Abstract
The identification and determination of the main influencing factors of lake salinity play a key role in the control measures and suggestions to prevent lake pollution. To ascertain the salinity status, its evolutionary trend in WL, and its impact on the lake, data describing water quality and the 10 major influencing factors for the period 2003–2012 were employed to analyze the evolutionary process and trend characteristics of the main factors affecting upper irrigation and drainage. The principal component analysis (PCA) method was used to identify the key influencing factors of the salinity of the lake; then, regression analysis was combined with PCA modeling to predict the salinity. Results showed that using a multivariate statistical technique is an effective and objective method for identifying the main influencing factors of salinity in WL, which can provide a scientific basis for the pollution control and environmental management of WL.
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