Combined Sewer Research Articles

Change in microplastic concentration during various temporal events downstream of a combined sewage overflow and in an urban stormwater creek

Changes in microplastic concentrations were examined during various temporal events including heavy rain and snowmelt in a river and an urban stream receiving stormwater. Additionally, microplastic concentrations were measured in an urban river during an active combined sewage overflow event. Microplastic concentrations downstream of a combined sewage outfall were observed to increase seven times compared to ambient conditions. During heavy rainfall an increase of 50 times the microplastic concentration was observed in the urban creek with microplastic concentrations doubling in the urban river. However, the largest increase in microplastic concentration at both locations was observed during the primary snowmelt of spring, with microplastic concentrations increasing 114 times in the urban creek and 11 times in the urban river. These results suggest that more research is required to further establish the influence of both combined sewage overflows and snowmelt as a major temporal conduit of microplastics to freshwater environments.

A decade of monitoring micropollutants in urban wet-weather flows: What did we learn?

Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns. We highlight micropollutants to be prioritized due to their high occurrence and critical concentration levels compared to environmental quality standards. These top-listed micropollutants include contaminants from all chemical classes (pesticides, heavy metals, polycyclic aromatic hydrocarbons, personal care products, pharmaceuticals, and industrial and household chemicals). Analysis of over 30,000 event mean concentrations shows a large fraction of measurements (> 50%) were below the limit of quantification, stressing the need for reliable, standard monitoring procedures. High variability was observed among events and sites, with differences between micropollutant classes. The number of events required for a reliable estimate of site mean concentrations (error bandwidth of 1 around the “true" value) depends on the individual micropollutant. The median minimum number of events is 7 for CSO (2 to 31, 80%-interquantile) and 6 for SWO (1 to 25 events, 80%-interquantile). Our analysis indicates the minimum number of sites needed to assess global pollution levels and our data collection and analysis can be used to estimate the required number of sites for an urban catchment. Our data-driven analysis demonstrates how future wet-weather monitoring programs will be more effective if the consequences of high variability inherent in urban wet-weather discharges are considered.

Year-long wastewater monitoring for SARS-CoV-2 signals in combined and separate sanitary sewers.

COVID‐19 wastewater‐based epidemiology has been performed in catchments of various sizes and sewer types with many short‐term studies available and multi‐seasonal studies emerging. The objective of this study was to compare weekly observations of SARS‐CoV‐2 genes in municipal wastewater across multiple seasons for different systems as a factor of sewer type (combined, separate sanitary) and system size. Sampling occurred following the first wave of SARS‐CoV‐2 cases in the study region (June 2020) and continued through the third wave (May 2021), the period during which clinical testing was widely available and different variants dominated clinical cases. The strongest correlations were observed between wastewater N1 concentrations and the cumulative clinical cases reported in the 2 weeks prior to wastewater sampling, followed by the week prior, new cases, and the week after wastewater sampling. Sewer type and size did not necessarily explain the strength of the correlations, indicating that other non‐sewer factors may be impacting the observations. In‐system sampling results for the largest system sampled are presented for 1 month. Removing wet weather days from the data sets improved even the flow‐normalized correlations for the systems, potentially indicating that interpreting results during wet weather events may be more complicated than simply accounting for dilution.Practitioner Points SARS‐CoV‐2 in wastewater correlated best with total clinical cases reported in 2 weeks before wastewater sampling at the utility level.Study performed when clinical testing was widespread during the year after the first COVID‐19 wave in the region.Sewer type and size did not necessarily explain correlation strength between clinical cases and wastewater‐based epidemiology results.Removing wet weather days improved correlations for 3/4 utilities studied, including both separate sanitary and combined sewers.

