Quantifying the impact of human activities on water quality based on spatialization of social data: a case study of the Pingzhai Reservoir Basin

Abstract

Abstract In water pollution source research, it is difficult to quantify the impact of human activities on water quality. Based on pollution load theory and the concept of spatialization of social data, this study integrates land-use type, slope gradient, and spatial position, and uses the contribution of human activities to quantify the impact of farmland fertilizers, livestock and poultry wastes, and human domestic pollution on water quality in the study area. The results show that livestock manure is the largest source of total phosphorus (TP) and total nitrogen (TN) discharges in the research area, and domestic pollution is the largest source of chemical oxygen demand (COD) discharges. The total equal standard pollution load (as well as the load of each pollution source and its pollutant amount) is the highest in the Nayong River Basin and the lowest in the Baishui River Basin. The contributions of human activities to TP and TN have similar spatial distributions. The impact of human activities on COD discharge is minimal. The quantitative results of this model are basically consistent with the actual conditions in the Pingzhai Reservoir Basin, which suggests that the model reasonably reflects the impact of human activities on the water environment of the basin.