Optimization Configuration Of Low Impact Development Practices For The Control Of Urban Non-Point Source Pollution Under Uncertainty

With the rapid development of urbanization,urban non-point source(NPS)pollution has become an urgent issue that need to be addressed in the current urban development process,as it hinders sustainable development of cities.Environmental problems such as water eutrophication caused by urban NPS pollution not only affect urban ecological environment,but also threat human health.However,the evaluation and management systems of urban NPS pollution are subject to multiple uncertain factors,such as interval and stochastic information,which seriously affect the control of urban NPS pollution and the implementation of low impact development(LID)practices.Therefore,an uncertainty optimization configuration model of LID practices for controlling urban NPS pollution can provide methodological support for city decision-makers in controlling urban NPS pollution and optimizing LID practices under multiple uncertain characteristics.In this study,an uncertainty optimization configuration model for urban NPS pollution was developed,which combines SWMM model,Monte Carlo simulation,interval linear programming,and double-sided chance-constrained programming.The proposed model can evaluate the export loads of urban NPS pollution and the pollution reduction efficiency of LID practices,and analyze its corresponding uncertain characteristics.Simultaneously,the model can provide reliable and optimal implementation schemes for LID practices under different scenarios,effectively addressing uncertain characteristics in the management process of urban NPS pollution.The case study was conducted in the Songshan Lake Campus of Dongguan University of Technology in Dongguan City,China.The main work and research achievements are summarized as follows:(1)Evaluate the export load of urban NPS pollution and analyze the corresponding uncertain characteristics.The data of the study area was collected to build the SWMM model.Based on the model,the export loads of urban NPS pollution were simulated.The uncertain characteristics of the model parameters were obtained by the modified Morris screening method and Monte Carlo simulation.Stochastic uncertain characteristics of export loads of urban NPS pollution were obtained.The results showed that the ranges of pollution load of total suspended solids,chemical oxygen demand,total nitrogen,and total phosphorus were76430-165698 kg,44366-74155 kg,2118-3830 kg,and 97-177 kg in 2021,respectively.The mean values of the output load of the four pollutants were 105505 kg,58190 kg,2913 kg and138 kg,and standard deviation were 17790 kg,6547 kg,328 kg and 19 kg,respectively.Concurrently,the pollution load in each functional region has significant spatial heterogeneity,which is mainly affected by the area and land use types.(2)Assess the reduction efficiencies of LID practices on urban NPS pollution and analyze the corresponding uncertain characteristics.According to the actual condition of the study area,the appropriate LID practices were selected to control urban NPS pollution.On the basis of the load assessment and uncertainty analysis of urban NPS pollution,the reduction efficiencies of LID practices on urban NPS pollution were evaluated and analyzed through the LID modules of SWMM model and scenario settings.The random distribution characteristics of reduction efficiency of each practice for urban NPS pollution were identified.The results indicated that LID practices could effectively control the output loads of urban NPS pollution.The pollution reduction efficiency of bioretention cells is higher than that of green roof and permeable pavement.Simultaneously,the pollution reduction efficiency of LID practices would increase with increasing implementation areas of LID practices,and would decrease with the increase of rainfall return periods.(3)Develop an uncertainty optimization configuration model for LID practices considering urban NPS pollution control.An interval double-sided chance-constrained programming(IDCCP)model was developed by coupling interval linear programming and double-sided chance-constrained programming.Then,a SWMM-IDCCP model was proposed by integrating SWMM model,Monte Carlo simulation,and IDCCP model.The proposed SWMM-IDCCP model could provide the optimal configuration schemes of LID practices under different pollution reduction targets and significance levels,dealing with uncertainties such as discrete interval and double-sided stochastic parameters in the implementation process of LID practices.The results of the model in the study area showed that the implementation areas of LID practices would increase as pollution reduction targets and significance levels improve.The functional region with more pollution loads should be implemented more LID practices to reduce urban NPS pollution.This study could provide multiple decision-making schemes for decision maker through obtained optimization results of LID practices under different pollution reduction targets and significance levels.The proposed model has great applicability in the control of urban NPS pollution and optimization configuration of LID practices.The model can also provide methodological support for decision-makers.