Financial allocation and network recovery for interdependent wastewater treatment infrastructure: development of resilience metrics

References

• Abdullah, L., Chan, W., & Afshari, A. (2019). Application of PROMETHEE method for green supplier selection: A comparative result based on preference functions. Journal of Industrial Engineering International, 15(2), 271–285. https://doi.org/10.1007/s40092-018-0289-z
   Google Scholar
• Almoghathawi, Y., González, A. D., & Barker, K. (2021). Exploring recovery strategies for optimal interdependent infrastructure network resilience. Networks and Spatial Economics, 21(1), 229–260. https://doi.org/10.1007/s11067-020-09515-4 .
   Web of Science ®Google Scholar
• Anaokar, G., Khambete, A., & Christian, R. (2018). Evaluation of a performance index for municipal wastewater treatment plants using MCDM – TOPSIS. International Journal of Technology, 9(4), 715. https://doi.org/10.14716/ijtech.v9i4.102
   Web of Science ®Google Scholar
• Balci, P., & Cohn, A. (2014). NYC wastewater resiliency plan: climate risk assessment and adaptation. Icsi, 2014, 246–256. https://doi.org/10.1061/9780784478745.021
   Google Scholar
• Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200(1), 198–215. https://doi.org/10.1016/j.ejor.2009.01.021
   Web of Science ®Google Scholar
• Binmore, K., Rubinstein, A., & Wolinsky, A. (1986). The Nash bargaining solution in economic modelling. Journal of Economics, 17(2), 176–188. https://doi.org/10.2307/2555382
   Web of Science ®Google Scholar
• Blake, E. S., Kimberlain, T. B., Berg, R. J., Cangialosi, J. P., & Beven Ii, J. L. (2013). Tropical cyclone report: Hurricane sandy. National Hurricane Center, 12, 1-10.
   Google Scholar
• Bristow, D. N. (2015). Asset system of systems resilience planning: The Toronto case. Infrastructure Asset Management, 2(1), 15–22. https://doi.org/10.1680/iasma.14.00044
   Google Scholar
• Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O’Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. A., & von Winterfeldt, D. (2003). A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra, 19(4), 733–752. https://doi.org/10.1193/1.1623497
   Web of Science ®Google Scholar
• Bruneau, M., & Reinhorn, A. (2007). Exploring the concept of seismic resilience for acute care facilities. Earthquake Spectra, 23(1), 41–62. https://doi.org/10.1193/1.2431396
   Web of Science ®Google Scholar
• Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247. https://doi.org/10.1016/0165-0114(85)90090-9
   Web of Science ®Google Scholar
• Chang, D.-Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655. https://doi.org/10.1016/0377-2217(95)00300-2
   Web of Science ®Google Scholar
• Chen, V. Y. C., Lien, H. P., Liu, C. H., Liou, J. J. H., Tzeng, G. H., & Yang, L. S. (2011). Fuzzy MCDM approach for selecting the best environment-watershed plan. Applied Soft Computing Journal, 11(1), 265–275. https://doi.org/10.1016/j.asoc.2009.11.017
   Web of Science ®Google Scholar
• Dewalkar, S. V., & Shastri, S. S. (2022). Integrated life cycle assessment and life cycle cost assessment based fuzzy multi-criteria decision-making approach for selection of appropriate wastewater treatment system. Journal of Water Process Engineering, 45, 102476. https://doi.org/10.1016/j.jwpe.2021.102476
   Web of Science ®Google Scholar
• Downer, C. W., & Ogden, F. L. (2004). GSSHA: Model to simulate diverse stream flow producing processes. Journal of Hydrologic Engineering, 9(3), 161–174. https://doi.org/10.1061/(ASCE)1084-0699(2004)9:3(161)
   Web of Science ®Google Scholar
• Duijnhoven, H., Nieuwenhuijs, A., van den Brink, P., Stolk, D., & van Ruijven, T. (2017). Critical infrastructure resilience: bridging the gap between measuring and governance. 7th REA Symposium. http://improverproject.eu/category/results/
   Google Scholar
• FEMA. (2003). Multi-hazard loss estimation methodology, Earthquake model, HAZUS, technical manual. Federal Emergency Management Agency.
