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Articles

Critical facility accessibility and road criticality assessment considering flood-induced partial failure

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Pages 337-355 | Received 26 Sep 2022, Accepted 12 Nov 2022, Published online: 25 Nov 2022

References

  • Abdulla, B., Kiaghadi, A., Rifai, H. S., & Birgisson, B. (2020). Characterization of vulnerability of road networks to fluvial flooding using sis network diffusion model. Journal of Infrastructure Preservation and Resilience, 1(1), 1–13. https://doi.org/10.1186/s43065-020-00004-z
  • Akbari, V., Shiri, D., & Salman, F. S. (2021). An online optimization approach to post-disaster road restoration. Transportation Research Part B: Methodological, 150, 1–25. https://doi.org/10.1016/j.trb.2021.05.017
  • Aksu, D. T., & Ozdamar, L. (2014). A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation. Transportation Research Part E: Logistics and Transportation Review, 61, 56–67. https://doi.org/10.1016/j.tre.2013.10.009
  • Alabbad, Y., Mount, J., Campbell, A. M., & Demir, I. (2021). Assessment of transportation system disruption and accessibility to critical amenities during flooding: Iowa case study. Science of the Total Environment, 793, 148476. https://doi.org/10.1016/j.scitotenv.2021.148476
  • Arrighi, C., Pregnolato, M., Dawson, R., & Castelli, F. (2019). Preparedness against mobility disruption by floods. Science of the Total Environment, 654, 1010–1022. https://doi.org/10.1016/j.scitotenv.2018.11.191
  • Aydin, N. Y., Casali, Y., Sebnem Duzgun, H., & Heinimann, H. R., (2019). Identifying changes in critical locations for transportation networks using centrality, in: International Conference on Computers in Urban Planning and Urban Management, Springer. pp. 405–423.
  • Barnard, P. L., Erikson, L. H., Foxgrover, A. C., Hart, J. A. F., Limber, P., O’Neill, A. C., van Ormondt, M., Vitousek, S., Wood, N., Hayden, M. K., & Jones, J. M. (2019). Dynamic flood modeling essential to assess the coastal impacts of climate change. Scientific Reports, 9(1), 1–13. https://doi.org/10.1038/s41598-019-40742-z
  • Barrette, P. D., Hori, Y., & Kim, A. M. (2022). The Canadian winter road infrastructure in a warming climate: Toward resiliency assessment and resource prioritization. Sustainable and Resilient Infrastructure, 1–19. https://doi.org/10.1080/23789689.2022.2094124.
  • Bates, P. D., Quinn, N., Sampson, C., Smith, A., Wing, O., Sosa, J., Savage, J., Olcese, G., Neal, J., Schumann, G., Giustraini, L., Coxon, G., Porter, J., Amodeo, M., Chu, Z., Lewis-Gruss, S., Freeman, N., Houser, T., Delgado, M., … Krajewski, W. (2021). Combined modeling of us fluvial, pluvial, and coastal flood hazard under current and future climates. Water Resources Research, 57(2), e2020WR028673. https://doi.org/10.1029/2020WR028673
  • Boakye, J., Guidotti, R., Gardoni, P., & Murphy, C. (2022). The role of transportation infrastructure on the impact of natural hazards on communities. Reliability Engineering & System Safety, 219, 108184. https://doi.org/10.1016/j.ress.2021.108184
  • Bonilla-Félix, M., & Suárez-Rivera, M. (2019). Disaster management in a nephrology service: Lessons learned from hurricane maria. Blood Purification, 47(1–3), 199–204. https://doi.org/10.1159/000494580
  • Bucar, R. C., & Hayeri, Y. M. (2020). Quantitative assessment of the impacts of disruptive precipitation on surface transportation. Reliability Engineering & System Safety, 203, 107105. https://doi.org/10.1016/j.ress.2020.107105
  • Chen, B. Y., Lam, W. H., Sumalee, A., Li, Q., & Li, Z. C. (2012). Vulnerability analysis for large-scale and congested road networks with demand uncertainty. Transportation Research Part A: Policy and Practice, 46, 501–516. https://doi.org/10.1016/j.tra.2011.11.018.
  • Climate Central. (2015). Delaware should do more to prepare for coastal flooding. Coastal Flooding, States at Risk: Delaware https://riskfinder.climatecentral.org/state/delaware.us?comparisonType=county&forecastType=NOAA2017_int_p50&level=5&unit=ft. Accessed 26 September, 2022.
