Stormwater Pollutant Loads Research Articles

Impacts of climate change on urban stormwater runoff quantity and quality in a cold region

Climate change poses significant challenges to urban environments affecting both flood risks and stormwater pollutant loadings. However, studies on variations in stormwater runoff quantity and quality in cold regions, which are highly sensitive to climate change, are notably limited. Integrating climatic, hydrologic, and hydraulic modelling, the study assesses the potential impacts of climate change on stormwater runoff volume and pollutant dynamics in a Canadian urban watershed (Calgary). A two-year field program was conducted to support the calibration and validation of the Storm Water Management Model (SWMM). Intensity–duration–frequency curves were employed to evaluate the impacts of climate change on peak flow rate and flooding duration. In addition, typical dry, average, and wet years were applied to continuously simulate stormwater runoff quantity and quality during the 2050s and 2080s. The results suggest substantial increases in peak flow rates and flooding durations, particularly for the 5-year return period rainfall, with 1-h, 4-h, and 24-h peak inflow rates increasing by 74.3% (170.7%), 89.2% (158.4%), and 64.1% (102.8%) in the 2050s (2080s) Furthermore, the runoff quantity is projected to rise by 2.4–10.2% in the 2050s and 11.8–17.5% in the 2080s. Total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) loadings are anticipated to increase by 2.0–36.1%, 3.1–21.4%, and 4.1–20.7%, respectively. As a result, the current stormwater system could overload and stormwater quality is likely to deteriorate under the impact of climate change. The findings are beneficial for cold regions to develop adaptive strategies that enhance urban water security and environmental sustainability under climate change.

Erratum to: An Adaptive Toolkit for Projecting the Impact of Green Infrastructure Provisions on Stormwater Runoff and Pollutant Load—A Case Study on the City of Galena Park, Texas, USA

Erratum to: An Adaptive Toolkit for Projecting the Impact of Green Infrastructure Provisions on Stormwater Runoff and Pollutant Load—A Case Study on the City of Galena Park, Texas, USA

Stormwater Suspended Solids and Pollutant Concentrations in an Urban Stream

The chemical and ecological quality of small rivers or streams is not normally classified, but any urban stormwater discharges will result in their impairment. To assist in understanding the resulting applied environmental stress to benthic communities, the empirical relationships between in-stream suspended solids and metal pollutants, initially identified by principal component analysis, are explored using data from a small urbanised upland catchment. When data are amalgamated from individual storms, a correlation for each metal pollutant with suspended solids is obtained, starting very strongly, and decreasing in the order Fe > Al > Mn > Pb > Cr > Zn > Cu > Ni. Comparison of pollutant/solids correlations for individual storms is, for some metals, excellent, but differing intercepts and/or gradients can be obtained for an individual metal between storms. The practice of assessing their correlation based on event mean concentrations or longer-term averages across several storm events may conceal strong correlations for individual storms, exemplifying the impact of variable catchment characteristics and storm conditions; Cd and Be are poorly correlated with suspended solids and are likely affected by changes in background pollution levels. The analysis of covariance also highlights a significant difference between certain storm events for specific metals, which calls into question the validity of using combined storm-event datasets. The relationships identified here enable the determination of stormwater pollutant loads from suspended solids concentrations for heavy metals and are useful for developing water quality assessments.

Improving detention ponds for effective stormwater management and water quality enhancement under future climate change: a simulation study using the PCSWMM model

