We use ground-motion simulations of the 2013 Bohol, Philippines, earthquake along with a new post-disaster exposure/damage database to constrain building fragility and vulnerability. The large number of damaged buildings (>70,000) and the wide spread of seismic intensities caused by this earthquake make it an ideal candidate for such a study. An extensive survey was conducted leading to a robust description of over 25,000 damaged and undamaged structures. Ground-motion fields were simulated using ground-motion prediction equations and stochastic modeling, and the estimated and observed values were compared. The finite source model used in the simulation was based on the analysis of aftershocks and SAR data. The ground motions were associated with the empirical database to derive fragility and vulnerability models. Results indicate that the pattern of damage is best captured in the stochastic simulation. Constraints were placed on seismic building fragility and vulnerability models, which can promote more effective implementation of construction regulations and practices.
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References
1.
Abo-El-EzzA., NolleM. J., and NastevM., 2013. Seismic fragility assessment of low-rise stone masonry buildings, Journal of Earthquake Engineering and Engineering Vibration12, 87–97.
2.
AkkarS., and BommerJ. J., 2010. Empirical equations for the prediction of PGA, PGV, and spectral accelerations in Europe, the Mediterranean region, and the Middle East, Seismological Research Letters81, 195–206.
3.
Association of Structural Engineers of the Philippines (ASEP), 2010. National Structural Code of the Philippines, 6th Edition, ASEP, Quezon City, The Philiipines.
4.
AtkinsonG., and BeresnevI., 2002. Ground motions at Memphis and St. Louis from M7.5-8.0 earthquakes in the New Madrid seismic zone, Bulletin of the Seismological Society of America92, 1015–1024.
5.
AtkinsonG. M., AssatouriansK., BooreD., CampbellK., and MotazedianD., 2009. A guide to differences between stochastic point-source and stochastic finite-fault simulations, Bulletin of the Seismological Society of America99, 3192–3201.
6.
AtkinsonG. M., and BooreD. M., 2006. Earthquake ground-motion prediction equations for eastern North America, Bulletin of the Seismological Society of America96, 2181–2205.
7.
AurelioM. A., 2004. Engineering Geological and Geohazard Assessment (EGGA) system for sustainable infrastructure development: The Philippine experience, Engineering Geology for Sustainable Development in Mountainous Areas Geological Society of Hong Kong, 33–39.
8.
BakerJ. W., 2007. Correlation of ground motion intensity parameters used for predicting structural and geotechnical response, in Tenth International Conference on Applications of Statics and Probability in Civil Engineering, 1–8.
9.
BakerJ. W., 2015. Efficient analytical fragility function fitting using dynamic structural analysis, Earthquake Spectra31, 579–599.
10.
BakerJ. W., and CornellC. A., 2006. Vector-Valued Ground Motion Intensity Measures for Probabilistic Seismic Demand Analysis PEER Report, Tech. Rep. 2006/08, Pacific Earthquake Engineering Research Center, University of California, Berkeley.
11.
BeresnevI. A., and AtkinsonG. M., 1997. Modeling finite-fault radiation from the ωn spectrum, Bulletin of the Seismological Society of America87, 67–84.
12.
BeresnevI. A., and AtkinsonG. M., 1998. Stochastic finite-fault modeling of ground motions from the 1994 Northridge, California, earthquake. I. Validation on rock sites, Bulletin of the Seismological Society of America88, 1392–1401.
13.
BodinT., SambridgeM., RawlinsonN., and ArroucauP., 2012. Transdimensional tomography with unknown data noise, Geophysical Journal International189, 1536–1556.
14.
BooreD. M., 2003. Simulation of ground motion using the stochastic method, Pure and Applied Geophysics160, 635–676.
15.
BooreD. M., and AtkinsonG. M., 2008. Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 s and 10.0 s, Earthquake Spectra24, 99–138.
16.
BradleyB. A., 2013. A New Zealand-specific pseudospectral acceleration ground-motion prediction equation for active shallow crustal earthquakes based on foreign models, Bulletin of the Seismological Society of America103, 1801–1822.
17.
ChiouB., and YoungsR., 2008. An NGA model for the average horizontal component of peak ground motion and response spectra, Earthquake Spectra24, 173–215.
