Health assessment of small and medium rivers based on GA-BP optimization model

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.