Urban Stormwater Phosphorus Export Control: Comparing Traditional and Low-impact Development Best Management Practices.

Data from the International Stormwater Best Management Practices (BMP) Database were used to compare the phosphorus (P) control performance of six categories of stormwater BMPs representing traditional systems (stormwater pond, wetland basin, and detention basin) and low-impact development (LID) systems (bioretention cell, grass swale, and grass strip). Machine learning (ML) models were trained to predict the reduction or enrichment factors of surface runoff concentrations and loadings of total P (TP) and soluble reactive P (SRP) for the different categories of BMP systems. Relative to traditional BMPs, LIDs generally enriched TP and SRP concentrations in stormwater surface outflow and yielded poorer P runoff load control. The SRP concentration reduction and enrichment factors of LIDs also tended to be more sensitive to variations in climate and watershed characteristics. That is, LIDs were more likely to enrich surface runoff SRP concentrations in drier climates, when inflow SRP concentrations were low, and for watersheds exhibiting high impervious land cover. Overall, our results imply that stormwater BMPs do not universally attenuate urban P export and that preferentially implementing LIDs over traditional BMPs may increase TP and SRP export to receiving freshwater bodies, hence magnifying eutrophication risks.

Distribution of microplastics in rainfall and their control by a permeable pavement in low-impact development facility.

Microplastics (MPs) released from plastic products in daily life are present in the air and could be transported to freshwater environments along with rain. Recently, low-impact development (LID) facilities, such as permeable pavements, have been used to treat non-point source pollutants, including rainfall runoff. While runoff is treated by LID facilities, the periodic monitoring of MPs in rainfall and the efficiency of removal of MPs through LID facilities have rarely been investigated. Therefore, this case study focused on monitoring MPs in rainwater runoff and permeate from a permeable pavement in Busan, South Korea, thus evaluating the removal efficiency of MPs by a LID system. The initial rainfall runoff and permeate through the LID system were sampled, and the amounts, types, sizes, and shapes of MPs in the samples were analyzed using micro-Fourier Transform Infrared (FTIR) spectroscopy. The results showed that the distribution of MPs in the initial rainfall was affected by population in tested area. Polyethylene was the most common type of MPs in all the samples. Polyamide was only found in the LID samples because of the pollution caused by water flows and pavement materials. Fragment type MPs was most commonly observed and consisted of relatively small-sized (under 100 µm) particles. LID facilities were able to capture approximately 98% of MPs in the rainfall through a filtration process in the permeable pavement.

Performance and uncertainty assessment of green roofs for urban flood reduction in a high-density catchment in Ahmedabad, India.

Urban flooding poses a significant challenge to the rapidly growing Indian cities. Low-impact development strategies such as green roofs have shown the potential to reduce urban flooding. However, their performance assessment significantly varies across different studies. Therefore, the study's primary objective is to evaluate green roofs in the Indian context. For this evaluation, the green roofs are assessed based on building-level implementation scenarios for a high-density urban area in India for 25%,50%, and 75% application rates and different rainfall intensities (2,3 and 4-h duration and 2,5,10 and 25-year frequencies). Secondly, to probe the variations in the green roof performance across studies, uncertainty contributions to the runoff reduction from different parameters are quantified. The results show that green roofs can reduce up to 62% of flood volume and 24% of runoff. However, they are reasonably effective only beyond 25% application rates. Further, rainfall intensity contributes the most to the uncertainty of runoff reduction from green roofs. This uncertainty assessment implies that localized evaluation of green roofs depending on local rainfall conditions is required for city-wide policy planning. The study has a significant contribution to building confidence in the ability of green roofs to reduce urban floods in the context of developing countries like India.

Spatial, temporal, and biological factors influencing plant responses to deicing salt in roadside bioinfiltration basins.

