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Ongoing and potential future changes in precipitation will affect water management infrastructure. Urban drainage systems are particularly vulnerable. Design standards for many stormwater practices rely on design storms based on precipitation intensity-duration-frequency (IDF) curves. In many locations, climate projections suggest relatively small changes in total precipitation volume, but increased magnitude of extreme events. We develop an approach for estimating future IDF curves that is efficient, can use widely available downscaled GCM output, and is consistent with published IDF curves for the USA that are used in local stormwater regulations and design guides. The method is GCM-agnostic and provides a relatively simple way to develop scenarios in a format directly useful to assessing risk to stormwater management infrastructure. Model biases are addressed through equidistant quantile mapping, in which the modeled change in both the location and scale of the cumulative distribution of storm events from historical to future conditions is used to adjust the extreme value fit used for IDF curve development. The approach requires only precipitation annual maxima, is readily automated, and hits a mid-point between theoretical rigor and ease of application that will be of practical use for the rapid screening of vulnerabilities across projections. We demonstrate estimation of future IDF curves at locations throughout the USA and link IDF-derived design storms to a rainfall-runoff model to evaluate the potential change in storage volume requirements for capture-based stormwater management practices by 2065.

Urban stormwater runoff is an important pathway for the introduction of microplastics and other anthropogenic pollutants into aquatic environments. Highly variable concentrations of microplastics have been reported globally in runoff, but knowledge of key factors within urban environments contributing to this variability remains limited. Furthermore, few studies to date have quantitatively assessed the release of microplastics to receiving waters via runoff. The objectives of this study were to assess the influence of different catchment characteristics on the type and amount of microplastics in runoff and to provide an estimate of the quantity of microplastics discharged during rain events. Stormwater samples were collected during both dry periods (baseflow) and rain events from 15 locations throughout the city of Calgary, Canada’s fourth largest city. These catchments ranged in size and contained different types of predominant land use. Microplastics were found in all samples, with total concentrations ranging from 0.7 to 200.4 pcs/L (mean = 31.9 pcs/L). Fibers were the most prevalent morphology identified (47.7 ± 33.0%), and the greatest percentage of microplastics were found in the 125–250 µm size range (26.6 ± 22.9%) followed by the 37–125 µm size range (24.0 ± 22.3%). Particles were predominantly black (33.5 ± 33.8%), transparent (22.6 ± 31.3%), or blue (16.0 ± 21.6%). Total concentrations, dominant morphologies, and size distributions of microplastics differed between rain events and baseflow, with smaller particles and higher concentrations being found during rain events. Concentrations did not differ significantly amongst catchments with different land use types, but concentrations were positively correlated with maximum runoff flow rate, catchment size, and the percentage of impervious surface area within a catchment. Combining microplastic concentrations with hydrograph data collected during rain events, we estimated that individual outfalls discharged between 1.9 million to 9.6 billion microplastics to receiving waters per rain event. These results provide further evidence that urban stormwater runoff is a significant pathway for the introduction of microplastics into aquatic environments and suggests that mitigation strategies for microplastic pollution should focus on larger urbanized catchments.

Pollutants transported in urban stormwater runoff induce pervasive water quality degradation in receiving waters. To accurately characterize stormwater quality and treatment system performance across the range of possible contaminant characteristics, comprehensive multi-residue analytical methods are necessary. Here, we developed a solid-phase extraction (SPE) and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method to quantify representative stormwater-derived organic contaminants across multiple chemical classes, including vehicle-related chemicals, corrosion inhibitors, industrial chemicals, pesticides, pharmaceuticals and personal care products, and antioxidants. Extraction conditions, isotope-labeled internal standards, and LC-MS/MS parameters were optimized to enhance recovery, minimize matrix effects, and maximize selectivity and sensitivity. The developed method was sensitive (method quantification limits < 10 ng/L for > 80% of selected analytes) and accurate (mean relative recoveries in the range of 70–130%, with relative standard deviations < 25% for 77% of the analytes) for most of the analytes. The method was used to analyze samples collected from nine urban watersheds during a storm event; 62% of the 39 analytes were detected at least once at concentrations up to 540 ng/L (1,3-diphenylguanidine). Spatial trends in detection and concentration were observed for vehicle-related and industrial chemicals that correlated with vehicle traffic. Total concentrations of pesticides suggested that residential uses could be more important sources than agriculture. This study illustrates the pervasive occurrence of a wide variety of stormwater-derived chemicals in urban receiving waters and highlights the need to better understand their environmental fate and ecological implications.

