Skip to main content

Advertisement

Log in

Active source zones and earthquake vulnerability around Sumatra subduction zone

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Abstract

Accurate identification of locations of earthquake clusters is critical for seismic risk and vulnerability estimation. About 19,500 earthquakes with magnitude >2.5 and depths <400 km were analysed to identify the most active seismic segments along the Sumatra subduction zone. The b-values appear to vary significantly spatially. A total of 16 clusters, each with more than 40 earthquakes that have been identified are distributed asymmetrically, and in-homogenously along the length of the subduction zone. Such inhomogeneous spatial distribution of earthquake clusters may be due to the segmentation of the Sumatran Fault caused by oblique convergence at varying rates. Furthermore, we evaluate vulnerability in the region by integrating two multi-criteria decision models, i.e., the analytical hierarchy process (AHP) and weighted aggregated sum product assessment (WASPAS) methods. We find that about 18.63–32.12% of the region is under moderate to high risk due to secondary effects of earthquakes, and about 49.25% of the region is a relatively low vulnerability. Our work may provide valuable insights to researchers and the hazard mitigation agencies working in the region by enabling them useful insights.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

References

  • Aden‐Antoniów F, Frank W B and Seydoux L 2022 An adaptable random forest model for the declustering of earthquake catalogs; J. Geophys. Res.: Solid Earth 127(2) e2021JB023254.

  • Aghataher R, Delavar M R, Nami M H and Samnay N 2008 A Fuzzy-AHP decision support system for evaluation of cities vulnerability against earthquakes; World Appl. Sci. J. 3(1) 66–72.

    Google Scholar 

  • Alizadeh M, Alizadeh E, Asadollahpour Kotenaee S, Shahabi H, Beiranvand A P, Panahi M and Saro L 2018a Social vulnerability assessment using an artificial neural network (ANN) model for earthquake hazard in Tabriz City, Iran; Sustainability 10(10) 3376.

    Article  Google Scholar 

  • Alizadeh M, Hashim M, Alizadeh E, Shahabi H, Karami M, Beiranvand A P, Pradhan B and Zabihi H 2018b Multi-criteria decision making (MCDM) model for seismic vulnerability assessment (SVA) of urban residential buildings; ISPRS Int. J. Geo-Inf. 7 444.

    Article  Google Scholar 

  • Ankerst M, Breuning M M, Kriegel H-P and Sander J 1999 OPTICS: Ordering points to identify the clustering structure; SIGMOD Rec. 28 49–60.

  • Barber A J, Crow M J and Milsom J 2005 Sumatra: Geology, resources and tectonic evolution; Geological Society of London.

  • Bilek S L, Engdahl E R, DeShon H R and Hariri M El 2011 The 25 October 2010 Sumatra tsunami earthquake: Slip in a slow patch; Geophys. Res. Lett. 38(14).

  • Boulos M N K 2003 Location-based health information services: A new paradigm in personalised information delivery; Int. J Health Geogr. 2(1) 2.

    Article  Google Scholar 

  • BPS (Badan Pusat Statistik) 2021 Central Java Province in Numbers.

  • Brown N A, Rovins J E, Feldmann-Jensen S, Orchiston C and Johnston D 2017 Exploring disaster resilience within the hotel sector: A systematic review of the literature; Int. J. Disaster Risk Reduct. 22 362–370.

    Article  Google Scholar 

  • Burton Paul W and Hall Thomas R 2014 Segmentation of the Sumatran fault; Geophys. Res. Lett. 41 4149–4158, https://doi.org/10.1002/2014GL060242.

    Article  Google Scholar 

  • Campello Ricardo J G B, Moulavi D and Sander J 2013 Density-based clustering based on hierarchical density estimates; In: Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Gold Coast, Australia, pp. 160–172, https://doi.org/10.1007/978-3-642-37456-2_14.

  • Campello Ricardo J G B, Moulavi D, Zimek A and Sander J 2015 Hierarchical density estimates for data clustering, visualisation, and outlier detection; ACM Transactions on Knowledge Discovery from Data (TKDD) 10(1) 5, https://doi.org/10.1145/2733381.

    Article  Google Scholar 

  • Chakraborty A and Joshi P K 2016 Mapping disaster vulnerability in India using analytical hierarchy process; Geomat. Nat. Hazards Risk 7(1) 308–325.

