Urban Stormwater Phosphorus Export Control: Comparing Traditional and Low-impact Development Best Management Practices.

Data from the International Stormwater Best Management Practices (BMP) Database were used to compare the phosphorus (P) control performance of six categories of stormwater BMPs representing traditional systems (stormwater pond, wetland basin, and detention basin) and low-impact development (LID) systems (bioretention cell, grass swale, and grass strip). Machine learning (ML) models were trained to predict the reduction or enrichment factors of surface runoff concentrations and loadings of total P (TP) and soluble reactive P (SRP) for the different categories of BMP systems. Relative to traditional BMPs, LIDs generally enriched TP and SRP concentrations in stormwater surface outflow and yielded poorer P runoff load control. The SRP concentration reduction and enrichment factors of LIDs also tended to be more sensitive to variations in climate and watershed characteristics. That is, LIDs were more likely to enrich surface runoff SRP concentrations in drier climates, when inflow SRP concentrations were low, and for watersheds exhibiting high impervious land cover. Overall, our results imply that stormwater BMPs do not universally attenuate urban P export and that preferentially implementing LIDs over traditional BMPs may increase TP and SRP export to receiving freshwater bodies, hence magnifying eutrophication risks.

Enhancing nitrogen and phosphorus removal in plant-biochar-pyrite stormwater bioretention systems: Impact of temperature and high-frequency heavy rainfall.

Global climate change and rapid urbanization have resulted in more frequent and intense rainfall events in urban areas, raising concerns about the effectiveness of stormwater bioretention systems. In this study, we optimized the design by constructing a multi-layer filler structure, including plant layer, biochar layer, and pyrite layer, and evaluated its performance in nitrogen (N) and phosphorus (P) removal under different temperatures (5-18 °C and 24-43 °C), rainfall intensity (47.06 mm rainfall depth), and frequency (1-5 days rainfall intervals) conditions. The findings indicate that over 775 days, the plant system consistently removed 62.3% of total nitrogen (TN) and 97.0% of total phosphorus (TP) from 103 intense rainfall events. Temperature fluctuations had minimal impact on nitrate nitrogen (NO3--N) and TP removal, with differences in removal rates of only 1.0% and 0.6%, respectively, among plant groups. Across the multi-layer structure, plant roots mitigated the impact of temperature differences on NO3--N removal, while high-frequency rainfall fluctuated the stability of NO3--N removal. Dense plant roots reinforced N and P removal by facilitating denitrification in the vadose zone (biochar) and strengthening denitrification processes. Biochar and pyrite contributed to stable microenvironments and diverse ecological functions, enhancing NO3--N and PO43- removal. In summary, the synergistic effects of the multi-layer filler structure improved and stabilized N and P removal, providing valuable insights for addressing runoff pollution in bioretention systems amidst rapid urbanization and climate change challenges.

A Compact, Low-Cost, and Low-Power Turbidity Sensor for Continuous In Situ Stormwater Monitoring.

Turbidity stands as a crucial indicator for assessing water quality, and while turbidity sensors exist, their high cost prohibits their extensive use. In this paper, we introduce an innovative turbidity sensor, and it is the first low-cost turbidity sensor that is designed specifically for long-term stormwater in-field monitoring. Its low cost (USD 23.50) enables the implementation of high spatial resolution monitoring schemes. The sensor design is available under open hardware and open-source licences, and the 3D-printed sensor housing is free to modify based on different monitoring purposes and ambient conditions. The sensor was tested both in the laboratory and in the field. By testing the sensor in the lab with standard turbidity solutions, the proposed low-cost turbidity sensor demonstrated a strong linear correlation between a low-cost sensor and a commercial hand-held turbidimeter. In the field, the low-cost sensor measurements were statistically significantly correlated to a standard high-cost commercial turbidity sensor. Biofouling and drifting issues were also analysed after the sensors were deployed in the field for more than 6 months, showing that both biofouling and drift occur during monitoring. Nonetheless, in terms of maintenance requirements, the low-cost sensor exhibited similar needs compared to the GreenSpan sensor.

