Correlation between Spatial-Temporal Variation in Landscape Patterns and Surface Water Quality: A Case Study in the Yi River Watershed, China

Abstract

The evidence for a correlation between landscape patterns and surface water quality is still weak. We chose the Yi River watershed in China as a study area. We selected and determined the chemical oxygen demand, ammonia nitrogen, total phosphorus, dissolved oxygen, and electric conductivity to represent the surface water quality. We analyzed the spatial distribution of the surface water quality. Buffer zones with five different radii were built around each sampling site to analyze landscape patterns on different scales. A correlation analysis was completed to examine the influencing rules and the response mechanisms between landscape patterns and surface water quality indicators. The results show that: (1) Different landscape composition types impact the surface water quality differently and increasing the area of forest land can effectively reduce non-point source pollution, (2) an increase in urban area may threaten the surface water quality, and (3) landscape compositional change has a greater influence on surface water quality compared to landscape configurational change. This study provides a scientific foundation for the spatial development of watersheds and outlines a strategy for improving the sustainability of surface water quality and the surrounding environment.