Analysis of swale factors implicated in pollutant removal efficiency using a swale database

Harnessing the runoff reduction potential of urban bioswales as an adaptation response to climate change

Nature-based solutions (NbS), including China's Sponge City Program (SCP), can address the challenges urban communities face due to surface runoff and flooding. The current capacity of SCP facilities in urban environments falls short of meeting the demands placed on communities by climate change. Bioswales are a form of SCP facility that plays an important role in reducing surface runoff by promoting infiltration. This study assesses the potential of SCP facilities to reduce runoff in urban communities under climate change using the storm water management model. The study site in Ningbo, China, was used to evaluate the potential role of bioswales in reducing runoff risks from climate change. We found that bioswales were most effective in scenarios when rainfall peaks occurred early and were less effective in right-skewed rainfall events. The overall performance of SCP facilities was similar across all climate scenarios. To maintain the current protection level of SCP facilities, bioswales would need to cover at least 4% of the catchment area. These findings from Ningbo provide a useful method for assessing NbS in other regions and indicative values for the increase in the bioswale coverage needed to adapt to climate change.

Screening of representative rainfall event series for long-term hydrological performance evaluation of grassed swales

Evaluation of the hydrological performance of grassed swales usually needs long-term monitoring data. At present, suitable techniques for simulating the hydrological performance using limited monitoring data are not available. Therefore, current study aims to investigate the relationship between saturated hydraulic conductivity (Ks) fitting results and rainfall characteristics of various events series length. Data from a full-scale grassed swale (Enschede, the Netherlands) were utilized as long-term rainfall event series length (95 rainfall events) on the fitting outcomes. Short-term rainfall event series were extracted from these long-term series and used as input in fitting into a multivariate nonlinear model between Ks and its influencing rainfall indicators (antecedent dry days, temperature, rainfall, rainfall duration, total rainfall, and seasonal factor (spring, summer, autumn, and winter, herein refer as 1, 2, 3, and 4). Comparison of short-term and long-term rainfall event series fitting results allowed to obtain a representative short-term series that leads to similar results with those using long-term series. A cluster analysis was conducted based on the fitting results of the representative rainfall event series with their rainfall event characteristics using average values of influencing rainfall indicators. The seasonal index (average value of seasonal factors) was found to be the most representative short rainfall event series indicator. Furthermore, a Bayesian network was proposed in the current study to predict if a given short-term rainfall event series is representative. It was validated by a data series (58 rainfall events) from another full-scale grassed swale located in Utrecht, the Netherlands. Results revealed that it is quite promising and useful to evaluate the representativeness of short-term rainfall event series used for long-term hydrological performance evaluation of grassed swales.

The influence of the correlation-covariance structure of measurement errors over uncertainties propagation in online monitoring: application to environmental indicators in SUDS

This paper presents a methodology to assess the influence of the correlation-covariance structure of measurement errors in online monitoring over the propagation of uncertainties, applied to wet-weather environmental indicators in sustainable urban drainage systems (SUDSs). The effect of auto-correlated and heteroskedastic errors in measured time-series over the estimated probability density function (PDF) of different environmental indicators is analyzed for a wide variety of possible error structures in the data. For this purpose, multiple correlation-covariance structures are randomly generated from exploring the parametric space of a linear exponent autoregressive (LEAR) model, employing a Bayesian-based Markov Chain Monte Carlo sampling technique. Significant differences tests are proposed to identify the most correlated parameters of the correlation-covariance error model with statistics of the environmental indicator PDFs. The method is applied to total suspended solids (TSS) and chemical oxygen demand (COD) time-series recorded during 13 rainfall events at the inlet and outlet of a SUDS train (stormwater settling tank-horizontal constructed wetland). In this case, results showed that the total error in the estimation of the analyzed environmental indicators is mostly explained by standard uncertainties (flattening of the PDFs) rather than bias contributions (displacement of the PDFs). The correlation-covariance model parameters related to the temporal delimitation of hydrographs/pollutographs and the intensity of the autocorrelation showed to have the strongest influence in the propagation of measurement errors (flattening/displacement of the PDFs).

