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

Modeling the effect of land use change to design a suitable low impact development (LID) system to control surface water pollutants

Growth in urbanization has led to increased impervious surfaces, exacerbating flood risks and water quality degradation. This study investigated the impact of land use change and Low-Impact Development (LID) systems on urban runoff quality and quantity in the second region of Tehran. Pioneering an innovative approach, the integration of the Land Change Modeler (LCM) with the Stormwater Management Model (SWMM) signifies a paradigm shift in urban water management. Combined with other hydrological models, this new approach provides a comprehensive method for assessing the future effectiveness of LID practices. The Event Mean Concentration Method (EMC) was used in this study to measure Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Total Phosphorus (TP), and Zinc (Zn) in urban runoff from five land uses. Results pinpointed transportation land uses as the primary source of pollutants. Using LCM, the study forecasted a surge in urban runoff pollutants by 2030, particularly in the Northwest area of the region due to anticipated land use shifts towards commercial and residential land uses. Model results showed an 11 % increase in TSS over a decade, highlighting the importance of land use change in runoff quality. The study used three types of LIDs to reduce contaminants in dense urban areas. Assessing the impact of LID scenarios on runoff pollutants using SWMM revealed that the bio-retention cell had the best performance, reducing TSS by 20.92 %, and the vegetative swale had the worst performance, reducing TSS by 8.43 %. The study also concluded that combining LIDs would be more effective than using them separately. The results of this study suggest that LID systems can be an effective way to reduce urban runoff pollutants and improve water quality in the second region of Tehran. However, more research is needed to optimize the design and placement of LID systems in different urban areas.

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

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

Assisting decision-makers select multi-dimensionally efficient infrastructure designs - Application to urban drainage systems

Multi-objective design approaches can help identify future infrastructure system designs that appropriately balance different engineering, environmental, and other societal goals. Planners benefit from assessing the trade-offs implied by the best-performing infrastructure system solutions. However, a large number of possible efficient system designs, obtained when using multi-objective optimization, can be overwhelming to interpret. This study attempts to aid decision-making in multi-criteria infrastructure system design by reducing the complexity of the identified set of efficient infrastructure designs, i.e., the Pareto-front. A soft clustering algorithm is applied, which identifies similarities between solutions, partitions the front accordingly, and selects a set of representative solutions while preserving the multi-dimensional structure of the solutions on the efficiency frontier. Three post-optimization decision-making metrics are introduced to help quantify the overall performance of the Pareto-optimal designs to further summarize design process outputs for decision-makers. We apply the method to an illustrious urban drainage network case study. Results show how the approach can simplify Pareto-fronts with thousands of solutions into sets of highlighted designs that aid interpreting the trade-offs implied by the best-performing simulated systems.

River Basin Export Reduction Optimization Support Tool; a tool to screen options for reducing nutrient loads while minimizing cost

Excess loading of nitrogen and phosphorus to river networks causes environmental harm, but reducing loads from large river basins is difficult and expensive. We develop a new tool, the River Basin Export Reduction Optimization Support Tool (RBEROST) to identify least-cost combinations of management practices that will reduce nutrient loading to target levels in downstream and mid-network waterbodies. We demonstrate the utility of the tool in a case study in the Upper Connecticut River basin in New England, USA. The total project cost of optimized lowest-cost plans ranged from $18.0 million to $41.0 million per year over 15 years depending on user specifications. Plans include both point source and non-point source management practices, and most costs are associated with urban stormwater practices. Adding a 2% margin of safety to loading targets improved estimated probability of success from 37.5% to 99%. The large spatial scale of RBEROST, and the consideration of both point and non-point source contributions of nutrients, makes it well suited as an initial screening tool in watershed planning.

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.

