Urban Runoff Management Research Articles

Optimal low-impact development Facility Design in Urban Environments: A multidimensional optimization approach employing slime mould and nondominated sorting genetic algorithms

This study presents the application of the slime mould algorithm (SMA) and the nondominated sorting genetic algorithm II (NSGA-II) to optimize low-impact development (LID) strategies in urban areas. The focus is on minimizing costs and improving water quality, using three LID practices (vegetated swales, bioretention systems, and porous pavements) in combination with a drainage system. The effectiveness of this stormwater management model (SWMM)-SMA-NSGA-II model is demonstrated in Tehran, Iran, where bioretention is found to be the most successful approach for improving water quality. The results also show that the SMA outperforms the NSGA-II in optimizing cost-effective LID solutions and is more computationally efficient, potentially due to its crossover operator. This research highlights the importance of considering qualitative aspects of urban runoff management. The study demonstrates that the combination of multiple LID strategies and the use of SMA and NSGA-II have the potential to achieve optimal solutions for managing stormwater in urban areas.

Flood adaptation impacts of blue-green infrastructure through hydrosocial framework.

Modern dualisms between society and nature affect understandings of “what water is?” and “how water fits into society?”, according to the hydrosocial cycle concept. Understanding the urban stormwater system within the tensions inherent in designing flood-resilient cities is crucial from a social, cultural, and ecological perspective. Therefore, it is essential to comprehend how the hydrosocial cycle altered the use of blue-green infrastructure over time and how these modifications reflect the values of urban waterscapes and urban flood adaptation. The purpose of this paper is to discuss and analyse historical and contemporary perspectives on correlations between the hydrosocial cycle and blue-green infrastructure networks, which are beneficial to water-sensitive urban design principles. A comprehensive literature review and comparative analysis of two case studies of waterscape impact on public space based on the hydrosocial framework were used to conduct the research. This study employs comparative case studies to evaluate the implementation of the hydrosocial cycle by examining the dynamics of social power and structure, technology and infrastructure, and the materiality of water at each respective site. The results of this study indicate that urban landscape and engineering systems that are influenced by ecological and social values are advantageous to the current state of flood adaptation and urban runoff management. The comparison demonstrated that the implementation of blue-green infrastructure that incorporates the symbiotic values of society and nature offers opportunities for urban flood adaptation. In a nutshell, the integration of the hydrosocial cycle in the context of reducing flood susceptibility contributes to the enhancement of the existing framework by incorporating an analysis of societal interactions and utilisation of urban waterscapes, alongside a transition towards urban flood adaptation.

Long-term Environmental Performance of Stormwater Biofiltration Sorption Media in Sustainable Drainage Systems (SuDS)

In this climate impacted world, there is an increasing need for countries facing potential water extremes to improve the reuse potential of grey water and storm water. By implementing best management practices for the treatment of stormwater and urban run-off, contaminants can be removed, and the water recycled and reused. The effectiveness of stormwater treatment is impacted by the clogging of equipment or where contaminant storage exceeds performance design. Poorly or untreated stormwater runoff can impact the environment through the release of total dissolved solids (TDS), suspended solids (turbidity), phosphate, ammonia, and elevated chemical and biochemical oxygen demand (COD and BOD, respectively). This study evaluated the hydraulic and environmental performance of gravity flow stormwater filters over a three-year period with the average filter life cycle four months. Six bespoke gravity stormwater filters employing sorbent pillows, and including peat moss, were tested for their effectiveness, including for nitrite and nitrate. An improvement in water quality of 80-98% was recorded. Oil and grease were managed effectively (peat moss and sorbent pillows reduced BOD, COD, color, and turbidity) but not significantly when compared to conventional filter media. The findings demonstrate that stormwater biofilters can be an innovative, low-cost, and sustainable solution for both urban and sub-urban runoff management, addressing water quality and resource quantity challenges.

