A simplified method based on fuzzy set theory is presented to incorporate uncertainty of parameters into a dynamic total phosphorus model. Uncertainty may arise from difference between calibrated conditions and projected condition as well as from inconsistency of available data in the literature. The uncertainty in parameters was represented by fuzzy numbers that can be generated through various ways such as model calibration process, soft interpretation of literature data, and subjective opinions of experts. The proposed fuzzy approach decomposed fuzzy parameters into interval numbers at different α level cuts, and solved for interval solutions through very simple calculation instead of solving nonlinear programming models. The interval solutions at each α level cut were could be combined to obtain fuzzy solutions. This method has been applied to the phosphorus load-response model of the Triadelphia Reservoir near the Washington, DC area. Two pollution control scenarios have been simulated with fuzzy parameters. The measures of necessity and possibility have been used to analyze the potential risk of the two scenarios. The research results indicated that uncertainty is a very important factor in water quality modeling. By incorporating uncertainty into model framework, the fuzzy model identified the highly risky scenario that was considered preferable based on solutions of the deterministic model.