  • CRED. (2018). Natural disasters in 2017: Lower mortality, higher cost. centre for research on the epidemiology of disasters, Brussels, Belgium. Research Institute Health Society (IRSS), Universite catholique de Louvain URL. https://cred.be/sites/default/files/CredCrunch50.pdf
  • Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2012). Social vulnerability to environmental hazards. In Cutter, S.L., (editor), Hazards vulnerability and environmental justice (pp. 143–160). Routledge.
  • Dehghani, M. S., Flintsch, G., & McNeil, S. (2014). Impact of road conditions and disruption uncertainties on network vulnerability. Journal of Infrastructure Systems, 20(3), 04014015. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000205
  • Delaware Sea Grant, (2022). Understanding flood risk: Help dealware communities prepare for storm flooding and sea level rise. https://www.deseagrant.org/flood-risk
  • Dong, S., Esmalian, A., Farahmand, H., & Mostafavi, A. (2020a). An integrated physical-social analysis of disrupted access to critical facilities and community service-loss tolerance in urban flooding. Computers, Environment and Urban Systems, 80, 101443. https://doi.org/10.1016/j.compenvurbsys.2019.101443
  • Dong, S., Gao, X., Mostafavi, A., & Gao, J. (2022). Modest flooding can trigger catastrophic road network collapse due to compound failure. Communications Earth & Environment, 3(1), 1–10. https://doi.org/10.1038/s43247-022-00366-0
  • Dong, S., Malecha, M., Farahmand, H., Mostafavi, A., Berke, P. R., & Woodruff, S. C. (2021). Integrated infrastructure-plan analysis for resilience enhancement of post-hazards access to critical facilities. Cities, 117, 103318. https://doi.org/10.1016/j.cities.2021.103318
  • Dong, S., Mostafizi, A., Wang, H., Gao, J., & Li, X. (2020b). Measuring the topological robustness of transportation networks to disaster-induced failures: A percolation approach. Journal of Infrastructure Systems, 26(2), 04020009. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000533
  • Dong, S., Wang, H., Mostafavi, A., & Gao, J. (2019). Robust component: A robustness measure that incorporates access to critical facilities under disruptions. Journal of the Royal Society Interface, 16(157), 20190149. https://doi.org/10.1098/rsif.2019.0149
  • Duan, Y., & Lu, F. (2014). Robustness of city road networks at different granularities. Physica A: Statistical Mechanics and Its Applications, 411, 21–34. https://doi.org/10.1016/j.physa.2014.05.073
  • Esmalian, A., Dong, S., Coleman, N., & Mostafavi, A. (2021a). Determinants of risk disparity due to infrastructure service losses in disasters: A household service gap model. Risk Analysis, 41(12), 2336–2355. https://doi.org/10.1111/risa.13738
  • Esmalian, A., Dong, S., & Mostafavi, A. (2021b). Susceptibility curves for humans: Empirical survival models for determining household-level disturbances from hazards-induced infrastructure service disruptions. Sustainable Cities and Society, 66, 102694. https://doi.org/10.1016/j.scs.2020.102694
  • Esparza, M., Esmalian, A., Dong, S., & Mostafavi, A. (2021). Examining spatial clusters for identifying risk hotspots of communities susceptible to flood-induced transportation disruptions. Computing in Civil Engineering, 482–489. https://doi.org/10.1061/9780784483893.060.
  • FEMA., (2022). Federal emergency management agency: Prioritizing mitigation actions for critical facilities. Risk Mapping, Assessment and Planning (Risk MAP) URL: https://www.fema.gov/sites/default/files/documents/fema_prioritizing-mitigation-actions_critical-facilities_region-three-06-2021.pdf
  • Feng, H., Bai, F., & Xu, Y. (2019). Identification of critical roads in urban transportation network based on gps trajectory data. Physica A: Statistical Mechanics and Its Applications, 535, 122337. https://doi.org/10.1016/j.physa.2019.122337
  • Fereshtehpour, M., Burian, S. J., & Karamouz, M. (2018). Flood risk assessments of transportation networks utilizing depth-disruption function, in: World Environmental and Water Resources Congress 2018: Water, Wastewater, and Stormwater; Urban Watershed Management. Municipal Water Infrastructure; and Desalination and Water Reuse. American Society of Civil Engineers Reston, VA
  • Flanagan, B. E., Gregory, E. W., Hallisey, E. J., Heitgerd, J. L., & Lewis, B. (2011). A social vulnerability index for disaster management. Journal of Homeland Security and Emergency Management, 8(1). https://doi.org/10.2202/1547-7355.1792
  • Gangwal, U., & Dong, S. (2022). Critical facility accessibility rapid failure early-warning detection and redundancy mapping in urban flooding. Reliability Engineering & System Safety, 224, 108555. https://doi.org/10.1016/j.ress.2022.108555
  • Gauthier, P., Furno, A., & El Faouzi, N. E. (2018). Road network resilience: How to identify critical links subject to day-to-day disruptions. Transportation Research Record, 2672(1), 54–65. https://doi.org/10.1177/0361198118792115
  • Geertman, S., Zhan, Q., Allan, A., & Pettit, C. (2019). Computational Urban Planning and Management for Smart Cities. Springer.
