Assessment of building recovery functions for local and global resilience assessment to tsunamis

Abstract

Resilience of residential buildings depends on the recovery process that follows the impact of natural hazards, such as tsunamis. In particular, the historical database from tsunamis that occurred in different Countries (Sri Lanka, Thailand, Indonesia, and Japan) have been considered. This study proposes a selection of the best-fitting models to assess the recovery process of tsunamis to derive a framework for resilience at geographical scales. Since the damage depends on the vulnerability of the buildings, several typologies have been considered. In addition, aggregations of different damage sources have been considered to propose comprehensive relationships. The definition of best-fitting recovery functions for different countries has been discussed to implement them in advanced platforms and calculate the resilience to tsunamis.

Keywords

Recovery / Residential buildings / Resilience / Tsunamis

Relevance to resilience

The paper contributes to resilience by proposing best-fitting models for use in specific recovery modelling after tsunamis. Data collected from different national databases for different typologies (permanent and transitional housing) of residential buildings were considered for Sri Lanka, Indonesia, Thailand, and Japan. The paper considers that among the different two-parameter trial recovery functions, logistic distribution performs well at a national scale, while a logarithmic function performs better at the city scale. Three-parameter trial recovery functions performed well for both national and city scales. In general, use of the general Pareto distribution is suggested to model recovery, if defining three parameter is feasible.

CRediT authorship contribution statement

Sabarethinam Kameshwar: Writing - original draft, Software, Investigation, Formal analysis, Data curation. Davide Forcellini: Writing - review & editing, Data curation, Conceptualization. Andre R. Barbosa: Writing - review & editing, Supervision, Methodology.

Declaration of competing interest

The authors Sabarethinam Kameshwar, Davide Forcellini, Andre R. Barbosa state that there are no conflicts of interest with the material proposed in the submitted paper titled “Assessment of recovery functions for local and global resilience assessment to tsunamis”. If you need to contact me, please use the above address or contact me via e-mail at [e-mail].

Acknowledgements

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

References

[1] The Indian Ocean tsunami: socio-economic impacts in Thailand on JSTOR. https://www.jstor.org/stable/3451210?seq=1.

[2] Athukorala P, Resosudarmo BP. The Indian Ocean tsunami: economic impact, disaster management, and lessons. Asian econ pap 2005; 4(1):1-39.

[3] Rodriguez H, Wachtendorf T, Kendra J, Trainor J.A snapshot of the 2004 Indian Ocean tsunami: societal impacts and consequences. Disaster Prev Manag: Int J 2006; 15(1):163-77.

[4] Wachtendorf T, Kendra JM, Rodríguez H, Trainor J. The social impacts and consequences of the December 2004 Indian ocean tsunami: observations from India and Sri Lanka. Earthq Spectra 2006; 22(3_suppl):693-714.

[5] Heger MP, Neumayer E. The impact of the Indian Ocean tsunami on Aceh’s longterm economic growth. J Dev Econ 2019;141:102365. https://doi.org/10.1016/j.jdeveco.2019.06.008.

[6] Mimura N, Yasuhara K, Kawagoe S, Yokoki H, Kazama S. Damage from the Great East Japan Earthquake and Tsunami-a quick report. Mitig adapt strateg glob change 2011;16:803-18.

[7] Suppasri A, Shuto N, Imamura F, Koshimura S, Mas E, Yalciner AC.Lessons learned from the 2011 Great East Japan tsunami: performance of tsunami countermeasures, coastal buildings, and tsunami evacuation in Japan. Pure Appl Geophys 2013;170:993-1018.

[8] Fraser S, Raby A, Pomonis A, Goda K, Chian SC, Macabuag J, Offord M, Saito K, Sammonds P. Tsunami damage to coastal defences and buildings in the March 11th 2011 M w 9.0 Great East Japan earthquake and tsunami. Bull earthq eng 2013;11: 205-39.

