Study On Methods Of Rainfall-runoff Simulation Based On Intelligent Calculation

The simulation of rainfall-runoff is an important part of hydrology simulation. So far, the law of the hydrological cycle is still unclear. However, with the strong influence of human actions and land use and land cover change increasing rapidly, it has being becoming more difficult for us to understand it. Furthermore, the data sacristy makes the traditional hydrologic simulation facing the more rigorous challenge. So new theory and methods are being urgently needed for the study on hydrology process simulation. Under these conditions, the hydrologic simulation method based on the intelligent calculation emerges, as the times require. This thesis focuses on employing the intelligent calculation method to simulate the rainfall-runoff simulation and the following four parts are included:(1) At the first of this paper the new situation that the hydrology and water resource is facing and the difficulty that the hydrologic simulation are encountering in our country are analyzed, and the intelligent functions of the humans and the springs up of the artificial intelligence are introduced, then the intelligent calculation's application in hydrologic simulation is summarized.(2) Aimed to the influence that land use and land cover change has had on the hydrologic process, and taking Chao river basin for example, an BP networks model is established to simulate the basin rainfall-runoff process with the land cover factors. Compared with the simulation that didn't consider the factor of land use/land cover, the more accurate simulating result is obtained by the model considering the influence of land use/land cover.(3) Owing to the lack of the big runoff samples in hydrology series, good precision is seldom obtained in the simulation of big flow. To improve this problem, a kind of neural network forecasting model is brought forward. This model rank the runoffs firstly and is based on two runoff taxonomies: the fuzzy C mean and the self-organization mapping. However, when the samples on the border of two sorts choose the local neural network models, they tend to make mistakes. According to this problem, a fuzzy logic selection model based on expert experiences is established.Taking the Wangjia Chang basin for example, the calculation results shows that the simulation precision of neural network model with classification is higher than that of integrated model without classification, and the fuzzy logical selection based on self-organization mapping classification-BP network model has the highest accuracy of all.(4) The hydrologic development requires the continuous introduce of new methods. So this paper attempts to use a newer intelligent technology-genetic programming to establish the rainfall-runoff experiential formula. The data is from the Wangjia Chang basin and results are satisfying, then the new method should be recommended.