Search Results (260)

Land-use changes cause disturbance to sediment dynamics, increasing downstream sediment loads discharged into ecosystems and provoking impacts on stream quality and damage to current stormwater infrastructures. Wastewater nature-based solutions (NBSWT) are bioretention techniques that alleviate downstream degradation caused by runoff sediment accumulation and are projected as an off-line street device that enhances treatment of runoff contaminant loads. This research assesses the economic, social, and environmental benefits from sediment load reduction in runoff by designing a new NBSWT in a selected urban area of the Mantiqueira Mountain Range (São Paulo, Brazil), considered an irreplaceable protected area for biodiversity and urban water supply. To achieve this quantification, the shadow prices methodology has been used. The results obtained here show the adaptive capacity that NBSWT have according to the territory and its climatic particularities, quantified at USD 40,475,255. This value demonstrates that the retention of runoff sediment generates a direct environmental benefit related to the ecosystem improvement of the river system located downstream, preserving its environmental and social importance. Hence, this study demonstrates the potential of using shadow prices methodology as a management tool for quantifying the environmental benefit of removing runoff solids by using NBSWT in developing urban areas. Full article

Over the past 30 years, the City of Portland, Oregon, USA, has emerged as a national leader in green stormwater infrastructure (GSI). The initial impetus for implementing sustainable stormwater infrastructure in Portland stemmed from concerns about flooding and water quality in the city’s two major rivers, the Columbia and the Willamette. Heavy rainfall often led to combined sewer overflows, significantly polluting these waterways. A partial solution was the construction of “The Big Pipe” project, a large-scale stormwater containment system designed to filter and regulate overflow. However, Portland has taken a more comprehensive and long-term approach by integrating sustainable stormwater management into urban planning. Over the past three decades, the city has successfully implemented GSI to mitigate these challenges. Low-impact development strategies, such as bioswales, green streets, and permeable surfaces, have been widely adopted in streetscapes, pathways, and parking areas, enhancing both environmental resilience and urban livability. This perspective highlights the history of the implementation of Portland’s GSI programs, current design and performance standards, and challenges and lessons learned throughout Portland’s recent history. Innovative approaches to managing runoff have not only improved stormwater control but also enhanced green spaces and contributed to the city’s overall climate resilience while addressing economic well-being and social equity. Portland’s success is a result of strong policy support, effective integration of green and gray infrastructure, and active community involvement. As climate change intensifies, cities need holistic, adaptive, and community-centered approaches to urban stormwater management. Portland’s experience offers valuable insights for cities seeking to expand their GSI amid growing concerns about climate resilience, equity, and aging infrastructure. Full article

Land requirements and impacts from future development are a significant concern throughout the world. In Florida (USA), the state’s population increased from 18.8 M to 21.5 M between 2010 and 2020, and is projected to reach 26.6 M by 2040. To accommodate these new residents, 801 km² of wetlands were converted to developed uses between 1996 and 2016. These conversions present a significant threat to Florida’s unique ecosystems and highlight the need to prioritize conservation and water resource protection, both for the natural and human services that wetland and upland landscapes provide. To better understand the relationship between future development and water resources, we used future development and event mean concentration (EMC) models for Escambia and Santa Rosa counties in Florida (USA) to assess impacts from development patterns on water quality/runoff and water resource protection priorities. This study found that if future development densities increased by 30%, reductions of 7713 acres for developed land, 17,768 acre feet of stormwater volume, ~88k lb/yr total nitrogen, and ~15k lb/yr total phosphorus could be achieved. It also found that urban infill, redevelopment, and stormwater management are essential and complementary tools to broader growth management strategies for reducing sprawl while also addressing urban stormwater impacts. Full article