Urban surfaces are often covered by impermeable materials such as concrete and asphalt which intensify urban runoff and pollutant concentration during storm events, and lead to the deterioration of the quality of surrounding water bodies. Detention ponds are used in urban stormwater management, providing two-fold benefits: flood risk reduction and pollution load minimization. This paper investigates the performance of nine proposed detention ponds (across the city of Renton, Washington, USA) under different climate change scenarios. First, a statistical model was developed to estimate the pollutant load for the current and future periods and to understand the effects of increased rainfall on stormwater runoff and pollutant loads. The Personal Computer Storm Water Management Model (PCSWMM) platform is employed to calibrate an urban drainage model for quantifying stormwater runoff and corresponding pollutant loads. The calibrated model was used to investigate the performance of the proposed nine (9) detention ponds under future climate scenarios of 100-year design storms, leading to identifying if they are likely to reduce stormwater discharge and pollutant loads. Results indicated significant increases in stormwater pollutants due to increases in rainfall from 2023 to 2050 compared to the historical period 2000–2014. We found that the performance of the proposed detention ponds in reducing stormwater pollutants varied depending on the size and location of the detention ponds. Simulations for the future indicated that the selected detention ponds are likely to reduce the concentrations (loads) of different water quality constituents such as ammonia (NH3), nitrogen dioxide (NO2), nitrate (NO3), total phosphate (TP), and suspended solids (SS) ranging from 18 to 86%, 35–70%, 36–65%, 26–91%, and 34–81%, respectively. The study concluded that detention ponds can be used as a reliable solution for reducing stormwater flows and pollutant loads under a warmer future climate and an effective adaptation option to combat climate change related challenges in urban stormwater management.

An Adaptive Toolkit for Projecting the Impact of Green Infrastructure Provisions on Stormwater Runoff and Pollutant Load-A Case Study on the City of Galena Park, Texas, USA.

The implementation of green infrastructure in retrofit projects to reduce flooding and pollution is a significant challenge in space- constrained and overly developed communities which also have complex underground utility systems. To overcome this challenge, the authors have developed an adaptive green infrastructure toolkit that can be tailored by both on-ground spatial size and underground depth of obstruction. This study aims to assess the effectiveness of this toolkit in mitigating flooding and non-point source pollutants by demonstrating the case of the city of Galena Park, Texas, USA, which has suffered from severe flooding as well as on-ground and underground space constraint issues. We first applied the toolkit to create a master plan for Galena Park and evaluated the effect of the plan by using the Delft3D-FM (Flexible Mesh) flood model alongside the Long-Term Hydrologic Impact Assessment (L-THIA) model. The results demonstrate progressive reductions in stormwater runoff and NPS pollutants across different phases. These findings highlight the toolkit's effectiveness in improving water management and pollution control, providing valuable empirical evidences for similar communities facing similar challenges.

Urban stormwater runoff pollutant loadings: GIS land use classification vs. sample-based predictions.

Cities are growing worldwide with an increase in stormwater quantity and decrease in quality, negatively impacting receiving water bodies. The characterization of stormwater is difficult given its high variability and the typically numerous outfalls to be monitored. However, loadings can be estimated via models and validated using actual outfall monitoring. This study determined stormwater pollutant loadings predicted using eight land-use classifications (i.e., a 'desktop' study) and via an outfall sampling regime (i.e., a 'monitoring' study) for seven stormwater catchment areas in Saskatoon, SK, Canada, where stormwater typically releases directly into the South Saskatchewan River. Pollutants considered were total suspended solids (TSS), chemical oxygen demand (COD), metals, and polycyclic aromatic hydrocarbons. Catchment areas were dominated by single-family residential (39%) and green areas (17%). The largest catchment area, Preston Crossing, was the major source of the predicted annual loadings, such as TSS at 550,000kg and COD at 265,000kg. For comparison, the sampled-based estimated loadings for TSS and COD were 362,700kg and 652,700kg, respectively. Differences between the average predicted and actual estimations ranged from 29 to 156% for the eight pollutants considered, with averages for the summed pollutants in each catchment area ranging from 48 to 130%. Overall, the assessment and monitoring of stormwater outfalls are needed for the determination of impacts of loadings on the environment and for the subsequent development and implementation of treatment technologies.

