Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea: Experimental and modeling approach

Soil properties and functional genes in nitrogen removal process of bioretention

The effects of different soil properties on hydrology and nitrogen removal were studied in a simulated bioretention system. Soil capacity of permeability and water retention, changes in the soil environment, leachate concentrations at the surface and bottom layers, quantification of N removal from soil, microorganism and plant by 15N isotope tracer technique, and functional genes abundance at different depths were evaluated. The results showed that shallow root plants, soil compaction, and low organic matter content were not conducive to the infiltration of bioretention systems. In the 72 h experiment, compaction (especially surface compaction) and planting of herbaceous plants (Ophiopogon japonicus) were not beneficial to the removal of TN, TP, and COD. Adding an appropriate amount of organic matter also affects nitrogen and phosphorus removal. In the process of denitrification, the order of the ability to remove nitrogen is soil adsorption > microbial assimilation > plant uptake. The contribution of soil denitrification is affected by soil compaction, compaction location, plant species and organic matter content. The abundance of 16S rRNA, nitrifying, denitrifying and nrfA genes decreased with soil depth. More copies of genes in topsoil were thought to be due to sufficient nutrients, aerobic condition, anaerobic microsites and submerged state. Soil compaction, organic matter content and plant species affected nitrification, denitrification and DNRA gene characteristics.

Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometry

Urban surface runoff contains chemicals that can negatively affect water quality. Urban runoff studies have determined the transport dynamics of many legacy pollutants. However, less attention has been paid to determining the first-flush effects (FFE) of emerging micropollutants using suspect and non-target screening (SNTS). Therefore, this study employed suspect and non-target analyses using liquid chromatography-high resolution mass spectrometry to detect emerging pollutants in urban receiving waters during stormwater events. Time-interval sampling was used to determine occurrence trends during stormwater events. Suspect screening tentatively identified 65 substances, then, their occurrence trend was grouped using correlation analysis. Non-target peaks were prioritized through hierarchical cluster analysis, focusing on the first flush-concentrated peaks. This approach revealed 38 substances using in silico identification. Simultaneously, substances identified through homologous series observation were evaluated for their observed trends in individual events using network analysis. The results of SNTS were normalized through internal standards to assess the FFE, and the most of tentatively identified substances showed observed FFE. Our findings suggested that diverse pollutants that could not be covered by target screening alone entered urban water through stormwater runoff during the first flush. This study showcases the applicability of the SNTS in evaluating the FFE of urban pollutants, offering insights for first-flush stormwater monitoring and management.

Machine learning parallel system for integrated process-model calibration and accuracy enhancement in sewer-river system

The process-based water system models have been transitioning from single-functional to integrated multi-objective and multi-functional since the worldwide digital upgrade of urban water system management. The proliferation of model complexity results in more significant uncertainty and computational requirements. However, conventional model calibration methods are insufficient in dealing with extensive computational time and limited monitoring samples. Here we introduce a novel machine learning system designed to expedite parameter optimization with limited data and boost efficiency in parameter search. MLPS, termed the machine learning parallel system for fast parameter search of integrated process-based models, aims to enhance both the performance and efficiency of the integrated model by ensuring its comprehensiveness, accuracy, and stability. MLPS was constructed upon the concept of model surrogation + algorithm optimization using Ant Colony Optimization (ACO) coupled with Long Short-Term Memory (LSTM). The optimization results of the Integrated sewer network and urban river model demonstrate that the average relative percentage difference of the predicted river pollutant concentrations increases from 1.1 to 6.0, and the average absolute percent bias decreases from 124.3% to 8.8%. The model outputs closely align with the monitoring data, and parameter calibration time is reduced by 89.94%. MLPS enables the efficient optimization of integrated process-based models, facilitating the application of highly precise complex models in environmental management. The design of MLPS also presents valuable insights for optimizing complex models in other fields.

Bibliometric analysis of global performance and trends of research on combined sewer overflows (CSOs) from 1990 to 2022

Combined sewer overflows (CSOs) are one of the main sources of pollution in urban water systems and significantly impede the restoration of water body functionalities within urban rivers and lakes. To understand the research and frontier trends of CSOs comprehensively and systematically, a visual statistical analysis of the literature related to CSOs in the Web of Science core database from 1990 to 2022 was conducted using the bibliometric method using HistCite Pro and VOSviewer. The results reveal a total of 1,209 pertinent publications related to CSOs from 1990 to 2022, and the quantity of CSOs-related publications indicated an increasing trend. Investigations of the distribution and fate of typical pollutants in CSOs and their ecological effects on receiving waters and studies on pollution control technologies (source reduction, process control, and end-of-pipe treatment) are the current focus of CSOs research. CSOs pollution control technologies based on source reduction and the monitoring and control of emerging contaminants are at the forefront of scientific investigations on CSOs. This study systematically and comprehensively summarized current research topics and future research directions of CSOs, thus providing a reference for CSOs control and water environment management research.

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.

Assessing spatial scales in hydrological effectiveness and economic costs of nature-based solutions within a scale-invariance framework

This study proposed a scale-invariance framework within the fractal and Universal Multifractal (UM) framework to assess hydrological performances and economic dimensions of nature-based solutions (NBS) across various spatial scales. Firstly, a series of NBS scenarios are created by implementing NBS heterogeneously over Guyancourt city (a peri-urban catchment located in the Southwest of Paris). Then, the spatial heterogeneity and the implementation levels of NBS in the NBS scenarios are quantified by a scale-invariance indicator (fractal dimension; DF) across various spatial scales. The X-band radar rainfall data with high space-time resolution was obtained from École des Ponts ParisTech, which is used as the rainfall forcing for numerical modelling experiments. Then, the hydrological responses of the NBS scenarios are simulated by using the fully distributed and physically-based hydrological model (Multi-Hydro) under the selected spatially variable rainfall event. The renormalised maximum probable singularity indicator (RI) is developed based on the UM framework, and it is employed to quantify the hydrological effectiveness in terms of efficiency in runoff reduction of the NBS scenarios. The economic indicator is represented by the life cycle costs (LCC), which are used to estimate the economic costs of NBS scenarios. Finally, the economic dimensions of NBS across various spatial scales are quantified by integrating DF and the LCC of NBS scenarios. The results show that the permeable pavement scenarios 3 and 4 perform better than the other NBS scenarios in mitigating overland flow. The assessment of the economic dimensions of NBS suggests that a higher implementation level of NBS measures in the small-scale range is necessary. The economic dimensions of NBS at the large-scale range vary between 225 m2 and 600 m2. Overall, this study will potentially provide valuable strategies for better managing stormwater runoff in urban catchments and support the decision-making processes of implementing NBS on multiple spatial scales.

Probabilistic assessment of failure of infiltration structures under model and parametric uncertainty

We focus on the quantification of the probability of failure (PF) of an infiltration structure, of the kind that is typically employed for the implementation of low impact development strategies in urban settings. Our approach embeds various sources of uncertainty. These include (a) the mathematical models rendering key hydrological traits of the system and the ensuing model parametrization as well as (b) design variables related to the drainage structure. As such, we leverage on a rigorous multi-model Global Sensitivity Analysis framework. We consider a collection of commonly used alternative models to represent our knowledge about the conceptualization of the system functioning. Each model is characterized by a set of uncertain parameters. As an original aspect, the sensitivity metrics we consider are related to a single- and a multi-model context. The former provides information about the relative importance that model parameters conditional to the choice of a given model can have on PF. The latter yields the importance that the selection of a given model has on PF and enables one to consider at the same time all of the alternative models analyzed. We demonstrate our approach through an exemplary application focused on the preliminary design phase of infiltration structures serving a region in the northern part of Italy. Results stemming from a multi-model context suggest that the contribution arising from the adoption of a given model is key to the quantification of the degree of importance associated with each uncertain parameter.