The effects of climate change and urbanisation, such as more intense rainfall and changing land use patterns, are putting increasing pressure on urban drainage systems. This study proposes a comprehensive methodology for evaluating the effectiveness of sustainable urban drainage systems (SUDSs) in mitigating flooding and managing stormwater in both current and future scenarios. The approach integrates geospatial data, including digital elevation models (DEMs) and land use information, to delineate catchments and characterise hydrological parameters. Historical rainfall records and hydrological modelling were employed to define two baseline storm events: an extreme storm involving 422 mm of rainfall over 2 h, and an average storm involving 2.84 mm of rainfall over 1 h and 18 min. Future scenarios were developed by updating these baseline events using annual rates of change in maximum and average precipitation derived from climate projections between 2025 and 2100. The analysis incorporates seven CMIP6 climate scenarios: SSP1-1.9, SSP1-2.6, SSP4-3.4, SSP4-2.5, SSP4-6.0, SSP3-7.0, and SSP5-8.5. A stochastic simulation of 1000 storms per year was carried out using a custom-built conceptual hydrological model based on CN and developed in Python, which reflects interannual variability. The results show that extreme storm volumes could increase by up to seven times and average storm volumes by up to two and a half times. Additionally, discharge peaks could exceed baseline values by up to 20% in some years, suggesting an increased occurrence of extreme runoff events. The methodology assesses SUDS performance by comparing runoff and hydrological responses between baseline and future estimates. This framework enables vulnerabilities and adaptation needs to be identified, ensuring the long-term effectiveness of SUDSs in managing urban flood risk. Addressing uncertainties in climate and land use projections emphasises the importance of integrating SUDS assessments into wider urban resilience strategies. Full article

Green roofs are increasingly recognized as effective Nature-Based Solutions (NBS) for urban stormwater management, contributing to sustainable and climate-resilient cities. The Soil Conservation Service Curve Number (SCS-CN) model is commonly used to simulate their hydrological performance due to its simplicity and low data requirements. However, the standard assumption of a fixed initial abstraction ratio (Ia/S = 0.2), long debated in hydrology, has been largely overlooked in green roof applications. This study investigates the variability of Ia/S and its impact on runoff simulation accuracy for a green roof under a humid subtropical climate. Event-based analysis across multiple storms revealed Ia/S values ranging from 0.01 to 0.62, with a calibrated optimal value of 0.17. This variability is primarily driven by the physical and biological characteristics of the green roof rather than short-term rainfall conditions. Using the fixed ratio introduced consistent biases in runoff estimation, while intermediate ratios (0.17–0.22) provided higher accuracy, with the optimal ratio yielding a median Curve Number (CN) of 89 and high model performance (NSE = 0.95). Additionally, CN values followed a positively skewed Weibull distribution, highlighting the value of probabilistic modeling. Though limited to one green roof design, the findings underscore the importance of site-specific parameter calibration to improve predictive reliability. By enhancing model accuracy, this research supports better design, evaluation, and management of green roofs, reinforcing their contribution to integrated urban water systems and global sustainability goals. Full article

The Soil and Water Assessment Tool (SWAT) was utilized to analyze the spatiotemporal distribution patterns of composite non-point source pollution in the Yapu Port Basin, China, and to quantify the pollutant load contributions from various sources. Scenario-based simulations were designed to assess the effectiveness of different mitigation strategies, focusing on both agricultural and urban non-point source pollution control. The watershed was divided into 39 sub-watersheds and 106 hydrologic response units (HRUs). Model calibration and validation were conducted using the observed data on runoff, total phosphorus (TP), and total nitrogen (TN). The results demonstrate good model performance, with coefficients of determination (R²) ≥ 0.85 and Nash–Sutcliffe efficiencies (NSEs) ≥ 0.84, indicating its applicability to the study area. Temporally, pollutant loads exhibited a positive correlation with precipitation, with peak values observed during the annual flood season. Spatially, pollution intensity increased from upstream to downstream, with the western region of the watershed showing higher loss intensity. Pollution was predominantly concentrated in the downstream region. Based on the composite source analysis, a series of management measures were designed targeting both agricultural and urban non-point source pollution. Among individual measures, fertilizer reduction in agricultural fields and the establishment of vegetative buffer strips demonstrated the highest effectiveness. Combined management strategies significantly enhanced pollution control, with average TN and TP load reductions of 22.18% and 22.70%, respectively. The most effective scenario combined fertilizer reduction, improved urban stormwater utilization, vegetative buffer strips, and grassed swales in both farmland and orchards, resulting in TN and TP reductions of 67.2% and 56.2%, respectively. Full article

