Water quality evaluation is a key task in water resource management and pollution control. Current evaluation methods are rooted in water quality index, which assesses the water quality based on the exact concentration of various pollutants. However, the interaction between the pollutants and the water environment should also be considered. This paper suggests a new approach, which integrates pollutant interaction with water environment and parameter uncertainty to water quality evaluation. The new approach is compared with traditional methods. Then, an inexact evaluation model, the integrated water quality evaluation model under uncertainty, is established in accordance with the proposed approach, in which catastrophe theory is used to deal with the ambiguous internal mechanism of the interaction between the pollutants and the water environment. As there are significant uncertainties in water quality evaluations, fuzzy random variables are employed to describe the inexact monitoring data. To solve the proposed model, a new algorithm is designed. The model is then applied to an actual case: Lake Chaohu, China. The results are compared between the proposed method and China's current evaluation method (i.e. max-index method). Some brief analysis and discussion are given about the results, which could be helpful in guiding environmental management decision-making.