Storm Water Management Model: Performance Review and Gap Analysis

New optimization strategies for SWMM modeling of stormwater quality applications in urban area

Build-up/wash-off models were originally developed for small-scale laboratory facilities with uniform properties. The effective translation of these models to catchment scale necessitates the meticulous calibration of model parameters. The present study combines the Mat-SWMM tool with a genetic algorithm (GA) to improve the calibration of build-up and wash-off parameters. For this purpose, Mat-SWMM was modified to equip it with the capacity to provide comprehensive water quality analysis outcomes. Additionally, this research also conducts a comparative examination of two distinct types of objective functions in the optimization. Rather than depending on previous literature, this study undertook a numerical campaign to ascertain an appropriate range for the relevant parameters within the case study, thereby ensuring the optimization algorithm's efficient functionality. This research also implements an integrated event calibration approach, i.e., a novel method that calibrates all rainfall events collectively, thus improving systemic interaction representation and model robustness. The findings indicate that employing this methodology significantly enhances the reliability of the outcomes, thereby establishing a more robust procedure. The first objective function (TSS instantaneous less squared difference function, OF 1), which is widely employed in the literature, was designed to minimize the difference between observed and predicted instantaneous Total Suspended Solids (TSS) concentrations. In contrast, the second function (mass and mass peak consistency function, OF 2) considers integral model outputs, i.e., the overall mass balance, the time of the peak mass flow rate, and its intensity. The analysis of the outputs revealed that both objective functions demonstrated sufficient performance. OF 1 provided slightly better performance in predicting the TSS concentrations, whereas OF 2 demonstrated superior ability in capturing global event characteristics. Notably, the optimal parameter set identified through OF 2 aligned with the physically plausible ranges traditionally recommended in technical manuals for urban catchments. In contrast, OF 1's optimal set necessitated an expansion in the acceptable parameter ranges. Finally, from a computational burden viewpoint, OF 1 demanded a significantly higher number of function evaluations, thus implying an escalating computational cost as the range expands. Conversely, OF 2 necessitated fewer evaluations to converge toward the optimal solution.

Implementing constructed wetlands for nutrient reduction at watershed scale: Opportunity to link models and real-world execution

The negative effects of nutrient pollution in streams, rivers, and downstream waterbodies remain widespread global problems. Understanding the cost-effectiveness of different strategies for mitigating nutrient pollution is critical to making informed decisions and defining expectations that best utilize limited resources, which is a research priority for the US Environmental Protection Agency. To this end, we modeled nutrient management practices including residue management, cover crops, filter strips, grassed waterways, constructed wetlands, and reducing fertilizer in the upper East Fork of the Little Miami River, an 892 km2 watershed in southwestern Ohio, United States. The watershed is 64% agriculture with 422 km2 of row crops contributing an estimated 71% of the system's nutrient load. The six practices were modeled to treat row crop area, and among them, constructed wetlands ranked highest for their low costs per kilogram of nutrient removed. To meet a 42% phosphorus (P) reduction target for row crops, the model results suggested that the runoff from 85.5% of the row crop area would need to be treated by the equivalent of 3.61 km2 of constructed wetlands at an estimated cost of US$2.4 million annually (or US$48.5 million over a 20-year life cycle). This prompted a series of projects designed to understand the feasibility (defined in terms of build, treatment, and cost potential) of retrofitting the system with the necessary extent of constructed wetlands. The practicalities of building this wetland coverage into the system, while leading to innovation in unit-level design, has highlighted the difficulty of achieving the nutrient reduction target with wetlands alone. Approximately US$1.2 million have been spent on constructing 0.032 km2 of wetlands thus far and a feasibility analysis suggests a cost of US$38 million for an additional 0.409 km2. However, the combined expenditures would only achieve an estimated 13% of the required treatment. The results highlight the potential effectiveness of innovative design strategies for nutrient reduction and the importance of considering realistic field-scale build opportunities, which include accounting for acceptance among landowners, in watershed-scale nutrient reduction simulations using constructed wetlands.

Parameterization of nutrients and sediment build-up/wash-off processes for simulating stormwater quality from specific land uses

Urbanization changes land cover through the expansion of impermeable surfaces, leading to a significant rise in runoff, sediment, and nutrient loading. The quality of stormwater is related to land use and is highly variable. Currently, stormwater is predominantly described through watershed models that rely minimally, if at all, on field monitoring data. The simple event mean concentration (EMC) wash-off approach by land use is a common method for estimating urban runoff loads. However, a major drawback of the EMC approach is it assumes concentration remains constant across events for a specific land use. Build-up/wash-off equations have been formulated to consider variations in concentration between events. However, several equation parameters are challenging to estimate, making them difficult to use. We conducted a monitoring and modeling study and investigated the impact of land use on stormwater quantity and quality and optimized and investigated the build-up/wash-off parameters for three homogenous urban land uses to estimate nutrients (nitrogen and phosphorus) and sediment loads. Stormwater from commercial, medium-density residential, and transportation land uses was sampled using automatic samplers during storm events, and water quality was characterized for a variety of them for 14 months. Analysis of stormwater samples included assessments for total nitrogen, total phosphorus, and total suspended solids. Results showed that medium-density residential land use had the highest median total nitrogen and total phosphorus event mean concentrations and commercial had the highest median total suspended solids EMCs. Water quality parameters (or build-up/wash-off parameters) exhibited significant variation between land uses, confirming that land use is a key determinant of stormwater quality. The median particle size for each land use was less than 150 μm, indicating that the most common particle size in stormwater was a very fine sand or smaller. This small size should be considered by stakeholders in the design of stormwater treatment systems.

Do baseline assumptions alter the efficacy of green stormwater infrastructure to reduce combined sewer overflows?

Green stormwater infrastructure (GSI) is growing in popularity to reduce combined sewer overflows (CSOs) and hydrologic simulation models are a tool to assess their reduction potential. Given the numerous and interacting water flows that contribute to CSOs, such as evapotranspiration (ET) and groundwater (GW), these models should ideally account for them. However, due to the complexity, simplified models are often used, and it is currently unknown how these assumptions affect estimates of CSOs, GSI effectiveness, and ultimately planning guidance. This study evaluates the effect on estimates of CSOs and GSI effectiveness when different flows and hydrologic processes are neglected. We modified an existing EPA SWMM model of a combined sewer system in Switzerland to include ET, GW, and upstream inflows. Historical rainfall data over 30 years are used to assess volume and duration of CSOs with and without three types of GSI (bioretention basins, permeable pavements and green roofs). Results demonstrate that neglect of certain flows in modelling can alter CSO volumes from -15 % to 40 %. GSI effectiveness also varies considerably, resulting in differences in simulated percent of CSO volume reduced from 8 % to 35 %, depending on the GSI type and modeled flow or process. Representation of GW within models is particularly crucial when infiltrating GSI are present, as CSOs could increase in certain subcatchments due to higher GW levels from increased infiltration. When basing GSI planning decisions on modeled estimates of CSOs, all relevant hydrologic processes should be included to the extent possible, and uncertainty and assumptions should always be considered.