Land cover based simulation of urban stormwater runoff and pollutant loading

Urban stormwater models such as PCSWMM are important tools for evaluating urban stormwater quantity and quality. However, due to the lack of consideration of land covers, traditional catchment delineation methods have defects in model precision, parameter transferability and assessment of contribution from individual land cover types. This paper used PCSWMM model as a foundation, built a new land-cover based (LCB) model and made a systematic comparison with the traditional watershed delineation tool (WDT) model to study the impacts of land cover on the simulation of stormwater runoff and pollutant loading. The models were applied to two urban catchments in Calgary, Canada. The results revealed that the LCB model performed better than the WDT model in hydrological simulation, and land cover consideration can considerably improve model accuracy. The two models showed comparable performances in simulation of total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) loading. The LCB model parameters could be regionalized based on land cover types. The hydrologic-hydraulic parameters can be satisfactorily transferred from neighboring gauged catchments to similar ungauged catchments. The transferring of water quality parameters did not perform as satisfactory. The LCB model could quantitively evaluate the contribution to runoff and pollutant loads of different land covers. Roads and roofs were found to be the major contributors to urban runoff and pollutants in the two urban catchments. Green space became important only during large storms events and its contribution could be ignored during dryer years.

Efficiencies of indigenous South African plant biofilters for urban stormwater runoff water quality improvement with a focus on nutrients and metals

Abstract In South Africa, urban activities contribute high levels of pollution to rivers and groundwater via stormwater runoff. In reducing urban stormwater loads of engineered plant biofiltration, an effective and self-sustaining component of green infrastructure is a treatment option. The country's extensive natural biodiversity offers untapped potential of indigenous species' use in plant biofilters. This paper presents the findings of a plant biofilter column experiment, which investigated the performance of nine indigenous plant species under varied urban stormwater pollutant load strengths. Average significant loads of dissolved Cd (>98%), Cu (>84%), Pb (>99%) and Zn (>95%), as well as NH3-N (>93%), were removed by the plant biofilters, whereas the removal of -N (−37 to 79%) and -P (−81 to 63%) was more variable. Biofilters equipped with indigenous plant species were on average at least 11% more efficient than unvegetated soil in the removal of urban nutrient and metal pollutants. Over time, planted biofilters improved nutrient and metal removal efficiencies. The results support the inclusion of indigenous plants in biofilters within urban stormwater green infrastructure initiatives. Further research to inform plant biofilter design practicalities and assess plant biofilter performance in the field is warranted.

Hybrid approach for urban hilly catchment runoff modelling and prediction of pollutant loads

ABSTRACT This paper presents a hybrid approach for stormwater runoff modelling and pollutant load estimation in a hilly catchment. The stormwater runoff hydrograph was simulated by developing a conceptual hybrid model (HM) using transfer function. Model parameters were estimated by non-linear optimization. The simulated runoff hydrographs showed an excellent match with the observed data. Next, a relationship was developed between runoff and pollutant load and the developed relationship was used for estimation of pollutant load. A novelty of this hybrid approach is that it could bring out a generic HM. By using the derived model, the pollutant load was successfully predicted from simulated runoff (R2 > 0.75) by considering rainfall as the only input. In addition, assessment, characterization and analysis of the first flush of urban runoff also form part of the study. The HM was tested and validated by applying it to 25 storm events monitored during two monsoon seasons in the Nainital Lake catchment (approx. 1900 m a.m.s.l.), India.

The hydrologic, water quality and flow regime performance of a bioretention basin in Melbourne, Australia

ABSTRACT To restore streams degraded by urbanisation, bioretention basins (‘raingardens’) are implemented worldwide to reduce stormwater volumes, peaks flows and pollutant loads entering streams. While they are effective at this, their ability to mimic natural flow regimes has received limited field investigation. We monitored the hydrology and water quality of a bioretention basin during a three-year period. We found that the basin reduced the delivery of polluted water to the stream (55–65% of catchment runoff released as treated outflow), with peak flows and event concentrations of TSS, TP and TN substantially lowered too. A smaller proportion of catchment runoff infiltrated into the surrounding soil, but the flow regime delivered by the basin to the local stream was not similar to nearby forested streams. Such systems can mitigate the impacts of urban runoff on streams and shift the urban water balance towards natural conditions, but complete flow regime restoration requires catchment-scale action.

