Assessment of karst water quality and analysis of pollution sources with a projection pursuit algorithm in Jinan spring area, China. Issue 3 (8th February 2022) - Yu, Miao; Xing, Xuerui; Xing, Liting; Zhao, Zhenhua; Li, Changsuo
Abstract: Karst water is one of the main drinking water sources in North China. The single factor method and projection pursuit algorithm (PPA) are employed to assess the karst water quality of the Baotu spring area in Jinan. The water quality distribution pattern, its causes, and the main groundwater pollution sources are analyzed. The water quality evaluation results of the PPA model are more reliable than those of the single factor method because the PPA model comprehensively considers the weight and correlation of various factors. The water quality of the study area is generally excellent, but the NO3 − index content is high. In recent years, the water quality grades have been mainly class II ∼ class IV. The driving factors of water quality evolution are not only human activities, including artificial recharge, but also natural factors, such as carbonate mineral dissolution. These factors control both the distribution and evolution trend of water quality. Urban nonpoint sources have a significant impact on groundwater quality. Based on the current water quality situation, it is urgent to strengthen protection of the ecological environment in the southern recharge area of the spring region and the water quality control in the western region. HIGHLIGHTS: A projection pursuit algorithm model of regional groundwater quality is established, which has good reliability. Anthropogenic activities are the main reason for the deterioration of water quality. Urban nonpoint source pollution has the greatest impact on the current water quality.