Incorporating a new landscape intensity indicator into landscape metrics to better understand controls of water quality and optimal width of riparian buffer zone

Abstract

River water quality plays a crucial role in numerous industries, necessitating the precise delineation of riparian buffer zones and the implementation of comprehensive management measures to preserve water quality. Determining the optimal riparian buffer zone through the impact of landscape metrics on water quality has been widely applied to river management. However, failure to differentiate the same indicators in areas with different anthropogenic activities could lead to inaccuracies in identifying the optimal riparian buffer zone, particularly in regions with notable gradient in anthropogenic activities. Here, we incorporated a new landscape intensity (NLI) indicator into the landscape metrics to better understand controls of water quality and optimal width of riparian buffer zone, considering the differences between areas with different anthropogenic activities. Based on water quality monitoring data from June 2010 to April 2013 in a typical agricultural-urban gradient with different anthropogenic activities, we adopted redundancy analysis (RDA) to quantify the spatial scale effects and seasonal dependence of various landscape metrics impact on river water quality, and then to reveal the importance of landscape metrics in explaining water quality by variance partitioning analysis (VPA). Results showed that landscape metrics were more effective at explaining the water quality variations during the dry season than the wet season (56.48% ∼ 68.99% vs 53.28% ∼ 58.91%). The 1000 m riparian buffer zone was found to be optimal for explaining water quality changes during the dry season, while the 200 m riparian buffer zone was optimal during the wet season. In addition, we found that NLI was the most important landscape metric in our study and could explain 26% to 52% of the variation in water quality. This study provides a new insight for developing a landscape metric that considers differences in anthropogenic activities, which can help us to better understand water quality changes and preserve aquatic ecosystems.