Exploring the adoption of water quality trading as an alternative stormwater regulatory compliance strategy for land development projects: A case study for Roanoke, Virginia.

Urban stormwater runoff is a significant source of nutrient pollution that is very costly to treat. Water quality trading (WQT) is a market-based strategy that can be used to lower the costs associated with meeting stormwater quality regulations. While many WQT programs have experienced low participation, Virginia's program has seen high participation due to the inclusion of land developers and other regulated stormwater dischargers. However, the extent to which WQT is used as a compliance option by regulated stormwater dischargers is not well understood, particularly when compared with the adoption of traditional compliance options. To address this knowledge gap, we collated a novel dataset comprising site characteristics and stormwater compliance methods for all development projects in the City of Roanoke, Virginia from December 2015 to March 2022. We analyzed this dataset to characterize the adoption of nutrient offset credits and other compliance methods being used, including best management practices (BMPs) and improved land covers associated with reduced nutrient export. Results show that credits are the preferred compliance option in Roanoke and were used as the only treatment compliance method for 59% of projects with treatment requirements. Projects using credits corresponded with a lower median disturbed area (1.36 acres) and lower median nutrient load reduction requirement (0.69 pounds of total phosphorus per year) compared with other compliance methods. Furthermore, we found that 58% of the projects that used credits achieved stormwater quantity compliance using methods other than implementing stormwater control devices. By mapping buyers and sellers of credits, we found that all credit sellers are downstream of the development projects. We discuss how this downstream trading could be a cause for concern, as part of a larger discussion of the advantages of tracking stormwater compliance methods, drawing on Roanoke as a case study.

A comparative analysis of methods and tools for low impact development (LID) site selection.

The site selection for Low Impact Development (LID) practices is a significant process. It affects the effectiveness of LID in controlling stormwater surface runoff, volume, flow rate, and infiltration. This research paper presents a comprehensive review of various methods used for LID site selection. It starts by introducing different methods and tools. Three main methods: index-based methods, GIS-based multi-criteria decision analysis (MCDA), and multi-criteria models and tools, are discussed in detail. A comparative analysis of these methods is then conducted based on ten different criteria. These criteria include the number of variables, data properties, the scale of analysis, benefits maximization approach, multi-attribute decision analysis, user-friendliness, community and stakeholder participation, and the validation methods. This comparison reveals limitations in each method. These include inadequate data availability and quality, lack of evaluation methods, comprehensive assessment criteria and spatial explicitness. These challenges underscore the need for future research to prioritize spatial clarity, broaden criteria, improve data quality through standardization, incorporate field visits and remote sensing for robust results, integrate big data, and develop web-based, open-source tools for enhanced accessibility. These key strategies provide valuable insights for advancing LID site selection methods.

Enhanced resilience in urban stormwater management through model predictive control and optimal layout schemes under extreme rainfall events.

Optimizing the layout of urban stormwater management systems is an effective method for mitigating the risk of urban flooding under extreme storms. However, traditional approaches that consider only economic costs or annual runoff control rates cannot dynamically respond to the uncertainties of extreme weather, making it difficult to completely avoid large accumulations of water and flooding in a short period. This study proposes an integrated method combining system layout optimization and Model Predictive Control(MPC)to enhance the system's resilience and effectiveness in flood control. An optimization framework was initially built to identify optimal system layouts, balancing annual average life cycle cost (AALCC) and resilience index. The MPC was then applied to the optimal layout selected using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, aiming to alleviate inundation cost-effectively. The adaptability of MPC to varying sets of control horizons and its efficacy in managing the hydrograph and flood dynamics of urban drainage system were examined. Conducted in Yubei, Chongqing, this study revealed patterns in optimal layout fronts among various extreme design rainfalls, showing that peak position rate and return period significantly influence system resilience. The contribution of MPC to the optimal system layout was particularly notable, resulting in improved instantaneous and overall flood mitigation. The application of MPC increased the resilience index by an average of 0.0485 and offered cost savings of 0.0514 million yuan in AALCC. Besides, our findings highlighted the importance of selecting an optimal set of control horizons for MPC, which could reduce maximum flood depth from 0.43m to 0.19m and decrease conduit peak flow by up to 14% at a flood-prone downstream location.

