Moving to a future of smart stormwater management: A review and framework for terminology, research, and future perspectives

Developing simple indicators of nitrogen and phosphorus removal in constructed stormwater wetlands

Quantifying pollutant removal by stormwater wetlands requires intensive sampling which is cost-prohibitive for authorities responsible for a large number of wetlands. Wetland managers require simple indicators that provide a practical means of estimating performance and prioritising maintenance works across their asset base. We therefore aimed to develop vegetation cover and metrics derived from monitoring water level, as simple indicators of likely nutrient pollutant removal from stormwater wetlands. Over a two-year period, we measured vegetation cover and water levels at 17 wetlands and used both to predict nitrogen (N) and phosphorus (P) removal. Vegetation cover explained 48 % of variation in total nitrogen (TN) removal; with a linear relationship suggesting an approximate 9 % loss in TN removal per 10 % decrease in vegetation cover. Vegetation cover is therefore a useful indicator of TN removal. Further development of remotely-sensed data on vegetation configuration, species and condition will likely improve the accuracy of TN removal estimates. Total phosphorus (TP) removal was not predicted by vegetation cover, but was weakly related to the median water level which explained 25 % of variation TP removal. Despite weak prediction of TP removal, metrics derived from water level sensors identified faults such as excessive inflow and inefficient outflow, which in combination explained 50 % of the variation in the median water level. Monitoring water levels therefore has the potential to detect faults prior to loss of vegetation cover and therefore TN removal, as well as inform the corrective action required.

Real-time control of urban drainage systems using neuro-evolution

With climate change and urbanization, existing urban drainage systems are being stressed beyond their design capacity in many parts of the world. Real-time control (RTC) can improve the performance of these systems and reduce the need for system upgrades. However, developing optimal control policies for RTC is a challenging research area due to computational demands, high uncertainties and system dynamics. This study presents a new RTC method using neuro-evolution for controlling combined sewer overflow (CSO) in urban drainage systems. Neuro-evolution is an approach to neural network research by evolutionary algorithms. Neuro-evolution realizes RTC by training the control policy in advance, thus avoiding the online optimization process in the application period. The simulation results of the benchmark Astlingen network indicate that the trained control policy outperforms the equal filling degree strategy in terms of CSO volume reduction and robustness in the face of tank level uncertainty. The performance analysis of the typical CSO events shows that the control policy mainly makes positive contributions during 'small' CSO events rather than 'large' ones. In particular, the effectiveness of the control policy in 'small' CSO events is more prominent in the initial phase of the events compared with the final phase. This work stands to support a foundation for future studies in the control of urban water systems based on neuro-evolution.

Urban stormwater quality: A review of methods for continuous field monitoring

Urban stormwater is contaminated by a wide range of substances whose concentrations vary greatly between locations, as well as between and during rain events. This literature review evaluates advantages and limitations of current methods for using continuous water quality monitoring for stormwater characterization and control. High-temporal-resolution measurements have been used to improve the understanding of stormwater quality dynamics and pollutant pathways, facilitate the performance evaluation of stormwater control measures and improve operation of the urban drainage system with real-time control. However, most sensors used to study stormwater were developed for either centralized water treatment or natural water contexts and adaptation is necessary. At present, the primary application of interest in stormwater - characterization of pollutant concentrations - can only be achieved through the use of indirect measurements with site-specific relationships of pollutants to basic physical-chemical parameters. In addition, various problems arise in the field context, associated with intermittent or variable flow rates, the accumulation of debris and sediment, adverse conditions for electrical equipment and human factors. Obtaining reliable continuous stormwater quality data requires the adoption of best practices, including the calibration and regular maintenance of sensors, verification of data and accounting for the considerable uncertainties in data; however, the literature review showed that improvement is needed among the scientific community in implementing and documenting these practices.

