The globalization era characterized by the largely and extensively economic development has delivered positive contributions as well as negative ones like the two opposing sides of the same coin. The larger and massive constructions in urban areas are negatively impacted by the shifting of natural land areas towards residential areas, private offices, business and shopping centers, and others. In further development, this phenomenon has disrupted the ecological balance. Therefore, the impervious cover tends to rise due to the increase of the closure of surface area with cement, asphalt, and waterproof area. In addition, the urbanization issue which is familiar with the urban areas development becomes the main cause of the impervious cover. Indeed, the land covers (impervious cover) generally occur in the urban areas and become its prominent characteristic. Due to its crucial influence, the impervious cover might become an environmental quality indicator toward the water resources quality. Meanwhile, the decline of surface water quality in China has occurred because of urbanization and high-speed of economic development. Consequently, the pollutant plays a significant role in influencing the surface water quality. The phenomenon of land utility shifting prescribes the need to investigate the correlation between the land covers and the water quality. For that purpose, this literature review is conducted by discussing and evaluating various researches. In this study, several statistical methods are discussed, such as correlation analysis, cluster analysis, primary component analysis, linear regression model, effect mixed linear model, exponential model, GWR, GIS, experiment, Anova, Turkey HSD and RDA analysis. The outcome of this literature review is the appearance of three primary variables which performs strong correlation toward the water resource quality. Those factors are the variables of population density, building density and building coverage ratio. In the advanced research, those factors would be observed by applying several methods such as the experiments, the data mapping using GIS and the GWR approach to test the significance of influence of each variable on others. The use of the GWR model in the advanced study is considered appropriate because the sample of experiments would be collected from several different points at various locations.