[9] Oregon Seismic Safety Policy Advisory Commission (2013) The Oregon resilience plan: reducing risk and improving recovery for the next Cascadia earthquake and tsunami.

[10] Washington’s Climate Resilience Strategy - Washington State Department of Ecology. https://ecology.wa.gov/air-climate/responding-to-climate-change/washingtons-climate-strategy.

[11] Building climate resilience. https://resources.ca.gov/initiatives/building-climate-resilience.

[12] Berkeley AR, Wallace M, Coo C. A framework for establishing critical infrastructure resilience goals. Final rep recomm counc natl infrastruct advis counc 2010;26.

[13] Kameshwar S, Cox DT, Barbosa AR, Farokhnia K, Park H, Alam MS, de Lindt JW van. Probabilistic decision-support framework for community resilience: incorporating multi-hazards, infrastructure interdependencies, and resilience goals in a Bayesian network. Reliab Eng Syst Saf 2019;191:106568.

[14] Chen M. (2021) Assessing Hawaiian climate resilience plans on flood management.

[15] Wildavsky A. (2017) Searching for safety. https://doi.org/10.4324/9781351316248.

[16] Holling CS, Schindler DW, Walker BW, Roughgarden J. Biodiversity in the functioning of ecosystems: an ecological synthesis. Biodivers Loss: Econ Ecol Issues 1995:44-83. https://doi.org/10.1017/CBO9781139174329.005.

[17] Home III JF, JE Orr. Assessing behaviors that create resilient organizations. Employ Relat Today 1997; 24(4):29-39. https://doi.org/10.1002/ert.3910240405.

[18] Mallak LA. Measuring resilience in health care provider organizations. Health Manpow Manage 1998; 24(4):148-52.

[19] A framework to quantitatively assess and enhance the seismic resilience of communities - Michel Bruneau, Stephanie E. Chang, Ronald T. Eguchi, George C. Lee, Thomas D. O’Rourke, Andrei M. Reinhorn, Masanobu Shinozuka, Kathleen Tierney, William A. Wallace, Detlof von Winterfeldt, 2003. https://journals.sagepub.com/doi/10.1193/1.1623497.

[20] Chang SE, Shinozuka M. Measuring improvements in the disaster resilience of communities. Earthq Spectra 2004; 20(3):739-55. https://doi.org/10.1193/1.1775796.

[21] Karakoc DB, Almoghathawi Y, Barker K, Gonz´alez AD, Mohebbi S.Community resilience-driven restoration model for interdependent infrastructure networks. Int J Disaster Risk Reduct 2019;38:101228. https://doi.org/10.1016/j.ijdrr.2019.101228.

[22] Wachter RF, Forcellini D, Warnell JMcManus, Walsh KQ. Relationship between coastal hazard countermeasures and community resilience in the T¯ohoku Region of Japan following the 2011 tsunami. Nat Hazards Rev 2023; 24(2):04023017. https://doi.org/10.1061/NHREFO.NHENG-1401.

[23] van de Lindt JW, Kruse J, Cox DT, Gardoni P, Lee JS, Padgett J, McAllister TP, Barbosa A, Cutler H, Van Zandt S. The interdependent networked community resilience modeling environment (IN-CORE). Resilient Cities Struct 2023; 2(2): 57-66.

[24] Cimellaro GP, Reinhorn AM, Bruneau M. Framework for analytical quantification of disaster resilience. Eng Struct 2010; 32(11):3639-49. https://doi.org/10.1016/j.engstruct.2010.08.008.

[25] Shinozuka M, Rose A, Eguchi RT.Engineering and socioeconomic impacts of earthquakes. Buffalo: MCEER; 1998.

[26] Reed DA, Powell MD, Westerman JM. Energy supply system performance for Hurricane Katrina. J Energy Eng 2010; 136(4):95-102. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000028.

[27] Shen L, Tang L. A resilience assessment framework for critical infrastructure systems. In: 2015 First International Conference on Reliability Systems Engineering (ICRSE); 2015. p. 1-5. https://doi.org/10.1109/ICRSE.2015.7366435.