Metal enrichment of soils in three urban drainage grass swales used for seasonal snow storage

Enrichment of soils in three urban drainage swales by metals associated with traffic sources was investigated in a cool temperate climate with seasonal snow. Such swales differed from those not exposed to snow by receiving additional pollutant loads from winter road maintenance involving applications of salt and grit, use of studded tires, and storage and melting of polluted snow cleared from trafficked areas into swales. Among the swales studied, swale L2 in the downtown was the oldest (built around 1960), drained runoff from a road with the highest traffic intensity, and exhibited the highest mean concentrations of most of the metals studied (Pb, Cu, Zn, Cr, Cd, Ni, Co, V, Ti, and W). In the case of Pb, this exceedance was about an order of magnitude: 71 mg/kg DW in L2, compared to about ~8 mg/kg DW in L1 and L3, both built in 1979. Among the metals originating from local geology, barium (Ba) was found in the swales and the grit material at high concentrations of ~650 mg/kg DW and 700-1000 mg/kg DW, respectively. Such concentrations exceeded the Swedish EPA guideline limits of 300 mg/kg DW for less sensitive soil use. The sequential extraction analysis of samples from swale L2 indicated that Ba was mostly in the immobile residual fraction (90%). The absence of clear decline in metal concentrations with distance from the trafficked surfaces suggested that stored snow was another source of metals partly balancing spatial distribution of metals in swale soils.

Evaluating the relationships between specific drainage area characteristics and soil metal concentrations in long-established bioswales receiving suburban stormwater runoff

Bioswales are used to attenuate stormwater pollution, but their long-term sustainability regarding sequestered metals is relatively unknown, and a clear rationale for prioritizing soil management is lacking. Impervious areas draining into four 14-year-old suburban bioswales were delineated, for which surface soils (top 10 cm; 72 samples) were sampled; soils from 4 adjacent reference sites were also sampled. Total and water soluble metals (Cd, Cu, Pb, Zn) were quantified, and the relationships between metal concentrations and drainage area characteristics evaluated. Annual metal loads were estimated using regional runoff data to simulate current and future metal concentrations; risks to soil biota were assessed by comparing metal concentrations to ecological screening levels. The drainage areas' percent imperviousness (37-71%) and ratios of impervious drainage area to bioswale area (2.0-5.7) varied, owing to differing proportions of rooftops, paved surfaces, lawns, and natural soils. Total Cu and Zn ranged from 10.0 to 43.2 mg/kg dry soil, and 15.6 to 129.5 mg/kg dry soil, respectively. Across all bioswales, total Zn was positively correlated to percent impervious area (r = 0.32, p = 0.0073), the ratio of connected impervious drainage area to infiltration area (r = 0.32, p = 0.0073), and percent drainage area as paved surfaces (r = 0.46, p = 5.6 E-05), but negatively correlated to percent drainage area as lawns (r = -0.48; p = 2.4 E-05). Water soluble metal concentrations were orders of magnitude lower than total metals. Given annual metal loads (0.2-0.4 mg Cu/kg dry soil; 1.5-3.1 mg Zn/kg dry soil), replacing bioswale soils to constrain metal concentrations would be unnecessary for decades. Taken together, this study proposes a transferable approach of estimating, then verifying via sampling and analysis, bioswale soil metal concentrations, such that soil management decisions can be benchmarked to ecological screening levels.

Next generation swale design for stormwater runoff treatment: A comprehensive approach

Swales are the oldest and most common stormwater control measure for conveying and treating roadway runoff worldwide. Swales are also gaining popularity as part of stormwater treatment trains and as crucial elements in green infrastructure to build more resilient cities. To achieve higher pollutant reductions, swale alternatives with engineered media (bioswales) and wetland conditions (wet swales) are being tested. However, the available swale design guidance is primarily focused on hydraulic conveyance, overlooking their function as an important water quality treatment tool. The objective of this article is to provide science-based swale design guidance for treating targeted pollutants in stormwater runoff. This guidance is underpinned by a literature review. The results of this review suggest that well-maintained grass swales with check dams or infiltration swales are the best options for runoff volume reduction and removal of sediment and heavy metals. For nitrogen removal, wet swales are the most effective swale alternative. Bioswales are best for phosphorus and bacteria removal; both wet swales and bioswales can also treat heavy metals. Selection of a swale type depends on the site constraints, local climate, and available funding for design, construction, and operation. Appropriate siting, pre-design site investigations, and consideration of future maintenance during design are critical to successful long-term swale performance. Swale design recommendations based on a synthesis of the available research are provided, but actual design standards should be developed using local empirical data. Future research is necessary to identify optimal design parameters for all swale types, especially for wet swales.

