It is important to understand the factors influencing the temporal and spatial variability of water quality in order to establish an effective customized management strategy for contaminated aquatic ecosystems. In this study, the spatial diversity of the 5-year (2015 - 2019) average total phosphorus (TP) concentration observed in 40 Total Maximum Daily Loads unit-basins in the Nakdong River watershed was analyzed using 50 predictive variables of watershed characteristics, climate characteristics, land use characteristics, and soil characteristics. Cross-correlation analysis, a two-stage exhaustive search approach, and Bayesian inference were applied to identify predictors that best matched the time-averaged TP. The predictors that were finally identified included watershed altitude, precipitation in fall, precipitation in winter, residential area, public facilities area, paddy field, soil available phosphate, soil magnesium, soil available silicic acid, and soil potassium. Among them, it was found that the most influential factors for the spatial difference of TP were watershed altitude in watershed characteristics, public facilities area in land use characteristics, and soil available silicic acid in soil characteristics. This means that artificial factors have a great influence on the spatial variability of TP. It is expected that the proposed statistical modeling approach can be applied to the identification of major factors affecting the spatial variability of the temporal average state of various water quality parameters.