Plants are arguably the most visible components of stormwater bioretention basins and play key roles in stabilizing soils and removing water through transpiration. In regions with cold winters, bioretention basins along roadways can receive considerable quantities of deicing salt, much of which migrates out of the systems prior to the onset of plant growth but the rest remains in the soil. The resulting effects on plants presumably vary with time (due to annual weather patterns), space (because stormwater exposure is location-dependent), and biology (because plant taxa differ in their salt tolerance). The goal of this study was to investigate the magnitude of deicing salt's effects on bioretention plants and how it varies with spatial, temporal, and biological factors. The study took place in a set of five bioretention basins in Philadelphia, USA that receive runoff from a major highway. Over a five-year period, the electrical conductivity (EC) of influent stormwater frequently exceeded 1 mS cm-1 in winter, and occasionally surpassed that of seawater (∼50 mS cm-1). In both of the years when soil EC was measured as well, it remained elevated through all spring months, especially near basin inlets and centers. Mortality of nine plant taxa ranged widely after three years (0-90%), with rankings largely corresponding to salt tolerances. Moreover, leaf areas and/or crown volumes were strongly reduced in proportion to stormwater exposure in seven of these taxa. In the three taxa evaluated for tissue concentrations of 14 potentially toxic elements (Hemerocallis 'Happy Returns', Iris 'Caesar's Brother', and Cornus sericea 'Cardinal'), only sodium consistently exceeded the toxicity limit for salt intolerant plants (500 mg kg-1). However, exceedance of the sodium toxicity limit was associated with plants' topographic positions, with median concentrations greatest in the bottom of basins and least on basin rims. This study demonstrates that deicing salts can have detrimental effects on plants in bioretention basins, with the strongest effects likely to occur in years with the greatest snowfall (and therefore deicing salt use), in portions of basins with greatest stormwater exposure (typically around inlets and centers), and in plants with minimal salinity tolerance. Our results therefore underscore the value of installing salt-tolerant taxa in basins likely to experience any frequency of deicing salt exposure.

Efficiency evaluation of low impact development practices on urban flood risk.

Urban flood risk assessment delivers invaluable information regarding flood management as well as preventing the associated risks in urban areas. The present study prepares a flood risk map and evaluate the practices of low-impact development (LID) intended to decrease the flood risk in Shiraz Municipal District 4, Fars province, Iran. So, this study investigate flood vulnerability using MCDM models and some indices, including population density, building age, socio-economic conditions, floor area ratio, literacy, the elderly population, and the number of building floors to. Then, the map of thematic layers affecting the urban flood hazard, including annual mean rainfall, land use, elevation, slope percentage, curve number, distance from channel, depth of groundwater, and channel density, was prepared in GIS. After conducting a multicollinearity test, data mining models were used to create the urban flood hazard map, and the urban flood risk map was produced using ArcGIS 10.8. The evaluation of vulnerability models was shown through the use of Boolean logic that TOPSIS and VIKOR models were effective in identifying urban flooding vulnerable areas. Data mining models were also evaluated using ROC and precision-recall curves, indicating the accuracy of the RF model. The importance of input variables was measured using Shapley value, which showed that curve number, land use, and elevation were more important in flood hazard modeling. According to the results, 37.8 percent of the area falls into high and very high categories in terms of flooding risk. The study used a stormwater management model (SWMM) to simulate node flooding and provide management scenarios for rainfall events with a return period ranging from 2 to 50 years and five rainstorm events. The use of LID practices in flood management was found to be effective for rainfall events with a return period of less than 10 years, particularly for two-year events. However, the effectiveness of LID practices decreases with an increase in the return period. By applying a combined approach to a region covering approximately 10 percent of the total area of Shiraz Municipal District 4, a reduction of 2-22.8 percent in node flooding was achieved. The analysis of data mining and MCDM models with a physical model revealed that more than 60% of flooded nodes were classified as "high" and "very high" risk categories in the RF-VIKOR and RF-TOPSIS risk models.

A comparative analysis of methods and tools for low impact development (LID) site selection.

The site selection for Low Impact Development (LID) practices is a significant process. It affects the effectiveness of LID in controlling stormwater surface runoff, volume, flow rate, and infiltration. This research paper presents a comprehensive review of various methods used for LID site selection. It starts by introducing different methods and tools. Three main methods: index-based methods, GIS-based multi-criteria decision analysis (MCDA), and multi-criteria models and tools, are discussed in detail. A comparative analysis of these methods is then conducted based on ten different criteria. These criteria include the number of variables, data properties, the scale of analysis, benefits maximization approach, multi-attribute decision analysis, user-friendliness, community and stakeholder participation, and the validation methods. This comparison reveals limitations in each method. These include inadequate data availability and quality, lack of evaluation methods, comprehensive assessment criteria and spatial explicitness. These challenges underscore the need for future research to prioritize spatial clarity, broaden criteria, improve data quality through standardization, incorporate field visits and remote sensing for robust results, integrate big data, and develop web-based, open-source tools for enhanced accessibility. These key strategies provide valuable insights for advancing LID site selection methods.

