case study of tsunami disaster

Login or signup to the library
my Channels
All Channels
List events
List channels
List collections

This Collection is part of the 'Tsunami Disaster Channel' containing a number of case studies and reports relevant to tsunami disasters, where we try to find out what we have learnt from the past and how we can best reduce risk in future natural disasters. Current guidance comes from leading global organizations: Foreign - Commonwealth & Development Office (FCDO) , Swiss Resource Centre and Consultancies for Development Foundation (SKAT) , Office of the UN Secretary General Special Envoy for Tsunami Recovery , United Nations Children's Fund (UNICEF) , United Nations Environment Programme (UNEP) , United Nations International Strategy for Disaster Reduction (UNISDR) . Please send suggestions for additional content for this Collection to [email protected] . You might find other helpful collections on tsunami disasters below."

Resources on this Collection

10 Lessons Learned from the South Asia Tsunami of 26th December 2004

Approaches to Equity in Post-Tsunami Assistance - Sri Lanka: A Case Study

Environment and Reconstruction in Aceh: two years after the tsunami

Evolving Strategies For Long-term Rehabilitation On Shelter and Development in the Tsunami Affected Areas of Tamil Nadu

Impact of the tsunami response on local and national capacities: Maldives country report

Indian Ocean Earthquake and Tsunami UNICEF response at six months update

You must be logged in to post a comment

0 Shopping Cart

2018 Sulawesi, Indonesia Earthquake and Tsunami Case Study

What caused the Sulawesi, Indonesian earthquake and what were the effects?

On Friday 28th September 2018 a magnitude 7.5 earthquake struck Palu, on the Indonesian island of Sulawesi, just before dusk wreaking havoc and destruction across the city and triggering a deadly tsunami on its coast. The 7.5 magnitude earthquake hit only six miles from the country’s coast.

A map to show the location of Palu

The shallow tremor was more powerful than a series of earthquakes that killed hundreds on the Indonesian island of Lombok this July and August.

Palu is located on the Indonesian island of Sulawesi, 1,650 kilometres northeast of Jakarta, at the mouth of the Palu River. It is the capital of the province of Central Sulawesi, situated on a long, narrow bay .

A satellite image to show the location of Palu – Source Google Earth

The coastal city of Palu is home to 350,000 people.

Small foreshocks had been happening throughout 28th September in Palu. However, in the early evening, the Palu-Koru fault suddenly slipped, a short distance offshore and only 10km (6 miles) below the surface. This generated the 7.5 magnitude earthquake.

The impact of the earthquake was magnified because of the thick layers of sediment on which the city lies. Whereas bedrock shakes in an earthquake, sediment moves a lot more, behaving like a liquid. Poorly constructed houses cannot withstand movement of this magnitude.

Scientists don’t pay much attention to the Palu-Koru fault line, as far as tsunamis are concerned. This is because the two plates are moving past each other, not with the vertical thrust required to form a tsunami.

Scientists are still trying to work out what happened to cause the tsunami. It is possible that the earthquake caused an underwater landslide which disturbed the water or there could be inaccuracies in the identification of the type of fault.

Once the wave started moving, Palu, at the end of a narrow 10km-long bay, was a sitting duck.

Tsunamis are no danger when out at sea. But when the waves come closer to land, their base drags on the seabed causing them to rise up.

Primary Effects

The quake destroyed thousands of homes in the city, as well as an eight-storey hotel, hospital and a large department store.

More before/after comparisons from around the #PaluTsunami and #PaluEarthquake captured by @planetlabs . Included rough lat/long. Keep an eye on https://t.co/Kz73HlYmGF as they often post the sat. imagery for responders, relief agencies et al. pic.twitter.com/1Vreovjt9b — Murray Ford (@mfordNZ) October 1, 2018

At least 2256 people have been confirmed dead, with more than 10,679 injured and 1075 missing. 200,000 people were in urgent need of assistance, about a quarter of them children.

The earthquake caused widespread liquefaction , which is when soil and groundwater mix. The ground becomes very soft, similar to quicksand. It causes foundations of buildings and other structures to sink into the ground.

In the case of Palu, buildings not only collapsed but some were moved by the liquefaction. This is why it is better to build on bedrock rather than on top of the soil.

The control tower and runway at Palu’s airport also sustained damage. Commercial flights were cancelled with only humanitarian and search and rescue flights permitted.

Secondary Effects

The earthquake triggered a tsunami reaching 6 metres in height. As the tsunami approached the coast it was reported to be travelling 250mph. The damage was as extensive: the main highway was cut off by a landslide and a large bridge washed away by the tsunami wave, which hit Palu’s Talise beach and the coastal town of Donggala.

Landslides, downed communications networks and collapsed bridges have made it hard for aid workers and rescuers to reach rural areas.

Due to hospitals being damaged, people received medical treatment in the open.

Strong aftershocks hit the island the day after the earthquake.

Immediate (Short Term) Response

A tsunami warning was issued by Indonesia’s geophysics agency (BMKG) when the earthquake was detected. However, the agency lifted the warning 34 minutes after it was first issued. The closest tidal sensor to Palu is around 200km (125 miles) away. The decision to lift the tsunami warning was based on this data.

Search and rescue teams were deployed to the worst-affected areas. Around 700 army and police officers were dispatched to assist in the emergency response.

The military sent cargo planes with aid from Jakarta and other cities. However, this was slow to arrive.

A large number of charities set up appeals to raise funds to support people in the affected area. Buckingham Palace reported that the Queen had made a donation to the Disasters Emergency Committee (DEC) appeal for survivors, which raised £6m in a day when it was launched.

The RAF delivered thousands of shelter kits, solar lanterns and water purifiers to the disaster zone in addition to trucks and power generators to help get them to where they are needed.

At least 70,000 people gathered in evacuation sites across the island.

Long-term Response

Premium Resources

Please support internet geography.

If you've found the resources on this page useful please consider making a secure donation via PayPal to support the development of the site. The site is self-funded and your support is really appreciated.

Lombok Indonesia Earthquake 2018 Case Study

Topic home, 2010 chile earthquake, share this:.

Click to share on Twitter (Opens in new window)
Click to share on Facebook (Opens in new window)
Click to share on Pinterest (Opens in new window)
Click to email a link to a friend (Opens in new window)
Click to share on WhatsApp (Opens in new window)
Click to print (Opens in new window)

If you've found the resources on this site useful please consider making a secure donation via PayPal to support the development of the site. The site is self-funded and your support is really appreciated.

Search Internet Geography

Latest Blog Entries

Pin It on Pinterest

Click to share
Print Friendly

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts
Review Article
Published: 23 August 2022

Giant tsunami monitoring, early warning and hazard assessment

Nobuhito Mori ORCID: orcid.org/0000-0001-9082-3235 1 ,
Kenji Satake ORCID: orcid.org/0000-0002-3368-3085 2 ,
Daniel Cox 3 ,
Katsuichiro Goda ORCID: orcid.org/0000-0003-3900-2153 4 ,
Patricio A. Catalan 5 ,
Tung-Cheng Ho ORCID: orcid.org/0000-0002-3678-8288 1 ,
Fumihiko Imamura ORCID: orcid.org/0000-0001-7628-575X 6 ,
Tori Tomiczek ORCID: orcid.org/0000-0003-4116-7547 7 ,
Patrick Lynett ORCID: orcid.org/0000-0002-2856-9405 8 ,
Takuya Miyashita 1 ,
Abdul Muhari 9 ,
Vasily Titov ORCID: orcid.org/0000-0002-1630-3829 10 &
Rick Wilson ORCID: orcid.org/0000-0003-3629-2167 11

Nature Reviews Earth & Environment volume 3 , pages 557–572 ( 2022 ) Cite this article

1235 Accesses

14 Citations

72 Altmetric

Metrics details

Physical oceanography
Solid Earth sciences

Earthquake-triggered giant tsunamis can cause catastrophic disasters to coastal populations, ecosystems and infrastructure on scales over thousands of kilometres. In particular, the scale and tragedy of the 2004 Indian Ocean (about 230,000 fatalities) and 2011 Japan (22,000 fatalities) tsunamis prompted global action to mitigate the impacts of future disasters. In this Review, we summarize progress in understanding tsunami generation, propagation and monitoring, with a particular focus on developments in rapid early warning and long-term hazard assessment. Dense arrays of ocean-bottom pressure gauges in offshore regions provide real-time data of incoming tsunami wave heights, which, combined with advances in numerical and analogue modelling, have enabled the development of rapid tsunami forecasts for near-shore regions (within 3 minutes of an earthquake in Japan). Such early warning is essential to give local communities time to evacuate and save lives. However, long-term assessments and mitigation of tsunami risk from probabilistic tsunami hazard analysis are also needed so that comprehensive disaster prevention planning and structural tsunami countermeasures can be implemented by governments, authorities and local populations. Future work should focus on improving tsunami inundation, damage risk and evacuation modelling, and on reducing the uncertainties of probabilistic tsunami hazard analysis associated with the unpredictable nature of megathrust earthquake occurrence and rupture characteristics.

The scale and tragedy of the 2004 Indian Ocean Tsunami and the 2011 Tohoku Tsunami prompted the widespread deployment of tsunami observation networks and the development of tsunami modelling, which have enabled tsunami early warning systems to approach near-real-time inundation forecasts, based on the dense arrays of offshore observation data.

Earthquake magnitude alone does not characterize the size or impact of the ensuing tsunami disaster. The tsunami source (such as earthquake location and rupture characteristics), coastal geomorphic features, and exposure of densely populated areas have key roles in tsunami behaviour, inundation extent and the level of impact.

Probabilistic tsunami hazard assessment (PTHA) is a recently developed method of considering the variability of tsunami conditions for risk mitigation. PTHA can be used in engineering design and to draw up tsunami inundation maps at different return period levels, which can be used to plan local and regional hazard mitigation.

To mitigate future tsunami risks, we must be able to reproduce the inundation depth and flow velocity of tsunamis that run up to urban areas. A combination of numerical and physical models is needed to better understand the complex interactions between building layouts, structures, debris and non-hydrostatic flow.

Long-term tsunami assessments will inform authorities about requirements for software and hardware countermeasures. Hardware or structural measures (such as sea walls) can reduce loss of life and assets during an event, whereas software or non-structural measures (such as evaluation, assessments and planning) can reduce loss of life.

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

24,99 € / 30 days

cancel any time

Subscribe to this journal

Receive 12 digital issues and online access to articles

92,52 € per year

only 7,71 € per issue

Rent or buy this article

Prices vary by article type

Prices may be subject to local taxes which are calculated during checkout

The enigmatic 1693 AD tsunami in the eastern Mediterranean Sea: new insights on the triggering mechanisms and propagation dynamics

Giovanni Scicchitano, Salvatore Gambino, … Carmelo Monaco

Characterizing storm-induced coastal change hazards along the United States West Coast

James B. Shope, Li H. Erikson, … Peter Ruggiero

Changing impacts of Alaska-Aleutian subduction zone tsunamis in California under future sea-level rise

Tina Dura, Andra J. Garner, … Benjamin P. Horton

Talley, H. C. & Cloud, W. K. United States Earthquakes, 1960 (US Geological Survey, 1984).

Satake, K. & Fujii, Y. Source models of the 2011 Tohoku earthquake and long-term forecast of large earthquakes. J. Disaster Res. 9 , 272–280 (2014).

Article Google Scholar

Uchida, N. & Bürgmann, R. A decade of lessons learned from the 2011 Tohoku–Oki earthquake. Rev. Geophys. 59 , e2020RG000713 (2021).

International Federation of Red Cross and Red Crescent Societies (IFRC). World Disasters Report 2005: Focus on Information in Disasters (Kumarian Press, 2005).

Hayes, G. P., Earle, P. S., Benz, H. M., Wald, D. J. & Briggs, R. W. 88 hours: the US Geological Survey National Earthquake Information Center response to the 11 March 2011 M w 9.0 Tohoku earthquake. Seismol. Res. Lett. 82 , 481–493 (2011).

Wirth, E. A., Sahakian, V. J., Wallace, L. M. & Melnick, D. The occurrence and hazards of great subduction zone earthquakes. Nat. Rev. Earth Environ. 3 , 125–140 (2022).

Ide, S., Baltay, A. & Beroza, G. C. Shallow dynamic overshoot and energetic deep rupture in the 2011 M w 9.0 Tohoku–Oki earthquake. Science 332 , 1426–1429 (2011).

Rudloff, A., Lauterjung, J., Münch, U. & Tinti, S. Preface “The GITEWS project (German-Indonesian Tsunami Early Warning System)”. Natural Haz. Earth Syst. Sci. 9 , 1381–1382 (2009).

Meinig, C., Stalin, S. E., Nakamura, A. I. & Milburn, H. B. Real-time Deep-ocean Tsunami Measuring, Monitoring, And Reporting System: The NOAA DART II Description And Disclosure 1–15 (NOAA, 2005).

Mochizuki, M. et al. S-net project: performance of a large-scale seafloor observation network for preventing and reducing seismic and tsunami disasters. In OCEANS 2018-MTS/IEEE Kobe Techno-Oceans 1–4 (IEEE, 2018); https://ieeexplore.ieee.org/abstract/document/8558823 .

Araki, E., Kawaguchi, K., Kaneko, S. & Kaneda, Y. Design of deep ocean submarine cable observation network for earthquakes and tsunamis. In OCEANS 2008-MTS/IEEE Kobe Techno-Oceans 1–4 (IEEE, 2008); https://ieeexplore.ieee.org/document/4531071 .

Selva, J. et al. Probabilistic tsunami forecasting for early warning. Nat. Commun. 12 , 5677 (2021).

Selva, J. Long-term multi-risk assessment: statistical treatment of interaction among risks. Natural Haz. 67 , 701–722 (2013).

User’s guide for the Pacific Tsunami Warning Center enhanced products for the Pacific Tsunami Warning System. In International Oceanographic Commission Technical Series Vol. 105 (IOC, 2015): https://unesdoc.unesco.org/ark:/48223/pf0000220368 .

Whitmore, P. M. & Sokolowski, T. J. Predicting tsunami amplitudes along the North American coast from tsunamis generated in the northwest Pacific Ocean during tsunami warnings. Sci. Tsunami Haz. 14 , 147–166 (1996).

Google Scholar

Synolakis, C. E., Bernard, E. N., Titov, T. T., Kânoğlu, U. & González, F. I. Standards, criteria, and procedures for NOAA evaluation of tsunami numerical models. In NOAA Technical Memorandum OAR PMEL-135 (NOAA/Pacific Marine Environmental Laboratory, 2007).

Aoi, S. et al. MOWLAS: NIED observation network for earthquake, tsunami and volcano. Earth Planets Space 72 , 126 (2020).

Earthquakes and tsunamis — disaster prevention and mitigation efforts. In JMA Brochure (Japan Meteorological Agency, 2021); https://www.jma.go.jp/jma/kishou/books/jishintsunami/en/jishintsunami_en.pdf .

Kato, T., Terada, Y., Nishimura, H., Nagai, T. & Koshimura, S. Tsunami records due to the 2010 Chile earthquake observed by GPS buoys established along the Pacific coast of Japan. Earth Planets Space 63 , e5–e8 (2011).

Kawai, H., Satoh, M., Kawaguchi, K. & Seki, K. Characteristics of the 2011 Tohoku tsunami waveform acquired around Japan by NOWPHAS equipment. Coast. Engin. J. 55 , 1350008 (2013).

Mulia, I. E. & Satake, K. Developments of tsunami observing systems in Japan. Front. Earth Sci. 8 , 145 (2020).

Kaneda, Y. et al. Development and application of an advanced ocean floor network system for megathrust earthquakes and tsunamis. In Seafloor Observatories 643–662 (Springer, 2015).

Tsushima, H., Hino, R., Fujimoto, H., Tanioka, Y. & Imamura, F. Near-field tsunami forecasting from cabled ocean bottom pressure data. J. Geophys. Res. Solid Earth 114 , B06309 (2009).

Tsushima, H., Hino, R., Ohta, Y., Iinuma, T. & Miura, S. tFISH/RAPiD: rapid improvement of near-field tsunami forecasting based on offshore tsunami data by incorporating onshore GNSS data. Geophys. Res. Lett. 41 , 3390–3397 (2014).

Maeda, T., Obara, K., Shinohara, M., Kanazawa, T. & Uehira, K. Successive estimation of a tsunami wavefield without earthquake source data: a data assimilation approach toward real-time tsunami forecasting. Geophys. Res. Lett. 42 , 7923–7932 (2015).

Gusman, A. R. et al. Tsunami data assimilation of Cascadia seafloor pressure gauge records from the 2012 Haida Gwaii earthquake. Geophys. Res. Lett. 43 , 4189–4196 (2016).

Wang, Y. & Satake, K. Real-time tsunami data assimilation of S-net pressure gauge records during the 2016 Fukushima earthquake. Seismol. Res. Lett. 92 , 2145–2155 (2021).

Wang, Y., Tsushima, H., Satake, K. & Navarrete, P. Review on recent progress in near-field tsunami forecasting using offshore tsunami measurements: source inversion and data assimilation. Pure Appl. Geophys. https://doi.org/10.1007/s00024-021-02910-z (2021).

Mori, N., Goda, K. & Cox, D. T. Recent process in probabilistic tsunami hazard analysis (PTHA) for megathrust subduction earthquakes. In The 2011 Japan Earthquake and Tsunami: Reconstruction and Restoration (eds Santiago-Fandiño, V., Sato, S., Maki, N. & Iuchi, K.) 469–485 (Springer, 2017).

Davies, G. et al. A global probabilistic tsunami hazard assessment from earthquake sources. Geol. Soc. Lond. Spec. Publ. 456 , 219–244 (2018).

Behrens, J. et al. Probabilistic tsunami hazard and risk analysis: a review of research gaps. Front. Earth Sci. 9 , 114 (2021).

Geist, E. L. & Parsons, T. Probabilistic analysis of tsunami hazards. Natural Haz. 37 , 277–314 (2006).

Grezio, A. et al. Probabilistic tsunami hazard analysis: multiple sources and global applications. Rev. Geophys. 55 , 1158–1198 (2017).

Davies, G. & Griffin, J. Sensitivity of probabilistic tsunami hazard assessment to far-field earthquake slip complexity and rigidity depth-dependence: case study of Australia. Pure Appl. Geophys . 177 , 1521–1548 (2020).

Tinti, S. & Armigliato, A. The use of scenarios to evaluate the tsunami impact in southern Italy. Mar. Geol. 199 , 221–243 (2003).

Baptista, M. A., Miranda, J. M., Omira, R. & Antuns, C. Potential inundation of Lisbon downtown by a 1755-like tsunami. Natural Haz. Earth Syst. Sci. 11 , 3319–3326 (2011).

Goda, K. Time-dependent probabilistic tsunami hazard analysis using stochastic rupture sources. Stoch. Environ. Res. Risk Assess. 33 , 341–358 (2019).

Geist, E. L. Complex earthquake rupture and local tsunamis. J. Geophys. Res. Solid. Earth 107 , ESE–2 (2002).

Melgar, D., Williamson, A. L. & Salazar-Monroy, E. F. Differences between heterogenous and homogenous slip in regional tsunami hazards modelling. Geophys. J. Int. 219 , 553–562 (2019).

Løvholt, F. et al. Stochastic analysis of tsunami runup due to heterogeneous coseismic slip and dispersion. J. Geophys. Res. Ocean 117 , C03047 (2012).

