Riparian habitat quality as an indicator of land use/land cover effects on riverine water quality

Abstract

Riparian land use/land cover (LULC) plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients. Nevertheless, establishing a direct relationship between water quality and LULC is challenging due to the multi-indicator nature of both factors. Water quality encompasses a multitude of physical, chemical, and biological parameters, while LULC represents a diverse array of land use types. Riparian habitat quality (RHQ) serves as an indicator of LULC. Yet, it remains to be seen whether RHQ can act as a proxy of LULC for assessing the impact of LULC on riverine water quality. This study examines the interplay between RHQ, LULC and water quality, and develops a comprehensive indicator to predict water quality. We measured several water quality parameters, including pH (potential of hydrogen), TN (total nitrogen), TP (total phosphorus), T_water (water temperature), DO (dissolved oxygen), and EC (electrical conductivity) of the Yue and Jinshui Rivers draining to the Han River during 2016, 2017 and 2018. The water quality index (WQI) was further calculated. RHQ is assessed by the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. Our study found noticeable seasonal differences in water quality, with a higher WQI observed in the dry season. The RHQ was strongly correlated with LULC compositions. RHQ positively correlated with WQI, and DO concentration and vegetation land were negatively correlated with T_water, TN, TP, EC, cropland, and construction land. These correlations were stronger in the rainy season. Human-dominated land, such as construction land and cropland, significantly contributed to water quality degradation, whereas vegetation promoted water quality. Regression models showed that the RHQ explained variations in WQI better than LULC types. Our study concludes that RHQ is a new and comprehensive indicator for predicting the dynamics of riverine water quality.