   Google Scholar
• FEMA. (2013). Multi-hazard loss estimation methodology, Flood model, HAZUS, technical manual. Federal Emergency Management Agency. www.msc.fema.gov
   Google Scholar
• Gay, L. F., Sinha, S. K. (2013). Resilience of civil infrastructure systems: Literature review for improved asset management. International Journal of Critical Infrastructures, 9(4). .330–350. https://doi.org/10.1504/IJCIS.2013.058172
   Google Scholar
• Gogus, O., & Boucher, T. O. (1998). Strong transitivity, rationality and weak monotonicity in fuzzy pairwise comparisons. Fuzzy Sets and Systems, 94(1), 133–144. https://doi.org/10.1016/S0165-0114(96)00184-4
   Web of Science ®Google Scholar
• Guidotti, R., Chmielewski, H., Unnikrishnan, V., Gardoni, P., McAllister, T., & van de Lindt, J. (2016). Modeling the resilience of critical infrastructure: The role of network dependencies. Sustainable and Resilient Infrastructure, 1(3–4), 153–168. https://doi.org/10.1080/23789689.2016.1254999
   PubMed Web of Science ®Google Scholar
• Hay, A. H. (2016). The incident sequence as resilience planning framework. Infrastructure Asset Management, 3(2), 55–60. https://doi.org/10.1680/jinam.16.00003
   Google Scholar
• He, X., & Cha, E. J. (2018). Modeling the damage and recovery of interdependent critical infrastructure systems from natural hazards. Reliability Engineering & System Safety, 177, 162–175. https://doi.org/10.1016/j.ress.2018.04.029
   Web of Science ®Google Scholar
• He, X., & Cha, E. J. (2020). Modeling the damage and recovery of interdependent civil infrastructure network using dynamic integrated network model. Sustainable and Resilient Infrastructure, 5(3), 152–167. https://doi.org/10.1080/23789689.2018.1448662
   Web of Science ®Google Scholar
• Henry, D., & Emmanuel Ramirez-Marquez, J. (2012). Generic metrics and quantitative approaches for system resilience as a function of time. Reliability Engineering and System Safety, 99, 114–122. https://doi.org/10.1016/j.ress.2011.09.002
   Web of Science ®Google Scholar
• Hosseini, S., Barker, K., & Ramirez-Marquez, J. E. (2016). A review of definitions and measures of system resilience. Reliability Engineering & System Safety, 145, 47–61. https://doi.org/10.1016/j.ress.2015.08.006
   Web of Science ®Google Scholar
• Imani, M., & Hajializadeh, D. (2020). A resilience assessment framework for critical infrastructure networks’ interdependencies. Water Science and Technology, 81(7), 1420–1431. https://doi.org/10.2166/wst.2019.367
   PubMed Web of Science ®Google Scholar
• Kabir, G., & Ahsan Akhtar Hasin, M. 2011. Comparative analysis of ahp and fuzzy ahp models for multicriteria inventory classification. International Journal of Fuzzy Logic Systems (IJFLS) 1(1), 1–16. https://wireilla.com/papers/ijfls/V1N1/1011ijfls01
   Google Scholar
• Karamlou, A., & Bocchini, P. (2015). Computation of bridge seismic fragility by large-scale simulation for probabilistic resilience analysis. Earthquake Engineering and Structural Dynamics, 44(12), 1959–1978. https://doi.org/10.1002/eqe.2567
   Web of Science ®Google Scholar
• Karamouz, M., & Fereshtehpour, M. (2019). Modeling DEM errors in coastal flood inundation and damages: A spatial nonstationary approach. Water Resources Research, 55(8), 6606–6624. https://doi.org/10.1029/2018WR024562
   Web of Science ®Google Scholar
• Karamouz, M., & Hojjat-Ansari, A. (2020). Uncertainty based budget allocation of wastewater infrastructures’ flood resiliency considering interdependencies. Journal of Hydroinformatics, 22(4), 768–792. https://doi.org/10.2166/hydro.2020.145
   Web of Science ®Google Scholar
• Karamouz, M., & Movahhed, M. (2021). Asset management based flood resiliency of water infrastructure. World Environmental and Water Resources Congress, 2021, 1081–1091. https://doi.org/10.1061/9780784483466.101
   Google Scholar
• Karamouz, M., Nazif, S., & Razmi, A. (2014). Integration of coastal storm inundation model (GSSHA) with grid surface and subsurface hydrological model. World Environmental and Water Resources Congress, 2014, 887–898. https://doi.org/10.1061/9780784413548.092
   Google Scholar
• Karamouz, M., Rasoulnia, E., Olyaei, M. A., & Zahmatkesh, Z. (2018). Prioritizing investments in improving flood resilience and reliability of wastewater treatment infrastructure. Journal of Infrastructure Systems, 24(4. https://doi.org/10.1061/(asce)is.1943-555x.0000434
   Google Scholar
• Karamouz, M., Rasoulnia, E., Zahmatkesh, Z., Olyaei, M. A., & Baghvand, A. (2016). Uncertainty-based flood resiliency evaluation of wastewater treatment plants. Journal of Hydroinformatics, 18(6), 990–1006. https://doi.org/10.2166/hydro.2016.084
   Web of Science ®Google Scholar
• Karamouz, M., Zoghi, A., & Mahmoudi, S. (2022). Flood modeling in coastal cities and flow through vegetated BMPs: A conceptual design. Journal of Hydrologic Engineering, 27(10). https://doi.org/10.1061/(ASCE)HE.1943-5584.0002206
   Google Scholar
• Kaya, İ., Çolak, M., & Terzi, F. (2019). A comprehensive review of fuzzy multi criteria decision making methodologies for energy policy making. Energy Strategy Reviews, 24(March), 207–228. https://doi.org/10.1016/j.esr.2019.03.003
   Web of Science ®Google Scholar
• Kong, J., & Simonovic, S. P. (2016). An original model of infrastructure system resilience. Proceedings, Annual Conference - Canadian Society for Civil Engineering, 3, 1771–1781.