Davies, G., Horspool, N. & Miller, V. Tsunami inundation from heterogeneous earthquake slip distributions: evaluation of synthetic source models. J. Geophys. Res. Solid Earth 120 , 6431–6451 (2015).

Mueller, C., Power, W., Fraser, S. & Wang, X. Effects of rupture complexity on local tsunami inundation: implications for probabilistic tsunami hazard assessment by example. J. Geophys. Res. Solid Earth 120 , 488–502 (2015).

Park, H. & Cox, D. T. Probabilistic assessment of near-field tsunami hazards: Inundation depth, velocity, momentum flux, arrival time, and duration applied to Seaside, Oregon. Coast. Eng. 117 , 79–96 (2016).

Sepúlveda, I., Liu, P. L. & Grigoriu, M. Probabilistic tsunami hazard assessment in South China Sea with consideration of uncertain earthquake characteristics. J. Geophys. Res. Solid Earth 124 , 658–688 (2019).

Goda, K. Multi-hazard portfolio loss estimation for time-dependent shaking and tsunami hazards. Front. Earth Sci. 8 , 592444 (2020).

Walton, M. et al. Toward an integrative geological and geophysical view of Cascadia subduction zone earthquakes. Ann. Rev. Earth Planet. Sci. 49 , 367–398 (2021).

Ogata, Y. Estimating the hazard of rupture using uncertain occurrence times of paleoearthquakes. J. Geophys. Res. Solid Earth 104 , 17995–18014 (1999).

Sykes, L. R. & Menke, W. Repeat times of large earthquakes: implications for earthquake mechanics and long-term prediction. Bull. Seismol. Soc. Am. 96 , 1569–1596 (2006).

Field, E. H. & Jordan, T. H. Time-dependent renewal-model probabilities when date of last earthquake is unknown. Bull. Seismol. Soc. Am. 105 , 459–463 (2015).

Shimazaki, K. & Nakata, T. Time-predictable recurrence model for large earthquakes. Geophys. Res. Lett. 7 , 279–282 (1980).

Kiremidjian, A. S. & Anagnos, T. Stochastic slip-predictable model for earthquake occurrences. Bull. Seismol. Soc. Am. 74 , 739–755 (1984).

Cornell, A. C. & Winterstein, S. R. Temporal and magnitude dependence in earthquake recurrence models. Bull. Seismol. Soc. Am. 78 , 1522–1537 (1988).

Matthews, M. V., Ellsworth, W. L. & Reasenberg, P. A. A Brownian model for recurrent earthquakes. Bull. Seismol. Soc. Am. 92 , 2233–2250 (2002).

Abaimov, S. G. et al. Earthquakes: recurrence and interoccurrence times. In Earthquakes: Simulations, Sources and Tsunamis (eds Tiampo, K. F., Weatherley, D. K. & Weinstein, S. A.) 777–795 (Birkhäuser, 2008).

Ceferino, L., Kiremidjian, A. & Deierlein, G. Probabilistic space- and time-interaction modeling of mainshock earthquake rupture occurrence. Bull. Seismol. Soc. Am. 110 , 2498–2518 (2020).

Mai, P. M. & Thingbaijam, K. K. SRCMOD: An online database of finite-fault rupture models. Seismol. Res. Lett. 85 , 1348–1357 (2014).

Blaser, L., Krüger, F., Ohrnberger, M. & Scherbaum, F. Scaling relations of earthquake source parameter estimates with special focus on subduction environment. Bull. Seismol. Soc. Am. 100 , 2914–2926 (2010).

Leonard, M. Earthquake fault scaling: self-consistent relating of rupture length, width, average displacement, and moment release. Bull. Seismol. Soc. Am. 100 , 1971–1988 (2010).

Strasser, F. O., Arango, M. C. & Bommer, J. J. Scaling of the source dimensions of interface and intraslab subduction-zone earthquakes with moment magnitude. Seismol. Res. Lett. 81 , 941–950 (2010).

Murotani, S., Satake, K. & Fujii, Y. Scaling relations of seismic moment, rupture area, average slip, and asperity size for M~9 subduction-zone earthquakes. Geophys. Res. Lett. 40 , 5070–5074 (2013).

Thingbaijam, K. K., Mai, P. M. & Goda, K. New empirical earthquake source-scaling laws. Bull. Seismol. Soc. Am. 107 , 2225–2246 (2017).

Goda, K. & De Risi, R. Multi-hazard loss estimation for shaking and tsunami using stochastic rupture sources. Int. J. Disaster Risk Reduct. 28 , 539–554 (2018).

Herrero, A. & Bernard, P. A kinematic self-similar rupture process for earthquakes. Bull. Seismol. Soc. Am. 84 , 1216–1228 (1994).

Mai, P. M. & Beroza, G. C. A spatial random field model to characterize complexity in earthquake slip. J. Geophys. Res. Solid Earth 107 , ESE-10 (2002).

Goda, K., Mai, P. M., Yasuda, T. & Mori, N. Sensitivity of tsunami wave profiles and inundation simulations to earthquake slip and fault geometry for the 2011 Tohoku earthquake. Earth Planets Space 66 , 1–20 (2014).

Goda, K., Yasuda, T., Mori, N. & Maruyama, T. New scaling relationships of earthquake source parameters for stochastic tsunami simulation. Coast. Eng. J. 58 , 1650010 (2016).

Melgar, D. & Hayes, G. P. The correlation lengths and hypocentral positions of great earthquakes. Bull. Seismol. Soc. Am. 109 , 2582–2593 (2019).

Li, L. et al. How heterogeneous coseismic slip affects regional probabilistic tsunami hazard assessment: a case study in the South China Sea. J. Geophys. Res. Solid Earth 121 , 6250–6272 (2016).

Scala, A. et al. Effect of shallow slip amplification uncertainty on probabilistic tsunami hazard analysis in subduction zones: use of long-term balanced stochastic slip models. Pure Appl. Geophys. 177 , 1497–1520 (2020).

Lomax, A., Michelini, A. & Piatanesi, A. An energy-duration procedure for rapid determination of earthquake magnitude and tsunamigenic potential. Geophys. J. Int. 170 , 1195–1209 (2007).

Howell, B. F. Jr On the saturation of earthquake magnitudes. Bull. Seismol. Soc. Am. 71 , 1401–1422 (1981).

Hanks, T. C. & Kanamori, H. A moment magnitude scale. J. Geophys. Res. Solid Earth 84 , 2348–2350 (1979).

Kanamori, H. & Rivera, L. Source inversion of W phase: speeding up seismic tsunami warning. Geophys. J. Int. 175 , 222–238 (2008).

Duputel, Z. et al. Real-time W phase inversion during the 2011 off the Pacific coast of Tohoku earthquake. Earth Planets Space 63 , 535–539 (2011).

Tsuboi, S., Abe, K., Takano, K. & Yamanaka, Y. Rapid determination of M w from broadband P waveforms. Bull. Seismol. Soc. Am. 85 , 606–613 (1995).

Lomax, A. & Michelini, A. M wpd : a duration–amplitude procedure for rapid determination of earthquake magnitude and tsunamigenic potential from P waveforms. Geophys. J. Int. 176 , 200–214 (2009).

Katsumata, A., Ueno, H., Aoki, S., Yoshida, Y. & Barrientos, S. Rapid magnitude determination from peak amplitudes at local stations. Earth Planets Space 65 , 843–853 (2013).

Wang, D. et al. Automated determination of magnitude and source length of large earthquakes using backprojection and P wave amplitudes. Geophys. Res. Lett. 44 , 5447–5456 (2017).

Cienfuegos, R. et al. What can we do to forecast tsunami hazards in the near field given large epistemic uncertainty in rapid seismic source inversions? Geophys. Res. Lett. 45 , 4944–4955 (2018).

MacInnes, B. T., Gusman, A. R., LeVeque, R. J. & Tanioka, Y. Comparison of earthquake source models for the 2011 Tohoku event using tsunami simulations and near-field observations. Bull. Seismol. Soc. Am. 103 , 1256–1274 (2013).

Mori, N., Mai, P. M., Goda, K. & Yasuda, T. Tsunami inundation variability from stochastic rupture scenarios: application to multiple inversions of the 2011 Tohoku, Japan earthquake. Coast. Eng. 127 , 88–105 (2017).

Catalan, P. A. et al. Design and operational implementation of the integrated tsunami forecast and warning system in Chile (SIPAT). Coast. Eng. J. 62 , 373–388 (2020).

Greenslade, D. J. et al. Evaluation of Australian tsunami warning thresholds using inundation modelling. Pure Appl. Geophys. 177 , 1425–1436 (2020).

Glimsdal, S., Pedersen, G. K., Harbitz, C. B. & Løvholt, F. Dispersion of tsunamis: does it really matter? Natural Haz. Earth Syst. Sci. 13 , 1507–1526 (2013).

Rabinovich, A. B., Woodworth, P. L. & Titov, V. V. Deep-sea observations and modeling of the 2004 Sumatra tsunami in Drake Passage. Geophys. Res. Lett. 38 , L16604 (2011).

Bai, Y., Yamazaki, Y. & Cheung, K. F. Interconnection of multi-scale standing waves across the Pacific Basin from the 2011 Tohoku tsunami. Ocean Model. 92 , 183–197 (2015).

Watada, S., Kusumoto, S. & Satake, K. Travel time delay and initial phase reversal of distant tsunamis coupled with the self-gravitating elastic Earth. J. Geophys. Res. Solid Earth 119 , 4287–4310 (2014).

Allgeyer, S. & Cummins, P. Numerical tsunami simulation including elastic loading and seawater density stratification. Geophys. Res. Lett. 41 , 2368–2375 (2014).

Watada, S. Tsunami speed variations in density-stratified compressible global oceans. Geophys. Res. Lett. 40 , 4001–4006 (2013).

Ho, T.-C., Satake, K. & Watada, S. Improved phase corrections for transoceanic tsunami data in spatial and temporal source estimation: application to the 2011 Tohoku earthquake. J. Geophys. Res. Solid Earth 122 , 10,155–10,175 (2017).

Baba, T. et al. Accurate numerical simulation of the far-field tsunami caused by the 2011 Tohoku earthquake, including the effects of Boussinesq dispersion, seawater density stratification, elastic loading, and gravitational potential change. Ocean Model. 111 , 46–54 (2017).

Carvajal, M., Cisternas, M. & Catalán, P. A. Source of the 1730 Chilean earthquake from historical records: implications for the future tsunami hazard on the coast of Metropolitan Chile. J. Geophys. Res. Solid Earth 122 , 3648–3660 (2017).

Matsuyama, M., Ikeno, M., Sakakiyama, T. & Takeda, T. A study of tsunami wave fission in an undistorted experiment. In Tsunami and its Hazards in the Indian and Pacific Oceans 617–631 (Birkhäuser, 2007).

Borrero, J. C., Lynett, P. J. & Kalligeris, N. Tsunami currents in ports. Phil. Trans. R. Soc. A 373 , 20140372 (2015).

Lynett, P. J. et al. Inter-model analysis of tsunami-induced coastal currents. Ocean Model. 114 , 14–32 (2017).

Mori, N., Cox, D. T., Yasuda, T. & Mase, H. Overview of the 2011 Tohoku earthquake tsunami damage and its relation to coastal protection along the Sanriku coast. Earthq. Spectra 29 , 127–143 (2013).

Suppasri, A., Koshimura, S. & Imamura, F. Developing tsunami fragility curves based on the satellite remote sensing and the numerical modeling of the 2004 Indian Ocean tsunami in Thailand. Natural Haz. Earth Syst. Sci. 11 , 173–189 (2011).

Suppasri, A. et al. Building damage characteristics based on surveyed data and fragility curves of the 2011 Great East Japan tsunami. Natural Haz. 66 , 319–341 (2013).

Shimozono, T. & Sato, S. Coastal vulnerability analysis during tsunami-induced levee overflow and breaching by a high-resolution flood model. Coast. Eng. 107 , 116–126 (2016).

Charvet, I., Suppasri, A., Kimura, H., Sugawara, D. & Imamura, F. A multivariate generalized linear tsunami fragility model for Kesennuma City based on maximum flow depths, velocities and debris impact, with evaluation of predictive accuracy. Natural Haz. 79 , 2073–2099 (2015).

Attary, N., van de Lindt, J. W., Unnikrishnan, V., Barbosa, A. R. & Cox, D. T. Methodology for development of physics-based tsunami fragilities. J. Struct. Eng. 143 , 04016223 (2017).

Fukui, N., Prasetyo, A. & Mori, N. Numerical modeling of tsunami inundation using upscaled urban roughness parameterization. Coast. Eng. 152 , 103534 (2019).

Fukui, N. et al. Variations in building-resolving simulations of tsunami inundation in a coastal urban area. J. Waterw. Port Coast. Ocean Eng. 148 , 04021044 (2022).

Park, H., Cox, D. T., Lynett, P. J., Wiebe, D. M. & Shin, S. Tsunami inundation modeling in constructed environments: a physical and numerical comparison of free-surface elevation, velocity, and momentum flux. Coast. Eng. 79 , 9–21 (2013).

Prasetyo, A., Tomiczek, T., Yasuda, T., Mori, N. & Mase, H. Characteristics of a tsunami wave using a hybrid tsunami generator. In Coastal Structures and Solutions to Coastal Disasters 2015: Tsunamis 164–175 (American Society of Civil Engineers, 2017).

Como, A. & Mahmoud, H. Numerical evaluation of tsunami debris impact loading on wooden structural walls. Eng. Struct. 56 , 1249–1261 (2013).

Park, H. & Cox, D. T. Effects of advection on predicting construction debris for vulnerability assessment under multi-hazard earthquake and tsunami. Coast. Eng. 153 , 103541 (2019).

Miyashita, T., Mori, N. & Goda, K. Uncertainty of probabilistic tsunami hazard assessment of Zihuatanejo (Mexico) due to the representation of tsunami variability. Coast. Eng. J. 62 , 413–428 (2020).

Chock, G. Y. K. Design for tsunami loads and effects in the ASCE 7-16 standard. J. Struct. Eng. 142 , 04016093 (2016).

Zamora, N., Catalán, P. A., Gubler, A. & Carvajal, M. Microzoning tsunami hazard by combining flow depths and arrival times. Front. Earth Sci. 8 , 591514 (2021).

Baker, J.W., Bradley, B. & Stafford, P. Seismic Hazard and Risk Analysis (Cambridge Univ. Press, 2021).

Goda, K. & De Risi, R. Probabilistic tsunami loss estimation: stochastic earthquake scenario approach. Earthq. Spectra 33 , 1301–1323 (2017).

Tarbotton, C., Dall’Osso, F., Dominey-Howes, D. & Goff, J. The use of empirical vulnerability functions to assess the response of buildings to tsunami impact: comparative review and summary of best practice. Earth Sci. Rev. 142 , 120–134 (2015).

Attary, N., Unnikrishnan, V. U., van de Lindt, J. W., Cox, D. T. & Barbosa, A. R. Performance-based tsunami engineering methodology for risk assessment of structures. Eng. Struct. 141 , 676–686 (2017).

Petrone, C., Rossetto, T. & Goda, K. Fragility assessment of a RC structure under tsunami actions via nonlinear static and dynamic analyses. Eng. Struct. 136 , 36–53 (2017).

Park, H. & Cox, D. T. Effects of advection on forecasting construction debris for vulnerability assessment under multi-hazard earthquake and tsunami. Coast. Eng. 153 , 103541 (2019).

Kameshwar, S. et al. Probabilistic decision-support framework for community resilience: incorporating multi-hazards, infrastructure interdependencies, and target objectives in a Bayesian network. Reliab. Eng. Syst. Saf. 191 , 106568 (2019).

Park, H., Alam, M. S., Cox, D. T., Barbosa, A. R. & van de Lindt, J. W. Probabilistic seismic and tsunami damage analysis (PSTDA) of the Cascadia subduction zone applied to Seaside, Oregon. Int. J. Disaster Risk Reduct. 35 , 101076 (2019).

Attary, N., van de Lindt, J. W., Barbosa, A. R., Cox, D. T. & Unnikrishnan, V. U. Performance-based tsunami engineering for risk assessment of structures subjected to multi-hazards: tsunami following earthquake. J. Earthq. Eng. 25 , 2065–2084 (2021).

Goda, K. et al. Multi-hazard earthquake-tsunami loss estimation of Kuroshio Town, Kochi Prefecture, Japan considering the Nankai–Tonankai megathrust rupture scenarios. Int. J. Disaster Risk Reduct. 54 , 102050 (2021).

Goda, K. et al. Earthquake-tsunami risk assessment and critical multi-hazard loss scenarios: a case study in Japan under the Nankai–Tonankai mega-thrust. In Engineering for Extremes 235–254 (Springer, 2022).

Li, L. et al. A modest 0.5-m rise in sea level will double the tsunami hazard in Macau. Sci. Adv. 4 , eaat1180 (2018).

Alhamid, A. K. et al. Framework for probabilistic tsunami hazard assessment considering the effects of sea-level rise due to climate change. Struct. Safety 94 , 102152 (2022).

Song, J. & Goda, K. Influence of elevation data resolution on tsunami loss estimation and insurance rate-making. Front. Earth Sci. 7 , 246 (2019).

Goda, K. Multi-hazard parametric catastrophe bond trigger design for subduction earthquakes and tsunamis. Earthq. Spectra. 37 , 1827–1848 (2021).

Shuto, N. & Fujima, K. Review: a short history of tsunami research and countermeasures in Japan. Proc. Jpn Acad. Ser. B 85 , 267–275 (2009).

Koshimura, S. & Shuto, N. Response to the 2011 Great East Japan earthquake and Tsunami disaster. Phil. Trans. R. Soc. A 373 , 20140373 (2015).

Kato, F., Suwa, Y., Watanabe, K. & Hatogai, S. Mechanisms of coastal dike failure induced by the Great East Japan earthquake tsunami. Coast. Eng. Proc. https://doi.org/10.9753/icce.v33.structures.40 (2012).

Chen, J., Jiang, C., Yang, W. & Xiao, G. Laboratory study on protection of tsunami-induced scour by offshore breakwaters. Natural Haz. 81 , 1229–1247 (2016).

Tanaka, N., Yasuda, S., Iimura, K. & Yagisawa, J. Combined effects of coastal forest and sea embankment on reducing the washout region of houses in the Great East Japan tsunami. J. Hydro-Environ. Res. 8 , 270–280 (2014).

Park, H., Cox, D. T. & Barbosa, A. R. Comparison of inundation depth and momentum flux based fragilities for probabilistic tsunami damage assessment and uncertainty analysis. Coast. Eng. 122 , 10–26 (2017).

Guler, H. G., Baykal, C., Arikawa, T. & Yalciner, A. C. Numerical assessment of tsunami attack on a rubble mound breakwater using OpenFOAM. Appl. Ocean. Res. 72 , 76–91 (2018).

Jelínek, R. & Krausmann, E. Approaches to tsunami risk assessment. JRC Sci. Tech. Rep. 48713 , 112 (2008).

Behrens, J. et al. Probabilistic tsunami hazard and risk analysis: a review of research gaps. Front. Earth Sci. https://doi.org/10.3389/feart.2021.628772 (2021).

Salgado-Gálvez, M. A., Zuloaga-Romero, D., Bernal, G. A., Mora, M. G. & Cardona, O.-D. Fully probabilistic seismic risk assessment considering local site effects for the portfolio of buildings in Medellín, Colombia. Bull. Earthq. Eng. 12 , 671–695 (2014).