Influence of particle size on diffuse particulate pollutants in combined sewer systems

Since combined sewer systems are still considered as a threat to urban water environment, understand their pollution transport process and load distribution characteristics during rainfall-runoff events would assist to mitigate urban stormwater pollution. In this study, built-up and wash-off processes of particulate pollutants on road surface and in sewer were synchronously observed during eight natural rainfall events in the combined sewer system in Zhuhai, Southern China. Field observation results showed the significant influence of particles size distribution characteristics on TSS concentration. High TSS concentrations (Road runoff, >200 mg/L; combined sewer runoff, >150 mg/L) usually contained relatively coarse particles (>100 μm) during the eight rainfall events, but the counter argument. Combined sewer runoff had a particle size coarser than road runoff. The relationship between the event means concentration (EMC) of TSS from road and combined sewer runoff varied with rainfall. EMC of TSS in road runoff were higher than that in sewer runoff during small rainfall, while that in combined sewer runoff were higher during large rainfall. The results also showed that 65.2 % of total nitrogen (TN) loadings and 62.3 % of total phosphorous (TP) loadings in the catchment came from combined sewer sediments, while 58.6 % of chemical oxygen demand (COD) loadings came from road runoff, which were mainly determined by the content of each pollutant in the sewer sediments and road-deposited sediments (RDS). Additionally, high pollutant loads phases (drainage of pollutant loads faster than runoff at a given incremental time during an event) of road runoff occurred earlier than that of combined sewer runoff. These findings can provide a basis for the type selection and scale determination of stormwater control measures in combined sewer systems.

Examining How a Smart Rainwater Harvesting System Connected to a Green Roof Can Improve Urban Stormwater Management

This study quantified how a smart rainwater harvesting cistern that collected stormwater runoff from a green roof reduced stormwater flow into a combined sewer system (CSS) during wet-weather flow. The studied smart rainwater harvesting cistern collected runoff from a green roof located in Bronx, New York City; it used the Continuous Monitoring and Adaptive Control (CMAC) smart sensor provided by OptiRTC, Inc., to regulate the water flow from the cistern. The cistern collected stormwater runoff from the roof, usually draining completely after 24 h of dry weather. However, the smart sensor used weather forecasting data, and if additional rainfall was predicted immediately following another storm, the cistern only drained a specific amount, calibrated to mitigate the CSO. Five years of data from the cistern system were used to understand the role of the cistern’s smart sensor in reducing stormwater flow into the CSS during storms. The study results demonstrate that connecting the smart cistern system to the green-roof maximized stormwater collection (compared with the green roof alone) for storm sizes between 2 mm and 25 mm and for antecedent dry-weather periods greater than 2 days. The total of 65.2% of rainfall retained over the monitoring period by the green roof alone increased to 75.6% when considering the total stormwater retained and detained together by the green roof and cistern, thus yielding a 10% improvement. The study results also demonstrate that the smart sensor’s use of weather forecasting data failed to improve system performance.

A Preliminary European-Scale Assessment of Microplastics in Urban Wastewater

Microplastics (MP) are not well defined from an analytical point of view and their measurement in the environment is still challenging. At the same time, their increasingly widespread presence is raising concerns for human health and ecosystems. In this contribution, we present a preliminary European-scale assessment of the environmental input of MP through urban wastewater and urban runoff. We quantify the emissions associated with urban wastewater based on the range of observed concentrations in wastewater treatment plants (WWTPs) effluents, and the emissions from tire wear particles (TWP) by assuming that a percentage of the particles generated on roads eventually reaches surface waters. In spite of the large uncertainties entailed in the calculation, it is apparent that TWP dominate the input of total plastic loads into European surface waters. The management of urban runoff, road runoff, and combined sewer overflows (CSO) is essential to control the emissions of MP from urban areas. On the other hand, WWTPs retain the majority of MP in the sewage sludge. The spreading of sewage sludge onto soil therefore represents a potential pathway of MP from urban wastewater into the environment.

Observations and Correlations from a 3-Year Study of Fecal Indicator Bacteria in the Mohawk River in Upstate NY

Fecal indicator bacteria (FIB), such as E. coli and Enterococci, are used to indicate the potential of fecal contamination in waterways. One known source of FIB in urbanized areas is the occurrence of combined sewer overflows (CSOs). To explore the impact of CSOs on local water quality and FIB presence, sampling was conducted during the summers of 2017–2019 of two cities, one with CSOs and one without, on the Mohawk River in upstate New York, USA. Sampling included in situ physiochemical parameters of pH, temperature, and dissolved oxygen and laboratory tests for E. coli, Enterococci, nitrates, and total organic carbon (TOC). Correlations between parameters were explored using the Wilcoxon rank sum test and Spearman’s Rank correlation with and without considerations of site and city location. Overall, positive correlations between FIB and rainfall were identified in one city but were less significant in the other, suggesting a buffering of FIB concentrations likely due to inflow contributions from a reservoir. Samples collected downstream from an active CSO reached the detection limit of the FIB tests, demonstrating a 2-log or greater increase in FIB concentrations from dry weather conditions. The city with CSOs demonstrated greater FIB concentrations, which are likely a combination of greater urban runoff, CSOs, and the potential resuspension of sediment during high flow events. Due to the widespread presence of FIB in the region, future research includes utilizing microbial source tracking to identify the sources of contamination in the region.

