Integrating social and spatial dimensions in tsunami evacuation modeling: a case study of Panggarangan coast, Indonesia
- 1Department of Anthropology, Faculty of Cultural Science, Gadjah Mada University
- 2Center for Applied Geography Research, University of Indonesia
- 3Meteorological, Climatological, and Geophysical Agency
Abstract
The Indian Ocean region, particularly the Indonesian archipelago, represents one of the most high-risk tsunami zones globally. Historical records indicate that the southern coast of Java is subject to recurrent seismic and tsunami events driven by the Sunda Megathrust activity. This study quantifies tsunami escape potential by integrating hazard timing, spatial constraints, and community evacuation behavior in Panggarangan, a coastal village in Banten, Indonesia. Tsunami arrival times and inundation characteristics were derived from BMKG megathrust scenarios to define the Available Evacuation Time. High-resolution topographic data and GIS-based network analysis were employed to estimate optimal evacuation trajectories and Required Travel Times to designated Temporary Evacuation Sites (TES). These quantitative spatial analyses were synthesized with longitudinal field-based ethnographic observations conducted between 2022 and 2025. Results indicate that compressed arrival windows (approximately 12–15 minutes), when compounded by topographic friction and behavioral latency (such as social confirmation and asset protection), substantially diminish evacuation feasibility. This research advances tsunami risk assessment by operationalizing evacuation capacity as a socio-spatial outcome, offering a more nuanced framework for near-field tsunami mitigation in under-researched coastal contexts.
Related
- Historical and projected land-cover dynamics in the Toba Highland Peatlands, Indonesia: An ANN–CA modeling approach
- Modeling of fracture intensity by integrating geostatistical and neural network methods: The asmari reservoir, Rag-e-Sefid Oilfield, SW Iran
- Integrating MODIS and TROPOMI Atmospheric Products into TUV for High-Accuracy Surface UV Irradiance Modeling in the Mountainous Southwest USA
- Reservoir eutrophication prediction with explainable framework integrating temporal convolutional networks and bidirectional sequence modeling
- Integrating a global glacier model into local hydrological modeling: Impacts on melt contributions
BibTeX
@article{jumantini2026integrating,
title = {{Integrating social and spatial dimensions in tsunami evacuation modeling: a case study of Panggarangan coast, Indonesia}},
author = {Ni Nyoman Era Jumantini and I Nyoman Putera Indrawan and Admiral Musa Julius},
journal = {npj Natural Hazards},
year = {2026},
month = jun,
doi = {10.1038/s44304-026-00230-7},
url = {https://doi.org/10.1038/s44304-026-00230-7},
note = {CC BY},
}
RIS
TY - JOUR
TI - Integrating social and spatial dimensions in tsunami evacuation modeling: a case study of Panggarangan coast, Indonesia
AU - Ni Nyoman Era Jumantini
AU - I Nyoman Putera Indrawan
AU - Admiral Musa Julius
PY - 2026
DA - 2026/06/01
JO - npj Natural Hazards
DO - 10.1038/s44304-026-00230-7
UR - https://doi.org/10.1038/s44304-026-00230-7
AB - The Indian Ocean region, particularly the Indonesian archipelago, represents one of the most high-risk tsunami zones globally. Historical records indicate that the southern coast of Java is subject to recurrent seismic and tsunami events driven by the Sunda Megathrust activity. This study quantifies tsunami escape potential by integrating hazard timing, spatial constraints, and community evacuation behavior in Panggarangan, a coastal village in Banten, Indonesia. Tsunami arrival times and inundation characteristics were derived from BMKG megathrust scenarios to define the Available Evacuation Time. High-resolution topographic data and GIS-based network analysis were employed to estimate optimal evacuation trajectories and Required Travel Times to designated Temporary Evacuation Sites (TES). These quantitative spatial analyses were synthesized with longitudinal field-based ethnographic observations conducted between 2022 and 2025. Results indicate that compressed arrival windows (approximately 12–15 minutes), when compounded by topographic friction and behavioral latency (such as social confirmation and asset protection), substantially diminish evacuation feasibility. This research advances tsunami risk assessment by operationalizing evacuation capacity as a socio-spatial outcome, offering a more nuanced framework for near-field tsunami mitigation in under-researched coastal contexts.
SN - 2948-2100
ER -