Abstract: Abstract: Influences of land use types and landscape pattern indexes on the water quality of ponds were explored here in southern Jiangsu of China, particularly for the environmental protection of rural water under the background of rapid urbanization. Taking 42 rural ponds in Sunan District as the research object, the water sample was collected for the land use data in July 2019 and September 2020. Some parameters were selected as the feature condition for the water quality of ponds, including the potential of Hydrogen (pH), electrical Conductivity (COND, μs/cm), Dissolved Oxygen (DO, mg/L), Phosphate (TDP, mg/L), and ammonia nitrogen (NH3-N, mg/L). Firstly, Fragstats 4.2 software was used to calculate the landscape pattern indexes. The comprehensive pollution index and pollution load ratio index were then calculated on the basis of the divided watershed. At last, Spearman correction and Redundancy Analysis (RDA) were thus combined to initially explore the impacts of land use and landscape pattern on the water quality. The results showed: 1) There was a great difference in the water quality of rural ponds in Sunan District. Specifically, there was an increasing trend of COND and NH3-N, a decreasing trend of TDP, while a trend of decreasing first and then increasing for the DO from north to south in the study area. The southern region was more polluted, indicating the most serious DO pollution. The intensity of land use was relatively high in the buffer zones at different scales. The cultivated land and construction land were dominant with an average ratio of 57.34%-73.19%. 2) The water quality varied significantly in the land use types. A positive correlation was obtained on the construction land with NH3-N and DO, whereas, a negative correlation with TDP and COND. A significant positive correlation was observed on the cultivated land with COND and NH3-N, particularly on the 200m and 400-500m scale with TDP. A certain positive effect was achieved on the woodland and grassland with the water quality purification, where a more obvious correlation was found on the 200m scale. 3) In the correlation analysis, Largest Patch Index (LPI) and Aggregation Index (AI) at 100m scale were significantly negatively correlated with COND and NH3-N, whereas, Landscape Shape Index (LSI) and Patch Division Index (DIVISION) at 100m scale were significantly positively correlated with COND and NH3-N. In the redundancy analysis, the cumulative percentage of the first sort axis (constraint axis) was 94.4% within the 100m buffer zone, and the correlation coefficient was 53.3%, indicating a better relationship between water quality and landscape pattern. 4) LPI, LSI, DIVISION, Patch Cohesion Index (COHESION) , and AI presented the most obvious relationship with the water quality characteristics. The findings can provide a sound reference for decision-making in land use planning.