A comprehensive review of spatial allocation of LID-BMP-GI practices: Strategies and optimization tools

Identifying the optimal type and locations of natural water retention measures using spatial modeling and cost-benefit analysis

Water management has shifted from solely technical and engineering approaches towards nature-based solutions (NBS), like natural water retention measures (NWRM), offering benefits beyond hydrology, such as improved well-being and biodiversity conservation. Determining the best type and location of these measures is challenging due to diverse options with varying benefits and effects depending on measure type and location characteristics. While most studies regarding the optimal allocation and implementation of NBS focus on the urban environment, this study presents a methodology for decision-makers focusing on inter-urban regions with limited data on NWRM implementation. Through hydrological modeling and cost-benefit analysis (CBA), we identify Pareto optimal NWRM sites and types, considering water quantity and quality alongside economic, environmental, and social objectives. We defined optimal locations that seek the most significant reduction of runoff, sediment, and pollutants, whilst optimal NWRM types are defined to seek the most cost-effective measures based on hydrological, ecological, and social criteria. Using the Open Non-point Source Pollution and Erosion Comparison Tool (OpenNSPECT), we simulated increased infiltration in different inter-urban areas and identified the optimal placement. The criteria for selecting suitable NWRM types for the identified areas are derived from the EU Directorate General for the Environment (DG-ENV) NWRM database. The results show different effective areas for reducing runoff, sediment, and pollutants. While one NWRM (natural bank stabilization) was identified as most beneficial for reducing sediment, several measures were selected for runoff reduction. Interestingly, measures with high potential for pollutant reduction seem to offer limited social and biodiversity benefits, suggesting conflicting objectives and highlighting the importance of accounting for multiple criteria. By employing simplified models and qualitative benefit assessments, this paper presents a practical decision-making approach to facilitate NWRM implementation in data-scarce areas.

Spatial allocation of bioretention cells considering interaction with shallow groundwater: A simulation-optimization approach

Green infrastructure (GI), as one type of ecological stormwater management practices, can potentially alleviate water problems and deliver a wide range of environmental benefits in urban areas. GIs are often planned and designed to reduce runoff and mitigate pollution. However, the influence of GI on groundwater hydrology and that of shallow groundwater on GI performance was seldom considered. This study utilized a calibrated surface-subsurface hydrological model, i.e., Storm Water Management Model coupled with USGS's modular hydrologic model (SWMM-MODFLOW) to consider the interaction between GI and groundwater into the process of GI planning. The optimal implementation ratio, aggregation level and upstream-downstream location of bioretention cells (BC, one type of GI) under different planning objectives and hydrogeologic conditions was explored. The consideration of groundwater management exerted a significant impact on the optimal spatial allocation of BCs. The results showed that when groundwater management was more concerned than runoff control, BCs were recommended to be allocated more apart from each other and more upstream in the catchment because more-distributed and upstream BCs can result in lower groundwater table rise which is beneficial. BCs were overall recommended to be allocated in areas of deeper groundwater tables, coarser soils, and flatter topographies. However, the spatial features of BCs are related to each other, the choice of them are affected by various hydrogeologic factors simultaneously. The exact location of BCs should be determined by considering the trade-off between runoff control efficiency and groundwater impact. The findings obtained in this study can provide guidance on GI planning in shallow groundwater areas.

Multi-objective optimization of the spatial layout of green infrastructures with cost-effectiveness analysis under climate change scenarios

Green infrastructure (GI) plays a significant role in alleviating urban flooding risk caused by urbanization and climate change. Due to space and financial limitations, the successful implementation of GI relies heavily on its layout design, and there is an increasing trend in using multi-objective optimization to support decision-making in GI planning. However, little is known about the hydrological effects of synchronously optimizing the size, location, and connection of GI under climate change. This study proposed a framework to optimize the size, location, and connection of typical GI facilities under climate change by combining the modified non-dominated sorting genetic algorithm-II (NSGA-II) and storm water management model (SWMM). The results showed that optimizing the size, location, and connection of GI facilities significantly increases the maximum reduction rate of runoff and peak flow by 13.4 %-24.5 % and 3.3 %-18 %, respectively, compared to optimizing only the size and location of GI. In the optimized results, most of the runoff from building roofs flew toward green space. Permeable pavement accounted for the highest average proportion of GI implementation area in optimal layouts, accounting for 29.8 %-54.2 % of road area. The average cost-effectiveness (C/E) values decreased from 16 %/105 Yuan under the historical period scenario to 14.3 %/105 Yuan and 14 %/105 Yuan under the two shared socioeconomic pathways (SSPs), SSP2-4.5 and SSP5-8.5, respectively. These results can help in understanding the optimization layout and cost-effectiveness of GI under climate change, and the proposed framework can enhance the adaptability of cities to climate change by providing specific cost-effective GI layout design.

Agricultural watershed conservation and optimization using a participatory hydrological approach

Maximizing the impact of agricultural wastewater conservation practices (CP) to achieve total maximum daily load (TMDL) scenarios in agricultural watersheds is a challenge for the practitioners. The complex modeling requirements of sophisticated hydrologic models make their use and interpretation difficult, preventing the inclusion of local watershed stakeholders' knowledge in the development of optimal TMDL scenarios. The present study develops a seamless modeling approach to transform the complex modeling outcomes of Hydrologic Simulation Program Fortran (HSPF) into a simplified participatory framework for developing optimized management scenarios. The study evaluates seven conservation practices in the Pomme de Terre watershed in Minnesota, USA, focusing on sediment and phosphorus pollutant load reductions incorporating farmers' opinions to guide practitioners toward implementing cost-effective CPs. Results show reduced tillage and filter strips are the most cost-effective practices for non-point source pollution reduction, followed by conservation cover perennials. The integration of SAM with HSPF is crucial for sustainable field-scale implementation of conservation practices through enhanced involvement of amateur-modeling stakeholders and farmers directly connected to fields.