Quantifying clogging patterns of infiltration systems to improve urban stormwater pollution reduction estimates

Infiltration systems are among the most commonly implemented practices to control urban stormwater and to attenuate pollutant delivery to receiving waters, because they are relatively cheap to build and amenable to space constraints in urbanized areas. However, infiltration systems tend to clog with sediments, which can rapidly reduce their performance. While clogging has been consistently identified as a significant determinant on infiltration BMP (best management practice) performance and lifespan, there have been few methods reported to predict rates of clogging or incorporate insights to urban catchment water quality modeling. We ran a series of laboratory and field experiments to identify clogging mechanisms and quantify infiltration performance declines as a function of sediment loading. The results show rapid initial declines of infiltration rate, primarily due to accumulation of material at the bottom of the infiltration BMP. The performance decline trajectories were sensitive to BMP geometry, with BMPs that had greater lateral infiltration surface area declining less quickly. We integrated these experimental results to a spatially distributed stormwater model to illustrate how they can be used to predict BMP performance declines over time and assess cost trade-offs. Results will be used to adapt algorithms in a cloud-based stormwater management platform to better inform maintenance needs for cities and improve the accuracy of urban stormwater pollutant load reduction estimates that support regulatory compliance tracking.

A participatory approach based on stochastic optimization for the spatial allocation of Sustainable Urban Drainage Systems for rainwater harvesting.

Rainwater Harvesting (RWH) is the practice of capturing and storing stormwater for later use. In addition to being an alternative source of water for non-potable applications, RWH is also used to effectively reduce stormwater runoff volumes and pollutant loads dropped into sewage systems. RWH is typically carried out by placing a variety of Sustainable Urban Drainage Systems (SUDS) in different locations of the urban landscape. However, because of the staggering number of potential combinations of SUDS typologies and spatial configurations that can be used, identifying a strategy that optimally selects and allocates SUDS to maximize the benefits of RWH is a complex endeavor. One of the challenges that emerges during the optimal design and location of these systems is incorporating the inherent uncertainty of the rainfall. In this paper, we develop a flexible computational framework that couples a Geographic Information System (GIS) with a two-stage stochastic mixed integer linear program (TS-MILP) to select and locate SUDS in order to minimize the use of potable water for irrigation and reduce the water runoff at a minimum cost. This framework incorporates an iterative participatory approach to engage stakeholders in the decision-making process. We tested the proposed methodology on a case study for the central campus at Universidad de Los Andes (Bogotá, Colombia). Our results showed that the expected value of the total runoff volume and the consumption of potable water can be reduced up to 67% and 50%, respectively.

A field and laboratory investigation of kerb side inlet pits using four media types

Kerb side inlets with adjacent leaky wells are an emerging tool to harvest stormwater and to reduce runoff volumes and peak flow rates. This is achieved by collecting the first flush runoff into kerb side storages and infiltrating this water into the surrounding soil, thereby also reducing stormwater pollutant loadings. The hydraulic performance of the kerb side inlet, filter media and surrounding soil are key factors in the performance of these systems. However, no field or laboratory data are currently available for the hydraulic performance of a kerb side tree inlet pit. In this study, 12 tree inlet pits were constructed and filled with various media types including gravel, water treatment solids (a recycled waste product), sandy loam and clay to examine (1) leaky well infiltration rates (2) emptying times of the wells and (3) the well capacity (runoff storage volume) before and after runoff filtering through the wells. Using a laboratory model, the water harvesting performance of the kerb side inlet plate was also examined for various road longitudinal slopes. Using the field and laboratory data, simulation of the well performance was undertaken using the Model for Urban Stormwater Improvement Conceptualisation (MUSIC) to assess the capacity of these systems to reduce runoff volumes at the residential street scale. It was hypothesised that the type of filter media used in leaky well systems has a significant impact on the infiltration rate, regardless of the native soil type through which the stormwater eventually infiltrates. The results showed that the infiltration rates of systems filled with gravel were significantly higher than for the other media types, and this was followed by water treatment solids, sandy loam and clay. The results of the MUSIC modelling indicated that 2.8% of the mean annual runoff volume in the catchment could be harvested by the systems at the case study site. It was found that selection of high infiltration rate media and regular maintenance are the key factors for maintaining long-term performance of these systems.