[28] Bocchini P., Dec`o A., Frangopol D.M. (2012) Probabilistic functionality recovery model for resilience analysis. Bridge maintenance, safety, management, resilience and sustainability, :1920-7. https://doi.org/10.1201/b12352-283.

[29] Dec`o A, Bocchini P, Frangopol DM. A probabilistic approach for the prediction of seismic resilience of bridges. Earthq Eng Struct Dyn 2013; 42(10):1469-87. https://doi.org/10.1002/eqe.2282.

[30] Bocchini P, Frangopol DM. Restoration of bridge networks after an earthquake: multicriteria intervention optimization. Earthq Spectra 2012; 28(2):426-55.

[31] Chandrasekaran S, Banerjee S. Retrofit optimization for resilience enhancement of bridges under multihazard scenario. J Struct Eng 2016:C4015012. https://doi.org/10.1061/(asce)st.1943-541x.0001396.

[32] Mina D, Karampour H, Forcellini D. Resilience of HP/HT pipelines to combined seismic and thermal loadings. Ocean Eng 2023;275:114098.

[33] Forcellini D. Quantification of the seismic resilience of bridge classes. J Infrastruct Syst 2024; 30(3):04024016. https://doi.org/10.1061/JITSE4.ISENG-2376.

[34] Mata R, Nu˜nez E, Forcellini D. Seismic resilience of composite moment frames buildings with slender built-up columns. J Build Eng 2025;111:113532. https://doi.org/10.1016/j.jobe.2025.113532.ring.25:103834.

[35] Moselhi O, Gong D, El-Rayes K. Estimating weather impact on the duration of construction activities. Can J Civ Eng 1997; 24(3):359-66.

[36] Sharma N, Tabandeh A, Gardoni P. Resilience analysis: a mathematical formulation to model resilience of engineering systems. Sustain Resilient Infrastruct 2018; 3(2):49-67.

[37] Gidaris I, Padgett JE, Barbosa AR, Chen S, Cox D, Webb B, Cerato A. Multiple- hazard fragility and restoration models of highway bridges for regional risk and resilience assessment in the United States: state-of-the-art review. J struct eng 2017; 143(3):04016188.

[38] Cimellaro GP, Reinhorn AM, Bruneau M. Seismic resilience of a hospital system. Struct Infrastruct Eng 2010; 6(1-2):127-44.

[39] Murao O. Post-tsunami Urban recovery process and current conditions in Sri Lanka, Thailand, and Indonesia. Recovery Indian Ocean Tsunami: Ten-Year Journey 2015: 73-88. https://doi.org/10.1007/978-4-431-55117-1_6.

[40] Murao O, Nakazato H. Recovery curves for housing reconstruction in sri lanka after the 2004 indian ocean tsunami. J Earthq Tsunami 2010; 04(02):51-60. https://doi.org/10.1142/S1793431110000765.

[41] Sugiyasu K., Murao O. (2010) Comparative analysis of the reconstruction process of urban facilities in indonesia based on recovery curves after the 2004 indian ocean tsunami.

[42] Gillespie TW, Frankenberg E, Fung Chum K, Thomas D. Night-time lights time series of tsunami damage, recovery, and economic metrics in Sumatra, Indonesia. Remote Sens Lett 2014; 5(3):286-94. https://doi.org/10.1080/2150704X.2014.900205.

[43] Hokugo A, Kaneko Y, Honjo Y, Toyoda T, Shiomi Y, Pinheiro ATK, Ghezelloo Y. Resident questionnaire survey on the lives and livelihoods recovery in the devastated area after ten years from the Great East Japan Earthquake and Tsunami: overall results review. Recovery Disaster Vict: Results Jt Surv East Jpn Aceh Sichuan Tacloban 2023:29-114.