Experimental surface runoff hydrographs from linear impervious subcatchments for rainfalls of extremely high intensity

This study focuses on lab-scale experimental runoff hydrographs from a linear completely impervious plane subcatchment. An improved method of surface runoff physical modelling was developed, allowing for expanded laboratory hydrograph simulations up to a linear scale of 10. Model rains of different intensities and durations were applied, and digital online data processing techniques were employed to ensure high time resolution and accurate flow rate determination. The experimental hydrographs were analyzed in a dimensionless form to facilitate generalization and comparison with widely used nonlinear reservoir method and unit hydrograph method. Wave-like fluctuations of the flow rate were observed in most experimental hydrographs as they approached the maximum runoff. The dimensionless phase time of the experimental hydrographs showed an increasing trend with higher rainfall intensity, and a power-law equation was derived to approximate this relationship. An averaged dimensionless runoff hydrograph was obtained by processing individual hydrographs, and it was approximated by the DR-Hill-Zerobackground model for the initial stage during the rainfall and by the Weibull model for the later stage, after the rainfall stopped. The findings of this study have significant implications for modelling surface runoff from small urban subcatchments, particularly under critical rainfall events with extremely high intensity.

Road criticality assessment to improve commutes during floods

Flooding undermines the functionality of road links, leading to commute disruption, such as increased commuting time and immobility. Therefore, identifying the critical roads under different flood scenarios is of great significance for transportation planning to minimize flood risk. Previous studies on the road criticality under pluvial floods have focused on mostly structural characteristics of the roads, lacking the quantification of the flood impact on traffic. We employed an integrated framework coupling pluvial flood modeling with commute simulation to assess the criticality of flooded road links under three scenarios (10, 30, and 50 year floods). The output of the flood modeling was used to reconstruct the road network. The routes of each individual commuter under a business as usual (BAU) scenario and three flood scenarios were obtained from the commute simulation. As the flood return period increased, the distribution of traffic flow became more uneven. The road criticality assessment revealed that greater flood impact on roads was closely related to the proximity of water bodies, low-lying topography, and greater commute demands of the region and provided evidence to prioritize locations for interventions. This study helps understand the resilience of transportation systems during floods, thereby enabling practitioners to design effective strategic plans in terms of emergency response, risk management, and urban planning.

Using SWMM for emergency response planning: A case study evaluating biological agent transport under various rainfall scenarios and urban surfaces

To assist in emergency preparedness for a biological agent terrorist attack or accidental pathogen release, potential contaminant levels and migration pathways of spores spread by urban stormwater were evaluated using a Storm Water Management Model (SWMM) of U.S. Coast Guard Base Elizabeth City, North Carolina. The high temporal-spatial resolution SWMM model was built using spore concentrations in stormwater runoff from asphalt, grass, and concrete collected from a point-scale field study. The subsequent modeled contamination scenarios included a notional plume release and point releases mimicking the field study under three rainfall conditions. The rainfall scenarios included a 6-hour natural rainfall event on Dec. 8, 2021 and two design storms (2-year and 100-year events). The observed spore concentrations from asphalt and concrete from the actual field experiment were applied to calibrate the washoff parameters in the SWMM model, using an exponential washoff function. The calibrated washoff coefficient (c₁) and exponent (c₂) were 0.01 and 1.00 for asphalt, 0.05 and 1.45 for grass, and 2.45 and 1.00 for concrete, respectively. The calibrated SWMM model simulated spore concentrations in runoff at times and magnitudes similar to the field study data. In the point release modeled scenario, the concrete surface generated 55.6% higher average spore concentrations than asphalt. Similarly, in the field experiment, a 175% (p < 0.05) higher average spore concentration in surface runoff was observed from concrete than from asphalt. This study demonstrates how SWMM may be used to evaluate spore washoff from urban surfaces under different precipitation amounts, intensities, and durations, and how visualized spatial migration pathways in stormwater runoff may be used for emergency planning and remediation.

How to simulate future scenarios of urban stormwater management? A novel framework coupling climate change, urbanization, and green stormwater infrastructure development

Climate change, urbanization, and green stormwater infrastructure (GSI) planning policies lead to uncertainties in future urban sustainability. Coupling multiple influencing factors such as climate change, urbanization, and GSI development, this study proposes a novel framework for simulating future scenarios of urban stormwater. Subsequently, the changes in annual surface runoff and runoff pollutants in Shanghai's new and old urban areas were compared and analyzed based on 35 typical future and seven baseline scenarios. The following results were obtained: 1) The runoff control rate of the new urban area was significantly higher than that of the old urban area before GSI construction. After GSI construction, both areas could control stormwater runoff and pollutants, while the decline in efficiency in GSI facilities enormously impacted the old area. 2) Surface runoff in the new urban area was mainly affected by urbanization, while climate change was a major factor in the old urban area; runoff pollutants in new and old urban areas were mainly affected by urbanization, and the change in pollutants in new areas was more pronounced. 3) GSI facilities were unlikely to guarantee the quantity and quality of water resources, especially in scenarios where the efficiency of GSI facilities decreases. In old urban areas, the more extreme climate change and urbanization were, the more significant the effect of improving stormwater management facilities. Our findings showed that future studies on stormwater management should specifically consider the different characteristics of new and old urban regions, pay attention to the maintenance and management of GSI facilities, and build adaptive strategies to cope with climate change, urbanization, and GSI facility destruction.

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.

Effectiveness of Design and Implementation Alternatives for Stormwater Control Measures Modeled at the Watershed Scale

To evaluate the effectiveness of dispersed stormwater control measures (SCMs), it is important to consider groundwater-surface water interactions and their consequences for stream hydrologic responses relevant to channel geomorphic stability and ecology. This study aimed to evaluate the effectiveness of different SCM design scenarios and implementation alternatives on exceedance levels and volumes of streamflow at the watershed scale. For this purpose, a process-based block-connector model of Sligo Creek, an urban watershed (29 km2) in the suburbs of Washington, DC, was used to study the effects of SCM system design on the stream hydrograph. The watershed has 34% impervious area (IA), which was discretized into 14 similar-sized subwatersheds, each consisting of pervious and impervious surface areas. Each subwatershed was compartmentalized with the representative overland flow, unsaturated flow, groundwater blocks, and links to main channel segments. The model was calibrated and validated to existing conditions using a 3-year time series of observed flow data. Afterward, a predevelopment simulation was configured. Three SCM unit designs and IA diversions through the SCM retrofit system were simulated. The three unit design scenarios represented a simple pond with surface storage and overflow or SCMs that infiltrate with an engineered soil layer and with or without an underdrain pipe. Differences among the model simulations were evaluated using flow exceedance probability curves. The area of the SCM system was modeled as 5% of the IA retrofit. Three implementation levels, including 10%, 50%, and 90% of the IA diverted through SCMs, were considered for each SCM unit design. The results showed that at least a 50% retrofit of runoff from IA watershedwide would be needed to achieve similar predevelopment base flows and peak flows. Intermediate flows could not be matched but were closest for the infiltration with the underdrain pipe design scenario. It was also found that concentrating the SCMs in the lower portion of the watershed resulted in more effectively achieving the predeveloped exceedance curves than uniform SCM implementation. The results are relevant to planning-level decisions that depend on effectiveness predictions of different SCM unit designs and implementation alternatives in developed watersheds.

