Paper:
Event-Based Seismic Risk Assessment for Indonesia’s Post-Disaster Fund to Stimulate House Damage Recovery
Fiza Wira Atmaja*1,*2
, Irwan Meilano*1
, Riantini Virtriana*1,
, Dumaria Rulina Tampubolon*3
, Rio Raharja*1
, and Garup Lambang Goro*4

*1Department of Geodesy and Geomatics Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung
Jl. Ganesha 10, Bandung, West Java 40132, Indonesia
Corresponding author
*2Department of Industry Research, Indonesia Re Institute, PT Reasuransi Indonesia Utama
Jakarta, Indonesia
*3Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung
Bandung, Indonesia
*4Department of Civil Engineering, State Polytechnic Semarang
Semarang, Indonesia
Indonesia, situated at the convergence of four major tectonic plates, has historically been prone to significant seismic activity. In response, the country has adopted Disaster Risk Financing and Insurance (DRFI) as a strategic approach to managing funds, particularly for post-disaster recovery, which poses significant budgeting challenges. This study conducted a detailed seismic risk assessment specifically aiming to enhance the management of funds designated for housing damage recovery after earthquakes. Employing downscaling exposure models and event-based seismic risk assessments, this study estimates the value of earthquake-affected residential properties in Indonesia at the sub-district level to be USD 380.6 billion as of 2022. Subsequent risk analysis employing the event-based seismic risk model produced a hazard map, an exceedance probability curve, and an average annual loss map, indicating an average annual loss ratio of 0.1035% relative to the total exposure. The accuracy of the model was validated using historical event loss data from the 2022 Cianjur earthquake, achieving a mean absolute percentage error of 3.0% at the regency level. This precision level confirms its utility in estimating funds necessary for housing recovery initiatives at this administrative level. The findings support the model’s reliability in assessing the risks associated with funding for earthquake-induced damage up to the regency level and suggest its potential to refine DRFI policies. This model is expected to enhance the effectiveness and inclusiveness of disaster finance strategies in Indonesia.
- [1] P. Bird, “An updated digital model of plate boundaries,” Geochemistry, Geophysics, Geosystems, Vol.4, No.3, 2003. https://doi.org/10.1029/2001GC000252
- [2] Badan Meteorologi, Klimatologi, dan Geofisika (BMKG), “Katalog Gempabumi Signifikan dan Merusak Tahun 1821-2018,” 2019 (in Indonesian).
- [3] Pusat Studi Gempa Nasional (PuSGeN), “Peta Sumber dan Bahaya Gempa Indonesia Tahun 2017,” Kementerian PUPR, 2017 (in Indonesian).
- [4] National Development Planning Agency (BAPPENAS), “Indonesia: Preliminary damage and loss assessment, the December 26, 2004 natural disaster,” BAPPENAS, 2005.
- [5] I. Meilano et al., “Source characteristics of the 2019 Mw 6.5 Ambon, Eastern Indonesia, earthquake inferred from seismic and geodetic data,” Seismological Research Letters, Vol.92, No.6, pp. 3339-3348, 2021. https://doi.org/10.1785/0220210021
- [6] I. Meilano et al., “The 2021 MW 6.2 Mamuju, West Sulawesi, Indonesia earthquake: Partial rupture of the Makassar Strait thrust,” Geophysical J. Int., Vol.233, No.3, pp. 1694-1707, 2023. https://doi.org/10.1093/gji/ggac512
- [7] R. Raharja, T. Ito, and I. Meilano, “Evaluation of earthquake potential using a kinematic crustal block motion model in Java, Indonesia, based on GNSS observation,” J. of Asian Earth Sciences: X, Vol.11, Article No.100171, 2024. https://doi.org/10.1016/j.jaesx.2023.100171
- [8] S. Rahmadani et al., “Geodetic observation of strain accumulation in the Banda Arc region,” Geomatics, Natural Hazards and Risk, Vol.13, No.1, pp. 2579-2596, 2022. https://doi.org/10.1080/19475705.2022.2126799
- [9] Kemenkeu RI, “Strategi Pembiayaan dan Asuransi Risiko Bencana,” 2018 (in Indonesian).
- [10] W. J. W. Botzen, O. Deschenes, and M. Sanders, “The economic impacts of natural disasters: A review of models and empirical studies,” Review of Environmental Economics and Policy, Vol.13, No.2, pp. 167-188, 2019. https://doi.org/10.1093/reep/rez004
- [11] Kemendagri, “Visualisasi Data Kependudukan.” https://gis.dukcapil.kemendagri.go.id/peta/ [Accessed June 30, 2019]
- [12] BIG, “Peta Rupa Bumi Indonesia,” Badan Informasi Geospasial, 2021.
- [13] Geofabrik, “OpenStreetMap data for Indonesia.” https://download.geofabrik.de/asia/indonesia.html [Accessed June 17, 2021]
- [14] Global Earthquake Model (GEM), “Indonesia Exposure Model,” 2018.
- [15] G. L. Goro, “Pengembangan peta risiko gempa Indonesia sebagai acuan strategi mitigasi dan pengurangan risiko bencana nasional,” Ph.D. thesis, Institut Teknologi Bandung, 2021 (in Indonesian).