Enhancing the SWAT model for creating efficient rainwater harvesting and reuse strategies to improve water resources management.

Rain barrels/cisterns are a type of green infrastructure (GI) practice that can help restore urban hydrology. Roof runoff captured and stored by rain barrels/cisterns can serve as a valuable resource for landscape irrigation, which would reduce municipal water usage and decrease runoff that other stormwater infrastructures need to treat. The expected benefits of rainwater harvesting and reuse with rain barrels/cisterns are comprehensive but neither systematically investigated nor well documented. A comprehensive tool is needed to help stakeholders develop efficient strategies to harvest rainwater for landscape irrigation with rain barrels/cisterns. This study further improved the Soil and Water Assessment Tool (SWAT) in simulating urban drainage networks by coupling the Storm Water Management Model (SWMM)'s closed pipe drainage network (CPDN) simulation methods with the SWAT model that was previously improved for simulating the impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns. The newly improved SWAT or SWAT-CPDN was applied to simulate the urban hydrology of the Brentwood watershed (Austin, TX) and evaluate the long-term effects of rainwater harvesting for landscape irrigation with rain barrels/cisterns at the field and watershed scales. The results indicated that the SWAT-CPDN could improve the prediction accuracy of urban hydrology with good performance in simulating discharges (15 min, daily, and monthly), evapotranspiration (monthly), and leaf area index (monthly). The impacts of different scenarios of rainwater harvesting and reuse strategies (rain barrel/cistern sizes, percentages of suitable areas with rain barrels/cisterns implemented, auto landscape irrigation rates, and landscape irrigation starting times) on each indicator (runoff depth, discharge volume, peak runoff, peak discharge, combined sewer overflow-CSO, freshwater demand, and plant growth) at the field or watershed scale varied, providing insights for the long-term multi-functional impacts (stormwater management and rainwater harvesting/reuse) of rainwater harvesting for landscape irrigation with rain barrels/cisterns. The varied rankings of scenarios found for achieving each goal at the field or watershed scale indicated that tradeoffs in rainwater harvesting and reuse strategies exist for various goals, and the strategies should be evaluated individually for different goals to optimize the strategies. Efficient rainwater harvesting and reuse strategies at the field or watershed scale can be created by stakeholders with the assist of the SWAT-CPDN to reduce runoff depth, discharge volume, peak runoff, peak discharge, CSO, and freshwater demand, as well as improve plant growth.

Study on the response analysis of LID hydrological process to rainfall pattern based on framework for dynamic simulation of urban floods.

An in-depth analysis of the urban flood disaster level in response to different rainfall characteristics and Low Impact Development (LID) measures is of significant importance for addressing unfavorable management conditions and implementing effective flood control measures. This study proposes a dynamic urban flood simulation framework based on the Storm Water Management Model (SWMM) and Geographic Information System (GIS) spatial analysis, incorporating an active inundation seed search algorithm. The framework is calibrated and validated using nine historical urban flood events. Subsequently, the impact of rainfall patterns on urban inundation under LID measures is analyzed based on the dynamic urban flood simulation framework. The results show that the urban flood simulation framework exhibits good applicability, with Nash-Sutcliffe Efficiency (NSE) values of 0.825 and 0.763 during the calibration and validation periods, respectively. The extent of inundation shows little variation for rainfall events with a return period greater than 20 years, and the location of flooding is minimally affected by rainfall patterns. LID measures have a decreasing effect on urban inundation control as the return period of rainfall increases, and there are variations in hydrological responses to different rainfall patterns under the same return period. For single-peak rainfall events with the same return period, the control rates of inundation volume, flow, and infiltration decrease as the rainfall peak coefficient increases, indicating a weakening effect of LID measures on flood control with increasing rainfall peak coefficient. Under the same return period conditions, LID measures exhibit the best runoff control effect for uniform rainfall, while their effectiveness is lower for double-peak rainfall events and single-peak rainfall events with an r = 0.75 coefficient. The findings of this study provide a theoretical basis for urban flood warning and management of Low Impact Development measures.