Ozer, S. C., Yalciner, A. C., Zaytsev, A., Suppasri, A. & Imamura, F. Investigation of hydrodynamic parameters and the effects of breakwaters during the 2011 Great East Japan tsunami in Kamaishi Bay. Pure Appl. Geophys. 172 , 3473–3491 (2015).

Syamsidik et al. Assessing the tsunami mitigation effectiveness of the planned Banda Aceh Outer Ring Road (BORR), Indonesia. Natural Haz. Earth Syst. Sci. 19 , 299–312 (2019).

Chock, G., Yu, G., Thio, H. K. & Lynett, P. J. Target structural reliability analysis for tsunami hydrodynamic loads of the ASCE 7 standard. J. Struct. Eng. 142 , 04016092–04016112 (2016).

Akiyama, M., Frangopol, D. M. & Ishibashi, H. Toward life-cycle reliability-, risk- and resilience-based design and assessment of bridges and bridge networks under independent and interacting hazards: emphasis on earthquake, tsunami and corrosion. Struct. Infrastruct. Eng. 16 , 26–50 (2020).

Muhari, A., Diposaptono, S. & Imamura, F. Toward an integrated tsunami disaster mitigation: lessons learned from previous tsunami events in Indonesia. J. Nat. Disaster Sci. 29 , 13–19 (2007).

Lunghino, B. et al. The protective benefits of tsunami mitigation parks and ramifications for their strategic design. Proc. Natl Acad. Sci. 117 , 10740–10745 (2020).

Tanaka, N. Effectiveness and limitations of coastal forest in large tsunami: conditions of Japanese pine trees on coastal sand dunes in tsunami caused by Great East Japan earthquake. J. Jpn Soc. Civil Eng. Ser. B1 68 , II_7–II_15 (2012).

Osti, R., Tanaka, S. & Tokioka, T. The importance of mangrove forest in tsunami disaster mitigation. Disasters 33 , 203–213 (2009).

Danielsen, F. et al. The Asian tsunami: a protective role for coastal vegetation. Science 310 , 643 (2005).

Goda, K. et al. Cascading geological hazards and risks of the 2018 Sulawesi Indonesia earthquake and sensitivity analysis of tsunami inundation simulations. Front. Earth Sci. 7 , 261 (2019).

American Society of Civil Engineers. Minimum design loads and associated criteria for buildings and other structures 7–22 (ASCE-SEI, 2022).

Taubenböck, H. et al. “Last-mile” preparation for a potential disaster — interdisciplinary approach towards tsunami early warning and an evacuation information system for the coastal city of Padang, Indonesia. Natural Haz. Earth Syst. Sci. 9 , 1509–1528 (2009).

Mas, E. et al. Recent advances in agent-based tsunami evacuation simulations: case studies in Indonesia, Thailand, Japan and Peru. Pure Appl. Geophys. 172 , 3409–3424 (2015).

Wood, N. J., Jones, J., Schmidtlein, M. C., Schelling, J. & Frazier, T. Pedestrian flow-path modeling to support tsunami evacuation and disaster relief planning in the US Pacific Northwest. Int. J. Disaster Risk Reduct. 18 , 41–55 (2016).

Muhammad, A. et al. Are current tsunami evacuation approaches safe enough? Stoch. Environ. Res. Risk Assess. 35 , 759–779 (2021).

Wood, N. J. & Schmidtlein, M. C. Anisotropic path modeling to assess pedestrian evacuation potential from Cascadia-related tsunamis in the US Pacific Northwest. Natural Haz. 62 , 275–300 (2012).

Schmidtlein, M. C. & Wood, N. J. Sensitivity of tsunami evacuation modeling to direction and land cover assumptions. Appl. Geogr. 56 , 154–163 (2015).

Kitamura, F., Inazu, D., Ikeya, T. & Okayasu, A. An allocating method of tsunami evacuation routes and refuges for minimizing expected casualties. Int. J. Disaster Risk Reduct. 45 , 101519 (2020).

Mostafizi, A., Wang, H., Dong, S., Cox, D. T. & Cramer, L. Agent-based tsunami evacuation modeling with unplanned network disruptions for evidence-driven resource allocation and planning strategies. Natural Haz. 88 , 1347–1372 (2017).

Castro, S., Poulos, A., Herrera, J. C. & de la Llera, J. C. Modeling the impact of earthquake-induced debris on tsunami evacuation times of coastal cities. Earthq. Spectra 35 , 137–158 (2019).

Makinoshima, F., Imamura, F. & Abe, Y. Behavior from tsunami recorded in the multimedia sources at Kesennuma City in the 2011 Tohoku Tsunami and its simulation by using the evacuation model with pedestrian-car interaction. Coast. Eng. J. 8 , 1640023 (2018).

Wilson, R. et al. Development and use of probabilistic tsunami hazard analysis maps in California. In Proc. 11th Nat. Conf. Earthq. Eng . 3411–3422 (EERI, 2018).

Basic guidelines for reconstruction in response to the Great East Japan earthquake. In Reconstruction and Revitalization Period 18 (Japan Reconstruction Agency, 2016).

Cosson, C. “Build back better”: between public policy and local implementation, the challenges in Tohoku’s reconstruction. Arch. Urban. Plan. 16 , 1–4 (2020).

Tsunami Resilience On The Oregon Coast (OSSPAC, 2022); https://www.oregon.gov/oem/Documents/OSSPAC_Agenda_Packet_2022-05-10.pdf .

Guidelines for evaluating and mitigation tsunami hazards in California . In California Geological Survey Special Publication 127 (in the press).

National tsunami hazard mitigation program strategic plan: 2018–2023 (NOAA, 2018).

Esteban, M. et al. Recent tsunamis events and preparedness: development of tsunami awareness in Indonesia, Chile and Japan. Int. J. Disaster Risk Reduct. 5 , 84–97 (2013).

Tohoku tsunami, March 11, 2011 main event page: global propagation animation of tsunami. In NOAA NCTR Experimental Research Product (NOAA, 2011); https://nctr.pmel.noaa.gov/honshu20110311/ .

Lynett, P. J. Precise prediction of coastal and overland flow dynamics: a grand challenge or a fool’s errand. J. Disaster Res. 11 , 615–623 (2016).

Goda, K. et al. Earthquake–tsunami risk assessment and critical multi-hazard loss scenarios: a case study in Japan under the Nankai–Tonankai mega-thrust. In Engineering For Extremes: Decision-making In An Uncertain World (eds Stewart, M. G. & Rosowsky, D. V.) Ch. 11 235–254 (Springer, 2022).

Download references

Acknowledgements

N.M. acknowledges funding from Grant-in-Aid for Scientific Research (KAKENHI) (grant numbers 20KK0095 and 21H04508), JST/JICA SATREPS Indonesia and the DPRI-ERI Research Fund (grant numbers 2019-K-01 and 2021-K-01). K.G. acknowledges funding from the Canada Research Chair programme (grant number 950-232015) and a Natural Sciences and Engineering Research Council Discovery Grant (grant number RGPIN-2019-05898). P.A.C. acknowledges funding from ANID; the Chile Centro de Investigación para la Gestión Integrada del Riesgo de Desastres (CIGIDEN) (grant number ANID/FONDAP/15110017) and the Centro Científico Tecnológico de Valparaíso (grant number ANID PIA/APOYO AFB180002). PMEL contribution #5397.

Author information

Authors and affiliations.

Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan

Nobuhito Mori, Tung-Cheng Ho & Takuya Miyashita

Earthquake Research Institute, University of Tokyo, Tokyo, Japan

Kenji Satake

School of Civil and Construction Engineering, Oregon State University, Corvallis, OR, USA

Department of Earth Sciences, Western University, London, Canada

Katsuichiro Goda

Departamento de Obras Civiles, Universidad Técnica Federico Santa María, Valparaíso, Chile

Patricio A. Catalan

International Research Institute of Disaster Science, Tohoku University, Sendai, Japan

Fumihiko Imamura

Department of Naval Architecture and Ocean Engineering, United States Naval Academy, Annapolis, MD, USA

Tori Tomiczek

Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, USA

Patrick Lynett

Badan Nasional Penanggulangan Bencana, Jakarta, Indonesia

Abdul Muhari

Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, Seattle, WA, USA

Vasily Titov

California Geological Survey, California Department of Conservation, Sacramento, CA, USA

Rick Wilson

You can also search for this author in PubMed Google Scholar

Contributions

N.M. and K.G. led the writing and revision of the manuscript, with input and contributions from K.S., D.C., P.A.C., F.I., T.T., P.L., T.M., A.M., V.T., T.-C.H. and R.W. All authors made substantial contributions to the discussion of content.

Corresponding author

Correspondence to Nobuhito Mori .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Reviews Earth & Environment thanks F. Løvholt, T. Lay, C. Mueller, and the other, anonymous, reviewer(s) 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.

Supplementary information

Supplementary information.

Estimation of hazard intensity and frequency based on historical data or model results.

Height or velocity of tsunami, used in tsunami hazard assessments.

Combination of hazard, exposure and vulnerability.

The boundary between the two converging tectonic plates at a subduction zone

A tsunami that occurs at a subduction zone following a megathrust earthquake.

(DART). A tsunami monitoring system that consists of OBP sensors and moored surface buoys for real-time communication of data via satellites, developed by NOAA.

Tsunami with waves that affect coastal regions far away (over 1,000 km) from the location of the tsunami source.

(OBP). A kind of sensor that monitors ocean-bottom pressure and converts it to sea-level heights, enabling detection of tsunamis in the deep ocean.

(S-net). A network of 150 OBP stations connected by a network of over 5,800 km of submarine cables, installed along the Japan Trench after the 2011 Tohoku tsunami.

(DONET/DONET2). A Japanese network of approximately 50 OBP sensors connected by submarine cables along the Nankai trough.

(TEWS). Real-time tsunami alert systems, in which estimates of tsunami heights are based on seismic and/or tsunami observation data.

Tsunami with waves that affect regions near the location of the tsunami source.

(PTHA). A probabilistic quantification of tsunami intensity and frequency, based on assessments of earthquake frequency, hazard footprints and damage susceptibility.

Earthquake early warning system developed by USGS and partners, which combines rapid earthquake detection with alert messages broadcast to a variety of people, infrastructure and devices, such as personal mobile phones.

A measure of an earthquake’s size or strength.

A tsunami that occurred prior to historical records or has no written observations.

Empirical relation used to estimate earthquake frequency.

( M w ). A measure of earthquake magnitude based on its seismic moment.

Waves of different periods that travel at different phase speeds (waves with shorter periods travel at slower phase speeds).

Purpose-designed spaces in coastal regions that are built to reduce tsunami forces beyond the park, thereby helping to protect critical infrastructure or communities.

Rights and permissions

Springer Nature or its licensor 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.

Reprints and permissions

About this article

Cite this article.

Mori, N., Satake, K., Cox, D. et al. Giant tsunami monitoring, early warning and hazard assessment. Nat Rev Earth Environ 3 , 557–572 (2022). https://doi.org/10.1038/s43017-022-00327-3

Download citation

Accepted : 07 July 2022

Published : 23 August 2022

Issue Date : September 2022

DOI : https://doi.org/10.1038/s43017-022-00327-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

Explore articles by subject
Guide to authors
Editorial policies

To read this content please select one of the options below:

Please note you do not have access to teaching notes, community preparedness for tsunami disaster: a case study.

Disaster Prevention and Management

ISSN : 0965-3562

Article publication date: 21 June 2011

The main objective of this study is to develop a tsunami emergency response plan for a coastal community by adopting a community‐based disaster preparedness approach.

Design/methodology/approach

A multi‐strategy research design utilizing both quantitative and qualitative methods was used. The weaknesses and strengths of the different agencies involved in responding to the 2004 tsunami disaster were identified through a focus group discussion. A survey was used to assess the preparedness of the community. Tsunami awareness and education were imparted through lectures, sermons, radio talk shows, informal briefings, workshops and printed materials. Tsunami evacuation routes, safe zones, warning protocols and evacuation plans were finalized through a consultation process with the community. A tsunami evacuation plan was verified during a table‐top exercise and was tested through a drill.

It is evident from the study that a community‐based approach (where the local community is taken as the primary focus of attention in disaster reduction) to tsunami mitigation and preparedness is viable. This process has provided an opportunity for tapping traditional organizational structures and mechanisms (including formal and informal community leaders) and capability‐building activities with the community disaster committees and volunteers.

Originality/value

Tsunami 2004 is the first ever tsunami disaster experienced in the country and thus the study provides significant lessons learned from the event. The community‐based approach to disaster preparedness is not the current practice in the country. Thus, the study demonstrates that the approach is a viable tool to enhance community preparedness to tsunami and other types of disasters as well.

Emergency response
Community preparedness
Evacuation routes

Mat Said, A. , Ahmadun, F. , Rodzi Mahmud, A. and Abas, F. (2011), "Community preparedness for tsunami disaster: a case study", Disaster Prevention and Management , Vol. 20 No. 3, pp. 266-280. https://doi.org/10.1108/09653561111141718

Emerald Group Publishing Limited

We’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

Agent-based models of human response to natural hazards: systematic review of tsunami evacuation

Review Article
Open access
Published: 05 October 2022
Volume 115 , pages 1887–1908, ( 2023 )

Cite this article

You have full access to this open access article

Karel Mls ORCID: orcid.org/0000-0002-7681-8277 1 ,
Milan Kořínek 1 ,
Kamila Štekerová ORCID: orcid.org/0000-0001-5847-7950 1 ,
Petr Tučník ORCID: orcid.org/0000-0002-6705-8974 1 ,
Vladimír Bureš ORCID: orcid.org/0000-0001-7788-7445 1 ,
Pavel Čech ORCID: orcid.org/0000-0002-2547-0629 1 ,
Martina Husáková ORCID: orcid.org/0000-0003-1116-4556 1 ,
Peter Mikulecký ORCID: orcid.org/0000-0002-2595-3989 1 ,
Tomáš Nacházel ORCID: orcid.org/0000-0001-6484-3793 1 ,
Daniela Ponce ORCID: orcid.org/0000-0001-5190-0453 1 ,
Marek Zanker ORCID: orcid.org/0000-0002-2745-4868 1 ,
František Babič ORCID: orcid.org/0000-0003-2225-5955 2 &
Ioanna Triantafyllou ORCID: orcid.org/0000-0002-8920-5322 3

3402 Accesses

4 Citations

1 Altmetric

Explore all metrics

A Correction to this article was published on 27 April 2023

This article has been updated

This systematic review provides a comprehensive overview of tsunami evacuation models. The review covers scientific studies from the last decade (2012–2021) and is explicitly focused on models using an agent-based approach. The PRISMA methodology was used to analyze 171 selected papers, resulting in over 53 studies included in the detailed full-text analysis. This review is divided into two main parts: (1) a descriptive analysis of the presented models (focused on the modeling tools, validation, and software platform used, etc.), and (2) model analysis (e.g., model purpose, types of agents, input and output data, and modeled area). Special attention was given to the features of these models specifically associated with an agent-based approach. The results lead to the conclusion that the research domain of agent-based tsunami evacuation models is quite narrow and specialized, with a high degree of variability in the model attributes and properties. At the same time, the application of agent-specific methodologies, protocols, organizational paradigms, or standards is sparse.

A Multi-agent Based Evacuation Planning for Disaster Management: A Narrative Review

Navroop Kaur & Harjot Kaur

Evaluation of the risk and the evacuation policy in the case of a tsunami in the city of Iquique, Chile

Ignacio A. Solís & Pedro Gazmuri

Avoid common mistakes on your manuscript.

1 Introduction

Natural disasters, in general, have the potential to impact inhabited areas heavily and can potentially cause many fatal injuries and massive damage to infrastructure and property. Our research is focused primarily on the consequences of tsunami waves, which usually follow severe earthquakes and affect large coastal areas. Given the nature of tsunamis, there is usually an extremely limited time window to handle the evacuation of people to shelters located either at higher altitudes or further from the zones of wave impact. During this limited time, it is necessary to maximize the efficiency of evacuation procedures and minimize the risks of endangering human lives. This is one of the main features of tsunami evacuation models that distinguishes our research from similar but more general studies of evacuation models (Kaur and Kaur 2022 ).

In order to find the best and most efficient practices, it is necessary to study evacuation processes in detail using various disaster scenarios under different settings. Mathematical models represent one of the standard approaches to examining patterns of group behavior. On the other hand, approaches based on real observations and experiments, e.g., during evacuation drills (Chen et al. 2022 ) provide valuable data that can be used to tune the parameters of computer models. These models, in turn, enable massive in silico testing of alternative scenarios, including extremely rare or risky ones.

This systematic review presents a detailed analysis of agent-based models (ABMs) used to study evacuation processes under various circumstances. The review focuses on the last decade of research in this domain (2012–2021) to take into account current results in particular. This choice is also supported by the fact that primary sources record the first works on the subject under review also in this time period (Web of Science from 2012, Scopus from 2010). Secondary sources, such as Google Scholar, record the first relevant article in 2001, but the majority of publications (about 90%) again fall into the last decade. We analyzed 171 papers or articles obtained from primary sources and belonging to the selected period, and after applying the discrimination criteria using the PRISMA methodology (Page et al. 2021 ), 53 of them were selected for detailed full-text analysis.

The focus of this review, specifically on ABM applications, is motivated by the scalability, adaptability, and customizability of the agent-oriented approach which has been proven in various domains (Bureš and Tučník 2014 ). Agents are capable of autonomous decision-making and social interactions, and can conclusively simulate human behavior during disasters, including phenomena such as panic, errors in judgment, health conditions, and weather. Since ABMs are usually constructed using a bottom-up approach, the overall performance can be studied under randomized/customized conditions at the global level (Bonabeau 2002 ). As such, agent-based (social) simulations have the potential to contribute meaningfully to a better understanding of the large-scale processes related to evacuation procedures and the mitigation of risks related to disasters. This review is also related to our previous research (Nacházel et al. 2021 ) focused on analyzing tsunami-related data and datasets. At the same time, the possibilities of ontologies as perspective methods of representation and formal description of the observed domain are investigated (Babič et al. 2022 ).

This systematic review is divided into six sections. The second section describes the methodology of the research and research questions that we aim to answer in this review. The third part focuses on the technical properties of ABMs (with special attention given to features specific to an agent-oriented approach), such as agent-based modeling tools, the validity of the models, and other technical parameters. The fourth section describes the model attributes, for example, the main purpose of the models, their special features, a representation of the environment, input and output data, and other model-related details. The fifth part is dedicated to the discussion and summarization of the results. Finally, the sixth section concludes this review.

2 Methodology

The present study is focused on an agent-based simulation of a tsunami evacuation. A review based on PRISMA methodology (Page et al. 2021 ) was conducted. We aim to answer the following four research questions:

What were agent-based models developed in relation to a tsunami evacuation?

How were such ABMs specifically designed?

Which goals or performance criteria were ABMs trying to pursue?

What are the research opportunities and gaps in the area of agent-based evacuation models of tsunami scenarios?

An initial cross-search was conducted using scientific databases Web of Science and Scopus in July–August 2021. The selection criteria and data collection strategy focused on agent-based simulation, tsunami, and evacuation. The review included full texts published in English between 2012 and 2021. Initially, standard search tools within WoS and Scopus were used, which returned all articles meeting the specified criteria. By applying the search to all fields of the databases, however, results were also found that mentioned the defined characteristics only marginally or partially—for example, in references to sources in the introductory or research section, or as “future work.”