Combined sewer overflow mitigation through SUDS - A review on modelling practices, scenario elaboration, and related performances

Hydrologic-hydraulic modelling of urban catchment is an asset for land managers to simulate Sustainable Urban Drainage Systems (SUDS) implementation to fulfil combined sewer overflow (CSO) regulations. This review aims to assess the current practices in modelling SUDS scenarios at large scale for CSO mitigation encompassing every stage of the modelling process from the choice of the equation to the validation of the initial state of the urban system, right through to the elaboration, modelling, and selection of SUDS scenarios to evaluate their performance on CSO. Through a quantitative and qualitative analysis of 50 published studies, we found a diversity of choices when modelling the status quo of the urban system. Authors generally do not explain the modelling processes of slow components (deep infiltration, groundwater infiltration) and interconnexion between SUDS and the sewer system. In addition, only a few authors explain how CSO structures are modelled. Furthermore, the modelling of SUDS implementation at catchment scale is highlighted in the 50 studies retrieved with three different approaches going from simplified to detailed. SUDS modelling choices seem to be consistent with the objectives: studies focusing on dealing with several objectives at the time typically opt for a complex system configuration that includes the surface processes, network, CSO, SUDS, and often the soil and/or groundwater components. Conversely, authors who have selected a basic configuration generally aim to address a single, straightforward question (e.g., which type of SUDS). However, elaboration and selection of scenarios for CSO mitigation is mainly based on local constraints, which does not allow hydrological performance to be directly optimised. In conclusion, to improve current practices in modelling SUDS scenarios at large scale for CSO mitigation, authors suggest to: (i) improve clear practices of CSO modelling, calibration and validation at the urban catchment scale, (ii) develop methods to optimize the performance of scenarios for CSO mitigation using hydrological drivers, and (iii) improve parsimonious and user-friendly models to simulate SUDS scenarios in a context of data scarcity.

Temporal variations in micropollutant inlet concentrations matter when planning the design and compliance assessment of stormwater control measures

Stormwater Control Measures (SCMs) contribute to reducing micropollutant emissions from separate sewer systems. SCM planning and design are often performed by looking at the hydrological performance. Assessment of pollutant removal and the ability to comply with discharge concentration limits is often simplified due to a lack of data and limited monitoring resources. This study analyses the impact of using different time resolutions of input stormwater concentrations when assessing the compliance of SCMs against water quality standards. The behaviour of three indicator micropollutants (MP - Copper, Diuron, Benzo[a]pyrene) was assessed in four SCM archetypes, which were defined to represent typical SCM removal processes. High resolution MP data were extrapolated by using high resolution (2 min) measurements of TSS over a long period (343 events). The compliance assessment showed that high resolution input concentrations can result in a different level of compliance with water quality standards, especially when discharged concentrations are close to the limit values. This study underlines the importance of considering the high temporal variability of stormwater micropollutants when planning and designing SCMs to identify the most effective solutions for stormwater pollution management and to ensure a thorough consideration of all the environmental implications.

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.

Water Sensitive Urban Design (WSUD) Spatial Prioritisation through Global Sensitivity Analysis for Effective Urban Pluvial Flood Mitigation

Water Sensitive Urban Design (WSUD) has attracted growing attention as a sustainable approach for mitigating pluvial flooding (also known as flash flooding), which is expected to increase in frequency and intensity under the impacts of climate change and urbanisation. However, spatial planning of WSUD is not an easy task, not only due to the complex urban environment, but also the fact that not all locations in the catchment are equally effective for flood mitigation. In this study, we developed a new WSUD spatial prioritisation framework that applies global sensitivity analysis (GSA) to identify priority subcatchments where WSUD implementation will be most effective for flood mitigation. For the first time, the complex impact of WSUD locations on catchment flood volume can be assessed, and the GSA in hydrological modelling is adopted for applications in WSUD spatial planning. The framework uses a spatial WSUD planning model, the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), to generate a grid-based spatial representation of catchment, and an urban drainage model, the U.S. EPA Storm Water Management Model (SWMM), to simulate catchment flooding. The effective imperviousness of all subcatchments was varied simultaneously in the GSA to mimic the effect of WSUD implementation and future developments. Priority subcatchments were identified based on their influence on catchment flooding computed through the GSA. The method was tested for an urbanised catchment in Sydney, Australia. We found that high priority subcatchments were clustering in the upstream and midstream of the main drainage network, with a few distributed close to the catchment outlets. Rainfall frequency, subcatchment characteristics, and pipe network configuration were found to be important factors determining the influence of changes in different subcatchments on catchment flooding. The effectiveness of the framework in identifying influential subcatchments was validated by comparing the effect of removing 6% of the Sydney catchment's effective impervious area under four WSUD spatial distribution scenarios. Our results showed that WSUD implementation in high priority subcatchments consistently achieved the largest flood volume reduction (3.5-31.3% for 1% AEP to 50% AEP storms), followed by medium priority subcatchments (3.1-21.3%) and catchment-wide implementation (2.9-22.1%) under most design storms. Overall, we have demonstrated that the proposed method can be useful for maximising WSUD flood mitigation potential through identifying and targeting the most effective locations.

Urban stormwater management at the meso-level: A review of trends, challenges and approaches

Cities worldwide are facing a significant threat of stormwater hazards caused by the increase in extreme downpours and urbanization. Meso-level urban stormwater management focuses on alleviating the detrimental impacts of urban flooding and enhancing water resource utilization at the block or community scale, typically through 1) specific policies and management rules; 2) catchment-scale scenario simulation, optimization and evaluation; 3) the group of stormwater control measures implementation. It may effectively coordinate macro-level urban stormwater management planning and micro-level distributed stormwater control facilities. This study conducts a review of Urban Stormwater Management at Meso-level (USM-M) with a view to research publication trends, citation analysis, geographic spread and subject category, as well as content analysis, including temporal progression and research gaps. The Web of Science database and CiteSpace are used for the bibliometric analysis of 66 articles from 2006 to 2021. The results show that the number of USM-M topic articles generally has an upward trend over the years. Whilst the United States and China are leading research on this topic, the European countries have diverse local research and dense cooperation. Research foci have generally shifted from theoretical frameworks to multi-element subdivided topics and specific technical roadmaps. Moreover, the spatial layout optimization and multi-functional integration are, or will be, potential research directions in terms of enhancing stormwater utilization and co-benefits of USM-M. This systematic review concludes trends, challenges and potential approaches of USM-M, and aims to provide recommendations for researchers and policymakers on the development of a more advanced and comprehensive USM-M.

