This paper focuses on several key issues of a BP neural network when it is applied to the comprehensive evaluation of water conservancy in a state of relative prosperity. Based on the analytic hierarchy process(AHP), 30 representative indicators were selected out of more than 100 water conservancy indicators, in order to build up a comprehensive evaluation system of water conservancy in a state of relative prosperity and grading standards as well. In practical application, the BP neural network has shortcomings, including the slow convergence and likely occurrence of local extreme values. To overcome these shortcomings, an LM-BP neural network model was established for comprehensive evaluation of water conservancy in a state of relative prosperity. In this case, training and testing samples were generated between standard thresholds using the random interpolation method. A concept of network fitness is proposed as well. The performance of the proposed model was evaluated using the network fitness, the average relative error, and three other statistical indicators. After the evaluation of the model achieved the expected accuracy and generalization ability, it was applied to the comprehensive evaluation of water conservancy in a state of relative prosperity in Wenshan Zhuang and Miao Autonomous Prefecture, and compared with traditional BP and RBF models. The results are as follows: (a)In both the training samples and testing samples, the LM-BP model had higher evaluation accuracy than traditional BP and RBF models by nearly an order of magnitude, indicating that the LM-BP model has high accuracy and generalization capability and is applicable to the comprehensive evaluation of water conservancy in a state of relative prosperity in Wenshan Zhuang and Miao Autonomous Prefecture. In addition, the LM-BP model has the advantages of fast convergence and a high degree of stability. (b)In the year 2010, water conservancy in a state of relative prosperity in Wenshan Zhuang and Miao Autonomous Prefecture and county-level administrative districts was at level I to II, the initial stages. It will reach level III in the year 2020 according to the prediction, which means that the water conservancy in the whole prefecture will basically achieve a state of relative prosperity.