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Assessment of human immediate response capability related to tsunami threats in Indonesia at a sub-national scale

Post, J., Wegscheider, S., Mück, M., Zosseder, K., Kiefl, R., Steinmetz, T., Strunz, G.·2009·Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-9-1075-2009
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Abstract

Abstract. Human immediate response is contextualized into different time compartments reflecting the tsunami early warning chain. Based on the different time compartments the available response time and evacuation time is quantified. The latter incorporates accessibility of safe areas determined by a hazard assessment, as well as environmental and demographic impacts on evacuation speed properties assessed using a Cost Distance Weighting GIS approach. Approximately 4.35 million Indonesians live in tsunami endangered areas on the southern coasts of Sumatra, Java and Bali and have between 20 and 150 min to reach a tsunami-safe area. Most endangered areas feature longer estimated-evacuation times and hence the population possesses a weak immediate response capability leaving them more vulnerable to being directly impacted by a tsunami. At a sub-national scale these hotspots were identified and include: the Mentawai islands off the Sumatra coast, various sub-districts on Sumatra and west and east Java. Based on the presented approach a temporal dynamic estimation of casualties and displacements as a function of available response time is obtained for the entire coastal area. As an example, a worst case tsunami scenario for Kuta (Bali) results in casualties of 25 000 with an optimal response time (direct evacuation when receiving a tsunami warning) and 120 000 for minimal response time (no evacuation). The estimated casualties correspond well to observed/reported values and overall model uncertainty is low with a standard error of 5%. The results obtained allow for prioritization of intervention measures such as early warning chain, evacuation and contingency planning, awareness and preparedness strategies down to a sub-district level and can be used in tsunami early warning decision support.

