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Tsunami Science Four Years after the 2004 Indian Ocean Tsunami: Part I: Modelling and Hazard Assessment PDF

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Tsunami Science Four Years after the 2004 Indian Ocean Tsunami Part I: Modelling and Hazard Assessment Edited by Phil R. Cummins Laura S. L. Kong Kenji Satake Birkhäuser Basel · Boston · Berlin Reprint from Pure and Applied Geophysics (PAGEOPH), Volume 165 (2008) No. 11/12 Phil R. Cummins Laura S. L. Kong Geoscience Australia UNESCO Intergovernmental Oceanographic P.O. Box 378 Commission (IOC) Canberra, ACT 2601 International Tsunami Information Centre Australia 737 Bishop Street Email: [email protected] Suite 2200 Honolulu, HI, 96813 Kenji Satake USA Earthquake Research Institute Email: [email protected] University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Email: [email protected] Library of Congress Control Number: 2009920437 Bibliographic information published by Die Deutsche Bibliothek: Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the Internet at <http://dnb.ddb.de> ISBN 978-3-0346-0056-9 Birkhäuser Verlag AG, Basel · Boston · Berlin This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustra- tions, recitation, broadcasting, reproduction on microfilms or in other ways, and storage in data banks. For any kind of use, permission of the copyright owner must be obtained. © 2009 Birkhäuser Verlag AG Basel · Boston · Berlin P.O. Box 133, CH-4010 Basel, Switzerland Part of Springer Science+Business Media Printed on acid-free paper produced from chlorine-free pulp. TCF ∞ Cover graphic: Based on a picture provided by Dr. Pål Wessel, Department of Geology and Geophysics, School of Ocean and Earth Science and Technology (SOEST), University of Ha- waii at Manoa, Honolulu, USA. Printed in Germany ISBN 978-3-0346-0056-9 e-ISBN 978-3-0346-0057-6 9 8 7 6 5 4 3 2 1 www.birkhauser.ch Contents 1983 Introduction to ‘‘Tsunami Science Four Years After the 2004 Indian Ocean Tsunami,PartI:ModellingandHazardAssessment’’ P.R.Cummins,L.S.L.Kong,K.Satake 1991 AComparisonStudyofTwoNumericalTsunamiForecastingSystems D.J.M.Greenslade,V.V.Titov 2003 TheEffectoftheGreatBarrierReefonthePropagationofthe2007Solomon IslandsTsunamiRecordedinNortheasternAustralia T.Baba,R.Mleczko,D.Burbidge,P.R.Cummins,H.K.Thio 2019 Numerical Modeling and Observations of Tsunami Waves in Alberni Inlet andBarkleySound,BritishColumbia I.V.Fine,J.Y.Cherniawsky,A.B.Rabinovich,F.Stephenson 2045 EvaluatingTsunamiHazardintheNorthwesternIndianOcean M.Heidarzadeh,M.D.Pirooz,N.H.Zaker,C.E.Synolakis 2059 AProbabilisticTsunamiHazardAssessmentforWesternAustralia D.Burbidge,P.R.Cummins,R.Mleczko,H.K.Thio 2089 TsunamiProbabilityintheCaribbean Region T.Parsons,E.L.Geist 2117 ScenariosofEarthquake-GeneratedTsunamisfortheItalianCoast oftheAdriaticSea M.M.Tiberti,S.Lorito,R.Basili,V.Kastelic,A.Piatanesi,G.Valensise 2143 Stromboli Island (Italy): Scenarios of Tsunamis Generated by Submarine Landslides S.Tinti,F.Zaniboni,G.Pagnoni,A.Manucci 2169 NumericalModellingoftheDestructiveMeteotsunamiof15June,2006 ontheCoastoftheBalearicIslands I.Vilibic´,S.Monserrat,A.Rabinovich,H.Mihanovic´ 2197 ValidationandVerificationofTsunamiNumericalModels C.E.Synolakis,E.N.Bernard,V.V.Titov,U.Kaˆnog˘lu,F.I.Gonza´lez 2229 An Efficient and Robust Tsunami Model on Unstructured Grids. Part I: InundationBenchmarks Y.J.Zhang,A.M.Baptista 2249 RunupCharacteristicsofSymmetricalSolitaryTsunamiWaves of‘‘Unknown’’Shapes I.Didenkulova,E.Pelinovsky,T.Soomere 2265 ATsunamiDetectionandWarning-focusedSeaLevelStationMetadataWeb Service J.J.Marra,U.S.Kari,S.A.Weinstein 2275 Long-Term Tsunami Data Archive Supports Tsunami Forecast, Warning, Research,andMitigation P.K.Dunbar,K.J.Stroker,V.R.Brocko,J.D.Varner,S.J.McLean, L.A.Taylor,B.W.Eakins,K.S.Carignan,R.R.Warnken