Using the Gansu section of the Yellow River Basin as the research object, Fragstats 3.3 software and Pearson correlation analysis method were used to calculate the landscape pattern index of the river buffer zone, analyze the correlation between water quality and landscape pattern indicators, and investigate the factors influencing the water quality of the Yellow River’s main stream and tributaries in Gansu Province. The data included the land use data with the resolution of 30m in 2020, water quality monitoring data, and socio-economic data from 2018 to 2021. The results indicated that:（1）From 2018 to 2021, the water quality of the main stream and tributaries of the Yellow River in Gansu Province were improving, except the Taohe River, where the concentration of water quality indicators was in the increasing trend；however, TN at more than 80% of monitoring sites remained above Class V water quality standards, with significant nitrogen pollution persisting in the Weihe River, Jinghe River, and Zhuanglang River. High concentrations of TN and NH₄⁺-N were mainly distributed in the central and eastern parts of the basin, TP levels were elevated across most areas, and COD was dispersed, with hotspots concentrated in parts of Lanzhou City and central Linxia Hui Autonomous Prefecture.（2）A significant correlation was observed between landscape patterns and water quality indicators. Higher aggregation and connectivity of landscape patches were associated with better water quality, whereas higher levels of fragmentation and dispersion increased the risk of water pollution.（3）Water quality indicators exhibited strong spatial heterogeneity. The driving factor analysis revealed that NH₄⁺-N, TP, permanganate index, and COD were primarily influenced by rural activities, while TN and DO were mainly affected by urban living and industrial production.