2. Materials and Methods
2.1. Developing the Framework
2.2. Ethical Principles and Decision Support Methods
2.3. Evaluating Models Based on Framework
3.1. Goals, Criteria, and Preferences
3.2. Risk Analysis
4. Evaluation of Models Based on the Framework
4.1. Models on I/I and Decision Support
- Sola et al.  presented a model for analyzing the consequences of I/I-water by comparing the four measures of full restoration of all wastewater pipes, increasing pump capacity, using local retention basins, and business as usual in the municipality of Asker in Norway. In the model, the costs of performing the different measures including operation costs are compared to the benefits of improved bathing-water quality and the avoidance of basement flooding.
- Davalos et al.  presented a model to identify pumping stations in Miami-Dade County in the United States where it is more efficient to perform rehabilitation measures than to adapt the system to the I/I-water volumes. The costs of performing measures to reduce I/I-water based on historical data is compared to savings for not having to treat and transport the I/I-water, as well as savings for not constructing or oversizing WWTPs, pipes, or pumping stations due to I/I-water.
- Diogo et al.  presented a model including two functions to optimize I/I-water reduction. In the first function, the costs for rehabilitation of each link and node, as well as costs for the removal of wrongly connected laterals in the sewer system, are compared to the savings of not having to transport and treat I/I-water. In the second function, the structural condition for each node and link in the system is included. By minimizing the functions, it can be determined if each node and link in the system should be rehabilitated or not, as well as which of the wrongly connected laterals should be removed. A case study is included using a simplified approach at three locations in Coimbra, Portugal.
- Moskwa et al.  presented a model to evaluate four different rehabilitation measures to reduce infiltration in a large trunk sewer in the region of Halton, California, United States. Eight different evaluation criteria, e.g., cost, infiltration elimination, and local availability are set up. For each rehabilitation measure, scores are assigned, and, after including weighing for the evaluation criteria, a total score for each rehabilitation measure can be obtained.
- Vallin  presented a model aiming to examine the suitability of using multicriteria analysis for the spatial resource allocation of stormwater solutions in order to reduce inflow. In the model, all properties and hard surfaces in an area are assigned a score symbolizing their need for improvement based on the risk of large volumes of I/I-water, basement flooding, and CSOs. The properties and hard surfaces are merged into sub-areas and their scores compared to the cost of performing a measure to reduce the inflow. Hence, the sub-areas where it is most efficient to perform a measure can be identified. A case study using the model in Bjurås in Sweden is included.
- Lee et al.  presented a model aiming to facilitate decisions on which order the wastewater system in subareas should be rehabilitated to minimize I/I-water to the WWTP during the rehabilitation process. Based on detected defects on each pipe in the system, the volume of I/I-water in the subareas was estimated. In the following step, the optimal rehabilitation order was determined. A case study was performed in Seoul, South Korea.
- King County  presented a model aiming to identify cost-effective I/I-water reduction projects in King County, Washington, United States. The county identified system improvements that were required to manage the projected future flows. The costs of these projects were then compared to the cost of performing I/I measures, e.g., the disconnection of public and private laterals and rehabilitation. In those cases where the I/I measure in a subarea resulted in reaching the targets and the cost of performing the measure was below the cost of the conveyance system improvement, the I/I measure was recommended.
- DeMonsabert and Thornton  presented a model aiming to find the most effective method of repair for each defected manhole or pipe in a system. An equation was set up including possible repairs within the system for each component, as well as the change of I/I-water and the cost of treating I/I-water. The equation was then minimized to determine which method, if any, was most efficient to use for each component. A case study was carried out in Washington, DC, United States.
4.2. Examples of Other Models with a Broader Scope
- This paper presents a novel framework for risk-based decision support for handling infiltration and inflow (I/I) to wastewater systems based on established concepts, e.g., definitions by ISO , and the decision-making process described by Aven . Fundamental features of the framework are (1) the assessment of the risk of I/I by taking into account the complete chain from the source of I/I to the resulting effects and consequences, using events, consequences, and uncertainties; and (2) taking the three dimensions of sustainability, i.e., economic, social, and environmental aspects, into account.
- Among the eight published and reviewed existing models on I/I and decision support, none fully fulfil the evaluation criteria based on the presented framework. Only one of the models uses a risk-based approach, and two include uncertainties to any extent. Further, most of the models only include project internal economic effects, excluding the social and environmental dimensions of sustainability.