It is essential to emphasize the significant impacts of climate change, which are evident in the form of severe and prolonged droughts, hurricanes, snowstorms, and other climatic disturbances. These challenges are particularly pronounced in urban environments and among human populations. The situation is further aggravated by the increasing utilization of available open spaces for residential and industrial development, leading to heightened energy consumption, elevated pollution levels, and increased carbon emissions, all of which negatively affect public health. The primary objective of this review article is to provide a comprehensive evaluation of current research, with a particular focus on the innovative use of residual biomass from urban vegetation for biochar production in the United States. This research entails an exhaustive review of existing literature to assess the implementation of a carbon-negative wood biomass biochar system as a strategic approach to sustainable urban management. By transforming urban wood waste—including tree trimmings, construction debris, and storm-damaged timber—into biochar through pyrolysis, a thermochemical process that sequesters carbon while generating renewable energy, we can leverage this valuable resource. The resulting biochar offers a range of co-benefits: it enhances soil health, improves water retention, reduces stormwater runoff, and lowers greenhouse gas emissions when applied in urban green spaces, agriculture, and land restoration projects. This review highlights the advantages and potential of converting urban wood waste into biochar while exploring how municipalities can strengthen their green ecosystems. Furthermore, it aims to provide a thorough understanding of how the utilization of woody biomass biochar can contribute to mitigating urban carbon emissions across the United States. Full article

Rapid suburbanization can alter catchment flow regime and increase stormwater runoff, posing threats to sensitive ecosystems. Applications of Nature-based Solutions (NbS) have increasingly been adopted as part of integrated water management efforts to tackle the hydrological impact of urbanization with co-benefits for improved urban resilience, sustainability, and community well-being. However, the implementation of NbS can be hindered by gaps in performance assessment. This paper introduces a physically based dynamic modeling approach to assess the performance of a nature-based storage facility designed to capture excess runoff from an urbanizing catchment (Armstrong Creek catchment) in Geelong, Australia. The study adopts a numerical modelling approach, supported by extensive field monitoring of water levels over a 2.5-year period. The model provides a decision support tool for Geelong local government in managing stormwater runoff to protect Lake Connewarre, a Ramsar-listed wetland under the Port Phillip Bay (Western Shoreline) and Bellarine Peninsula. Runoff is currently managed via a set of operating rules governing gate operations that prevents flows into the ecological sensitive downstream waterbody from December to April (drier periods in summer and most of autumn). Comparison with observed water level data at three monitoring stations for a continuous simulation period of May 2022 to October 2024 demonstrates satisfactory to excellent model performance (NSE: 0.55–0.79, R²: 0.80–0.89, ISE rating: excellent). Between 1670 × 10³ m³ and 2770 × 10³ m³ of runoff was intercepted by the nature-based storage facility, representing a 56–70% reduction in stormwater discharge into Lake Connewarre. Our model development underscores the importance of understanding and incorporating user interventions (gate operations and emergency pumping) from the standard operation plan to better manage catchment runoff. As revealed by the seasonal flow analysis for consecutive years, adaptive runoff management practices, capable of responding to rainfall variability, should be incorporated. Full article

The fast pace of urban development and increasing intensity of precipitation events have made managing urban stormwater an increasingly difficult challenge. Hydrologic models are commonly used to predict flows and assess the performance of stormwater controls, often based on a hypothetical yet standardized design storm. The Storm Water Management Model (SWMM) is widely used for simulating runoff in urban watersheds. However, calibration of SWMM, as with all hydrologic models, is often plagued with issues such as subjectivity, and an abundance of model parameters, leading to delays and inefficiencies in model development and application. Further development of modeling and simulation tools to aid in design is critical in improving the function of stormwater management systems. To address these issues, we developed an integration of PySWMM (a Python wrapper (tool) for SWMM) and Pymoo (a Python package for multi-objective optimization) to automate the SWMM calibration process. The tool was tested using a case study urban watershed in Fredericksburg, VA. This tool can employ either a single-objective or multi-objective approach to calibrate a SWMM model by minimizing the error between prediction and observed values. This tool uses performance metrics including Nash-Sutcliffe Efficiency (NSE), Percent Bias (PBIAS), and Root Mean Square Error (RMSE) Standardized Ratio (RSR) for both single-event and long-term continuous rainfall-runoff processes. During multi-objective optimization calibration, the model achieved NSE, PBIAS, and RSR values of 0.73, 17.1, and 0.52, respectively; while the validation period recorded values of 0.86, 13.1, and 0.37, respectively. Additionally, in the single-objective optimization test case, the model yielded NSE values of 0.68 and 0.73 for the calibration and validation, respectively. The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. The tool successfully calibrated the SWMM model, delivering reliable results with suitable computational performance. Full article

