99 −0.99 0.99 0.99 0.99 0.02 −0.08 0.02 0.39 0.85 0.71 
Y2 −0.05 −0.05 −0.05 0.05 0.05 0.05 0.98 0.99 0.98 0.87 0.16 0.55 

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