Evaluation of climate change, urbanization, and low-impact development practices on urban flooding

The Personal Computer Storm Water Management Model was used in this study to evaluate the potential impacts of climate change, urbanization, and low-impact developments (LIDs) on urban flooding in Robe town, Ethiopia. To achieve the objective, four scenarios were developed in order to simulate changes in peak runoff, inundated volume, and the performance of existing drainage systems. The findings revealed that as urbanization increased from 10% to 70%, the inundated volume of nodes and peak runoff increased from 35,418 to 52,118 × 10³ m³ and 89.4-111.96 m³/s, respectively. Furthermore, the peak runoff in response to climate change is increased by 46.9%, 34.8%, and 37.5%, respectively, as a result of the Rossby Centre Regional Climate Model version 4 (RCA4), Regional Atmospheric Climate Model (RACMO22T), and the hydrostatic version of the regional model (REMO2009). Overall, the findings showed that existing drainage systems were unable to collect and convey the amplified inundation from different simulated scenarios, and the Welmel sub-city to roundabout was threatened by increased flooding, causing significant damage to properties and infrastructure. The implemented LIDs are capable of reducing the expected peak runoff, flooding magnitude, and flooded junctions in climate change and urbanization scenarios; however, combining both mitigation measures can further reduce the study area. The implementation of a mitigation strategy with adequate drainage systems will be required to mitigate the flooding risks in Robe town.

Generate_SWMM_inp: An Open-Source QGIS Plugin to Import and Export Model Input Files for SWMM

SWMM is an open-source model and software developed by the US EPA for the simulation of rainfall-runoff and routing in water bodies, sewer systems and wastewater infrastructures. It has been applied in numerous practical works and research projects. For a new SWMM model, objects such as nodes, links and catchments can either be drawn via SWMM’s graphical user interface (GUI) or specified manually in a plain text file in “.inp” format (“input file”). Since the required data regarding sewer geometries and river systems are usually available as spatial data in a GIS environment, there is a need for user-friendly interfaces for the model setup. SWMM contains neither an import function for geodata nor processing tools as provided in geographic information systems (GIS) such as the open-source software QGIS. Existing approaches were script-based or required commercial all-in-one products. We developed a free and open-source QGIS plugin to generate SWMM models from geodata and to import existing SWMM input files into QGIS. An application example is presented to demonstrate the basic features and usage of the plugin.

Development of Rainfall-Runoff Models for Sustainable Stormwater Management in Urbanized Catchments

Modelling of stormwater networks and the related object (combined sewer overflows, diversion chambers, retention tanks) is a complex task requiring colleting of data with appropriate time and spatial resolution as well as application of adequate models. Often there is a need to find balance between the costs of conducting measurement (period, resolution) and the uncertainty of the model results. This paper presents an overview of simulation tools for sewerage networks modelling, related objects, as well as low-impact development (LID) systems in relation to the hydrodynamic and statistical models. Consecutive stages of data collection, sources of data uncertainty, limitations resulting from the adopted measurement methodology, as well as their influence on the simulation results and possible decision-making using the developed hydrodynamic or statistical model, are discussed. Attention is drawn to the optimization methods enabling reduction in the uncertainty of statistical models. The methods enabling the analysis of model uncertainty, as well as evaluation of its influence on the calculation results pertaining to stormwater hydrographs, retention tank capacity and combined sewers overflows, are also discussed. This is a very important aspect in terms of optimizing construction works in the sewerage network and designing their appropriate dimensions to achieve the assumed hydraulic effects.

A review of non-point source water pollution modeling for the urban-rural transitional areas of China: Research status and prospect

China has experienced a rapid period of urbanization since the 1980s. Many traditional agricultural areas were transformed into the urban-rural transitional areas, in which both urban and rural characteristics exist. Non-point source pollution (NPSP) has become a major side effect of urbanization and agricultural production which caused wide public concerns. It is crucial to carry out research on identifying the spatiotemporal variation in NPSP in the urban-rural transitional area (especially in developing countries, e.g., in China), which is a prerequisite for improving water quality and guiding NPSP control efforts. Modeling approaches are great tools to provide quantitative information on NPSP and optimize the best management practices for NPSP control. We reviewed over twenty years of publications on NPSP modeling and applications in urban, rural and its transitional areas. The strengths and limitations of 20 commonly used NPSP models in China were concluded based on a brief introduction and the evolution history. Reporting the strengths and weaknesses of each NPSP model could enhance its utility in practice. In terms of the unique characteristics of urban-rural transitional areas, which are neither strictly urban nor rural, non-point source pollutants are often distinctly different between traditional pollutants from urban and agricultural areas since the great differences in the hydrological processes, and none of existing NPSP models are fully applicable to urban-rural transitional areas. Based on limited NPSP modeling studies in urban-rural transitional areas, the existing research insufficiency were technical and mechanism limitations of the model despite of numerous improvements in the past, concerns about simulation accuracy, limited investigations on new pollutants, and lack of monitoring data. Future development trend and concerns of NPSP models for urban-rural transitional areas were discussed, which could be of great help to the development of NPSP models and their applications in water quality management in the rapid urbanized China.

Land cover based simulation of urban stormwater runoff and pollutant loading

Urban stormwater models such as PCSWMM are important tools for evaluating urban stormwater quantity and quality. However, due to the lack of consideration of land covers, traditional catchment delineation methods have defects in model precision, parameter transferability and assessment of contribution from individual land cover types. This paper used PCSWMM model as a foundation, built a new land-cover based (LCB) model and made a systematic comparison with the traditional watershed delineation tool (WDT) model to study the impacts of land cover on the simulation of stormwater runoff and pollutant loading. The models were applied to two urban catchments in Calgary, Canada. The results revealed that the LCB model performed better than the WDT model in hydrological simulation, and land cover consideration can considerably improve model accuracy. The two models showed comparable performances in simulation of total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) loading. The LCB model parameters could be regionalized based on land cover types. The hydrologic-hydraulic parameters can be satisfactorily transferred from neighboring gauged catchments to similar ungauged catchments. The transferring of water quality parameters did not perform as satisfactory. The LCB model could quantitively evaluate the contribution to runoff and pollutant loads of different land covers. Roads and roofs were found to be the major contributors to urban runoff and pollutants in the two urban catchments. Green space became important only during large storms events and its contribution could be ignored during dryer years.

Intensity-Duration-Frequency Curves at Ungauged Sites in a Changing Climate for Sustainable Stormwater Networks

Intensity-duration-frequency (IDF) curves representing the variation of the magnitude of extreme rainfall events with a return period and storm duration are widely used in hydrologic infrastructure design, flood risk management projects, and climate change impact studies. However, in many locations worldwide, short-duration rainfall-observing sites with long records do not exist. This paper introduces a new methodological framework for extracting IDF curves at ungauged sites transferring information from gauged ones with a relatively homogeneous extreme rainfall climate. This methodology is grounded on a simple scaling concept based on the multifractal behaviour of rainfall. A nonstationary Generalized Extreme Value (GEV) distribution fitted to annual rainfall monthly maxima at the ungauged site using a moving-time window approach is also applied to consider effects of a changing climate on IDF curve construction. An application is presented at the study site of Fourni, Crete, to derive IDF curves under changing climate conditions and present implications of the proposed methodology in the design of a sustainable stormwater network. The methodology introduced in this work results in increased rainfall extremes up to 20.5%, while the newly designed stormwater network is characterised by increased diameters of its primary conduits, compared to the ones resulting under fully stationary conditions.

