Abstract
Changes in land use and landscape patterns constitute prominent contributors to the degradation of river water quality. The granularity of land use data resolution plays a pivotal role in delineating the spatial distribution of land use within a catchment area. Despite its significance, scant attention has been devoted to investigating the impact of land use data resolution on the interplay between catchment landscape patterns and river water quality. Employing the Yong'an River Basin in eastern China as a case study, this research leverages land use and water quality change data spanning from 1980 to 2020 to scrutinize the influence of watershed landscape patterns on changes in river water quality across varying land use resolutions (30m, 100m, 300m, 500m, 1000m). The findings reveal that alterations in the landscape pattern of grassland, urban land, rural residential land, and paddy fields significantly shape changes in river water quality within the study area. Moreover, the explanatory power of catchment landscape patterns for variations in river water quality varies under distinct data resolutions, with the highest interpretation rate observed at the 300m resolution (88.2%) and the lowest at the 1000m resolution (87.7%). The interpretation rate exhibits an initial ascent followed by a descent as data resolution decreases. Further analysis elucidates that data resolution influences the responsiveness of the landscape index to river water quality by impacting the fitting accuracy of said index. Notably, the 300m resolution exhibits superior fitting accuracy. The degree of grassland fragmentation and the concentration of construction land, along with the fragmentation and area of paddy fields, emerge as pivotal landscape factors influencing changes in river water quality within the study area. Hence, adopting an appropriate land use resolution can mitigate the impact of data redundancy and facilitate a more nuanced exploration of the driving forces behind variations in river water quality.
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