Abstract
The recurrence of extreme weather events has led to the development of methods for assessing the vulnerability and interdependencies of physical and human systems. A case example is Hurricane Maria (H-Maria), where Puerto Rico experienced damage to 80% of its electrical power system, leading to massive disruptions of essential services for months. Here we evaluate the effectiveness of various interventions aimed at reducing vulnerability by considering power and water infrastructure and respective water–power dependencies while also considering the social vulnerability of affected communities associated with the physical infrastructure upgrades. On the basis of the current infrastructure configuration, we found that all communities suffered enormously from power and water outages. As one upgrade option, we show that incorporating regional energy grids would reduce outages in an H-Maria scenario. However, a large portion of disadvantaged communities will face service disruption under this option. In contrast, hardening transmission lines, as the second option, would improve service delivery and, most importantly, provide uninterrupted service to the higher portion of the vulnerable population.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 /Â 30Â days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Data availability
The datasets generated and/or analysed during the current study are available in the Zenodo repository https://doi.org/10.5281/zenodo.7388021.
References
Bennett, J. A. et al. Extending energy system modelling to include extreme weather risks and application to hurricane events in Puerto Rico. Nat. Energy 6, 240–249 (2021).
Yates, D. et al. Stormy weather: assessing climate change hazards to electric power infrastructure: a Sandy case study. IEEE Power Energy Mag. 12, 66–75 (2014).
Schmeltz, M. T. et al. Lessons from Hurricane Sandy: a community response in Brooklyn, New York. J. Urban Health 90, 799–809 (2013).
Pasch, R. J., Penny, A. B. & Berg, R. National Hurricane Center Tropical Cyclone Report Hurricane Maria (AL152017) 16–30 September 2017. National Hurricane Center (2019).
Birk Jones, C., Bresloff, C. J., Darbali-Zamora, R., Lave, M. & Aponte Bezares, E. E. Geospatial assessment methodology to estimate power line restoration access vulnerabilities after a hurricane in Puerto Rico. IEEE Open Access J. Power Energy https://doi.org/10.1109/OAJPE.2022.3191954 (2022).
Lu, D. & Alcantara, C. After Hurricane Maria, Puerto Rico was in the dark for 181 days, 6 hours and 45 minutes. The Washington Post. April 4, 2018 (2018).
Mahzarnia, M., Moghaddam, M. P., Baboli, P. T. & Siano, P. A review of the measures to enhance power systems resilience. IEEE Syst. J. 14, 4059–4070 (2020).
Panteli, M., Trakas, D. N., Mancarella, P. & Hatziargyriou, N. D. Power systems resilience assessment: hardening and smart operational enhancement strategies. Proc. IEEE 105, 1202–1213 (2017).
Bagheri, A., Zhao, C., Qiu, F. & Wang, J. Resilient transmission hardening planning in a high renewable penetration era. IEEE Trans. Power Syst. 34, 873–882 (2019).
Elizondo, M. A. et al. Risk-Based Dynamic Contingency Analysis Applied to Puerto Rico Electric Infrastructure (US Department of Energy, 2020); https://doi.org/10.2172/1771798
Boyle, E. et al. Social vulnerability and power loss mitigation: a case study of Puerto Rico. SSRN Electron. J. https://doi.org/10.2139/SSRN.3838896 (2021).
Kwasinski, A., Andrade, F., Castro-Sitiriche, M. J. & O’Neill-Carrillo, E. Hurricane Maria effects on Puerto Rico electric power infrastructure. IEEE Power Energy Technol. Syst. J. 6, 85–94 (2019).
O’Neill-Carrillo, E. & Irizarry-Rivera, A. How to harden Puerto Rico’s grid against hurricanes. IEEE Spectr. 56, 42–48 (2019).
Siddiqi, A., Kajenthira, A. & Anadón, L. D. Bridging decision networks for integrated water and energy planning. Energy Strategy Rev. 2, 46–58 (2013).
Roni, M. S. et al. Integrated water–power system resiliency quantification, challenge and opportunity. Energy Strategy Rev. 39, 100796 (2022).
Zuloaga, S. & Vittal, V. Integrated electric power/water distribution system modeling and control under extreme mega drought scenarios. IEEE Trans. Power Syst. 36, 474–484 (2021).
Pant, R., Thacker, S., Hall, J. W., Alderson, D. & Barr, S. Critical infrastructure impact assessment due to flood exposure. J. Flood Risk Manage. 11, 22–33 (2018).
Dargin, J., Berk, A. & Mostafavi, A. Assessment of household-level food–energy–water nexus vulnerability during disasters. Sustainable Cities Soc. 62, 102366 (2020).
