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Prioritizing Investments in Improving Flood Resilience and Reliability of Wastewater Treatment Infrastructure
Infrastructures are important facilities in urban areas servicing societies. Failure of these systems could pose a significant threat to the public. Increasing the infrastructure’s reliability is one way to ensure that these facilities preserve their performance during natural hazards such as flooding. In this study, a scheme is proposed for financial resource allocation to waste water treatment plants (WWTPs) with the goal of improving resilience and reliability. For this purpose, after determining which WWTPs’ factors (characteristics) are effective on flood resilience, a multicriteria decision-making approach is used to quantify resilience. Then, factors that could be improved by financial resource allocation are identified to increase resilience. To best allocate the available financial resources to these factors, an optimization routine is proposed. This routine uses the technique for order of preference by similarity to ideal solution method and genetic algorithm, and results in a trade-off curve for each plant. To find the optimal way of allocating financial resources among all WWTPs, a second optimization routine is proposed. Finally, to evaluate the WWTPs’ performance against flooding, reliability is calculated using the load-resistance concept. Fourteen WWTPs in New York City were considered in the case study to test the methodology. Results show that by using optimization tools, financial resources allocation could substantially improve resilience and the reliability of WWTPs. The results also indicate that in evaluating the system’s performance to deal with flooding, reliability and resilience result in compatible findings; however, they measure the performance based on different concepts and enumerations. The proposed methodology can be extended and applied for other infrastructures as well.
Prioritizing Investments in Improving Flood Resilience and Reliability of Wastewater Treatment Infrastructure
Infrastructures are important facilities in urban areas servicing societies. Failure of these systems could pose a significant threat to the public. Increasing the infrastructure’s reliability is one way to ensure that these facilities preserve their performance during natural hazards such as flooding. In this study, a scheme is proposed for financial resource allocation to waste water treatment plants (WWTPs) with the goal of improving resilience and reliability. For this purpose, after determining which WWTPs’ factors (characteristics) are effective on flood resilience, a multicriteria decision-making approach is used to quantify resilience. Then, factors that could be improved by financial resource allocation are identified to increase resilience. To best allocate the available financial resources to these factors, an optimization routine is proposed. This routine uses the technique for order of preference by similarity to ideal solution method and genetic algorithm, and results in a trade-off curve for each plant. To find the optimal way of allocating financial resources among all WWTPs, a second optimization routine is proposed. Finally, to evaluate the WWTPs’ performance against flooding, reliability is calculated using the load-resistance concept. Fourteen WWTPs in New York City were considered in the case study to test the methodology. Results show that by using optimization tools, financial resources allocation could substantially improve resilience and the reliability of WWTPs. The results also indicate that in evaluating the system’s performance to deal with flooding, reliability and resilience result in compatible findings; however, they measure the performance based on different concepts and enumerations. The proposed methodology can be extended and applied for other infrastructures as well.
Prioritizing Investments in Improving Flood Resilience and Reliability of Wastewater Treatment Infrastructure
Karamouz, M. (author) / Rasoulnia, E. (author) / Olyaei, M. A. (author) / Zahmatkesh, Z. (author)
2018-07-17
Article (Journal)
Electronic Resource
Unknown
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