Pureappl.geophys.165(2008)1983–1989 (cid:2)Birkha¨userVerlag,Basel,2008 0033–4553/08/111983–7 Pure and Applied Geophysics DOI10.1007/s00024-008-0423-8 Introductionto‘‘TsunamiScienceFourYearsAfterthe2004IndianOcean Tsunami, Part I: Modelling and Hazard Assessment’’ PHIL R. CUMMINS,1 LAURA S. L. KONG,2 and KENJI SATAKE3 Abstract—Inthisintroductionwebrieflysummarizethe14contributionstoPartIofthisspecialissueon TsunamiScienceFourYearsafterthe2004IndianOceanTsunami.Thesepapersarerepresentativeofthenew tsunamisciencebeingconductedsincetheoccurrenceofthattragicevent.Mostofthesewerepresentedatthe session:TsunamiGenerationandHazard,oftheInternationalUnionofGeodesyandGeophysicsXXIVGeneral AssemblyheldatPerugia,Italy,inJulyof2007.Thatsessionincludedoveronehundredpresentationsonawide rangeoftopicsintsunamiresearch.ThepapersgroupedintoPartI,andintroducedhere,covertopicsdirectly related to tsunami mitigation such as numerical modelling, hazard assessment and databases. Part II of this specialissue,ObservationsandDataAnalysis,willbepublishedinasubsequentvolumeofPureandApplied Geophysics. Keywords: Tsunami,seiche,harborresonance,numericalmodeling,hazardassessment,inundation, tsunamimitigation,tsunamiwarningsystem,runup,tsunamidatabase,rissaga. 1. Introduction Four years after the 2004 Indian Ocean Tsunami, the most lethal tsunami disaster in human history, tsunami science continued to move forward rapidly. The research and disaster management community that supports tsunami mitigation has expanded greatly. Observationplatforms,especiallyintheIndianOcean,havefarsurpassedtheirpre-2004 capacity for detecting and measuring tsunamis and the earthquakes that most frequently cause them. A remarkable crosssection of this research was presented in the session Tsunami Generation and Hazard, at the International Union of Geodesy and Geophysics (IUGG) XXIV General Assembly in Perugia, Italy, held in July of 2007. Over one hundred presentations were made at this session, spanning topics ranging from paleotsunami research, to nonlinear shallow-water theory, to tsunami hazard and risk 1 GeoscienceAustralia,GPO,Box378,Canberra,ACT2601,Australia. E-mail:[email protected] 2 UNESCOIOCInternationalTsunamiInformationCentre,737BishopSt.Ste.2200,Honolulu, Hawaii96813,USA.E-mail:[email protected] 3 EarthquakeResearchInstitute,UniversityofTokyo,1-1-1Yayoi,Bunkyo-ku,Tokyo113-0032,Japan. E-mail:[email protected] 1984 P.R.Cumminsetal. Pureappl.geophys., assessment. The IUGG’s Tsunami Commission arranged for a selection of this work, alongwithotherpapersonsimilartopics,tobepublishedindetailinthe28papersofthis 2-part special issue of Pure and Applied Geophysics. Inthisintroductorypaper,webrieflydiscussthepapersinPartIof‘‘TsunamiScience Four Years After the 2004 Indian Ocean Tsunami’’. In Section 2 we discuss new advancesinthefundamentalnumericaltechniquesusedtomodeltsunamisandSection 3 reviewsseveralcontributionsthatapplysuchtechniquestoimproveourunderstandingof how near-coast processes affect tsunami propagation. Sections 4 and 5 discuss the application of tsunami modeling to tsunami hazard assessment, in a deterministic and a probabilistic sense, respectively. Section 6 describes two database efforts that are supporting researchers and warning system operators to access the most current and accurate information on tsunami events. 