Relationship between infiltration, sewer rehabilitation, and groundwater flooding in coastal urban areas

Nature-based solution enhances resilience to flooding and catalyzes multi-benefits in coastal cities in the Global South

Coastal cities are facing a rise in groundwater levels induced by sea level rise, further triggering saturation excess flooding where groundwater levels reach the topographic surface or reduce the storage capacity of the soil, thus stressing the existing infrastructure. Lowering groundwater levels is a priority for sustaining the long-term livelihood of coastal cities. In the absence of studies assessing the possibility of using tree-planting as a measure of alleviating saturation excess flooding in the context of rising groundwater levels, the multi-benefit nature of tree-planting programs as sustainable Nature-based solutions (NBSs) in coastal cities in the Global South is discussed. In environments where groundwater is shallow, trees uptake groundwater or reduce groundwater recharge, thereby contributing to lower groundwater levels and increasing the unsaturated zone thickness, further reducing the risk of saturation excess flooding. Tree-planting programs represent long-term solutions sustained by environmental factors that are complementary to conventional engineering solutions. The multi-benefit nature of such NBSs and the expected positive environmental, economic, and social outcomes make them particularly promising. Wide social acceptance was identified as crucial for the long-term success of any tree-planting program, as the social factor plays a major role in addressing most weaknesses and threats of the solution. In the case of Nouakchott City (Mauritania), where a rise in groundwater levels has led to permanent saturation excess flooding, a tree-planting program has the potential to lower the groundwater levels, thereby reducing flooding during the rainy season.

Rapid quantification of the surface overflow and underground infiltration in sewer pipes based on computer vision and continuous optimization

The overloading of the sewer network caused by unwarranted infiltration of stormwater may lead to waterlogging and environmental pollution. The accurate identification of infiltration and surface overflow is essential to predict and reduce these risks. To retrieve the limitations of infiltration estimation and the failure of surface overflow perception using the common stormwater management model (SWMM), a surface overflow and underground infiltration (SOUI) model is proposed to estimate the infiltration and overflow. First, the precipitation, water level of the manhole, surface water depth and images of the overflowing point, and volume at the outfall are collected. Then, the surface waterlogging area is identified based on computer vision to reconstruct the local digital elevation model (DEM) by spatial interpolation, and the relationship between the waterlogging depth, area and volume is established to identify the real-time overflow. Next, a continuous genetic algorithm optimization (CT-GA) model is proposed for the underground sewer system to determine the inflow rapidly. Finally, surface and underground flow estimations are combined to perceive the state of the urban sewer network accurately. The results show that, compared with the common SWMM simulation, the accuracy of the water level simulation is improved by 43.5% during the rainfall period, and the time cost of the computational optimization is reduced by 67.5%. The proposed method can effectively diagnose the operation state and overflow risk of the sewer networks in real time during rainfall seasons.

Estimation of the impact of combined sewer overflows on surface water quality in a sparsely monitored area

Combined sewer overflows (CSOs) can have a severe negative, local impact on surface water systems. To assure good ecological surface water quality and drinking water production that meets the demands, the impact of sewer system overflows on the surrounding water bodies for current and future climate conditions needs to be assessed. Typically, integrated, detailed hydrological and hydrodynamic water quantity and quality models are used for this purpose, but often data and computational resource requirements limit their applicability. Therefore, an alternative computationally efficient, integrated water quantity and quality model of sewer systems and their receiving surface waters is proposed to assess the impact of CSOs on surface water quality in a sparsely observed area. A conceptual model approach to estimate CSO discharges is combined with an empirical model for estimating CSO pollutant concentrations based on waste water treatment plant influent observations. Both methods are compared with observations and independent results of established reference methods as to evaluate their performance. The methodology is demonstrated by modelling the current impact of CSOs on the water abstraction area of a major drinking water production centre in Flanders, Belgium. It is concluded that the proposed conceptual models achieve similar results for daily WWTP effluent and CSO frequency, whereby the accumulated CSO volume is similar to more detailed full hydrodynamic models. Further, the estimated pollutant concentrations correspond with another dataset based on high resolution sampled overflows. As a result, the proposed computational efficient method can give insights in the impact of CSOs on the water quality at a catchment level and can be used for planning monitoring campaigns or performing analyses of e.g. the current and future water availability for a data scarce areas.