Investigating the performance of pervious concrete pavement to clogging control for urban runoff management

Investigating the performance of pervious concrete pavement to clogging control for urban runoff management

Development and Research Regarding Stormwater Runoff Management: Bibliometric Analysis from 2001 to 2021

As a result of climate change and urbanization, human activities are placing increasing pressure on nature, including with regard to urban stormwater runoff; consequently, various concepts related to urban stormwater runoff management have been proposed to tackle this problem in multiple countries. In this study, the latest research and techniques related to stormwater runoff management are reviewed in detail. A bibliometric analysis of proposed stormwater runoff management concepts developed from 2001 to 2021 was conducted based on a screening of 1771 studies obtained from the Web of Science (WoS). Bibliometric analysis is a research method that can be used to quantitatively analyze academic literature. Visualization of the data obtained from the literature using CiteSpace software and subsequent analysis of patent data through S-curve prediction were performed. The United States, China, and Australia were the top three countries from which publications on this issue were sourced. Each country tends to study its own most relevant issues and has a particularly clear understanding of its own research landscape. The development of stormwater runoff management concepts was analyzed using reference emergence analysis. This was followed by keyword clustering and keyword emergence analysis to identify current research hotspots, trends, technological developments, and limitations. The limitations and emerging trends related to current stormwater runoff management concepts are discussed thoroughly, and suggestions for future studies are provided.

THE FIRST FLUSH ANALYSIS OF STORMWATER RUNOFF IN A HUMID CLIMATE

This study focuses on the pollutants from urban runoff to Zarjoob River, which is one of the rivers leading to Anzali International Wetland, which was listed in the Montreux Record in 1993 as a site in need of priority conservation. Storm water runoff from a residential area in Rasht (the largest city on Iran’s Caspian Sea coast) was monitored in this study during thirteen rainfall events, with a total of 58 storm runoff samples collected from 2018 to 2019. In most rainfall events, the mean concentration of total suspended solids (TSS) and chemical oxygen demand (COD) were higher than the other pollutants. The event mean concentrations (EMC) of TSS loads ranged from 57.3 mg/L to 682.5 mg/L and from 46.7 mg/L to 590.4 mg/L for COD. The site mean concentrations (SMC) for TSS, COD, total phosphorus (Total P), nitrate-nitrogen (NO3-N), and total lead (Pb) were 219, 205, 1.91, 20.63, and 0.25 mg/L, respectively. The first flush coefficient (b) was used to evaluate the first flushing of various events. The results of the study confirmed that the first flush occurred in all events, and the average ranking of first flush strength among the pollutants was COD > NO3-N > TP > Pb > TSS. Controlling one-third of the initial runoff volume appeared to be critical for managing the quality of urban rivers in humid regions. The findings of this study can be applied to urban runoff management strategies in cities with similar climatic conditions.

Optimization of Locations for Bioswales Stormwater Management Using BMP Siting Tool - Case Study of Sulaymaniyah City-KRG-Iraq

Today, urban Stormwater management is one of the main concerns of municipalities and stakeholders. Drought and water scarcity made rainwater harvesting one of the main steps toward climate change adaptation. Due to the deterioration of the quality of urban runoff and the increase of impermeable urban land use, the treatment of urban runoff is essential. Best Management Practice (BMP) and Low Impact Development (LID) approaches are necessary to combat climate change consequences by improving the quantity and quality of water resources. The application of Bioswales along urban streets and roadways can reduce the stress on water resources, recharge groundwater and prevent groundwater pollution. While Sulaymaniyah City has a combined sewer network, the application of Bioswales makes wastewater treatment possible in all seasons. This study aimed to determine suitable locations for LID as one of the methods of urban runoff management in Sulaymaniyah City, KRG Iraq. The research modeled and optimized the placement of Bioswales using the BMP Sitting Tool (BST) in the ArcGIS program. Results of the study suggested a total area of 104329 m2 in 530 locations for the installation of the Bioswale system. Also, results showed that land use parameters and soil hydrological groups could be considered important factors in selecting a suitable location for Bioswale system establishment.