Performance of two contrasting pilot swale designs for treating zinc, polycyclic aromatic hydrocarbons and glyphosate from stormwater runoff

Swales are a widespread stormwater management solution to reduce pollutant concentrations in runoff. An innovative pilot facility was constructed to evaluate the treatment efficiency of the two main types of water-quality swales, i.e. standard swales and filtering swales. Using stormwater roof runoff, without any additions or spiked with organic micropollutants, 12 runoff simulation runs mimicking frequent storm events were discharged longitudinally or laterally over the pilot swales. The performance of each swale was assessed for 4 micropollutants, i.e. zinc (Zn), glyphosate, pyrene and phenanthrene. These substances were mainly found in the dissolved phase of the stormwater runoff used to supply the pilot swales. The standard swale, constructed from a silt loam soil, partially managed stormwater runoff by infiltration. Micropollutant concentration reductions were higher in the infiltrated water (35-85%) than in the overflow (-13-66%). The filtering swale, made of a sandy central part bordered by silt loam embankments, completely managed stormwater runoff by infiltration, providing high micropollutant concentration reductions (65-100%). Mass load reductions were higher for the filtering swale (67-90% for Zn and ≥89% for organic micropollutants) than for the standard swale (33-73% for Zn, 19-67% for glyphosate and ≥50% for both pyrene and phenanthrene). For both swales, lateral inflow was often associated with significantly higher concentration and mass reductions than longitudinal inflow. Consequently, when designing swales for the treatment of micropollutants, practitioners should preferentially promote filtering swales and installations providing lateral diffuse inflow over the facility.

Descriptive Analysis of the Performance of a Vegetated Swale through Long-Term Hydrological Monitoring: A Case Study from Coventry, UK

Vegetated swales are a popular sustainable drainage system (SuDS) used in a wide range of environments from urban areas and transport infrastructure, to rural environments, sub-urban and natural catchments. Despite the fact that vegetated swales, also known as grassed swales, have received scientific attention over recent years, especially from a hydrological perspective, there is a need for further research in the field, with long-term monitoring. In addition, vegetated swales introduce further difficulties, such as the biological growth occurring in their surface layer, as well as the biological evolution taking place in them. New developments, such as the implementation of thermal devices within the cross-section of green SuDS for energy saving purposes, require a better understanding of the long-term performance of the surface temperature of swales. This research aims to contribute to a better understanding of these knowledge gaps through a descriptive analysis of a vegetated swale in Ryton, Coventry, UK, under a Cfb Köppen climatic classification and a mixed rural and peri-urban scenario. Precipitation and temperature patterns associated with seasonality effects were identified. Furthermore, a level of biological evolution was described due to the lack of periodical and planned maintenance activities, reporting the presence of both plant species and pollinators. Only one event of flooding was identified during the three hydrological years monitored in this research study, showing a robust performance.

Evaluating the Thermal Performance of Wet Swales Housing Ground Source Heat Pump Elements through Laboratory Modelling

Land-use change due to rapid urbanization poses a threat to urban environments, which are in need of multifunctional green solutions to face complex future socio-ecological and climate scenarios. Urban regeneration strategies, bringing green infrastructure, are currently using sustainable urban drainage systems to exploit the provision of ecosystem services and their wider benefits. The link between food, energy and water depicts a technological knowledge gap, represented by previous attempts to investigate the combination between ground source heat pump and permeable pavement systems. This research aims to transfer these concepts into greener sustainable urban drainage systems like wet swales. A 1:2 scaled laboratory models were built and analysed under a range of ground source heat pump temperatures (20–50 °C). Behavioral models of vertical and inlet/outlet temperature difference within the system were developed, achieving high R2, representing the first attempt to describe the thermal performance of wet swales in literature when designed alongside ground source heat pump elements. Statistical analyses showed the impact of ambient temperature and the heating source at different scales in all layers, as well as, the resilience to heating processes, recovering their initial thermal state within 16 h after the heating stage.