| The rapid urbanization process has resulted in the rapid increase of impermeable underlying surface of the city.Global warming has caused extreme weather to form urban heat island effects and rain island effects,coupled with imperfect urban stormwater drainage systems,resulting in urban waterlogging disasters and deterioration of water quality,which seriously threatens the safety of people's lives and property.To effectively prevent urban waterlogging disasters,control water pollution,and formulate reasonable urban stormwater management measures,we must grasp the temporal and spatial characteristics of rainfall runoff in the context of urbanization.Urban rainwater model is an indispensable key supporting technology for urban stormwater management.Its simulation accuracy has an important impact on the urban waterlogging control and stormwater management measures.The calibration and validation of model parameters is a key step to ensure the veracity and dependability of the model.For the SWMM,there is short of parameter auto-calibration module.The manual calibration has a large workload,low efficiency,subjective influence,and even the result of losing the physical meaning of the parameter.The research puts forward an improved harmony search algorithm and uses MATLAB to write the optimization algorithm program.Based on MatSWMM toolbox,the application interface function of SWMM dynamic link library is extended by C language programming.SWMM automatic parameter calibration is realized by calling SWMM dynamic link library,coupling SWMM and improved harmony search algorithm.Finally,the D area of the second phase of Rongqiao City,Nan'an District,Chongqing City was used as the research object,the validity of the algorithm for calibreting parameters of the model is verified and compared.The main study contents,results and conclusions are as follows:(1)Aiming at the problem that the basic harmony search algorithm has strong dependence on parameters,poor convergence and easy to trap in local optimum,we improved it in two aspects to improve its search optimization ability: The first is to dynamically adjust the parameters in algorithm and weakening the sensitivity of the algorithm to the parameters;The second is to change the generating mechanism of the new harmonic vector when the variables are fine-tuned to improve the local exact search performance of the algorithm and accelerate the convergence speed of the algorithm.In this paper,six classical performance test functions are used to test algorithm performance,and the performance of the improved algorithm is compared.The results show that compared with the basic harmonic search algorithm,the veracity,stability and convergence rate of the improved harmonic search algorithm are superior to that of the basic harmonic search algorithm when processing complex function optimization problems.(2)Based on MatSWMM toolbox,the interface function of SWMM dynamic link library is expanded with C language programming,which not only realizes the reading of input data such as ID,attribute value,statistic value of each element in input file,etc,but also realizes the modification of the parameters in the input file.Based on MATLAB programming,the improved harmony search algorithm and SWMM model are coupled,and the function of adding automatic optimization rate of SWMM parameters to the original function of MatSWMM toolbox is realized.(3)Based on the measured rainfall-runoff data on September 24,2018,the parameters of the SWMM in the study area are determined automatically by using the improved harmony search algorithm before and after.In the process of optimization,the value of objective function which does not satisfy the constraint condition is directly set to a maximum number to eliminate the solution which does not satisfy the constraint and avoid the penalty function.Comparing the simulation results of the improved pre-and post-algorithm,it is found that under the same number of iterations,the objective function values of the basic harmonic search algorithm and the improved harmonic search algorithm are 10.473 and 6.633 respectively,and the calculation precision of the improved algorithm is 36.67% higher than that of the pre-improved algorithm.The parameter calibration results of the improved harmonic search algorithm are selected and the stability of the model is verified by using two measured rainfall runoff data of different intensities.The results show that under the rainfall series used for the constant rate,the stability of the model is verified.Through parameter optimization,the simulation results of model are well matched with the monitoring data,and the Nash efficiency coefficient is 0.969,the simulated peak flow is 24.237 L / s,the measured peak flow is 23.101 L / s,and the peak time is the same.The relative percentage error of peak flow is 4.91%;Under the two rainfall sequence used for verification,the simulation results of the model after parameter optimization are consistent with the overall trend of monitoring data,and the monitoring values are in good agreement with the simulated values.The Nash efficiency coefficients are 0.843 and 0.91 respectively,and the relative percentages of peak flow are 9.31% and 9.95% respectively,which meet the evaluation index,indicating that the veracity and stability of the optimization model is better. |
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