Urban waterlogging and the deterioration of receiving water quality caused by stormwater runoff have become increasingly significant problems. Based on the concept of combining grey and green infrastructure, a combined permeable concrete pavement (PCP) and constructed wetland (CW) system has been developed to treat stormwater runoff and enable on-site reuse. The results showed that the removal rate of suspended solids (SS) by PCP ranged from 96.61 to 99.20%; however, the chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) concentrations in the effluent did not meet the standards required for rainwater reuse. For the combined PCP-CW system, the removal rates of COD, TN and TP by the CW were 48.45–75.12%, 47.26–53.05%, and 59.04–75.28%, respectively, under different hydraulic loading (HL) rates; thus, the effluent TN concentrations did not consistently meet the reuse standards. Further optimization of aeration in different parts of the CW revealed that aeration in the middle and front sections of the wetland had the most significant effect on pollutant removal, under which the TN concentrations in the effluent met the standard required for reuse. The effluent from the combined PCP-CW system was able to fully meet the stormwater reuse standards under these optimized conditions, and the reuse of urban stormwater runoff can therefore be realized.

Urban development affects the quantity and quality of urban surface runoff. In recent years, the best management practices (BMPs) concept has been widely promoted for control of both quality and quantity of urban floods. However, means to optimize the BMPs in a conjunctive quantity/quality framework are still under research. In this paper, three objective functions were considered: (1) minimization of the total flood damages, cost of BMP implementation and cost of land-use development; (2) reducing the amount of TSS (total suspended solid) and BOD5 (biological oxygen demand), representing the pollution characteristics, to below the threshold level; and (3) minimizing the total runoff volume. The biological oxygen demand and total suspended solid values were employed as two measures of urban runoff quality. The total surface runoff volume produced by sub-basins was representative of the runoff quantity. The construction and maintenance costs of the BMPs were also estimated based on the local price standards. Urban runoff quantity and quality in the case study watershed were simulated with the Storm Water Management Model (SWMM). The NSGA-II (Non-dominated Sorting Genetic Algorithm II) optimization technique was applied to derive the optimal trade off curve between various objectives. In the proposed structure for the NSGA-II algorithm, a continuous structure and intermediate crossover were used because they perform better as far as the optimization efficiency is concerned. Finally, urban runoff management scenarios were presented based on the optimal trade-off curve using the k-means method. Subsequently, a specific runoff control scenario was proposed to the urban managers.

PurposeThe objective of this paper is to review nature-based solution (NbS) research and design practices and identify knowledge gaps that may create barriers to effective NbS implementation for management of particle-bound metals.MethodsA case study of two constructed wetlands in residential areas of Geelong, Australia, is presented with an extended literature review to address the research objective. Bed sediment was collected at 38 sites in the Grand Lakes constructed wetland and 17 sites in the Warralily wetland for analysis of total Pb, Cu, Zn, Cr, and Cd using X-Ray Fluorescence. Benthic macroinvertebrates were sampled at five sites around the inlet to the Warralily wetland and five sites near the outlet. Macroinvertebrates were identified to the lowest practical level using local identification keys and categorized with the Shannon-Weiner Diversity Index and presence/absence of pollutant-tolerant organisms.ResultsThe wetland sediments were not grossly polluted, but a limited number of samples exceeded the consensus-based probable effect concentration (PEC) for aquatic organisms. The highest metal levels were associated with the designed depositional areas. Benthic macroinvertebrate communities were less diverse and exhibited a more pollutant-tolerant assemblage near the inlet depositional area of the Warralily wetland, compared to the outlet area.ConclusionNature-based solution is an emerging focus of urban design and with careful multidisciplinary guidance can provide effective water management options in balance with habitat opportunities and community wellbeing. Based on the combined case study wetland results and the literature review, future research should focus on characteristics of bioretention cell mitigation for metal treatment (including the role of vegetation and substrate amendments), metals bioavailability, climate-specific design characteristics, developing system-wide, connected design guidelines rather than individual discrete feature design guidelines, establishing a standardized weight-of-evidence approach to assess ecological risk in NbS systems, and full cost accounting of NbS systems.