Flanagan, B. E., Gregory, E. W., Hallisey, E. J., Heitgerd, J. L. & Lewis, B. A social vulnerability index for disaster management. J. Homeland Secur. Emerg. Manage. 8, 1–8 (2011).
Cutter, S. L., Mitchell, J. T. & Scott, M. S. Revealing the vulnerability of people and places: a case study of Georgetown County, South Carolina. Ann. Assoc. Am. Geogr. 90, 713–737 (2000).
Emrich, C. T. & Cutter, S. L. Social vulnerability to climate-sensitive hazards in the Southern United States. Weather Clim. Soc. 3, 193–208 (2011).
Blaikie, P., Cannon, T., Davis, I. & Wisner, B. At risk: natural hazards, people’s vulnerability and disasters. Risk https://doi.org/10.4324/9780203974575 (2005).
West, J., Riosmena, F. & Thomas, K. Comparing social vulnerability and population loss in Puerto Rico after Hurricane Maria. M.A. thesis, University of Colorado Boulder. 1–5 (2022).
Wood, E., Sanders, M. & Frazier, T. The practical use of social vulnerability indicators in disaster management. Int. J. Disaster Risk Reduct. 63, 102464 (2021).
Bergstrand, K., Mayer, B., Brumback, B. & Zhang, Y. Assessing the relationship between social vulnerability and community resilience to hazards. Social Indic. Res. 122, 391–409 (2015).
Spielman, S. E. et al. Evaluating social vulnerability indicators: criteria and their application to the Social Vulnerability Index. Nat. Hazards 100, 417–436 (2020).
Montoya-Rincon, J. P., Gonzalez, J. E. & Jensen, M. P. Evaluation of Transmission Line Hardening Scenarios using a Machine Learning Approach. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B: Mechanical Engineering https://doi.org/10.1115/1.4063012 (2023).
Carvalhaes, T. et al. A simulation framework for service loss of power networks under extreme weather events: a case of Puerto Rico. In IEEE International Conference on Automation Science and Engineering 1532–1537 https://doi.org/10.1109/CASE48305.2020.9216849 (2020).
Román, M. O. et al. NASA’s Black Marble nighttime lights product suite. Remote Sens. Environ. https://doi.org/10.1016/j.rse.2018.03.017 (2018).
Montoya-Rincon, J. P. et al. On the use of satellite nightlights for power outages prediction. IEEE Access 10, 16729–16739 (2022).
Román, M. O. et al. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS ONE 14, e0218883 (2019).
Azad, S. & Ghandehari, M. A study on the association of socioeconomic and physical cofactors contributing to power restoration after Hurricane Maria. IEEE Access 9, 98654–98664 (2021).
Wang, Z. et al. Monitoring disaster-related power outages using NASA Black Marble nighttime light product. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 42, 1853–1856 (2018).
Innovyze Store InfoWater (Innovyze Store, 2021); https://store.innovyze.com/WaterDistribution/InfoWater?cclcl=en_US
Manrique, S. A. M., Harmsen, E. W., Khanbilvardi, R. M. & González, J. E. Flood impacts on critical infrastructure in a coastal floodplain in western Puerto Rico during Hurricane MarÃa. Hydrology 8, 104 (2021).
US Army Corps of Engineers Gridded Surface Subsurface Hydrologic Analysis (US Army Corps of Engineers, 2022); https://www.erdc.usace.army.mil/Media/Fact-Sheets/Fact-Sheet-Article-View/Article/476714/gridded-surface-subsurface-hydrologic-analysis/#:~%7B%7D:text=GSSHA
Giovanni-Prieto, M. Development of a Regional Integrated Hydrologic Model for a Tropical Watershed. MSc thesis, Univ. of Puerto Rico, Mayaguez Campus (2007).
Rojas-González, A. M. Flood Prediction Limitations in Small Watersheds with Mountains Terrain and High Rainfall Variability. Ph.D dissertation, Univ. of Puerto Rico, Mayaguez Campus (2012).
Silva-Araya, W. F., Santiago-Collazo, F. L., Gonzalez-Lopez, J. & Maldonado-Maldonado, J. Dynamic modeling of surface runoff and storm surge during hurricane and tropical storm events. Hydrology 5, 13 (2018).
Moriasi, D. N., Gitau, M. W., Pai, N. & Daggupati, P. Hydrologic and water quality models: performance measures and evaluation criteria. Trans. ASABE 58, 1763–1785 (2015).
Yuan, H., Zhang, W., Zhu, J. & Bagtzoglou, A. C. Resilience assessment of overhead power distribution systems under strong winds for hardening prioritization. ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A Civ. Eng. 4, 04018037 (2018).
