To explore the relationship between landscape patterns and water quality at different spatial and temporal scales, we choose the Yellow River Basin as the research object. Based on the data of river water quality and land use in 2018, the three spatial scales (1000 m reach buffer, 500 m riparian corridor buffer, and catchment) of the landscape pattern were extract, combined with four seasons of water quality, using redundancy analysis to quantitatively explore the impact of landscape pattern on water quality at multiple spatial and temporal scales, to obtain the most effective scales for water quality management. The results showed that: (1) Under the three spatial scales, the proportion of farmland and grassland was the largest. The value of patch density (PD) was larger in reach scale, while the Shannon diversity index (SHDI) varied little at the three scales, and the spatial distribution was relatively balanced. (2) There were significant differences in seasons and spatial scales of water quality indicators, and water quality in the summer was better than that in the winter. (3) The landscape pattern had the most significant impact on water quality in the summer and the reach scale. (4) Different landscapes had different impact on water quality. That is, farmland, forest, unused land and PD were the most significant influence on water quality. Except for the increase in farmland and PD value, which will lead to a decline in water quality, other land use indices can improve water quality at most temporal and spatial scales. The relationship between landscape pattern and water quality was quantitatively studied based on different scales, which provides references for optimizing landscape pattern and rational planning of land use, to protect water quality safety in the river basin.