Application of multi-criteria decision-making on low-impact development practice selection for the Kinyerezi River sub-catchments in Dar es Salaam, Tanzania.

The impermeable areas in catchments are proportional to peak flows that result in floods in river reaches where the flow-carrying capacity is inadequate. The high rate of urbanization witnessed in the Kinyerezi River catchment in Dar es Salaam city has been noted to contribute to floods and siltation in the Msimbazi River. The Low-Impact Development (LID) practices that includes bio-retention (BR) ponds, rain barrels (RBs), green roofs (GRs), etc. can be utilized to mitigate portion of the surface runoff. This study aims to propose suitable LID practices and their sizes for mitigating runoff floods in the Kinyerezi River catchment using the Multi-Criteria Decision-Making (MCDM) approach. The results indicated that the BR and RBs were ranked high in capturing the surface runoff while the sediment control fences were observed to be the best in reducing sediments flowing into the BR. The proposed BR ponds were greater than 800 m2 with 1.2 m depth while RB sizes for Kinyerezi and Kisungu secondary schools and Kinyerezi and Kifuru primary schools were 2,730; 2,748; 1,385; and 1,020 m3, respectively. The BR ponds and RBs are capable of promoting water-demanding economic activities such as horticulture, gardening, car washing while reducing the school expenses and runoff generation.

Optimal designs of LID based on LID experiments and SWMM for a small-scale community in Tianjin, north China.

Urban flooding and waterlogging are becoming increasingly serious due to rapid urbanization and climate change. The stormwater management philosophy of low-impact development (LID) has been applied in urban construction to alleviate these problems. The selection and placement of LID designs are the most important tasks. In this study, LID experiments were performed to calibrate the Storm Water Management Model (SWMM). Then, a multi-objective optimization model, which adopted the minimum surface runoff coefficient, surcharge time, and investment cost as objectives, was established by coupling the SWMM and non-dominated sorting genetic algorithm-II (NSGA-II). Hydrological simulations were performed with the SWMM, and optimal calculations were conducted with NSGA-II. Real-coded optimal variables containing detailed size and location information of multiple LID measures were generated, and a decision space for LID design selection was obtained. The optimization designs reduced the surface runoff coefficient from 0.7 to approximately 0.5, the conduit surcharge duration was reduced from 1.62 h to 0.04-0.47 h, and the total investment cost only ranged from 395,000-872,000 ¥. Thus, the optimization model could achieve synchronous optimization of all objectives. This study could provide valuable information for LID design with the aim of urban flooding and waterlogging control.

The potential of multilayer green roofs for stormwater management in urban area under semi-arid Mediterranean climate conditions.

Different low impact development measures have been proposed to make cities more flood-resilient, and recent literature is paying great attention to the evaluation of their direct benefits in terms of flood risk mitigation and the numerous co-benefits that they may offer. This study describes an experimental prototype of a technologically advanced multilayer green roof installed in a Mediterranean urban area (i.e., Palermo, Italy) and explores the results of an analysis of data collected over a one-year monitoring period by a complex sensors network. Multilayer green roofs, or "blue-green" roofs (BGRs), are characterized by a high water retention capacity compared to traditional green roofs due to the presence of an additional storage layer (blue layer), usually equipped with a valve that allows for regulating discharge outflow and water storage. Due to their recent development, BGRs are still scarcely explored in literature and have never been tested before in semi-arid environments, where they could represent valid measures to counter possible climate change and growing urbanization effects. In this study, the hydrological effectiveness of the experimental BGR is quantitatively evaluated by using appropriate indicators, based on the comparison between the hydrological response of the system and an equal size benchmark "grey" roof. The analyses are prevalently focused on the system's stormwater retention function, also investigating the relative contributions of the green layer and the storage layer to the overall retention capacity through the introduction of new BGRs specific indicators. Results emphasize the high impact of storms characteristics, antecedent soil moisture of the green layer, and initial water storage in the blue layer on the system's retention capacity. The overall mean retention rate for the experimental BGR, on average equal to 77% at the daily scale and 61% at the event scale, is comparable to the typical values of traditional extensive green roofs and could be further improved through a "retention-oriented" management of the outflow valve. The system was able to entirely retain almost half of the rainfall events occurred during the monitoring period and, for all the others, it was however extremely effective in reducing runoff peaks and delaying the hydrograph produced.