Combined Sewer Overflow and Flooding Mitigation Through a Reliable Real‐Time Control Based on Multi‐Reinforcement Learning and Model Predictive Control

AbstractReal‐time control (RTC) of urban drainage systems (UDS) has been proved an efficient tool in combined sewer overflow (CSO) and flooding mitigation. Recently, new RTC approaches based on reinforcement learning (RL) were developed for flooding mitigation in stormwater systems. While these studies have made contributions to enable an improved urban water management, they are insufficient to allow for deeply understanding of the effectiveness of different RLs in UDS. Meanwhile, the risk of handing over the control process to a RL agent is still unavoidable because of the fluctuations of RLs' output and the unknown consequences of implementing RLs control strategy. This study conducted four tasks to address these problems. First, five RTC systems based on five individual RLs were designed to distinguish different RLs' performance in the context of UDS. Then, an independent security system based on SWMM was provided to forecast and evaluate the consequence of RL control strategy. After that, an innovative hybrid RTC system, called Voting, was developed by coupling multiple RLs and the independent security system through a model predictive control framework to avoid the fluctuations of RLs' output. Finally, the robustness of the RL agents was validated using uncertainty analysis. All the RLs were evaluated through simulation based on a Storm Water Management Model of a UDS located in Eastern China. According to the results, (a) different RLs show promise in CSO and flooding mitigation; (b) Voting selects a relatively reliable and optimal control trajectory compared with any single RL agents; (c) the performances of RL agents have certain robustness when facing different rainfall events and imperfect input.

Stormwater Management in the City of Warsaw: A Review and Evaluation of Technical Solutions and Strategies to Improve the Capacity of the Combined Sewer System

Urban flooding is an increasingly common phenomenon around the world. The reasons are usually attributed to the insufficient capacity of the combined sewer system and its inability to adapt to the changing dynamics of rainfall. This is also the case in Warsaw (the capital of Poland), where the sewage system was designed in the 1960s. The aim of the article is to highlight possible hydrological solutions that would significantly improve Warsaw’s situation in terms of rainfall runoff. The article looks at some solutions that were previously mentioned in the literature and presents an assessment of the possible changes in land use/land cover on the hydrological processes and improvements in the general hydrological situation of Warsaw. In addition, the article points out the need to update the programme and spatial approach to the discharge of water from specific watersheds in Warsaw, as well as to establish a single manager for stormwater drainage in the city of Warsaw. An important issue is the restoration of natural retention basins in the city and the construction of artificial basins in places with frequent local flooding. The article emphasises the importance of building individual detention basins (as well as low-impact developments) for newly planned investments. Other important aspects are as follows: the construction of suitable underground or open channels, the need to disconnect Ursynów’s stormwater runoff from the catchment area of the Służewiecki Stream and to channel it along the southern bypass for Warsaw (S-2) to the dry lakes and ponds in Wilanów. Finally, the article discusses the application of Sustainable Drainage Systems (SuDS) and Real-Time Control (RTC) in urban drainage systems as a possible solution to improve wastewater management in urban areas.

Development of Rainfall-Runoff Models for Sustainable Stormwater Management in Urbanized Catchments

Modelling of stormwater networks and the related object (combined sewer overflows, diversion chambers, retention tanks) is a complex task requiring colleting of data with appropriate time and spatial resolution as well as application of adequate models. Often there is a need to find balance between the costs of conducting measurement (period, resolution) and the uncertainty of the model results. This paper presents an overview of simulation tools for sewerage networks modelling, related objects, as well as low-impact development (LID) systems in relation to the hydrodynamic and statistical models. Consecutive stages of data collection, sources of data uncertainty, limitations resulting from the adopted measurement methodology, as well as their influence on the simulation results and possible decision-making using the developed hydrodynamic or statistical model, are discussed. Attention is drawn to the optimization methods enabling reduction in the uncertainty of statistical models. The methods enabling the analysis of model uncertainty, as well as evaluation of its influence on the calculation results pertaining to stormwater hydrographs, retention tank capacity and combined sewers overflows, are also discussed. This is a very important aspect in terms of optimizing construction works in the sewerage network and designing their appropriate dimensions to achieve the assumed hydraulic effects.