Green infrastructure optimization considering spatial functional zoning in urban stormwater management

Green infrastructure (GI) is used as an alternative and complement to traditional urban drainage system for mitigating urban stormwater issues mainly caused by climate change and urbanization. The combination of hydrological model and optimization algorithm can automatically find the optimal solution under multiple objectives. Given the multi-functional characteristics of GI, choosing the optimization objectives of GI are critical for multiple stakeholders. This study proposes a GI optimization method considering spatial functional zoning. Based on the basic conditions, the study area is divided into the flood risk control zone (FRCZ) and the total runoff control zone (TRCZ). The integrated model coupling hydrological model and optimization algorithm is applied to obtain the Pareto fronts and corresponding non-dominated solutions. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to support the decision-making process. The optimal solution obtained for the FRCZ achieves a flood risk reduction rate of 60.49% with an average life cycle cost per year of 0.20 × 108 Chinese Yuan (CNY); The optimal solution obtained for the TRCZ achieves a total runoff reduction rate of 22.83% with an average life cycle cost per year of 0.17 × 108 CNY. This study provides a reference for stakeholders in GI planning and design.

Investigating non-point pollution mitigation strategies in response to changing environments: A cross-regional study in China and Germany

Climate change and urbanization have altered regional hydro-environments. Yet, the impact of future changes on the pollution risk and associated mitigation strategies requires further exploration. This study proposed a hydraulic and water-quality modeling framework, to investigate the spatiotemporal characteristics of pollution risk mitigation by low impact development (LID) strategies under future Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP) scenarios. Results demonstrated that the LID strategies exhibited an effective performance of pollutant removal in the current hydro-environment, with the removal rates ranging from 33% to 56%. In future climate and urbanization scenarios, the LID performance declined and turned to be uncertain as the greenhouse gas (GHG) emissions increased, with the removal rates ranging from 12% to 59%. Scenario analysis suggested that the LID performance was enhanced by a maximum of 73% through the diversified implementation of LID practices, and the performance uncertainty was reduced by a maximum of 67% through the increased LID deployment. In addition, comparative analysis revealed that the LID strategies in a well-developed region (Dresden, Germany) were more resilient in response to changing environments, while the LID strategy in a high-growth region (Chaohu, China) exhibited a better pollutant removal performance under low-GHG scenarios. The methods and findings in this study could provide additional insights into sustainable water quality management in response to climate change and urbanization.

Stormwater runoff pollution control performance of permeable concrete pavement and constructed wetland combined system: toward on-site reuse

Urban waterlogging and the deterioration of receiving water quality caused by stormwater runoff have become increasingly significant problems. Based on the concept of combining grey and green infrastructure, a combined permeable concrete pavement (PCP) and constructed wetland (CW) system has been developed to treat stormwater runoff and enable on-site reuse. The results showed that the removal rate of suspended solids (SS) by PCP ranged from 96.61 to 99.20%; however, the chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) concentrations in the effluent did not meet the standards required for rainwater reuse. For the combined PCP-CW system, the removal rates of COD, TN and TP by the CW were 48.45-75.12%, 47.26-53.05%, and 59.04-75.28%, respectively, under different hydraulic loading (HL) rates; thus, the effluent TN concentrations did not consistently meet the reuse standards. Further optimization of aeration in different parts of the CW revealed that aeration in the middle and front sections of the wetland had the most significant effect on pollutant removal, under which the TN concentrations in the effluent met the standard required for reuse. The effluent from the combined PCP-CW system was able to fully meet the stormwater reuse standards under these optimized conditions, and the reuse of urban stormwater runoff can therefore be realized.

First flush stormwater pollution in urban catchments: A review of its characterization and quantification towards optimization of control measures

Identification, quantification, and control of First-Flush (FF) are considered extremely crucial in urban stormwater management. This paper reviews the methods for FF phenomenon identification, characteristics of pollutants flushes, technologies for FF pollution control, and the relationships among these factors. It further discusses FF quantification methods and optimization of control measures, aiming to reveal directions for future studies on FF management. Results showed that statistical analyses and Runoff Pollutographs Applying Curve (RPAC) fitting modelling of wash-off processes are the most applicable FF identification methods currently available. Furthermore, deep insights into the pollutant mass flushing of roof runoff may be a critical approach to characterizing FF stormwater. Finally, a novel strategy for FF control is established comprising multi-stage objectives, coupling LID/BMPs optimization schemes and Information Feedback (IF) mechanisms, aiming towards its application for the management of urban stormwater at the watershed scale.

Influence of double-layer filling structure on nitrogen removal and internal microbial distribution in bioretention cells

The nitrogen removal effect of traditional bioretention cells on runoff rainwater is not stable. The nitrogen removal effect of bioretention cells can be improved by setting up a layered filling structure, but the effect of changes in filling structure on the nitrogen removal process and microbial community characteristics is still unclear. Two types of porosity fillers were set up in the experiment, and a homogeneous bioretention cell and three bioretention cells with layered fillers were constructed by changing the depth range of the upper and lower layers to analyze the influence of the pore variation of different depth fillers on the nitrogen removal process and microbial community characteristics. The experimental results showed that, compared with the homogeneous filing structure, the layered filling structure can strengthen the adsorption of NH₄⁺-N and the conversion of NO₃^--N, so as to increase the removal rates of NH₄⁺-N and NO₃^--N by 20.71-81.56% and 9.25%-78.19%, respectively. Although the low porosity filler structure will reduce the nitrification activity and urease activity by 48.63%-66.68% and 8.00%-20.64% respectively, it can increase the denitrification activity by 19.14%-31.92%, thus significantly reducing the nitrate content in the filler. The low porosity filler structure can affect the growth and reproduction of various phylum bacteria such as Proteobacteria, Chloroflexi, Acidobacteria, and genus bacteria such as Nitrospira, Ellin6067, Rhizobacter, Pseudomonas, which can improve the diversity and richness of microorganisms.

Hydrologic-hydraulic assessment of SUDS control capacity using different modeling approaches: a case study in Bogotá, Colombia

Urban flooding has increased in response to impervious surface intensification, the loss of green areas, and high-intensity rainfall associated with climate change. Sustainable urban drainage systems (SUDS) are an appealing option for stormwater management; however, their hydraulic control capabilities have received little attention. We developed a comparative model-based approach with 24 scenarios to contrast the hydrologic and hydraulic response of a highly discretized (HD) 1D model and a coupled 1D-2D model, considering the impact of rainwater harvesting systems and tree pits. An additional scenario was modeled including attenuation storage tanks, green roofs, and pervious pavements. A heavily urbanized flood-prone catchment with severe land-use constraints in Bogotá, Colombia, was selected for analysis. The findings revealed that SUDS can contribute to reducing the number of flooded junctions, overloaded conduits' length, overloading time, nodal inundation depth, and waterlogging extent. Furthermore, the HD 1D model can reproduce the coupled 1D-2D model results in terms of hydrologic response and some hydraulic control indicators. Further research is needed for an accurate description of the internal hydraulic mechanisms of SUDS interacting with overland flow. The key findings of this study provide model-based evidence to support urban stormwater management decision-making in data-scarce environments.