Multi-stakeholder stochastic optimization of urban low impact developments for climate consistency under uncertainty

Sustainable management of urban floods can prevent damage to the city's infrastructure. In particular, low-impact developments (LIDs) collect and reuse urban stormwaters and mitigate their destructive effects. This study aims to optimize the design of urban LIDs in terms of location and surface area, considering the climatic parameters and model uncertainties. Accordingly, the urban runoff quality and quantity, in addition to the climatic parameters and their uncertainties were analyzed in the modeling by repeated execution of a rainfall-runoff model in MATLAB. Then, using the concept of conditional value at risk, the uncertainty risk consideration was incorporated in the optimal design of the LIDs. Using a non-cooperative game model, stakeholders' priorities were also considered in selecting the best design scenario. In comparison with the baseline scenario (no LID, maximum runoff quantity, and worst runoff quality), the selected scenario decreased runoff volume, and two quality indicators (i.e., total suspended solids (TSS) and biochemical oxygen demand (BOD)) by (56.1–64.6%), (22.1–27.1%), and (13.7–19.2%), respectively. This scenario is the best arrangement of LIDs (location and surface area) in different sub-basins that satisfies stakeholders' priorities. The novelty of this study lies in integrating uncertainty with social complexities in a sustainable quantitative and qualitative urban runoff management using a risk-based stochastic optimization and a flexible conflict resolution model. Incorporating conflict resolution concepts in LIDs design prevents wastage of time and money and facilitates achieving socioecological implications such as ecosystem services, neighborhood aesthetics, recreational spaces, and enhancing land values. The suggested methodology was tested in the Velenjak region, northern Tehran.

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.

Global Sensitivity Analysis-based Design of Low Impact Development Practices for Urban Runoff Management Under Uncertainty

Global Sensitivity Analysis-based Design of Low Impact Development Practices for Urban Runoff Management Under Uncertainty

A simplified geospatial model to rank LID solutions for urban runoff management

Studies have shown the usefulness of low impact development (LID) in runoff management in urban areas; however, there is a limited number of systematic decision-making models for ranking LID solutions (i.e., the location and type of LID required). This research proposes a physics-based GIS Multi Criteria Decision Making model (GIS-MCDM), which we refer to as the LID Solution Evaluation and Ranking ApproacH (SERAH). This model integrates the hydrological and socioeconomic-environmental benefits of LID with the subcatchment-level demand of LIDs – this has been traditionally overlooked in previous research. Specifically, SERAH integrates key the contributing criteria, including LID benefits, cost, feasibility, and subcatchment demand to rank LID solutions. To demonstrate the applicability of SERAH, a highly urbanized catchment in Toronto was used as a case-study and three types of LID: rain gardens, infiltration trenches, and porous pavements were considered. The hydrological performance of the ranked solutions was estimated using the stormwater management model, PCSWMM. The resulting LID ranking from SERAH corresponded to the best hydrological performance and LID co-benefits. Runoff volumes were reduced by 8.9–11.3%, and peak runoff values were reduced by 1.3–19.9% compared to the base scenario. The infiltration trench was ranked the highest in 16 of the 19 subcatchments where the cost was identified as a key factor. For the remaining three subcatchments, the rain garden was ranked the highest due to its socioeconomic-environmental benefits outweighing the higher cost. The effect of different rainfall durations, frequencies, and temporal patterns on the performance of the highest-ranked LID solution suggested that LID provide higher performance (runoff volume reduction) in more severe events. SERAH is useful for strategic planning for sustainable infrastructure. Future research is needed to better quantify the socioeconomic and environmental benefits of LID to improve SERAH.