2. Advances in Analytical and Numerical Modeling of Tsunamis Theincreasedfocusontsunamisciencesincethe2004Sumatra-AndamanEarthquake and subsequent Indian Ocean Tsunami has seen a rapid expansion in the tsunami modeling community. Prior to 2004, this community consisted of a handful of research groups that utilized a few well-tested codes for numerical modeling of tsunamis. Since 2004,manymoreresearch groups have takenaninterest intsunamimodeling, andthese groupshaveinsomecaseseitherdevelopednewcodesfortsunamimodeling,oradapted hydrodynamic codes that had originally been developed for other purposes. Tsunami forecastingvianumericalmodelingisalsoseeingincreaseduseasanoperationalpartof tsunami warning systems. In response to this recent proliferation of tsunami modeling codes, SYNOLAKIS et al. (2008)pointedouttheimportanceofvalidationandverificationofcodesusedintsunami hazard assessmentorforecastingsystems.Theyreviewedseveralmethodsbywhichthis can be accomplished. These included analytical and laboratory validation benchmarks, as well as examples of field observations against which numerical models can be verified. A summary of the theoretical development for formulae used as analytical benchmarks was given, and details of the laboratory experiments and field observations were reviewed. In addition to the use of these benchmarks for inundation modeling in tsunami hazard studies, operational requirements for forecasting tsunamis in real-time were discussed. ZHANGandBATISTA(2008)presentedanexampleoftheadaptationofamulti-purpose barocliniccirculationmodel(SELFE)totsunamiinundationandpropagation.Themodel hasseveralinterestingfeaturesthatmakeitausefuladditiontothesuiteoftoolsalready available: Release as open source, facilitating further development by a community of users; use of an unstructured grid, allowing for variable resolution to accommodate complexgeometryonlywherenecessary;animplicittime-steppingalgorithmthatavoids the stringent Courant–Friedrichs–Lewy stability condition, and a simple wetting/drying Vol.165,2008 TsunamiScienceFourYearsAfterthe2004IndianOceanTsunami 1985 algorithm that implements inundation. Along the lines suggested by SYNOLAKIS et al. (2008),theauthorspresentedvalidationresultsagainstscenariosfromthe3rdInternational WorkshopinLong-WaveRunupModels(http://www.cee.cornell.edu/longwave). GREENSLADEandTITOV(2008),ontheotherhand,useatriedandtestedtsunamicode (MOST – see TITOV and GOZAREZ, 1997) to compare two tsunami forecasting systems used by the U.S. National Oceanic and Atmospheric Administration (NOAA), and the Australian Bureau of Meteorology. The tsunamis caused by the 2006 Tonga and 2007 Sumatra earthquakes were used as test cases. Both systems use results of tsunami computationsmadepriortoearthquakesandstoredinadatabase.Whilethespecifications of numerical simulation of tsunami propagation are very similar, the scenario sources distributed around the Pacific Basins are slightly different. The Australian system assumes different faults depending on the earthquake magnitude, while the U.S. system scales the slip amount by assimilation of tsunameter (a.k.a. DART) data. Because different sources are used to approximate the Tonga and Sumatra earthquakes, the forecasted waveforms at offshore tsunameter locations are slightly different. However, the differences in waveforms computed at coastal tide gauges are considerably smaller, indicating insensitivity of coastal tsunamis to the details of the tsunami source. Despitesubstantialrecentprogressinnumericaltsunamimodeling,therapidforecast ofrunupvaluesremainsadifficultproblem,duetoitsnonlinearityandsensitivitytoinput data such as bathymetry and initial waveform. The paper by DIDENKULOVA et al. (2008) demonstrated that analytical results still have an important role to play in estimating runup. They discussed results from nonlinear shallow-water wave theory for runup of solitary tsunami waves, and showed that appropriate definitions of significant wave height and length (based on 2/3 of maximum wave height) result in formulae for computing runup characteristics that are relatively independent of incident wave shape (for symmetric incident waves). Such formulae may be used in rapidly estimating potential inundation once the tsunami height, wavelength and period in the open ocean are known. 