Optimizing first flush diverter for urban stormwater pollution load reduction by most efficiently utilizing first flush phenomena

In order to find the optimal design of first flush diverter, this study shifts the focus of first flush research from the existence of first flush phenomenon to utilization effect of the phenomenon. The proposed method consists of four parts: (1) key design parameters, which describing key structure of first flush diverter rather than first flush phenomenon; (2) continuous simulation, which replicating the uncertainty by using the full scope of runoff events that might occur over the years analyzed; (3) design optimization, through an overlapped contour graph of key design parameters and key performance indicators that are relevant to but different from conventional indicators describing first flush phenomena; (4) event frequency spectra, which presenting the diverter's behavior at daily temporal resolution. As an illustration, the proposed method was used to determine design parameters of first flush diverters for roof runoff pollution control in the northeast of Shanghai. The results show that annual runoff pollution reduction ratio (PLR) was insensitive to buildup model. This greatly reduced the difficulty of buildup modeling. The contour graph was useful in finding the optimal design, i.e., the optimal combination of design parameters that could meet PLR design goal with most concentrated first flush on average (quantified by MFF). For instances, the diverter could achieve PLR = 40% with MFF >1.95, and PLR = 70% with MFF = 1.7 at most. Pollutant load frequency spectra were generated for the first time. They showed that a better design reduced pollutant load more stably while diverting less volume of first flush within almost each runoff day.

Bibliometric analysis of global research on bioretention from 2007 to 2021

Bioretention is a typical low impact development (LID) practice that helps reduce peak urban stormwater runoff and runoff pollutant concentrations (e.g., heavy metals, suspended solids, organic pollutants), which has become an important part of urban stormwater management over the past 15 years. To understand the research hotspots and frontiers in the field of bioretention facility research and provide a reference for research into bioretention facilities, we conduct a statistical analysis of global bioretention literature published during 2007-2021 using the Web of Science core database and the data visualization and analysis software VOSviewer and HistCite. The number of published articles related to bioretention facilities shows a rising trend over the study period, with research from China contributing greatly to global research on bioretention facilities. However, the influence of articles needs to be increased. Recent studies mainly focus on the hydrologic effect and water purification effect of bioretention facilities and on the removal of nitrogen and phosphorus nutrients from runoff rainwater. Further studies should focus on the interaction of fillers, microorganisms, and plants in bioretention facilities and its impact on the migration, transformation, and concentrations of nitrogen and phosphorus; the purification effect and mechanism of specific emerging contaminants in runoff; the selection and configuration optimization of filler materials and plant species; and the optimization of the design parameters of the model for bioretention systems.

Optimal siting of rainwater harvesting systems for reducing combined sewer overflows at city scale

The installation of green infrastructure (GI) is an effective approach to manage urban stormwater and combined sewer overflow (CSO) by restoring pre-development conditions in urban areas. Research on simulation-optimization techniques to aid with GI planning decision-making is expanding. However, due to high computational expense, the simulation-optimization methods are often based on design storm events, and it is unclear how much different rainfall scenarios (i.e., design storm events vs. long-term historical rainfall data) impact the optimal siting of GI. The Parallel Pareto Archived Dynamically Dimensioned Search (ParaPADDS) algorithm in a novel simulation-optimization tool OSTRICH-SWMM was used to leverage distributed computing resources. A case study was conducted to optimally site rainwater harvesting cisterns within 897 potential subcatchments throughout the City of Buffalo, New York. Seven design storm events with different return periods and rainfall durations and a one-month historical rainfall time series were considered. The results showed that the optimal solutions of siting cisterns using event-based scenarios, though less computationally expensive, may not perform well under continuous rainfall scenarios, suggesting design rainfall scenarios should be carefully considered for optimizing GI planning. The impact of rainfall scenarios was particularly significant in the middle region of the Pareto front of multi-objective optimization. Utilizing high-performance parallel computing, OSTRICH-SWMM is a promising tool to optimize GI at large spatial and temporal scales.

The Life cycle Assessment Integrated with the Lexicographic Method for the Multi-Objective Optimization of Community-Based Rainwater Utilization

Community-based rainwater utilization (CB-RWU) has the advantage of easy maintenance and multiple benefits. However, its promotion proves to be a complicated task due to difficulties in quantifying and evaluating external benefits. This study integrated the life cycle assessment (LCA) with a multi-objective optimization model to optimize the relationship among all stages of CB-RWU, considering the trade-offs among the benefit-cost ratio, water-saving efficiency and environmental impact. The LCA results identified abiotic depletion potential for fossil fuels (ADPF) as the key impact indicators throughout the life cycle of CB-RWU. The optimal solution from the lexicographic method was 0.3098, 28.47% and 24.68 MJ for the benefit-cost ratio, water-saving efficiency and ADPF, respectively. Compared with the traditional optimization method, the lexicographic method improved the three object functions by 26%, 43% and 14%, respectively. The uncertainty of the environmental impact was the highest (C_V = 0.633) with variations in the floor area ratio, total runoff coefficient and reservoir volume. Changes in the total runoff coefficient were the main source of the uncertainty, which suggested that more attention should be paid to the area ratio of each underlying surface. In addition, economic support from the government is urgently required for the further promotion and development of CB-RWU.

Comprehensive analysis of waterlogging control and carbon emission reduction for optimal LID layout: a case study in campus

Nowadays, sponge city reconstruction has become the focus of research because of the increasingly serious urban waterlogging. Carbon emission reduction, waterlogging area reduction, cost, and other indicators were considered to explore the optimal sponge allocation scheme in the study area. The two-dimensional coupled model MIKE FLOOD was established to analyze the causes of waterlogging through numerical simulation. Low-impact development (LID) combination scenarios were set to analyze the control effects of waterlogging water and total runoff. The carbon emission reduction capacity and economic benefit of each scenario were calculated and evaluated. The analytic hierarchy process (AHP) was used to comprehensively evaluate the LID combination scenario and explore the optimal cost-benefit LID configuration scheme. The results show that the campus rainwater pipe network is under overload operation, and the number of overflow nodes accounts for up to 58.1% under the 3a rainfall return periods. After setting up LID measures, the runoff control rate can be increased by 26.15-42.84%, and the waterlogging area where the depth exceeds 15 cm can be reduced by 72.87-100%. If the energy conservation and emission reduction benefits and costs are considered at the same time, the layout scenario of 9% bioretention facility + 3% green roof + 3% permeable pavement can achieve the best benefits. The research can provide a reference for planning and reconstruction of sponge campus and residential areas.

Effects of Low-Impact Development Facilities (Water Systems of the Park) on Stormwater Runoff in Shallow Mountainous Areas Based on Dual-Model (SWMM and MIKE21) Simulations

Rapid urbanization has triggered more serious urban flood risks. Many studies have focused on intra-urban flooding, but less attention has been paid to rainfall and flood risks at the urban fringe. Nowadays, China is vigorously promoting the construction of sponge cities in the whole area. It is important to study the construction of sponge cities in shallow mountainous areas, which are an important barrier between cities and mountains. The purpose of this paper is to investigate the performance of Low-Impact Development (LID) facilities under different rainfall scenarios in developed shallow mountainous areas. The second garden and flower exposition ("the Expo Park") in Hebei Province is used as an example. The SWMM and MIKE21 models were used to simulate the hydrological processes before and after the construction of "the Expo Park", and the models were calibrated with the measured data. Peak flow rate, outflow volume, rainfall-outflow ratio, runoff velocity, and water feature area of the water system were used as indicators to evaluate their effectiveness. The results showed that the placement of LID facilities had a positive impact on the construction of the shallow mountain area. Specifically, (1) LID facilities can reduce the peak flow rate, delayed peak flow time, outflow volume, and rainfall outflow ratio of stormwater runoff in mountainous areas; and (2) they can effectively collect rainwater and become a supplement to the landscape water system of the site. These findings provide a scientific basis for the construction of LID facilities in shallow mountainous areas, which is important for the development and flood management of shallow mountainous areas.