Performance and uncertainty assessment of green roofs for urban flood reduction in a high-density catchment in Ahmedabad, India.

Urban flooding poses a significant challenge to the rapidly growing Indian cities. Low-impact development strategies such as green roofs have shown the potential to reduce urban flooding. However, their performance assessment significantly varies across different studies. Therefore, the study's primary objective is to evaluate green roofs in the Indian context. For this evaluation, the green roofs are assessed based on building-level implementation scenarios for a high-density urban area in India for 25%,50%, and 75% application rates and different rainfall intensities (2,3 and 4-h duration and 2,5,10 and 25-year frequencies). Secondly, to probe the variations in the green roof performance across studies, uncertainty contributions to the runoff reduction from different parameters are quantified. The results show that green roofs can reduce up to 62% of flood volume and 24% of runoff. However, they are reasonably effective only beyond 25% application rates. Further, rainfall intensity contributes the most to the uncertainty of runoff reduction from green roofs. This uncertainty assessment implies that localized evaluation of green roofs depending on local rainfall conditions is required for city-wide policy planning. The study has a significant contribution to building confidence in the ability of green roofs to reduce urban floods in the context of developing countries like India.

Determining the most appropriate stormwater management strategies within the development of urban landscape infrastructure using the TOPSIS method: applications to Rize city.

In this study, the application of multi-criteria decision-making (MCDM) methods in determining the most appropriate stormwater management strategy is examined using different areas in Rize. The determination of the most appropriate stormwater management practices for the Rize coastal park and Güneysu-Rize connection highway with TOPSIS is presented in detail within this study. In this context, commonly used applications suitable for urban areas are discussed. The criteria and their weights used for the evaluation of the selected applications were determined by consulting expert opinions from leading researchers. The most suitable applications in different scenarios such as changes in the cost or the amount of precipitation for Rize coastal park and Güneysu-Rize connection road were determined by the TOPSIS method. The TOPSIS analyses' ranking of the ideal solutions matches the results of the SWMM simulations one to one. SWMM results confirm that the outcomes of TOPSIS are the alternatives that provide maximum decrease in surface runoff.

Green infrastructure layout based on a dynamic operation feature of drainage systems.

Increasingly frequent urban floods strain the traditional grey infrastructure, overwhelming the capacity of drainage networks and causing challenges in managing stormwater. The heavy precipitation leads to flooding and damage to drainage systems. Consequently, efficient mitigation strategies for flooding have been researched deeply. Green infrastructure (GI) has proved to be effective in responding the increasing risk of flood and alleviate pressure on drainage systems. However, as the primary infrastructure of stormwater management, there is still a lack of attention to the dynamic operation feature of urban sewer systems during precipitation events. To fill this gap, we proposed a novel approach that integrates hydraulic characteristics and the topological structure of a sewer network system. This approach aims to identify influential nodes, which contribute to the connectivity of the sewer network amidst dynamic changes in inflow during precipitation events. Furthermore, we adopted rain barrels to serve as exemplars of GI, and 14 GI layout schemes are produced based on the different ranks of influential nodes. Implementing GI measures on both poorly performing and well-performing nodes can yield distinct benefits in mitigating node flooding. This approach provides a new perspective for stormwater management, establishing effective synergy between GI and the drainage system.

An alternative for predicting real-time water levels of urban drainage systems.

