Search Results (162)

The U.S. Environmental Protection Agency (EPA) developed the concept of Water Quality Volume (WQv) as a Best Management Practice (BMP) to treat the first 25.4 mm of rainfall in urban areas, aiming to capture approximately 90% of annual runoff. However, applying this urban-based standard—designed for areas with over 50% imperviousness—to rural regions with higher infiltration and pervious surfaces may result in overestimated facility capacities. In Korea, a uniform WQv criterion of 5 mm is applied nationwide, regardless of land use or hydrological conditions. This study examines the suitability of this 5 mm standard in rural catchments using the Hydrological Simulation Program–Fortran (HSPF). Eight sub-watersheds in the target area were simulated under varying cumulative runoff depths (1–10 mm) to assess pollutant loads and runoff characteristics. First-flush effects were most evident below 5 mm, with variation depending on land cover. Nature-based treatment systems for constructed wetlands were modeled for each sub-watershed, and their effectiveness was evaluated using Flow Duration Curves (FDCs) and Load Duration Curves (LDCs). The findings suggest that the uniform 5 mm WQv criterion may result in overdesign in rural watersheds and highlight the need for region-specific standards that consider local land-use and hydrological variability. 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

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

Accurate modeling of pollutant transport during storm events is critical for watershed management and pollution mitigation. This study extends Diskin’s Cell Model, originally developed for rainfall–runoff simulations, to incorporate pollutant transport dynamics. By integrating an Instantaneous Unit Hydrograph (IUH), the model transforms pollutant loads into effective mass transport predictions while ensuring mass conservation. The framework accounts for contamination mobilized by rainfall, including agricultural runoff and industrial discharges, and applies convolution-based routing to capture pollutant dispersion. Calibrations using single-cell, two-cell, and fifteen-cell watersheds validate the model’s predictive capability and demonstrate its effectiveness in estimating pollutant accumulation at downstream locations. The results highlight the model’s potential for scalable water quality assessments, stormwater pollution control, and data-driven watershed management strategies. 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

Mountainous cities are especially vulnerable to flooding and water quality degradation due to surrounding steep terrain, variable precipitation, and fragile ecosystems. Existing studies often rely on small-scale scenario simulations or computationally intensive optimization algorithms, limiting their practical application. This study proposes a spatial layout strategy for stormwater management tailored to mountainous environments, using the Xining sponge city pilot area as a case study. Based on the “source–sink” theory, flood risk was assessed at the district scale, and the Storm Water Management Model (SWMM) was applied to evaluate four Low-Impact Development (LID) deployment schemes. A novel indicator—the source–sink coupling optimization degree (SSCOD)—was introduced to quantify LID spatial coordination between source and sink zones and identify optimal configuration thresholds. Results show that the four LID allocations significantly reduce runoff and improve water quality compared to the no-LID baseline. Analyses also reveal diminishing returns: optimal LID performance occurs when SSCOD ranges from 0.345 to 0.423, with 24.24–24.41% of LID facilities placed in high-risk zones. Beyond this range, effectiveness plateaus or declines, leading to potential resource waste. The proposed framework provides a technical basis and practical strategy for guiding stormwater infrastructure planning in mountainous cities, balancing effectiveness with resource efficiency. 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

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

This study evaluated the allocation of residential detention tanks in the Alto da Boa Vista Condominium, Federal District, Brazil, using hydrological and hydraulic modeling using the PCSWMM software (version 7.6.3610). The objective was to investigate the impact of urbanization on local hydrology, considering the occurrence of erosive processes in the area. Critical points in the infrastructure and regions susceptible to flooding were identified. The methodology involved implementing residential detention tanks in different allocation scenarios, including the use of isochrones. Isochrones, which represent lines of equal concentration time in the drainage network, were employed to segment the basin into three main regions: upstream (ISO 1+2), central (ISO 3+4), and downstream (ISO 5+6). The isochrone-based scenarios enabled the assessment of the impact of concentrating residential detention tanks in these specific zones. Additionally, two other scenarios were analyzed: one with the residential detention tanks uniformly distributed throughout the basin and another without the presence of these devices. Finally, a scenario with a random distribution of residential detention tanks was tested, encompassing a total of 54 distinct configurations, to investigate the influence of different spatial arrangements on the basin’s hydraulic performance. The results indicated that the number of residential detention tanks installed is the main determinant for peak flow attenuation at the basin’s outlet. It was observed that, regardless of the distribution of the devices, whether in concentrated scenarios (upstream, central, and downstream, as defined by the isochrones) or in randomly distributed configurations, the results were similar. In all cases, installing residential detention tanks in more than 30% of the basin area resulted in an approximately 5% reduction in peak flow at the outlet. It is concluded that implementing residential detention tanks is an effective and feasible solution for sustainable stormwater management, significantly contributing to surface runoff control and peak flow mitigation in urbanized areas. Full article

Urbanization and climate change amplify urban flooding risks, demanding efficient, data-minimal tools to strengthen flood resilience. This study presents a pioneering multi-dimensional framework that quantifies the contributions of source reduction, stormwater pipes, and drainage/flood control systems, circumventing the need for intricate hydrological models. Leveraging rainfall depth (mm), runoff volume (m³), and peak flow rate (m³/h) provides a comprehensive evaluation of stormwater management efficacy. Applied to a hypothetical city, City A, under 30- and 50-year rainfall scenarios, the framework reveals efficiencies of 91.0% for rainfall depth and runoff volume, and 90.8% for peak flow in the 30-year case (9% shortfall), declining to 75.7% peak flow efficiency with a 24.3% deficit in the 50-year scenario, underscoring constraints in extreme-event response. Contributions analysis shows stormwater pipes (42.8–47.6%, mean: 46.0%) and drainage/flood control (40.8–43.2%, mean: 41.6%) predominate, while source reduction adds 11.6–14.0% (mean: 12.4%). A primary contribution lies in reducing data demands by approximately 70% compared to traditional approaches, rendering this framework a practical, scalable solution for flood management and sponge city design in data-limited settings. These findings elucidate system vulnerabilities and offer actionable strategies, advancing urban flood resilience both theoretically and practically. Full article

Evaluating the performance of sponge city practices under actual conditions is essential for managing urban stormwater. Existing studies in urban stormwater management have rarely employed numerical simulations to model hydrological processes under actual Three-Dimensional (3D) conditions. In this study, a numerical computational model is developed to simulate the hydrological processes and reveal the temporal and spatial variation of runoff in relation to impervious surfaces and concave herbaceous fields. The applicability of the 3D modules was evaluated using the Chicago rain pattern formula under three recurrence periods: precipitation within one, five, and ten years. The results indicate that the thickness and slope of planting soil are the most sensitive factors regarding sponge city performance, with comprehensive factors of 0.754 and 0.461. The optimal structural parameters of the concave herbaceous field were obtained as follows: aquifer height, 200 mm; planting soil thickness, 600 mm; planting soil slope, 1.5%; planting soil porosity, 0.45; overflow pipeline porosity, 0.3. The flood peak reduction rate, delay rate, and total runoff control rate were the best in a recurrence period of 5a, with 88.93%, 51.11%, and 78.76%, respectively. This study offers technical and conformed methodological support for simulating water quantity processes in sponge cities, and for the control of waterlogging and the recycling of runoff. Full article