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Abstract Surface water quality has a vital role in determining the ecological environment, public health, and social and economic development. This study analyzed the spatial and seasonal differences in surface water quality in the Dan River basin based on three monitoring sections over the period of 2009–2015. The main influencing factors and their contributions to water quality in different seasons were determined using statistical analysis, Hurst exponent and redundancy analysis. Results indicated that vegetation coverage in the Dan River basin increased substantially from 2009 to 2015, particularly forested land. Higher concentrations of major water pollution indicators were recorded in the downstream monitoring sites. Nitrate nitrogen (NN) and total phosphorus (TP) made the largest contributions to the pollution of water quality and indicated spatial and seasonal changes. Lower NN concentrations were more frequent during the summer, whereas TP concentrations were higher during the spring. Thus, the factor making the largest contribution to water quality varied with the season. The contribution of the normalized difference vegetation index (NDVI) to water quality gradually decreased from spring to winter, whereas contributions of land use to water quality gradually increased from spring to winter. Analyses of landscape metrics suggested that patch connectivity was the primary factor influencing water quality in the different seasons. Water level was the main hydrological parameter impacting stream water quality. These results suggested that seasonal differences in the major factors influencing water quality should be taken into account for effective water management. Highlights • The time series of vegetation coverage was a consistent sequence in Dan River. • Factors making the largest contribution to water quality varied with the season. • Patch connectivity was the primary factor influencing water quality. • Water level was the main hydrological parameter impacting stream water quality. [ABSTRACT FROM AUTHOR]