Optimisation of urban-rural nature-based solutions for integrated catchment water management

Nature-based solutions (NBS) have co-benefits for water availability, water quality, and flood management. However, searching for optimal integrated urban-rural NBS planning to maximise co-benefits at a catchment scale is still limited by fragmented evaluation. This study develops an integrated urban-rural NBS planning optimisation framework based on the CatchWat-SD model, which is developed to simulate a multi-catchment integrated water cycle in the Norfolk region, UK. Three rural (runoff attenuation features, regenerative farming, floodplain) and two urban (urban green space, constructed wastewater wetlands) NBS interventions are integrated into the model at a range of implementation scales. A many-objective optimisation problem with seven water management objectives to account for flow, quality and cost indicators is formulated, and the NSGAII algorithm is adopted to search for optimal NBS portfolios. Results show that rural NBS have more significant impacts across the catchment, which increase with the scale of implementation. Integrated urban-rural NBS planning can improve water availability, water quality, and flood management simultaneously, though trade-offs exist between different objectives. Runoff attenuation features and floodplains provide the greatest benefits for water availability. Regenerative farming is most effective for water quality and flood management, though it decreases water availability by up to 15% because it retains more water in the soil. Phosphorus levels are best reduced by expansion of urban green space to decrease loading on combined sewer systems, though this trades off against water availability, flood, nitrogen and suspended solids. The proposed framework enables spatial prioritisation of NBS, which may ultimately guide multi-stakeholder decision-making, bridging the urban-rural divide in catchment water management.

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.

Spatial allocation of LID practices with a water footprint approach

Urban water problems due to stormwater have been aggravated by the higher frequency of high-intensity precipitation events and the increase of paved surfaces. However, with appropriate stormwater management practices, such as low-impact development (LID), stormwater can provide an additional urban water resources rather than cause damage. This study aims to apply a water footprint to location determination of LID practices in the urban area. The LID planning procedure was demonstrated with the highest population density region in Taipei, Taiwan. In order to improve the spatial resolution of LID allocation, the "first-level dissemination area" with 450 residents was used as a spatial unit. The performance of LID practices was then evaluated with the simulation using the Storm Water Management Model (SWMM). Three LID practices, rainwater harvesting systems, permeable pavements, and bioretention systems, were selected. After the water footprint accounting, ten sites were suggested for LID implementation. The runoff reduction rate reached up to 65 % by rainwater harvesting systems or at least 3 % by permeable pavements. This study provides a simpler and more effective approach to ways of integrating an urban water footprint into LID planning and stormwater management in urban areas.

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.

Designing coupled LID-GREI urban drainage systems: Resilience assessment and decision-making framework

As flooding risks rise in urban areas, research suggests combining low impact development (LID) and grey infrastructure (GREI) in urban drainage systems. Several frameworks have been proposed to plan such coupled systems, but there is not a comprehensive framework to assess their resilience under diverse failure scenarios and sources of uncertainty. This study proposes a framework which considers both technological and operational resilience. Technological resilience has to do with the performance of the system under extreme loads. Operational resilience has to do with the performance and long-term efficiency of the system after structural damage or degradation, using appropriate probability distributions to quantify the likelihood of failures. The proposed framework is based on an optimization and multi-criteria decision-making platform. It improves on previous research, which lacked consideration of uncertainty in resilience over the life span. We also apply the proposed framework to a real-world test case, and find that in a high-density urban area, a coupled system is more cost-effective than GREI alone. Furthermore, decentralized systems with greater flexibility show significantly better technological and operational resilience. The proposed framework can better support decision-making for planning robust and cost-effective urban drainage systems, particularly in highly urbanized areas.

A new LID spatial allocation optimization system at neighborhood scale: Integrated SWMM with PICEA-g using MATLAB as the platform

Despite the growing interest, limited studies have been conducted on LID spatial allocation optimization (SAO) at neighborhood scale, and no study has applied modifications to the optimization algorithm to improve its performance. In this study, such a new LID SAO system was proposed, which integrated a hydrological computing engine (SWMM) with an optimization algorithm (PICEA-g) using a programming language (MATLAB) as the platform. The specific modifications to the PICEA-g algorithm include: new methodologies for initializing candidate solutions, defining goal vector boundaries and enhanced genetic operators. The new LID SAO system was tested in a typical urban residential neighborhood in western Canada, and optimal solutions for LID implementation (bioretention, rain garden, permeable pavement and green roof) were obtained. The results showed that promising hydrologic benefits of reducing peak flow rate and total volume of stormwater runoff from the catchment, can be achieved with a relatively low cost. The LID SAO system provides users with flexibility and feasibility for a variety of drainage locations, scales and objectives (e.g., water quality).

A Multiobjective Spatial Optimization Model of LID Based on Catchment Landuse Type

Aiming to solve the problem of the low efficiency and single objective of low impact development (LID) layout, the objectives of stormwater control, water quality purification, and economic cost are selected to present the performance of LID practices. A novel method of evaluating urban runoff and pollutant concentration is put forward based on the land-use type of each catchment. Shenzhen City is selected as the study area, and three LID scenarios are designed and contrasted for an ideal solution according to their land-use type. The results show that the multiobjective optimization model based on runoff evaluation, pollutant simulation, and investment calculation can be more efficient and can be applied in other areas.

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.

Modeling the Hydrologic Performance and Cost-Effectiveness of LID in a Residential Park Area Using a Decentralized Design Approach

Low Impact Development (LID) is one of the current research interests toward green infrastructures and urban flood control that have the capability to return developed watersheds to pre-development hydrological conditions, bringing numerous water quantity and quality benefits, while being cheaper than their traditional counterparts. However, there is a current research gap about LIDs within tropical regions. This study aims to evaluate the cost efficiency of LID scenarios in varying surface areas through a cost-effectiveness (C/E) analysis and to assess flow reduction and infiltration improvement of the cost-effective LID scenarios using US EPA Stormwater Management Model (SWMM) in a tropical residential catchment receiving an annual rainfall of 1780.5 mm (70.1″), under a Type 1 Philippine Climate. Results have shown that the Weibull plotting position generated the largest rainfall amounts. A total of 2112 manually simulated LID scenarios were modeled to obtain the cost-effective or optimal LID scenarios, where they can generate a maximum of 38.67% flow reduction and 29.73% peak flow reduction, all observed in the multiple LID scenarios. At high rainfall amounts, the multiple LID scenarios can also peak at a 1113% increase in total infiltration in the given sub-catchments. Determining the target capture goal, applicable LID types, and cost estimations from a pilot project are vital components in the future application of LIDs in these regions.