- Future research on implementing the framework, e.g., when performing a CBA or MCDA, is suggested, as well as a deeper analysis on how the system boundaries affect the assessed risk of I/I. More research is also needed on the behavior of I/I-water and potential risk treatment options in the wastewater systems to decrease epistemic uncertainties.
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
- USEPA. Control of Infiltration and Inflow into Sewer Systems; Environmental Protection Agency, Water Quality Office: Washington, DC, USA, 1970. [Google Scholar]
- Haghighatafshar, S.; Becker, P.; Moddemeyer, S.; Persson, A.; Sörensen, J.; Aspegren, H.; Jönsson, K. Paradigm shift in engineering of pluvial floods: From historical recurrence intervals to risk-based design for an uncertain future. Sustain. Cities Soc. 2020, 61, 102317. [Google Scholar] [CrossRef]
- ISO. Risk Management-Guidelines ISO 31000:2018; International Organization for Standardization: Geneva, Switzerland, 2018. [Google Scholar]
- Kaplan, S.; Garrick, B.J. On The Quantitative Definition of Risk. Risk Anal. 1981, 1, 11–27. [Google Scholar] [CrossRef]
- Aven, T. On how to define, understand and describe risk. Reliab. Eng. Syst. Saf. 2010, 95, 623–631. [Google Scholar] [CrossRef]
- Bedford, T.; Cooke, R. Probabilistic Risk Analysis: Foundations and methods; Cambridge University Press: Cambridge, UK, 2001. [Google Scholar]
- Aven, T. Foundations of Risk Analysis: Second Edition; John Wiley & Sons: Hoboken, NJ, USA, 2012. [Google Scholar]
- O’Hagan, A. Expert knowledge elicitation: Subjective but scientific. Am. Stat. 2019, 73 (Suppl. 1), 69–81. [Google Scholar] [CrossRef]
- Durbach, I.N.; Stewart, T.J. Modeling uncertainty in multi-criteria decision analysis. Eur. J. Oper. Res. 2012, 223, 1–14. [Google Scholar] [CrossRef]
- UN General Assembly. Resolution adopted by the General Assembly on 16 September 2005. 2005 World Summit Outcome. 2005. Available online: https://www.un.org/ga/search/view_doc.asp?symbol=A/RES/60/1&Lang=E (accessed on 16 September 2020).
- UN General Assembly Transforming Our World: The 2030 Agenda for Sustainable Development. Available online: https://www.refworld.org/docid/57b6e3e44.html (accessed on 17 December 2020).
- Anscombe, G.E.M. Modern moral philosophy. Philosophy 1958, 33, 1–19. [Google Scholar] [CrossRef]
- Sinnott-Armstrong, W. Consequentialism. In The Stanford Encyclopedia of Philosophy (Summer 2019 Edition); Zalta, E.N., Ed.; Available online: https://plato.stanford.edu/archives/sum2019/entries/consequentialism (accessed on 25 February 2021).
- Bentham, J. An Introduction to the Principles of Morals and Legislation; Oxford Clarendon Press: Oxford, UK, 1789. [Google Scholar]
- Mill, J.S. Utilitarianism, 1863 Reprinted in Marshall Cohen (ed.); The Philosophy of John Stuart Mill; Modern Library: New York, NY, USA, 1961; pp. 321–398. [Google Scholar]
- McFarland, M.S. Occidental Engineering Case Study: Part 1; Markkula Center for Applied Ethics. 2012. Available online: https://www.scu.edu/ethics/focus-areas/more/engineering-ethics/engineering-ethics-cases/occidental-engineering-case-study-part-5/ (accessed on 25 February 2020).
- Broad, C.D. Five Types of Ethical Theory; Routhledge & Kegan Paul: London, UK, 1930. [Google Scholar]
- Kant, I. Groundwork of the Metaphysics of Morals; tr. H. Paton. Harper & Row: New York, NY, USA, 1948. [Google Scholar]
- Howarth, R.B. Sustainability under uncertainty: A deontological approach. Land Econ. 1995, 1, 417–427. [Google Scholar] [CrossRef]
- Spash, C.L. Ethics and Environmental Attitudes With Implications for Economic Valuation. J. Environ. Manag. 1997, 50, 403–416. [Google Scholar] [CrossRef]
- DCLG. Multi-Criteria Analysis: A Manual; Department for Communities and Local Government: London, UK, 2009. Available online: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/7612/1132618.pdf (accessed on 16 February 2021).