18.
ChiouB., and YoungsR., 2014. Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra, Earthquake Spectra30, 1117–1153.
19.
CorpuzA. G., 2001. Some implications of the July 16, 1990 earthquake on urban and regional planning in the Philippines: The July 16 Luzon earthquake, a technical monograph, available at http://www.phivolcs.dost.gov.ph://www.phivolcs.dost.gov.ph (last accessed February 2017).
20.
EkstromG., NettlesM., and DziewonskiA., 2012. The global CMT project 2004–2010: Centroid-moment tensors for 13, 017 earthquakes, Phys. Earth Planets Inter. 200–201, 1–9.
21.
Earthquake & Megacities Initiative (EMI), 2014. The Mw7.2 15 October 2013 Bohol, Philippines Earthquake, Technical Report TR-14-01, Quezon City, Philippines.
22.
FooS., and DavenportA., 2003. Seismic hazard mitigation for buildings, Natural Hazards28, 517–535.
23.
FukushimaY., and TanakaT., 1990. A new attenuation relation for peak horizontal acceleration of strong earthquake ground motion in Japan, Bulletin of the Seismological Society of America80, 757–783.
GeyerC. J., 2011. Introduction to Markov Chain Monte Carlo, in Handbook of Markov Chain Monte Carlo, (BrooksS., GelmanA., JonesG. and MengX.L., eds.), Chapman and Hall/CRC Press, Boca Raton, FL, 3–48.
GhasemiH., FukushimaY., KoketsuK., MiyakeH., WangZ., and AndersonJ. G., 2010. Ground-motion simulation for the 2008 Wenchuan, China, earthquake using the stochastic finite-fault method, Bulletin of the Seismological Society of America100, 2476–2490.
28.
GhofraniH., AtkinsonG. M., GodaK., and AssatouriansK., 2013. Stochastic finite-fault simulations of the 2011 Tohoku, Japan, earthquake, Bulletin of the Seismological Society of America103, 1307–1320.
29.
GodaK., KiyotaT., PokhrelR. M., ChiaroG., KatagiriT., SharmaK., and WilkinsonS., 2015. The 2015 Gorkha Nepal earthquake: Insights from earthquake damage survey, Frontiers in Built Environment1, 1–15.
30.
HartzellS. H., 1978. Earthquake aftershocks as Green's functions, Geophysical Research Letters5, 1–4.
31.
HolzerT. L., PadovaniA. C., BennettM. J., NoceT. E., and TinsleyJ. C., 2005. Mapping NEHRP V S30 site classes, Earthquake Spectra21, 353–370.
32.
JaiswalK., AspinallW., PerkinsD., WaldD. J., and PorterK. A., 2012. Use of expert judgment elicitation to estimate seismic vulnerability of selected building types, IN15th World Conference on Earthquake Engineering, 24–28 September 2012, Lisbon, Portugal.
33.
JaiswalK., WaldD. J., and HearneM. G., 2009. Estimating casualties for large earthquakes worldwide using an empirical approach, U.S. Geological Survey Open-File Report 2009-1136, 78.
34.
KanaoM., and ItoK., 1992. Attenuation of coda waves in the source area of the 1990 July 16 Luzon earthquake, Philippines, Bull. Disas. Prev. Res. Inst.42, 31–51.
35.
KapposA. J., PanagopoulosG., PanagiotopoulosC., and PenelisG., 2006. A hybrid method for the vulnerability assessment of R/C and URM buildings, Bulletin of Earthquake Engineering4, 391–413.
36.
KobayashiT., 2014. Remarkable ground uplift and reverse fault ruptures for the 2013 Bohol earthquake (Mw 7.1), Philippines, revealed by SAR pixel offset analysis, Geoscience Letters1, 7.
37.
LallemantD., KiremidjianA., and BurtonH., 2015. Statistical procedures for developing earthquake damage fragility curves, Earthquake Engineering & Structural Dynamics44, 1373–1389.
38.
MartinsL., SilvaV., MarquesM., CrowleyH., and DelgadoR., 2015. Development and assessment of damage-to-loss models for moment-frame reinforced concrete buildings, Earthquake Engineering and Strutural Dynamics44, 797–817.