Storm Water Management Model (SWMM) developed by the United States Environmental Protection Agency (EPA) has been widely applied throughout the world for analysis associated with stormwater runoff, combined sewers, and other drainage facilities. To appropriately manage the runoff in urban areas, an integrated system including the simulations of sewer flow, street flow, and regional channel flow, called the 1D/1D SWMM model, was advocated to be performed. Nevertheless, the execution efficiency of this integrated system still needs to be promoted to meet the demand for real-time forecasting of urban floods. The objective of this study is to seek an alternative for predicting water levels both in the sewer system and on the streets within an urban district during rainstorms by utilizing a dynamic neuron network model. To strengthen the physical structure of the artificial intelligence (AI) model and simultaneously make up for the lack of measured data, simulation results of the 1D/1D SWMM model are provided as labels for the training of the proposed model. The novelty of this research is to propose a new methodology to effectively train the AI model for predicting the spatial distributions of depths based on the hydrologic conditions, geomorphologic properties, as well as the network relation of the drainage system. A two-stage training procedure is proposed in this study to consider more possible inundation conditions in both sewer and street (open channel) drainage networks. The research findings show that the proposed methodology is capable of reaching satisfactory accuracy and assisting the numerical-based SWMM model for real-time warning of drainage systems in the urban district.

Assessing and improving the outcomes of nonpoint source water quality trading policies in urban areas: A case study in Virginia.

Nonpoint source (NPS) water quality trading (WQT) is a market-based approach to improving water quality. Past work has shown that these programs could increase localized pollutant loadings, in part by exporting water quality controls from urban to rural areas. Virginia's NPS WQT program has enabled thousands of transactions and may provide a model for other programs, but its impacts on urban water quality have not been thoroughly assessed. We quantify the impact of NPS WQT purchases in Virginia on water quality and hydrology in an urban catchment. We go on to assess outcomes of a policy alternative where buyers and sellers are collocated in the urban catchment. Simulation results show that NPS WQT increased total phosphorus (TP) loading by an average of 0.8 lbs TP/year for each 1.0 offsite credits purchased in the analyzed catchment. The TP loading increased in years with greater rainfall, such that TP loads were increased by up to 1.2 lbs TP/year for each offsite credit purchased. These loading increases may or may not be acceptable, depending on the cumulative number of purchases within an urban catchment and existing local water quality issues. In our policy alternative with buyers and sellers collocated in the catchment, we found that the TP increase from development was completely offset at the catchment scale, with a decrease of 4.3 lbs TP/year for each 1.0 credits purchased. This suggests that credits awarded for urban mitigation practices are undervalued compared with water quality requirements for credit purchasers. This undervaluation is a result of the Virginia trading program using one approach to compute the credit value for buyers and a different approach to compute the credit value for sellers. We demonstrate how using a single model to determine both buyer and seller credit values in urban areas could provide greater transparency and mitigate the risk of urban pollution hot spots. This work demonstrates the importance of consistency in the scale of pollutant load calculations between buyers and sellers for NPS WQT, and contributes novel insight into the implications of WQT for urban NPS pollution.

Rooftop water harvesting for managed aquifer recharge and flood mitigation in tropical cities: Towards a strategy of co-benefit evaluations in João Pessoa, northeast Brazil.

Intense urbanisation in many coastal areas has led to intensification of groundwater consumption, while reducing permeable areas and increasing the frequency and magnitude of flooding. Among the potential strategies to compensate for these adverse effects, which are expected to become worse as a result of climate change, rooftop rainwater harvesting (RWH) in combination with managed aquifer recharge (MAR), may be indicated. This work investigated the performance of different configurations of such a system, tested as a twofold sustainable stormwater and domestic water management tool in a tropical metropole (João Pessoa, Brazil). This area located over a sedimentary aquifer system illustrates the water security challenges of densely urbanised areas in southern cities. To that end, several configurations of rooftop catchments and storage volumes were evaluated, by simulating a MAR-RWH system connected to the regional unconfined aquifer (Barreiras Formation) through a 6″ diameter injection well. Rainfall-runoff-recharge processes and water balances were simulated using monitored high-temporal resolution rainfall data. The results showed that catchments ranging from 180 to 810 m2, connected to tanks from 0.5 to 30.0 m³, are the optimal solutions in terms of efficient rainwater retention and peak flow reduction. These solutions provided mean annual estimates of aquifer recharge between 57 and 255 m³/yr from 2004 to 2019. The results of this study highlight the opportunity for MAR schemes to reconcile stormwater management and water supply goals.

