Exploring the Spatially Varying Impact of Urbanization on Water Quality in Eastern Massachusetts Using Geographically Weighted Regression

Abstract

The impact of urbanization on water quality might vary over space because watershed characteristics, pollution sources, and land use patterns are not the same in different places. However, the spatially varying impact is usually not considered using conventional statistical methods, such as ordinary least squares regression (OLS) and Spearman’s rank correlation analysis. This study applies a geospatial statistical technique, geographically weighted regression (GWR), to analyze the relationships between urbanization and water quality indicators across watersheds with varied urbanization levels in eastern Massachusetts, USA. The study finds that the relationships between water quality and urbanization indicators vary across the urbanization gradient in the studied watersheds. Percentage of developed land and population density are more strongly related to concentrations of water pollutants in less-urbanized areas than in highly-urbanized areas. The adverse impact of urbanization on water quality is more substantial in less-urbanized suburban areas than highly-urbanized central cities, which is associated with the dominant pattern of urbanization in the study area: urban sprawl. The study suggests that GWR is a useful geospatial technology for policy makers, regional and local agencies, and researchers to unveil the local pollution causes, to improve the understanding of local pollution status, and to adopt appropriate environmental and land use planning policies suitable to the local watershed conservation and management.