- Boardman, A.E.; Greenberg, D.H.; Vining, A.R.; Weimer, D.L. Cost-Benefit Analysis: Concepts and Practice; Cambridge University Press: Cambridge, UK, 2017. [Google Scholar]
- Bäckman, H.; Hellström, B.G.; Jaryd, A.; Jonsson, Å. Measures to Minimize the Influence of Infiltration and Drainage in Sewerage Systems; VAV AB: Stockholm, Sweden, 1997. (In Swedish) [Google Scholar]
- Staufer, P.; Scheidegger, A.; Rieckermann, J. Assessing the performance of sewer rehabilitation on the reduction of infiltration and inflow. Water Res. 2012, 46, 5185–5196. [Google Scholar] [CrossRef]
- Gustafsson, L.-G. In Alternative Drainage Schemes for Reduction of Inflow/Infiltration-Prediction and Follow-up of Effects with the Aid of an Integrated Sewer/Aquifer Model. In Proceedings of the 1st International Conference on Urban Drainage via Internet, Niagara Falls, ON, Canada, 12–17 September 2000; pp. 21–37. [Google Scholar]
- Marleni, N.; Gray, S.; Sharma, A.; Burn, S.; Muttil, N. Impact of water management practice scenarios on wastewater flow and contaminant concentration. J. Environ. Manag. 2015, 151, 461–471. [Google Scholar] [CrossRef]
- Bäckman, H. Infiltration/Inflow in Separate Sewer Systems: Some Aspects on Sources and a Methodology for Localization and Quantification of Infiltration into Sanitary Sewers Caused by Leaking Storm Sewers. Ph.D. Thesis, Chalmers University of Technology, Gothenburg, Sweden, 1985. [Google Scholar]
- Beheshti, M.; Saegrov, S.; Ugarelli, R. Infiltration/Inflow Assessment and Detection in Urban Sewer System. VANN 2015, 1, 24–34. [Google Scholar]
- Sola, K.J.; Bjerkholt, J.T.; Lindholm, O.G.; Ratnaweera, H. Analysing consequences of infiltration and inflow water (I/I-water) using cost-benefit analyses. Water Sci. Technol. 2020, 82, 1312–1326. [Google Scholar] [CrossRef]
- Davalos, P.; Humphrey, G.; Eagle, S.; Roque, R.; Bedoya, J.; Edwards, D.; Torrealba, F.; Perez, J.; Dvorak, A. Cost Effective Infiltration and Inflow Analysis and Remediation Efforts in Miami-Dade County. In Proceedings of the 91st Annual Water Environment Federation Technical Exhibition and Conference (WEFTEC), New Orleans, LA, USA, 29 September–3 October 2018; pp. 2994–3023. [Google Scholar]
- Diogo, A.F.; Barros, L.T.; Santos, J.; Temido, J.S. An effective and comprehensive model for optimal rehabilitation of separate sanitary sewer systems. Sci. Total Environ. 2018, 612, 1042–1057. [Google Scholar] [CrossRef]
- Moskwa, P.; Filipovic, J.; Latimer, N.; Bainbridge, K. Eliminating Sewer Infiltration within the Region of Halton. In Proceedings of the NASTT’s 2018 No-Dig Show, Palm Springs, CA, USA, 25–29 March 2018. [Google Scholar]
- Vallin, H. Evaluation of Multi Criteria Analysis as a Tool for Spatial Resource Allocation of Stormwater Measures for Inflow and Infiltration to the Sewage Water System. Master’s Thesis, Uppsala University, Uppsala, Sweden, 2016. (In Swedish). [Google Scholar]
- Lee, J.H.; Baek, C.W.; Kim, J.H.; Jun, H.D.; Jo, D.J. Development of a Decision Making Support System for Efficient Rehabilitation of Sewer Systems. Water Resour Manag. 2009, 23, 1725–1742. [Google Scholar] [CrossRef]
- King County. Benefit/Cost Analysis Report-Regional Infiltration and Inflow Control Program; Department of Natural Resources and Parks: Seattle, WA, USA, 2005. [Google Scholar]
- DeMonsabert, S.; Thornton, P. A benders decomposition model for sewer rehabilitation planning for infiltration and inflow planning. Water Environ. Res. 1997, 69, 162–167. [Google Scholar] [CrossRef]