The abstracts, keywords, and practical chapters of these articles were subsequently screened to pre-exclude articles we identified as not meeting the search criteria (Table 1 ).

Thus, 171 articles were initially identified from primary scientific databases. After removing duplicates and irrelevant papers based on orientation screening (by title, abstract, and non-research chapters), 70 papers were advanced to the full-text evaluation phase for eligibility. The result of this preparatory phase was 53 papers suitable for both qualitative and quantitative analysis. The entire process is illustrated in Fig. 1 and a complete list of selected papers is given in Online Resource 1.

PRISMA flow diagram

Two lists of paper characteristics are defined for the implementation of qualitative and quantitative analysis. List A focuses on the technical properties of papers (agent-based modeling-related issues and standards), resulting in descriptive statistics (see Sect. 3 ):

What agent-based modeling tool or programming language was used?

Are the source code and documentation available?

Are any scenarios defined?

Are experiments presented?

Were statistical methods applied?

Was a sensitivity analysis conducted?

What validation method was used?

List B focuses on a more detailed analysis of the models used in the articles (see Sect. 4 ):

What geographical area is simulated by a model?

What is the general purpose of the model?

Are any special features/aspects/issues of evacuation explored?

How is the environment represented?

What types of agents are defined, what are their attributes?

What are the agents’ attributes, if specified?

What input data/variables are used in the models?

What output data/variables/measures does the model produce?

Are there any simplifications or features omitted from the model and/or proposed by the authors for future work?

Are there any specific algorithms used by agents?

Each paper was reviewed by at least two reviewers.

3 Technical properties of ABM models

The descriptive analysis focused on the technical properties of the selected texts (as listed in Sect. 2 , List A), and, in addition to the binary outputs (condition met/not met), the occurrences of specific responses were also recorded (e.g., types of ABM tools and scenarios/experiments used in simulations).

3.1 Item A1: What agent-based modeling tool or programming language was used?

With this question, we focused on determining which software tools were used in selected articles to implement the agent models. Dozens of different tools have been created and used to varying degrees over the years (Nikolai and Madey 2009 ). Currently, the most well-known tools in application domains such as traffic simulations, GIS, mobility planning, and evacuation are summarized in Table 2 .

In 16 out of 53 analyzed papers (30%), the authors did not mention any specific tool or platform used in their research. In other texts, the use of the universal academic NetLogo platform (10x) prevailed over specialized tools Repast Simphony (5x), GAMA (5x), and MATSim (2x) (see Fig. 2 ).

Frequency of occurrence of individual software tools in the analyzed texts

3.2 Item A2: Are the source code and documentation available?

Only 5 of the 53 papers were accompanied by source code (Aguilar et al. 2017 ; Nakanishi et al. 2020 ; Naqvi 2017 ; Slucki and Nielek 2015 ; Wijerathne et al. 2013 ) and only one pseudocode (Poulos et al. 2018 ) was found. This means that approximately 90% of the models are virtually impossible to replicate and the published results cannot therefore be at least quantitatively verified. This finding is in accord with the results of previous studies (Schulze et al. 2017 ).

3.3 Item A3: Are any scenarios defined?

In 36 of the papers, the scenarios are defined, and in 17, they are not. Because the multi-agent system can be used to model human behavior and various “what if” scenarios, it can also be used to model and simulate multiple situations that are difficult to test in real life for security reasons. The results then illustrate the way people behave in the proposed situation and can provide a reliable and credible conclusion corresponding to real-time scenarios. Scenarios can be based on various complex patterns of agent behavior—from simple reactive interaction with the environment to complicated and realistic behavior controlled by artificial intelligence (Sharma et al. 2018 ) (Table 3 ).

3.4 Item A4: Are experiments presented?

If we consider the framework scenarios, the next logical step in modeling is to focus on specific experiments. From the analyzed articles, it is clear that both scenarios and experiments are given paramount attention by the authors.

In 42 of the selected papers, experiments are presented, and only in 7 they are not; in addition, in only 2 of the papers are the final results given (Aguilar et al. 2017 ; Alam and Habib 2020 ), and the final 2 describe the results briefly or in general (Mas et al. 2015 ; Slucki and Nielek 2015 ) (Table 4 ).

3.5 Item A5: Were statistical methods applied?

In 19 papers from the analyzed set, statistical methods were applied, while in 34 they were not; in addition, most authors provided simple descriptive statistics (bar graphs), or they state that due to the fact that multi-agent models are stochastic in nature, it is necessary to repeat the simulations many times and use only the mean values of the results.

3.6 Item A6: Was a sensitivity analysis conducted?

Among the papers studied, 39 did not specify any method of sensitivity analysis, whereas in 11 publications (Alam and Habib 2020 , Kunwar et al. 2014 , Le et al. 2013 , 2014 , 2015 , 2017 , Mostafizi et al. 2017 , 2019a , b , Poulos et al. 2018 ; Solís and Gazmuri 2017 ) some mentions of the analysis are given. In one paper, the authors present the analysis as “future work” (Makinoshima et al. 2018 ), and in (Takabatake et al. 2020a , b , c ) the “effects of change of behavior on mortality rate” are discussed, whereas in (Wang et al. 2016 ) “model sensitivity to critical depth and model sensitivity to s and r ” is presented.

3.7 Item A7: What validation method was used?

In 39 of the papers, no explicit validation method was specified. A comparison with real-world data is presented in (Castro et al. 2019 ; Katayama et al. 2019 ; Sahal et al. 2013 ; Takabatake 2020a , b ), whereas comparison with other models is less common (Alam and Habib 2020 ; Faucher et al. 2020 ). The use of mobile phone data to calibrate the ABM outcomes (León et al. 2021 ) and video analysis (Poulos et al. 2018 ) or comparison with a shelter plan analysis (Usman et al. 2017 ) are other validation methods applied.

4 Analysis of model attributes

This section of the review focuses on a detailed analysis of the model attributes, listed specifically in Sect. 2 , List B.

4.1 Item B1: What geographical area is simulated by a model?

The majority of the models described in papers can be perceived to a certain extent as case studies for specific regions. This is a reasonable approach because it indirectly validates the model results to a certain extent and improves the applicability of the new knowledge obtained from the simulation results. The research is usually focused on areas where tsunamis are a frequent phenomenon, such as coastal regions of Southeast Asia, the western coast of South America or Middle America, and the Mediterranean Sea. This can potentially be important for other parameters of the model settings; therefore, this parameter was included in this study (Table 5 ).

In the context of geographical regions, it is also worth noting that geographical regions may not be limited to the coastal part of the region. It seems that a part of the seabed is often included as well because it may provide important, more detailed information about tsunami wave propagation and parameters. Nonetheless, these more specific details are covered by item 7 in List B, which is focused on various data sources or datasets used for the initial configuration of the model parameters. Therefore, this aspect was not included in this part of the analysis. In almost every ABM included in the full-text analysis (see Sect. 2 ), a more specific part of the selected national state was used, that is, the specification of the geographic area usually has the structure of a nation-national region. Because this seems to be the most frequently used academic approach, this study adopts the same method.

4.2 Item B2: What is the general purpose of the model?

The model attributes describe the major aim or purpose of the model. This review is focused on evacuation models and is therefore the joint purpose of all models in this review, despite significant variations in how the topic is handled. These differences are indicated in the model attributes.

The results of the analysis indicate that many models are focused on one of three approaches, which can be distinguished by their temporal aspects (which phase of evacuation the model is primarily focused on). These three approaches are (1) preparation and planning (e.g., urban planning, various tools to improve the recognition of tsunami-related risks), (2) the evacuation process itself (during the tsunami wave impact), and (3) optimization and improvement (application of risk/damage mitigation measures as a result of previous experience or knowledge). Other than these three major categories, there are other factors at play, although many more models can be added to one or more of these groups (Table 6 ).

4.3 Item B3: Are any special features/aspects/issues of evacuation explored?

Many models have special characteristics that can be of further interest. For example, along with the evacuation problem itself, the model can also work with issues related to traffic, multimodal transportation, COVID-19, debris, and building damage, among others. Therefore, this attribute helps to further distinguish individual models from each other and provides more information to the reader.

The most frequently researched aspect found is the study of individual behaviors. This is usually related to evacuation planning issues, and several studies have used scalable models that combine micro- and macro-scale perspectives. Another branch of research is focused on the environment, using approaches such as evacuation sign placement or urban planning and a design used to minimize the evacuation times. This is connected to transportation optimization and efficient path planning. GIS-based data are often used as a base layer for an environmental representation (Table 7 ).

4.4 Item B4: How is the environment represented?

There were significant differences in the representation of the environment. Some models use a simplified version of such a representation, and others use quite an elaborate environment model. This varies greatly among the models used; for example, bordered regions using only statistics, scaling up to highly detailed models with complex simulations of the hydrodynamics of tsunami wave advancement.

The most frequently used approach is to create a model using real map data, such as models based on GIS data, networks, or roads, which are derived from standard navigation application data (usually for land traffic, and quite less frequently for maritime traffic). More formal models use discrete mathematical representations, such as network graphs or grid-based approaches.

Another specific group consists of models focused on interior representations rather than maps or larger geographical areas. Although such an approach is usually related to highly detailed mechanisms for the simulation of building damage, interior evacuations, and other factors, surprisingly, several examples of combinations of interior/exterior perspectives were found as well. In these cases, exterior areas are usually limited to city districts, tourist venues, or other similarly limited exterior spaces (Table 8 ).

4.5 Item B5: What types of agents are defined, what are their attributes?

Because all models included in this study are to a smaller or larger extent related to evacuation issues, there is usually some representation of the evacuees included. However, many other entities may be represented in the model as agents. This attribute is quite important for the differentiation of the individual models because it is closely related to the complexity of the multi-agent systems used. Again, the complexity varies from a highly simplified representation and uncomplicated agent architectures to complex models incorporating social aspects of behavior and mutual interactions.

To date, the type of agent that is most frequently used is typically a form of pedestrian representation, which is combined with vehicles in certain studies. Quite often, various types of individuals are further distinguished to capture differences between local populations, tourists, evacuees, and other individuals (Table 9 ).

4.6 Item B6: What are the agents’ attributes, if specified?

The complexity of the model is often reflected in the number of individual attributes incorporated in the model. The purpose of this attribute is to reflect this complexity by providing a general description of the aspects of this model. In some cases, it was impossible to obtain a complete list of attributes, which were often not listed in the papers covered in this study. However, the number of individual attributes is an important aspect that reflects the complexity of the model, and as such, it was included as one of the monitored characteristics.

Although many papers do not list agent-related attributes specifically, the most frequently used factor is speed. Given the fact that there is generally a temporal limitation for evacuation procedures, this is quite logical. Speed is often combined with position, location, and direction. It can be assumed that the number of papers working with position attributes is actually higher, although this is usually not specifically mentioned in the literature. Other personal characteristics also seem to play important roles here, i.e., age, role, psychological aspects (often related to decision making), gender, and field of vision. Several studies used a large number of descriptive attributes in the models, going as far as listing over 50 attributes to provide an example (Table 10 ).

4.7 Item B7: What input data/variables are used in the models?

Models are often constructed on reliable real-world datasets or input data. This is a crucial factor when evaluating the validity of the model because randomly generated data tend to provide less reliable results. Another factor that makes this attribute of the model important is the ability to reproduce the experiments.

As can be expected, there is a frequent use of GIS-related data or standard formats of regional navigational maps, known from normally used navigation devices. However, the most frequently used characteristics are individual physical attributes and a speed of movement description provided in the models. This correlates with the analysis of item B6 (see Sect. 4.6 ), in which speed plays the most important role as well. Many models use census data and surveys or official data provided by various official organizations related to tsunami impact mitigation efforts, which generally have a positive impact on the model validity (Table 11 ).

4.8 Item B8: What output data/variables/measures does the model produce?

The models vary in complexity, level of detail, number of agents, and other aspects, and therefore produce various types of output data. This is another important attribute of a model because it straightforwardly reflects its purpose and indicates the key performance factors being measured.

The results showed that the most frequently used output parameters were the number of people saved or lost and the evacuation time/speed. Because many models are focused on optimizing evacuation routes, these factors in the form of traffic network optimization or the use of shortest paths to safe zones are used as output factors as well (Table 12 ).

4.9 Item B9: Are there any simplifications or features omitted from the model and/or proposed by the authors for future work?

The models presented in this paper are commonly the results of ongoing long-term research and are becoming more complex and elaborate over time. This attribute serves as an indication of what is being either intentionally omitted from the model or intended for implementation in future research.

Although the majority of studies do not mention any simplifications specifically, when they are mentioned, there is a large variability in the topics. The most frequently mentioned is the incorporation of more detailed social mechanics into the models. Other factors and future topics of research are too varied to show some common trends (Table 13 ).

4.10 Item B10: Are there any specific algorithms used by agents?

In many cases, agents implemented in the model use standard, well-known algorithms for some of their behavioral components, such as pathfinding, coordination, movement, and communication protocols. Because this can be an important factor for differentiation between models, it is one of the monitored model attributes.

In the majority of studies, no specific algorithms were mentioned. When they are used, they are usually related to pathfinding and path planning approaches. This correlates with the attributes mentioned above, where speed and evacuation times seem to be the most crucial performance indicators in the models (Table 14 )..

5 Conclusions

Our paper critically assessed the latest papers on agent-based models of human response to natural disasters, namely tsunamis. Typically, the ABM approach was adopted to represent the evacuation process, exploration of crowd behavior during a natural disaster (earthquake and subsequent tsunami), evacuation planning and optimization, and estimation of casualties. Typical input variables are the magnitude and spatial distribution of shelters, distances or zones, size of the population, and categories (e.g., locals or tourists and children or adults).

The output variables are the evacuation time, number of casualties and survivors, and optimal evacuation routes (in the case of a comparison of the scenarios).

Surprisingly, the papers did not follow the agent-based modeling approach and standards. From a methodological perspective, applied models are not as systemic as one would expect based on experience from other domains (Bureš 2006 ). Moreover, the models are not described in a particularly sophisticated way: the ODD protocol was not broadly adopted, and validation and verification methods were not systematically applied. Documentation and source codes were also not provided by the authors of the models; therefore, replication of the experiments is nearly impossible.

The models typically illustrate the phenomena using a selected algorithm; for example, pathfinding to shelters was frequently examined using Dijkstra’s method. Few models focus on specific issues, such as exploration of COVID transmission during a tsunami evacuation in the lockdown of the city (Callejas et al. 2020 ) or exploration of the performance and scalability of an agent-based mass tsunami evacuation simulation within high-performance and distributed computing (Aguilar et al. 2017 ).

In general, these models illustrate the significant potential of an agent-based approach in relation to the exploration of natural hazards; however, their achievements are insufficient.

Through a systematic analysis of relevant sources from the subject domain, we have identified the following two directions in research, which have not yet been presented and will become the motivation for our further study:

Specifications of the large-scale agent-based metamodel of the tsunami are necessary. The metamodel integrates precise environmental/hydrodynamical flooding models with models of human response (immediate response such as crowd evacuation as well as long-term plans and measures to mitigate potential hazards).

Development of agent-based simulations in massive multi-user online map-based game frameworks supporting 3D graphics. The inspiration here comes from (Massey et al. 2018 ) and (Cheliotis 2021 ).

Code Availability

No code or software has been developed for this research.

Change history

27 april 2023.

A Correction to this paper has been published: https://doi.org/10.1007/s11069-023-05919-w

Abar S, Theodoropoulos GK, Lemarinier P, O’Hare GM (2017) Agent based modelling and simulation tools: a review of the state-of-art software. Comp Sci Rev 24:13–33. https://doi.org/10.1016/j.cosrev.2017.03.001

Article Google Scholar

Aguilar L, Lalith M, Ichimura T, Hori M (2017) On the performance and scalability of an HPC enhanced multi agent system based evacuation simulator. Proc Comp Sci 108:937–947. https://doi.org/10.1016/j.procs.2017.05.284

Alam MDJ, Habib MA (2020) Modeling traffic disruptions during mass evacuation. Procedia Comput Sci 170:506–513. https://doi.org/10.1016/j.procs.2020.03.115

Babič F, Bureš V, Čech P, Husáková M, Mikulecký P, Mls K, Nacházel T, Ponce D, Štekerová K, Triantafyllou I, Tučník P, Zanker M et al (2022) Review of tools for semantics extraction: application in tsunami research domain. Information 13(1):4. https://doi.org/10.3390/info13010004

Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci 99(suppl_3):7280–7287. https://doi.org/10.1073/pnas.082080899

Bureš V (2006) Systems thinking as a basis for ambient intelligence. In: Proceedings of the 11th annual SIGCSE conference on Innovation and technology in computer science education (ITICSE '06). Association for Computing Machinery, New York, NY, USA, 318. https://doi.org/10.1145/1140124.1140224

Bureš V, Tučník P (2014) Complex agent-based models: application of a constructivism in the economic research. E+M Ekonomie a Manage 17(3):152–168. https://doi.org/10.15240/tul/001/2014-3-012

Callejas E, Inostrosa-Psijas A, Moreno F, Oyarzun M, Carvajal-Schiaffino R (2020) COVID-19 transmission during a tsunami evacuation in a lockdown city. In: Proceedings of 39th international conference of the Chilean Computer Science Society (SCCC). IEEE, New York, pp 1–8. https://doi.org/10.1109/SCCC51225.2020.9281149

Castro S, Poulos A, Urrutia A, Herrera JC, Cienfuegos R, De La Llera JC (2018) Impact of earthquake magnitude on the estimation of tsunami evacuation casualties. In: Proceedings of the 11th national conference in earthquake engineering. Earthquake Engineering Research Institute. https://11ncee.org/images/program/papers/11NCEE-001593.pdf . Accessed 25 February 2022

Castro S, Poulos A, Herrera JC, de la Llera JC (2019) Modeling the impact of earthquake-induced debris on tsunami evacuation times of coastal cities. Earthquake Spectra 35:137–158. https://doi.org/10.1193/101917EQS218M

Cheliotis K (2021) ABMU: an agent-based modelling framework for Unity3D. SoftwareX 15:100771. https://doi.org/10.1016/j.softx.2021.100771

Chen C, Mostafizi A, Wang H, Cox D, Cramer L (2022) Evacuation behaviors in tsunami drills. Nat Hazards 112:845–871. https://doi.org/10.1007/s11069-022-05208-y

Faucher JE, Dávila S, Hernández-Cruz X (2020) Modeling pedestrian evacuation for near-field tsunamis fusing ALCD and agent-based approaches: a case study of Rincón, PR. Int J Disaster Risk Reduct 49:101606. https://doi.org/10.1016/j.ijdrr.2020.101606

Faucher JE, Dávila S, Hernández-Cruz X (2019) A hybrid pedestrian evacuation model for tsunamis. In: Proceedings of IIE annual conference. Institute of Industrial and Systems Engineers (IISE), pp 982–987. https://www.proquest.com/docview/2511386571?pq-origsite=gscholar&fromopenview=true . Accessed 25 February 2022

Hatayama M, Kosaka T, Hernandeze AH (2019) Analysis on tsunami evacuation options with agent-based simulation in tourist area. In: Proceedings of 2018 5th International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). IEEE, New York, pp 1–8. https://doi.org/10.1109/ICT-DM.2018.8636385

Helton WS, Kemp S, Walton D (2013) Individual differences in movements in response to natural disasters: Tsunami and earthquake case studies. In: Proc of the human factors and ergonomics society annual meeting. SAGE Publications, Thousand Oaks, pp 858–862. https://doi.org/10.1177/1541931213571186