- [16] Badan Nasional Penanggulangan Bencana (BNPB), “Peraturan Kepala Badan Nasional Penanggulangan Bencana Nomor 15 Tahun 2011 tentang Pedoman Pengkajian Kebutuhan Pasca Bencana,” 2011 (in Indonesian).
- [17] Kemenkeu, “Nota Keuangan beserta RAPBN Tahun Anggaran 2023,” 2022.
- [18] R. Paulik et al., “RiskScape: A flexible multi-hazard risk modelling engine,” Natural Hazards, Vol.119, No.2, pp. 1073-1090, 2023. https://doi.org/10.1007/s11069-022-05593-4
- [19] F. Elmer, A. H. Thieken, I. Pech, and H. Kreibich, “Influence of flood frequency on residential building losses,” Natural Hazards and Earth System Science, Vol.10, No.10, pp. 2145-2159, 2010. https://doi.org/10.5194/nhess-10-2145-2010
- [20] V. Silva, “Critical issues on probabilistic earthquake loss assessment,” J. of Earthquake Engineering, Vol.22, No.9, pp. 1683-1709, 2018. https://doi.org/10.1080/13632469.2017.1297264
- [21] S. C. Loughlin, S. Sparks, S. K. Brown, S. F. Jenkins, and C. Vye-Brown (Eds.), “Global volcanic hazards and risk,” Cambridge University Press, 2015. https://doi.org/10.1017/CBO9781316276273
- [22] G. M. Atkinson and D. M. Boore, “Empirical ground-motion relations for subduction-zone earthquakes and their application to Cascadia and other regions,” Bulletin of the Seismological Society of America, Vol.93, No.4, pp. 1703-1729, 2003. https://doi.org/10.1785/0120020156
- [23] J. X. Zhao et al., “An empirical site-classification method for strong-motion stations in Japan using H/V response spectral ratio,” Bulletin of the Seismological Society of America, Vol.96, No.3, pp. 914-925, 2006. https://doi.org/10.1785/0120050124
- [24] N. Abrahamson, N. Gregor, and K. Addo, “BC hydro ground motion prediction equations for subduction earthquakes,” Earthquake Spectra, Vol.32 No.1, pp. 23-44, 2016. https://doi.org/10.1193/051712EQS188MR
- [25] D. M. Boore, J. P. Stewart, E. Seyhan, and G. M. Atkinson, “NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes,” Earthquake Spectra, Vol.30, No.3, pp. 1057-1085, 2014. https://doi.org/10.1193/070113EQS184M
- [26] K. W. Campbell and Y. Bozorgnia, “NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra,” Earthquake Spectra, Vol.30, No.3, pp. 1087-1115, 2014. https://doi.org/10.1193/062913EQS175M
- [27] B. S. J. Chiou and R. R. Youngs, “Update of the Chiou and Youngs NGA ground motion model for average horizontal component of peak ground motion and response spectra,” PEER Report 2013/07, 2013.
- [28] G. M. Atkinson and D. M. Boore, “Erratum to empirical ground-motion relations for subduction zone earthquakes and their application to Cascadia and other regions,” Bulletin of the Seismological Society of America, Vol.98, No.5, pp. 2567-2569, 2008. https://doi.org/10.1785/0120080108
- [29] G. M. Atkinson and D. M. Boore, “Empirical ground-motion relations for subduction-zone earthquakes and their application to Cascadia and other regions,” Bulletin of the Seismological Society of America, Vol.93, No.4, pp. 1703-1729, 2003. https://doi.org/10.1785/0120020156
- [30] Geomatrix Consultants, “Seismic margin earthquake for the Trojan site: Final unpublished report prepared for Portland General Electric Trojan Nuclear Plant, Ranier, Oregon,” 1993.
- [31] V. Silva et al., “Development of a global seismic risk model,” Earthquake Spectra, Vol.36, No.1_suppl, pp. 372-394, 2020. https://doi.org/10.1177/8755293019899953
- [32] T. I. Allen and D. J. Wald, “Topographic slope as a proxy for seismic site-conditions (VS30) and amplification around the globe,” U.S. Geological Survey Open-File Report 2007-1357, 2007.
- [33] Global Earthquake Model (GEM) Foundation, “Indonesia: Country Seismic Risk Profile (Global Seismic Risk Profiles v2023.0.0),” 2023.
- [34] GEM Foundation, “Indonesia: Country seismic risk profile,” 2019.
- [35] J. Wainwright and M. Mulligan (Eds.), “Environmental Modelling: Finding Simplicity in Complexity,” Wiley, 2004.
- [36] G. L. Pita, “Foundation and development of natural catastrophe modeling,” Natural Hazards Review, Vol.23, No.4, 2022. https://doi.org/10.1061/(asce)nh.1527-6996.0000567
- [37] S. M. Khan et al., “A systematic review of disaster management systems: Approaches, challenges, and future directions,” Land, Vol.12, No.8, Article No.1514, 2023. https://doi.org/10.3390/land12081514
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