Investigating the influences of concave depths on stormwater runoff and pollution retention of urban grasslands

In this study, scale-based runoff plots of concave grasslands were designed and simulated rainfall experiments were conducted to investigate their retention effectiveness for runoff volume and pollutant loads, and to analyze the influences of concave depths on runoff and pollution retention of grasslands. Results showed that mean time to runoff of concave grasslands was 88.5 minutes, which was 5.3 times than that of flat grassland. Average peak flow rate of concave grasslands was reduced by 36.2% compared with flat grassland. Concaved grasslands averagely retained 58.2% of stormwater runoff. Deeper concave depths significantly increased runoff detention and retention performance of grasslands. Total suspended solids (TSS) load reduction rates of concave grasslands were ranged from 50.8% to 97.3%. Total nitrogen (TN) load reduction rate was 49.8% for concave depth of 10 cm. Total phosphorus (TP) load reduction rates were 45.0% and 93.9% for grasslands with 5 cm and 10 cm concave depths, respectively. Pollution load reduction rates of TSS, TN and TP enhanced along with the increase in concave depths. The estimated minimum area ratios of upslope impervious surface to grasslands of 5 cm and 10 cm concave depths were approximately 1:1 under 20 mm rainfall events, and 38:1 under 5 mm rainfalls, respectively.

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.

Incorporating receiving waters responses into the framework of spatial optimization of LID-BMPs in plain river network region

Deep insights into the receiving waters responses to optimal spatial allocation of LID-BMPs are considered extremely important. This study addressed the urgent need to incorporate receiving waters responses into the spatial allocation optimization of LID-BMPs and demonstrated the efficiency of the approach to guide watershed management. The integration of an overland-river coupling model and the NSGA-III algorithm resulted in the proposal of a general simulation-optimization framework for the optimal layout of LID-BMPs. The coupled model was swapped out for the surrogates to increase computational efficiency. When 40.71%, 36.06%, and 61.80% reductions in runoff volume, flood volume, and TP concentration are achieved, the newly proposed framework can save 34.44% and 16.31% cost compared to the approach that does not consider receiving waters responses and refined spatial allocation, respectively. Results indicate that the incorporation of receiving waters responses and refined spatial allocation are essential for the optimal design of LID-BMPs. This new framework offers the potential for more cost-effective high-cost solutions. The results of spatial optimization are significantly influenced by imperviousness.

Numerical Experiments on Low Impact Development for Urban Resilience Index

Low impact development (LID) has become one of the strategies that effectively mitigate the impacts of climate change. In addition to the ability to reduce nonpoint source (NPS) pollution caused by flash floods from the surface runoff, LID has also been applied to control water quantity under extreme rainfall events. Due to the fact that studies about LID configuration optimization tended to control water quantity and gradually ignored the main functions of water quality treatment, this study aims to consider water quantity and quality to estimate the benefits and optimal configuration of LID by Non-Dominated Genetic Algorithm (NSGA-II). In addition, regarding to the outlet peak flow, hydrologic footprint residence (HFR) was considered to be the water quantity indicator due to the ability to represent the dynamics of flow changes, and the modified quality indicator (Mass Emission First Flush ratio, MEFF30) was corrected to represent the pollutant transport process in a large catchment area. The results show that the flood and MEFF30 reduction rate of LID are inversely proportional to rainfall duration and intensity. The benefit of pollutant reduction, which can still be maintained by 20% and 15% under a big return period and the long duration was about three times than the quantity control. Taking the cost into account, although the rain barrel had the best effect of reduction per unit area, green roofs and permeable pavements had a higher unit cost reduction rate due to the lower costs. The upper and middle reaches of the open channel and the confluence of rainwater sewers should be the optimal LID configuration to achieve the benefits of both flood and pollution reduction.

A novel multi-objective optimization framework for urban green-gray infrastructure implementation under impacts of climate change

Frequent urban flooding disasters can cause severe economic and property losses. Accordingly, the construction of sponge city has become critical to alleviating urban flooding. However, the functional and structural integration of Green Infrastructure (GI) and Gray Drainage Facility (GDF) is still a matter of concern. This study proposed a novel implementation framework for GI and GDF synchronization optimization (G-GSOIF) based on the SWMM and SUSTAIN models, and used data from Beilin District in Xi'an, China to verify the effects. The results show that the spatiotemporal integrated optimization design of GI and GDF proves to be effective in stormwater management. The total investment was reduced by 16.7% and economic benefit was increased by 15.4% based on disaster risk control, and the utilization rate of rainwater resources exceeded 40%. The Staged optimization model (SSOM) based on the SUSTAIN model established in the G-GSOIF was demonstrated to effectively cope with the impact of future climate change by adjusting and optimizing the design scheme dynamically in different simulation scenarios. Integrated LID (I-LID) measures are conducive for simulation of large catchment areas, and have the same implementation effect as distributed LID measures. The results of this study could support decision-making for urban stormwater management and sponge city construction.

Urban stormwater runoff pollutant loadings: GIS land use classification vs. sample-based predictions

Cities are growing worldwide with an increase in stormwater quantity and decrease in quality, negatively impacting receiving water bodies. The characterization of stormwater is difficult given its high variability and the typically numerous outfalls to be monitored. However, loadings can be estimated via models and validated using actual outfall monitoring. This study determined stormwater pollutant loadings predicted using eight land-use classifications (i.e., a 'desktop' study) and via an outfall sampling regime (i.e., a 'monitoring' study) for seven stormwater catchment areas in Saskatoon, SK, Canada, where stormwater typically releases directly into the South Saskatchewan River. Pollutants considered were total suspended solids (TSS), chemical oxygen demand (COD), metals, and polycyclic aromatic hydrocarbons. Catchment areas were dominated by single-family residential (39%) and green areas (17%). The largest catchment area, Preston Crossing, was the major source of the predicted annual loadings, such as TSS at 550,000 kg and COD at 265,000 kg. For comparison, the sampled-based estimated loadings for TSS and COD were 362,700 kg and 652,700 kg, respectively. Differences between the average predicted and actual estimations ranged from 29 to 156% for the eight pollutants considered, with averages for the summed pollutants in each catchment area ranging from 48 to 130%. Overall, the assessment and monitoring of stormwater outfalls are needed for the determination of impacts of loadings on the environment and for the subsequent development and implementation of treatment technologies.

Assessing Hydrological Cost-Effectiveness of Stormwater Multi-Level Control Strategies in Mountain Park under the Concept of Sponge City

Within the concept of sponge city in China, green stormwater measures have been widely used in urban mountain parks. This study provides an integrated assessment framework for hydrological cost-effectiveness in the Nanjing Guanyao Mountain Park under various precipitation scenarios. A grey drainage basic strategy and four multi-level control strategies with progressively increasing graded interception or storage facilities at mid-and terminal levels were designed and evaluated. Results show that the multi-level interception and storage strategy (S4) proved to be the most beneficial, followed by the multi-level interception strategy (S2) having slightly lower results than the multi-level storage strategy (S3), while the terminal strategy (S1) showed poor results. However, the hydrological cost-effectiveness exhibits the opposite trend under 2–5-year storms. A high multi-level strategy limited by life-cycle costs may not impart high hydrological cost-effectiveness in response to each return period of storms in this mountain stormwater practice. This study validates the hydrological performance and cost-effectiveness of multi-level distributed strategies in an urban mountain park, bridges the limitations of the previous studies on single scheme design and hydrological performance assessment for sloped sites, and provides a technical reference and design basis for similar studies and practices.

