Framework for Risk-Based Decision Support on Infiltration and Inflow to Wastewater Systems
Abstract
:1. Introduction
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. 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
- A.
- Sola et al. [29] 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.
- B.
- Davalos et al. [30] 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.
- C.
- Diogo et al. [31] 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.
- D.
- Moskwa et al. [32] 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.
- E.
- Vallin [33] 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.
- F.
- Lee et al. [34] 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.
- G.
- King County [35] 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.
- H.
- DeMonsabert and Thornton [36] 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
5. Conclusions
- 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 [3], and the decision-making process described by Aven [7]. 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.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Ethical theory | |||||
---|---|---|---|---|---|
Effects | Utilitarian | Deontological | |||
CBA 1 | CBA 2 | MCDA 1 | MCDA 2 | ||
Monetized | Environmental | ||||
Social | |||||
Financial | |||||
Not monetized | Social | ||||
Environmental |
Evaluation Criteria | |
---|---|
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? |
Sustainability | |
Economic | |
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? |
Level | A | B | C | D | E | F | G | H | |
---|---|---|---|---|---|---|---|---|---|
System | System | Component | One pipe | System | Component | System | Component | ||
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 system | - | |
Temporary effects | Basement flooding, CSOs | - | - | - | Basement flooding, CSOs | - | - | - | |
Measure (risk treatment option) | Rehabilitation Upsizing Retention | Rehabilitation Upsizing | Rehabilitation Disconnection | Rehabilitation | Open stormwater solutions | Rehabilitation | Rehabilitation Upsizing Disconnection | Rehabilitation |
Evaluation Criterion | A | B | C | D | E | F | G | H |
---|---|---|---|---|---|---|---|---|
Risk-based | ✓ | |||||||
Uncertainty | ✓ | (✓) | ||||||
Sustainability | ||||||||
Economic | ||||||||
Internal | € | € | € | ✓ | € | € | € | € |
External | € | |||||||
Social | € | ✓ | ||||||
Environmental | € | ✓ |
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Ohlin Saletti, A.; Rosén, L.; Lindhe, A. Framework for Risk-Based Decision Support on Infiltration and Inflow to Wastewater Systems. Water 2021, 13, 2320. https://doi.org/10.3390/w13172320
Ohlin Saletti A, Rosén L, Lindhe A. Framework for Risk-Based Decision Support on Infiltration and Inflow to Wastewater Systems. Water. 2021; 13(17):2320. https://doi.org/10.3390/w13172320
Chicago/Turabian StyleOhlin Saletti, Anna, Lars Rosén, and Andreas Lindhe. 2021. "Framework for Risk-Based Decision Support on Infiltration and Inflow to Wastewater Systems" Water 13, no. 17: 2320. https://doi.org/10.3390/w13172320