Real-time model predictive and rule-based control with green infrastructures to reduce combined sewer overflows

The impact of integrating large-scale distribution of green infrastructures (GIs) with different real-time control strategies on combined sewer overflows (CSOs) is assessed for the southern area of the City of Montreal's combined sewer system (Canada). An iterative process involving a synthetic design rainfall event and model predictive control (MPC) of the sewer system is developed to distribute GIs according to cost-efficiency and spatial analysis criteria. The distributed GIs are alternatively integrated with static, rule-based control (RBC) and MPC, for which model simulations are performed for a two-month period. The performance of the three strategies is compared in terms of CSO volume and frequency reductions, fulfillment of the outfall environmental priorities and transfer of runoff capture to CSO volume reduction. A gradual increase in GI implementation levels and an alternative scenario of GIs distribution are also considered to assess the performance of the two real-time control (RTC) strategies. By comparing the scenarios where GIs are uniformly distributed with those where no GIs are implemented and omitting the most extreme rainfall event, average CSO volume reduction is about 65%, 82% and 92%, respectively, for static control, RBC and MPC. Moreover, the scenario integrating GIs with MPC is the only one permitting to avoid almost all CSO events and the fulfilment of the outfall environmental priorities. GIs efficiency performance (the transferability between global runoff capture and CSO volume reduction) is also the highest under MPC, even when considering varying GI implementation levels and spatial distribution schemes.

Formulation of energy loss in a four-way circular manhole at crossroad.

Energy loss at a manhole which is at a junction of storm sewers or combined sewers is important for accurately estimating its discharge capacity. However, even in Japan, the energy loss at the manhole is usually ignored in designing sewers and flood inundation analysis. One of the reasons for the ignorance is difficulty to formulate the energy loss at the manhole because the number of variables which must be considered increases as the number of sewers connected to the manhole increases. The authors have formulated the energy loss of a four-way circular manhole with three inflow sewers and one outflow sewer at crossroad. The formula is applicable only to the equal flow rates in two opposite lateral inflow sewers. In this paper, a new formula for the energy losses is proposed based on experimental data on a four-way circular manhole with different flow rates on three inflow sewers. It shows that the energy losses calculated with it almost reproduce the measured ones.

Exploring the use of water resource recovery facility instrument data to visualise dynamic resilience to environmental stressors

Water resource recovery facilities (WRRF) face increasingly dynamic stressors, such as higher rainfall intensity and extended dry periods, which can exert stress on ageing water infrastructure and processes. These events can generate process stresses, which lead to wastewater process failures which result in pollution events that could be identified from instrument data used for operational/compliance monitoring. This extraction can be performed on two levels (1) for discrete processes that generate data to monitor process control variables and (2) at the WRRF process boundary (global), which is mainly used for compliance. Both levels of data hold valuable information on the dynamic influence of environmental stressors (cause) and the resulting process stress or resilience (effect) as ‘dynamic resilience’. This paper proposes a novel methodology that uses actual water company instrument data to evaluate the ‘discrete’ (unit processes) and ‘global’ (WRRF boundary) dynamic resilience of a WRRF in the south of the UK. Dynamic resilience is presented as a four-stage methodology, which; (1) cleans WRRF data and extracts a standard operating condition; (2) identifies dynamic high and low flow environmental stressor events (one in five years); (3) models the process stresses and resilience generated by the imposed dynamic stressor before; (4) generating a contoured heat map of process-related stresses or resilience as a self ordering window. These methods demonstrate the possibility of visualising the dynamics of WRRF resilience (dynamic stressors and process stresses/resilience) resulting from high and low flow dynamic environmental stressors. Despite some challenges experienced with self ordering window scaling, the results demonstrate the possibility of identifying zones of process stress and resilience. It may also be possible to expand the methods developed to incorporate storm flows and combined sewer discharges.