Ranking Three Water Sensitive Urban Design (WSUD) Practices Based on Hydraulic and Water Quality Treatment Performance: Implications for Effective Stormwater Treatment Design

Bioretention basins, constructed wetlands and roadside swales are among the most common Water-Sensitive Urban Design (WSUD) or stormwater quality treatment systems. Although these systems can reduce stormwater quantity and improve quality, their hydraulic and water quality treatment performances are different. The aim of this study was to investigate the hydraulic and water quality performance of a bioretention basin, a constructed wetland and a roadside swale by analyzing monitored water quantity and quality data from a range of rainfall events using a ranking approach. The study outcomes showed that a bioretention basin performed better in relation to peak flow and runoff volume reduction while the constructed wetland tended to produce better outflow water quality. The roadside swale had a relatively lower capacity for treating stormwater. These results suggest that a bioretention basin could be the preferred option when the primary requirement is water quantity improvement. However, if water quality improvement is the primary consideration, a constructed wetland could be more efficient. Additionally, when designing a treatment train, it appears to be preferable to place a bioretention basin prior to a constructed wetland. Further, a swale appears to be more appropriate for use as a pretreatment device. The research study outcomes will contribute to effective stormwater treatment design.

First Flush Stormwater Runoff in Urban Catchments: A Bibliometric and Comprehensive Review

First flush is a phenomenon in stormwater runoff that has been considered a topic of great interest in the field of nonpoint source pollution. Despite several attempts to define the first flush quantitively, the specified characteristics of the phenomenon vary among sources. To address these uncertainties, a bibliometric and comprehensive review on published articles related to first flush was conducted. A corpus of 403 research articles was obtained from the Scopus database, which was then parsed using the CorText Manager for the bibliometric analysis. The study examined quantitative definitions of first flush from various sources; climate and topographic characteristics of monitoring and experimental sites where the studies on first flush were performed; the sample collection methods applied; the first flush values obtained on the studies and how it influenced the nonpoint source pollution in urban watersheds. A network map, two contingency matrices, and a Sankey diagram were created to visualize the relationship of significant keywords related to first flush, as well as their co-occurrences with journals, countries, and years. It was found that the strength of the first flush effect could vary depending on the geographical location of the site, climatic conditions, and the pollutants being analyzed. Therefore, initial rainfall monitoring, runoff sampling, and water quality testing were seen as critical steps in characterizing the first flush in urban catchments. Furthermore, the characterization of first flush was found to be significant to the selection of best management practices and design of low-impact development (LID) technologies for stormwater runoff management and nonpoint source pollution control.

Effects of low impact development on the stormwater runoff and pollution control

The frequent urbanization and extreme rainfall events have posed the threat to the urban environment. The implementation of low impact development (LID) practices with great potential for control urban flood and overflow pollution is not comprehensively understood yet due to the influence of complex factors (i.e., hydrological pattern, installation location, and vertical parameter setting). In this study, the hydraulic and water quality model were used to analyze the hydrological and pollution reduction of outfall and storage under different hydrological patterns, vertical parameter setting, and green infrastructure installation locations, which can determine the best implementation of the scheme for overflow pollution control. The results showed that nine parameters of the vertical layer regarding the four parameters impacted the peak value and load of suspended solids (SS). The combination scheme of the LID practices was further proposed based on the selection and analysis of the single LID practice. Besides, considering the installation location, the downstream installed location was a better choice. The horizontal connection of overflow runoff and pollution could be reduced by up to 9.75% and 36.46%, respectively. In addition, the horizontal connection can effectively reduce the peak value of inflow and pollutants at the time of assessing storage tank impact, which reach the maximum of 14.08% and 29.25%, respectively. The pollutants distribution became uniform and showed better resilience against rainfall intensity, which is beneficial to the management of stormwater. Our findings can provide guidance for Sponge City construction and effectively alleviate the combined sewer overflow.

Efficient Urban Runoff Quantity and Quality Modelling Using SWMM Model and Field Data in an Urban Watershed of Tehran Metropolis

This study aims to calibrate and validate the EPA Storm Water Management Model from field measurements of rainfall and runoff, in order to simulate the rainfall-runoff process in an urban watershed of Tehran metropolis, Iran. During and after three significant storm events, the flow rates, total suspended solids (TSS), total phosphorus (TP), and total Kjeldahl nitrogen (TKN) concentrations were measured at the outlet of the catchment, and were used in the model calibration and validation process. The performance of the SWMM model was evaluated based on the statistical criteria, as well as graphical techniques. In this study, a local sensitivity analysis was carried out to identify the key model parameters, show that “the percentage of impervious surface in each subwatershed had the most effect on the model output”. Based on the analysis of the results, SWMM model calibration and validation can be judged as satisfactory, and the goodness-of-fit indices for simulating runoff quality and quantity are placed in acceptable ranges. The adjustment obtained for the variations in the measured and simulated flow rates, pollutograph concentrations, total pollutant load, peak concentration, and the event mean concentration (EMC) confirms the considerable predictive capability of the SWMM model when it is well calibrated by using field measurements.

The Application of Low Impact Development Facility Chain on Storm Rainfall Control: A Case Study in Shenzhen, China

In recent decades, low impact development (LID) has become an increasingly important concern as a state-of-the-art stormwater management mode to treat urban flood, preferable to conventional urban drainage systems. However, the effects of the combined use of different LID facilities on urban flooding have not been fully investigated under different rainfall characteristics. In this study, a residential, neighborhood-scale catchment in Shenzhen City, southern China was selected as a case study, where the effects of four LID techniques (bio-retention, bio-swale, rain garden and pervious pavement) with different connection patterns (cascaded, semi-cascaded and paralleled) on runoff reduction efficiency were analyzed by the storm water management model (SWMM), promoted by the U.S. EPA. Three kinds of designed storm events with different return periods, durations and time-to-peak ratios were forced to simulate the flood for holistic assessment of the LID connection patterns. The effects were measured by the runoff coefficient of the whole storm–runoff process and the peak runoff volume. The results obtained indicate that the cascaded connect LID chain can more effectively reduce the runoff than that in the paralleled connect LID chain under different storms. The performances of the LID chains in modeling flood process in SWMM indicate that the runoff coefficient and the peak runoff volume increase with the increase in the rain return periods and the decrease in rain duration. Additionally, the move backward of the peak rain intensity to the end of the storm event slightly affects the peak runoff volume obviously while gives slight influence on the total runoff volume. This study provides an insight into the performance of LID chain designs under different rainfall characteristics, which is essential for effective urban flood management.

Biological nitrogen removal from stormwater in bioretention cells: a critical review

Excess nitrogen in stormwater degrades surface water quality via eutrophication and related processes. Bioretention has been recognized as a highly effective low-impact development (LID) technology for the management of high runoff volumes and reduction of nitrogen (N) pollutants through various mechanisms. This paper provides a comprehensive and critical review of recent developments on the biological N removal processes occurring in bioretention systems. The key plant- and microbe-mediated N transformation processes include assimilation (N uptake by plants and microbes), nitrification, denitrification, and anammox (anaerobic ammonia oxidation), but denitrification is the major pathway of permanent N removal. Overall, both laboratory- and field-scale bioretention systems have demonstrated promising N removal performance (TN: >70%). The phyla Bacteroidetes and Proteobacteria are the most abundant microbial communities found to be enriched in biofilter media. Furthermore, the denitrifying communities contain several functional genes (e.g., nirK/nirS, and nosZ), and their concentrations increase near the surface of media depth. The N removal effectiveness of bioretention systems is largely impacted by the hydraulics and environmental factors. When a bioretention system operates at: low hydraulic/N loading rate, containing a saturation zone, vegetated with native plants, having deeper and multilayer biofilter media with warm climate temperature and wet storm events periods, the N removal efficiency can be high. This review highlights shortcomings and current knowledge gaps in the area of total nitrogen removal using bioretention systems, as well as identifies future research directions on this topic.