  • Hauer, M. E., Evans, J. M., & Mishra, D. R. (2016). Millions projected to be at risk from sea-level rise in the continental United States. Nature Climate Change, 6(7), 691–695. https://doi.org/10.1038/nclimate2961
  • Hauer, M. E., Hardy, D., Kulp, S. A., Mueller, V., Wrathall, D. J., & Clark, P. U. (2021). Assessing population exposure to coastal flooding due to sea level rise. Nature Communications, 12(1), 1–9. https://doi.org/10.1038/s41467-021-27260-1
  • Helderop, E., & Grubesic, T. H. (2019). Flood evacuation and rescue: The identification of critical road segments using whole-landscape features. Transportation Research Interdisciplinary Perspectives, 3, 100022. https://doi.org/10.1016/j.trip.2019.100022
  • Henning, S., Biemelt, P., Abdelgawad, K., Gausemeier, S., Evers, H. H., & Trächtler, A. (2017). Methodology for determining critical locations in road networks based on graph theory. IFAC- PapersOnLine, 50(1), 7487–7492. https://doi.org/10.1016/j.ifacol.2017.08.1065
  • He, Y., Thies, S., Avner, P., & Rentschler, J. (2021). Flood impacts on urban transit and accessibility—a case study of Kinshasa. Transportation Research Part D: Transport and Environment, 96, 102889. https://doi.org/10.1016/j.trd.2021.102889
  • HIFLD., (2022). Homeland infrastructure foundation-level data. URL: https://hifld-geoplatform.opendata.arcgis.com/
  • Howell, J., (2020). What does climate change look like in delaware?. Delaware Today. URL: https://delawaretoday.com/life-style/what-does-climate-change-look-like-in-delaware/.
  • Jafino, B. A., Kwakkel, J., & Verbraeck, A. (2020). Transport network criticality metrics: A comparative analysis and a guideline for selection. Transport Reviews, 40(2), 241–264. https://doi.org/10.1080/01441647.2019.1703843
  • Jasour, Z. Y., Reilly, A. C., Tonn, G. L., & Ferreira, C. M. (2022). Roadway flooding as a bellwether for household retreat in rural, coastal regions vulnerable to sea-level rise. Climate Risk Management, 36, 100425. https://doi.org/10.1016/j.crm.2022.100425
  • Jenelius, E., & Mattsson, L. G. (2015). Road network vulnerability analysis: Conceptualization, implementation and application. Computers, Environment and Urban Systems, 49, 136–147. https://doi.org/10.1016/j.compenvurbsys.2014.02.003
  • Kaiser, R., Karaye, I. M., Olokunlade, T., Hammond, T. A., Goldberg, D. W., & Horney, J. A. (2021). Hemodialysis clinics in flood zones: A case study of hurricane harvey. Prehospital and Disaster Medicine, 36(2), 135–140. https://doi.org/10.1017/S1049023X21000042
  • Kaviani, A., Thompson, R. G., & Rajabifard, A. (2017). Improving regional road network resilience by optimised traffic guidance. Transportmetrica A: Transport Science, 13(9), 794–828. https://doi.org/10.1080/23249935.2017.1335807
  • Kermanshah, A., & Derrible, S. (2017). Robustness of road systems to extreme flooding: Using elements of gis, travel demand, and network science. Natural Hazards, 86(1), 151–164. https://doi.org/10.1007/s11069-016-2678-1
  • Knighton, J., Hondula, K., Sharkus, C., Guzman, C., & Elliott, R., (2021). Flood risk behaviors of United States riverine metropolitan areas are driven by local hydrology and shaped by race. Proceedings of the National Academy of Sciences 118, e2016839118.