Multi-objective optimization for stormwater management by green-roofs and infiltration trenches to reduce urban flooding in central Delhi

Urban surface runoff management via best management practices (BMP) and low impact development (LID) has earned significant recognition owing to positive environmental and ecological impacts. However, due to the complexity of the parameters involved, the estimation of LID efficiency in attenuating the urban surface runoff at the watershed scale is challenging. A planning analysis of employing Green Roofs and Infiltration Trenches as BMPs/LIDs practices for urban surface runoff control is presented in this study. A multi-objective optimization decision-making framework is established by coupling SWMM (Storm Water Management Model) with NSGA-II models to check the performance of BMPs/LIDs concerning the cost-benefit analysis of LID at the watershed scale. Two urbanized areas belonging to Central Delhi in India were used as case studies. The results showed that the SWMM model is useful in simulating optimization problems for managing urban surface runoff. The optimum scenarios efficiently minimized the urban runoff volume while maintaining the BMPs/LIDs implementation costs and size. With BMPs/LIDs implementation, the reduction in runoff volume increases as expenses increase initially; however, there is no noticeable reduction in flood volume after a certain threshold. Contrasted with the haphazard arrangement of BMPs/LIDs, the proposed approach demonstrates 22%–24% runoff reductions for the same expenditures in watershed 1 and 23%–26% in watershed 2. The result of the study provides insights into planning and management of the urban surface runoff control with LID practices. The proposed framework assists the hydrologists in optimum selection and placements of BMPs/LIDs practices to acquire the most extreme ecological advantages with the least expenses.

Permeable Reactive Concrete Using Recycled Waste Materials for Nutrient Contamination Removal in Urban Surface Runoff

In recent years, stormwater control measures (SCMs) such as permeable concrete pavement have been experimentally investigated and used to manage hydrologic and water quality impacts of stormwater runoff. Research revealed the potential of permeable pavement in reducing and delaying peak flow rate, reducing runoff volume, and capturing heavy metals and other particulate-bound pollutants from stormwater runoff. However, few studies have evaluated the effects of permeable pavement on nutrients in stormwater runoff. This research aims to produce permeable reactive concrete (PRC) from waste fly ash, waste gypsum board and waste coco peat and to investigate its effectiveness in removing nutrient contamination present in stormwater or urban surface runoff. The raw materials underwent through granulation process to produce granulated filtering media (GFM). Cylindrical samples of PRC were then made and subjected to various physical and water quality tests. The use of GFM as partial coarse aggregates of PRC for urban surface runoff management and nutrient contamination removal has been tested and evaluated. After performing all the tests, the researchers concluded that GFM as partial coarse aggregates of PRC is effective due to the significant increase in infiltration rate of the entire sample compared to the traditional permeable concrete that has an average infiltration rate of 2-6 mm/s. The results in the water quality test revealed that PRC with GFM as partial coarse aggregates lessen the nitrate, phosphate, and ammonia that are present on urban surface runoff.

Developing an urban runoff management model by using satellite precipitation datasets to allocate low impact development systems under climate change conditions

Developing an urban runoff management model by using satellite precipitation datasets to allocate low impact development systems under climate change conditions

Vegetated roofs for managing stormwater quantity in cold climate

Vegetated roofs, i.e. green roofs, were continuously measured for runoff to quantify their capacity to manage stormwater in a field experiment in southern Finland, with distinct seasonality and varying weather conditions. Attention was paid to heavy storms to study the potential in mitigating urban flooding. In addition, the impact of biochar amendment (10% v/v) on rainfall retention was studied. Meadow vegetation was established on crushed brick based substrate either by introducing plants as seedlings and seeds or by using pre-grown readymade mats. Annual retention varied from 40% to 70%. The highest retention, ca. 80%, was found in summer even though it was the rainiest season. Wintertime retention was 30–40%. The coarse substrate enabled infiltration even when frozen and, thus, the roofs operated also in winter. Heavy storms occurred mainly in summer, the season with the highest hydrologic performance of the roofs, resulting in >80% peak attenuation and slow release of runoff. In individual rain events, runoff from meadow roofs was largely a function of rainfall depth. However, retention was weakly explained by the amount of rainfall or by other variables, such as rainfall intensity or antecedent dry period, indicating the difficulty in capturing the complex phenomena behind variable weather conditions. Biochar improved retention only slightly, at maximum by ca. 10%. The empirical evidence of this study highlights vegetated roofs as a feasible technology to be applied in urban runoff management even in cold climate.