Preliminary Model-Based Evaluation of Water Conservation Strategies in a Semi-Arid Urban Zone

The U.S. Environmental Protection Agency stormwater management model was applied to a semi-arid urban micro watershed. The sub-catchment’s current features were modeled as scenario A, while the insertion of a set of LID technologies (rain barrels, bioretention cells, permeable pavement, and infiltration trenches) was represented as scenario B. A third scenario (C), considering only the most feasible LID technologies, was also modeled. All the scenarios were evaluated under two representative storm events (30 and 9 mm in two consecutive days, and 39 mm of rainfall in one day) occurred during the sampling performed in this study. Water quality was also simulated for a 30-mm storm event and compared against field assessment results after a real 30-mm storm event. Through the model, the inefficiency of current evacuation methods after 30- and 39-mm storm events was demonstrated. Simulation of scenario B showed that LID technologies could satisfactorily diminish peak flows generated by the selected storm events as well as runoff-conveyed pollution, while the realistic scenario allowed a lower but satisfactory hydrological performance and almost the same runoff quality than scenario B. This preliminary study could contribute to spread awareness about the benefits of LID technologies in semi-arid urban areas of the developing world.

An Effectiveness Study on the Use of Different Types of LID for Water Cycle Recovery in a Small Catchment

Low-Impact Development (LID) is alleviating the water cycle problems that arise from an increasing impervious surface area caused by urbanization. However, there is insufficient research on the application and analyses of LID techniques that are used for studying the management goals for water cycle restoration. The present study applied various LID techniques, utilizing the stormwater management model (SWMM) in the Naju-Noan Waterfront Zone Construction Project and studying its effects, aiming to restore the runoff that had increased due to urbanization to its pre-development state. The five LID techniques used in the analysis were permeable pavements, bioswales, rainwater gardens, green roofs, and planter boxes, which took up 36.2% of the total area. Our analysis showed that development increased the runoff rate from 39.4% to 62.4%, and LID reduced it to 34.7%. Furthermore, development increased the peak flow from 0.77 m³/s to 1.08 m³/s, and the application of LID reduced it to 0.78 m³/s. An effective reduction in the runoff and peak flow was shown in every recurrence period that was tested, and the bioretention cell type of LID showed the best effectiveness per unit area compared with permeable pavements and green roofs.

Inclusion of Narrow Flow Paths between Buildings in Coarser Grids for Urban Flood Modeling: Virtual Surface Links

Urban flood modeling benefits from new remote sensing technologies, which provide high-resolution data and allow the consideration of small-scale urban key features. Since high-resolution data often result in large simulation runtimes, coarsening of the 2D grid via resampling techniques can be used to achieve a good balance between accuracy and computation time. However, the representation of urban features and topographical properties degrades, since small-scale features are blurred. Therefore, narrow flow paths between buildings are often not considered, building’s sizes are overestimated, and their arrangement in the grid changes. Thus, flow paths change and waterways are blocked, leading to incorrect inundations around buildings. This paper develops a method to improve the simulation results of coarser grids by adding virtual surface links (VSL) between buildings. The VSL mimic the flow paths of a high-resolution model in the areas of interest. The approach is developed for dual-drainage 1D/2D models. The approach shows a visible improvement at the localized level where the VSL are applied, in terms of under/overestimating flooding and a moderate overall improvement of the simulation results. Relatively to the model resolution of 2 m, the computational time, by applying this method, is reduced by 93.6% when using a 5 m grid and by 99% when using a 10 m grid. For a small test case, where the local effects are investigated, the error in the maximum water volume, relative to a grid size of 2 m, is reduced from 69.63% to 5.03% by using a 5 m grid and from 152.75% to 22.92% for a 10 m grid.

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

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

Nature-based solutions efficiency evaluation against natural hazards: Modelling methods, advantages and limitations

Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS.

Design and Simulation of Stormwater Control Measures Using Automated Modeling

Stormwater control measures (SCMs) are decentralized technical elements, which can prevent the negative effects of uncontrolled stormwater flow while providing co-benefits. Optimal SCMs have to be selected and designed to achieve the desired hydrological response of an urban catchment. In this study, automated modeling and domain-specific knowledge in the fields of modeling rainfall-runoff (RR) and SCMs are applied to automate the process of optimal SCM design. A new knowledge library for modeling RR and SCMs, compliant with the equation discovery tool ProBMoT (Process-Based Modeling Tool), was developed. The proposed approach was used to (a) find the optimal RR model that best fits the available pipe flow measurements, and (b) to find the optimal SCMs design that best fits the target catchment outflow. The approach was applied to an urban catchment in the city of Ljubljana, Slovenia. First, nine RR models were created that generally had »very good« performance according to the Nash–Sutcliffe efficiency criteria. Second, six SCM scenarios (i.e., detention pond, storage tank, bio-retention cell, infiltration trench, rain garden, and green roof) were automatically designed and simulated, enabling the assessment of their ability to achieve the target outflow. The proposed approach enables the effective automation of two complex calibration tasks in the field of urban drainage.

Building resiliency to climate change uncertainty through bioretention design modifications

Climate stationarity is a traditional assumption in the design of the urban drainage network, including green infrastructure practices such as bioretention cells. Predicted deviations from historic climate trends associated with global climate change introduce uncertainty in the ability of these systems to maintain service levels in the future. Climate change projections are made using output from coarse-scale general circulation models (GCMs), which can then be downscaled using regional climate models (RCMs) to provide predictions at a finer spatial resolution. However, all models contain sources of error and uncertainty, and predicted changes in future climate can be contradictory between models, requiring an approach that considers multiple projections. The performance of bioretention cells were modeled using USEPA's Storm Water Management Model (SWMM) to determine how design modifications could add resilience to these systems under future climate conditions projected for Knoxville, Tennessee, USA. Ten downscaled climate projections were acquired from the North American Coordinated Regional Downscaling Experiment program, and model bias was corrected using Kernel Density Distribution Mapping (KDDM). Bias-corrected climate projections were used to assess bioretention hydrologic function in future climate conditions. Several scenarios were evaluated using a probabilistic approach to determine the confidence with which design modifications could be implemented to maintain historic performance for both new and existing (retrofitted) bioretention cells. The largest deviations from current design (i.e., concurrently increasing ponding depths, thickness of media layer, media conductivity rates, and bioretention surface areas by 307%, 200%, 200%, and 300%, respectively, beyond current standards) resulted in the greatest improvements on historic performance with respect to annual volumes of infiltration and surface overflow, with all ten future climate scenarios across various soil types yielding increased infiltration and decreased surface overflow compared to historic conditions. However, lower performance was observed for more conservative design modifications; on average, between 13-82% and 77-100% of models fell below historic annual volumes of infiltration and surface overflow, respectively, when ponding zone depth, media layer thickness, and media conductivity were increased alone. Findings demonstrate that increasing bioretention surface area relative to the contributing catchment provides the greatest overall return on historic performance under future climate conditions and should be prioritized in locations with low in situ soil drainage rates. This study highlights the importance of considering local site conditions and management objectives when incorporating resiliency to climate change uncertainty into bioretention designs.

Using the General Regression Neural Network Method to Calibrate the Parameters of a Sub-Catchment

Computer software is an effective tool for simulating urban rainfall–runoff. In hydrological analyses, the storm water management model (SWMM) is widely used throughout the world. However, this model is ineffective for parameter calibration and verification owing to the complexity associated with monitoring data onsite. In the present study, the general regression neural network (GRNN) is used to predict the parameters of the catchment directly, which cannot be achieved using SWMM. Then, the runoff curve is simulated using SWMM, employing predicted parameters based on actual rainfall events. Finally, the simulated and observed runoff curves are compared. The results demonstrate that using GRNN to predict parameters is helpful for achieving simulation results with high accuracy. Thus, combining GRNN and SWMM creates an effective tool for rainfall–runoff simulation.