Influence of landscape patterns on nitrate and particulate organic nitrogen inputs to urban stormwater runoff.

This study investigated the effect of the landscape pattern of permeable/impermeable patches on NO3--N and particulate organic nitrogen (PON) concentrations during stormwater runoff transport and their source contributions. Six landscape pattern indices, namely, mean proximity index (MPI), largest patch index (LPI), mean shape index (MSI), landscape shape index (LSI), connect index (CONNECT), and splitting index (SPLIT), were selected to reflect the fragmentation, complexity, and connectivity of permeable patches in urban catchments. The results show that lower fragmentation, higher complexity, and greater connectivity can reduce NO3--N concentrations in road runoff and drainage flow (i.e., the flow in the stormwater drainage network), as well as PON concentrations in road runoff. Further, the above landscape pattern is effective for mitigating the contributions of NO3--N and PON from road runoff. Low impact development (LID) can be incorporated with the landscape pattern of permeable/impermeable patches to mitigate nitrogen pollution in urban stormwater at the catchment scale by optimizing the spatial arrangement.

Assessing runoff control of low impact development in Hong Kong's dense community with reliable SWMM setup and calibration.

Low impact development (LID) is a sustainable practice to managing urban runoff. However, its effectiveness in densely populated areas with intense rainfall, such as Hong Kong, remains unclear due to limited studies with similar climate conditions and urban patterns. The highly mixed land use and complicated drainage network present challenges for preparing a Storm Water Management Model (SWMM). This study proposed a reliable framework for setting up and calibrating SWMM by integrating multiple automated tools to address these issues. With a validated SWMM, we examined LID's effects on runoff control in a densely built catchment of Hong Kong. A designed full-scale LID implementation can reduce total and peak runoffs by around 35-45% for 2, 10 and 50-year return rainfalls. However, LID alone may not be adequate to handle the runoff in densely built areas of Hong Kong. As the rainfall return period increases, total runoff reduction increases, but peak runoff reduction remains close. Percentages of reduction in total and peak runoffs decline. The marginal control diminishes for total runoff while remaining constant for peak runoff when increasing the extent of LID implementation. In addition, the study identifies the crucial design parameters of LID facilities using global sensitivity analysis. Overall, our study contributes to accelerating the reliable application of SWMM and deepening the understanding of the effectiveness of LID in ensuring water security in densely built urban communities located near the humid-tropical climate zone, such as Hong Kong.

Quantifying and improving flood resilience of urban drainage systems based on socio-ecological criteria.

In this paper, a new framework is developed for evaluating the resilience of urban drainage systems (UDSs) under floods by proposing and quantifying some technical and socio-ecological (SE) criteria. The proposed criteria are used to quantify the seven principles of building resilience in socio-ecological systems. The criteria mainly focus on preserving diversity and multiplicity in a UDS, managing variables that gradually change over time (slow variables), improving structural and functional connectivity, maintaining system adaptability, encouraging learning, broadening participation, and promoting polycentric governance systems. For evaluating the efficiency of the proposed framework, it is applied to a real-world case study of improving resilience of the UDS in the eastern part of Tehran metropolitan area. Three scenarios for flood management are proposed based on the Low Impact Development (LID) practices which are simulated using the Storm Water Management Model (SWMM). The Entropy method is used to consider the uncertainty in the relative importance of different criteria in estimating the flood resilience. The estimated values for the proposed criteria regarding the current drainage system in the study area show its undesirable condition in many sub-catchments. The results also show that using around 2.3 km2 of LID practices in this urban watershed can significantly improve the resilience in many sub-catchments (nearly, 30%) and reduce the total volume of the overflow (about 50%). The results also show that using the flood management scenarios, improving connectivity is the most influential factor that enhances the general resilience of the system.