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Fig. 1 Overview on presented assessment scale, coverage area of results (in orange), distribution of warning segments along the coast (grey polygons) and tsunami-genic sources (red stars). Areas where exemplary results are shown are highlighted as green boxes.
Fig. 1 Overview on presented assessment scale, coverage area of results (in orange), distribution of warning segments along the coast (grey polygons) and tsunami-genic sources (red stars). Areas where exemplary results are shown are highlighted as green boxes.CC-BY · From the PDF
Fig. 2 Assigned time components for the assessment of human response capability to tsunami warning.
Fig. 2 Assigned time components for the assessment of human response capability to tsunami warning.CC-BY · From the PDF
Fig. 3 Workflow to determine credible emergency planning zones (EPZ) based on a multi-scenario approach. Credible EPZs are assigned according to tsunami warning levels (defined by the national warning centre) according to wave height at the coast: < =3 m (left side) and wave height at coast > 3 m (right side). The tsunami scenario data base is provided by the Alfred Wegener Institute, Bremen, Germany (AWI) in the context of the GITEWS (GermanIndonesian Tsunami Early Warning) project.
Fig. 3 Workflow to determine credible emergency planning zones (EPZ) based on a multi-scenario approach. Credible EPZs are assigned according to tsunami warning levels (defined by the national warning centre) according to wave height at the coast: < =3 m (left side) and wave height at coast > 3 m (right side). The tsunami scenario data base is provided by the Alfred Wegener Institute, Bremen, Germany (AWI) in the context of the GITEWS (GermanIndonesian Tsunami Early Warning) project.CC-BY · From the PDF
Fig. 4 Workflow to calculate evacuation time (ET) based on key determinants assigned parameterisations (see Table 1) and a cost distance weighting approach.
Fig. 4 Workflow to calculate evacuation time (ET) based on key determinants assigned parameterisations (see Table 1) and a cost distance weighting approach.CC-BY · From the PDF
Fig. 5 Examples for Denpasar (Bali, a and b ) and Cilacap (Java, c and d ), Indonesia for quantified evacuation times (ET) based on major warning tsunami (left column) and warning tsunami impact area (right column) visualized as 15 min time classes. Designated safe areas for evacuation are depicted in green. Light pink to dark purple areas constitute credible emergency planning zones (derived from hazard assessment). (e) and (f) show classifications of weak, moderate and good response capability for Cilacap (e) and Denpasar (Bali, f ).
Fig. 5 Examples for Denpasar (Bali, a and b ) and Cilacap (Java, c and d ), Indonesia for quantified evacuation times (ET) based on major warning tsunami (left column) and warning tsunami impact area (right column) visualized as 15 min time classes. Designated safe areas for evacuation are depicted in green. Light pink to dark purple areas constitute credible emergency planning zones (derived from hazard assessment). (e) and (f) show classifications of weak, moderate and good response capability for Cilacap (e) and Denpasar (Bali, f ).CC-BY · From the PDF
Fig. 6 Sub-national scale representation of human response capability categorized as good, moderate and weak. The represented area is aggregated on a Kecamatan (sub-district) administrative level. Human response capabilities are based on optimal reaction and institutional notification and decision times and hence e.g. red areas generally posses a weak response capability even if people take immediate action and were notified 8 min after a tsunami-genic event.
Fig. 6 Sub-national scale representation of human response capability categorized as good, moderate and weak. The represented area is aggregated on a Kecamatan (sub-district) administrative level. Human response capabilities are based on optimal reaction and institutional notification and decision times and hence e.g. red areas generally posses a weak response capability even if people take immediate action and were notified 8 min after a tsunami-genic event.CC-BY · From the PDF
Fig. 7 Number of casualties as a function of response time and median ETA values for warning segments Pantai Kuta Bali (a, b) , Cilacap Jateng (c, d) , Aceh Jaya (e, f) and Banda Aceh (g, h) and considering major warning impact zone (left) and warning impact zone (right).
Fig. 7 Number of casualties as a function of response time and median ETA values for warning segments Pantai Kuta Bali (a, b) , Cilacap Jateng (c, d) , Aceh Jaya (e, f) and Banda Aceh (g, h) and considering major warning impact zone (left) and warning impact zone (right).CC-BY · From the PDF
Fig. 8 Comparison of reported dead or missing after the Aceh 2004 tsunami event (red bar, JICA, 2005) to estimated values of casualties for 5 and 15 min response times (black bars) for Kabupaten (District) Aceh Jaya (a) and Kota (District) Banda Aceh. Please note that estimated values are based on major warning level tsunami impact area which is not identical to inundation extent of the Aceh 2004 tsunami in the respective regions.
Fig. 8 Comparison of reported dead or missing after the Aceh 2004 tsunami event (red bar, JICA, 2005) to estimated values of casualties for 5 and 15 min response times (black bars) for Kabupaten (District) Aceh Jaya (a) and Kota (District) Banda Aceh. Please note that estimated values are based on major warning level tsunami impact area which is not identical to inundation extent of the Aceh 2004 tsunami in the respective regions.CC-BY · From the PDF
Fig. 9 Spatial distribution of uncertainty considering the percentage coefficient of variation (COV, 'standard error') for a representative sub-set of the study area (region Cilacap, Java see Fig. 1).
Fig. 9 Spatial distribution of uncertainty considering the percentage coefficient of variation (COV, 'standard error') for a representative sub-set of the study area (region Cilacap, Java see Fig. 1).CC-BY · From the PDF

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Research works printed but not linked: 7

  1. Doocy, S., Gorokhovich, Y., Burnham, G., Balk, D., and Robinson, C.: Tsunami Mortality Estimates and Vulnerability Mapping in Aceh, Indonesia, American Journal of Public Health, 97, S146, 2007.
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  7. Thompson, P.: Simulex: simulated people have needs too. NIST Workshop on Building Occupant Movement during Fire Emer- gencies, NIST, 1-10, 2004.

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Metadata

Authors
Post, J., Wegscheider, S., Mück, M., Zosseder, K., Kiefl, R., Steinmetz, T., & Strunz, G.
Venue
Natural Hazards and Earth System Sciences
Publisher
Copernicus GmbH
Published
2009-07-06
Volume
9
Issue
4
Pages
1075-1086
ISSN
1684-9981
DOI
10.5194/nhess-9-1075-2009
Cited by
73
References
0
Language
en
Licence
creativecommons.org/licenses/by/3.0/ (vor)

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