Using Multiobjective Optimization to Inform Green Infrastructure Decisions as Part of Robust Integrated Water Resources Management Plans

Uncertainty in the impacts of climate change and development on freshwater resources pose significant challenges for water resources management. Integrated and adaptive approaches to water resources management are a promising means of addressing uncertainty that afford flexibility in balancing multiple stakeholder objectives. However, guidance on designing such plans is lacking. In this study, we use multi-objective optimization to strategically incorporate green infrastructure (GI) into water resources management plans that maximize reductions in nutrient loads, minimize stormwater runoff, and minimize costs. Robust decision-making methods are applied to the resulting plan options to evaluate how optimized GI implementation varies under different possible future climates and to determine which solutions would be robust under a range of plausible future conditions. We demonstrate these coupled methods using a case study in southern Massachusetts, to address water quality issues related to point and nonpoint source nutrients in a rapidly developing watershed.

Predicting flood events in Kathmandu Metropolitan City under climate change and urbanisation

Urbanisation and climate change collectively impose the threat of urban flood. The impervious transformation and changes in local climatic conditions increase the risk of frequent pluvial flooding in Kathmandu. Therefore, this study aims to assess the integrated impact of urbanisation and climate change on pluvial flooding in Kathmandu Metropolitan City, using the Personal Computer Storm Water Management Model. The future daily rainfall from three Regional Climate Models under two Representative Concentration Pathways (RCPs) and the observed daily data has been disaggregated to hourly series using temporal rainfall disaggregation. The result shows that the combined impact on pluvial flood is likely to intensify with relatively more contribution from climate change. The CNRM-CM5-CSIRO-CCAM under the RCP 4.5 scenario projects the maximum increase (60-90%) in flood volume for current (75%) and extreme (90%) imperviousness, under a 2-year and 20-year return period (RP) with the extent of the flood area increasing more than the depth. For a 2-year RP, areas with a depth of 0.10-0.25 m are likely to expand while those from 0.25 to 0.40 m in depth are projected to have more velocity, and these trends are expected to be magnified for higher RPs. The study shows that even though urbanisation contributes less to urban pluvial flood, it can be a catalyst for exaggerating other factors and implementing management measures. For instance, the application of small-scale rainwater harvesting, and overflow storage reduced the runoff, thereby reducing the flood volume by 20-35%. Furthermore, the findings highlight the need for planning management strategies such as evaluation and upgrading of conventional drainage systems with low impact measures (rainwater harvesting and green roofs); technical and financial assistance to urban dwellers in adopting the management measures or a combination of them based on the location, requirements, and availability of information and resources to reduce the effects of pluvial flood in Kathmandu.

Next generation swale design for stormwater runoff treatment: A comprehensive approach

Swales are the oldest and most common stormwater control measure for conveying and treating roadway runoff worldwide. Swales are also gaining popularity as part of stormwater treatment trains and as crucial elements in green infrastructure to build more resilient cities. To achieve higher pollutant reductions, swale alternatives with engineered media (bioswales) and wetland conditions (wet swales) are being tested. However, the available swale design guidance is primarily focused on hydraulic conveyance, overlooking their function as an important water quality treatment tool. The objective of this article is to provide science-based swale design guidance for treating targeted pollutants in stormwater runoff. This guidance is underpinned by a literature review. The results of this review suggest that well-maintained grass swales with check dams or infiltration swales are the best options for runoff volume reduction and removal of sediment and heavy metals. For nitrogen removal, wet swales are the most effective swale alternative. Bioswales are best for phosphorus and bacteria removal; both wet swales and bioswales can also treat heavy metals. Selection of a swale type depends on the site constraints, local climate, and available funding for design, construction, and operation. Appropriate siting, pre-design site investigations, and consideration of future maintenance during design are critical to successful long-term swale performance. Swale design recommendations based on a synthesis of the available research are provided, but actual design standards should be developed using local empirical data. Future research is necessary to identify optimal design parameters for all swale types, especially for wet swales.

Robustness analysis of storm water quality modelling with LID infrastructures from natural event-based field monitoring

Sponge city construction (SCC) in China, as a new concept and a practical application of low-impact development (LID), is gaining wide popularity. Modelling tools are widely used to evaluate the ecological benefits of SCC in stormwater pollution mitigation. However, the understanding of the robustness of water quality modelling with different LID design options is still limited due to the paucity of water quality data as well as the high cost of water quality data collection and model calibration. This study develops a new concept of 'robustness' measured by model calibration performances. It combines an automatic calibration technique with intensive field monitoring data to perform the robustness analysis of storm water quality modelling using the SWMM (Storm Water Management Model). One of the national pilot areas of SCC, Fenghuang Cheng, in Shenzhen, China, is selected as the study area. Five water quality variables (COD, NH3-N, TN, TP, and SS) and 13 types of LID/non-LID infrastructures are simulated using 37 rainfall events. The results show that the model performance is satisfactory for different water quality variables and LID types. Water quality modelling of greenbelts and rain gardens has the best performance, while the models of barrels and green roofs are not as robust as those of the other LID types. In urban runoff, three water quality parameters, namely, SS, TN and COD, are better captured by the SWMM models than NH₃-N and TP. The modelling performance tends to be better under heavy rain and significant pollutant concentrations, denoting a potentially more stable and reliable design of infrastructures. This study helps to improve the current understanding of the feasibility and robustness of using the SWMM model in sponge city design.

Robust Vegetation Parameterization for Green Roofs in the EPA Stormwater Management Model (SWMM)

In increasingly expanding cities, roofs are still largely unused areas to counteract the negative impacts of urbanization on the water balance and to reduce flooding. To estimate the effect of green roofs as a sustainable low impact development (LID) technique on the building scale, different approaches to predict the runoff are carried out. In hydrological modelling, representing vegetation feedback on evapotranspiration (ET) is still considered challenging. In this research article, the focus is on improving the representation of the coupled soil–vegetation system of green roofs. Relevant data to calibrate and validate model representations were obtained from an existing field campaign comprising several green roof test plots with different characteristics. A coupled model, utilizing both the Penman–Monteith equation to estimate ET and the software EPA stormwater management model (SWMM) to calculate the runoff, was set up. Through the application of an automatic calibration procedure, we demonstrate that this coupled modelling approach (Kling–Gupta efficiency KGE = 0.88) outperforms the standard ET representation in EPA SWMM (KGE = −0.35), whilst providing a consistent and robust parameter set across all green roof configurations. Moreover, through a global sensitivity analysis, the impact of changes in model parameters was quantified in order to aid modelers in simplifying their parameterization of EPA SWMM. Finally, an improved model using the Penman–Monteith equation and various recommendations are presented.