  • Koks, E. E., Rozenberg, J., Zorn, C., Tariverdi, M., Vousdoukas, M., Fraser, S., Hall, J., & Hallegatte, S. (2019). A global multi-hazard risk analysis of road and railway infrastructure assets. Nature Communications, 10(1), 1–11. https://doi.org/10.1038/s41467-019-10442-3
  • Lam, J. C., Heitzler, M., Hackl, J., Adey, B. T., & Hurni, L. (2020). Modelling the functional capacity losses of networks exposed to hazards. Sustainable and Resilient Infrastructure, 5(1–2), 30–48. https://doi.org/10.1080/23789689.2018.1469357
  • Li, F., Jia, H., Luo, Q., Li, Y., Yang, L., & Guo, Y. (2020). Identification of critical links in a large-scale road network considering the traffic flow betweenness index. PloS one, 15(4), e0227474. https://doi.org/10.1371/journal.pone.0227474
  • Liu, Y., McNeil, S., Hackl, J., & Adey, B. T. (2022b). Prioritizing transportation network recovery using a resilience measure. Sustainable and Resilient Infrastructure, 7(1), 70–81. https://doi.org/10.1080/23789689.2019.1708180
  • Liu, K., Zhai, C., Dong, Y., & Meng, X. (2022a). Post-earthquake functionality assessment of urban road network considering emergency response. Journal of Earthquake Engineering, 1–26. https://doi.org/10.1080/13632469.2022.2113001.
  • Li, X., & Willems, P. (2020). A hybrid model for fast and probabilistic urban pluvial flood prediction. Water Resources Research, 56(6), e2019WR025128. https://doi.org/10.1029/2019WR025128
  • Logan, T., Anderson, M., & Reilly, A., (2022). Isolation: Revising the estimated risk of sea-level rise. https://doi.org/10.21203/rs.3.rs-1523232/v1.
  • Logan, T. M., & Guikema, S. D. (2020). Reframing resilience: Equitable access to essential services. Risk Analysis, 40(8), 1538–1553. https://doi.org/10.1111/risa.13492
  • Luathep, P., Sumalee, A., Ho, H., & Kurauchi, F. (2011). Large-scale road network vulnerability analysis: A sensitivity analysis based approach. Transportation, 38(5), 799–817. https://doi.org/10.1007/s11116-011-9350-0
  • Maldonado, A., Collins, T. W., & Grineski, S. E. (2016). Hispanic immigrants’ vulnerabilities to flood and hurricane hazards in two United States metropolitan areas. Geographical Review, 106(1), 109–135. https://doi.org/10.1111/j.1931-0846.2015.12103.x
  • Martinich, J., Neumann, J., Ludwig, L., & Jantarasami, L. (2013). Risks of sea level rise to disadvantaged communities in the United States. Mitigation and Adaptation Strategies for Global Change, 18(2), 169–185. https://doi.org/10.1007/s11027-011-9356-0
  • Meerow, S., Pajouhesh, P., & Miller, T. R. (2019). Social equity in urban resilience planning. Local Environment, 24(9), 793–808. https://doi.org/10.1080/13549839.2019.1645103
  • Merschman, E., Doustmohammadi, M., Salman, A. M., & Anderson, M. (2020). Postdisaster decision framework for bridge repair prioritization to improve road network resilience. Transportation Research Record, 2674(3), 81–92. https://doi.org/10.1177/0361198120908870
  • Mishra, S., Welch, T. F., & Jha, M. K. (2012). Performance indicators for public transit connectivity in multi-modal transportation networks. Transportation Research Part A: Policy and Practice, 46, 1066–1085. https://doi.org/10.1016/j.tra.2012.04.006.