    Article  Google Scholar 

  • Duzgun H S B, Yucemen M S, Kalaycioglu H S, Celik K, Kemec S, Ertugay K and Deniz A 2011 An integrated earthquake vulnerability assessment framework for urban areas; Nat. Hazards 59(2) 917–947.

    Article  Google Scholar 

  • Ester M, Kriegel H P, Sander J and Xu X 1996 A density-based algorithm for discovering clusters in large spatial databases with noise; In: Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining (KDD-96) 96(34) 226–231.

  • Gahalaut V K, Nagarajan B, Catherine J K and Kumar S 2006 Constraints on 2004 Sumatra–Andaman earthquake rupture from GPS measurements in Andaman–Nicobar Islands; Earth Planet. Sci. Lett. 242(3–4) 365–374.

    Article  Google Scholar 

  • Gardner J K and Knopoff L 1974 Is the sequence of earthquakes in Southern California, with aftershocks removed Poissonian?; Bull. Seismol. Soc. Am. 64 1363–1367.

    Article  Google Scholar 

  • Gutenberg B and Richter C 1944 Frequency of earthquakes in California; Bull. Seismol. Soc. Am. 34 185–188.

    Article  Google Scholar 

  • Hall Thomas R, Nixon Casey W, Keir D, Burton Paul W and Ayele A 2018 Earthquake clustering and energy release of the African-Arabian rift system; Bull. Seismol. Soc. Am. 108(1) 155–162.

    Article  Google Scholar 

  • Hamilton W 1979 Tectonics of the Indonesian Region;USGS Professional Paper 1078 345.

  • Hartmann J and Moosdorf N 2012 The new global lithological map database GLiM: A representation of rock properties at the Earth surface; Geochem. Geophys. Geosyst. 13(12).

  • Hassanzadeh R, Nedović-Budić Z, Razavi A A, Norouzzadeh M and Hodhodkian H 2013 Interactive approach for GIS-based earthquake scenario development and resource estimation (Karmania hazard model); Comput. Geosci. 51 324–338.

    Article  Google Scholar 

  • Ho W 2008 Integrated analytic hierarchy process and its applications – a literature review; Eur. J. Oper. Res. 186 211–228.

    Article  Google Scholar 

  • Hosseini K A, Hosseini M, Jafari M K and Hosseinioon S 2009 Recognition of vulnerable urban fabrics in earthquake zones: A case study of the Tehran metropolitan area; J. Seismol. Earthq. Eng. 10 175–187.

    Google Scholar 

  • Jankowski P and Nyerges T 2001 GIS-supported collaborative decision-making results of an experiment; Ann. Ass. Am. Geogr. 91(1) 48–70.

    Article  Google Scholar 

  • Jena R, Pradhan B and Beydoun G 2020 Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model; Int. J. Disaster Risk Reduct. 46 101518.

    Article  Google Scholar 

  • Karig D E, Suparka S, Moore G F and Hehanussa P E 1979 Structure and Cenozoic evolution of the Sunda Arc in the Central Sumatra Region; Convergent Margins.

  • Karimzadeh S, Miyajima M, Hassanzadeh R, Amiraslanzadeh R and Kamel B 2014 A GIS-based seismic hazard, building vulnerability, and human loss assessment for the earthquake scenario in Tabriz; Soil Dyn. Earthq. Eng. 66 263–280.

    Article  Google Scholar 

  • Kaufman L and Rousseeuw P J 1987 Clustering by means of Medoids; In: Statistical Data Analysis Based on the –Norm and Related Methods (ed.) Dodge Y, North-Holland, pp. 405–416.

  • Kogan J 2007 Introduction to clustering large and high-dimensional data; Cambridge University Press, New York.

    Google Scholar 

  • Liu S, Suardi I, Xu X, Yang S and Tong P 2021 The geometry of the subducted slab beneath Sumatra revealed by regional and teleseismic travel time tomography; J. Geophys. Res.: Solid Earth 126(1) e2020JB020169.

  • Lloyd Stuart P 1982 Least squares quantisation in PCM; Information Theory, IEEE Trans. 28(2) 129–137.