Adaptive pressure-driven multi-criteria spatial decision-making for a targeted placement of green and grey runoff control infrastructures

Traditional runoff control measures ignore the spatial imbalance of regional pressures, thereby failing to achieve a site-specific placement for green and grey infrastructure simultaneously. A multi-criterion decision-making framework for runoff control infrastructure spatial planning was therefore developed in this study. The pressure-state-response framework was applied to creatively match the pressure induced adjustment demands with the infrastructure effectiveness. The pressures were quantified from the perspective of environment, economy, and ecology on a grid scale. States were considered as the relative priority of regional pressure adjustment demand in multiple perspectives. Responses were presented as state-targeted green and grey infrastructure placement. Multi-perspective effectiveness of different green and grey infrastructure was simultaneously evaluated at an effective scale of controlling 1 m³/s runoff for comparison. Methods such as data mining, hydrological model simulation, and remote sensing inversion were combined to quantify the regional pressures. The capital investment and ecological impact of infrastructures were quantified from a life cycle perspective. A case study was carried out in Wuhan, China. The study area was clustered by gridded pressure into three regions. In region Ⅰ, ecological and environmental pressure were of higher weight. In region Ⅱ, the environmental pressure was dominant. In region Ⅲ, the ecological pressure took precedence over the environmental and economic constraints. The area ratios of the region Ⅰ, Ⅱ, and Ⅲ were 43%, 36%, and 21% respectively. The result indicated a synergy and spatial heterogeneity of multi-perspective pressures, and further demonstrating that expert experience tends to fail to weigh the multi-function of green and grey infrastructures for coping with the pressures. Results also stated that green infrastructures were more acceptable in areas that aspire to achieve simultaneous runoff control and ecological improvement. The decision-making framework developed in this study can maximize the overall performance by providing targeted infrastructure placement solutions.

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.

Assessment of the Impact of Loss-of-Retention Fees on Green Infrastructure Investments

Urbanization leads to the growth of impervious surfaces, which increases surface runoff, causing pluvial and flash flood phenomena. Furthermore, it significantly limits the infiltration of stormwater into the ground; this, in turn, reduces groundwater supply, ultimately intensifying drought effects. In order to adapt urbanized areas to climate change, the objective is to stop these unfavorable processes and strive for recreating the natural water cycle through developing decentralized stormwater management practices on private properties. An important management instrument that motivates property owners to invest is economic incentives, such as stormwater or impact fees associated with a system of rebates/discounts that depend on the applied stormwater runoff reduction solutions. Herein, we analyze a new economic instrument—a fee for reducing natural field retention—which is planned to be introduced in Poland. We assessed the incentive and funding (income-generating) function of the fee based on the example of the Sudół river catchment in Krakow, Poland. The research involved conducting simulation calculations and assessing the incentive impact through calculating investment Net Present Value (NPV), which is the investor’s response to the proposed economic incentives included in the structure of the fee and the rebate system. This study demonstrated errors and loopholes in the suggested fee rules—too low rates that prevent achieving profitability (negative NPV) for small-scale stormwater retention practices, and incorrect conditions that enable obtaining discounted fees. We also estimated the fee rate that ensures investment profitability.

Sustainable Urban Drainage System (SUDS) modeling supporting decision-making: A systematic quantitative review

Decision Support Systems (DSS) for Sustainable Urban Drainage Systems (SUDS) are a valuable aid for SUDS widespread adoption. These tools systematize the decision-making criteria and eliminate the bias inherent to expert judgment, abridging the technical aspect of SUDS for non-technical users and decision-makers. Through the collection and careful assessment of 120 papers on SUDS models and SUDS-DSS, this review shows how these tools are built, selected, and used to assist decision-makers questions. The manuscript classifies the DSS based on the question they assist in answering, the spatial scale used, the software selected, among other aspects. SUDS-DSS aspects that require more attention are identified, including environmental and social considerations, SUDS trains performance and criteria for selection, stochasticity of rainfall, and future scenarios impact. Suggestions for SUDS-DSS are finally offered to better equip decision-makers in facing emerging stormwater challenges in urban centers.

Hybrid Approach for Excess Stormwater Management: Combining Decentralized and Centralized Strategies for the Enhancement of Urban Flooding Resilience

Urban sprawl and soil sealing has gradually led to an impervious surface increase with consequences on the enhancement of flooding risk. During the last decades, a hybrid approach involving both traditional storm water detention tanks (SWDTs) and low-impact development (LID) has resulted in the best solution to manage urban flooding and to improve city resilience. This research aimed at a modeling comparison between drainage scenarios involving the mentioned hybrid approach (H-SM), with (de)centralized LID supporting SWDTs, and a scenario representative of the centralized approach only involving SWDTs (C-SM). Results highlighted that the implementation of H-SM approaches could be a great opportunity to reduce SWDTs volumes. However, the performances varied according to the typology of implemented LID, their parameterization with specific reference to the draining time, and the rainfall severity. Overall, with the increase of rainfall severity and the decrease of draining time, a decrease of retention performances can be observed with SWDTs volume reductions moving from 100% to 28%. In addition, without expecting to implement multicriteria techniques, a preliminary cost analysis pointed out that the larger investment effort of the (de)centralized LID could be, in specific cases, overtaken by the cost advantages resulting from the reduction of the SWDTs volumes.

Identifying Key Sites of Green Infrastructure to Support Ecological Restoration in the Urban Agglomeration

The loss and fragmentation of natural space has placed tremendous pressure on green infrastructure (GI), especially in urban agglomeration areas. It is of great importance to identify key sites of GI, which are used to economically and efficiently restore urban ecological network. However, in the existing research, few scholars have explored the identification and application of GI key sites. Taking the Southern Jiangsu Urban Agglomeration as an example, based on the ecosystem service assessment and landscape connectivity analysis, we identified the multi-class key sites of GI in the study area by MSPA, InVEST model, MCR model, and Linkage mapper. The results showed that: (1) a total of 60 GI sources and 130 GI corridors were extracted. The ecological resources of the study area were densely distributed in the north and south and sparsely in the middle. (2) Three-hundred eighty GI key sites were identified, including 53 water ecological points, 251 ecological fracture points, and 76 ecological pinch points. The GI key sites we identified were large in number and widely distributed, yet were hardly included in the existing ecological protection policies. These key sites should be prioritized in GI planning and differentiated for management strategies, ensuring that limited land resources and public funds can be directed to where restoration is really needed. The present study provides land managers and urban planners with additional tools to better understand how to effectively restore and develop the ecosystems of urban agglomerations in the context of scarce land resources.