  • Mobley, W., Sebastian, A., Blessing, R., Highfield, W. E., Stearns, L., & Brody, S. D. (2021). Quantification of continuous flood hazard using random forest classification and flood insurance claims at large spatial scales: A pilot study in southeast Texas. Natural Hazards and Earth System Sciences, 21(2), 807–822. https://doi.org/10.5194/nhess-21-807-2021
  • Morelli, A. B., & Cunha, A. L. (2021). Measuring urban road network vulnerability to extreme events: An application for urban floods. Transportation Research Part D: Transport and Environment, 93, 102770. https://doi.org/10.1016/j.trd.2021.102770
  • Mostafavi, A. (2018). A system-of-systems framework for exploratory analysis of climate change impacts on civil infrastructure resilience. Sustainable and Resilient Infrastructure, 3(4), 175–192. https://doi.org/10.1080/23789689.2017.1416845
  • Mostafizi, A., Wang, H., Cox, D., Cramer, L. A., & Dong, S. (2017). Agent-based tsunami evacuation modeling of unplanned network disruptions for evidence-driven resource allocation and retrofitting strategies. Natural Hazards, 88(3), 1347–1372. https://doi.org/10.1007/s11069-017-2927-y
  • Nagenborg, M. (2019). Urban resilience and distributive justice. Sustainable and Resilient Infrastructure, 4(3), 103–111. https://doi.org/10.1080/23789689.2019.1607658
  • NASEM. (2022). National Academies of Sciences, Engineering, and Medicine: Equitable and resilient infrastructure investment. https://doi.org/10.17226/26633.
  • NCEI., (2019). NOAA national centers for environmental information (NCEI) U.S. billion-dollar weather and climate disasters URL: https://www.ncei.noaa.gov/access/billions/
  • Nofal, O. M., & van de Lindt, J. W. (2021). High-resolution flood risk approach to quantify the impact of policy change on flood losses at community-level. International Journal of Disaster Risk Reduction, 62, 102429. https://doi.org/10.1016/j.ijdrr.2021.102429
  • Nofal, O. M., & Van De Lindt, J. W. (2022). Understanding flood risk in the context of community resilience modeling for the built environment: Research needs and trends. Sustainable and Resilient Infrastructure, 7(3), 171–187. https://doi.org/10.1080/23789689.2020.1722546
  • Novak, D. C., & Sullivan, J. L. (2014). A link-focused methodology for evaluating accessibility to emergency services. Decision Support Systems, 57, 309–319. https://doi.org/10.1016/j.dss.2013.09.015
  • Papilloud, T., & Keiler, M. (2021). Vulnerability patterns of road network to extreme floods based on accessibility measures. Transportation Research Part D: Transport and Environment, 100, 103045. https://doi.org/10.1016/j.trd.2021.103045
  • Pregnolato, M., Ford, A., Wilkinson, S. M., & Dawson, R. J. (2017). The impact of flooding on road transport: A depth-disruption function. Transportation Research Part D: Transport and Environment, 55, 67–81. https://doi.org/10.1016/j.trd.2017.06.020
  • Pyatkova, K., Chen, A. S., Djordjević, S., Butler, D., Vojinović, Z., Abebe, Y. A., & Hammond, M. (2019). Flood impacts on road transportation using microscopic traffic modelling techniques. In Behrisch, M., Weber, M., (eds.), Simulating urban traffic scenarios (pp. 115–126). Springer.
  • Ramirez-Rios, D., Wallace, W. A., Kinsler, J., Viota, N. M., & Mendez, P. (2022). Exploring post- disaster transportation barriers to healthcare of socially vulnerable Puerto Rican communities. Natural Hazards Center, University of Colorado Boulder.
  • Singh, P., Sinha, V. S. P., Vijhani, A., & Pahuja, N. (2018). Vulnerability assessment of urban road network from urban flood. International Journal of Disaster Risk Reduction, 28, 237–250. https://doi.org/10.1016/j.ijdrr.2018.03.017
  • Snelder, M., Van Zuylen, H., & Immers, L. (2012). A framework for robustness analysis of road networks for short term variations in supply. Transportation Research Part A: Policy and Practice, 46, 828–842. https://doi.org/10.1016/j.tra.2012.02.007.
  • Sohn, J. (2006). Evaluating the significance of highway network links under the flood damage: An accessibility approach. Transportation Research Part A: Policy and Practice 40, 491–506. https://doi.org/10.1016/j.tra.2005.08.006.
  • Sohouenou, P. Y., & Neves, L. A. (2021). Assessing the effects of link-repair sequences on road network resilience. International Journal of Critical Infrastructure Protection, 34, 100448. https://doi.org/10.1016/j.ijcip.2021.100448
  • Sweet, W., Hamlington, B., Kopp, R., Weaver, C., Barnard, P., Bekaert, D., Brooks, W., Craghan, M., Dusek, G., Frederikse, T., Garner, G, Genz, A., Krasting, J., Larour, E., Marcy, D., Marra, J., Obeysekera, J., Osler, M., Pendleton, M., Roman, D., Schmied, L., Veatch, W., White, K., & Zuzak, C . (2022). Global and regional sea level rise scenarios for the United States: Updated mean projections and extreme water level probabilities along US coastlines. Technical Report. NOAA Technical Report. https://doi.org/10.1016/j.tra.2005.08.006.