Integrating socioecological indexes in multiobjective intelligent optimization of green-grey coupled infrastructures

Ecological conservation is an important objective in urban runoff management today. Maintaining a sustainable ecological system is as equally important a task as to ensure the safety of drainage systems and runoff management cost control. Thus, the socioecological influences of runoff control infrastructure are innovatively included in a uniform evaluation framework with the control functions and capital investments in this study. These indexes are quantified through hydrological model simulation, life cycle cost analysis, and life cycle assessment. Traditional grey infrastructure and rapidly developing green infrastructure for runoff control are optimized simultaneously. For the trade-off between multiobjectives and configurations of multi-infrastructures, nondominated sorting genetic algorithm-II is utilized to achieve automatic optimization of runoff control infrastructure scale, thereby avoiding the dilemma where manually arranged schemes cannot perform optimally. This multiobjective intelligent optimization is applied to a sponge city pilot region in Wuhan, China, and trade-offs are made in the Pareto optimal solution set. A breakthrough is claimed in quantifying the respective contribution of green and grey infrastructures to the optimal scenario in terms of runoff control function, cost input, and socioecological influence. For socioecological influence, the paybacks can meet the investment in the aspect of toxicity health hazard, pathogenic matter, global warming, terrestrial acidification, and water eutrophication (average socioecological paybacks are 2.0, 2.1, 2.9, 1.9, and 2.1 times to the investments respectively). Results prove the necessity of considering multiobjective optimization and green-grey couple infrastructures in a uniform framework.

Bridging the Form and Function Gap in Urban Green Space Design through Environmental Systems Modeling

Using a case study approach from past projects in Singapore, Australia, Cambodia, Thailand and Vietnam, we examine the benefits, but also some of the challenges, to implementing green space in urban design. Green space can have multiple physical and psychological wellbeing benefits, as well as environmental benefits, including urban runoff quantity and quality management, urban heat island abatement, air quality improvement, and noise reduction. Water sensitive urban design (WSUD) can be an important element of green space design and here we explore how modeling of ecosystem services and dynamic modeling of WSUD can help to facilitate sound planning and management decision making in support of green space implementation. As we illustrate with examples for Australia, Singapore and Cambodia, we believe that application of an urban ecosystem services modeling approach can elucidate environmental benefits of urban green space that otherwise may not be considered. Engineers may include dynamic modeling of WSUD in support of an urban master plan, or urban redevelopment, but generally urban planners are less conversant in applying models. We discuss some of the challenges to integrating multidisciplinary visioning and modeling of green space design and performance evaluation through our experience with a stormwater and wastewater design study for Cha Am, Thailand, that included landscape architecture and engineering classes at Thammasat University, Mahidol University, and AIT. Through a case study of Phnom Penh, we illustrate how modeling and 3D visualization can be used to effectively explore the benefits of green space. We conclude that a user-friendly decision support system is needed to integrate modeling and visualization tools and thereby bridge the gap between form and function in urban green space design.

Enhanced removal of heavy metals and phosphate in stormwater filtration systems amended with drinking water treatment residual-based granules

To address the clogging issues in stormwater filtration systems, a drinking water treatment residual (DWTR)-based granule (DBG) substrate was developed herein by pyrolyzing and granulating the DWTR with bentonite and corncob. Toxicity characteristic leaching procedure studies indicated that fabricating into DBG stabilized the Al and heavy metals in DWTR and restrained the leaching risk. Then the removal performance of phosphate (PO₄-P) and heavy metal ions by the DWTR and DBG was evaluated in batch and laboratory-scale column experiments. Results from batch tests showed that the amount of Pb(Ⅱ) adsorbed by DBG (18.47 ± 0.56 mg g⁻1) was approximately 2.3 times of that adsorbed by DWTR (8.05 ± 0.19 mg g⁻1), whereas the PO₄-P adsorption capacity of DBG (8.63 ± 0.24 mg g⁻1) was much lower than that of DWTR (25.33 ± 0.81 mg g⁻1). This could be ascribed to the addition of corncob and bentonite (at a mass ratio of 20% and 40% in DBG, respectively), which provided extremely high cation exchange capacity for the Pb(Ⅱ) adsorption, while no effective PO₄-P adsorption component was involved. Moreover, the pyrolysis process could improve the Pb(Ⅱ) and PO₄-P adsorption capacity of the raw-mixture by 42% and 7%, whereas granulation process decreased those of the pyrolysis-mixture by 15% and 20%, respectively, owing to the reduction of accessible surface area in the DBG. Under various stormwater runoff conditions, the involvement of DBG in stormwater filtration systems exerted consistently fancy performance of Cu(Ⅱ), Pb(Ⅱ), Cd(Ⅱ) and PO₄-P removal, with average removal rates of over 86.20% and desorption rates of less than 3.50%, indicating irreversible and strong complexion between the contaminants and DBG. The DBG column manifested good permeability and stable hydraulic conductivity (2.74–2.52 m d⁻1) over a 54-day rainfall period, which was beneficial to address the clogging issue of DWTR. Overall, this study provides an alternative pathway to enhance the hydraulic condition and treatment performance of the stormwater filtration systems for urban runoff management.

