［Objective］This study aimed to investigate the response of water quality to land use and landscape patterns at different scales during the flood and non-flood seasons in the Taihu Basin.［Methods］Based on water quality data from 31 monitoring sites in the Jiangsu section of the Taihu basin from 2020 to 2023 and land use data in 2020，six water quality and pollution indicators were selected，including potassium permanganate，dissolved oxygen，ammonia nitrogen，total phosphorus，total nitrogen，and turbidity. Then land use and landscape pattern characteristics within multi-scale circular buffer zones（100，300，500，1 000，1 500 and 2 000 m）were extracted. Finally，redundancy analysis was employed to determine the optimal spatial scale and key influencing factors that explain water quality during the flood and non-flood seasons.［Results］Water quality was generally better during the flood season than during the non-flood season. However，dissolved oxygen levels were significantly higher in the non-flood season than in the flood season（p<0.05）. The spatial distribution of water quality within the study area revealed relatively good water quality in and around Taihu Lake，while water quality was relatively poor in the eastern and southern regions. This spatial variation in water quality was likely associated with the region's uneven economic development，which was characterized by "higher in the south and lower in the north，stronger in the east and weaker in the west". The 300-m buffer zone explained the strongest relationship between landscape metrics and water quality during both the flood and non-flood seasons，with the explanation rate for the flood season reaching 55.9%. The aggregation index of construction land，the percentage and division of farmland at the class level，along with Shannon's diversity index and edge density at the landscape level，were the principal factors influencing water quality in the Jiangsu section of the Taihu basin. Within the optimal 300-m buffer zone，the mean patch area，the aggregation index of construction land，and the percentage of farmland were negatively correlated with water quality and pollution indicators，including potassium permanganate，total nitrogen，total phosphorus， and turbidity. This suggests that more fragmented landscape，more dispersed patches of construction land，and the absence of dominant farmland patches，are associated with the deterioration of water quality.［Conclusion］The findings of this research provide theoretical support for the scientific formulation of land use planning and landscape pattern optimization strategies，thereby enhancing the scientific basis and precision of water quality management. In particular， the implementation of dynamic regulatory measures under varying seasonal conditions can significantly improve water quality.