Urban Green Space Arrangement for an Optimal Landscape Planning Strategy for Runoff Reduction

Increased impervious surfaces due to urbanization have reduced evaporation and infiltration into the soil compared with existing natural water cycle systems, which causes various problems, such as urban floods, landslides, and deterioration of water quality. To effectively solve the urban water cycle issue, green infrastructure using urban green space has emerged to reduce runoff and increase evaporation. It has the advantage of restoring the water cycle system of urban areas by complementing the failure of conventional stormwater treatment systems. However, urban areas under high-density development have limited green space for stormwater treatment. Hence, it is necessary to efficiently utilize street trees and small green spaces to improve the urban water cycle through green space. In this study, we simulated different green space distribution scenarios in the virtual domain to find the optimal strategy of green space planning. Compared to clustered scenarios, dispersed green space distribution scenarios and placing green space downstream were more effective in reducing the runoff amount. The paper provides insights into the considerations for determining green space spatial plan and zoning regulations for stormwater treatment by green infrastructure.

Bioretention systems for stormwater management: Recent advances and future prospects

Bioretention is a popular stormwater management strategy that is often utilized in urban environments to combat water quality and hydrological impacts of stormwater. This goal is achieved by selective designing of a system, which consists of suitable vegetation at the top planted on an engineered media with drainage system and possible underdrain at the bottom. Bibliometric analysis on bioretention studies indicates that most of the original research contributions are derived from a few countries and selected research groups. Hence, most of the bioretention systems installed in diverse geographical locations are based on guidelines from climatically different countries, which often lead to operational failures. The current review critically analyzes recent research findings from the bioretention literature, provides the authors' perspectives on the current state of knowledge, highlights the key knowledge gaps in bioretention research, and points out future research directions to make further advances in the field. Specifically, the role and desired features of bioretention components, the importance of fundamental investigations in laboratory, field-based studies and modeling efforts, the real-time process control of bioretention cells, bioretention system design considerations, and life cycle assessment of full-scale bioretention systems are discussed. The importance of local conditions in guiding bioretention designs in difference climates is emphasized. At the end of the review, current technical challenges are identified and recommendations to overcome them are provided. This comprehensive review not only offers fundamental insights into bioretention technology, but also provides novel ideas to combat issues related to urban runoff and achieve sustainable stormwater management.

Development and modelling of realistic retrofitted Nature-based Solution scenarios to reduce flood occurrence at the catchment scale

Decentralized Nature-based Solutions such as Urban Green Infrastructures (UGI) are increasingly promoted to reduce flooding in urban areas. Many studies have shown the effectiveness of flood control of UGI at a plot or neighbourhood level. Modelling approaches that extrapolate their flood reducing impact to larger catchment scales are often based on a simplistic assumption of different percentages of UGI implementation. Additionally, such approaches typically do not consider the suitable space for UGI and potential implementation constraints. This study proposes a scenario development and modelling approach for a more realistic upscaling of UGI based on empirical insights from a representative neighbourhood. The results from this study, conducted in the metropolitan area of Costa Rica, show that upscaling the full potential for UGI could significantly reduce surface runoff, peak flows, and flood volumes. In particular, the permeable pavement has the highest potential for flood reducing in public space while cisterns perform best at the property level. These results can guide the formation of policies that promote UGI.

Development and Application of a SWMM-Based Simulation Model for Municipal Scale Hydrologic Assessments

There is growing interest for the installation of green stormwater infrastructure (GSI) to improve stormwater control, increase infiltration of stormwater, and improve receiving water body quality. Planning level tools are needed to inform municipal scale decisions on the type and extent of GSI to apply. Here, a modified methodology is developed for the EPA Storm Water Management Model (SWMM) to create SWMM for Low Impact Technology Evaluation (SWWM-LITE) that enables municipal scale assessment of stormwater control measure (SCM) performance with minimal input data requirements and low processing time. Hydrologic outputs of SWMM-LITE are compared to those for SWMM and the National Stormwater Calculator (SWC) to assess the performance of SWMM-LITE. Three scenarios including the baseline without SCMs and the installation of varying SCMs were investigated. Across the three scenarios, SWMM-LITE estimates of annual average hydrologic performance (runoff, infiltration, and evaporation) were within +/−0.1% of estimates from a rigorously developed SWMM model in the City of Fort Collins, CO, for an evaluation of 30 years of continuous simulation. Analysis conducted for 2 year (y), 10 y, and 100 y storm events showed less than +/−2.5% difference between SWMM and SWMM-LITE hydrologic outputs. SWC provided reasonable estimates of hydrologic parameters for the case study area, but was designed for site level analyses of performance of SCMs rather than on the municipal scale. A sensitivity analysis revealed that the most sensitive parameters were primarily consistent for the SWMM-LITE and the complete SWMM. SWMM-LITE has low input data requirements and processing time and can be applied for assessing the hydrologic performance of SCMs to inform planning level decisions.

Impact of green infrastructure on the mitigation of road-deposited sediment induced stormwater pollution

As a vital stormwater pollution source, the pollutants associated with road-deposited sediment (RDS) have become a growing concern in urban water management. Green infrastructure has exhibited great potential in stormwater pollution mitigation, but is not comprehensively understood yet due to the influences of complex RDS-associated pollutant migration processes (i.e., build-up, wash-off, and discharge). In this study, a city-scale hydraulic and water quality model was used to analyze the migration and removal processes of four RDS-associated pollutants (total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP)) under different hydrological patterns, land-cover types, and green infrastructure installation locations. Results show that the antecedent dry-weather period was the main factor influencing RDS build-up, while the precipitation pattern strongly impacted RDS wash-off, discharge, and removal. The downstream-installed green infrastructures reduced the RDS-induced stormwater pollution by up to 68% and relieved the pollution-mitigation pressure of the studied drainage networks by almost 50%. The TSS and COD removal rates were higher (62.22-68.09%) near green space, while those of TN and TP were higher around buildings and roads (40.00-62.50%). Sensitivity analysis indicated that seven parameters regarding the surface layer characteristics and soil texture class strongly impacted the pollution-mitigation performance among the 31 technical parameters of green infrastructure. The results of this study would assist urban water management by optimizing green infrastructure for stormwater pollution mitigation.

Optimal implementation of low impact development for urban stormwater quantity and quality control using multi-objective optimization

Stormwater runoff is a major concern in urban areas which is mostly the result of vast urbanization. To reduce urban stormwater runoff and improve water quality, low impact development (LID) is used in urban areas. Therefore, it is vital to find the optimal combination of LID controls to achieve maximum reduction in both stormwater runoff and pollutants with optimal cost. In this study, a simulation-optimization model was developed by linking the EPA Storm Water Management Model (SWMM) to the Multi-Objective Particle Swarm Optimization (MOPSO) using MATLAB. The coupled model could carry out multi-objective optimization (MOO) and find potential solutions to the optimization objectives using the SWMM simulation model outputs. The SWMM model was developed using data from the BUNUS catchment in Kuala Lumpur, Malaysia. The total suspended solids (TSS) and total nitrogen (TN) were selected as pollutants to be used in the simulation model. Vegetated swale and rain garden were selected as LID controls for the study area. The LID controls were assigned to the model using the catchment characteristics. The target objectives were to minimize peak stormwater runoff, TSS, and TN with the minimum number of LID controls applications. The LID combination scenarios were also tested in SWMM to identify the best LID types and combination to achieve maximum reduction in both peak runoff and pollutants. This study found that the peak runoff, TSS, and TN were reduced by 13%, 38%, and 24%, respectively. The optimal number of LID controls that could be used at the BUNUS catchment area was also found to be 25.