39.
MatsuokaM., WakamatsuK., FujimotoK., and MidorikawaS., 2006. Average shear-wave velocity mapping using Japan engineering geomorphologic classification map, Structural Engineering/Earthquake Engineering23, 57s–68s.
40.
MavroeidisG. P., and ScottiC. M., 2013. Finite-fault simulation of broadband strong ground motion from the 2010 Mw 7.0 Haiti earthquake, Bulletin of the Seismological Society of America103, 2557–2576.
41.
MoghaddamH., FanaieN., and HamzehlooH., 2008. Studying the important parameters in earthquake simulation based on stochastic finite fault modeling, in 14th World Conference on Earthquake Engineering, Beijing, China, 1–8.
42.
MolasG., and YamazakiF., 1994. Seismic macrozonation of the Philippines based on seismic hazard analysis, Structural Engineering/Earthquake Engineering11, 33–43.
43.
MonelliD., PaganiM., WeatherillG., SilvaV., and CrowleyH., 2012. The hazard component of OpenQuake: The calculation engine of the Global Earthquake Model, IN15th World Conference on Earthquake Engineering, 24–28 September 2012, Lisbon, Portugal.
44.
MotazedianD., and AtkinsonG. M., 2005. Stochastic Finite-Fault Modeling Based on a Dynamic Corner Frequency, Bulletin of the Seismological Society of America95, 995–1010.
45.
National Institute of Building Sciences (NIBS), 2002. A Guide to Using HAZUS for Mitigation, Technical Report, Washington, D.C.
46.
PadgettJ. E., and DesRochesR., 2008. Methodology for the development of analytical fragility curves for retrofitted bridges, Earthquake Engineering & Structural Dynamics37, 1157–1174.
47.
PaganiM., MonelliD., WeatherillG., DanciuL., CrowleyH., SilvaV., HenshawP., ButlerL., NastasiM., PanzeriL., SimionatoM., and ViganoD., 2014. OpenQuake engine: An open hazard (and risk) software for the global earthquake model, Seismological Research Letters85, 692–702.
48.
PerezJ., VillamilC., DecierdoP., CayabyabF., and Martinez-VillegasM., 2014. Earthquake intensity distribution and isoseismal map of the 2013 Mw7.2 Bohol earthquake, in Asian Seismological Commission Conference, 17–20 November 2014, Makati, Philippines.
49.
PinhoR., 2012. GEM: A participatory framework for open, state-of-the-art models and tools for earthquake risk assessment, in 15th World Conference on Earthquake Engineering, 24–28 September 2012, Lisbon, Portugal.
50.
PomonisA., 2012. Derivation of globally applicable casualty rates for use in earthquake loss estimation models, IN15th World Conference on Earthquake Engineering, 24–28 September 2012, Lisbon, Portugal.
51.
Provincial Planning & Development Office (PPDO), 2010. Physical Framework Plan PDPFP, Tech. Rep. 2010–2015, Bohol, Philippines.
PunongbayanB., KumagaiH., PulidoN., BonitaJ., NakanoM., YamashinaT., MaedaY., InoueH., MelosantosA., FigueroaM., AlconesP., SorianoK., NaragI., and SolidumR., 2015. Development and operation of a regional moment tensor analysis system in the Philippines: Contributions to the understanding of recent damaging earthquakes, Journal of Disaster Research10, 25–34.
57.
QueanoK. L., AliJ. R., MilsomJ., AitchisonJ. C., and PubellierM., 2007. North Luzon and the Philippine sea plate motion model: Insights following paleomagnetic, structural, and agedating investigations, Journal of Geophysical Research112, 1–44.
58.
RainerJ. H., and KaracabeyliE., 2000. Performance of wood-frame construction in earthquakes, in The 12th World Conferences on Earthquake Engineering, 2454–2461.
59.
RanginC., Le PichonX., MazzottiS., PubellierM., Chamot-RookeN., AurelioM., WalpersdorfA., and QuebralR., 1999. Plate convergence measured by GPS across the Sundaland/Philippine sea plate deformed boundary: The Philippines and eastern Indonesia, Geophysical Journal International139, 296–316.