Supervised Machine Learning for Estimation of Total Suspended Solids in Urban Watersheds

Machine Learning (ML) algorithms provide an alternative for the prediction of pollutant concentration. We compared eight ML algorithms (Linear Regression (LR), uniform weighting k-Nearest Neighbor (UW-kNN), variable weighting k-Nearest Neighbor (VW-kNN), Support Vector Regression (SVR), Artificial Neural Network (ANN), Regression Tree (RT), Random Forest (RF), and Adaptive Boosting (AdB)) to evaluate the feasibility of ML approaches for estimation of Total Suspended Solids (TSS) using the national stormwater quality database. Six factors were used as features to train the algorithms with TSS concentration as the target parameter: Drainage area, land use, percent of imperviousness, rainfall depth, runoff volume, and antecedent dry days. Comparisons among the ML methods demonstrated a higher degree of variability in model performance, with the coefficient of determination (R2) and Nash–Sutcliffe (NSE) values ranging from 0.15 to 0.77. The Root Mean Square (RMSE) values ranged from 110 mg/L to 220 mg/L. The best fit was obtained using the AdB and RF models, with R2 values of 0.77 and 0.74 in the training step and 0.67 and 0.64 in the prediction step. The NSE values were 0.76 and 0.72 in the training step and 0.67 and 0.62 in the prediction step. The predictions from AdB were sensitive to all six factors. However, the sensitivity level was variable.

Highly Resolved Rainfall-Runoff Simulation of Retrofitted Green Stormwater Infrastructure at the Micro-Watershed Scale

Green Stormwater Infrastructure (GSI), a sustainable engineering design approach for managing urban stormwater runoff, has long been recommended as an alternative to conventional conveyance-based stormwater management strategies to mitigate the adverse impact of sprawling urbanization. Hydrological and hydraulic simulations of small-scale GSI measures in densely urbanized micro watersheds require high-resolution spatial databases of urban land use, stormwater structures, and topography. This study presents a highly resolved Storm Water Management Model developed under considerable spatial data constraints. It evaluates the cumulative effect of the implementation of dispersed, retrofitted, small-scale GSI measures in a heavily urbanized micro watershed of Costa Rica. Our methodology includes a high-resolution digital elevation model based on Google Earth information, the accuracy of which was sufficient to determine flow patterns and slopes, as well as to approximate the underground stormwater structures. The model produced satisfactory results in event-based calibration and validation, which ensured the reliability of the data collection procedure. Simulating the implementation of GSI shows that dispersed, retrofitted, small-scale measures could significantly reduce impermeable surface runoff (peak runoff reduction up to 40%) during frequent, less intense storm events and delay peak surface runoff by 5–10 min. The presented approach can benefit stormwater practitioners and modelers conducting small scale hydrological simulation under spatial data constraint.

PySWMM: The Python Interface to Stormwater Management Model (SWMM)

Stormwater management seeks to reduce runoff from rain or melted snow and improve water quality. Where it can absorb into soil, runoff is filtered and returns to streams, rivers, and aquifers, but in developed areas, precipitation often cannot soak into the ground because impervious surfaces (e.g., pavement, buildings), and already saturated soils can create excess runoff. This water, which can contain pollutants, then runs across urban surfaces and into storm drains, drainage ditches, and sewer systems. Stormwater runoff can cause flooding, erosion, infrastructure and habitat damage, and contamination (including combined and sanitary sewer overflows). In urban and developed areas, effective stormwater management that routes and detains stormwater helps to mitigate these impacts and improve water quality.

Modeling Urban Flood Inundation and Recession Impacted by Manholes

Urban flooding, caused by unusually intense rainfall and failure of storm water drainage, has become more frequent and severe in many cities around the world. Most of the earlier studies focused on overland flooding caused by intense rainfall, with little attention given to floods caused by failures of the drainage system. However, the drainage system contributions to flood vulnerability have increased over time as they aged and became inadequate to handle the design floods. Adaption of the drainages for such vulnerability requires a quantitative assessment of their contribution to flood levels and spatial extent during and after flooding events. Here, we couple the one-dimensional Storm Water Management Model (SWMM) to a new flood inundation and recession model (namely FIRM) to characterize the spatial extent and depth of manhole flooding and recession. The manhole overflow from the SWMM model and a fine-resolution elevation map are applied as inputs in FIRM to delineate the spatial extent and depth of flooding during and aftermath of a storm event. The model is tested for two manhole flooding events in the City of Edmonds in Washington, USA. Our two case studies show reasonable match between the observed and modeled flood spatial extents and highlight the importance of considering manholes in urban flood simulations.

Detailed Quantification of the Reduction Effect of Roof Runoff by Low Impact Development Practices

Low impact development (LID) has been widely applied to mitigate urban rainwater problems since the 1990s. However, the effect of LID practices has seldom been evaluated in detail. In this study, the effect of individual and combined LID practices on the reduction of roof runoff are specifically quantified considering the hydrological relationship between LID at the building scale and the campus scale at Beijing Normal University (BNU). The results show that individual and combined LID practices effectively reduce roof runoff for all types of rainfall and for rainfall with return periods from 0.5 to 50 years at the building scale. Combination scenarios maintain good performance with fewer areas of composed LID. Most values for the effect of combination scenarios are between the effects of composed LID. To achieve the highest cost efficiency, low elevation greenbelts should be the first choice, and green roofs should only be selected when low elevation greenbelts and rain barrels cannot be implemented. At the campus scale, individual and combined LID practices effectively reduce the outflow from and the overflow in the campus and combination scenarios have the best reduction performance. This study provides an important reference for urban water management and LID related decision making.

Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models

Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.

Simulation of watershed-scale practices for mitigating stream thermal pollution due to urbanization

Thermally enriched runoff from urban impervious surfaces can be harmful to aquatic life; however, only limited information is available on how to mitigate these impacts at the watershed-scale. This study evaluates the effects of retrofitting an urban watershed with thermal mitigation practices (TMPs) relative to thermal toxicity thresholds for aquatic species. The Minnesota Urban Heat Export Tool (MINUHET) and Storm Water Management Model (SWMM) models were used to evaluate TMPs that help reduce temperature and total heat loads (THL) from the Stroubles Creek watershed in Blacksburg, Virginia. We used the aquatic health criteria for brook trout (Salvelinus fontinalis), the most sensitive species present downstream of the watershed, as a performance measure. TMPs included bioretention systems, methods for reducing the albedo of surfaces (cool surfaces), and increasing forest canopy. Performance metrics included Event Mean Temperature (EMT), and the Percentage of Time Temperature Exceeded the 21 °C Acute Toxicity Threshold [Percentage of Time above the Threshold (PTAT)] for brook trout; these metrics were used to quantify reductions in heat loads and temperatures. TMPs were evaluated during continuous simulation and selected storm events. Increased forest canopy alone produced the greatest reduction of stream temperature, as quantified by EMT and PTAT metrics during continuous and event-based simulations. In contrast, cool surfaces reduced THL more than any other individual TMP for the continuous simulation. A comprehensive mitigation plan (CMP) integrating all three TMPs reduced THL by 62.3%, and PTAT by approximately 12%, for the entire summer of 2015. The CMP was also applied to select storm events, during which streamflow EMT was reduced up to 9%, and PTAT was reduced nearly to zero. This study, which is the first to simulate watershed-scale TMPs for a large, complex urban area, demonstrates the application of appropriate strategies for restoring aquatic habitats in the thermally impacted Stroubles Creek.