Continuous use of agricultural chemicals and fertilizers, sporadic sewer overflow events, and an increase in urbanization have led to significant nutrient/pollutant loadings into the semi-arid Arroyo Colorado River basin, which is located in South Texas, U.S. Priority nutrients that require reduction include phosphorus and nitrogen and to mitigate issues of low dissolved oxygen, in some of its river segments. Consequently, the river’s potential to support aquatic life has been significantly reduced, thus highlighting the need for restoration. To achieve this restoration, a watershed protection plan was developed, comprising several preventive mitigation measures, including installing green infrastructure (GI) practices. However, for effective reduction of excessive nutrient loadings, there is a need to study the effects of different combinations of GI practices under current and future land use scenarios to guide decisions in implementing the cost-effective infrastructure while considering factors such as the existing drainage system, topography, land use, and streamflow. Therefore, this study coupled the Soil and Water Assessment Tool (SWAT) model with the System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) model to determine the effects of different combinations of GI practices on the reduction of nitrogen and phosphorus under changing land use conditions in three selected Arroyo Colorado subwatersheds. Two land use maps from the U.S. Geological Survey (USGS) Forecasting Scenarios of land use (FORE-SCE) model for 2050, namely, A1B and B1, were implemented in the coupled SWAT-SUSTAIN model in this study, where the urban area is projected to increase by 6% and 4%, respectively, with respect to the 2018 land use scenario. As expected, runoff, phosphorus, and nitrogen slightly increased with imperviousness. The modeling results showed that implementing either vegetated swales or wet ponds reduces flow and nutrients to meet the Total Maximum Daily Loads (TMDLs) targets, which cost about USD 1.5 million under current land use (2018). Under the 2050 future projected land use changes (A1B scenario), the cost-effective GI practice was implemented in vegetated swales at USD 1.5 million. In contrast, bioretention cells occupied the least land area to achieve the TMDL targets at USD 2 million. Under the B1 scenario of 2050 projected land use, porous pavements were most cost effective at USD 1.5 million to meet the TMDL requirements. This research emphasizes the need for collaboration between stakeholders at the watershed and farm levels to achieve TMDL targets. This study informs decision-makers, city planners, watershed managers, and other stakeholders involved in restoration efforts in the Arroyo Colorado basin. Full article

Green roofs (GRs) are increasingly implemented for stormwater management, and retrofitting conventional roofs is emerging as a key strategy for climate change resilience. However, their impact on diffuse pollution, particularly regarding total organic carbon (TOC) and pollutant mass transport, remains insufficiently understood, especially in aged substrates. This study evaluated and compared the runoff quality from aged GRs and ceramic roofs (CRs) by analyzing TOC, pH, electrical conductivity (EC), first-flush occurrence and intensity, and pollutant release patterns. Results showed that GR retrofitting could help mitigate acid-rain effects due to its elevated pH. Despite higher TOC and EC concentrations in runoff, GRs remained within acceptable water quality limits and exhibited a more gradual release of organic matter over time compared with CRs. Statistical analysis revealed that pollutant concentrations in CR runoff followed Lognormal and Weibull distributions, while GR runoff was best described by Normal, Lognormal, and Weibull distributions. These findings reinforce GRs as a viable stormwater management strategy but highlight the need for full runoff treatment when used for rainwater harvesting. The results also emphasize the importance of tailored statistical models to enhance runoff predictions and optimize GR performance in urban water management. The results provide valuable insights for urban planners and policymakers by reinforcing the potential of GRs in stormwater quality management and supporting the development of incentives for green infrastructure. Future research should expand to different GR configurations, climates, and maintenance practices to enhance the understanding of long-term hydrological and water quality performance. Full article

Low-impact development (LID) facilities serve as a fundamental approach in urban stormwater management. However, significant variations in land use among different plots lead to discrepancies in runoff reduction demands, frequently leading to either the over- or under-implementation of LID infrastructure. To address this issue, we propose a cost-effective optimization framework grounded in the concept of “Capacity Trading (CT)”. The study area was partitioned into multi-scale grids (CT-100, CT-200, CT-500, and CT-1000) to systematically investigate runoff redistribution across heterogeneous land parcels. Integrated with the Sequential Least Squares Programming (SLSQP) optimization algorithm, LID facilities are allocated according to demand under two independent constraint conditions: runoff coefficient ($\phi$ ≤ 0.49) and runoff control rate ($\eta$ ≥ 70%). A quantitative analysis was conducted to evaluate the construction cost and reduction effectiveness across different trading scales. The key findings include the following: (1) At a constant return period, increasing the trading scale significantly reduces the demand for LID facility construction. Expanding trading scales from CT-100 to CT-1000 reduces LID area requirements by 28.33–142.86 ha under the $\phi$-constraint and 25.5–197.19 ha under the $\eta$-constraint. (2) Systematic evaluations revealed that CT-500 optimized cost-effectiveness by balancing infrastructure investments and hydrological performance. This scale allows for coordinated construction, avoiding the high costs associated with small-scale trading (CT-100 and CT-200) while mitigating the diminishing returns observed in large-scale trading (CT-1000). This study provides a refined and efficient solution for urban stormwater management, overcoming the limitations of traditional approaches and demonstrating significant practical value. Full article