Ishida R, Izumi T, Nakatani Y (2013) Simulation system of tsunami evacuation behavior during an earthquake around JR Osaka station area. In: Zlatanova S., Peters R., Dilo A., Scholten H. (eds) Intelligent systems for crisis management. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, pp 67–78. https://doi.org/10.1007/978-3-642-33218-0_6

Ishida Y, Hashimoto S (2015) Asymmetric characterization of diversity in symmetric stable marriage problems: an example of agent evacuation. Proc Comp Sci 60:1472–1481. https://doi.org/10.1016/j.procs.2015.08.229

Ito E, Kawase H, Matsushima S, Hatayama M (2020) Tsunami evacuation simulation considering road blockage by collapsed buildings evaluated from predicted strong ground motion. Nat Hazards 101:959–980. https://doi.org/10.1007/s11069-020-03903-2

Jumadi CS, Quincey D (2016) A conceptual framework of volcanic evacuation simulation of Merapi using agent-based model and GIS. Proc Soc Behav Sci 227:402–409. https://doi.org/10.1016/j.sbspro.2016.06.092

Karbovskii VA, Voloshin DV, Puzyreva KA, Zagarskikh AS (2014) Personal decision support mobile service for extreme situations. Proc Comp Sci 29:1646–1655. https://doi.org/10.1016/j.procs.2014.05.150

Karbovskii V, Voloshin D, Karsakov A, Bezgodov A, Zagarskikh A (2015) Multiscale agent-based simulation in large city areas: emergency evacuation use case. Proc Comp Sci 51:2367–2376. https://doi.org/10.1016/j.procs.2015.05.407

Katayama K, Takahashi H, Yokota N, Sugiyasu K, Kitagata G, Kinoshita T (2019) An effective multi-UAVs-based evacuation guidance support for disaster risk reduction. In: Proceedings of IEEE International Conference on Big Data and Smart Computing (BigComp), pp 1–6. https://doi.org/10.1109/BIGCOMP.2019.8679474

Kaur N, Kaur H (2022) A multi-agent based evacuation planning for disaster management: a narrative review. Arch Comput Methods Eng, pp 1–29. https://doi.org/10.1007/s11831-022-09729-4

Kunwar B, Simini F, Johansson A (2014) Large scale pedestrian evacuation modeling framework using volunteered geographical information. Transp Res Proc 2:813–818. https://doi.org/10.1016/j.trpro.2014.09.092

Le VM, Chevaleyre Y, Zucker JD, Vinh HT (2013) Speeding up the evaluation of casualties in multi-agent simulations with Linear Programming application to optimization of sign placement for tsunami evacuation. In: Proceedings of the 2013 RIVF international conference on computing & communication technologies-research, innovation, and vision for future (RIVF). IEEE, New York, pp 215–220. https://doi.org/10.1109/RIVF.2013.6719896

Le VM, Chevaleyre Y, Zucker JD, Vinh HT (2014) Approaches to optimize local evacuation maps for helping evacuation in case of Tsunami. In: Proceedings of international conference on information systems for crisis response and management in Mediterranean countries. Springer, Cham, pp 21–31. https://doi.org/10.1007/978-3-319-11818-5_3

Le VM, Chevaleyre Y, Vinh HT, Zucker JD (2015) Hybrid of linear programming and genetic algorithm for optimizing agent-based simulation. Application to optimization of sign placement for tsunami evacuation. In: Proceedings of the 2015 IEEE RIVF international conference on computing & communication technologies-research, innovation, and vision for future (RIVF). IEEE, New York, pp 138–143. https://doi.org/10.1109/RIVF.2015.7049889

Le VM, Vinh HT, Zucker JD (2017) Reinforcement learning approach for adapting complex agent-based model of evacuation to fast linear model. In: Proceedings of 2017 seventh international conference on information science and technology (ICIST). IEEE, New York, pp 369–375. https://doi.org/10.1109/ICIST.2017.7926787

León J, March A (2014a) An urban design framework for tsunami evacuation safety: a case study of two Chilean cities. In: Proceedings of the 5th international disaster and risk conference: integrative risk management—the role of science, technology and practice, Davos, Switzerland, pp 407–410

León J, March A (2014b) Urban morphology as a tool for supporting tsunami rapid resilience. A case study of Talcahuano. Chile Habitat Int 43:250–262. https://doi.org/10.1016/j.habitatint.2014.04.006

León J, March A (2016) An urban form response to disaster vulnerability: improving tsunami evacuation in Iquique, Chile. Environ Plann B: Plann Des 43:826–847. https://doi.org/10.1177/0265813515597229

León J, Mokrani C, Catalán P, Cienfuegos R, Femenías C (2018) Examining the role of urban form in supporting rapid and safe tsunami evacuations: a multi-scalar analysis in Viña del Mar, Chile. Proc Eng 212:629–636. https://doi.org/10.1016/j.proeng.2018.01.081

León J, Castro S, Mokrani C, Gubler A (2020) Tsunami evacuation analysis in the urban built environment: a multi-scale perspective through two modeling approaches in Viña del Mar, Chile. Coast Eng J 62:389–404. https://doi.org/10.1080/21664250.2020.1738073

León J, Mas E, Catalán PA, Moya L, Gubler A, Koshimura S, Cienfuegos R (2021) Development of calibrated tsunami evacuation models through real-world collected data: The case study of Coquimbo-La Serena, Chile. In: Proceedings of IOP conference series: earth and environmental science. IOP Publishing, Bristol, p. 012005. https://doi.org/10.1088/1755-1315/630/1/012005

Makinoshima F, Imamura F, Abe Y (2018) Enhancing a tsunami evacuation simulation for a multi-scenario analysis using parallel computing. Simul Model Pract Theory 83:36–50. https://doi.org/10.1016/j.simpat.2017.12.016

Mas E, Koshimura S, Imamura F, Suppasri A, Muhari A, Adriano B (2015) Recent advances in agent-based tsunami evacuation simulations: case studies in Indonesia, Thailand, Japan and Peru. Pure Appl Geophys 172:3409–3424. https://doi.org/10.1007/s00024-015-1105-y

Massey D, Ahlqvist O, Vatev K, Rush J (2018) A massively multi-user online game framework for agent-based spatial simulation. In: Wang S, Goodchild M (eds) CyberGIS for Geospatial Discovery and Innovation. GeoJournal Library, vol 118. Springer, Dordrecht, pp 213–224 . https://doi.org/10.1007/978-94-024-1531-5_11

Medina N, Sanchez A, Vojinovic Z (2016) The potential of agent based models for testing city evacuation strategies under a flood event. Proc Eng 154:765–772. https://doi.org/10.1016/j.proeng.2016.07.581

Mostafizi A, Wang H, Cox D, Cramer LA, Dong S (2017) Agent-based tsunami evacuation modeling of unplanned network disruptions for evidence-driven resource allocation and retrofitting strategies. Nat Hazards 88:1347–1372. https://doi.org/10.1007/s11069-017-2927-y

Mostafizi A, Wang H, Cox D, Dong S (2019a) An agent-based vertical evacuation model for a near-field tsunami: choice behavior, logical shelter locations, and life safety. Int J Disaster Risk Reduct 34:467–479. https://doi.org/10.1016/j.ijdrr.2018.12.018

Mostafizi A, Wang H, Dong S (2019b) Understanding the multimodal evacuation behavior for a near-field tsunami. Transp Res Record: J Transp Res Board 2673:480–492. https://doi.org/10.1177/0361198119837511

Nacházel T, Babič F, Baiguera M, Čech P, Husáková M, Mikulecký P, Mls K, Ponce D, Salmanidou D, Štekerová K, Triantafyllou I, Tučník P, Zanker M, Bureš V (2021) Tsunami-related data: a review of available repositories used in scientific literature. Water 13:2177. https://doi.org/10.3390/w13162177

Nakanishi H, Wise S, Suenaga Y, Manley E (2020) Simulating emergencies with transport outcomes Sim (SETOSim): application of an agent-based decision support tool to community evacuation planning. Int J Disaster Risk Reduct 49:101657. https://doi.org/10.1016/j.ijdrr.2020.101657

Naqvi A (2017) Deep impact: Geo-simulations as a policy toolkit for natural disasters. World Dev 99:395–418. https://doi.org/10.1016/j.worlddev.2017.05.015

Nguyen TNA, Zucker JD, Nguyen MH, Drogoul A, Nguyen HP (2012) Simulation of emergency evacuation of pedestrians along the road networks in Nhatrang city. In: Proceedings of 2012 IEEE RIVF international conference on computing & communication technologies, research, innovation, and vision for the future, pp 1–6. https://doi.org/10.1109/rivf.2012.6169853

Nikolai C, Madey G (2009) Tools of the trade: a survey of various agent based modeling platforms. J Artif Soc Soc Simulat 12:2. https://www.jasss.org/12/2/2.html . Accessed 25 February 2022

Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg 88:105906. https://doi.org/10.1016/j.ijsu.2021.105906

Poulos A, Tocornal F, de la Llera JC, Mitrani-Reiser J (2018) Validation of an agent-based building evacuation model with a school drill. Transp Res C Emerg Technol 97:82–95. https://doi.org/10.1016/j.trc.2018.10.010

Sahal A, Leone F, Péroche M (2013) Complementary methods to plan pedestrian evacuation of the French Riviera’s beaches in case of tsunami threat: graph- and multi-agent-based modelling. Nat Hazard 13:1735–1743. https://doi.org/10.5194/nhess-13-1735-2013

Schulze J, Müller B, Groeneveld J, Grimm V (2017) Agent-based modelling of social-ecological systems: achievements, challenges, and a way forward. J Artif Soc Soc Simulat 20:8. https://doi.org/10.18564/jasss.3423

Sharma S, Ogunlana K, Scribner D, Grynovicki J (2018) Modeling human behavior during emergency evacuation using intelligent agents: a multi-agent simulation approach. Inf Syst Front 20:741–757. https://doi.org/10.1007/s10796-017-9791-x

Slucki A, Nielek R (2015) Advantages of cooperative behavior during tsunami evacuation. In: Agarwal N., Xu K., Osgood N. (eds) Social computing, behavioral-cultural modeling, and prediction. SBP 2015. Lecture Notes in Computer Science, vol 9021. Springer, Cham, pp 203–212. https://doi.org/10.1007/978-3-319-16268-3_21

Solís IA, Gazmuri P (2017) Evaluation of the risk and the evacuation policy in the case of a tsunami in the city of Iquique, Chile. Nat Hazards 88:503–532. https://doi.org/10.1007/s11069-017-2876-5

Tagg A, Davison M, Wetton M (2016) Use of agent-based modelling in emergency management under a range of flood hazards. In: Proceedings of 3rd European conference on flood risk management (FLOODrisk 2016), p 8. https://doi.org/10.1051/e3sconf/20160719006

Takabatake T, Shibayama T, Esteban M, Ishii H, Hamano G (2017) Simulated tsunami evacuation behavior of local residents and visitors in Kamakura, Japan. Int J Disaster Risk Reduct 23:1–14. https://doi.org/10.1016/j.ijdrr.2017.04.003

Takabatake T, Shibayama T, Esteban M, Ishii H (2018) Advanced casualty estimation based on tsunami evacuation intended behavior: case study at Yuigahama Beach, Kamakura, Japan. Nat Hazards 92:1763–1788. https://doi.org/10.1007/s11069-018-3277-0

Takabatake T, Esteban M, Nistor I, Shibayama T, Nishizaki S (2020a) Effectiveness of hard and soft tsunami countermeasures on loss of life under different population scenarios. Int J Disaster Risk Reduct 45:101491. https://doi.org/10.1016/j.ijdrr.2020.101491

Takabatake T, Fujisawa K, Esteban M, Shibayama T (2020b) Simulated effectiveness of a car evacuation from a tsunami. Int J Disaster Risk Reduct 47:101532. https://doi.org/10.1016/j.ijdrr.2020.101532

Takabatake T, Nistor I, St-Germain P (2020c) Tsunami evacuation simulation for the District of Tofino, Vancouver Island, Canada. Int J Disaster Risk Reduct 48:101573. https://doi.org/10.1016/j.ijdrr.2020.101573

Usman F, Murakami K, Dwi Wicaksono A, Setiawan E (2017) Application of agent-based model simulation for tsunami evacuation in Pacitan, Indonesia. In: MATEC Web of Conferences. EDP Sciences, p. 01064. https://doi.org/10.1051/matecconf/20179701064

Wafda F, Saputra RW, Nurdin Y, Munadi K (2013) Agent-based tsunami evacuation simulation for disaster education. In: Proceedings of international conference on ICT for smart society. IEEE, New York, pp 1–4. https://doi.org/10.1109/ICTSS.2013.6588087

Wang Z, Jia G (2021) A novel agent-based model for tsunami evacuation simulation and risk assessment. Nat Hazards 105:2045–2071. https://doi.org/10.1007/s11069-020-04389-8

Wang H, Mostafizi A, Cramer LA, Cox D, Park H (2016) An agent-based model of a multimodal near-field tsunami evacuation: decision-making and life safety. Transp Res C Emerg Technol 64:86–100. https://doi.org/10.1016/j.trc.2015.11.010

Wijerathne MLL, Melgar LA, Hori M, Ichimura T, Tanaka S (2013) HPC enhanced large urban area evacuation simulations with vision based autonomously navigating multi agents. Proc Comp Sci 18:1515–1524. https://doi.org/10.1016/j.procs.2013.05.319

Wijerathne L, Petprakob W, Aguilar L, Hori M, Ichmura T (2018) Scalable HPC enhanced agent based system for simulating mixed mode evacuation of large urban areas. Transp Res Proc 34:275–282. https://doi.org/10.1016/j.trpro.2018.11.042

Wood N, Henry K, Peters J (2020) Influence of demand and capacity in transportation simulations of short-notice, distant-tsunami evacuations. Transp Res Interdisciplinary Perspect 7:100211. https://doi.org/10.1016/j.trip.2020.100211

Download references

Acknowledgements

The VES20 Inter-Cost LTC 20020 project supported this research. The authors also express gratitude to the COST Action AGITHAR leaders and team members.

This work was supported by the VES20 Inter-Cost LTC 20020 project.

Author information

Authors and affiliations.

Faculty of Informatics and Management, University of Hradec Králové, 500 03, Hradec Králové, Czech Republic

Karel Mls, Milan Kořínek, Kamila Štekerová, Petr Tučník, Vladimír Bureš, Pavel Čech, Martina Husáková, Peter Mikulecký, Tomáš Nacházel, Daniela Ponce & Marek Zanker

Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00, Košice, Slovakia

František Babič

Department of Geology and Geoenvironment, National & Kapodistrian University of Athens, 15772, Athens, Greece

Ioanna Triantafyllou

You can also search for this author in PubMed Google Scholar

Contributions

VB, KŠ, and PT were had the idea for the article; KŠ, PT, KM, and MK were involved in literature search and data analysis; PT, VB, DP, PM, and KŠ helped in conceptualization; KŠ, PT, PM, and FB contributed to methodology; KŠ, PČ, MH, TN, and MZ were involved in formal analysis; VB and PT helped in project administration; VB contributed to funding acquisition; FB and VB helped in supervision; PČ, FB, IT, and VB were involved in validation. The first draft of the manuscript was written by KŠ, PT, and KM and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Karel Mls .

Ethics declarations

Conflict of interest.

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised due to retrospective open access.

The original online version of this article was revised due to Ioanna Triantafyllou’s affiliation changes.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 209 kb)

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Mls, K., Kořínek, M., Štekerová, K. et al. Agent-based models of human response to natural hazards: systematic review of tsunami evacuation. Nat Hazards 115 , 1887–1908 (2023). https://doi.org/10.1007/s11069-022-05643-x

Download citation

Received : 06 March 2022

Accepted : 24 September 2022

Published : 05 October 2022

Issue Date : February 2023

DOI : https://doi.org/10.1007/s11069-022-05643-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Agent-based model
Natural hazard
Crowd motion
Find a journal
Publish with us
Track your research

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

We're Hiring!
Help Center

DISASTER INCUBATION THEORY FOR REDUCING THE NATURAL DISASTER RISK: A CASE STUDY OF TSUNAMI, 2004

2021, Academia Letters

Related Papers

Journal of Emergency Management

Dagan Schwartz

The tsunami of December 26, 2004, can be described as one of the worst disasters medical systems have ever had to face. This paper will describe the geophysical properties of tsunamis and their disastrous impact on human beings and infrastructure. Finally, we will present three different modes of response to the tsunami that were present in different provinces in Thailand. These three modes represent different strategies of disaster management, and analyzing each will help to begin understanding how best to respond to the next large-scale natural disaster.

Mohammad Mokhtari

Wiko Setyonegoro

Gloria I. López

Joachim Post

More than 4 million Indonesians live in tsunami-prone areas on the southern and western coasts of Sumatra, Java and Bali. Depending on the location of the tsunamigenic earthquake, in many cases the time to reach a tsunami-safe area is as short as 15 or 20 minutes. To increase the chances of a successful evacuation a comprehensive and thorough planning and preparation is necessary. For this purpose, detailed knowledge on potential hazard impact and safe areas, exposed elements such as people, critical facilities and lifelines, deficiencies in response capabilities and evacuation routes is crucial. The major aims of this paper are (i) to assess and quantify people's response capabilities and (ii) to identify high risk areas which have a high need of action to improve the response capabilities and thus to reduce the risk. The major factor influencing people's ability to evacuate successfully is the factor time. The estimated time of arrival of a tsunami at the coast which determines the overall available time for evacuation after triggering of a tsunami can be derived by analyzing modeled tsunami scenarios for a respective area. But in most cases, this available time frame is diminished by other time components including the time until natural or technical warning signs are received and the time until reaction follows a warning (understanding a warning and decision to take appropriate action). For the time to receive a warning we assume that the early warning centre is able to fulfil the Indonesian presidential decree to issue a warning within 5 minutes. Reaction time is difficult to quantify as here human intrinsic factors as educational level, believe, tsunami knowledge and experience play a role. Although we are aware of the great importance of this factor and the importance to minimize the reaction time, it is not considered in this paper. Quantifying the needed evacuation time is based on a GIS approach. This approach is relatively simple and enables local authorities to implement it at low technical complexity and relatively low cost and time needs. Basic principle is to define the best evacuation route from a given point to the nearest safe area. Here the fastest path from that point to the shelter location has to be found. Thereby the impact of land cover, slope, population density, population age and gender distribution are taken into account as literature studies prove these factors as highly important. Knowing the fastest path and the distance to the nearest safe area together with a spatially distributed pattern of evacuation speed delivers the time needed from each location to a shelter. A shelter location can either be a horizontal area or an evacuation building (vertical evacuation). For both kinds of evacuation target points, one limiting factor can be again time: are the people able to reach the target point within the available time? Especially for evacuation buildings, there is a second possibly limiting factor, namely capacity. In the majority of cases in all of the three study areas where this approach was applied to, capacity was the critical factor instead of time. Consequently, for planning purposes it is essential to know which area can be served by an evacuation building and which areas have to be assigned to a different evacuation target point due to exhausted capacity of the nearest one. The coverage of a building is also derived on basis of a GIS approach using the beforehand derived available and needed evacuation times and detailed population distribution data. Evacuation time and derived evacuable areas are then used to identify high risk areas. In combination with detailed population distribution data, hazard probability and hazard intensity, it is possible to identify areas with high risk and large deficiencies in response capabilities. Often enough, human response capabilities can be increased by thorough disaster planning and thus, the results of this paper provide valuable information for planning authorities to decrease the risk. This paper presents results exemplarily for the study area Kuta, Bali where we tested this approach and where it is also in progress to be implemented by local authorities.