Processes improving urban stormwater quality in grass swales and filter strips: A review of research findings

Increasing interest in urban drainage green infrastructure brings attention to grass swales and filter strips (GS&GFS) and their role in stormwater management. While the understanding of the hydrology and hydraulics of these stormwater control measures is adequate for current needs, there are knowledge gaps in understanding the water quality processes in GS&GFS and such a finding motivated preparation of the review paper that follows. The review revealed that most of the empirical studies of GS&GFS flow quality focused on the removal of pollutants associated with road runoff, and particularly solids, with relatively few studies addressing nutrients, traffic associated hydrocarbons, oxygen demanding substances, chloride, and faecal indicator bacteria. The reported results suffer from limitations caused by experimental conditions often representing a steady flow used to irrigate GS&GFS and generate runoff, non-submerged flows, no lateral inflows along swale side slopes, constant dosing of solids, emphasis on larger-than-typical solids, incomplete descriptions of experimental conditions, and limited attention to experimental uncertainties. Besides settling, other treatment processes, like adsorption/desorption, plant uptake, chemical precipitation and microbial degradation are often acknowledged, but without attempting to quantify their effects on flow quality. The modelling of GS&GFS flow quality would be beneficial for an improved understanding of green urban drainage infrastructure, but currently it is infeasible without a better knowledge of stormwater quality processes in GS&GFS facilities.

Research on the Construction Method of the Service-Oriented Web-SWMM System

On a global scale, with the acceleration of urbanization and the continuous expansion of cities, the problem of urban flooding has become increasingly prominent. An increasing number of experts and scholars have begun to focus on this phenomenon and build corresponding models to solve the problem. The storm water management model 5 (SWMM5) is a dynamic rainfall-runoff simulation model developed by the US Environmental Protection Agency (EPA); this model simulates urban flooding and drainage well and is widely favored by researchers. However, the use of SWMM5 is relatively cumbersome and limited by the operational platform, and these factors hinder the further promotion and sharing of SWMM5. Based on the OpenGMS platform, this study first encapsulates, deploys, and publishes SWMM5 and further builds the Web-SWMM system for the model. With Web-SWMM, the user can conveniently use network data resources online and call SWMM5 to carry out calculations, avoiding the difficulties caused by the localized use of SWMM5 and enabling the sharing and reuse of SWMM5.

Impact of Urban Stormwater Runoff on Cyanobacteria Dynamics in A Tropical Urban Lake

Worldwide, eutrophication and cyanobacteria blooms in lakes and reservoirs are a great concern for water resources management. Coupling a catchment hydrological model and a lake model has been a strategy to assess the impact of land use, agricultural practices and climate change on water quality. However, research has mainly focused on large lakes, while urban reservoirs and their catchments, especially in tropical regions, are still poorly studied despite the wide range of ecosystem services they provide. An integrated modelling approach coupling the hydrological model Storm Water Management Model SWMM and the lake ecological model DYRESM-CAEDYM is proposed for Lake Pampulha (Brazil). Scenarios of increased imperviousness of the catchment and of reduction in the load of nutrients and total suspended solids (TSS) in dry weather inflow were simulated. Runoff water quality simulations presented a fair performance for TSS and ammonium (NH4+) while the dynamics of total phosphorus (TP) and nitrate (NO3−) were poorly captured. Phytoplankton dynamics in the lake were simulated with good accuracy (Normalized Mean Absolute Error, NMAE = 0.24 and r = 0.89 in calibration period; NMAE = 0.55 and r = 0.54 in validation period). The general trends of growth, decline and the magnitude of phytoplankton biomass were well represented most of the time. Scenario simulations suggest that TP reduction will decrease cyanobacteria biomass and delay its peaks as a consequence of orthophosphate (PO43−) concentration reduction in the lake surface layers. However, even decreasing TP load into Lake Pampulha by half would not be sufficient to achieve the water quality objective of a maximum concentration of 60 µg chla L−1. Increased imperviousness in the catchment will raise runoff volume, TSS, TP and NO3− loads into Lake Pampulha and promote greater cyanobacteria biomass, mainly in the beginning of the wet season, because of additional nutrient input from catchment runoff. Recovering Lake Pampulha water quality will require the improvement of the sanitation system. The lake water quality improvement will also require more sustainable and nature-based solutions for urban drainage in order to reduce non-point pollution through infiltration and retention of stormwater and to enhance natural processes, such as chemical sorption, biodegradation and phytoremediation. The integrated modelling approach here proposed can be applied for other urban reservoirs taking advantage of existing knowledge on Lake Pampulha.

Can We Really Have It All?—Designing Multifunctionality with Sustainable Urban Drainage System Elements

Multifunctionality is seen as one of the key benefits delivered by sustainable urban drainage systems (SUDS). It has been promoted by both scientific research and practical guidelines. However, interrelations between different benefits are vaguely defined, thus highlighting a lack of knowledge on ways they could be promoted in the actual design process. In this research, multifunctionality has been studied with the help of scenario analysis. Three stormwater scenarios involving different range of SUDS elements have been designed for the case area of Kirstinpuisto in the city of Turku, Finland. Thereafter, the alternative design scenarios have been assessed with four criteria related to multifunctionality (water quantity, water quality, amenity, and biodiversity). The results showed that multifunctionality could be analyzed in the design phase itself, and thus provided knowingly. However, assessing amenity and biodiversity values is more complex and in addition, we still lack proper methods. As the four criteria have mutual interconnections, multifunctionality should be considered during the landscape architectural design, or else we could likely lose some benefits related to multifunctionality. This reinforces emerging understanding that an interdisciplinary approach is needed to combine ecological comprehension together with the system thinking into SUDS design, locating them not as individual elements or as a part of the treatment train, but in connection with wider social ecological framework of urban landscape.

Assessment of stormwater pollutant loads and source area contributions with storm water management model (SWMM)

Decentralized urban runoff management requires detailed information about pollutant sources and pathways. However, scarce data of local water quality compel simplified approaches in water quality modelling. This study investigated the use of constant source concentrations in modelling pollutant loads. The source area contributions of total suspended solids, total phosphorus, total nitrogen, lead, copper and zinc were modelled with SWMM based on literature event mean concentrations (EMCs) for different land cover types and on-site rainfall and discharge data for a residential area in southern Finland. The simulated pollutant loads were compared with loads measured at the catchment outlet. Large differences were evident in the modelled catchment-scale and land cover specific loads, depending on the EMC data source. The simulated loads exceeded the measured loads especially during wet conditions, which was explained by the dilution effect of large stormwater volumes on measured EMCs. In addition, the mismatch was explained by the lack of local data for the source area EMCs and by the unaccountability of the mechanisms affecting loads along the pollutant pathways from source areas to sewer outlet. The spatial simulation of stormwater pollutant loads enabled the assessment of source area contributions at the catchment scale, as well as the pollutant pathways and the total diffuse pollution load. For a single pollutant, one or two important pollutant sources contributed the majority of the catchment load, which provides useful information for stormwater management. However, for a group of pollutants, no single land cover type dominated the pollutant loads, reflecting the challenges in decentralized water quality management in the scale of a residential area. Overall, the results emphasize that the widely used stormwater quality modelling with constant EMCs is uncertain even when on-site water quality and rainfall-runoff data from a catchment outlet are available.