Stochastic Determination of Combined Sewer Overflow Loads for Decision-Making Purposes and Operational Follow-Up

Characterizing the emissions and impact of combined sewer overflows (CSOs) remains one of the key challenges in the field of urban wastewater. Considering the large number of existing CSOs, decision-makers need a pragmatic approach that allows fairly easy, hands-on determination of emissions (particularly loads) without compromising accuracy. This philosophy is incorporated in the Cockle tool presented here, which uses stochastically processed input from a vast amount of pre-registered water quality data (pollutant concentrations) in combination with spill flow time series either generated from hydrodynamic models or converted from monitored overflow water levels. Uncertainty is intrinsically covered by the statistical output range of the reported results. As a fully automated tool, Cockle allows to readily assess emissions within a chosen time frame, facilitating more accurate guidance for further remediation actions and/or mapping of the current state for operational follow-up.

Quality Assessment of Small Urban Catchments Stormwater Models: A New Approach Using Old Metrics

Small urban catchments pose challenges in applying performance metrics when comparing measured and simulated hydrographs. Indeed, results are hampered by the short peak flows, due to rainfall variability and measurement synchronization errors, and it can be both difficult and inconvenient to remove base flows from the analysis, given their influence on combined sewer overflow (CSO) performance. A new approach, based on the application of metrics to peak flows for a selected set of different durations, is proposed and tested to support model quality assessment and calibration. Its advantages are: avoiding inconveniences arising from lags in peak flows and subjectivity of possible adjustments; favouring the assessment of the influence of base flow variability and flow lamination by CSOs; promoting integrated analysis for a wide range of rainfall events; facilitating bias identification and also guiding calibration. However, this new approach tends to provide results (e.g., for NSE, r2 and PBIAS) closer to optimal values than when applying metrics to compare the measured and simulated values of hydrographs, so the comparison of results with thresholds widely used in the literature should be done with caution. The various case study examples highlight the importance of using a judicious set of different metrics and graphical analyses.

Combined Sewer Overflows and Gastrointestinal Illness in Atlanta, 2002-2013: Evaluating the Impact of Infrastructure Improvements.

Background:Combined sewer overflows (CSOs) discharge untreated sewage into surface and recreational water, often following heavy precipitation. Given projected increases in frequency and intensity of precipitation due to climate change, it is important to understand the health impacts of CSOs and mediating effects of sewerage systems.Objectives:In this study we estimate associations of CSO events and emergency department (ED) visits for gastrointestinal (GI) illness among City of Atlanta, Georgia, residents and explore how these associations vary with sewerage improvements.Methods:We estimate associations using Poisson generalized linear models, controlling for time trends. We categorized CSOs by overflow volume and assessed effects of CSO events prior to ED visits with 1-, 2- and 3-wk lags. Similarly, we evaluated effects of weekly cumulative precipitation greater than the 90th percentile at the same lags. We also evaluated effect modification by ZIP Code Tabulation Area (ZCTA)-level poverty and infrastructure improvement period using interaction terms.Results:Occurrence of a large volume CSO in the previous week was associated with a 9% increase in daily ED visits for GI illness. We identified significant interaction by ZCTA-level poverty, with stronger CSO–GI illness associations in low than high poverty areas. Among areas with low poverty, we observed associations at 1-wk and longer lags, following both large and lower volume CSO events. We did not observe significant interaction by infrastructure improvement period for CSO– nor precipitation–GI illness associations; however, the number of CSO events decreased from 2.31 per week before improvements to 0.49 after improvements.Discussion:Our findings suggest that CSOs contribute to acute GI illness burden in Atlanta and that the magnitude of this risk may be higher among populations living in areas of low poverty. We did not find a protective effect of sewerage system improvements. Nonetheless, observed reductions in CSO frequency may lower the absolute burden of GI illness attributable to these events. https://doi.org/10.1289/EHP10399

A hydrological model to estimate pollution from combined sewer overflows at the regional scale: Application to Europe