    Article  Google Scholar 

  • Malakar S, Rai A K and Gupta A K 2022 Earthquake risk mapping in the Himalayas by integrated analytical hierarchy process, entropy with neural network; Nat. Hazards., https://doi.org/10.1007/s11069-022-05706-z.

  • Malod J, Karta K, Beslier M and Zen M Jr 1995 From normal to oblique subduction: Tectonic relationships between Java and Sumatra; J. Southeast Asian Earth Sci. 12(1–2) 85–93.

    Article  Google Scholar 

  • Manshoori M R 2011 Evaluation of seismic vulnerability and failure modes for pipelines; Proc. Eng. 14 3042–3049.

    Article  Google Scholar 

  • Martins V N, Silva D S and Cabral P 2012 Social vulnerability assessment to seismic risk using multi-criteria analysis: The case study of Vila Franca de Campo (Miguel Island, Azores, Portugal); Nat. Hazards 62 385–404.

    Article  Google Scholar 

  • McCloskey J, Lange D, Tilmann F, Nalbant S S, Bell A F, Natawidjaja D H and Rietbrock A 2010 The September 2009 Padang earthquake; Nat. Geosci. 3(2) 70–71.

  • McInnes L, Healy J and Astels S 2017 hdbscan: Hierarchical density-based clustering; J. Open Source Software, The Open J. 2(11).

  • McKerrow S W, Leggett J K and Eales M H 1977 Imbricate thrust model of the Southern Uplands of Scotland; Nature 267 237–239.

    Article  Google Scholar 

  • Meng Y and Malczewski J 2015 A GIS-based multi-criteria decision-making approach for evaluating accessibility to public parks in Calgary, Alberta; Human Geogr. 9(1) 29.

    Google Scholar 

  • Natawidjaja D H, Sieh K, Galetzka J, Suwargadi B W, Cheng H, Edwards R L and Chlieh M 2007 Interseismic deformation above the Sunda Megathrust recorded in coral microatolls of the Mentawai islands, West Sumatra; J. Geophys. Res.: Solid Earth 112(B2).

  • Nath S K, Adhikari M D, Devaraj N and Maiti S K 2015 Seismic vulnerability and risk assessment of Kolkata City, India; Nat. Hazards Earth Syst. Sci. 15 1103–1121.

    Article  Google Scholar 

  • Nath S K and Thingbaijam K K S 2009 Seismic hazard assessment – a holistic microzonation approach; Nat. Hazards Earth Syst. Sci. 9 1445–1459.

    Article  Google Scholar 

  • Nyimbili P H, Erden T and Karaman H 2018 Integration of GIS, AHP, and TOPSIS for earthquake hazard analysis; Nat. Hazards 92 1523–1546.

    Article  Google Scholar 

  • Pagani M, Garcia-Pelaez J, Gee R, Johnson K, Poggi V, Silva V, Simionato M, Styron R, Viganò D, Danciu L and Monelli D 2020 The 2018 version of the Global Earthquake Model: Hazard component; Earthq. Spectra 36(Suppl.) 226–251.

  • Pailoplee S 2017 Probabilities of earthquake occurrences along the Sumatra–Andaman Subduction Zone; Open Geosci. 9 53–60.

  • Panahi M, Rezaie F and Meshkani S A 2014 Seismic vulnerability assessment of school buildings in Tehran city based on AHP and GIS; Nat. Hazards Earth Syst. Sci. 14(4) 969–979.

    Article  Google Scholar 

  • Pollitz F F, Stein R S, Sevilgen V and Bürgmann R 2012 The 11 April 2012 east Indian Ocean earthquake triggered large aftershocks worldwide; Nature 490(7419) 250–253.

    Article  Google Scholar 

  • Prawirodirdjo L and Bock Y 2004 Instantaneous global plate motion model from 12 years of continuous GPS observations; J. Geophys. Res.: Solid Earth 109(B8).

  • Reasenberg P A 1985 Second-order moment of central California seismicity; J. Geophys. Res. 90 5479–5495.

    Article  Google Scholar 

  • Rousseeuw Peter J 1987 Silhouettes: A graphical aid to the interpretation and validation of cluster analysis; Comput. Appl. Math. 20 53–65, https://doi.org/10.1016/0377-0427(87)90125-7.

