| Most parts of our country is affected by the monsoon climate,the uneven distribution of precipitation in time and space,prone to flood disasters,with global warming,coupled with the construction of urban drainage facilities for a long time,the flood control standards in some cities are too low,the underlying surface of the hard area increases and other reasons,resulting in the frequency and severity of urban waterlogging is increasingly upgraded,has become an important bottleneck restricting China’s economic and social development.Therefore,how to scientifically quantify the risk of urban rainstorm disaster,and how to conduct pre-disaster prevention and comprehensive disaster reduction according to the existing weak links of the city has become one of the key issues to be solved urgently.To solve the problem of urban waterlogging,the concept and construction model of sponge city came into being.Although China’s sponge city construction has been promoted since 2015,it is mostly concentrated on the engineering construction level,and there is still a lack of quantitative evaluation research on its construction combined with modern information technology.This paper takes the national Sponge City Construction Demonstration Zone of Beijing City Subcenter as the research area,and the basis of in-depth investigation of sponge city construction planning,summarizes and classifies the sponge city construction data,and builds a sponge city construction database.Using machine learning technology,5 primary indexes and 15 secondary indexes of water resources,water environment,water ecology,water management and water security were proposed and determined.Combined with the proposed comprehensive index evaluation model based on game theory,the subjective empowerment(SW)and objective empowerment(OW)methods were used to identify the contribution of each index,establish the sponge city construction evaluation index system,and then put forward the sponge city construction evaluation method coupled with machine learning comprehensively and quantitatively.According to the water security index,the urban rainstorm waterlogging model(SWMM-CCHE)was developed to quantitatively analyze the construction effect of sponge city.Specific strategies and suggestions are put forward for the optimization of sponge city construction from online monitoring-evaluation-control platform,organizational management mode and construction system.In this paper,the sponge city construction evaluation method based on coupled machine learning is used to quantitatively evaluate the construction effect of Beijing city sub-center sponge city.The concrete conclusion is that the comprehensive score of Beijing sub-center sponge city construction is 71.01,which is in the "medium" grade and developing to the "good" grade.The level of water safety and water management construction is high,98.02 and 84.92 respectively,which has basically met the construction requirements;However,the scores of water ecology and water environment were lower,77.35 and 71.05 respectively,so it is still necessary to strengthen construction and management.The utilization of water resources,especially rainwater resources(20 points),is relatively weak and needs continuous optimization and improvement.In this paper,numerical model technique is used to discuss the reduction effect of low impact development measures(LID)on runoff under different recurrence periods of designed heavy rainfall.The depth of waterlogging water and the number of waterlogging points are the greatest under the condition of rainstorm once in 5 years.At the same time,compared with permeable pavement and green space,the biological retention pond has a better effect on reducing runoff,especially under the condition of100 years,the runoff reduction rate can reach 28.4%.In this paper,taking Beijing City Sub-center as an example,the quantitative evaluation,model research and other aspects of sponge city construction are carried out,which can provide certain reference for sponge city construction. |
PDF Full Text Request