Assessment of stormwater pollutant loads and source area contributions with storm water management model (SWMM)

Decentralized urban runoff management requires detailed information about pollutant sources and pathways. However, scarce data of local water quality compel simplified approaches in water quality modelling. This study investigated the use of constant source concentrations in modelling pollutant loads. The source area contributions of total suspended solids, total phosphorus, total nitrogen, lead, copper and zinc were modelled with SWMM based on literature event mean concentrations (EMCs) for different land cover types and on-site rainfall and discharge data for a residential area in southern Finland. The simulated pollutant loads were compared with loads measured at the catchment outlet. Large differences were evident in the modelled catchment-scale and land cover specific loads, depending on the EMC data source. The simulated loads exceeded the measured loads especially during wet conditions, which was explained by the dilution effect of large stormwater volumes on measured EMCs. In addition, the mismatch was explained by the lack of local data for the source area EMCs and by the unaccountability of the mechanisms affecting loads along the pollutant pathways from source areas to sewer outlet. The spatial simulation of stormwater pollutant loads enabled the assessment of source area contributions at the catchment scale, as well as the pollutant pathways and the total diffuse pollution load. For a single pollutant, one or two important pollutant sources contributed the majority of the catchment load, which provides useful information for stormwater management. However, for a group of pollutants, no single land cover type dominated the pollutant loads, reflecting the challenges in decentralized water quality management in the scale of a residential area. Overall, the results emphasize that the widely used stormwater quality modelling with constant EMCs is uncertain even when on-site water quality and rainfall-runoff data from a catchment outlet are available.

Evaluation of field-scale stormwater bioretention structure flow and pollutant load reductions in a semi-arid coastal climate

Bioretention has become an effective option for the treatment of stormwater in urbanized watersheds. This field-scale study evaluated a bioretention system designed to reduce runoff volume and pollutant loading and compared its performance over a 13-month period with that of traditional asphalt pavement located in the same parking area at South Texas College (STC), McAllen, Texas. The average runoff volume from the bioretention cell was 82% lower than that of the traditional asphalt pavement section. Water quality samples from bioretention effluents showed a significant reduction (p < 0.05) in various pollutants, including indicator bacteria. For indicator bacteria, the bioretention showed an overall E. coli removal of 49%. Antecedent dry periods were found to influence the treatment performance of runoff reduction and water quality improvement. The bioretention cell field results were used to evaluate WinSLAMM model performance, and the calibrated model outflow volumes were not significantly (p > 0.05) different and showed a strong correlation with the observed results and calculated storage volumes.

Modelling stormwater runoff, quality, and pollutant loads in a large urban catchment

Modelling stormwater runoff, quality, and pollutant loads in a large urban catchment

Post Construction Green Infrastructure Performance Monitoring Parameters and Their Functional Components

Drainage system infrastructures in most urbanized cities have reached or exceeded their design life cycle and are characterized by running with inadequate capacity. These highly degraded infrastructures are already overwhelmed and continued to impose a significant challenge to the quality of water and ecological systems. With predicted urban growth and climate change the situation is only going to get worse. As a result, municipalities are increasingly considering the concept of retrofitting existing stormwater drainage systems with green infrastructure practices as the first and an important step to reduce stormwater runoff volume and pollutant load inputs into combined sewer systems (CSO) and wastewater facilities. Green infrastructure practices include an open green space that can absorb stormwater runoff, ranging from small-scale naturally existing pocket of lands, right-of-way bioswales, and trees planted along the sidewalk as well as large-scale public parks. Despite the growing municipalities’ interest to retrofit existing stormwater drainage systems with green infrastructure, few studies and relevant information are available on their performance and cost-effectiveness. Therefore, this paper aims to help professionals learn about and become familiar with green infrastructure, decrease implementation barriers, and provide guidance for monitoring green infrastructure using the combination of survey questionnaires, meta-narrative and systematic literature review techniques.

