The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data

Abstract

The Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt (UAMLYREB) have experienced rapid and intense urbanization over the past decades with natural ecosystems being converted to impervious surfaces. Thus, impervious surfaces are recognized as critical parameters when considering the effect of urbanization on water quality. While understanding how the threshold of impervious surfaces affects water quality has been a hot topic, there has been little quantitative analysis on how such thresholds change during rapid urbanization periods across large urban areas. To remedy this deficiency, this article made use of remotely-sensed impervious surface area data and in situ water quality monitoring observations for the period 2000 to 2018 to quantitively derive the temporal variation in the thresholds of the percentage of the impervious surface area (PISA) when inferring the relationship between PISA and a set of water quality indicators for a selection of watersheds within the UAMLYREB. We employed segmented regression model to derive the nonlinear relationship between PISA, the water quality indicators, and the PISA-related thresholds. Our results indicate that PISA may be considered a useful water quality indicator over watershed spatial scales. We also found that the threshold effects differed between water quality indicators (DO, CODMn, NH3-N), where, except for NH3-N, the indicators showed a PISA threshold of 30.08 to 42.34%, with slight variations over the study period. These results imply that maintaining PISA to be around 30% in watershed areas may be sufficient to mitigate against water quality degradation during the urbanization process.

Keywords

• Impervious surface
• rapid urbanization
• remote sensing
• segmented regression
• threshold
• water quality