[44] Liew S.C., Gupta A., Wong P.P., Kwoh L.K. (2010) Recovery from a large tsunami mapped over time: the Aceh coast, Sumatra. Geomorphology, 114(4):520-9. https://doi.org/10.1016/j.geomorph.2009.08.010.

[45] Parape CD, Premachandra C, Tamura M, Bari A, Disanayake R, Welikanna D, Jin S, Sugiura M. Building damage and business continuity management in the event of natural hazards: case study of the 2004 tsunami in Sri Lanka. Sustainability 2013; 5 (2):456-77. https://doi.org/10.3390/su5020456.

[46] Dikmen SÜ, Akbiyikli R, S¨onmez M. Assessment of the disaster recovery progress through mathematical modelling. Tek Dergi 2020; 31(4):10113-26. https://doi.org/10.18400/tekderg.473099.

[47] Murao O. Recovery curves for housing reconstruction from the 2011 Great East Japan Earthquake and comparison with other post-disaster recovery processes. Int J Disaster Risk Reduct 2020;45:101467. https://doi.org/10.1016/j.ijdrr.2019.101467.

[48] Federal Emergency Management Agency (2013) Tsunami methodology technical manual.

[49] Murao O. Recovery curves for permanent houses after the 2011 great east Japan earthquake. In: 16th World Conference on Earthquake Engineering. Tokyo, Japan: International Association for Earthquake Engineering; 2017. 1865.

[50] Platt S, Brown D, Hughes M. Measuring resilience and recovery. Int J Disaster Risk Reduct 2016;19:447-60. https://doi.org/10.1016/j.ijdrr.2016.05.006.

[51] Ayyub BM. Practical resilience metrics for planning, design, and decision making. ASCE-ASME J Risk Uncertain Eng Syst A: Civ Eng 2015; 1(3):04015008.

[52] Kafali C, Grigoriu M. Rehabilitation decision analysis. In: ICOSSAR’05: proceedings of the ninth international conference on structural safety and reliability; 2005.

[53] Forcellini D, Walsh KQ. Seismic resilience for recovery investments of bridges methodology. Proc Inst Civ Eng-Bridge Eng 2021; 177(3):160-72.

[54] Jayasuriya S., Steele P., Weerakoon D. (2006) Post-tsunami recovery: issues and challenges in Sri Lanka.

[55] Jayasuriya S., Peter McCawley (2010) The asian Tsunami: aid and reconstruction after a disaster. https://www.adb.org/publications/asian-tsunami-aid-and-reconstruction-after-disaster.

[56] Kennedy J, Ashmore J, Babister E, Kelman I. The meaning of ‘build back better’: evidence from post-tsunami Aceh and Sri Lanka. J contingencies crisis manag 2008; 16(1):24-36.

[57] Steinberg F. Housing reconstruction and rehabilitation in Aceh and Nias, Indonesia—Rebuilding lives. Habitat Int 2007; 31(1):150-66.

[58] Rigg J, Grundy-Warr C, Law L, Tan-Mullins M.Grounding a natural disaster: thailand and the 2004 tsunami. Asia Pac Viewp 2008; 49(2):137-54.

[59] Suppasri A, Mas E, Charvet I, Gunasekera R, Imai K, Fukutani Y, Abe Y, Imamura F. Building damage characteristics based on surveyed data and fragility curves of the 2011 Great East Japan tsunami. Nat Hazards 2013; 66(2):319-41. https://doi.org/10.1007/s11069-012-0487-8.

[60] Matanle P., Rausch A.S. (2011) Japan’s shrinking regions in the 21st century: contemporary responses to depopulation and socioeconomic decline.

[61] Suppasri A, Shuto N, Imamura F, Koshimura S, Mas E, Yalciner AC.Lessons learned from the 2011 Great East Japan tsunami: performance of tsunami countermeasures, coastal buildings, and tsunami evacuation in Japan. Pure Appl Geophys 2013; 170(6):993-1018.

[62] Burnham K.P., Anderson D.R. (2002) Model selection and multimodel inference: a practical information-theoretic approach.