    Article  Google Scholar 

  • Rygel L, O’Sullivan D and Yarnal B A 2006 Method for constructing a social vulnerability index: An application to hurricane storm surges in a developed country; Mitig. Adapt. Strateg. Global Change 11 741–764.

    Article  Google Scholar 

  • Saaty T L 1980 The analytic hierarchy process: Planning, priority setting, resource allocation; McGraw, New York, 281p.

    Google Scholar 

  • Scitovski S 2018 A density-based clustering algorithm for earthquake zoning; Comput. Geosci. 110 90–95.

    Article  Google Scholar 

  • Scordilis E M 2006 Empirical global relations converting Ms and mb to moment magnitude; J. Seismol. 10 225–236.

    Article  Google Scholar 

  • Sieh K and Natawidjaja D 2000 Neotectonics of the Sumatra fault, Indonesia; J. Geophys. Res.: Solid Earth 105(B12) 18,295–28,326.

  • Soe M, Ryutaro T, Ishiyama D, Takashima I and Charusiri K W I P 2009 Remote sensing and GIS-based approach for earthquake probability map: A case study of the northern Sagaing fault area, Myanmar; J. Geol. Soc. Thail. 1 29–46.

    Google Scholar 

  • Syakuri M A, Khotimah B K, Rochman E M S and Satoto B D 2018 Integration K-means clustering method and elbow method for identification of the best customer profile cluster; IOP Conf. Ser.: Mater. Sci. Eng. 336 012017.

  • Tsang L L, Meltzner A J, Philibosian B, Hill E M, Freymueller J T and Sieh K 2015 A 15-year slow-slip event on the Sunda megathrust offshore Sumatra; Geophys. Res. Lett. 42(16) 6630–6638.

    Article  Google Scholar 

  • Wajzer M R, Barber A J and Hidayat S 1991 Accretion, collision and strike-slip faulting: The Woyla Group as a key to the tectonic evolution of North Sumatra; J. Southeast Asian Earth Sci. 6(3–4) 447–461.

    Article  Google Scholar 

  • Weatherill G and Burton Paul W 2009 Delineation of shallow seismic source zones using K-means cluster analysis, with application to the Aegean region; Geophys. J. Int. 176 565–588.

    Article  Google Scholar 

  • Weston J, Engdahl E R, Harris J, Di Giacomo D and Storchack D A 2018 ISC-EHB: Reconstruction of a robust earthquake dataset; Geophys. J. Int., https://doi.org/10.1093/gji/ggy155.

    Article  Google Scholar 

  • Wieland M 2016 Safety aspects of sustainable storage dams and earthquake safety of existing dams; Engineering 2 325–331.

    Article  Google Scholar 

  • Wisner B, Blaikie P, Cannon T and Davis I 2014 At risk: Nat. Hazards, People’s Vulnerability, and Disasters; Routledge.

    Google Scholar 

  • Zavadskas E K and Turskis Z 2011 Multiple criteria decision making (MCDM) methods in economics: An overview; Technol. Econ. Dev. Econ. 17 397–427.

    Article  Google Scholar 

  • Zavadskas E K, Turskis Z, Antucheviciene J and Zakarevicius A 2012 Optimisation of weighted aggregated sum product assessment; Elektronika Ir Elektrotechnika 122(6) 3–6.

    Article  Google Scholar 

Download references

Acknowledgements

The authors sincerely thank IIT Kharagpur for extending necessary infrastructure, computational facilities, and financial support through ISIRD grant. We also extend our sincere thanks to the various agencies for making the data available through various public platforms used in this study. Funding was supported by the Innovative Research and Development (ISIRD), Sponsored Research and Industrial Consultancy, IIT Kharagpur.

Author information

Authors and Affiliations

Authors

Contributions

Abhishek K Rai: Conceptualisation, methodology, analysis and writing – reviewing; Sukanta Malakar: Conceptualisation, methodology, analysis and writing; Susmita Goswami: Analysis and editing.

Corresponding author

Correspondence to Abhishek K Rai.

Additional information

Communicated by Somnath Dasgupta

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rai, A.K., Malakar, S. & Goswami, S. Active source zones and earthquake vulnerability around Sumatra subduction zone. J Earth Syst Sci 132, 66 (2023). https://doi.org/10.1007/s12040-023-02070-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12040-023-02070-9

Keywords

Navigation