Study On BP Network And Hydraulic Model With Integrated Drainage Knowledge In Urban Waterlogging Simulation

In recent years, with the acceleration of the country’s urbanization, the urban underground pipelines exposed many problems. Cities such as underground pipeline accidents occur frequently, especially every rainy season, many cities have varying degrees into urban waterlogging, so that the people suffered serious losses of life and property. These issues of urban planning and management present new challenges and requirements. Urban waterlogging problem plaguing many cities, and river flooding is an important feature of urban waterlogging disasters, Therefore, the use of information and data simulation of urban drainage and river water level forecasts, this approach to flood prevention, disaster prevention plans developed great significance.Based on the study of the drainage network hydraulic model and explain the concept and the historical development of the hydraulic model, the drainage network system modeling technology route was proposed, the system completed the establishment of Kunming Area drainage network hydraulic model. Given the high water level and low water level model waterlogging case, the drainage system operation and management Kunming provides reference and basis. Traditional hydraulic model to predict river water level, requires a lot of data, computational complexity and other defects, and therefore can no longer be effective in the short term. This paper uses BP neural network to build river water level prediction model, based on artificial network knowledge, access less data, high accuracy, can simulate Kunming Panlongjiang water levels along the coast under storm conditions well. Added to the overall knowledge of drainage area, you can further improve the accuracy and objectivity of disaster prevention. Analysis and study of urban waterlogging have some assistance, research in this article enhance the scientific study of urban waterlogging.