Toward shotgun metagenomic approaches for microbial source tracking sewage spills based on laboratory mesocosms

Little is known about the genomic diversity of the microbial communities associated with raw municipal wastewater (sewage), including whether microbial populations specific to sewage exist and how such populations could be used to improve source attribution and apportioning in contaminated waters. Herein, we used the influent of three wastewater treatment plants in Atlanta, Georgia (USA) to perturb laboratory freshwater mesocosms, simulating sewage contamination events, and followed these mesocosms with shotgun metagenomics over a 7-day observational period. We describe 15 abundant non-redundant bacterial metagenome-assembled genomes (MAGs) ubiquitous within all sewage inocula yet absent from the unperturbed freshwater control at our analytical limit of detection. Tracking the dynamics of the populations represented by these MAGs revealed varied decay kinetics, depending on (inferred) phenotypes, e.g., anaerobes decayed faster than aerobes under the well-aerated incubation conditions. Notably, a portion of these populations showed decay patterns similar to those of common markers, Enterococcus and HF183. Despite the apparent decay of these populations, the abundance of β-lactamase encoding genes remained high throughout incubation relative to the control. Lastly, we constructed genomic libraries representing several different fecal sources and outline a bioinformatic approach which leverages these libraries for identifying and apportioning contamination signal among multiple probable sources using shotgun metagenomic data.

Preparing for Sea-Level Rise through Adaptive Managed Retreat of a New Zealand Stormwater and Wastewater Network

Sea-level rise increasingly affects low-lying and exposed coastal communities due to climate change. These communities rely upon the delivery of stormwater and wastewater services which are often co-located underground in coastal areas. Due to sea-level rise and associated compounding climate-related hazards, managing these networks will progressively challenge local governments as climate change advances. Thus, responsible agencies must reconcile maintaining Levels of Service as the impacts of climate change worsen over the coming decades and beyond. A critical question is whether such networks can continue to be adapted/protected over time to retain Levels of Service, or whether eventual retreat may be the only viable adaptation option? If so, at what performance threshold? In this paper, we explore these questions for stormwater and wastewater, using a dynamic adaptive pathway planning (DAPP) approach designed to address thresholds and increasing risk over time. Involving key local stakeholders, we here use DAPP to identify thresholds for stormwater and wastewater services and retreat options, and for developing a comprehensive and area-specific retreat strategy comprising pathway portfolios, retreat phases, potential land use changes, and for exploring pathway conflicts and synergies. The result is a prototype for an area near Wellington, New Zealand, where a managed retreat of water infrastructure is being considered at some future juncture. Dynamic adaptive strategies for managed retreats can help to reduce future disruption from coastal flooding, signal land use changes early, inform maintenance, and allow for gradual budget adjustments by the agencies that can manage expenditure over time. We present this stepwise process in a pathway form that can be communicated spatially and visually, thereby making a retreat a more manageable, sequenced, adaptation option for water agencies, and the communities they serve.

Sensitivity Analysis of a Groundwater Infiltration Model and Sea-Level Rise Applications for Coastal Sewers

Groundwater elevations in coastal cities will be affected by climate-change-induced sea level rise (SLR) and wastewater collection systems will experience increased groundwater infiltration (GWI) due to greater submergence of sewer pipes. Commercial sewer hydraulics models consider GWI to be a constant quantity estimated via a low-flow monitoring campaign and are incapable of predicting future flows due to changes in GW elevations. A global sensitivity analyses conducted for a two-dimensional GWI pipe flow model found the most important input parameters are groundwater head and surrounding soil hydraulic conductivity. Two case studies were conducted considering a range of pipe defect severity to estimate increases in GWI associated with predictions of future SLR. The findings are that SLR will begin to have noticeable impacts in terms of increased average dry weather flow (ADWF) as soon as 2030 (3–10%) and will increase dramatically in the future (10–29% by 2050, and 50% or more by 2100). Daily and seasonal tide ranges affect the normal diurnal flow variations by between 3% and 10%. The estimation methodology and case studies described here illustrate the coming future importance of SLR effects on GWI in coastal collection systems that should be included in facilities planning and design.