Monitoring spore washoff during a biological contamination incident response using automated stormwater samplers and sensors to predict contamination movement

This study examined the washoff of Bacillus globigii (Bg) spores from concrete, asphalt, and grass surfaces by stormwater. Bg is a nonpathogenic surrogate for Bacillus anthracis, which is a biological select agent. Areas (2.74 m × 7.62 m) of concrete, grass, and asphalt were inoculated twice at the field site during the study. Spore concentrations were measured in runoff water after seven rainfall events (1.2-65.4 mm) and complimentary watershed data were collected for soil moisture, depth of water in collection troughs, and rainfall using custom-built telemetry units. An average surface loading of 107.79 Bg spores/m2 resulted in peak spore concentrations in runoff water of 102, 260, and 4.1 CFU/mL from asphalt, concrete, and grass surfaces, respectively. Spore concentrations in the stormwater runoff were greatly reduced by the third rain event after both inoculations, but still detectable in some samples. When initial rainfall events occurred longer after the initial inoculation, the spore concentrations (both peak and average) in the runoff were diminished. The study also compared rainfall data from 4 tipping bucket rain gauges and a laser disdrometer and found they performed similarly for values of total rainfall accumulation while the laser disdrometer provided additional information (total storm kinetic energy) useful in comparing the seven different rain events. The soil moisture probes are recommended for assistance in predicting when to sample sites with intermittent runoff. Sampling trough level readings were critical to understanding the dilution factor of the storm event and the age of the sample collected. Collectively the spore and watershed data are useful for emergency responders faced with remediation decisions after a biological agent incident as the results provide insight into what equipment to deploy and that spores may persist in runoff water at quantifiable levels for months. The spore measurements are also a novel dataset for stormwater model parameterization for biological contamination of urban watersheds.

Realising smarter stormwater management: A review of the barriers and a roadmap for real world application

Effective management of stormwater systems is necessary for protection of both the built and natural environments. However, stormwater management is facing multiple, growing challenges, including climate change, ageing infrastructure, population growth, urbanisation, environmental concerns, regulatory and institutional changes and public awareness. While the potential of 'smart', internet-of-things enabled stormwater management systems to address these challenges is increasingly being recognised, with considerable evidence in literature for the benefits of more data-driven approaches, implementation to date remains low. This paper, therefore, provides a comprehensive review of the potential barriers to adoption of smarter stormwater management practices that require addressing, and provides a roadmap for real world application. Barriers related to all elements of stormwater management, from the asset sensing to the data analytics and online optimisation, are identified. Technical challenges discussed include the availability and reliability of technologies, technological and physical limitations, decision making, uncertainty and security. Technical barriers are rapidly reducing and there is increasing evidence in the academic literature of the efficacy of smart technologies. However, socio-economic barriers remain a significant challenge, and issues such as trust and lack of confidence, resistance to change, expense, and lack of knowledge and guidance are reviewed. A 'smart stormwater management wheel' that provides a flexible and iterative approach for implementing smart functionality is also presented. Whilst acting as a roadmap, this aims to facilitate a structured methodology for overcoming barriers and benchmarking progress, and may be used to explore trade-offs and relationships between differing levels of implementation for each of the constituent technologies in a smart stormwater system.

Urban stormwater management at the meso-level: A review of trends, challenges and approaches

Cities worldwide are facing a significant threat of stormwater hazards caused by the increase in extreme downpours and urbanization. Meso-level urban stormwater management focuses on alleviating the detrimental impacts of urban flooding and enhancing water resource utilization at the block or community scale, typically through 1) specific policies and management rules; 2) catchment-scale scenario simulation, optimization and evaluation; 3) the group of stormwater control measures implementation. It may effectively coordinate macro-level urban stormwater management planning and micro-level distributed stormwater control facilities. This study conducts a review of Urban Stormwater Management at Meso-level (USM-M) with a view to research publication trends, citation analysis, geographic spread and subject category, as well as content analysis, including temporal progression and research gaps. The Web of Science database and CiteSpace are used for the bibliometric analysis of 66 articles from 2006 to 2021. The results show that the number of USM-M topic articles generally has an upward trend over the years. Whilst the United States and China are leading research on this topic, the European countries have diverse local research and dense cooperation. Research foci have generally shifted from theoretical frameworks to multi-element subdivided topics and specific technical roadmaps. Moreover, the spatial layout optimization and multi-functional integration are, or will be, potential research directions in terms of enhancing stormwater utilization and co-benefits of USM-M. This systematic review concludes trends, challenges and potential approaches of USM-M, and aims to provide recommendations for researchers and policymakers on the development of a more advanced and comprehensive USM-M.