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.

Optimizing the maintenance strategies for a network of green infrastructure: An agent-based model for stormwater detention basins.

Various stormwater best management practices and green infrastructures (GIs) are recommended to address flooding, stormwater runoff, water quality, and sustainability. While detention basins are considered one of the main GI strategies, their benefits cannot be fully realized without properly maintaining them and making sure that they stay operational. Therefore, this paper used agent-based modeling (ABM) to devise an optimal maintenance program for detention basins to ensure that they function properly and continue to perform their water quality and flood control functions. More specifically, the following 2 agent types were incorporated in the model: 1) the detention basins were considered as static agents, and 2) the service teams responsible for the operation (maintenance, repair, and replacement) of the detention basins were considered as active agents. The developed ABM was applied for the entire network of stormwater detention basins in Newark, NJ. Sensitivity analysis was conducted to identify the most critical variables affecting the total cost of operating the network of detention basins as well as the functioning percentage of detention basins. In addition, optimization was implemented to determine the best maintenance program or policy that minimizes the total cost of operations, while also making sure that a desired functionality level or threshold is achieved for the entire network of detention basins. Finally, the ABM was statistically validated using a total of 10,000 Monte Carlo runs and 99% confidence intervals. The optimization results showed that, in order to minimize the total cost of maintaining the entire network of detention basins and ensure that at least 80% of the basins are in a functioning state at the end of the planning horizon, the decision-maker should implement the following maintenance program or strategy: have 2 service teams for the operations of the detention basins, follow a replacement policy, and replace detention basins after 3 maintenance periods. Also, the identified optimal maintenance program or strategy would result with an average total annual cost of around $4,085,000, where the average annual repair cost is around $2,572,200, the average annual maintenance cost is around $19,700, the average annual replacement cost is around $763,100, and the average annual service team cost is around $730,000. The proposed ABM for detention basins can be extended to other GIs as well as to different geographical areas. The usage of ABM has the advantage to reduce the subjectivity in developing plans for managing GIs.

Impact of wood-derived biochar on the hydrologic performance of bioretention media: Effects on aggregation, root growth, and water retention.

Bioretention systems are one example of green stormwater infrastructure that may mitigate the hydrologic impact of stormwater runoff. To improve water retention while maintaining rapid stormwater infiltration, conventional bioretention soil media (BSM) might be augmented with biochar. Biochar may improve the BSM's structure by increasing soil aggregation, which might improve water retention and increase stormwater infiltration while also improving root growth. Pots with BSMs representing high and moderate sand content media were amended with a wood-derived biochar, planted with switchgrass, and subjected to weekly storms for 20 weeks, followed by a 10-week drought. In the high sand content medium (NC mix), biochar amendment increased hydraulic conductivity (Ksat), and this effect increased with time. At 0 weeks, 2% and 4% (w/w) biochar increased Ksat by 4 ± 2% and 10 ± 4%, respectively, while at 30 weeks the increase was 30 ± 10 and 70 ± 20%, respectively, above biochar-free media. Similar improvements were seen in plant available water (PAW) in NC mix. However, minimal improvements in Ksat and PAW from biochar amendment were found in the moderate sand content BSM that contained compost and mulch (DE mix). Where biochar promoted Ksat, this was correlated with increased water-stable aggregate size (r = 0.86), fine root volume (r = 0.88), and below ground biomass (r = 0.83). Important factors affecting Ksat and aggregation in the NC mix were biochar's influence on organo-mineral association, fungal hyphae length, and plant roots. Wood-derived biochar amendment to BSM may obviate the need for compost/mulch since biochar has similar effects on improving BSM hydrology and root growth without the risk of undesired nutrient leaching.