Extreme precipitation events are one of the common hazards in eastern Texas, generating a large amount of storm water. Water running off urban areas may carry non-point source (NPS) pollution to natural resources such as rivers and lakes. Urbanization exacerbates this issue by increasing impervious surfaces that prevent natural infiltration. This study evaluated the efficacy of rain gardens, a nature-based best management practice (BMP), in mitigating NPS pollution from urban stormwater runoff. Stormwater samples were collected at inflow and outflow points of three rain gardens and analyzed for various water quality parameters, including pH, electrical conductivity, fluoride, chloride, nitrate, nitrite, phosphate, sulfate, salts, carbonates, bicarbonates, sodium, potassium, aluminum, boron, calcium, mercury, arsenic, copper iron lead magnesium, manganese and zinc. Removal efficiencies for nitrate, phosphate, and zinc exceeded 70%, while heavy metals such as lead achieved reductions up to 80%. However, certain parameters, such as calcium, magnesium and conductivity, showed increased outflow concentrations, attributed to substrate leaching. These increases resulted in a higher outflow pH. Overall, the pollutants were removed with an efficiency exceeding 50%. These findings demonstrate that rain gardens are an effective and sustainable solution for managing urban stormwater runoff and mitigating NPS pollution in eastern Texas, particularly in regions vulnerable to extreme precipitation events. Full article

The implementation of a decentralized blue–green infrastructure (BGI) is a key strategy in climate adaptation and stormwater management. However, the integration of urban trees into the multifunctional infrastructure remains insufficiently addressed, particularly regarding rooting space in dense urban environments. Addressing this gap, the BoRSiS project developed the soil-pipe system (SPS), which repurposes the existing underground pipe trenches and roadway space to provide trees with significantly larger root zones without competing for additional urban space. This enhances tree-related ecosystem services, such as cooling, air purification, and runoff reduction. The SPS serves as a stormwater retention system by capturing excess rainwater during heavy precipitation events of up to 180 min, reducing the pressure on drainage systems. System evaluations show that, on average, each SPS module (20 m trench length) can store 1028–1285 L of water, enabling a moisture supply to trees for 3.4 to 25.7 days depending on the species and site conditions. This capacity allows the system to buffer short-term drought periods, which, according to climate data, recur with frequencies of 9 (7-day) and 2 (14-day) events per year. Geotechnical and economic assessments confirm the system stability and cost-efficiency. These findings position the SPS as a scalable, multifunctional solution for urban climate adaptation, tree vitality, and a resilient infrastructure. Full article

Grass swales have emerged as a cost-effective and sustainable stormwater management solution, addressing the increasing challenges of urbanization, flooding, and water pollution. This study conducted a bibliometric analysis of 224 publications to assess research trends, key contributors, and knowledge gaps in grass swale applications. Findings highlighted the growing emphasis on optimizing hydrological performance, particularly in response to intensifying climate change and urban flood risks. Experimental and simulation-based studies have demonstrated that grass swale efficiency is influenced by multiple design factors, including vegetation type, substrate composition, hydraulic retention time, and slope gradient. Notably, pollutant removal efficiency varies significantly, with total suspended solids (TSS) reduced by 34.09–89.90%, chemical oxygen demand (COD) by 7.75–56.71%, and total nitrogen (TN) by 32.37–56.71%. Additionally, studies utilizing the Storm Water Management Model (SWMM) and TRAVA models have demonstrated that integrating grass swales into urban drainage systems can result in a 17% reduction in total runoff volume and peak flow attenuation. Despite these advancements, key research gaps remain, including cost-effective design strategies, long-term maintenance protocols, and integration with other green infrastructure systems. Future research should focus on developing innovative, low-cost swale designs, refining optimal vegetation selection, and assessing seasonal variations in performance. Addressing these challenges will enhance the scientific foundation for grass swale implementation, ensuring their sustainable integration into climate-resilient urban planning. Full article