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Reservoirs play a key role in many infrastructure functions for people like flood control, irrigation, and water supply. In this work, we focused on the water quality evaluation model for Shimen Reservoir. Based on the monthly changes of factors such as pH, nitrate, ammonia nitrogen (NH3-N) and total nitrogen (TN) in 2013 and 2014, the information diffusion theory and fuzzy neural network technology were utilized to evaluate the water quality comprehensively. The probability distribution of these four factors in the reservoir was analysed and the water quality of the reservoir evaluated. The results show its reliability and these two methods can provide a basis for water quality control of Shimen Reservoir. Furthermore, the methods can be universally applied to the analysis and research of water quality in other regions.