Computational fluid dynamics modeling of floating treatment wetland retrofitted stormwater pond: Investigation on design configurations.

Floating Treatment Wetland (FTW) is a cost-effective and easy-to-retrofit device for stormwater treatment. Its treatment efficiency largely depends on the fraction of inflow entering FTW and the residence time within it. Thus hydrodynamics play a crucial role, which is affected by the design configurations of FTW and stormwater pond. Despite a spike in research on FTWs, very little is known about how various design configurations affect treatment efficiency by an FTW. Our study hypothesizes that relative positions of FTW geometry, FTW position and pond inlet-outlet have impact on the hydrodynamics and as a consequence, treatment efficiency. To explore these design features, we employed computational fluid dynamics (CFD) modeling conducted in ANSYS Fluent, validated by experimental data to examine the impact of the aforementioned design features. The results revealed that circular FTW geometry positioned near inlet coupled with center inlet-side outlet configuration achieved the highest removal (94.8%) for a non-dimensional removal rate of krtHRT = 20 (kr is the first order removal rate in per day, tHRT is the nominal hydraulic residence time of the pond in days). Far side inlet-side outlet configuration performed the worst due to profound promotion of short-circuiting. FTW positioned near inlet performed better (61.8% mass removal on an average) than center (42.7%) and near outlet positions (54.1%) for krtHRT = 20. Sensitivity analysis revealed that the treatment efficiency is most sensitive to inlet-outlet configurations. The design implications of this study will help practitioners achieving better water quality and ecological improvement goals.

From flood paths to floodways, an efficient method to map, identify and evaluate suitable floodways: A case study from Trondheim, Norway.

Due to climate change and rapid urbanisation, many Norwegian cities and urban areas suffer from pluvial flooding caused by intense rainfall exceeding the capacity of the stormwater management system. This results in increased runoff rates, volumes and peak flows in the drainage network. In response to these challenges, the authors explore the potential of utilising the urban surface's ability to transport floodwater as an integral component of the stormwater infrastructure. When the capacity of the stormwater drainage system is exceeded, the overland flow paths transporting floodwater are considered a part of the stormwater management system, as floodways. The study proposes a spatial GIS method to map existing drainage lines and identify existing surface areas that function as floodways, combined with an automated process to identify which drainage lines could be implemented as stormwater management measures. Critical points are introduced to assess the floodways' potential hazards, combined with a classification method to evaluate and sort floodways. A case study from Trondheim, Norway, was used to demonstrate how drainage lines can be identified as floodways using the proposed method. The case study is also used to illustrate how a GIS-based analysis can be extended from identifying to evaluating floodways and whether GIS is sufficient for floodway evaluation. The method enables urban planners and municipalities to identify which areas of the urban surface already function as floodways during extreme events, and to prioritise measures to secure such areas and increase the city's flood resilience. The results highlight the need to assess existing areas that function as floodways, and to implement and design needed areas as floodways. GIS-based methods combined with an evaluation scheme can be an adequate tool to map and evaluate floodways in urban areas. When using GIS-based methods, however, the corresponding hazard potential, and also the uncertainty of the floodway's spatial placement, should be considered.

Insights into the transport and bio-degradation of dissolved inorganic nitrogen in the biochar-pyrite amended stormwater biofilter using dynamic modeling.

