In this study, water samples were taken from 34 sampling points in the main stream and tributaries of the Ganjiang River in January and July 2015, and the water quality indicators such as electrical conductivity (EC), water chemical ions and the concentrations of inorganic nitrogen were determined. The land use structure in the Ganjiang River Basin was represented by landscape type ratios, and the landscape pattern was represented by landscape indexes, based on the 30 m resolution land use data. The Pearson correlation analysis, Bioenv analysis, Mantle test and variation partitioning analysis (VPA) were used to analyze the impacts of watershed land use structure and landscape pattern on the water quality of the Ganjiang River. The results showed that: (1) The concentrations of Cl^- and Na⁺ were the highest in the upstream, EC, concentrations of Cl^-, Na⁺, K⁺ and Ca²⁺ were the lowest in the middle stream, and EC, concentrations of HCO₃^-, SO₄^2-, Mg²⁺, Ca²⁺ and NO₃^--N were the highest in the downstream. (2) The construction land was the individual land use type that best explained the variations in water quality. Forest land, paddy fields and construction land were the subset of land use types that best explained the variations in water quality. (3) The ENN_MN index was the individual landscape index that best explained the variations in water quality. NP, COHES and ENN_MN were the subset of landscape index that best explained the variations in water quality. (4) In the dry season, the land use structure and landscape pattern accounted for 41.1% and 17.2% of the variance in water quality, respectively; the effect of landscape pattern was totally interacted with land use structure, without an independent contribution. In the wet season, the land use structure and landscape pattern accounted for 51% and 53% of the variance in water quality, respectively; the interactive part was 37%. Both land use structure and the landscape pattern have a great influence on water quality of Ganjiang River, and their interactive parts play an important role in this influence. The influence of landscape pattern on water quality in dry season was included in the interaction with land use structure.