Study regionCombined Sewer Overflows (CSO) of 671 Functional Urban Areas (FUAs) throughout the European Union + UK (EU28), representing almost half of the EU28 population. Study focusCSO loads can be quantified at the local scale through measurements, or with calibrated hydrological models. However, they are difficult to quantify at a large scale (e.g. regional or national), due to a lack of data, and the models used at local scale cannot be applied in the absence of knowledge of the combined sewer (CS) network. This paper presents a 6-parameter lumped hydrological model to simulate a CS network and its overflows, using population and rainfall data of 671 EU28 FUAs. New hydrological insights for the regionWhen properly calibrated, the model can predict the CSO hydrographs as well as aggregated CSO descriptors of a catchment with known impervious surface area connected to a CS with a reasonable reliability. When model calibration is not possible, using default values of the parameters enables a first approximation estimate of CSOs, accurate within one order of magnitude, which can be used to support scenario analysis for regional and continental CSO management. At the EU28 scale, the estimated total CSO volume is 5.7·103 Mm3/y, with a dry weather flow content in CSOs of 460 Mm3/y (assuming a dry weather flow of 200 l/population equivalent (PE)/day including sanitary discharges, industrial discharge and infiltration). A collection of case studies on CSOs is also provided.

Analysis of E. coli trends in the Wheeling Creek watershed

Escherichia coli (E. coli) is a gut bacterium found in intestinal tracts of warm-blooded animals and pollutes water bodies through fecal contamination. At high concentrations some strains can cause serious illnesses if ingested by individuals. High concentrations of E. coli can also indicate the presence of other potentially harmful pathogens. Surface waters can become contaminated via nonpoint sources of runoff from agricultural lands and resident waterfowl population and point sources including leaking sewage infrastructure and combined sewer overflows (CSOs). In freshwaters E. coli can live free floating throughout the water column or attached to streambed sediments, and when these sediments are resuspended due to precipitation E. coli concentrations increase in the water column. The USEPA has set a maximum safe limit for recreational waters at 235 CFU/100 mL of water for a single sample and a 30-day five-sample mean of 126 CFU/100 mL. We chose seventeen sampling sites to monitor and identify trends and predictors of E. coli in Wheeling Creek watershed, in the northern panhandle of West Virginia. We measured water temperature, pH, dissolved oxygen, conductivity, chloride, and turbidity in the field and used an IDEXX system for E. coli quantification. Our results indicate that 51% of samples (125 out of 245) have exceeded that single sample safe limit (235 CFU/100ml). Escherichia coli concentrations are increasing with increasing urban development and show a positive correlation with turbidity, this could suggest that humans are the primary source of E. coli in Wheeling Creek.

Valuing the public benefits of green roofs

Green roofs are being incorporated into stormwater management programs around the world. While numerous studies have estimated the private benefits to the owners and residents of buildings with green roofs, the value of the multiple public benefits received by non-building residents are less well known. We use a choice experiment survey to estimate the public benefits for a proposed green roof program in Portland, Oregon, USA. These benefits include reduced combined sewer overflows, reduced urban heat island effects, and an increase in pollinators such as birds, bees and butterflies. Past investments in stormwater infrastructure have exposed some residents to poor water quality and urban flooding, so we also explore if respondents’ willingness to pay varies based on where new green roofs are located. Across models, the largest estimated benefit in our study area is from a reduction in combined sewer overflows. Model results also show that respondents prefer to not fully concentrate new green roofs in Portland’s Central City area, which is where most green roofs are currently located. Total willingness to pay estimates for the 1-year program range from around $202 to $442 per household, or $54.4 to $116.8 million for the city of Portland, Oregon, depending on program characteristics.

Studying the effect of sea level rise on nuisance flooding due to groundwater in a coastal urban area with aging infrastructure

In this paper, we present a study focused on the effect of sea level rise (SLR) on nuisance flooding due to groundwater (or groundwater flooding). A densely populated coastal urban area along a river estuary was selected for this work. We developed a three-dimensional (3D) shallow unconfined aquifer model of the site. We calibrated it with field measurements and used it to predict areas prone to groundwater flooding under different SLR scenarios. Results show that the water table is controlled by the river level as well as by aging infrastructure such as aging combined sewer and drinking water networks which drain and recharge the unconfined aquifer. Steady-state simulations run considering current river level scenarios show a very shallow aquifer throughout the area and simulations under different SLR scenarios predict that the water table starts to emerge from the ground in the low-lying parts of the site for 0.4 m of SLR.Overall, this work suggests that groundwater in coastal urban areas is regulated by anthropogenic and natural systems and is susceptible to climate change contributing to inundation together with marine flooding and intense precipitation.