MATEC Web of Conferences

Titi Kurniati

After tsunami disaster hit Aceh and Mentawai Island, Indonesia Government prepare disaster prevention plan for the areas that could be hit by tsunami disaster. Government has predicted that 19 areas could hit by tsunami disaster if big earthquake occur in that areas. Based on that condition, Regional Disaster Management Agency (BPBD) in several cities has prepared the evacuation facilities to reduce the effect of tsunami if the disaster is occurred. Although, the evacuation facilities have been built, however the risk from the impact of tsunami in that areas are still could not be measured. This paper shows the method to measure tsunami disaster risk, and method to determine the priorities handling tsunami impacts in certain area. This risk analysis method was developed based on risk analysis method developed by Federal Emergency Management Agency (FEMA). The risk of tsunami disaster is determined based on three parameters, i.e: threat of tsunami, vulnerability of people, infrastruc...

Fritsay Elle

SSRN Electronic Journal

Anil Minhans

MIMBAR, Jurnal Sosial dan Pembangunan

Emrizal Emrizal

Trevor Smith

Mass Fatality Management following the South Asian Tsunami Disaster: Case Studies in Thailand, Indonesia, and Sri Lanka

Oliver w morgan.

1 Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom

Pongruk Sribanditmongkol

2 Department of Forensic Medicine, Faculty of Medicine, Chiang Mai University, Chaing Mai, Thailand

Clifford Perera

3 Department of Forensic Medicine, University of Ruhuna, Galle, Sri Lanka

Yeddi Sulasmi

4 World Health Organization, Banda Aceh, Indonesia

Dana Van Alphen

5 Pan American Health Organization, Washington, District of Columbia, United States of America

Egbert Sondorp

Following natural disasters, mismanagement of the dead has consequences for the psychological well-being of survivors. However, no technical guidelines currently exist for managing mass fatalities following large natural disasters. Existing methods of mass fatality management are not directly transferable as they are designed for transport accidents and acts of terrorism. Furthermore, no information is currently available about post-disaster management of the dead following previous large natural disasters.

Methods and Findings

After the tsunami disaster on 26 December 2004, we conducted three descriptive case studies to systematically document how the dead were managed in Thailand, Indonesia, and Sri Lanka. We considered the following parameters: body recovery and storage, identification, disposal of human remains, and health risks from dead bodies. We used participant observations as members of post-tsunami response teams, conducted semi-structured interviews with key informants, and collected information from published and unpublished documents.

Refrigeration for preserving human remains was not available soon enough after the disaster, necessitating the use of other methods such as dry ice or temporary burial. No country had sufficient forensic capacity to identify thousands of victims. Rapid decomposition made visual identification almost impossible after 24–48 h. In Thailand, most forensic identification was made using dental and fingerprint data. Few victims were identified from DNA. Lack of national or local mass fatality plans further limited the quality and timeliness of response, a problem which was exacerbated by the absence of practical field guidelines or an international agency providing technical support.

Conclusions

Emergency response should not add to the distress of affected communities by inappropriately disposing of the victims. The rights of survivors to see their dead treated with dignity and respect requires practical guidelines and technical support. Mass fatality management following natural disasters needs to be informed by further field research and supported by a network of regional and international forensic institutes and agencies.

Case studies were conducted to systematically document how the bodies of those killed in the tsunami were managed in Thailand, Indonesia, and Sri Lanka. Many lessons can be learned, though more research is needed.

Editors' Summary

Background..

Some 226,408 people died in the tsunami that hit countries across South Asia on 26 December 2004. As well as providing assistance to the living, a crucially important part of the disaster relief effort was the recovery, identification, and disposal of the dead. However, there is very little consensus about the best way to handle and identify large numbers of bodies. Although natural disasters that kill many people occur frequently, most guidelines for the management of large numbers of dead bodies have come out of the experience gained from transport accidents and from terrorist incidents, and these guidelines are not directly relevant; for example, natural disasters often cause many more deaths than transport accidents or terrorist attacks. It is important for survivors that the bodies of the dead are handled with respect and that the dead are identified so that survivors know what has happened to missing relatives. However, at the same time many people are afraid of what the effect of many dead bodies might be on the living; one belief is that dead bodies are a source of disease. Such a belief can lead to the inappropriately rapid burial of bodies before identification has been done.

Why Was This Study Done?

The tsunami of 2004 provided an opportunity to study four different aspects of how the dead were handled in a number of different countries: how the bodies were recovered, how the bodies were identified, how the bodies were disposed of, and what, if any, were the health effects of the large number of bodies on survivors. The authors wanted to then use the results to make recommendations for use in future natural disasters.

What Did the Researchers Do and Find?

The authors interviewed in person, in writing, and by E-mail key people involved in the handling of the dead in three of the countries affected by the tsunami: Thailand (where 8,345 people died), Indonesia (where 165,708 people died), and Sri Lanka (where 35,399 people died). The authors discovered that there were a huge number of people and agencies involved in the handling of the dead; for example, in Indonesia 42 different organizations were involved in recovering bodies.

None of the countries had sufficient refrigerated storage available to store bodies until they could be identified. Some effective alternatives were used, such as temporary burial in shallow graves—where the temperature is lower than in the ambient air—with the intention of exhuming the bodies later for identification. However, many bodies were hurriedly buried in mass graves because they were decomposing; these bodies were almost impossible to identify.

Methods and efficiency of identification varied between and within countries. One hospital in Sri Lanka excelled by systematically photographing all bodies brought in and recording sex, height, and personal effects: 87% of the bodies brought here were identified. But in most areas rates of identification were much lower. It seemed that simple methods of identification were the most useful: photographs taken quickly before the bodies started to decompose, dental records, and personal effects found on the bodies. DNA analysis was only useful for a small number of bodies.

When it came to disposal of the bodies, again procedures differed widely, and in some cases were dictated by religious needs—for example, in some Muslim communities all bodies were buried within 24 hours, making counting and identification of the dead very difficult. Mass graves were often used, but these caused problems; for example, haphazard arrangement of the bodies meant that later exhumation and identification would be impossible.

The authors concluded that there was virtually no health impact of the dead bodies on survivors. Other studies found that there were no epidemics among the surviving population, and that most effects were on those who handled bodies in temporary morgues, where there were the expected variety of sharp-implement injuries and mucosal splashes with body fluids, along with heat stress and dehydration due to overuse of personal protective equipment such as respirators.

What Do These Findings Mean?

How efficiently bodies were handled after the tsunami varied widely across and even within countries. The authors conclude that much of this variety was because of a lack of national or local plans for such mass fatalities, along with a lack of practical field guidelines. There was little coordination of all of the different organizations involved. However, in some places bodies were handled very well. The authors drew on their findings to suggest guidelines for the possible future management of large numbers of bodies, and also suggested that further research should be done. Reassuringly, the large numbers of bodies did not cause problems for the survivors, so in the future survivors should be encouraged to systematically identify the dead rather than rushing to bury them because of fear of disease.

Additional Information.

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0030195 .

• The World Heath Organization has a Web page that brings together much information on the tsunami and its aftermath

• News from the United Nations special envoy for the tsunami can be found on its Web site

• An article published by the Pan American Health Organization called “Disaster Myths That Just Won't Die”

• Field guidelines for managing mass fatality natural disasters developed by an international workshop following the tsunami

Introduction

Globally, there are at least six natural disasters every year that kill more than 500 people [ 1 ]. Although management of human remains is one of the most difficult aspects of disaster response, there are currently no technical guidelines for dealing with large numbers of dead bodies following natural disasters. Existing methods developed for transport accidents and acts of terrorism are not directly transferable as they are designed for a smaller number of victims within a criminal or international medico-legal framework [ 2 – 4 ]. Developing appropriate guidelines for natural disasters is further complicated by the absence of information about post-disaster management of the dead following previous disasters.

Experience from the last 25 y suggests that a common reaction following mass fatality natural disasters is fear that dead bodies will cause epidemics [ 5 , 6 ]. This fear has frequently been used to justify rapid burial of human remains in mass graves with no identification [ 7 ]. Consequences of such mismanagement include increased psychological distress for survivors and legal problems affecting inheritance, compensation, insurance, and re-marriage of spouses [ 7 – 9 ]. Diplomatic tensions may also occur when foreign tourists are involved.

The tsunami disaster in South Asia on 26 December 2004 was one of the largest natural disasters in recent times ( Table 1 ). Management of the dead varied remarkably between affected countries, with the biggest international forensic investigation in history following a natural disaster mounted in Thailand, while in other countries, local authorities were left to cope as best they could. The size of the disaster and the different responses provided an important opportunity to systematically document and learn about methods for managing human remains following large natural disasters. In this paper we present our findings from three case studies in Indonesia, Sri Lanka, and Thailand, and make recommendations for future disasters.

Natural Disasters That Have Caused at Least 100,000 Deaths between 1900 and 2005

An external file that holds a picture, illustration, etc.
Object name is pmed.0030195.t001.jpg

We used a descriptive multiple-case study design [ 10 ]. The study was deliberately designed to compare and contrast the management of a large number of fatalities in different countries affected by the tsunami. Each case was a different country. Our resources enabled us to select three countries. We therefore selected countries with (1) a large number of fatalities caused by the tsunami and (2) different levels of sophistication used to manage the dead.

At the beginning of the study we determined to examine four parameters: (1) methods of body recovery and storage, (2) methods of victim identification, (3) methods of disposal of human remains, and (4) public health issues associated with the management of a large number of dead bodies. Where possible, we used triangulation, whereby data were sought from different sources to supplement and validate observations. Several authors (P. S., C. P., Y. S., and D. V. A.) made participant observations while working as members of post-tsunami response teams in the affected countries. Semi-structured interviews using a checklist/question prompt were conducted with key informants by one of the authors (O. W. M.) between 18 February and 4 March 2005. Purposive sampling [ 11 ] was used to select individuals with operational and managerial responsibility for the management of the dead. Where face-to-face interviews were not possible, interviews were conducted by telephone or E-mail. Interviews were conducted in English or with the aid of an interpreter recruited in each country specifically for the study. In each country we sought published and unpublished documents (situation reports, official statistics, evaluation reports, technical documents, guidelines for victim identification, and public health reports) from national ministries of health and government offices, the World Health Organization (WHO), non-governmental organisations, and voluntary groups. We analysed field and interview notes thematically and inductively (generating ideas from the data), using the study parameters as a framework for analysis [ 10 , 11 ].

We selected Thailand, Sri Lanka, and Indonesia for this study. The number of fatalities in each of these countries has been estimated as 8,345, 35,399, and 165,708, respectively [ 1 ]. Participant observers (P. S., C. P., Y. S., and D. V. A.) spent at least 4 wk working in affected areas. Interviews were conducted with 40 key informants from the voluntary sector ( n = 9), ministries of health ( n = 8), military ( n = 6), WHO ( n = 5), police ( n = 5), hospital staff ( n = 4), and government officials ( n = 3). Reviewed documents included WHO situation reports ( n = 37) [ 12 ], evaluation or surveillance reports ( n = 4), and technical documents ( n = 4).

Body Recovery and Storage

Body recovery is the first phase of the management of dead bodies. In all countries it was characterised as being initially chaotic and uncoordinated, involving a large number of different actors. In Thailand, body recovery was done by foreign tourists, local volunteers, Thai non-governmental organisations that specialise in body recovery following disasters (Po-Tek-Tung Foundation and Ruam-Ka-Tan-Yu Foundation), the military, and the police. In Indonesia, the body recovery phase lasted several months ( Figure 1 ), and, under the coordination of the military, 42 different organisations were involved. In Sri Lanka, body recovery was done almost exclusively by the affected communities themselves. In all cases, bodies were taken to multiple locations, and relatives did not know where their family members had been taken.

An external file that holds a picture, illustration, etc.
Object name is pmed.0030195.g001.jpg

Districts include Pantai Barat, Pantai Timur, Aceh Besar, and Band Aceh.

(Source: Badan Koordinasi Nasional Penanggulangan Bencana Dan Penanganan Pengungsi—BAKORNAS PBP)

None of the countries had sufficient refrigerated storage immediately available. In Thailand, the only country able to mobilise large numbers of refrigerated containers, it took about 2 wk to provide about 100 containers needed to store around 3,600 bodies. Temporary burial in shallow trench graves (about 1 m deep) was used effectively to store about 600 bodies. Effective use of dry ice proved difficult: when placed on top of the bodies it damaged them because of its low temperature, while not providing sufficient overall cooling to stop decomposition. Handling large quantities of dry ice also caused many skin burns among individuals handling it [ 13 ]. However, it was found that an effective method was to build a small wall of dry ice surrounding a group of bodies, and then to cover the group with a tent or tarpaulin.

Identification

Victim identification differed considerably between the three countries. In Indonesia, simple visual identification was attempted in the first few days. However the sheer number of bodies meant that it was impossible to arrange viewing for all bodies or store the bodies for later identification. Nevertheless, the body recovery teams successfully identified over 500 victims using personal effects such as identity cards and jewellery, and even mobile telephone SIM cards.

In Sri Lanka, the Centre for National Operations (an ad hoc governmental disaster management committee) mandated that local authorities take photographs and collect fingerprints of all the victims. However, because of damaged communications infrastructure, these instructions only arrived after 2 or 3 d, by which time decomposition had distorted facial features. In all, many hundreds of photographs were taken by police photographers, medical staff, journalists, and freelance photographers. In some cases, the films were not developed as there were insufficient funds to pay either the developer or freelance photographers. There were, however, outstanding examples, such as the hospital at Matara, where digital photographs were taken and basic information recorded (sex, height, and personal effects) for each body as it was brought into the hospital. Over 87% of the 547 victims handled by the hospital were identified [ 14 ]. Foreign victims, largely found in the eastern part of the country, were sent directly to the capital city Colombo, where an Identification Centre was established with support from the British government. During 2005, the Identification Centre also supervised six major exhumations to search for missing foreigners who were buried along with Sri Lankan nationals. A total of 155 bodies were examined by the disaster victim identification team. Analysis of DNA and dental records was used to successfully identify these individuals, who came from 18 different countries.

On 27 December, the first Thai forensic teams, many travelling independently under their institutes, started arriving in the affected areas of southern Thailand. They rapidly set up basic identification facilities in local temples. During the first 7–10 d of operations, Thai forensic teams examined around 3,600 bodies. The examination included external examination, photography, and recording of all personal effects. Fingerprints were taken from about 600 cadavers. DNA samples were collected from almost all bodies during the first few days, and included hair and soft tissues and, later, ribs and teeth. During this initial phase, Thai forensic teams identified about 1,100 human remains and released them to the families. In addition, about 500 bodies were identified and released to relatives by local physicians and police without the support of forensic specialists.

After the first week, forensic teams from other countries started to arrive in Thailand. They formed an international disaster victim identification committee to work in collaboration with the Royal Thai Police [ 15 ]. In Phuket, the committee's information centre was established with the financial support of the Australian government. The Thai government decided to combine the efforts of the Thai forensic experts, the Thai Royal Police, and international disaster victim identification committee teams, and on 13 January the Thai Tsunami Victim Identification (TTVI) centre was established in Phuket [ 16 ]. In collaboration with Interpol, the TTVI established a central mortuary in Phuket, sponsored by the Norwegian government. It was decided to examine or re-examine all 3,777 remaining victims using Interpol's standard protocol [ 17 ]. This included external examination, personal effects, photographs, fingerprints, forensic pathological examination, dental examination, and DNA sampling from bone and teeth. As of 27 July 2005, 7 mo after the disaster, TTVI had identified 2,010 victims, with over 1,800 cadavers remaining unidentified [ 18 ]. Sixty-one percent of victims were identified by TTVI using dental examinations ( n = 1,235), 19% using fingerprint records ( n = 378), 1.3% using DNA analysis ( n = 26), and 0.3% using physical evidence ( n = 6). In a further 18% of cases ( n = 365), more than one type of evidence was used [ 19 ].

Disposal of Human Remains

In Thailand, unidentified victims were stored in refrigerated containers during identification activities. Bodies that were identified were disposed of by cremation or burial according to local custom. Bodies of foreign victims were repatriated by their respective embassies. Around Banda Aceh, Indonesia, there were 14 mass graves, the largest, at Lambarro, reportedly containing 60,000–70,000 victims. Finding suitable government land for these large graves was difficult, and in some instances graves were sited very close to communities. In the areas surrounding Banda Aceh, smaller village-level graves were often used. Many were constructed rapidly, sometimes within the village itself. This has caused difficulty for returning survivors wanting to exhume and re-locate the graves to outside the village. In many rural areas, there was no formal body recovery and disposal of remains. In Sri Lanka, most human remains were buried after 3 or 4 d. Common graves, in which bodies were buried haphazardly in several layers, were sited largely within existing cemeteries. However, within some Muslim communities the deceased were buried within the first 24 h according to custom, making it difficult for the local authorities to identify and count the dead. Additionally, there were concerns that some of the deceased, who were buried as Muslims, may have been from other religious groups.

Health Impact from Dead Bodies

Shortly after the tsunami, WHO and national governments established early warning disease surveillance. No epidemics among the surviving populations were identified in the weeks after the tsunami [ 20 ]. In Banda Aceh, Indonesia, it took some 2 mo to bury the thousands of bodies ( Figure 1 ). In spite of the prolonged presence of dead bodies, no epidemics occurred [ 21 ]. Among individuals handling human remains (recovery, identification, and disposal), we did not identify any reports of “occupational” infections. A health and safety assessment of temporary morgues in Thailand by the United States Centers for Disease Control and Prevention and the Thai Ministry of Public Health reported sharp-implement injuries and mucosal splashes with body fluids as well as heat stress and dehydration due to overuse of personal protective equipment such as respirators [ 13 ]. A questionnaire survey conducted by the Thai Ministry of Public Health of around 200 individuals involved in body recovery did not identify any reports of infectious disease (S. Sirituttanapruk, personal communication). Back injuries, caused by lifting bodies into trucks, were reported by Indonesian military. Body recovery teams faced potential injury risk from working among debris, especially from earthquake-damaged buildings. In Sri Lanka, most dead bodies were taken to local hospitals, which had an indirect health impact by disrupting the provision of medical assistance to survivors and threatening to close hospitals because of the smell of decomposition.

Coordination and Preparedness

In each country, a large number of individuals and organisations were involved in managing the dead. Body recovery involved the affected community, voluntary organisations, the police, and the military. Doctors, medical staff, and forensic specialists were involved in death certification and collecting post-mortem data. National police forces and consulates or embassies were involved in collecting ante-mortem data (information about the deceased collected before death, such as dental or fingerprint records). Disposal of the bodies was done by the military or police, who also had legal responsibility for victim identification. No single person or organisation had a clear mandate to coordinate the process of collecting, identifying, and disposing of the dead, either nationally or locally. None of the countries had mass fatality plans.

The technical and logistical challenges of recovering and identifying victims after the tsunami were exceptional. The hot climate increased the rate of decomposition: bloating and discolouration of the human face rendered visual identification almost impossible after 24–48 h. Odours from decomposition caused concern about epidemics, and led local communities and national authorities to sanction mass (unplanned) burial without identification. Refrigeration for preserving human remains was not available soon enough, and no country had sufficient forensic capacity to identify thousands of victims. Lack of national or local mass fatality plans further limited the quality and timeliness of response, as did the absence of practical field guidelines or an international agency providing technical support.

