Cause and effect oriented sewer degradation evaluation to support scheduled inspection planning

Towards a decentralized solution for sewer leakage detection - a review

Sewer pipelines often leak due to physical, operational, and environmental deterioration factors. Due to the hidden infrastructure of the sewer systems, leakage detection is often costly, challenging, and crucial at the city scale. Various sewer inspection methods (SIMs) have been developed and implemented at this time. This study evaluates the existing SIMs and categorizes them based on their area of impact (AoI) into three classes. Tier-one (T-I) methods, such as deterioration models and hotspot mapping, tend to grasp a broader and reliable understanding of the sewer systems' structural health and pinpoint the network sections that are more prone to leakage. As an intermediate solution, Tier-two (T-II) non-destructive methods, such as aerial thermal imagery (ATI) and electrical resistivity tomography (ERT), inspect the potential pipe clusters regardless of their material and visualize the leaked plume generated from defects and cracks. Tier-three (T-III) methods include in-pipe SIMs, such as visual and multi-sensory inspections, that can provide an in-depth understanding of the pipe and its deterioration stage. In this study, we suggest that a sustainable sewer inspection plan should include at least two SIMs belonging to different tiers to provide a dual investigation of precision and AoI, a balance between cost and time as well as an equilibrium between self-sufficiency and decentralization.

Harmonized assessment of nutrient pollution from urban systems including losses from sewer exfiltration: a case study in Germany

A growing literature indicates that untreated wastewater from leaky sewers stands among major sources of pollution to water resources of urban systems. Despite that, the quantification and allocation of sewer exfiltration are often restricted to major pipe areas where inspection data are available. In large-scale urban models, the emission from sewer exfiltration is either neglected (particularly from private sewers) or represented by simplified fixed values, and as such its contribution to the overall urban emission remains questionable. This study proposes an extended model framework which incorporates sewer exfiltration pathway in the catchment model for a better justified pollution control and management of urban systems at a nationwide scale. Nutrient emission from urban areas is quantified by means of the Modelling of Nutrient Emissions in River Systems (MONERIS) model. Exfiltration is estimated for public and private sewers of different age groups in Germany using the verified methods at local to city scales, upscaling techniques, and expert knowledge. Results of this study suggest that the average exfiltration rate is likely to be less than 0.01 L/s per km, corresponding to approximately 1 mm/m/year of wastewater discharge to groundwater. Considering the source and age factors, the highest rate of exfiltration is defined in regions with significant proportions of public sewers older than 40 years. In regions where public sewers are mostly built after 1981, the leakage from private sewers can be up two times higher than such from public sewers. Overall, sewer exfiltration accounts for 9.8% and 17.2% of nitrate and phosphate loads from urban systems emitted to the environment, which increases to 11.2% and 19.5% in the case of no remediation scenario of projected defective sewer increases due to ageing effects. Our results provide a first harmonized quantification of potential leakage losses in urban wastewater systems at the nationwide scale and reveal the importance of rehabilitation planning of ageing sewer pipes in public and private sewer systems. The proposed model framework, which incorporates important factors for urban sewer managers, will allow further targeting the important data need for validating the approach at the regional and local scales in order to support better strategies for the long-term nutrient pollution control of large urban wastewater systems.

Using deterioration modelling to simulate sewer rehabilitation strategy with low data availability

Most cities face the problem of an aging infrastructure in need of extensive and ongoing repair, renovation or replacement. Since the 1980s, CCTV has been the industry standard for sewer system inspection and the main source of information for structural performance evaluation. Due to low inspection rates and the lack of information about sewer condition, deterioration models have been developed to simulate the condition of non-inspected sewers and assess the influence of several rehabilitation scenarios. This paper presents an innovative modelling tool for long-term sewer rehabilitation planning based on the integration of a deterioration and a rehabilitation model. The tool is demonstrated in full scale using CCTV and sewer data of the city of Sofia, in Bulgaria. Results provide tangible proofs of investment needs for sewer rehabilitation and support the utility in the negotiation of budgets with the municipality. Since age is one key variable for deterioration modelling, a new method is proposed to estimate missing construction years in the utility database with a prediction error of less than 7 years.

Sewer Condition Prediction and Analysis of Explanatory Factors

Sewer condition is commonly assessed using closed-circuit television (CCTV) inspections. In this paper, we combine inspection results, pipe attributes, network data, and data on pipe environment to predict pipe condition and to discover which factors affect it. We apply the random forest algorithm to model pipe condition and assess the variable importance using the Boruta algorithm. We analyse the impact of predictor variables on poor condition using partial dependence plots, which are a valuable technique for this purpose. The results can be used in screening pipes for future inspections and provide insight into the dynamics between predictor variables and poor condition.