Exploring the Influences of Stream Network Structure and Connectivity on Water Environment Risk in China

Abstract

Stream networks are the transportation channels of pollutants that can significantly influence water environment risk (WER). However, the influences of stream network structure and connectivity (SC) on WER at the national scale and its regional variability have been rarely investigated in China. In this study, the WER was assessed from the grey water footprint of nitrogen and phosphorus in 214 catchments in China. The relationship between WER and SC and its regional variability were analyzed using correlation and grey relational analysis. Results showed that the water environment risk index (RI) in some catchments located in the Hai and Liao River Basins was the highest in China (RI > 0.8). On national scale, longitudinal connectivity (Cl) and cyclical connectivity (Cc) had the strongest influences on WER with grey relational degree index (GRAI) of 0.68 and 0.67, respectively. The average slope (Sr) was the most important in humid zones, whereas Cl and water surface ratio (Rw) had a stronger influence in arid zones. In zones with intensive human activities, Cc, river density (Rd), and the node connection ratio (Rnc) mostly affected WER. The main influenced factors varied significantly among nationwide and different zones, which indicated that climate and human activities played an important role in the spatial variation of the relationship between WER and SC. This study highlights the important role of SC on WER and that the relationship between WER and SC varies with climate and human activities.

Keywords

• water environment risk
• stream network structure and connectivity
• regional variability
• climate
• human activity intensity
• grey relational analysis