Identification of ecological networks and nodes in Fujian province based on green and blue corridors

China's Green Space System Planning (GSSP) research has gradually expanded from central urban areas to municipal and provincial scales in recent years. Besides, the research on the role of green space in the water environment has also attracted much attention. However, the study of green corridors usually ignored hydrological data, which widespread absence especially in the large area scale. And the scale of green corridor construction mainly focused on central urban areas. This paper took China's Fujian province as an example. Based on the DEM elevation data, the article identified blue corridors without hydrological data. In addition, the green corridors were determined based on the land use data. According to the green corridors and blue corridors protection, we identified the ecological networks and nodes by the network analysis method. The results showed that the blue corridors identified by DEM data were consistent with the hydrological status quo. The regional status of the identified ecological networks and nodes were basically in line with their characteristics, proving the value of the planning methods. Finally, based on the identification results, suggestions for Fujian's ecological networks and nodes are put forward.

Web of Science-Based Green Infrastructure: A Bibliometric Analysis in CiteSpace

Many cities worldwide are using re-greening strategies to help reverse urbanization patterns that aggravate environmental issues. Green infrastructure (GI) has become a significant and effective strategy to address environmental problems. To better understand GI, this study uses CiteSpace to analyze 5420 published papers in the field of GI on the Web of Science database from 1990-2020. This bibliometric analysis will help new scholars and researchers to better understand the current status and trends in GI research, as well as identify further research needed in the field. This study evaluated research on GI trends according to publication amounts, keywords, journals, disciplines, countries, institutions, and authors. Results show that, first, GI research has experienced rapid growth since 2014. Second, GI, ecosystem services, and city are the top three keywords related to GI research, with green roof as the keyword with the strongest linkage. Third, Sustainability, Urban Forestry and Urban Greening, and Landscape and Urban Planning are the top three journals publishing GI research. Fourth, the top three disciplines researching GI are environmental science, engineering, and science and technology. Fifth, the USA is the top ranked country in terms of the number of published GI-related papers (1514 papers), followed by China (730 papers) and England (546 papers). Sixth, the US Environmental Protection Agency (84 papers) is the top institution in terms of publications, followed by the Chinese Academy of Science (83 papers) and the Swedish University of Agriculture (66 papers). Finally, D. Haase has the most published articles (29 papers), followed by S. Pauleit (28 papers) and P. Angelstam (26 papers). These findings indicate that GI has developed significantly in the last 30 years, with a high probability for increased growth in the future.

Incorporating stakeholders' preferences into a multi-criteria framework for planning large-scale Nature-Based Solutions

Hydro-meteorological risks are a growing issue for societies, economies and environments around the world. An effective, sustainable response to such risks and their future uncertainty requires a paradigm shift in our research and practical efforts. In this respect, Nature-Based Solutions (NBSs) offer the potential to achieve a more effective and flexible response to hydro-meteorological risks while also enhancing human well-being and biodiversity. The present paper describes a new methodology that incorporates stakeholders' preferences into a multi-criteria analysis framework, as part of a tool for selecting risk mitigation measures. The methodology has been applied to Tamnava river basin in Serbia and Nangang river basin in Taiwan within the EC-funded RECONECT project. The results highlight the importance of involving stakeholders in the early stages of projects in order to achieve successful implementation of NBSs. The methodology can assist decision-makers in formulating desirable benefits and co-benefits and can enable a systematic and transparent NBSs planning process.

Regenerating Sponge City to Sponge Watershed through an Innovative Framework for Urban Water Resilience

In recent years, cities universal are advocating ‘resilience’ in terms of water-related challenges. Accompanied by the development of sponge city construction, several emerging stormwater management practices are prevailing worldwide. This paper proposes a regenerative argument for sponge city construction from the urban scale towards the watershed scale by strengthening the urban water resilience and sustainability. An innovative framework is established to address urban water issues and human livability via 20 conventional and advanced indicators and the interrelations between the modules of water resilience, water resource, water treatment, water ecology, waterscape, and water management. Six representative cities from the sponge city construction pilot in South China have been selected, and the compatibility and divergence between their guidelines and the sponge watershed framework are revealed through pair analyses and parameter calculation. The diverse perspectives behind the scores have been discussed carefully, and the successful experiences of excellent cities are systematically summarized and promoted. The analyses and findings in this research have significant methodological implications for shifting the sponge city practice towards linking urban development with watershed ecological conservation. The proposed framework and strategies provide a reference for an integrated solution of watershed health and wellbeing in the next generation sponge city practice.

Low-cost biomonitoring and high-resolution, scalable models of urban metal pollution

As the global toll on human lives and ecosystems exacted by urban pollution grows, planning tools still lack the resolution to identify priority sites where toxic pollution can be most efficiently averted at a spatial scale that matches funding and management. Here we tackle this gap by demonstrating novel scalable methods to monitor and predict urban metal pollution at high resolution (<5 m) across large areas (10,000-100,000 km²) to guide pollution reduction and stormwater management. We showcase and calibrate predictive models of Zn, Cu, and a synthetic index of pollution for the Puget Sound region of Washington State, U.S., a densely urbanized yet important ecosystem of conservation interest, and exemplify their transferability across the entire United States. We leveraged widely and freely available datasets of car traffic characteristics and land use as predictor variables and trained the models with biological monitoring data of metal concentrations in epiphytic moss from >100 trees based on new rapid and low-cost protocols introduced in this study. Our model predictions, showing that 50% of the total Cu and Zn pollution across the Puget Sound watershed is deposited over only 3.3% of the land area, will allow cities to effectively and efficiently target toxic hotspots.

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.

A rapid fine-scale approach to modelling urban bioclimatic conditions

Surface characteristics play a vital role in simulations for urban bioclimatic conditions. Changing relationships and distribution patterns of sealed and vegetated surfaces as well as building geometry across different scales in urban environments influence surface temperatures. Cities comprise different urban forms, which, depending on their surface characteristics, enhance the heating process, increasing the emergence of urban heat islands (UHIs). Detecting priority areas to introduce multi-beneficial climate change adaptation measures is set to be a key task for the cities long-term strategies to improve climatic conditions across different urban structures and scales. We introduce a simple and fast spatial modelling approach to carry out fine-scale simulations for land surface temperature (LST), mean radiant temperature (MRT) and Universal Thermal Climate Index (UTCI) in a 2D environment. Capabilities of our modelling approach are demonstrated in evaluating urban thermal comfort in the alpine city of Innsbruck, the capital of Tyrol in western Austria. Results show a major contrast between sealed and vegetated surfaces reflected in the distributional patterns and values of LST, MRT and UTCI, correlating with the appearance and frequency of specific surface classes. We found the Sky View Factor to have a substantial impact on calculations for bioclimatic conditions and see high-albedo surfaces decrease LST but increase the apparent temperature (MRT and UTCI values) effecting human thermal comfort. Furthermore, MRT and UTCI are more sensitive to changes in emissivity values, whereas LST is more sensitive to changes in Bowen Ratio values. Application of our modelling approach can be used to identify priority areas and maximise multi-functionality of climate change adaptation measures, to support urban planning processes for heat mitigation and the implementation of policy suggestions to achieve sustainable development goals and other political objectives.