Strengths and Limitations

Unlike study designs that make statistical inferences about a population, case study designs are suitable for describing and understanding why events occur and for generating hypotheses for future study. Therefore, rather than select cases to be “representative”, we selected cases to highlight a range of experience. A case study design was especially appropriate in this situation because we had no previous information about how the management of mass fatalities is undertaken following natural disasters (and hence no a priori hypotheses to test).

Conducting research during a humanitarian emergency presents many challenges. For example, individuals from relief agencies and governmental bodies have heavy workloads and are under considerable stress. Consequently, allocating time to participate in research activities may be of secondary importance. The stressful nature of disaster response leads to a high turnover of staff, and some of the key informants were no longer available for interview during our fieldwork. We attempted to contact these individuals by telephone and E-mail, but this was not always possible. Finally, we found that the management of dead bodies was politically very sensitive, both at local and national government levels. For these reasons, it is likely that some key informants were not included.

Storage, Identification, and Burial

Cold storage is vital for preserving evidence for identification. None of the countries could quickly mobilise sufficient refrigerated containers after the tsunami, and in Thailand, where refrigerated containers did eventually become available, most of the bodies had decomposed considerably by that time. The use of dry ice was reasonably effective, but it was difficult to manage, logistically intensive, and a significant cause of work-related injury. An alternative is normal ice (frozen water), as used after the Bali bombing in 2002 [ 22 ]. However, large quantities of melted water are produced that contain products of decomposition, which are likely to create additional management problems [ 22 , 23 ]. For large numbers of dead bodies, the most practical option is temporary burial in trench graves. The temperature underground is lower than at the surface, and burial acts as “natural refrigeration”. At 1.2 m depth, bodies have been well preserved for several months [ 24 ]. However, this approach must include careful recording of the location of each body and good communications with the public and media, who may mistakenly interpret this as disposal of victims without identification.

The simplest form of identification used after the tsunami was visual recognition and photographs of fresh bodies. In the absence of cold storage, this needs to be done rapidly. After 24–48 h without cooling, gases build up within the body, swelling the face and lips and forcing the tongue out of the mouth, making visual identification unreliable. The epidermis detaches from the body, leaving un-pigmented skin, giving the appearance of a white cadaver, even in dark-skinned individuals [ 25 ]. Further, while visual identification is relatively simple, it will result in some misidentification. Injuries to the body, or the presence of blood, fluids, or dirt, especially around the head, will reduce the chance of correct recognition. Following the Bali bombing, visual identification was incorrect in about one-third of victims [ 22 ]. The effectiveness of this method following natural disasters is unknown, although reports from one hospital in Sri Lanka suggest that it can have good results [ 14 ].

Forensic techniques such as dental, fingerprint, and DNA analysis are effective because they can identify decomposed or damaged bodies. However, for large disasters they require many trained specialists and are resource intensive. Most importantly, these methods are only useful if comparative data are available. While fingerprint data are recorded for Thai citizens when identity cards are issued, and many Western victims had dental records, comparative data may be scarce in many parts of the world. Few countries have the capacity for DNA collection and analysis following large natural disasters. DNA identification is expensive, technically demanding, and logistically difficult to implement on a large scale [ 2 ]. In the case of the tsunami in Thailand, it proved to be a relatively unimportant method of identification. DNA identification should not be considered as a first-line method of identification, but rather should only be implemented when physical, fingerprint, and dental methods have been unsuccessful [ 26 ].

Communal burial may be necessary when the number of human remains is large, as happened in Sri Lanka and Indonesia. Haphazard commingling of cadavers in mass graves makes future exhumations extremely difficult. Communal graves should be clearly marked, with bodies well organised and buried in one layer. All affected countries had difficulty finding locations for graves while considering the wishes of the local community, access for relatives, and land ownership. Although few cremations took place in the countries studied, they should be avoided because they make identification exceptionally difficult, require large amounts of fuel, and rarely achieve complete incineration, necessitating burial of partially burned cadavers.

Health Risks

The fear that dead bodies will cause epidemics among survivors, often encouraged by the media, prejudices proper handling and identification [ 6 , 27 ]. The unpredictable and chaotic nature of disasters means epidemiological evidence about associated infections is unavailable. A risk assessment suggests that the risk is small for members of the public and is primarily due to diarrhoea from drinking water contaminated with faecal matter from dead bodies [ 28 ]. This assessment of low risk, along with anecdotal observations over the last 20 y [ 6 ] and the absence of outbreaks in Banda Aceh despite the presence of several thousand bodies, should be considered the most convincing evidence to date that dead bodies pose a negligible threat to the general public after natural disasters.

Individuals who handle the dead (recovery, identification, and disposal) may be exposed to blood, body fluids, or faeces that contain chronic infections such as hepatitis B and C, HIV, tuberculosis, and gastrointestinal pathogens [ 28 ]. Simple precautions such as wearing gloves and washing hands will reduce transmission and hence reduce risks considerably. We did not identify any reports of “occupational” infections among body handlers. However, considering the relatively long incubation period for blood-borne infections and the low likelihood of testing among these individuals, it may have been too early to detect their incidence. Long term follow-up of this group is needed.

None of the countries had a single organisation with jurisdiction for recovery, identification, and disposal of bodies. Not only did this cause tension, but also added to the confusion and stress of relatives searching for family members. The lack of mass fatality plans meant that these issues had to be worked out during the response.

Recommendations and Conclusions

The South Asian tsunami in 2004 was an extreme natural event resulting in many thousands of fatalities. Several important lessons can be highlighted for future disasters ( Box 1 ). Until now, the failure to document and learn following mass fatality natural disasters means that similar mistakes occur time and time again. In May 2005, WHO, the Pan American Health Organization, and the International Committee of the Red Cross/Red Crescent convened an international workshop in the city of Lima, Peru, to share the experience of the tsunami and other previous disasters and to develop a first responders' manual for mass fatality natural disasters. These practical field guidelines were published in April 2006 [ 29 ].

Box 1. Recommendations for the Management of the Dead after Natural Disasters

Health Impacts

• The health risk to the general public of large numbers of dead bodies is negligible

• Drinking water must be treated to avoid possible diarrhoeal diseases

• Body handlers should follow universal precautions for blood and body fluids, wear gloves, and wash their hands

Body Storage

• Refrigerated containers provide the best storage, if available

• Temporary burial in trench graves can be used if refrigeration is not available

Body Identification

• Visual recognition or photographs of fresh bodies are the simplest forms of non-forensic identification and should be attempted after all natural disasters

• If resources and comparative data are available, simpler methods can be supplemented by forensic techniques (dental, fingerprint, and DNA analysis)

Body Disposal

• Communal graves may be necessary following large disasters

• Bodies should be buried in one layer to facilitate future exhumation

• Graves should be clearly marked

Coordination

• A named person/organisation should have an agreed mandate to coordinate the management of dead bodies

Preparedness

• Mass fatality plans should be included in national and local disaster preparedness activities

• Systematic documentation about how the dead are managed in future disasters is needed to learn from them

Communications

• Close working with the media is needed to avoid misinformation and to promote the rights of the survivors to see their dead treated with dignity and respect

Management of the dead has important socio-cultural implications, and emergency response should not add to the distress of affected communities through inappropriate handling and disposal of the victims. Promoting the rights of the survivors to see their dead treated with dignity and respect requires guidelines and technical support, which must be informed by further field research ( Box 2 ). Moreover it is important that the international community promotes the rights of victims and communities by including standards for the management of the dead in existing humanitarian Sphere Project guidelines [ 30 ] (the Sphere Project is a collaboration of over 400 organisations that agree on minimum standards in disaster relief). Finally, no country has sufficient capacity to respond to very large disasters, and networks of countries, forensic institutes, and international agencies such as Interpol and WHO are needed to provide assistance for the management of the dead following future disasters.

Box 2. Areas of Further Research in the Management of Dead Bodies following Natural Disasters

• Different methods of body storage where refrigeration is not available.

• Hydrological characteristics of mass communal burial and measures to avoid groundwater contamination.

• Epidemiological studies of infectious and non-infectious health risks for individuals recovering and identifying dead bodies.

• Methods for victim identification in situations where specialist forensic support is limited or unavailable, especially using visual and fingerprint identification.

• Strategies for developing regional and international forensic capacity and resources.

• Systems and protocols for managing information about the dead and missing.

• Social and cultural impacts of bereavement and the imperative to identify missing relatives and friends.

• Social and cultural acceptability of technical approaches for identification.

• Community-level approaches to disaster preparedness and response with regard to the management of the dead.

Acknowledgments

We would like to thank Jean Luc Poncelet and Ciro Ugarte at the Pan American Health Organization. Claude de Ville de Goyet provided valuable comments about the study protocol, facilitated the fieldwork, and provided comments on the paper. William Black at the Pan American Health Organization and Katri Jalava from the European Programme for Field Epidemiology Training provided comments on drafts of this paper.

Author contributions. OWM and ES designed the study. OWM conducted the interviews. PS, CP, YS, and DVA provided data from field observations. All authors contributed to the analysis and writing of the paper.

Abbreviations

Citation: Morgan OW, Sribanditmongkol P, Perera C, Sulasmi Y, Van Alphen D, et al. (2006) Mass fatality management following the South Asian tsunami disaster: Case studies in Thailand, Indonesia, and Sri Lanka. PLoS Med 3(6): e195. DOI: 10.1371/journal.pmed.0030195

Funding: This project was supported by a grant from the Pan American Health Organization. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Université Catholique de Louvain. EM-DAT: The International Disaster Database. 2005 Available: http://www.em-dat.net . Accessed 10 August 2005. [ Google Scholar ]
Technical Working Group for Mass Fatality. Forensic Identification (2005 June) Mass fatality incidents: A guide for human forensic identification. Washington (D. C.): Office of Justice Programs, United States Department of Justice; Available: http://www.ncjrs.org/pdffiles1/nij/199758.pdf . Accessed 8 September 2005. [ Google Scholar ]
INTERPOL. Disaster victim identification—Guide. 2005 Available: http://www.interpol.int/Public/DisasterVictim/Guide/Default.asp . Accessed 21 August 2005. [ Google Scholar ]
Home Office. Guidance on dealing with fatalities in emergencies. London: UK Resilience; 2004. Available: http://www.ukresilience.info/publications/fatalities.pdf . Accessed 5 April 2005. [ Google Scholar ]
de Ville de Goyet C. Maladies transmissibles et surveillance épidémiologique lors de désastres naturels. Bull World Health Organ. 1979; 57 :153–165. [ PMC free article ] [ PubMed ] [ Google Scholar ]
de Ville de Goyet C. Stop propagating disaster myths. Lancet. 2000; 356 :762–764. [ PubMed ] [ Google Scholar ]
de Ville de Goyet C. Epidemics caused by dead bodies: A disaster myth that does not want to die. Rev Panam Salud Publica. 2004; 15 :297–299. [ PubMed ] [ Google Scholar ]
Perera C. After the tsunami: Legal implications of mass burials of unidentified victims in Sri Lanka. PLoS Med. 2005; 2 :e185. doi: 10.1371/journal.pmed.0020185. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Weiss M, Saraceno B, Saxena S, van Ommeren M. Mental health in the aftermath of disasters: Consensus and controversy. J Nerv Ment Dis. 2003; 191 :611–615. [ PubMed ] [ Google Scholar ]
Yin RK. Case study research: Design and methods, 3rd ed. London: Sage Publications; 2003. 179 pp. [ Google Scholar ]
Bowling A. Research methods in health: Investigating health and health services, 2nd ed. Buckingham: Open University Press; 2002. 486 pp. [ Google Scholar ]
World Health Organization. South Asia tsunami situation reports. 2005 Available: http://www.who.int/hac/crises/international/asia_tsunami/sitrep/en/index.html . Accessed 7 January 2006. [ Google Scholar ]
Centers for Disease Control and Prevention. Health concerns associated with disaster victim identification after a tsunami—Thailand, December 26, 2004–March 31, 2005. MMWR Morb Mortal Wkly Rep. 2005; 54 :349–352. [ PubMed ] [ Google Scholar ]
Padmitilaka K. Tsunami Disaster—2004. Emergency management and aftercare in General Hospital Matara. Matara (Sri Lanka): Matara General Hospital; 2005. 15 pp. [ Google Scholar ]
Interpol. Interpol's operational response to the tsunami disaster. 2005 Available: http://www.interpol.net/Public/asiandisaster/Synopsis20050126.asp . Accessed 2 April 2005. [ Google Scholar ]
Thai Tsunami Victim Identification. Official Thai tsunami information center. 2005 Available: http://www.csiphuket.com . Accessed 7 August 2005. [ Google Scholar ]
Interpol. Disaster victim identification—Forms: Instructions for use of the Interpol DVI form set. 2005 Available: http://www.interpol.int/Public/DisasterVictim/Forms/Default.asp . Accessed 2 September 2005. [ Google Scholar ]
Thai Tsunami Victim Identification. TTVI press release 2000th identification. 2004 July Available: http://www.csiphuket.com/2000th.html . Accessed 7 August 2005. [ Google Scholar ]
Sribanditmongkol P, Pongpanitanont P, Porntrakulseree N, Petju M, Kunaratanapruk S, et al. Forensic aspect of disaster casualty management. WHO Conference on the Health Aspects of the Tsunami Disaster in Asia; Phuket, Thailand; 4–6 May 2005. Geneva: World Health Organization; 2005. Available: http://www.who.int/hac/events/tsunamiconf/presentations/en/index.html . Accessed 6 April 2006. [ Google Scholar ]
World Health Organization. Three months after the Indian Ocean earthquake-tsunami. 2005 Available: http://www.who.int/hac/crises/international/asia_tsunami/3months/report/en/print.html . Accessed 3 August 2005. [ Google Scholar ]
World Health Organization. Epidemic-prone disease surveillance and response after the tsunami in Aceh Province, Indonesia. Wkly Epidemiol Rec. 2005; 80 :160–163. [ PubMed ] [ Google Scholar ]
Lain R, Griffiths C, Hilton M. Forensic dental and medical response to the Bali bombing. Med J Aust. 2003; 179 :362–365. [ PubMed ] [ Google Scholar ]
Centers for Disease Control and Prevention. Disposing of liquid waste from autopsies in tsunami-affected areas: Interim guidance from the Centers for Disease Control and Prevention. 2005 Available: http://www.bt.cdc.gov/disasters/tsunamis/pdf/tsunami-autopsyliquidwaste.pdf . Accessed 6 April 2006. [ Google Scholar ]
Mann R, Bass W, Meadows L. Time since death and decomposition of the human body: Variables and observations in case and experimental field studies. J Forensic Sci. 1990; 35 :103–111. [ PubMed ] [ Google Scholar ]
Vass A, Barshick S, Sega G, Caton J, Skeen J, et al. Decomposition chemistry of human remains: A new methodology for determining the postmortem interval. J Forensic Sci. 2002; 47 :542–553. [ PubMed ] [ Google Scholar ]
Hirsch C, Brondolo T, Butcher B. Report to H. E. Dr. Surachai, Minister of Public Health, Thailand, and Dr. William Aldis, WHO Representative to Thailand World Health Organization. Assessment of victim identification operations: Thailand tsunami disaster. New York: City of New York Office of Chief Medical Examiner; 2005. 11 pp. [ Google Scholar ]
Morgan O, de Ville de Goyet C. Dispelling disaster myths about dead bodies and disease: The role of scientific evidence and the media. Rev Panam Salud Publica. 2005; 18 :33–36. [ PubMed ] [ Google Scholar ]
Morgan O. Infectious disease risk of dead bodies following natural disasters. Rev Panam Salud Publica. 2004; 15 :307–312. [ PubMed ] [ Google Scholar ]
Morgan O, Tidball-Binz, Van Alphen D, editors. Management of dead bodies after disasters: A field manual for first responders. Washington (D. C.): Pan American Health Organization; 2006. Available: http://www.paho.org/english/dd/ped/DeadBodiesFieldManual.htm . Accessed 22 April 2006. [ Google Scholar ]
Sphere Project. Sphere handbook, 2004 revised ed. 2004 Available: http://www.sphereproject.org/content/view/27/84/lang ,English. Accessed 22 November 2005. [ Google Scholar ]

Was Today’s Earthquake Connected to the Solar Eclipse?

The tidal forces on Earth grow as the sun, moon and Earth begin to align, a configuration that can lead to a solar eclipse. But the results of several studies of the relationship between earthquakes and tides are inconclusive, a geophysicist said.

Share full article

An image of the total solar eclipse in August 2017.

By Katrina Miller

April 5, 2024

With a total solar eclipse set to pass through the United States on Monday, it is easy to imagine a linkage between unusual events in the heavens and on Earth. But geoscientists were cautious about making such a connection.

Earthquakes happen along fault lines, or cracks between two blocks of rock on Earth’s crust. Tides stretch and squish the land on Earth just as they contribute to waves in the ocean, and those tidal forces grow as the sun, moon and Earth begin to align — a configuration that sometimes creates a solar eclipse.

One theory is that this may introduce additional stress along Earth’s fault lines.

“We do know that the relative position of the Earth and the moon and the sun does exert tidal forces,” said William Frank, a geophysicist at the Massachusetts Institute of Technology. “And we know that changes the stress that can be on a fault that can host an earthquake.”

But the results of several studies of the relationship between earthquakes and tides are inconclusive, according to Seth Stein, a geophysicist at Northwestern University. “If there’s any effect, it would be incredibly weak,” he said.

Earthquakes are driven most often by the motion between two tectonic plates making up Earth’s crust — either when two plates slide along each other in opposite directions, or when one slides under the other.

Both types of movements introduce strain at the junction, which often gets relieved by an earthquake.

But at the moment, it’s difficult to say that plate motion was responsible for the quake that shook the Northeast Friday morning.

“It’s not quite as obvious, because there is no tectonic plate boundary that is active,” Dr. Frank said.

Still, he added, fault lines from past activity are everywhere on Earth’s crust.

“Some of these faults can still be storing stress and be closure to failure,” he said. “And it can just require a little bit more to push it over the edge.”

Katrina Miller is a science reporting fellow for The Times. She recently earned her Ph.D. in particle physics from the University of Chicago. More about Katrina Miller

What to know about the crisis of violence, politics and hunger engulfing Haiti

A woman carrying two bags of rice walks past burning tires

A long-simmering crisis over Haiti’s ability to govern itself, particularly after a series of natural disasters and an increasingly dire humanitarian emergency, has come to a head in the Caribbean nation, as its de facto president remains stranded in Puerto Rico and its people starve and live in fear of rampant violence.

The chaos engulfing the country has been bubbling for more than a year, only for it to spill over on the global stage on Monday night, as Haiti’s unpopular prime minister, Ariel Henry, agreed to resign once a transitional government is brokered by other Caribbean nations and parties, including the U.S.

But the very idea of a transitional government brokered not by Haitians but by outsiders is one of the main reasons Haiti, a nation of 11 million, is on the brink, according to humanitarian workers and residents who have called for Haitian-led solutions.

“What we’re seeing in Haiti has been building since the 2010 earthquake,” said Greg Beckett, an associate professor of anthropology at Western University in Canada.

Haitians take shelter in the Delmas 4 Olympic Boxing Arena

What is happening in Haiti and why?

In the power vacuum that followed the assassination of democratically elected President Jovenel Moïse in 2021, Henry, who was prime minister under Moïse, assumed power, with the support of several nations, including the U.S.