- Rehan, R.; Knight, M.A.; Unger, A.J.A.; Haas, C.T. Financially sustainable management strategies for urban wastewater collection infrastructure–development of a system dynamics model. Tunn. Undergr. Space Technol. 2014, 39, 116–129. [Google Scholar] [CrossRef]
- Baah, K.; Dubey, B.; Harvey, R.; McBean, E. A risk-based approach to sanitary sewer pipe asset management. Sci. Total Environ. 2015, 505, 1011–1017. [Google Scholar] [CrossRef]
- Vladeanu, G.J. Wastewater Pipe Condition and Deterioration Modeling for Risk-Based Decision-Making. Ph.D. Thesis, Lousiana Tech University, LA, USA, 16 August 2018. [Google Scholar]
- Vladeanu, G.; Matthews, J.C. Analysis of risk management methods used in trenchless renewal decision making. Tunn. Undergr. Space Technol. 2018, 72, 272–280. [Google Scholar] [CrossRef]
- Korving, H.; Van Noortwijk, J.M.; Van Gelder, P.H.A.J.M.; Clemens, F.H.L.R. Risk-based design of sewer system rehabilitation. Struct. Infrastruct. Eng. 2009, 5, 215–227. [Google Scholar] [CrossRef]
- Dusenbury, R.; Zickler, E.; Phillips, J.; Lancaster, A. A Paper on Balancing CSO Program Investment: The King County Green Infrastructure Scorecard. In Proceedings of the 91st Annual Water Environment Federation Technical Exhibition and Conference (WEFTEC), New Orleans, LA, USA, 29 September–3 October 2018; pp. 4817–4835. [Google Scholar]
- Alves, A.; Sanchez, A.; Vojinovic, Z.; Seyoum, S.; Babel, M.; Brdjanovic, D. Evolutionary and holistic assessment of green-grey infrastructure for CSO reduction. Water 2016, 8, 402. [Google Scholar] [CrossRef]
- Casal-Campos, A.; Fu, G.; Butler, D.; Moore, A. An Integrated Environmental Assessment of Green and Gray Infrastructure Strategies for Robust Decision Making. Environ. Sci. Technol. 2015, 49, 8307–8314. [Google Scholar] [CrossRef] [PubMed]
- Sadr, S.M.K.; Casal-Campos, A.; Fu, G.; Farmani, R.; Ward, S.; Butler, D. Strategic planning of the integrated urban wastewater system using adaptation pathways. Water Res. 2020, 182, 116013. [Google Scholar] [CrossRef] [PubMed]
- Beheshti, M.; Sægrov, S. Sustainability assessment in strategic management of wastewater transport system: A case study in Trondheim, Norway. Urban Water J. 2018, 15, 1–8. [Google Scholar] [CrossRef]
|CBA 1||CBA 2||MCDA 1||MCDA 2|
|Risk-based||Does the model include any quantification of risk using conceptslike probability and consequence?|
|Uncertainty||Are uncertainties in input data considered, e.g., by assigning probability distributions?|
|Internal||Are any internal economic effects included in the model?|
|External||Are any external economic effects included in the model?|
|Social||Are any social effects included in the model?|
|Environmental||Are any environmental effects included in the model?|
|Infiltration/inflow||Infiltration & inflow||Infiltration & inflow||Infiltration & inflow||Infiltration||Infiltration||Inflow||Infiltration & inflow||Infiltration|
|Effects||Transportation/treatment||Transportation & treatment||Transportation & treatment||Transportation & treatment||-||Transportation & treatment||Treatment||-||Transportation & treatment|
|Capacity issues||Constructing new WWTP||Capital construction||-||-||-||-||Increase sewer |
|Temporary effects||Basement flooding, CSOs||-||-||-||Basement flooding, CSOs||-||-||-|
|Measure (risk treatment option)||Rehabilitation|
|Rehabilitation||Open stormwater solutions||Rehabilitation||Rehabilitation|
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).