Thermal evaluation of urbanization using a hybrid approach

Urban development increases runoff temperatures from buildings and pavement, which can be harmful to aquatic life. However, our ability to predict runoff temperature as a function of land use is limited. This paper explores available tools for simulating runoff temperature with respect to brook trout (Salvelinus sp.), a sensitive species. The Minnesota Urban Heat Export Tool (MINUHET) and the Storm Water Management Model (SWMM) were applied to a 14.1 km² portion of the Stroubles Creek watershed near Blacksburg, Virginia for two summers. Streamflow, water temperature, and weather data were acquired from the Virginia Tech StREAM Lab (Stream Research, Education, and Management) monitoring stations. SWMM and MINUHET were calibrated and validated for streamflow, and stream temperature, respectively. The models were sensitive to imperviousness (SWMM-predicted streamflow) and dew point temperature (MINUHET-predicted water temperature). While the models output time-step was 15 min, the model performance in simulating streamflow was evaluated using Nash-Sutcliffe Efficiency (NSE) on hourly time-steps. NSE values were 0.67 and 0.65 for SWMM and 0.62 and 0.57 for MINUHET during the calibration and validation periods, respectively, indicating that SWMM performed better than MINUHET in streamflow simulation. Stream temperatures were simulated using MINUHET with NSE value of 0.58 for the validation period, demonstrating a satisfactory simulation of water temperature. Since SWMM is not capable of stream temperature simulation beyond simple mixing. Hydrologic and thermal outputs from SWMM and MINUHET were combined in a hybrid approach that emphasized the strength of each respective model, i.e. SWMM for runoff and streamflow and MINUHET for water temperature. Heat loads were simulated using the MINUHET and the Hybrid models; the Hybrid model (0.56) had a greater NSE than MINUHET (0.45) alone. MINUHET predictions indicated water temperatures would exceed the trout toxicity threshold of 21 °C during 39% and 38% of calibration and validation periods, respectively. Since the observed temperature exceeded the toxicity threshold 59% and 53% of the time for the calibration and validation periods, respectively, MINUHET was not a conservative predictor of the duration of temperatures exceeding the toxicity threshold value.

A Comprehensive Review of Low Impact Development Models for Research, Conceptual, Preliminary and Detailed Design Applications

This review compares and evaluates eleven Low Impact Development (LID) models on the basis of: (i) general model features including the model application, the temporal resolution, the spatial data visualization, the method of placing LID within catchments; (ii) hydrological modelling aspects including: the type of inbuilt LIDs, water balance model, runoff generation and infiltration; and (iii) hydraulic modelling methods with a focus on the flow routing method. Results show that despite the recent updates of existing LID models, several important features are still missing and need improvement. These features include the ability to model: multi-layer subsurface media, tree canopy and processes associated with vegetation, different spatial scales, snowmelt and runoff calculations. This review provides in-depth insight into existing LID models from a hydrological and hydraulic point of view, which will facilitate in selecting the best-suited model. Recommendations on further studies and LID model development are also presented.

Cumulative Effects of Low Impact Development on Watershed Hydrology in a Mixed Land-Cover System

Low Impact Development (LID) is an alternative to conventional urban stormwater management practices, which aims at mitigating the impacts of urbanization on water quantity and quality. Plot and local scale studies provide evidence of LID effectiveness; however, little is known about the overall watershed scale influence of LID practices. This is particularly true in watersheds with a land cover that is more diverse than that of urban or suburban classifications alone. We address this watershed-scale gap by assessing the effects of three common LID practices (rain gardens, permeable pavement, and riparian buffers) on the hydrology of a 0.94 km2 mixed land cover watershed. We used a spatially-explicit ecohydrological model, called Visualizing Ecosystems for Land Management Assessments (VELMA), to compare changes in watershed hydrologic responses before and after the implementation of LID practices. For the LID scenarios, we examined different spatial configurations, using 25%, 50%, 75% and 100% implementation extents, to convert sidewalks into rain gardens, and parking lots and driveways into permeable pavement. We further applied 20 m and 40 m riparian buffers along streams that were adjacent to agricultural land cover. The results showed overall increases in shallow subsurface runoff and infiltration, as well as evapotranspiration, and decreases in peak flows and surface runoff across all types and configurations of LID. Among individual LID practices, rain gardens had the greatest influence on each component of the overall watershed water balance. As anticipated, the combination of LID practices at the highest implementation level resulted in the most substantial changes to the overall watershed hydrology. It is notable that all hydrological changes from the LID implementation, ranging from 0.01 to 0.06 km2 across the study watershed, were modest, which suggests a potentially limited efficacy of LID practices in mixed land cover watersheds.

Simulation of the hydraulic performance of highway filter drains through laboratory models and stormwater management tools

Road drainage is one of the most relevant assets in transport infrastructure due to its inherent influence on traffic management and road safety. Highway filter drains (HFDs), also known as "French Drains", are the main drainage system currently in use in the UK, throughout 7000 km of its strategic road network. Despite being a widespread technique across the whole country, little research has been completed on their design considerations and their subsequent impact on their hydraulic performance, representing a gap in the field. Laboratory experiments have been proven to be a reliable indicator for the simulation of the hydraulic performance of stormwater best management practices (BMPs). In addition to this, stormwater management tools (SMT) have been preferentially chosen as a design tool for BMPs by practitioners from all over the world. In this context, this research aims to investigate the hydraulic performance of HFDs by comparing the results from laboratory simulation and two widely used SMT such as the US EPA's stormwater management model (SWMM) and MicroDrainage®. Statistical analyses were applied to a series of rainfall scenarios simulated, showing a high level of accuracy between the results obtained in laboratory and using SMT as indicated by the high and low values of the Nash-Sutcliffe and R ² coefficients and root-mean-square error (RMSE) reached, which validated the usefulness of SMT to determine the hydraulic performance of HFDs.

Drainage area characterization for evaluating green infrastructure using the Storm Water Management Model

Urban stormwater runoff quantity and quality are strongly dependent upon catchment properties. Models are used to simulate the runoff characteristics, but the output from a stormwater management model is dependent on how the catchment area is subdivided and represented as spatial elements. For green infrastructure modeling, we suggest a discretization method that distinguishes directly connected impervious area from the total impervious area. Pervious buffers, which receive runoff from upgradient impervious areas should also be identified as a separate subset of the entire pervious area. This separation provides an improved model representation of the runoff process. With these criteria in mind, an approach to spatial discretization for projects using the U.S. Environmental Protection Agency's Storm Water Management Model (SWMM) is demonstrated for the Shayler Crossing watershed, a well-monitored, residential suburban area occupying 100 ha, east of Cincinnati, Ohio. The model relies on a highly resolved spatial database of urban land cover, stormwater drainage features, and topography. To verify the spatial discretization approach, a hypothetical analysis was conducted. Six different representations of a common urban scape that discharges runoff to a single storm inlet were evaluated with eight 24 h synthetic storms. This analysis allowed us to select a discretization scheme that balances complexity in model set-up with presumed accuracy of the output with respect to the most complex discretization option considered. The balanced approach delineates directly and indirectly connected impervious areas, buffering pervious area receiving impervious runoff, and the other pervious area within a SWMM subcatchment. It performed well at the watershed scale with minimal calibration effort (Nash-Sutcliffe coefficient = 0.852; R 2 = 0.871). The approach accommodates the distribution of runoff contributions from different spatial components and flow pathways that would impact green infrastructure performance. A developed SWMM model using the discretization approach is calibrated by adjusting parameters per land cover component, instead of per subcatchment, and, therefore, can be applied to relatively large watersheds if the land cover components are relatively homogeneous and/or categorized appropriately in the GIS that supports the model parameterization. Finally, with a few model adjustments, we show how the simulated stream hydrograph can be separated into the relative contributions from different land cover types and subsurface sources, adding insight to the potential effectiveness of planned green infrastructure scenarios at the watershed scale.