3. Modeling of Near-Coast Effects on Tsunami Propagation Oneofthemostchallengingaspectsoftsunamimodelingisaccuraterepresentationof propagation effects near the coast, including reflection and refraction by shallow bathymetry,andresonancesinsemi-enclosedbaysandinlets.Severalpapersinthisissue address these topics. BABA et al. (2008) examined the effects of Great Barrier Reef, the world’s largest coral reef located offshore Australia, on the tsunami generated by the April 1, 2007 Solomon Islands earthquake. They carried out tsunami numerical simulation from a sourcemodelbasedontheirseismicwaveforminversion.Thesimulatedwaveformsshow goodagreementwithtidegaugedatainnortheastAustralia.Inordertoexaminetheeffect of the coral reef, they also made tsunami simulations with artificial bathymetry data 1986 P.R.Cumminsetal. Pureappl.geophys., withoutthe coralreef;the reefwasreplacedwithdeep ocean inonedatasetandshallow ocean in the other. Simulations with these models indicate that the tsunami energy was reduced by direct reflection outside the reef and by refraction when the tsunami passed through the reef. As a result, the tsunami was delayed by 10–15 minutes, the amplitude became about a half or less, and the period became longer. Semi-enclosed bays and inlets present another challenge to tsunami modeling in the form of potential resonant enhancement of tsunamis. Alberni inlet is a long (*40 km) andnarrow(1–2 km)fjordinVancouverIsland,Canada.Thetsunamicausedbythe1964 Alaskan earthquake had a height of about 8 m above mean sea level at Port Alberni, locatedattheheadoftheinletandabout65 kmfromthePacificOcean.FINEetal.(2008) examined resonance characteristics of the Alberni inlet by using numerical calculations. Their results indicated that strong amplification occurred at a period of 112 min with an amplification factor of more than 10. VILIBIC´ et al. (2008) presented a comprehensive analysis of a destructive meteots- unami (rissaga) that occurred in the Balearic Islands in 2006. This event was not associated with an earthquake source and excited destructive harbor oscillations of several meters amplitude, resulting in an economic loss estimated at tens of millions of euros. VILIBIC´ et al. used a numerical model, verified using a series of measurements made during smaller rissaga events in 1997, and microbarograph measurement to show how the 2006 rissaga resulted from ocean-atmosphere resonance excited by a travelling atmospheric disturbance, which in turn induced the hazardous harbor oscillations observed.Thepotentialfordevelopingarissagawarningsystembasedonthismodelwas also discussed. 4. Scenario Modeling for Tsunami Hazard Assessment In addition to rapid tsunami forecasts that may form part of a tsunami warning, emergency managers and planners in coastal communities need information about how largetsunamisaffectingtheircommunitiesmightbe.Suchquestionscanbeansweredby scenario modeling, which forms the basis of a deterministic hazard assessment. Such assessments are normally designed to encompass the worst credible, as well as the most likely, scenarios. TIBERTI et al. (2008) numerically modeled potential tsunamis in the Adriatic Sea. Maximumcredibleearthquakeswereassumedalongthesixsourcezones.Theyclassified the computed maximum tsunami heights into three levels: marine, land and severe land for 0.05 m, 0.5 m and 1.0 m, respectively. The results indicate that the largest tsunamis are expected on the Apulia and Gargano coasts of southern Italy. They found that focusing of energy due to bathymetric features enhances the tsunami heights. At Stromboli volcano, southern Italy, on December 30, 2002, a moderate-sized landslide(withavolumeof0.02–0.03 km3)generatedatsunami,withamaximumrunup heightofabout10 m.Becauseitoccurredinthewinter,therewasnolossofhumanlife,

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