  • Thompson, C. A. (2017). Special patient populations needed special attention during hurricane. American Journal of health-system Pharmacy, 74(22), 1841–1843. https://doi.org/10.2146/news170077
  • Twumasi-Boakye, R., & Sobanjo, J. O. (2021). A computational approach for evaluating post-disaster transportation network resilience. Sustainable and Resilient Infrastructure, 6(3–4), 235–251. https://doi.org/10.1080/23789689.2019.1605754
  • Ulusan, A.& Ergun, O. . (2018). Restoration of services in disrupted infrastructure systems: A network science approach. PloS one, 13(2), e0192272. https://doi.org/10.1371/journal.pone.0192272
  • USGS., (2022). U.S. Geological Survey: Floods and recurrent intervals. https://www.usgs.gov/special-topics/water-science-school/science/floods-and-recurrence-intervals accessed on 08 January 2022
  • Wang, J., Ding, Z., Zou, L., & Zuo, J., (2013). Proceedings of the 17th International Symposium on Advancement of Construction Management and Real Estate. Springer Science & Business Media.
  • Wang, W., Yang, S., Stanley, H. E., Gao, J., Zeller, S., Voigtsberger, J., Schlott, N., Henrichs, K., Sann, H., Trinter, F., Schmidt, L. P. H., Kalinin, A., Schöffler, M. S., Jahnke, T., Lein, M., & Dörner, R. (2019). Local floods induce large-scale abrupt failures of road networks. Nature Communications, 10(1), 1–11. https://doi.org/10.1038/s41467-018-07882-8
  • Weiss, D., Nelson, A., Vargas-Ruiz, C., Gligorić, K., Bavadekar, S., Gabrilovich, E., Bertozzi-Villa, A., Rozier, J., Gibson, H., Shekel, T., Kamath, C., Lieber, A., Schulman, K., Shao, Y., Qarkaxhija, V., Nandi, A. K., Keddie, S. H., Rumisha, S., Amratia, P., … Gething, P. W. (2020). Global maps of travel time to healthcare facilities. Nature Medicine, 26(12), 1835–1838. https://doi.org/10.1038/s41591-020-1059-1
  • Wiśniewski, S., Borowska-Stefańska, M., Kowalski, M., & Sapińska, P. (2020). Vulnerability of the accessibility to grocery shopping in the event of flooding. Transportation Research Part D: Transport and Environment, 87, 102510. https://doi.org/10.1016/j.trd.2020.102510
  • Wu, J., & Wang, P. (2021). Post-disruption performance recovery to enhance resilience of interconnected network systems. Sustainable and Resilient Infrastructure, 6(1–2), 107–123. https://doi.org/10.1080/23789689.2019.1710073
  • Yin, J., Yu, D., Yin, Z., Liu, M., & He, Q. (2016). Evaluating the impact and risk of pluvial flash flood on intra-urban road network: A case study in the city center of shanghai, China. Journal of Hydrology, 537, 138–145. https://doi.org/10.1016/j.jhydrol.2016.03.037
  • Young, C. E., Cunniff, S. E., & McDow, W. C. (2021). Evaluating and tracking investments in natural infrastructure to reduce coastal flooding hazards. Sustainable and Resilient Infrastructure, 1–18. https://doi.org/10.1080/23789689.2021.1920662.
  • Yuan, F., Fan, C., Farahmand, H., Coleman, N., Esmalian, A., Lee, C. C., Patrascu, F. I., Zhang, C., Dong, S., & Mostafavi, A. (2022). Smart flood resilience: Harnessing community-scale big data for predictive flood risk monitoring, rapid impact assessment, and situational awareness. Environmental Research: Infrastructure and Sustainability, 2, 025006. https://doi.org/10.1088/2634-4505/ac7251.
  • Zhang, N., & Alipour, A. (2019). Integrated framework for risk and resilience assessment of the road network under inland flooding. Transportation Research Record, 2673(12), 182–190. https://doi.org/10.1177/0361198119855975
  • Zhou, Y., Fang, Z., Thill, J. C., Li, Q., & Li, Y. (2015). Functionally critical locations in an urban transportation network: Identification and space–time analysis using taxi trajectories. Computers, Environment and Urban Systems, 52, 34–47. https://doi.org/10.1016/j.compenvurbsys.2015.03.001