Social Barriers and the Hiatus from Successful Green Stormwater Infrastructure Implementation across the US

Green stormwater infrastructure (GSI), a nature-inspired, engineered stormwater management approach, has been increasingly implemented and studied especially over the last two decades. Though recent studies have elucidated the social benefits of GSI implementation in addition to its environmental and economic benefits, the social factors that influence its implementation remain under-explored thus, there remains a need to understand social barriers on decisions for GSI. This review draws interdisciplinary research attention to the connections between such social barriers and the potentially underlying cognitive biases that can influence rational decision making. Subsequently, this study reviewed the agent-based modeling (ABM) approach in decision support for promoting innovative strategies in water management for long-term resilience at an individual level. It is suggested that a collaborative and simultaneous effort in governance transitioning, public engagement, and adequate considerations of demographic constraints are crucial to successful GSI acceptance and implementation in the US.

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.

Assessing the Effectiveness and Cost Efficiency of Green Infrastructure Practices on Surface Runoff Reduction at an Urban Watershed in China

Studies on the assessment of green infrastructure (GI) practice implementation effect and cost efficiency on an urban watershed scale helps the GI practice selection and investment decisions for sponge city construction in China. However, few studies have been conducted for these topics at present. In this study, the Long-Term Hydrologic Impact Assessment—Low Impact Development (L-THIA-LID) 2.1 model was applied to assess the effectiveness and cost efficiency of GI practices on surface runoff volume reduction in an urban watershed—the Hexi watershed, Nanjing City, China. Grassed swales, bioretentions, green roofs, rain cisterns, permeable pavements, wet ponds, dry ponds, and wetlands were chosen as potential GI practices for sponge city construction based on feasibility analysis. Results showed that grassed swales were the most cost-effective practice (0.7 CNY/m3/yr), but the total implementation effect of grassed swales was not obvious due to the small area of suitable locations. Permeable pavements performed best on runoff reduction, but the cost efficiency was much lower. Correspondingly, bioretentions were compromise practices. Green roofs were the least cost-effective practices, with the cost efficiency at 122.3 CNY/m3/yr, but it was much lower for rain cisterns, which were 3.2 CNY/m3/yr. Wet ponds, dry ponds, and wetlands were potential practices implemented in development areas, of which dry ponds were the most cost-effective (2.7 CNY/m3/yr), followed by wet ponds (10.9 CNY/m3/yr). The annual runoff volume of the total area could be reduced by up to 47.01% by implementing GI practices in buildup areas. Rain cisterns (RC) and permeable pavements (PP) were the best combination for this area, and bioretentions (BR) and green roofs (GR) followed. Grassed swales (GS1), dry ponds (DP), wet ponds (WP), and wetlands (WL) were not wise choices due to the small suitable location areas. This study also demonstrated the feasibility of the L-THIA-LID 2.1 model for the evaluation of GI practice implementation effects and cost efficiency on urban runoff in sponge city construction in China.

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.

China's sponge city development for urban water resilience and sustainability: A policy discussion

China recently introduced a national policy initiative called sponge city development as a holistic, ecosystem-based approach integrated with urban planning and development to address storm-induced pluvial flooding as well as other urban water and environmental issues. The initiative, while following the U.S. low impact development with a concept also similar to the U.K. sustainable drainage systems and Australian water sensitive cities, is subject to a major design issue in practice with infrastructure projects of similar types adopted unanimously across regions despite spatially diverse and heterogeneous hydrological and biophysical conditions. The ecosystem services framework as applied to the urban setting, particularly its holistic consideration of ecosystem structure and management intervention in relation to services or benefits delivery, can and should guide the planning, design, development, and evaluation of relevant projects or nature-based practices for carrying out the policy initiative, a perspective of practical value with foreseeable transformative impact that has received little recognition in China's current green urban movement toward water resilience and sustainability.

A spatial planning-support system for generating decentralised urban stormwater management schemes

Current Water Sensitive Urban Design (WSUD) models are either purely technical or overly simplified, lacking consideration of urban planning and stakeholder preferences to adequately support stakeholders. We developed the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), which integrates stormwater management with urban planning to support the design and implementation of WSUD. This study specifically describes and tests UrbanBEATS' WSUD Planning Module, which combines spatial analysis, infrastructure design, preference elicitation and Monte Carlo methods to generate feasible stormwater management and harvesting infrastructure options in greenfield and existing urban environments. By applying UrbanBEATS to a real-world greenfield development case study in Melbourne, Australia (with data sourced from the project's water management plans and design consultants), we explore the variety of options generated by the model and analyse them collectively to demonstrate that UrbanBEATS can design similar WSUD systems (e.g. select suitable technology types, their sizes and locations) to actual infrastructure choices.

Prioritization of stormwater management sites in urban areas

Multiple pressures as urbanization, densification and climate change lead to the need for adaptation of sewer systems within urban environments. To increase the adaptive capacity of stormwater management systems, there is a shift towards decentralized nature-based solutions (NBS). Especially in densely built areas the availability of land can be a limiting factor for the implementation of NBS. To consider the spatial framework conditions in planning we developed an integrated modelling framework for prioritizing sites for NBS implementation for stormwater management within built urban structures. The implementation potential of NBS from a settlement structure model and a street typology model are combined with the discharge reduction potential from a sewer model. In effectiveness matrices priorities for stormwater management sites for individual NBS are identified. This modelling framework offers a transparent and flexible approach to decision making for the implementation of NBS.

Analyzing Evidence of Sustainable Urban Water Management Systems: A Review through the Lenses of Sociotechnical Transitions

Sustainability concerns and multiple socio-environmental pressures have necessitated a shift towards Sustainable Urban Water Management (SUWM) systems. Viewing SUWM systems as sociotechnical, this paper departs from eight factors previously identified by transition research: Pressures, Context, Purposes, Actors, Instruments, Processes, Outputs, and Outcomes as a methodological framework for a structured review of 100 articles. The study seeks to analyze empirical cases of planning and implementing SUWM systems worldwide. A wide range of public actors—driven by social and environmental factors rather than by economic pressures—have initiated SUWM projects so as to locally fulfill defined social and environmental purposes. We provide evidence on the emergence of new actors, such as experts, users, and private developers, as well as on the diverse and innovative technical and societal instruments used to promote and implement SUWM systems. We also explore their contexts and institutional capacity to deal with pressures and to mobilize significant financial and human resources, which is in itself vital for the transition to SUWM. Planned or implemented SUWM outputs are divided into green (wet ponds, raingardens, and green roofs) and gray (rain barrels and porous pavements) measures. The outcomes of SUWM projects—in terms of societal and technical learning, and their institutional uptakes—are often implicit or lacking, which seemingly reduces the rate of desirable change.