Nutrient delivery efficiency of a combined sewer along a lake challenged by incipient eutrophication

Although sewage diversion outside of a lake's watershed is now ordinary practice in the restoration of eutrophic lakes, often the observed recovery is slower than expected and the internal load from the lake anoxic sediments is identified as a possible reason. However, in the case of combined sewer, the quantification of the residual nutrient load discharged from sewer spillways must also be questioned. In this paper, the diversion efficiency of the sewer system along the east coast of Lake Iseo, a prealpine Italian lake where eutrophication effects are still severe, is investigated. To this purpose, a representative part of the sewer system was modelled by PCSWMM and calibrated by using an extensive series of discharge measurements. Water quality monitoring during wet weather periods reveals that the first flush is common in tributary sewers, whereas it is absent along the main collector. Moreover, flow discharges are strongly affected by infiltration waters, which are controlled by the lake water level. The calibrated model, including infiltration modeling, was used to assess the annual overflow volumes and the nutrient load through a continuous 10-year simulation. Simulations were conducted both with regard to the current conditions and to a climate change scenario. Results show that the discharged residual load is at least 7 times larger than the design value, with the water infiltration contributing to 17% to the overflow volume and that non-structural practices could considerably reduce the overall impact of the sewer. This research thus provides important insight into the potential impact of combined sewer overflows on lacustrine environments and addresses effective mitigation measures in similar contexts.

GIP-SWMM: A new Green Infrastructure Placement Tool coupled with SWMM

A new Green Infrastructure Placement Tool coupled with Storm Water Management Model (GIP-SWMM) is developed for selection and strategic placement of Green Infrastructure (GI) practices. The tool supports GI placement at multiple scales - from a few city blocks to large watersheds. GI is a multi-benefit option for stormwater management and can revitalize communities while reducing sewage overflows and improving runoff quality. However, cost-effective planning and placement of GI to achieve management goals remains a challenge and requires an integrated watershed approach. An optimization approach was developed coupled with the SWMM to find optimal combination and placement of GI to meet target flow and pollutant load reduction while minimizing cost at a watershed scale. The tool includes 13 GI types and selection and placement of GI within a watershed is based on their capital cost and effectiveness. The tool generates cost-effectiveness curves (cost vs size of GIs) for discharge and pollutants. GIP-SWMM provides a means for objective analysis of managing alternatives among multiple interacting and competing options. The desired outcome from the system application is a thorough, practical, and informative assessment considering economic, and engineering factors. The performance of the tool was evaluated in the Meade-Hawthorne drainage basin in Rapid City, South Dakota. GI placement options were assessed for multiple target levels for discharge, TSS, E coli, and Fecal coliform. Cost-effectiveness curves were developed for discharge, TSS, E coli, and Fecal coliform. Total GI cost increased as the target discharge, TSS, E coli, and Fecal coliform concentration at the outlet of the watershed was reduced. The tool placed a larger percentage of the GIs at the locations where most of the discharge and pollutant loads originated. This case study demonstrates that GIP-SWMM is a planning level decision support framework that allows for optimization of GIs and is adaptable for use in addressing regulatory compliance and practices across the U.S.

Water Conservation and Green Infrastructure Adaptations to Reduce Water Scarcity for Residential Areas with Semi-Arid Climate: Mineral de la Reforma, Mexico

The increasing population and urban sprawl will continue to add significant pressure to natural resources in arid and semi-arid zones. This study evaluates the theoretical effectiveness of adapting resilient strategies such as water conservation and green infrastructure to mitigate the water scarcity faced by the inhabitants of a residential area with a semi-arid climate. Three scenarios were analyzed at a micro-basin level to determine the mitigation of surface runoff and the volume that can be theoretically intercepted for further use: (a) unaltered natural watershed (scenario 1), (b) currently urbanized watershed (scenario 2), and (c) watershed adapted with resilient strategies (scenario 3). For this last scenario, the annual usable volume of rainwater intercepted on the dwelling rooftops was obtained. The runoff and peak flow in the natural watershed were lower than in the other two scenarios. In contrast, a decrease in the runoff was observed in scenario 3 concerning scenario 2, which indicates that the interception of rainwater on house roofs and the adoption of green infrastructure solutions would significantly reduce the diameter of urban drainage pipes required in new developments, as well as the dependency of inhabitants on potable water services. In sites with semi-arid climates, it is possible to take advantage of the rainwater harvested on rooftops and the runoff intercepted through green infrastructure to mitigate local water scarcity problems, which should be considered and adopted in new residential developments.

Assessment of Rain Garden Effects for the Management of Urban Storm Runoff in Japan

Storm runoff is a growing concern against a background of increasing urban densification, land-use adaptation and climate change. In this study, a storm water management model was used to analyze the hydrological and water-quality effects of rain gardens (also known as bioretention cells) as nonpoint source control solutions in low-impact development (LID) practices for an urban catchment in the Nakagyo Ward area of Kyoto in Japan. The results of simulations with input involving Chicago hyetographs derived for different rainfall return periods (referred to as 3 a, 5 a, 10 a, 30 a, 50 a and 100 a) indicated the effectiveness of this arrangement, in particular for rainstorm 3 a, which exhibited the maximum contaminant reduction ratio (Total Suspended Solids (TSS) 15.50%, Chemical Oxygen Demand (COD) 16.17%, Total Nitrogen (TN) 17.34%, Total Phosphorus (TP) 19.07%) and a total runoff reduction volume of 46.56 × 106 L. With 5 a, the maximum number of flooding nodes was reduced to 87, demonstrating that rain gardens handle rainfall effectively over a five-year return period. There was a one-minute delay for 100 a, which again indicates that rain gardens support control of urban runoff and mitigate flooding. Such gardens were associated with reduced stormwater hazards and enhanced resistance to short-term rainstorms at the research site, and should be considered for urban planning in Kyoto and other cities all over the world.

Sensitivity Analysis of the Rainfall–Runoff Modeling Parameters in Data-Scarce Urban Catchment

Rainfall–runoff phenomena are among the main processes within the hydrological cycle. In urban zones, the increases in imperviousness cause increased runoff, originating floods. It is fundamental to know the sensitivity of parameters in the modeling of an urban basin, which makes the calibration process more efficient by allowing one to focus only on the parameters for which the modeling results are sensitive. This research presents a formal sensitivity analysis of hydrological and hydraulic parameters—absolute–relative, relative–absolute, relative–relative sensitivity and R2—applied to an urban basin. The urban basin of Tuxtla Gutiérrez, Chiapas, in Mexico is an area prone to flooding caused by extreme precipitation events. The basin has little information in which the records (with the same time resolution) of precipitation and hydrometry match. The basin model representing an area of 355.07 km2 was characterized in the Stormwater Management Model (SWMM). The sensitivity analysis was performed for eight hydrological parameters and one hydraulic for two precipitation events and their impact on the depths of the Sabinal River. Based on the analysis, the parameters derived from the analysis that stand out as sensitive are the Manning coefficient of impervious surface and the minimum infiltration speed with R2 > 0.60. The results obtained demonstrate the importance of knowing the sensitivity of the parameters and their selection to perform an adequate calibration.

Experimental Study on the Rainfall-Runoff Responses of Typical Urban Surfaces and Two Green Infrastructures Using Scale-Based Models

In this study, scale models of typical urban surfaces and two green infrastructures (concave grassland and porous pavement) were constructed, and two simulated rainfall intensities (low intensity was 0.3 mm/min with 25.4 mm depth, and high intensity was 0.6 mm/min with 42.0 mm) were utilized to investigate their runoff responses and the impacts of pervious surface positions and initial soil moisture on the runoff processes. Results indicated that impervious concrete surface exhibited a faster generation of runoff and with a runoff coefficient of 89%. Grassland surface represented that time to runoff was about 25 times than that of the impervious surface and recorded the smallest runoff coefficient of 34 and 53%. Compared with the impervious area, concave grassland was able to effectively delay time to runoff, while the porous pavement was able to significantly reduce runoff discharge and peak flow rate. A high rainfall intensity led to a reduction in time to runoff and an acceleration of runoff discharge and peak flow rate. Pervious surface under the lower side generated runoff at a slower rate, and registered a smaller runoff coefficient compared with the pervious surface under the upper side. The initial soil moisture and time to runoff had a significant negative correlation, and a positive correlation was found between the initial soil moisture and runoff coefficient. These findings facilitate a better understanding of runoff processes of urban surfaces and green infrastructures that may be able to help in better hydrology system design for mitigating urban flooding.