   Google Scholar
• Kong, J., Simonovic, S. P., & Zhang, C. (2019). Sequential hazards resilience of interdependent infrastructure system: A case study of greater Toronto area energy infrastructure system. Risk Analysis, 39(5), 1141–1168. https://doi.org/10.1111/risa.13222
   PubMed Web of Science ®Google Scholar
• Kurtz, S. S. J., Saur, G., & Ainscough, C. (2013). Utilization of underground and overhead power lines in the city of New York. Office of Long-Term Planning and Sustainability, Office of the Mayor, City of New York.
   Google Scholar
• Lafortezza, R., Chen, J., van den Bosch, C. K., & Randrup, T. B. (2018). Nature-based solutions for resilient landscapes and cities. Environmental Research, 165, 431–441. https://doi.org/10.1016/j.envres.2017.11.038
   PubMed Web of Science ®Google Scholar
• Liu, Y., Eckert, C. M., & Earl, C. (2020). A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 161, 113738. https://doi.org/10.1016/j.eswa.2020.113738
   Web of Science ®Google Scholar
• Ma, L., Bocchini, P., & Christou, V. (2020). Fragility models of electrical conductors in power transmission networks subjected to hurricanes. Structural Safety, 82, 101890. https://doi.org/10.1016/j.strusafe.2019.101890
   Web of Science ®Google Scholar
• Malano, H. M., Chien, N. V., & Turral, H. N. (1999). Asset management for irrigation and drainage infrastructure. Irrigation and Drainage Systems, 13(2), 109–129. https://doi.org/10.1023/A:1006254924281
   Google Scholar
• Noori, A., Bonakdari, H., Salimi, A. H., & Gharabaghi, B. (2021). A group multi-criteria decision-making method for water supply choice optimization. Socio-Economic Planning Sciences, 77(December), 101006. https://doi.org/10.1016/j.seps.2020.101006
   Web of Science ®Google Scholar
• NYCDEP (NewYork City Department of Environmental Protection). (2013). NYC wastewater resiliency plan, climate risk assessment and adaptation study. Department of Environmental Protection, New York City, USA.
   Google Scholar
• OECD. (2021). Building resilience: New strategies for strengthening infrastructure resilience and maintenance. OECD Public Governance Policy Papers, No. 05, OECD Publishing, Paris. https://doi.org/10.1787/354aa2aa-en
   Google Scholar
• Olyaei, M. A., Karamouz, M., & Farmani, R. (2018). Framework for assessing flood reliability and resilience of wastewater treatment plants. Journal of Environmental Engineering, 144(9. https://doi.org/10.1061/(asce)ee.1943-7870.0001422
   Google Scholar
• Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering & System Safety, 121, 43–60. https://doi.org/10.1016/j.ress.2013.06.040
   Web of Science ®Google Scholar
• Ouyang, M., & Dueñas-Osorio, L. (2014). Multi-dimensional hurricane resilience assessment of electric power systems. Structural Safety, 48, 15–24. https://doi.org/10.1016/j.strusafe.2014.01.001
   Web of Science ®Google Scholar
• Reed, D. A., Kapur, K. C., & Christie, R. D. (2009). Methodology for assessing the resilience of networked infrastructure. IEEE Systems Journal, 3(2), 174–180. https://doi.org/10.1109/JSYST.2009.2017396
   Web of Science ®Google Scholar
• Rinaldi, S. M. (2004). Modeling and simulating critical infrastructures and their interdependencies. 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of The, 37, 8 pp. https://doi.org/10.1109/HICSS.2004.1265180
   Google Scholar
• Saaty, R. W. (1987). The analytic hierarchy process-what it is and how it is used Mathematical Modelling, 9(5):161–176. https://doi.org/10.1016/0270-0255(87)90473-8
   Web of Science ®Google Scholar
• Salman, A. M., & Li, Y. (2016). Age-dependent fragility and life-cycle cost analysis of wood and steel power distribution Poles subjected to hurricanes. Structure and Infrastructure Engineering, 12(8), 890–903. https://doi.org/10.1080/15732479.2015.1053949
   Web of Science ®Google Scholar
• Sánchez-Muñoz, D., Domínguez-García, J. L., Martínez-Gomariz, E., Russo, B., Stevens, J., & Pardo, M. (2020). Electrical grid risk assessment against flooding in Barcelona and Bristol cities. Sustainability, 12(4), 1527. https://doi.org/10.3390/su12041527
   Web of Science ®Google Scholar
• Schoen, M., Hawkins, T., Xue, X., Ma, C., Garland, J., & Ashbolt, N. J. (2015). Technologic resilience assessment of coastal community water and wastewater service options. Sustainability of Water Quality and Ecology, 6, 75–87. https://doi.org/10.1016/j.swaqe.2015.05.001
   Google Scholar
• Shin, S., Lee, S., Judi, D. R., Parvania, M., Goharian, E., McPherson, T., & Burian, S. J. (2018). Water (Switzerland), 10(2):164–188. https://doi.org/10.3390/w10020164.
