摘要:河流健康评价是河流生态修复的前提和依据，但目前中小河流还缺乏相应的评价标准。为客观评估中小河流健康状况，以桥边河为例，构建了河流水生生物、水环境、水文、形态、社会服务功能5个要素17个指标的健康评价体系，利用遗传算法（GA）优化BP神经网络方法建立GA-BP模型确定其指标权重，采用赋分法进行评价。GA-BP模型输出结果显示，指标权重中水环境指标赋值最大，其次是河流水文指标>河流水生生物指标>河流形态指标>河流社会服务功能指标。通过建立的评价体系对桥边河进行评价，结果表明有3个点健康等级评价为Ⅰ级，3个点评价为Ⅱ级，2个点评价为Ⅲ级。总体来看，桥边河流域基本处于健康状态，上游健康状况明显优于下游，从上游到下游越靠近河口位置，河流的健康状况越差。



Abstract:River health assessment is the premise and basis of river ecological restoration, but up to date there is no corresponding health assessment standard for small and medium-sized rivers. In order to objectively evaluate the health status of small and medium-sized rivers, this paper takes Qiaobian River as an example and constructs a health evaluation system around 5 elements, namely the river aquatic organisms, water environment, hydrology, morphology and social service functions, which contains 17 indexes. Then we capitalize genetic algorithm (GA) to optimize BP neural network method to establish GA-BP model to confirm the weight of these indexes, and use the scoring method to evaluate. According to the output of GA-BP model, the river's water environment has the largest value in the weights of indexes, sequentially followed by river hydrological index, river aquatic organism index, river shape index, and river social service function indicators. The result of evaluating in Qiaobian River through the established evaluation system shows that 3 points of them have a health rating of level I, 3 points are rated level Ⅱ, and 2 points are rated level Ⅲ. Overall, the Qiaobian River is basically in a healthy state, and the health status of the upper reaches of the basin is significantly better than that of the downstream. The closer to the estuary from upstream to downstream, the worse the health of the river is.





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