Surface Water Storage Capacity of Twenty Tree Species in Davis, California.

Urban forestry is an important green infrastructure strategy because healthy trees can intercept rainfall, reducing stormwater runoff and pollutant loading. Surface saturation storage capacity, defined as the thin film of water that must wet tree surfaces before flow begins, is the most important variable influencing rainfall interception processes. Surface storage capacity is known to vary widely among tree species, but it is little studied. This research measured surface storage capacities of 20 urban tree species in a rainfall simulator. The measurement system included a rainfall simulator, digital balance, digital camera, and computer. Eight samples were randomly collected from each tree species. Twelve rainfall intensities (3.5-139.5 mm h) were simulated. Leaf-on and leaf-off simulations were conducted for deciduous species. Stem and foliar surface areas were estimated using an image analysis method. Results indicated that surface storage capacities varied threefold among tree species, 0.59 mm for crape myrtle ( L.) and 1.81 mm for blue spruce ( Engelm.). The mean value across all species was 0.86 mm (0.11 mm SD). To illustrate application of the storage values, interception was simulated and compared across species for a 40-yr period with different rainfall intensities and durations. By quantifying the potential for different tree species to intercept rainfall under a variety of meteorological conditions, this study provides new knowledge that is fundamental to validating the cost-effectiveness of urban forestry as a green infrastructure strategy and designing functional plantings.

Evaluation of stormwater runoff quality during monsoon and inter-monsoon seasons at tropical urban catchments

ABSTRACTInformation on pollution level and the influence of a hydrologic regime on stormwater pollutant loading in tropical urban areas remains scarce. More local data is still required, as rainfall and runoff generation processes in tropical environment differ greatly from temperate regions. This study compares the stormwater runoff quality from urban catchments during monsoon and inter-monsoon seasons in the south of Peninsular Malaysia. Stormwater samples and flow rate data were collected from 38 storm events at three individual sites. Samples were analysed for total suspended solids (TSS), 5-day biochemical oxygen demand (BOD), chemical oxygen demand (COD), oil and grease (O&G), nitrate nitrogen (NO3-N), ammoniacal nitrogen (NH3-N), and total phosphorus (TP). Event mean concentration (EMC) was calculated for each pollutant for every monitored storm event at all study sites. The Mann–Whitney test was used to test for significance (p < 5%) in differences between the median EMCs of the pollutants. The results revealed that EMCs for stormwater runoff during the monsoon season were lower than that during the inter-monsoon season. Significant differences (p < .05) were found for EMC values for TSS, oil and grease, NH3-N, and TP but not for BOD, COD, and NO3-N. Stormwater pollutant loading of TSS, NH3-N, and TP is higher during the inter-monsoon season while BOD, COD, and NO3-N show higher loadings during the monsoon season. A better understanding of pollutant transport mechanisms will aid in formulating an effective stormwater management measures to control the urban stormwater pollution in the tropics.

Land-use based stormwater pollutant load estimation and monitoring system design

Accurate quantification of the amount, quality and sources of urban stormwater runoff are a prerequisite for effective stormwater management. The goal of this study was to estimate city-scale stormwater pollutant export, examine the effect of data sources on export estimates, and develop an optimization method for stormwater monitoring. The results were presented for the city of Lahti in southern Finland, where site mean pollutant concentrations (SMCs), annual pollutant loads, and monitoring guidelines for specific land use types were determined for total suspended solids (TSS), nutrients (total nitrogen TN and total phosphorus TP), chemical oxygen demand (COD), and metals (Pb, Zn, Cu, Cr, and Ni). Depending on the data source, differences between estimated pollutant exports ranged from -89% to 215%. Lack of reference data for every urban land use type and differences in land use classification schemes were identified as key factors limiting the accuracy of pollutant load estimation.