Influences of landscape pattern on water quality at multiple scales in an agricultural basin of western China

Abstract

Determining the associations between landscape pattern and river water quality and quantifying the abrupt change points of landscape metrics are vital to optimize landscape planning and improve basin water quality. This study took an agricultural basin in western China as a case study. River water quality of 61 sub-basin outlets were monitored during wet and dry seasons from 2020 to 2021. Landscape metrics were extracted at 100 m, 300 m, 500 m riparian buffer and sub-basin scales, respectively. Relationships between water quality and landscape pattern at multiple scales were explored by using redundancy analysis (RDA). Results showed that urban-related landscape metrics served as the primary contributor to degrade water quality during both seasons, followed by cropland-related metrics, which might be attributed to the increase of urban land and reduction of agricultural chemical fertilizer use. Landscape metrics could better explain the water quality variations during wet season than dry season. The explanatory abilities of landscape metrics to overall water quality appeared little difference among spatial scales during wet season, whereas landscape metrics within 100 m riparian buffer had much larger explanatory rate than other spatial scales during dry season. Results of abrupt change point analysis revealed that the abrupt change interval values (ACIVs) of percentage of urban land (PLANDurban) and the largest patch index of urban land (LPIurban) differed among COD, TN, and TP. The recommended threshold values of PLANDurban and LPIurban for COD, TN, and TP management were smaller than 11.0%, 2.5%, and 1.0%, respectively. When the PLANDurban or LPIurban exceeded 19.0%, the TN, TP, and COD pollution would all significantly accelerate. Therefore, a limit value of 19% of PLANDurban and LPIurban, respectively is put forward. From dry season to wet season, the ACIVs of PLANDurban and LPIurban for COD concentration increased, whereas they decreased for TN and TP concentrations. Our results can provide scientific insights into sustainable landscape planning and effective water quality protection in agricultural basins.