Modeling graphene oxide transport and retention in biochar

Experimental data from fixed-bed column studies and a numerical model based on convection-dispersion equations were used to describe transport and retention of Graphene Oxide (GO) in sand, biochar (BC), and BC modified with nanoscale zero-valent iron (BC-nZVI). Three blocking functions, namely no blocking, site-blocking, and depth-dependent blocking, were used to analyze GO transport and retention behavior in each media as a function of Ionic Strength (IS). An inverse modeling approach was implemented to determine the attachment coefficient (K_a) and maximum solid-phase retention capacity (S_max). The Langmuirian attachment model with site-blocking function effectively described experimental GO breakthrough curves (R² ~ 0.70-0.99) compared to other models, indicating the importance of introducing a limit on the attachment capacity of the media. The K_a values for BC and BC-nZVI were significantly higher than sand, attributable to high porosity, roughness, and surface chemical properties. The models predicted an increasing trend in K_a (0.065 to 0.615 min^-1) in BC with increasing IS (0.1 to 10 mM), while K_a values decreased (2.26 to 0.349 min^-1) for BC-nZVI. A consistent increase in S_max was observed for both BC and BC-nZVI with increasing IS. Scenario analysis was conducted to further understand the effect of influent IS, GO concentration, and treatment depth. BC-nZVI exhibited a higher K_a and S_max and as a result, higher GO retention than BC at lower IS (0.1 and 1.0 mM). BC-nZVI had a relatively lower K_a (0.349 min^-1) at 10 mM IS, however, it outperformed BC when GO retention capacities are compared over a longer period attributable to a higher S_max (6.47). Complete GO breakthrough occurred in a 5 cm media after 350 and 465 days for BC and BC-nZVI, respectively at 10 mM IS and influent concentration of 0.1 mg·L^-1. GO breakthrough time increased with increasing treatment depth, however, the relation was non-linear.

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

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

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

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

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.

Urban Flood Analysis in Ungauged Drainage Basin Using Short-Term and High-Resolution Remotely Sensed Rainfall Records

Analyzing flooding in urban areas is a great challenge due to the lack of long-term rainfall records. This study hereby seeks to propose a modeling framework for urban flood analysis in ungauged drainage basins. A platform called “RainyDay” combined with a nine-year record of hourly, 0.1° remotely sensed rainfall data are used to generate extreme rainfall events. These events are used as inputs to a hydrological model. The comprehensive characteristics of urban flooding are reflected through the projection pursuit method. We simulate runoff for different return periods for a typical urban drainage basin. The combination of RainyDay and short-record remotely sensed rainfall can reproduce recent observed rainfall frequencies, which are relatively close to the design rainfall calculated by the intensity-duration-frequency formula. More specifically, the design rainfall is closer at high (higher than 20-yr) return period or long duration (longer than 6 h). Contrasting with the flood-simulated results under different return periods, RainyDay-based estimates may underestimate the flood characteristics under low return period or short duration scenarios, but they can reflect the characteristics with increasing duration or return period. The proposed modeling framework provides an alternative way to estimate the ensemble spread of rainfall and flood estimates rather than a single estimate value.

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

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

A Site-Scale Tool for Performance-Based Design of Stormwater Best Management Practices

The objective of this research is to develop a module for the design of best management practices based on percent pollutant removal. The module is a part of the site-scale integrated decision support tool (i-DSTss) that was developed for stormwater management. The current i-DSTss tool allows for the design of best management practices based on flow reduction. The new water quality module extends the capability of the i-DSTss tool by adding new procedures for the design of best management practices based on treatment performance. The water quality module can be used to assess the treatment of colloid/total suspended solid and dissolved pollutants. We classify best management practices into storage-based (e.g., pond) and infiltration-based (e.g., bioretention and permeable pavement) practices for design purposes. Several of the more complex stormwater tools require expertise to build and operate. The i-DSTss and its component modules including the newly added water quality module are built on an accessible platform (Microsoft Excel VBA) and can be operated with a minimum skillset. Predictions from the water quality module were compared with observed data, and the goodness-of-fit was evaluated. For percent total suspended solid removal, both R2 and Nash–Sutcliffe efficiency values were greater than 0.7 and 0.6 for infiltration-based and storage-based best management practices, respectively, demonstrating a good fit for both types of best management practices. For percent total phosphorous and Escherichia. coli removal, R2 and Nash–Sutcliffe efficiency values demonstrated an acceptable fit. To enhance usability of the tool by a broad range of users, the tool is designed to be flexible allowing user interaction through a graphical user interface.