A Heuristic Method for Determining Changes of Source Loads to Comply with Water Quality Limits in Catchments

A common land and water management task is to determine where and by how much source loadings need to change to meet water quality limits in receiving environments. This paper addresses the problem of quantifying changes in loading when limits are specified in many locations in a large and spatially heterogeneous catchment, accounting for cumulative downstream impacts. Current approaches to this problem tend to use either scenario analysis or optimization, which suffer from difficulties of generating scenarios that meet the limits, or high complexity of optimization approaches. In contrast, we present a novel method in which simple catchment models, load limits, upstream/downstream spatial relationships and spatial allocation rules are combined to arrive at source load changes. The process iteratively establishes the critical location (river segment or lake) where the limits are most constraining, and then adjusts sources upstream of the critical location to meet the limit at that location. The method is demonstrated with application to New Zealand (268,000 km²) for nutrients and the microbial indicator E. coli, which was conducted to support policy development regarding water quality limits. The model provided useful insights, such as a source load excess (the need for source load reduction) even after mitigation measures are introduced in order to comply with E. coli limits. On the other hand, there was headroom (ability to increase source loading) for nutrients. The method enables assessment of the necessary source load reductions to achieve water quality limits over broad areas such as large catchments or whole regions.

The Low-Impact Development Demand Index: A New Approach to Identifying Locations for LID

The primary goal of low impact development (LID) is to capture urban stormwater runoff; however, multiple indirect benefits (environmental and socioeconomic benefits) also exist (e.g., improvements to human health and decreased air pollution). Identifying sites with the highest demand or need for LID ensures the maximization of all benefits. This is a spatial decision-making problem that has not been widely addressed in the literature and was the focus of this research. Previous research has focused on finding feasible sites for installing LID, whilst only considering insufficient criteria which represent the benefits of LID (either neglecting the hydrological and hydraulic benefits or indirect benefits). This research considered the hydrological and hydraulic, environmental, and socioeconomic benefits of LID to identify sites with the highest demand for LID. Specifically, a geospatial framework was proposed that uses publicly available data, hydrological-hydraulic principles, and a simple additive weighting (SAW) method within a hierarchical decision-making model. Three indices were developed to determine the LID demand: (1) hydrological-hydraulic index (HHI), (2) socioeconomic index (SEI), and (3) environmental index (ENI). The HHI was developed based on a heuristic model using hydrological-hydraulic principles and validated against the results of a physical model, the Hydrologic Engineering Center-Hydrologic Modeling System model (HEC-HMS). The other two indices were generated using the SAW hierarchical model and then incorporated into the HHI index to generate the LID demand index (LIDDI). The framework was applied to the City of Toronto, yielding results that are validated against historical flooding records.

Hybrid green-blue-gray decentralized urban drainage systems design, a simulation-optimization framework

Recent studies suggested hybrid green-blue-gray infrastructures (HGBGI) as the most promising urban drainage systems that can simultaneously combine reliability, resilience, and acceptability of gray infrastructures (networks of pipes) with multi-functionality, sustainability, and adaptability of green-blue infrastructures (GBI). Combining GBI and gray measures for designing new urban drainage systems forms a nonlinear multimodal mixed integer-real optimization problem that is highly constrained and intractable. For this purpose, this study presents a simulation-optimization framework to optimize urban drainage systems considering HGBGI alternatives and different degrees of centralization. The proposed framework begins with the characterization of the site under design and drawing the base graph. Then, different layouts with different degrees of centralization are generated and hydraulically designed using a recent algorithm called hanging gardens algorithm. After introducing the feasible GBI to the model, we now perform second optimization to find the optimum distribution of GBIs in a way that minimizes total life cycle costs of GBIs and pipe networks. Finally, resiliency and sustainability of different scenarios are evaluated using several design storms that provide material for final assessment and decision-making. The performance of the proposed framework is evaluated using a real large-scale case study, a part of the city of Ahvaz in Iran. Finally, results are presented and discussed with recommendations for future studies.

Governance factors of sustainable stormwater management: A study of case cities in China and Sweden

Cities worldwide are increasingly using green infrastructure to mitigate challenges related to stormwater, in an approach regarded as sustainable stormwater management (SSM). Various governance factors have been identified as one of the major barriers to SSM implementation. In this study, we examined specific governance factors influencing local SSM implementation in four case cities in Sweden and China. Based on systems thinking, we first developed a general causal loop diagram (SSM-CLD) illustrating the interrelations between previously identified influencing governance factors in SSM. We then used this general SSM-CLD as a framework to conduct and analyze 23 semi-structured interviews with local government officers in the four case cities. Based on the analysis, we summarized the most frequently mentioned governance factors and created one SSM-CLD for each case city. We then examined the main differences between the local SSM-CLDs and the general SSM-CLD, and the differences between the Chinese and Swedish case cities. The results revealed that, in the two Chinese case cities, the role of national policy in setting local leaders' priorities, the strong organizational set-up, and planning instruments are significant for SSM implementation. In the two Swedish case cities, public awareness, local government politicians' priorities, and trust in SSM performance are important for SSM implementation. Acquiring funding for long-term maintenance of SSM was identified as a common challenge in all four cities studied. These results provide a better understanding and potential lessons for other cities on how governance factors influence SSM.