Simultaneous degradation of sulfadiazine and dissolved organic matter based on low-impact development facilities.

Sulfadiazine (SD) is a common antibiotic administered to treat bacterial infections in livestock, and its fate and migration are greatly affected by dissolved organic matter (DOM). The soil infiltration system [a typical low-impact development (LID) facility] can significantly alter DOM properties during runoff pollution, thus affecting the complexation of SD with DOM. Here, the binding characteristics of different DOM components and SD in the soil infiltration system were explored using spectroscopic techniques (excitation-emission matrices, parallel factor analysis, and synchronous fluorescence spectroscopy). Combined with the weakening of DOM fluorescence intensity and 78.63% reduction in mean SD concentration following treatment, synchronous degradation may have occurred. The binding sequence of SD and DOM fluorophores was further explored using two-dimensional correlation spectroscopy. Effluent DOM showed greater sensitivity to SD and more binding sites than influent DOM. Moreover, hydrophobic protein-like substances exhibited higher log KM values than other fluorescent components, indicating that protein-like components play significant roles in SD complexation. The soil percolation system improved the complexation stability and binding sequence of fulvic-like substances. Thus, SD-DOM can be intercepted and degraded using LID facilities to reduce the risk of SD in aquatic environments.

Runoff control simulation and comprehensive benefit evaluation of low-impact development strategies in a typical cold climate area.

With the acceleration of urbanization, the proportion of surface imperviousness is increasing continuously in cities, resulting in frequent waterlogging disasters. In this context, storm water management, based on the low-impact development (LID) concept, offers an effective measure for the management of urban storm waters. First, the storm water management model (SWMM) was built for a typical cold climate city (Changchun) in China. Next, the two-stage calibrated model was employed to explore the surface runoff and storm sewer control effects of four LID combination plans. Finally, these plans were put through a "cost-benefit" evaluation through an analytic hierarchy process. According to the results, after using four LID plans, the reduction rates of peak runoff exceeded 40% and the problem of overflow load of the storm sewage was significantly mitigated. The infiltration-oriented Plan I proved to be the optimal plan, with the lowest proportions of the overflow nodes and full-load pipe sections in each return period, as well as with maximum overall performance. This study offers technical and conformed methodological support to cold cities for the prevention and control of waterlogging disasters and recycling of rainwater resources.

The optimization of Low Impact Development placement considering life cycle cost using Genetic Algorithm.

Low Impact Development (LID) is an effective measure in controlling the urban runoff and mitigating the non-point source pollution. The determination of LID facilities and layouts for a sub-catchment is important for designing stormwater management system. However, there are remain large uncertainty and challenge exist in determination of LID facilities when consider budget, land use, soil surface and groundwater as well as local climate etc. To address this issue, this study employed Genetic Algorithm (GA) for optimization of the selection and layout of LID. The urban runoff was simulated using Environmental Protection Agency (EPA) Storm Water Management Model (SWMM). The LID planning was encoded as 0 and 1 in GA algorithm. The multiple objectives which include runoff reduction, area of LID and life cycle cost were selected as optimization targets. To test the model performance, the Airport Economic Zone in Tianjin, China was chosen as the study area. The results demonstrate that the combination of LID approaches are most effective measures on runoff reduction through long-term simulation (10 years' rainfall events). The impact of different weights of land area and cost on LID selection were evaluated when considering life cycle cost. Bio-Retention is preferred when considering the area of LID and Green Roof is recommended when the cost is prioritized. The present research proved GA is feasible for LID planning in urban area. The proposed method can help the decision-makers to determine the LID plan more scientific based on SWMM model and GA.

A novel spatial optimization approach for the cost-effectiveness improvement of LID practices based on SWMM-FTC.