   Google Scholar
• Simonovic, S. P., & Peck, A. (2013). Dynamic resilience to climate change caused natural disasters in coastal megacities quantification framework. British Journal of Environment and Climate Change, 3(3), 378–401. https://doi.org/10.9734/BJECC/2013/2504
   Google Scholar
• Sitorus, F., Cilliers, J. J., & Brito-Parada, P. R. (2019). Multi-criteria decision making for the choice problem in mining and mineral processing: Applications and trends. Expert Systems with Applications, 121, 393–417. https://doi.org/10.1016/j.eswa.2018.12.001
   Web of Science ®Google Scholar
• Sun, W., Bocchini, P., & Davison, B. D. (2020). Sustainable and Resilient Infrastructure, 5(3): 168–199.https://doi.org/10.1080/23789689.2018.1448663
   Web of Science ®Google Scholar
• Sweetapple, C., Fu, G., Farmani, R., & Butler, D. (2022). General resilience: Conceptual formulation and quantitative assessment for intervention development in the urban wastewater system. Water Research, 211. https://doi.org/10.1016/j.watres.2022.118108
   Google Scholar
• Tahmasebi Birgani, Y., & Yazdandoost, F. (2018). An integrated framework to evaluate resilient-sustainable urban drainage management plans using a combined-adaptive MCDM technique. Water Resources Management, 32(8), 2817–2835. https://doi.org/10.1007/s11269-018-1960-2
   Web of Science ®Google Scholar
• Tong, L., Pu, Z., Chen, K., & Yi, J. (2020). Sustainable maintenance supplier performance evaluation based on an extend fuzzy PROMETHEE II approach in petrochemical industry. Journal of Cleaner Production, 273, 122771. https://doi.org/10.1016/j.jclepro.2020.122771
   Web of Science ®Google Scholar
• Vugrin, E., Castillo, A., & Silva-Monroy, C. (2017). Resilience metrics for the electric power system: A performance-based approach. https://doi.org/10.2172/1367499
   Google Scholar
• Wu, Y., Wang, Y., Chen, K., Xu, C., & Li, L. (2017). Social sustainability assessment of small hydropower with hesitant PROMETHEE method. Sustainable Cities and Society, 35, 522–537. https://doi.org/10.1016/j.scs.2017.08.034
   Web of Science ®Google Scholar
• Xiao, F. (2019). EFMCDM: Evidential fuzzy multicriteria decision making based on belief entropy. IEEE Transactions on Fuzzy Systems, 28(7), 1. https://doi.org/10.1109/TFUZZ.2019.2936368
   Web of Science ®Google Scholar
• Yu, J.-Z., Whitman, M., Kermanshah, A., & Baroud, H. (2021). A hierarchical Bayesian approach for assessing infrastructure networks serviceability under uncertainty: A case study of water distribution systems. Reliability Engineering & System Safety, 215(July 2020), 107735. https://doi.org/10.1016/j.ress.2021.107735
   Web of Science ®Google Scholar
• Zamani, R., Ali, A. M. A., & Roozbahani, A. (2020). Evaluation of adaptation scenarios for climate change impacts on agricultural water allocation using fuzzy MCDM methods. Water Resources Management, 34(3), 1093–1110. https://doi.org/10.1007/s11269-020-02486-8
   Web of Science ®Google Scholar