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传统的模糊模式识别理论在水质评价中应用时,均为对水质进行5级评价,而当水质指标监测值超出Ⅴ类水质标准时,5级水质评价结果较实际情况偏好,这样使得评价结果与真实情况有较大偏差。针对这一问题,提出一种改进的基于模糊模式识别理论的6级水质评价模型,并以小清河为例,采用该改进的水质评价方法进行水质评价,并将评价结果与单因子评价法和传统的5级模糊综合评价法进行比较,结果表明：改进的水质评价方法既考虑了所有参评指标对水质的综合影响,又考虑了水质指标超出Ⅴ类水质标准的情况,评价结果较接近水质的实际情况。“,”The traditional Fuzzy Pattern Recognition Theory in the application of water quality evaluation is used to making 5-level evaluation to water quality. But when the water quality indicator values exceed class V water quality standard that the evaluation is no longer in line with the actual situation and the result of 5-level water quality evaluation is better than the physical truth. For this issue, this paper introduced an improved 6-level Fuzzy Pattern Recognition Model in water quality and applied this method to the instance of water quality evaluation of Xiaoqing River and compared the result with Single Factor Evaluation Method and water quality evaluation of traditional 5-level Fuzzy Pattern Recognition Theory. The result shows that this improved water quality evaluation method considers the combined influence on water quality of all contestant indexes and the situation when the water quality exceeds class V. So the reflect of the improved water quality evaluation method in this paper is more close to the actual situation of water quality.