Remotely Operated Water Surface Cleaner

Eight million tons of plastic debris is being dumped every year in the ocean, most of them come from beach tourists, urban and storm runoff, sewer overflows and inadequate waste management. Plastic waste encourages the growth of pathogens in the ocean, which is affecting marine life very badly, making many water species endangered and jeopardizing the natural ambience of marine life. Marine debris is disrupting the entire bio-geo cycle giving rise to unwanted problems to the whole marine eco-system. Floating vessel with robust technology is needed to clean our rivers, dams, and lakes. For that purpose, we have developed a vehicle that can collect plastic lying on the surface of the water. It is operated wirelessly and has a long-range wireless connection. A camera is mounted on top of the vehicle to see things around by using concepts of control systems and communication systems. There is a small opening in front of the vehicle to collect plastic from the surface of the water. After collecting plastic or debris, it disposed near the surface. Our proposed cleaner is convenient and can be operated easily by anyone with little hardware knowledge. By using just the flat design of the vehicle, it can float on the surface of the water and a brain to control the vehicle. The integration of all technical things is seamless and intuitive.

Optimizing green infrastructure placement under precipitation uncertainty

• Green Infrastructure (GI) practices are low cost, low regret strategies that can contribute to urban runoff management. • Stochastic programming models are used to determine the optimal placement of GI practices under precipitation uncertainties. • A novel scenario generation process is used to efficiently evaluate the impact of precipitation on the entire watershed system under various combinations of GI practice placement. • Optimal GI placement in an urban watershed of a mid-sized city in the US can contribute to up to 9.5% reduction in total expected runoff, given a limited budget of 25 million dollars. • Using a stochastic programming model with perturbed parameters reduces the computational times, without compromising the solution quality. • Accounting for sub-catchment-level runoff reduction considerations can increase resilience against precipitation uncertainty. Increased urbanization, infrastructure degradation, and climate change threaten to overwhelm stormwater systems across the nation, rendering them ineffective. Green Infrastructure (GI) practices are low cost, low regret strategies that can contribute to urban runoff management. However, questions remain as to how to best distribute GI practices through urban watersheds given precipitation uncertainty and the variable hydrological responses to them. We develop stochastic programming models to determine the optimal placement of GI practices across a set of candidate locations in a watershed to minimize the total expected runoff under medium-term precipitation uncertainties. Specifically, we first develop a two-stage stochastic programming model. Next, we reformulate this model using perturbed parameters to reduce the requisite computational time and extend it to multi-stage. In addition, we introduce constraints that allow for incorporating sub-catchment-level runoff reduction considerations. We account for hydrological connectivity in the watershed using an underlying acyclic connectivity graph of sub-catchments and incorporate various practical considerations into the models. In addition, we develop a systemic approach to downscale the existing daily precipitation projections into hourly units and efficiently estimate the corresponding hydrological responses. These advancements are brought together in a case study for an urban watershed in a mid-sized city in the U.S., where we perform sensitivity analyses, evaluate the importance of the considered constraints, and provide insights.