Identification of surface water quality pollution areas and pollution sources based on spatial clustering and random forest in Henan, China

Abstract

Abstract Maintaining good surface water quality is essential to protecting ecosystems and human health, and different targeted measures for different polluted areas are an effective way to maintain good water quality. This paper takes Henan as an example to study the spatial dependence of surface water quality and explore its spatial clustering pattern, and find out the main driving factors affecting the water quality and analyze the sources of heavily polluted areas by random forest. The results indicate that the spatial pollution pattern of surface water quality in Henan Province can be roughly categorized as insignificant pollution in the northern part, heavy pollution in the central part, and light pollution in the southern part. The heavily polluted areas are mainly located in Zhengzhou, Luoyang and Kaifeng cities. The main indicators affecting water quality in heavily polluted areas are NH3-N, CODMn and TP. The main causes of the deterioration in the region are urban sewage and industrial wastewater discharges. The results not only provide a scientific basis for the systematic management of surface water quality pollution in Henan Province, but also provide a new method for regional water pollution management.