Stormwater biofilter treatment model for faecal microorganisms

BioRTC model enables exploration of real time control strategies for stormwater biofilters

Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a 'base' model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (Ec) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively.

Performance analysis of a stormwater green infrastructure model for flow and water quality predictions

Nature-based solutions or Green infrastructure (GI) used for managing stormwater pollution are growing in popularity across the globe. Stormwater GI models are important tools to inform the planning of these systems (type, design, size), in the most efficient and cost-effective manner. MUSIC, an example of such a tool, uses regression and first order decay models. Studies validating MUSIC model performance are, however, scarce, hindering future model development and transferability of the model for systems operating under different design and climatic conditions. To close this gap, this paper evaluates MUSIC for a field scale bioretention system, stormwater wetland and vegetated swale operating under Singapore tropical climate. The treatment modules were able to simulate outflows and effluent pollutant concentrations reasonably well for cumulative event volumes (mostly within ±25%) and cumulative TP and TN loads (within ±30%). Outflow TSS loads were significantly under-estimated as a result of greater variability in measured TSS concentrations across events. The findings indicate that simple empirical models such as MUSIC can be transferred to different regions provided that management decisions are based on long-term modelling efforts. The modules generally simulated the outflow hydrographs and pollutographs of the different inflow and drying/wetting conditions relatively poorly.

Modular Design of Bioretention Systems for Sustainable Stormwater Management under Drivers of Urbanization and Climate Change

The increase in urbanization and climate change projections point to a worsening of floods and urban river contamination. Cities need to adopt adaptive urban drainage measures capable of mitigating these drivers of change. This study presents a practical methodology for a modular design of bioretention systems incorporating land use and climate change into existing sizing methods. Additionally, a sensitivity analysis for these methods was performed. The methodology was applied to a case study in the city of Sao Carlos, SP, Brazil. Three application scales were evaluated: property scale (PS), street scale (SS) and neighborhood scale (NS) for three temporal scenarios: current, 2015–2050 and 2050–2100. The choice of the sizing method was the factor with greatest influence on the final bioretention performance, as it considerably affected the surface areas designed, followed by the hydraulic conductivity of the filtering media. When analyzing the sensitivity of the parameters for each method, the runoff coefficient and the daily precipitation with 90% probability were identified as the most sensitive parameters. For the period 2050–2100, there was an increase of up to 2×, 2.5× and 4× in inflow for PS, SS and NS, respectively. However and despite the great uncertainty of future drivers, bioretention performance would remain almost constant in future periods due to modular design.

A comprehensive review on the long-term performance of stormwater biofiltration systems (SBS): Operational challenges and future directions

Stormwater biofiltration systems (SBS) are a popular technology for mitigating the negative effects of urbanization on the hydrological processes and water quality in urban areas. However, little is known about SBS's long-term performance in actual field conditions. The findings of a review of the scientific literature on the long-term performance of SBS are presented in this paper. The findings show that only a few studies have investigated the performance of SBS and its change over time, and that the results of laboratory and field experiments differed due to the presence of plants, regular maintenance, and some uncertain environmental factors. Based on the existing knowledge gaps in this field, the main challenges observed was the lack of long-term field data series, and the existing mathematical models are not able to accurately forecast the long-term performance of SBS. This could be owing to the difficulties in monitoring activities, the high costs involved and the unpredictability around the operational timeframe. Future study should concentrate on the implementation of simulation and modeling-based research in pilot and full-scale SBS, and the inclusion of new performance indicators should be considered as a priority.

Evaluating low impact development practices potentials for increasing flood resilience and stormwater reuse through lab-controlled bioretention systems

Low impact development practices (LID) as alternative measures of urban drainage can be used within the approach of resources recycling and co-management. This study evaluates the potential contribution of a bioretention system to flood control, non-potable water demands (NPD) and resources co-management. Bioretention setups were tested experimentally under variable conditions to identify operational key-factors to multiple purposes. Additionally, the efficiencies obtained for laboratory scale were extrapolated for household and watershed scale, quantifying the indicators of water demand reduction (WDR), energy demand reduction (EDR) and carbon emission reduction (CER) for hybrid systems with LID. The laboratory results indicated that the use of a bioretention with a submerged zone can improve the quality of the water recovered for reuse, while maintaining the efficiency of runoff retention and peak flow attenuation. Comparing the bioretention effluent quality with the Brazilian standards for stormwater reuse, the parameters color, turbidity, E. coli and metals were above the limits, indicating the necessity of a better treatment for solids particles and disinfection. Expanding the analysis to watershed scale, the bioretention helped to reduce NPD demands up to 45%, leading to a reduction in energy demand and carbon emission from the centralized water supply system.

