Research On Optimization Of Rainwater Retention Via Hydraulic Model

In recent years, with the acceleration of urbanization in our country and the change of global climate, the urban extreme waterlogging disasters occur frequently, so frequent and serious urban waterlogging disasters that have caused a huge impact on people’s life security and the development of society and economy.Rainwater rentention as a low impact development facility can effectively cut down the peak flow to reduce the risk of urban waterlogging. So far, domestic and foreign researchs are focused on the role of rainwater retention to control non-point source pollution and the methods to design it. This paper is amied to study the optimal location and design parameters of rainwater retention based on the consideration of the cost of rainwater retention and the risk of urban waterlogging via the hydraulic model of urban drainage network, the main contents of this paper can be divided into three parts.Firstly,this paper studies the modeling of ubran drainage network. This paper introduces the thoery of ubran drainage network model, and focuses on studying the basic principles of SWMM model. As an important input parameter of urban drainage network model——storm intensity formula, the methods of deriving storm intensity formula are being researched, the different methods of adjusting the the frequency distribution curve based on different criteria of curve fitting demonstrate that the criterion of curve fitting based on rainfall intensity residuals minimum can achieve a better curve fitting result; The research on the calculation of the parameters of the storm intensity formula was studied based on an improved Gauss-Newton method, and contrasted with the particle swarm optimization algorithm(PSO) and real-coded genetic optimization algorithm(RCGA), the results show that this method has a higher accuracy. Based on the storm intensity formula we drove, the hydraulic model of the urban drainage network of a district in W city is established using SWMM software.Secondly, this paper studies the multi-objective evolutionary algorithm NSGAII. Based on the master-slave model a parallel NSGA-II is proposed, and some basic multi-objective optimization problems are used to test this new algorithm, the results show that the proposed algorithm is a fast and efficient algorithm.At last,this paper studies the optimization of rainwater retention. In this paper, based on the SWMM model and the optimization problem, the API functions of SWMM model is expanded that 11 external interface functions are developed. Taking the position and design parameters of retention as the decision variables,the cost of retention, the total overflow of flooding nodes and the number of flooding nodes as the objective functions establishes a multi-objective optimization model of rainwater retention. The conclusions are drawn by solving the optimization model via parallel NSGA-II. Results show that the space distribution of optimal solutions(the locations of rainwater retention) is consistent with the spatial distribution of urban waterlogging points; At the same time, the optimal solutions located at different positions have different interference effects on two hydraulic goals that shows an obvious transition rule from upstream to downstream, the optimal solutions located at upstream and midstream has more advantages to reduce the number of flooding nodes, and the optimal solutions located at downstream has more advantages to reduce the total overflow of flooding nodes.