Due to the increasingly frequent occurrence of urban waterlogging, the spatial optimization of low impact development (LID) practices has been commonly used to detain and reduce storm water runoff in the most cost-effective way. In this study, the flow transmission chain (FTC) was proposed to replace the routing portion of the Storm Water Management Model (SWMM) and was combined with the runoff component of the SWMM to simulate LID practices (SWMM-FTC). In the SWMM-FTC, the third Evolution Step of Generalized Differential Evolution (GDE3) was employed to optimize the LID layout design. The results showed that the relative error between the modified SWMM-FTC and the calibrated SWMM was less than 0.25% under various LID scenarios, and the computational efficiency of the SWMM-FTC was improved by 19.3 times. Moreover, the GDE3 outperformed the commonly used non-dominated sorting genetic algorithm (NSGA-II), the strength Pareto evolutionary algorithm (SPEA2), and the multi-objective shuffled frog leaping algorithm (MOSFLA) due to its ability to find the most cost-effective solution. The LID layout obtained from the SWMM-FTC with the GDE3 saved $210-1067 to achieve a 1% reduction in storm water runoff. This result demonstrates that the SWMM-FTC with the GDE3 can achieve higher environmental benefits than comparable models, providing better guidance for managers and stakeholders.

Optimal configuration of low impact development practices for the management of urban runoff pollution under uncertainty.

The urbanization process has seen an accelerated increase in recent decades, leading to urban runoff pollution becoming more prominent. However, uncertainty of the pollution output and complexity of management systems have made controlling urban runoff pollution challenging. Therefore, it is necessary to propose advanced modeling methods for these challenges. This research presents an integrated urban runoff pollution management (IURPM) model for optimal configuration of low impact development (LID) practices under multiple uncertainties. The IURPM model combines the hybrid land-use prediction and improved pollution estimation models with interval parameter, stochastic parameter, and multi-objective programming. The proposed IURPM model can not only predict the output characteristics, but also provide optimal configuration schemes for the LID practices in the management of urban runoff pollution under multiple scenarios. In addition, uncertainties expressed as discrete intervals and probability density function in the management systems can be effectively addressed. A case study of the IURPM model was conducted in Dongguan City, South China. Results show that considerable amounts of urban runoff pollutants would export from Dongguan City by 2025. The export loads and pollution output flux per unit area would have significant spatial heterogeneity. The results further indicate that population size, gross domestic product, and regional area size are expected to play important roles in the pollution export, while impervious surface coverage and population density would likely have great influences on the output flux of urban runoff pollution. Based on the model findings, multiple LID practices should be adopted in Dongguan City to reduce the urban runoff pollution loads. Using the IURPM model, multiple LID implementation schemes can be obtained under different pollution reduction scenarios and significance levels, that can provide decision-making support for urban water environmental management, considering variations in the policymaker's decision-making preferences. This study demonstrates that the IURPM model can be applied to the optimal configuration of LID practices for the management of urban runoff pollution under uncertainty.

An integrated framework for the comprehensive evaluation of low impact development strategies.

The impacts of urbanization on water quality, hydrology, society, and the environment can be minimized through low impact development (LID) practices in urban areas. This study has evaluated the performances of seven different LID scenarios including stand-alone and different combinations of green roof (GR), bioretention cells (BC), permeable pavement (PP), and infiltration trench (IT) in the Ayamama watershed, which is one of the most densely urbanized areas in Istanbul. Stormwater Management Model (SWMM) was used to obtain the performances of LID scenarios in quantitative (i.e., volume reduction and peak runoff reduction) and qualitative (i.e., Total Suspended Sediment, Chemical Oxygen Demand, Total Nitrate, Total Phosphate reductions) manner. To calibrate the SWMM model, the Parameter EStimation Tool (PEST) was integrated for sensitivity analysis and parameter optimization. A focus group discussion (FGD) was performed to identify the criteria and LID scenarios applicable to the study area. 16 criteria were determined as suitable, based on three dimensions of sustainability such as social, economic, and environmental. The criteria were evaluated in compliance with the fuzzy analytical hierarchy process (AHP) method before performing technique for order preference by similarity to ideal solution (TOPSIS) for a comprehensive assessment of LID scenarios. The results showed that community resistance, operation feasibility, and quantitative benefits were the most significant criteria for LID scenario selection in social, economic, and environmental aspects, respectively. The integrated evaluation showed that the impacts of urban flooding can be reduced significantly with the combination of GR and BC. Thus, this study provides an integrated and sustainable solution to the topic based on the PEST-SWMM-fuzzy AHP-TOPSIS framework. Furthermore, the developed framework could assist decision-makers and governmental authorities to designate optimal LID scenarios.