The stormwater biofilter is a prevailing green infrastructure for urban stormwater management, but it is less effective in dissolved nitrogen removal, especially for nitrate. The mechanism that governs the nitrate leaching and performance stability of stormwater biofilters is poorly understood. In this study, a water quality model was developed to predict the ammonium and nitrate dynamics in a biochar-pyrite amended stormwater biofilter. The transport of dissolved nitrogen species was described by advection-dispersion models. The kinetics of adsorption and pyrite-based autotrophic denitrification are included in the model and simulated with a steady-state saturated flow. The model was calibrated and validated using eleven storm events. The modeling results reveal that the contribution of pyrite-based autotrophic denitrification to nitrate leaching alleviation improves with the increased drying duration. The nitrate removal efficiency was affected by a series of design parameters. Pyrite filling rate has a minor effect on nitrate removal promotion. Service area ratio and submerged zone depth are the key parameters to prevent nitrate leaching, as they influence the emergence and discharge time of nitrate breakthrough. The high inflow volume (high service area ratio) and small submerged zone can lead to earlier and increased discharge of peak nitrate otherwise the peak nitrate could be retained in the submerged zone and denitrified during the drying period. The developed mechanistic model provides a useful tool to evaluate the treatment ability of stormwater biofilters under varying conditions and offers a guideline for biofilter design optimization.

Optimization and trade-off framework for coupled green-grey infrastructure considering environmental performance.

Implementing runoff control infrastructure has been regarded as an efficacious measure in stormwater management. The issue of its cost-effectiveness is a primary concern for decision makers since it is an exorbitant investment. However, most of existed studies only concentrated on the cost-effectiveness optimization of runoff control infrastructure, especially green infrastructure, between hydrological and economic aspects, and therefore, the potential layout scenarios with high extra environmental benefits could be neglected in the traditional two-dimensional frameworks. In this study, a novel carbon dioxide equivalent-based index was quantified to represent the extra environmental benefits of runoff control infrastructure besides stormwater management and was further integrated into the assessment framework. The effectiveness of green and grey infrastructure was comprehensively evaluated and traded off between hydrological, environmental and economic aspects. The results demonstrated that grey infrastructure is a better measure than green infrastructure when only hydrological (HF index) and economic (CI index) performances were considered. Nevertheless, the environmental performance (EROI index) of green infrastructure prevails over grey infrastructure, and when optimizing green and grey infrastructure simultaneously in the three-dimensional framework considering environmental effectiveness, green infrastructure is comparable with grey infrastructure. Furthermore, an appropriate composition of coupled green-grey infrastructure is requisite, which could achieve an optimal trade-off between hydrological and environmental effectiveness. The sources of environmental benefits were also identified and analyzed from three representative preference scenarios. The findings of the study could serve as a trade-off basis between green and grey infrastructure, as well as between EROI and HF.

Stormwater Bioretention Cells Are Not an Effective Treatment for Persistent and Mobile Organic Compounds (PMOCs).

Bioretention cells are a stormwater management technology intended to reduce the quantity of water entering receiving bodies. They are also used to reduce contaminant releases, but their performance is unclear for hydrophilic persistent and mobile organic compounds (PMOCs). We developed a novel eight-compartment one-dimensional (1D) multimedia model of a bioretention cell ("Bioretention Blues") and applied it to a spike and recovery experiment conducted on a system near Toronto, Canada, involving PMOC benzotriazole and four organophosphate esters (OPEs). Compounds with (log DOC) (organic carbon-water distribution coefficients) < ∼2.7 advected through the system, resulting in infiltration or underdrain flow. Compounds with log DOC > 3.8 were mostly sorbed to the soil, where subsequent fate depended on transformation. For compounds with 2.7 ≤ log DOC ≤ 3.8, sorption was sensitive to event size and compound-specific diffusion parameters, with more sorption expected for smaller rain events and for compounds with larger diffusion coefficients. Volatilization losses were minimal for all compounds tested. Direct uptake by vegetation also played a negligible role regardless of the compounds' physicochemical properties. Nonetheless, model simulations showed that vegetation could play a role by increasing transpiration, thereby increasing sorption to the bioretention soil and reducing PMOC release. Model results suggest design modifications to bioretention cells.