60.
Rodríguez-PérezQ., OttemöllerL., and CastroR. R., 2012. Stochastic finite-fault ground-motion simulation and source characterization of the 4 April 2010 Mw7.2 El Mayor-Cucapah earthquake, Seismological Research Letters83, 235–249.
61.
RosenthalJ. S., 2011. Optimal proposal distributions and adaptive MCMC, in Handbook of Markov Chain Monte Carlo, (BrooksS., GelmanA., JonesG. and MengX.-L., eds.), Chapman and Hall/CRC Press, Boca Raton, FL, 93–112.
62.
RossettoT., IoannouI., and GrantD., 2013. Existing Empirical Fragility and Vulnerability Functions: Compendium and Guide for Selection, Technical Report GEM Technical Report 2013-X GEM Foundation, Pavia, Italy.
63.
RotaM., PennaA., and StrobbiaC. L., 2008. Processing Italian damage data to derive typological fragility curves, Soil Dynamics and Earthquake Engineering28, 933–947.
64.
SengaraI., SuarjanaM., BeethamD., CorbyN., EdwardsM., GriffithM., WehnerM., and WellerR., 2010. The 30th September 2009 West Sumatra Earthquake Padang Region Damage Survey, Tech. Rep. 2010/44, Geoscience Australia, Canberra, Australia, 201.
65.
ShelterCluster, 2013. Post-Earthquake Shelter Assessment-Bohol Philippines, Final Report, PhilippinesShelter Cluster.
66.
SilvaV., CrowleyH., PaganiM., MonelliD., and PinhoR., 2014. Development of the Open-Quake engine, the global earthquake model's open-source software for seismic risk assessment, Natural Hazards72, 1409–1427.
67.
StraubD., and Der KiureghianA., 2008. Improved seismic fragility modeling from empirical data, Structural Safety30, 320–336.
68.
TorregosaR., SugitoM., and NojimaN., 2001. Strong motion simulation for the Philippines based on seismic hazard assessment, Journal of Natural Disaster Science23, 35–51.
69.
United Nations Educational, Scientific and Cultural Organization (UNESCO), 2016. Towards Resilient Non-Engineered Construction Guide for Risk-Informed Policy Making, Tech. Rep., Paris France.
70.
University of the Philippines, Institute of Civil Engineering (UPD-ICE), 2013. Development of Vulnerability Curves of Key Building Types in the Greater Metro Manila Area, Tech. Rep., Quezon City, Philippines.
WellsD. L., and CoppersmithK. J., 1994. New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement, Bulletin of the Seismological Society of America84, 974–1002.
73.
WordenC. B., GerstenbergerM. C., RhoadesD. A., and WaldD. J., 2012. Probabilistic relationships between ground-motion parameters and modified Mercalli intensity in California, Bulletin of the Seismological Society of America102, 204–221.
74.
YalcinkayaE., PinarA., UskulogluO., TekebasS., and FiratB., 2012. Selecting the most suitable rupture model for the stochastic simulation of the 1999 Izmit earthquake and prediction of peak ground motions, Soil Dynamics and Earthquake Engineering42, 1–16.
75.
Yepes-EstradaC., SilvaV., RossettoT., D'AyalaD., IoannouI., MeslemA., and CrowleyH., 2016. The global earthquake model physical vulnerability database, Earthquake Spectra32, 2567–2585.
76.
YoshidaY., and AbeK., 1992. Source mechanism of the Luzon, Philippines earthquake of July 16, 1990, Geophysical Research Letters19, 545.
77.
YumulG., DimalantaC., MaglambayanV., and MarquezE., 2008. Tectonic setting of a composite terrane: A review of the Philippine island arc system, Geosciences Journal12, 7–17.
78.
ZhaoJ. X., ZhangJ., AsanoA., OhnoY., OouchiT., TakahashiT., OgawaH., IrikuraK., ThioH. K., SomervilleP. G., FukushimaY., and FukushimaY., 2006. Attenuation relations of strong ground motion in Japan using site classification based on predominant period, Bulletin of the Seismological Society of America96, 898–913.