Approaches to Multi-Objective Optimization and Assessment of Green Infrastructure and Their Multi-Functional Effectiveness: A Review

Green infrastructure (GI) is a contemporary area of research worldwide, with the implementation of the findings alleviating issues globally. As a supplement and alternative to gray infrastructure, GI has multiple integrated benefits. Multi-objective GI optimization seeks to provide maximum integrated benefits. The purpose of this review is to highlight the integrated multifunctional effectiveness of GI and to summarize its multi-objective optimization methodology. Here, the multifunctional effectiveness of GI in hydrology, energy, climate, environment, ecology, and humanities as well as their interrelationships are summarized. Then, the main components of GI multi-objective optimization including the spatial scale application, optimization objectives, decision variables, optimization methods and optimization procedure as well as their relationships and mathematical representation are examined. However, certain challenges still exist. There is no consensus on how to measure and optimize the integrated multi-functional effectiveness of GI. Future research directions such as enhancing integrated multi-objective assessment and optimization, improving life cycle analysis and life cycle cost, integrating benefits of GI based on future uncertainties and developing integrated green–gray infrastructure are discussed. This is vital for improving its integrated multifunctional effectiveness and the final decision-making of stakeholders.

A User-Friendly Software Package to Develop Storm Water Management Model (SWMM) Inputs and Suggest Low Impact Development Scenarios

Increases in imperviousness due to urbanization and industrialization increases stormwater runoff and nonpoint source pollution. Approaches reducing these hydrological impacts include low impact development (LID) methods. Various methods have been developed and applied to date, and an evaluation of stormwater runoff and a reduction of non-point source pollution has been conducted. The Storm Water Management Model (SWMM) is capable of simulating various LID approaches, although selecting and implementing a suitable method for a specific target area, when considering the cost of various low impact development approaches, requires significant time and effort. A software program called Storm Water Management Model–low impact development design program (SWMM-ING), that can be optimally applied to deal with the cost of low impact development methods, was developed in this study. For SWMM-ING, an optimization process was conducted for low impact development, which can reduce stormwater runoff by 10%, suspended solid by 15%, and total phosphorus by 15%. The spatial arrangement and the area of the permeable pavement, bioretention cells, infiltration trenches, and green roofs were determined. Because SWMM-ING has a user-friendly graphical interface, and the optimization process of the low impact development approach is simple and straightforward, it has the advantage of not requiring specialized knowledge.

Does the spatial location of green roofs affects runoff mitigation in small urbanized catchments?

Green roofs have been treated as practical low impact development (LID) strategies to retain stormwater runoff and alleviate the rainfall-induced flooding risks in urban regions. The purpose of this study was to analyze the hydrological effects of the spatial location of green roofs in urbanized catchments. In the built-up region of Beijing, 12 urbanized catchments with various architectural patterns were chosen as the study areas. To distinguish the spatial characteristics of roof surfaces, we defined the effective roof surfaces to distinguish from other types of roofs, which have more convenient or direct hydrological connections to drainage systems. A hydrological model was then used to simulate the stormwater mitigation performance of green roofs for the study catchments, which were assigned to different rainfall conditions. The simulation results confirmed the benefits of implementing green roofs for urban stormwater regulation. However, the spatial variability of green roofs showed inherent influences on the runoff mitigation capacity in urbanized catchments. Greening on effective roof surfaces would provide more effective stormwater regulation benefits, for reductions in both runoff volume and peak flow. In addition, the spatial arrangement characteristics of roof surfaces also influenced the hydrological efficiency of green roofs. The effect of the spatial location of green roofs on runoff mitigation was rainfall-dependent. These findings provide insights into the hydrological role of green roofs, and suggest that proper siting of LID facilities should be a consideration for urban stormwater management in order to fulfill the hydrological efficiency and cost-effectiveness planning target.

Performance assessment of coupled green-grey-blue systems for Sponge City construction

In recent years, Sponge City has gained significant interests as a way of urban water management. The kernel of Sponge City is to develop a coupled green-grey-blue system which consists of green infrastructure at the source, grey infrastructure (i.e. drainage system) at the midway and receiving water bodies as the blue part at the terminal. However, the current approaches for assessing the performance of Sponge City construction are confined to green-grey systems and do not adequately reflect the effectiveness in runoff reduction and the impacts on receiving water bodies. This paper proposes an integrated assessment framework of coupled green-grey-blue systems on compliance of water quantity and quality control targets in Sponge City construction. Rainfall runoff and river system models are coupled to provide quantitative simulation evaluations of a number of indicators of land-based and river quality. A multi-criteria decision-making method, i.e., Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is adopted to rank design alternatives and identify the optimal alternative for Sponge City construction. The effectiveness of this framework is demonstrated in a typical plain river network area of Suzhou, China. The results demonstrate that the performance of Sponge City strategies increases with large scale deployment under smaller rainfall events. In addition, though surface runoff has a dilution effect on the river water quality, the control of surface pollutants can play a significant role in the river water quality improvement. This framework can be applied to Sponge City projects to achieve the enhancement of urban water management.

Investigating Tradeoffs of Green to Grey Stormwater Infrastructure Using a Planning-Level Decision Support Tool

Integrated decision support tools are needed to investigate the tradeoffs of stormwater control measures (SCMs) and determine the optimal suite of SCMs based on the needs of watersheds. In this study, an urbanized watershed undergoing infill development (the Berkeley neighborhood located in Denver, CO, USA) was modeled using a modified version of the U.S. Environmental Protection Agency’s (EPA) System for Urban Stormwater Treatment and Analysis IntegratioN (SUSTAIN). The primary goal was to compare the relative performance between green and grey SCMs, use optimizations and a planning-level approach to assist in decision-making, and discuss how stakeholder and community preferences can shift which SCMs are optimal for the watershed. Green and grey SCMs have variable hydrologic performance based on design and function, and both offer benefits that may be important to decision makers. Our results showed that infiltration trenches and underground infiltration were optimal for reducing flow volumes while vegetated swales and underground detention were optimal for pollutant concentration reduction. Stakeholders value both of these benefits and so the optimal stormwater solution in the Berkeley neighborhood included a mix of green and grey SCMs. Determining the optimal SCMs while considering tradeoffs in costs and associated benefits was complex and multifaceted. Modeling results such as those presented here are critical for informing stakeholders’ decision-making process.

Cost-benefit analysis of low-impact development at hectare scale for urban stormwater source control in response to anticipated climatic change

Investigation of the cost-effectiveness of low-impact development (LID) practices at the hectare scale in response to impacts of possible climate change was conducted using representative concentration pathways (RCPs). An LID project in Guangzhou has been selected to illustrate changes in the hydrologic performance for alternative source control strategies for a variety of future climate models and scenarios. Frequent storms of shorter duration in RCP 8.5 cause more dramatic fluctuation of hydrologic performance. Hydrologic performance of LID practices on reducing runoff volume and peak flow in test catchment are different in climate scenarios. Based on the constraints of life cycle costs and environmental impacts of LID alternatives, comprehensive strategies were found effective in managing surface runoff at the source to adapt to the influence of climate change. The methodology described herein could be useful in considering LID practices for critical source management with limited budgets and considering environmental impacts under long-term climate change.