Optimal adaptation pathway for sustainable low impact development planning under deep uncertainty of climate change: A greedy strategy

Robustness and cost effectiveness are major concerns for sustainable stormwater management under deep uncertainty of climate change. Given that many traditional static planning strategies are not working with unpredictable future conditions, the possibility of system failure, and the lock-in effects, the Adaptation Pathway (AP) approach was adopted for dynamically robust and cost-effective planning in this paper. In order to increase optimization accuracy of multi-staged planning, a continuous definition of the AP optimization problem was raised by improving the simplified versions in existing studies. A case study in Suzhou, a provincial pilot Sponge City in China undergoing increasing annual rainfall and severe water environment deterioration, was included by integrating Long-Term Hydrologic Impact Assessment-Low Impact Development model with optimization methods, aiming to persistently control the non-point source total phosphorus loading below an acceptable amount in the following unforeseen 20 years via multi-staged low-impact development (LID) construction. A novel optimization method developed by the authors in a companion paper, namely marginal-cost-based greedy strategy (MCGS), was successfully applied to efficiently solve the continuous version of the AP optimization problem. The popular genetic algorithm (GA) was used as a contrast. A weather generator was elaborated based on four Representative Concentration Pathway scenarios and 17 spatial downscaled general circulation models to simulate the unforeseen future annual rainfalls that helped with evaluating cost effectiveness of each prospective LID plan. Results showed that the adaptation pathways optimized by MCGS could save the whole life net present cost of an LID plan by 1%-60% compared with those optimized by GA, and the computational efficiency of MCGS was over 13 times faster than GA.

Urban stormwater characterization, control, and treatment

This review summarizes over 250 studies published in 2018 related to the characterization, control, and management of urban stormwater runoff. The review covers three broad themes: (a) quantity and quality characterization of stormwater, (b) control and treatment of stormwater runoff, and (c) implementation and assessment of watershed-scale green stormwater infrastructure (GSI). Each section provides an overview of the 2018 literature, common themes, and future work. Several themes emerged from the 2018 literature including exploration of contaminants of emerging concern within stormwater systems, characterization and incorporation of vegetation-driven dynamics in stormwater control measures, and the need for interdisciplinary perspectives on the implementation and assessment of GSI. PRACTITIONER POINTS: Over 250 studies were published in 2018 related to the characterization, control, and treatment of stormwater. Studies cover general stormwater characteristics, control and treatment systems, and watershed-scale assessments. Trends in 2018 include treatment trains, vegetation dynamics, and interdisciplinary perspectives.

Understanding the synergistic effect between LID facility and drainage network: With a comprehensive perspective

In recent years, low impact development (LID) has been deemed as an effective strategy for better storm water management. Among tremendous literature concerning the effectiveness of LID facilities to improve urban drainage system (UDS) performance, the scale, location, variety, and parameters of LIDs are fully discussed while the role of urban drainage network is rarely considered. Since LIDs and drainage network work together to realize the function of UDS, this research aims to explore their synergistic effects on the social, environmental, and technological performance of UDS. To represent different synergistic effects, a case area in Kunming, China is divided into upstream, midstream, and downstream sections. The hydraulic and topological characteristics of the drainage network in different sections are varied and 4 LID siting strategies are designed to distribute LID facilities in one of the 3 sections or in the total catchment evenly. Uncertainties from rainfall intensity and LID distribution are discussed as well. Based on the modeling results, the existence of synergistic effect is confirmed. Different spatial relationships between LIDs and the drainage network lead to disparate UDS performance. The synergistic effect may appear as the aggravation or mitigation of the conflicts among various functions of UDS, such as the reduction of urban flooding, combined sewer overflow, and shock loadings to wastewater treatment plant. The synergistic effect is sensitive to the rainfall intensity, suggesting the necessity of system performance investigation under non-design conditions. Due to the complicated synergistic effect, even distribution of LIDs in the target area can be a regretless and simplified solution. The discoveries reveal the significance of the synergistic effect and its implications for the LID planning.

Evaluation of the effectiveness of green infrastructure on hydrology and water quality in a combined sewer overflow community

Evaluation of the effectiveness of green infrastructure (GI) practices on improving site hydrology and water quality and their associated cost could provide valuable information for decision makers when creating development/re-development strategies. In this study, a watershed scale rainfall-runoff model (the Long-Term Hydrologic Impact Analysis - Low Impact Development model, the L-THIA-LID 2.1 model) was enhanced to improve its simulation of urban water management practices including GI practices. The enhanced model (L-THIA-LID 2.2) is capable of: simulating in more detail impervious surfaces including sidewalks, roads, driveways, and parking lots; conducting cost calculations for converting these impervious surfaces to porous pavements; and, selecting suitable areas for bioretention in the study area. The effectiveness of GI practices on improving hydrology and water quality in a combined sewer overflow urban watershed-the Darst Sewershed in the City of Peoria, IL-was examined in eleven simulation scenarios using 8 practices. The total cost and the cost effectiveness for each scenario considering a 20-year practice lifetime were calculated. Results showed: combined implementation of GI practices performed better than applying individual practices alone; adoption levels and combinations of GI practices could potentially reduce runoff volume by 0.2-23.5%, TSS by 0.18-30.8%, TN by 0.2-27.9%, and TP by 0.2 to 28.1%; adding more practices did not necessarily achieve substantial runoff and pollutant reductions based on site characteristics; the most cost-effective scenario out of eleven considered had an associated cost of $9.21 to achieve 1 m³ runoff reduction per year and $119 to achieve 1 kg TSS reduction per year assuming residents' cooperation in implementing GI practices on their properties; adoption of GI practices on all possible areas could potentially achieve the greatest runoff and pollutant reduction, but would not be the most cost-effective option. This enhanced model can be applied to different locations to support assessing the beneficial uses of GI practices.

Green infrastructure practices simulation of the impacts of land use on surface runoff: Case study in Ecorse River watershed, Michigan

As an urban fringe district, the Ecorse River watershed is faced with increased impervious area caused by urban expansion. Effects of Green Infrastructure (GI) practice implementation were simulated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 model (L-THIA-LID 2.1). Suitable locations of each GI practice were identified, based on construction condition requirements and demand on GI practices in the study area. Using the data of 2011, various GI practice combination scenarios were explored according to the cost-efficiency of each GI practice. GI practice implementation scenarios in 2050 were also simulated based on projected land use and rainfall data. Results show that grassed swales, rain barrels (residential areas) and dry ponds were the top three most cost-efficient GI practices, with the cost at $1.5/m³/yr, $3.0/m³/yr and $3.4/m³/yr, respectively. Green roofs with rain cisterns (industrial and commercial area) were the most expensive GI practices, with the cost at $92.9/m³/yr. With the increase of investment in GI practices, the changing curves of the annual runoff volume, Total Nitrogen (TN) load and Total Phosphorus (TP) load reduction ratios match the law of diminishing marginal utility. The scenario with grassed swales, rain barrels, dry ponds and porous pavement would be the most cost-efficient scenario for runoff water quantity reduction. In addition, the scenario with additional wet ponds would be the most cost-efficient one for TN load and TP load reduction. GI practices in each scenario for expected 2050 conditions show better effectiveness on water quantity and quality management.