A Need for Standardized Reporting: A Scoping Review of Bioretention Research 2000–2019

Bioretention cells are a type of low-impact development technology that, over the past two decades, have become a critical component of urban stormwater management. Research into bioretention has since proliferated, with disparate aims, intents and metrics used to assess the “performance” of bioretention cells. We conducted a comprehensive, systematic scoping review to answer the question of “How is the field performance of bioretention assessed in the literature?”, with the aim of understanding (1) how is the performance of bioretention defined in the literature? (2) what metrics are used to assess actual and theoretical performance? A review of 320 studies (mostly peer reviewed articles) found that performance was defined in terms of hydrologic controls, while investigations into water quality pathways and mechanisms of contaminant transport and fate and the role of vegetation were lacking; additionally, long term field and continuous modelling studies were limited. Bioretention field research was primarily conducted by a small number of institutions (26 institutions were responsible for 50% of the research) located mainly in high income countries, particularly Australia and the United States. We recommend that the research community (I) provide all original data when reporting results, (II) prioritize investigating the processes that determine bioretention performance and (III) standardize the collection, analysis and reporting of results. This dissemination of information will ensure that gaps in bioretention knowledge can be found and allow for improvements to the performance of bioretention cells around the world.

Validation and uncertainty analysis of a stormwater biofilter treatment model for faecal microorganisms

Stormwater biofilters, also known as rain gardens or bioretention systems, are effective stormwater treatment systems. This paper presents the validation, sensitivity and uncertainty analyses of a model for microbial removal in stormwater biofilters. The model, previously developed based on a rather limited laboratory study, was fully validated using the data collected in extensive laboratory experiments and field tests. The lab-scale and field-scale systems used for validation were of various designs (e.g., system size, plant type, media type), and have been operated under a wide range of operational conditions (e.g., length of antecedent dry period, and the inflow volume and concentration). For each tested biofilter design, the predicted E. coli concentrations in biofilters' outflow showed relatively good agreement with the measured ones: e.g., Nash-Sutcliffe Efficiency (E_c) ranged from 0.50 to 0.60 for the laboratory tests, and E_c = 0.55 for the field system. The results from sensitivity analysis confirmed the significance of adsorption and desorption processes, and also revealed the impact of temperature on microbial die-off (which was not fully represented in the model development stage). Finally, parameter transferability from one system to another with similar design was examined, achieving generally promising E_c values (0.04-0.56 with the best-fit parameter set for the other system; maximum value: 0.46-0.63) and acceptable uncertainties (intersection between prediction uncertainty band and observation: 50%-97%). Most importantly, the prediction of E. coli outflow concentrations from the field system was reasonably good when laboratory-determined parameter values were adopted: with the best-fit parameter set for the lab-scale system, E_c = 0.39; maximum E_c = 0.55; intersection between prediction and observation = 83%. These results suggested that the very rare biofilter model for microbial removal could provide reliable prediction for large scale field systems, by simply calibrating parameters with limited laboratory-scale experiments.

Nonpoint source pollution

A comprehensive review of the research papers published in 2018 focusing on nonpoint source (NPS) pollution is presented in this review article. The identification of pollution from different sources and estimation of NPS pollution using various models are summarized in this review paper. Various innovative techniques are also examined to abate NPS pollution. PRACTITIONER POINTS: The non-point source pollution in 2018 is systematically reviewed and documented. This review evaluates and summarizes the identification, quantification, reduction, and management of NPS pollution. Future perspectives of NPS pollution research are discussed.

Urban stormwater characterization, control, and treatment

This review summarizes over 250 studies published in 2018 related to the characterization, control, and management of urban stormwater runoff. The review covers three broad themes: (a) quantity and quality characterization of stormwater, (b) control and treatment of stormwater runoff, and (c) implementation and assessment of watershed-scale green stormwater infrastructure (GSI). Each section provides an overview of the 2018 literature, common themes, and future work. Several themes emerged from the 2018 literature including exploration of contaminants of emerging concern within stormwater systems, characterization and incorporation of vegetation-driven dynamics in stormwater control measures, and the need for interdisciplinary perspectives on the implementation and assessment of GSI. PRACTITIONER POINTS: Over 250 studies were published in 2018 related to the characterization, control, and treatment of stormwater. Studies cover general stormwater characteristics, control and treatment systems, and watershed-scale assessments. Trends in 2018 include treatment trains, vegetation dynamics, and interdisciplinary perspectives.