The stormwater runoff may act as a nonpoint pollutant source and contributes to aquatic ecosystem quality decay in urban environments. The aim of this work was to evaluate the runoff characteristics on the transport of total solids and total metals, as well as pH and conductivity responses during the rainfall evolution. During 2017 and 2018, 12 rain events were monitored in 4 sampling stations at a car parking lot located at Nuclear and Energy Research Institute (IPEN/CNEN) in São Paulo/Brazil. A 4-chamber integrated collector allowed the sequential/temporal runoff evolution assessment. The runoff composition, in decreasing order of quantities, was Ca > K > Mg > Si > Al > Fe > Na > Zn > Mn > Sr > Ti > Mo > V > Cu > B > Pb > Ni > Ce > Sb > Cr > La > U > Th > Cd. The amount of total solids, Al, and Fe exceeded the Brazilian water quality standards. Principal component analysis (PCA) identified the elemental clusters linked to the facility activity, soil, and traffic/atmospheric-related deposition. The results show that the runoff characteristics could be differentiated by pollutant source. Factors such as seasonal variation, rain event intensity, air mass from oceanic or continental origin, spatial distribution inside the monitoring area, and the intensity of the first flush must be considered in order to disentangle the elemental clusters and pollution source contributions. In winter, continental air masses were associated with higher concentrations of heavy metals in the surface runoff. Spatial changes with no seasonal variation were observed for U, Th, La, and Ce.

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.

The paper presents a geochemical approach to estimating the local background values of major ionic solutes and trace elements in headwater streams. Understanding the natural geochemical properties of each surface water body is essential for tracking environmental changes, identifying anthropogenic influences, and establishing baseline conditions for water quality management. This research aims to evaluate the elemental concentrations, water quality, and background values (BGVs) of stream water through systematic sampling, laboratory analysis, and hydrogeochemical and statistical interpretations. Water samples were analyzed for hydrochemical solutes such as major cations and anions using standard procedures, whereas concentrations of 44 trace elements, including heavy metals and metalloids, were determined using inductively coupled plasma mass spectrometry (ICP-MS). Water samples were collected in places that were unaffected by industrial or mining activity, as well as in generally clean areas. Statistical techniques were employed to distinguish between natural variability and potential human impacts. Hence, the mean + 2SD was then used to determine the BGV. In addition, spatial distribution maps of hydrochemical parameters were used to identify potential sources of contamination. The obtained concentrations were then compared to global water quality standards. The calculated BGVs revealed critical concentration levels of Al and Fe that surpassed the maximum limitations set by the legislation. These significantly elevated levels may constitute a health risk to people, particularly in rural locations where they rely solely on stream water and the aquatic environment. Heavy metals and metalloids including As, Cr, Cd, Pb, Ni, Hg, Zn, Cu, and Mn are found in trace amounts or below detection limits and pose no threat to the environment or human health. The levels of dissolved REEs in water samples are relatively low, indicating a geologic source. The proposed BGVs will serve as a reference to determine the impact of human activities (such as industrial discharges, agricultural runoff, and urban expansion) on water quality at the local level. The geochemical study of water also provides a robust framework for assessing the health of public and aquatic ecosystems and designing effective environmental management plans.