When Haiti failed to hold elections multiple times — Henry said it was due to logistical problems or violence — protests rang out against him. By the time Henry announced last year that elections would be postponed again, to 2025, armed groups that were already active in Port-au-Prince, the capital, dialed up the violence.

Even before Moïse’s assassination, these militias and armed groups existed alongside politicians who used them to do their bidding, including everything from intimidating the opposition to collecting votes . With the dwindling of the country’s elected officials, though, many of these rebel forces have engaged in excessively violent acts, and have taken control of at least 80% of the capital, according to a United Nations estimate.

Those groups, which include paramilitary and former police officers who pose as community leaders, have been responsible for the increase in killings, kidnappings and rapes since Moïse’s death, according to the Uppsala Conflict Data Program at Uppsala University in Sweden. According to a report from the U.N . released in January, more than 8,400 people were killed, injured or kidnapped in 2023, an increase of 122% increase from 2022.

“January and February have been the most violent months in the recent crisis, with thousands of people killed, or injured, or raped,” Beckett said.

Armed groups who had been calling for Henry’s resignation have already attacked airports, police stations, sea ports, the Central Bank and the country’s national soccer stadium. The situation reached critical mass earlier this month when the country’s two main prisons were raided , leading to the escape of about 4,000 prisoners. The beleaguered government called a 72-hour state of emergency, including a night-time curfew — but its authority had evaporated by then.

Aside from human-made catastrophes, Haiti still has not fully recovered from the devastating earthquake in 2010 that killed about 220,000 people and left 1.5 million homeless, many of them living in poorly built and exposed housing. More earthquakes, hurricanes and floods have followed, exacerbating efforts to rebuild infrastructure and a sense of national unity.

Since the earthquake, “there have been groups in Haiti trying to control that reconstruction process and the funding, the billions of dollars coming into the country to rebuild it,” said Beckett, who specializes in the Caribbean, particularly Haiti.

Beckett said that control initially came from politicians and subsequently from armed groups supported by those politicians. Political “parties that controlled the government used the government for corruption to steal that money. We’re seeing the fallout from that.”

Haiti Experiences Surge Of Gang Violence

Many armed groups have formed in recent years claiming to be community groups carrying out essential work in underprivileged neighborhoods, but they have instead been accused of violence, even murder . One of the two main groups, G-9, is led by a former elite police officer, Jimmy Chérizier — also known as “Barbecue” — who has become the public face of the unrest and claimed credit for various attacks on public institutions. He has openly called for Henry to step down and called his campaign an “armed revolution.”

But caught in the crossfire are the residents of Haiti. In just one week, 15,000 people have been displaced from Port-au-Prince, according to a U.N. estimate. But people have been trying to flee the capital for well over a year, with one woman telling NBC News that she is currently hiding in a church with her three children and another family with eight children. The U.N. said about 160,000 people have left Port-au-Prince because of the swell of violence in the last several months.

Deep poverty and famine are also a serious danger. Gangs have cut off access to the country’s largest port, Autorité Portuaire Nationale, and food could soon become scarce.

Haiti's uncertain future

A new transitional government may dismay the Haitians and their supporters who call for Haitian-led solutions to the crisis.

But the creation of such a government would come after years of democratic disruption and the crumbling of Haiti’s political leadership. The country hasn’t held an election in eight years.

Haitian advocates and scholars like Jemima Pierre, a professor at the University of British Columbia, Vancouver, say foreign intervention, including from the U.S., is partially to blame for Haiti’s turmoil. The U.S. has routinely sent thousands of troops to Haiti , intervened in its government and supported unpopular leaders like Henry.

“What you have over the last 20 years is the consistent dismantling of the Haitian state,” Pierre said. “What intervention means for Haiti, what it has always meant, is death and destruction.”

Image: Workers unload humanitarian aid from a U.S. helicopter at Les Cayes airport in Haiti, Aug. 18, 2021.

In fact, the country’s situation was so dire that Henry was forced to travel abroad in the hope of securing a U.N. peacekeeping deal. He went to Kenya, which agreed to send 1,000 troops to coordinate an East African and U.N.-backed alliance to help restore order in Haiti, but the plan is now on hold . Kenya agreed last October to send a U.N.-sanctioned security force to Haiti, but Kenya’s courts decided it was unconstitutional. The result has been Haiti fending for itself.

“A force like Kenya, they don’t speak Kreyòl, they don’t speak French,” Pierre said. “The Kenyan police are known for human rights abuses . So what does it tell us as Haitians that the only thing that you see that we deserve are not schools, not reparations for the cholera the U.N. brought , but more military with the mandate to use all kinds of force on our population? That is unacceptable.”

Henry was forced to announce his planned resignation from Puerto Rico, as threats of violence — and armed groups taking over the airports — have prevented him from returning to his country.

An elderly woman runs in front of the damaged police station building with tires burning in front of it

Now that Henry is to stand down, it is far from clear what the armed groups will do or demand next, aside from the right to govern.

“It’s the Haitian people who know what they’re going through. It’s the Haitian people who are going to take destiny into their own hands. Haitian people will choose who will govern them,” Chérizier said recently, according to The Associated Press .

Haitians and their supporters have put forth their own solutions over the years, holding that foreign intervention routinely ignores the voices and desires of Haitians.

In 2021, both Haitian and non-Haitian church leaders, women’s rights groups, lawyers, humanitarian workers, the Voodoo Sector and more created the Commission to Search for a Haitian Solution to the Crisis . The commission has proposed the “ Montana Accord ,” outlining a two-year interim government with oversight committees tasked with restoring order, eradicating corruption and establishing fair elections.

For more from NBC BLK, sign up for our weekly newsletter .

CORRECTION (March 15, 2024, 9:58 a.m. ET): An earlier version of this article misstated which university Jemima Pierre is affiliated with. She is a professor at the University of British Columbia, Vancouver, not the University of California, Los Angeles, (or Columbia University, as an earlier correction misstated).

Patrick Smith is a London-based editor and reporter for NBC News Digital.

Char Adams is a reporter for NBC BLK who writes about race.

Skip to main content
Keyboard shortcuts for audio player

Weekend Edition Sunday

Latest Show

Sunday Puzzle

Corrections

Listen to the lead story from this episode.

Politics chat: What it'll take to win 2024

by Ayesha Rascoe , Mara Liasson

Middle East

6 months of war: palestinians say the u.s. government lacks empathy for their plight.

by Ayesha Rascoe

Threats and vulnerabilities cast a shadow on NATO's 75th anniversary

The Apple Pay app on an iPhone in New York. Consumers tend to spend about 10% more when they adopt mobile contactless payment methods, a researcher says. Jenny Kane/AP hide caption

Using your phone to pay is convenient, but it can also mean you spend more

by Matthew Schuerman , Ayesha Rascoe

Those in the path of totality for the eclipse might have to watch out for traffic

by Geoff Brumfiel

Environment

A group of volunteers will shepherd lake michigan fish's journey upstream.

Sunday Puzzle NPR hide caption

Sunday Puzzle: Idioms for the eclipse

by Greg Pliska , Will Shortz

The Cherokee community in North Carolina celebrates a high school championship win

by Laura Hackett

Music Interviews

Matt lowell of lo moon on the group's new album and going back to high school, 6 months of war: israelis say netanyahu isn't doing enough to bring home the hostages, 6 months of war: anger grows even in arab countries having peace treaties with israel.

by Jane Arraf

White House economist on the latest jobs report and where we stand with inflation

There are people still aboard the ship that crashed into the baltimore bridge, nevada bans camping in public spaces in response to its homelessness crisis.

by Bert Johnson

Why some voters are convinced Biden won't really be on the ballot in November

by Tamara Keith

Kentucky's gambling addiction cases may be more than it can handle

by Jacob Munoz

Here's what NASA's looking for in the next generation of astronauts

Movie interviews, a new documentary follows hundreds of high school girls forming a mock government.

Searching for a song you heard between stories? We've retired music buttons on these pages. Learn more here.

IMAGES

A LEVEL GEOGRAPHY TSUNAMI CASE STUDIES
(PDF) Case Study on Japan Earthquake and Tsunami
2004 tsunami: 17 years on, a look back at one of the deadliest
Indian ocean tsunami case study
a case study on tsunami
(PDF) Community preparedness for Tsunami disaster: A case study

VIDEO

The World's Worst Tsunami in History
Why can't a tsunami also defeat the lighthouse?
Japan Tsunami 2011 Street View
Dam Breach Experiment
The Deadliest Tsunamis in History #short
First Person: Tsunami Survivor Stories

COMMENTS

A comprehensive report on the 28th September 2018 Indonesian Tsunami along with its causes
The topography of the seabed has a vital role to play in deciding the damage, a tsunami can cause. Usually, it's not the first waves of the tsunami that are damaging, but the subsequent second, third and fourth waves do most of the damage (Indonesian Tsunami information centre, 2018).Most of the tsunami occurrences (>80%) are centred along the Pacific Ring of Fire, a highly tectonically active ...
Tsunami Disasters: Case Studies and Reports
Indian Ocean Earthquake and Tsunami UNICEF response at six months update. This Collection is part of the 'Tsunami Disaster Channel' containing a number of case studies and reports relevant to tsunami disasters, where we try to find out what we have learnt from the past and how we can best reduce risk in future natural disasters.
2018 Sulawesi, Indonesia Earthquake and Tsunami Case Study
On Friday 28th September 2018 a magnitude 7.5 earthquake struck Palu, on the Indonesian island of Sulawesi, just before dusk wreaking havoc and destruction across the city and triggering a deadly tsunami on its coast. The 7.5 magnitude earthquake hit only six miles from the country's coast. A map to show the location of Palu.
(PDF) Tsunami Case Studies
TABLE 4.1 Summary of Tsunami Case Studies Reviewed in This Chapter (M. w. Earthquake Moment Magnitude) ... aftermath of the Japanese 2011 tsunami disaster. 4.2.6 1908 Messina e Reggio Earthquake ...
Response to the 2011 Great East Japan Earthquake and Tsunami disaster
We revisited the lessons of the 2011 Great East Japan Earthquake Tsunami disaster specifically on the response and impact, ... Throughout the case study in Sendai city, the proposed reconstruction plan was evaluated from the tsunami engineering point of view to discuss how the post 2011 paradigm was implemented in coastal communities for future ...
Human Response to Extreme Events: a review of three post-tsunami
In this paper, we review three post-tsunami disaster case studies: the Indian Ocean tsunami (IOT) on 26 December 2004, the Java tsunami on 17 July 2006 and the South Pacific tsunami on 29 September 2009. The 2004 IOT and 2006 Java tsunami surveys involved delayed-response post-disaster research using video interviewing. The 2009 South Pacific ...
Giant tsunami monitoring, early warning and hazard assessment
Tsunami evacuation models have been used for case studies worldwide and can be used for evidence-driven resource allocation 154, to understand the impact of earthquake-induced debris on evacuation ...
General Review of the Worldwide Tsunami Research
With the advancement of the global economy, the coastal region has become heavily developed and densely populated and suffers significant damage potential considering various natural disasters, including tsunamis, as indicated by several catastrophic tsunami disasters in the 21st century. This study reviews the up-to-date tsunami research from two different viewpoints: tsunamis caused by ...
Tsunami Case Studies
The 2004 Indian Ocean Tsunami is by far the worst natural disaster of its kind in recorded human history (Athukorala, 2012). Show abstract In this study, we developed a preliminary assessment of current domestic water supply and use in Banda Aceh, Indonesia, a city that was hardest hit by the Indian Ocean Tsunami of 2004.
Connecting community's perspectives on tsunami risk to anticipated
Employing a case study approach, this research aims to evaluate the impact of tsunamis based on historical seismic potential. ... aims to assess the knowledge and perceptions of coastal communities to understand and evaluate their preparedness for tsunami disasters. The study area is a vulnerable region directly impacted by a tsunami two ...
Community preparedness for tsunami disaster: a case study
A tsunami evacuation plan was verified during a table‐top exercise and was tested through a drill., - It is evident from the study that a community‐based approach (where the local community is taken as the primary focus of attention in disaster reduction) to tsunami mitigation and preparedness is viable.
Indian Ocean tsunami of 2004
The tsunami and its aftermath were responsible for immense destruction and loss on the rim of the Indian Ocean. On December 26, 2004, at 7:59 am local time, an undersea earthquake with a magnitude of 9.1 struck off the coast of the Indonesian island of Sumatra. Over the next seven hours, a tsunami —a series of immense ocean waves—triggered ...
Tsunami Risk Analysis and Disaster Management by Using GIS
Objectives. 1. To show a topographic mapping with UAV provide the basis for tsunami hazard classification. 2. To examine the potential damages and losses based on tsunami hazard modeling. 3. To recognize tsunami-affected areas after a disaster in addition to mapping tsunami vulnerable areas before a disaster.
Community preparedness for Tsunami disaster: A case study
Abstract. Purpose The main objective of this study is to develop a tsunami emergency response plan for a coastal community by adopting a community‐based disaster preparedness approach. Design ...
Extreme Events, Resilience and Disaster Management: Lessons from Case
3.2 Case Study II: Extremely Severe Cyclone 'Fani' 2019 (a) ... In 2005 (after the 2004 tsunami) National Disaster Management Authority ... Table 4 Lessons for disaster management from the case studies. Full size table (i) Include biological disasters in our disaster management plans;
Agent-based models of human response to natural hazards ...
This systematic review provides a comprehensive overview of tsunami evacuation models. The review covers scientific studies from the last decade (2012-2021) and is explicitly focused on models using an agent-based approach. The PRISMA methodology was used to analyze 171 selected papers, resulting in over 53 studies included in the detailed full-text analysis. This review is divided into two ...
PDF Connecting community's perspectives on tsunami risk to anticipated
Aceh Province. e study location is shown in Fig. 2, fac-ing the open sea. Lam Pageu Mukim was selected as the study location based on several considerations. is area is vulnerable to direct tsunami attacks, as evidenced by the impact of the 2004 tsunami and the absence of physi-cal mitigation systems in the eld. Additionally, there is
Community preparedness for tsunami disaster: a case study
This research is to describe level of knowledge, attitude, disaster plan, emergency disaster, early warning system, mobilization of resources in a tsunami disaster. Methods: This study is a descriptive study with 98 respondents were all members of the community. The sampling technique used purposed sampling with 50 questionnaires, and analysis ...
Disaster Incubation Theory for Reducing the Natural Disaster Risk: a
ACADEMIA Letters DISASTER INCUBATION THEORY FOR REDUCING THE NATURAL DISASTER RISK: A CASE STUDY OF TSUNAMI, 2004 Chinthani Senavirathna 1. Introduction There are many natural disasters in the world and Tsunami which is the giant waves is one of the natural disasters caused by geological processes. The speed of tsunami waves depends on ocean ...
Environmental hazards Case study: Indian Ocean Tsunami 2004
A very common case study for earthquakes is the South-East Asian tsunami of 2004. Other case studies include Mexico 1985, San Francisco 1989, Kobe 1995 and Pakistan 2005. This video can not be played
Mass Fatality Management following the South Asian Tsunami Disaster
After the tsunami disaster on 26 December 2004, we conducted three descriptive case studies to systematically document how the dead were managed in Thailand, Indonesia, and Sri Lanka. We considered the following parameters: body recovery and storage, identification, disposal of human remains, and health risks from dead bodies.
Was Today's Earthquake Connected to the Solar Eclipse?
The tidal forces on Earth grow as the sun, moon and Earth begin to align, a configuration that can lead to a solar eclipse. But the results of several studies of the relationship between ...
Communication technology support in disaster-prone areas: Case study of
Tsunami" 5.1.2. Disaster information from social media. Some information that can use their cellphones during a disaster explained that they got information about a disaster through social media. An informant explained: "Shortly after the earthquake … I was able to get information in the WhatsApp group that there had been a tsunami …
The Haiti crisis, explained: Violence, hunger and unstable political
Chaos has gutted Port-au-Prince and Haiti's government, a crisis brought on by decades of political disruption, a series of natural disasters and a power vacuum left by the president's assassination.
Weekend Edition Sunday for April 7, 2024 : NPR
The Apple Pay app on an iPhone in New York. Consumers tend to spend about 10% more when they adopt mobile contactless payment methods, a researcher says.
Theoretical and practical considerations in the creation of a disaster
Educational settings present both opportunities and challenges for students, teachers, and decision-makers in terms of creating a disaster risk reduction culture. The selection of a framework, the creation of adequate materials, and the choice of dissemination mechanisms are as important as the contents and the targets prioritized. This study reviews the disaster risk reduction educational ...

You are here

Resources on this Collection

10 Lessons Learned from the South Asia Tsunami of 26th December 2004

Approaches to Equity in Post-Tsunami Assistance - Sri Lanka: A Case Study

Environment and Reconstruction in Aceh: two years after the tsunami

Evolving Strategies For Long-term Rehabilitation On Shelter and Development in the Tsunami Affected Areas of Tamil Nadu

Impact of the tsunami response on local and national capacities: Maldives country report

Indian Ocean Earthquake and Tsunami UNICEF response at six months update

2018 Sulawesi, Indonesia Earthquake and Tsunami Case Study

Primary Effects

Secondary Effects

Immediate (Short Term) Response

Long-term Response

Premium Resources

Related Topics

Lombok Indonesia Earthquake 2018 Case Study

Search Internet Geography

Latest Blog Entries

Pin It on Pinterest

Giant tsunami monitoring, early warning and hazard assessment

Access options

Similar content being viewed by others

The enigmatic 1693 AD tsunami in the eastern Mediterranean Sea: new insights on the triggering mechanisms and propagation dynamics

Characterizing storm-induced coastal change hazards along the United States West Coast

Changing impacts of Alaska-Aleutian subduction zone tsunamis in California under future sea-level rise

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Peer review

Additional information

Related links

Supplementary information

Rights and permissions

About this article

Share this article

Quick links

To read this content please select one of the options below:

Design/methodology/approach

Originality/value

Related articles

All feedback is valuable

Join us on our journey

Questions & More Information

Agent-based models of human response to natural hazards: systematic review of tsunami evacuation

Cite this article

Similar content being viewed by others

A Multi-agent Based Evacuation Planning for Disaster Management: A Narrative Review

Evaluation of the risk and the evacuation policy in the case of a tsunami in the city of Iquique, Chile

1 Introduction

2 Methodology

3 Technical properties of ABM models

3.1 Item A1: What agent-based modeling tool or programming language was used?

3.2 Item A2: Are the source code and documentation available?

3.3 Item A3: Are any scenarios defined?

3.4 Item A4: Are experiments presented?

3.5 Item A5: Were statistical methods applied?

3.6 Item A6: Was a sensitivity analysis conducted?

3.7 Item A7: What validation method was used?

4 Analysis of model attributes

4.1 Item B1: What geographical area is simulated by a model?

4.2 Item B2: What is the general purpose of the model?

4.3 Item B3: Are any special features/aspects/issues of evacuation explored?

4.4 Item B4: How is the environment represented?

4.5 Item B5: What types of agents are defined, what are their attributes?

4.6 Item B6: What are the agents’ attributes, if specified?

4.7 Item B7: What input data/variables are used in the models?

4.8 Item B8: What output data/variables/measures does the model produce?

4.9 Item B9: Are there any simplifications or features omitted from the model and/or proposed by the authors for future work?

4.10 Item B10: Are there any specific algorithms used by agents?

5 Conclusions

Code Availability

Change history

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Additional information