Salman, A. M., Li, Y. & Stewart, M. G. Evaluating system reliability and targeted hardening strategies of power distribution systems subjected to hurricanes. Reliab. Eng. Syst. Saf. 144, 319–333 (2015).
Wang, Y., Rousis, A. O. & Strbac, G. On microgrids and resilience: a comprehensive review on modeling and operational strategies. Renew. Sustain. Energy Rev. 134, 110313 (2020).
Aros-Vera, F., Gillian, S., Rehmar, A. & Rehmar, L. Increasing the resilience of critical infrastructure networks through the strategic location of microgrids: a case study of Hurricane Maria in Puerto Rico. Int. J. Disaster Risk Reduct. 55, 102055 (2021).
Puerto Rico Integrated Resource Plan 2018-2019 Vol. 1 (Siemens Industry, 2019); https://energia.pr.gov/wp-content/uploads/sites/7/2019/06/2-IRP2019-Main-Report-REV2-06072019.pdf
Zamzam, A. S., Dall’Anese, E., Zhao, C., Taylor, J. A. & Sidiropoulos, N. D. Optimal water–power flow-problem: formulation and distributed optimal solution. IEEE Trans. Control Network Syst. 6, 37–47 (2019).
Shinozuka, M. et al. Resilience of integrated power and water systems. Seism. Eval. Retrofit Lifeline Syst. 65, 65–86 (2003).
Dugan, J., Byles, D. & Mohagheghi, S. Social vulnerability to long-duration power outages. Int. J. Disaster Risk Reduct. 85, 103501 (2023).
Tarling, H. A. Comparative Analysis of Social Vulnerability Indices: CDC’s SVI and SoVI. Division of Risk Management and Societal Safety, Lund University (2017).
Cutter, S. L., Boruff, B. J. & Shirley, W. L. Social vulnerability to environmental hazards*. Social Sci. Q. 84, 242–261 (2003).
Carvalhaes, T. et al. Integrating spatial and ethnographic methods for resilience research: a thick mapping approach for Hurricane Maria in Puerto Rico. Ann. Am. Assoc. Geogr. https://doi.org/10.1080/24694452.2022.2071200 (2022).
Chakalian, P. M., Kurtz, L. C. & Hondula, D. M. After the lights go out: household resilience to electrical grid failure following Hurricane Irma. Nat. Hazards Rev. 20, 05019001 (2019).
Puerto Ricans at risk of waterborne disease outbreaks in wake of Hurricane Maria. CBS News. Oct 25, 2017 (2017).
Breiman, L. Random forests. Mach. Learn. https://doi.org/10.1023/A:1010933404324 (2001).
Pokhrel, R., Cos del, S., Montoya Rincon, J. P., Glenn, E. & González, J. E. Observation and modeling of Hurricane Maria for damage assessment. Weather Clim. Extremes https://doi.org/10.1016/j.wace.2021.100331 (2021).
Skahill, B. E., Charles, D. W. & Bagget, J. S. A Practical Guide to Calibration of a GSSHA Hydrologic Model Using ERDC Automated Model Calibration Software – Effective and Efficient Stochastic Global Optimization. U.S. Army Engineer Research and Development Center (2012).
2014–2018 ACS 5-year Estimates (US Census Bureau, 2018); https://www.census.gov/programs-surveys/acs/technical-documentation/table-and-geography-changes/2018/5-year.html
OpenStreetMap contributors. Planet Dump. OpenStreetMap (2017).
Tormos-Aponte, F., GarcÃa-López, G. & Painter, M. A. Energy inequality and clientelism in the wake of disasters: from colorblind to affirmative power restoration. Energy Policy 158, 112550 (2021).
Acknowledgements
The authors gratefully acknowledge the financial support received by the US National Science Foundation under grant CBET-1832678, the National Science Foundation Program for Critical Resilient Interdependent Infrastructure Systems and Processes titled ‘Integrated Socio-Technical Modeling Framework to Evaluate and Enhance Resiliency in Islanded Communities’ under award 1832678.
Author information
Authors and Affiliations
Contributions
J.P.M.-R.: data collection, formal analysis, writing, review and editing. S.A.M.-M.: data collection, formal analysis, writing, review and editing. S.A.: data collection, formal analysis, writing, review and editing. M.G.: funding acquisition, review and editing. E.W.H.: funding acquisition, review and editing. R.K.: funding acquisition and review. J.E.G.-C.: funding acquisition, project lead, review and editing.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Energy thanks the anonymous reviewers for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Montoya-Rincon, J.P., Mejia-Manrique, S.A., Azad, S. et al. A socio-technical approach for the assessment of critical infrastructure system vulnerability in extreme weather events. Nat Energy 8, 1002–1012 (2023). https://doi.org/10.1038/s41560-023-01315-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41560-023-01315-7