Optimal siting of rainwater harvesting systems for reducing combined sewer overflows at city scale

The installation of green infrastructure (GI) is an effective approach to manage urban stormwater and combined sewer overflow (CSO) by restoring pre-development conditions in urban areas. Research on simulation-optimization techniques to aid with GI planning decision-making is expanding. However, due to high computational expense, the simulation-optimization methods are often based on design storm events, and it is unclear how much different rainfall scenarios (i.e., design storm events vs. long-term historical rainfall data) impact the optimal siting of GI. The Parallel Pareto Archived Dynamically Dimensioned Search (ParaPADDS) algorithm in a novel simulation-optimization tool OSTRICH-SWMM was used to leverage distributed computing resources. A case study was conducted to optimally site rainwater harvesting cisterns within 897 potential subcatchments throughout the City of Buffalo, New York. Seven design storm events with different return periods and rainfall durations and a one-month historical rainfall time series were considered. The results showed that the optimal solutions of siting cisterns using event-based scenarios, though less computationally expensive, may not perform well under continuous rainfall scenarios, suggesting design rainfall scenarios should be carefully considered for optimizing GI planning. The impact of rainfall scenarios was particularly significant in the middle region of the Pareto front of multi-objective optimization. Utilizing high-performance parallel computing, OSTRICH-SWMM is a promising tool to optimize GI at large spatial and temporal scales.

Battle of centralized and decentralized urban stormwater networks: From redundancy perspective

Recent research underpinned the effectiveness of topological decentralization for urban stormwater networks (USNs) during the planning stage in terms of both capital savings and resilience enhancement. However, how centralized and decentralized USNs' structures with various degrees of redundancy (i.e., redundant water flow pathways) project resilience under functional and structural failure remains an unresolved issue. In this work, we present a systemic and generic framework to investigate the impact of adding redundant flow paths on resilience based on three strategies for optimal centralized versus decentralized USNs. Furthermore, a tailored graph-theory based measure (i.e., eigenvector centrality) is proposed to introduce redundant paths to the critical locations of USNs. The proposed framework is then applied to a real large-scale case study. The results confirm the critical role of layout decentralization under both functional (e.g., extreme precipitation events), and structural failure (e.g., pipe collapse). Moreover, the findings indicate that the implementation of redundant paths could increase resilience performance by up to 8% under functional failure without changing the network's major structural characteristics (i.e., sewer diameters, lengths, and storage capacity), only by leveraging the effective flow redistribution. The scheme proposed in this study can be a fruitful initiative for further improving the USNs' resilience during both planning and rehabilitation stages.

Characterization of contaminant leaching from asphalt pavements: A critical review of measurement methods, reclaimed asphalt pavement, porous asphalt, and waste-modified asphalt mixtures

In recent years, the pavement industry has been seeking sustainable development through recycling reclaimed asphalt pavement and reusing other waste materials as replacements for asphalt mixture constituents. Incorporating waste material into asphalt mixture and the presence of pollutants such as exhaust fumes and gasoline due to vehicle traffic may lead to contaminants leaching from asphalt pavements to underlying soil layers and groundwater aquifers, posing serious risks to ecosystems and the environment. To cast light on contaminant leaching from asphalt pavements, this article presents a comprehensive review of the literature that is divided into four research areas: evaluation of leaching measurement methods, leaching from recycled asphalt materials, leaching characteristics of porous asphalt pavements, and waste-modified asphalt mixtures. Moreover, a critical discussion of bibliometric data, literature content and knowledge gaps in this domain is provided to help highway agencies and environmental scientists address contaminant leaching from asphalt pavements. Finally, some potential research directions are suggested for future research works.