A water quality assessment model is built based on projection pursuit technique. A great quantity of sample data is applied to increase the model's precision. A new genetic algorithm combined with conditional optimization method is proposed and applied to the model optimization, which can deal with global optimization problem with various restrictions effectively. The case study shows that this model can give appropriate assessment of water quality. And more important, it can determine the index weights in an objective way or in the way of taking decision makers' bias into account, which is difficult in other assessment methods.