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January 31, 2026International Journal of Disaster Risk Reduction0 citationsOpen Access

Forecasting tephra fall building impacts and losses at Awu volcano, Sangihe Island (Indonesia)

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ETEleanor TennantSJSusanna F. JenkinsCWChristina Widiwijayanti

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Abstract

Moving beyond volcanic hazard assessment to forecast how hazards affect communities provides valuable information for risk mitigation. Awu, a remote volcano on Sangihe Besar Island, Indonesia, is currently experiencing unrest (December 2025). With the entire population living within 45 km of the volcano, there is a need for actionable risk information. We integrated probabilistic tephra fall hazard analysis with building exposure and vulnerability information to forecast losses from a likely VEI 4 eruption. To address limited exposure data, we extracted building roof types from satellite imagery and applied Bayesian inference to combine existing vulnerability models into a hybrid framework suited to local conditions. Results indicate a 95% probability of exceeding ∼11 million USD (∼179 billion IDR) in building damage and a 75% probability of exceeding 25 million USD (∼407 billion IDR). Losses are concentrated in the northern districts, with Tahuna, the capital most affected. Losses at Awu were not well forecast by column height and wind conditions, parameters currently used to trigger insurance payouts from volcanic catastrophe risk bonds. Existing probabilistic volcanic loss calculations often couple a single hazard footprint representing the Nth percentile intensity with exposure and vulnerability data. Here we calculated loss for each individual hazard footprint computing 100 million values to capture uncertainty in both hazard and vulnerability. Losses calculated using the median hazard footprint were 5% higher than the median of the loss population. In addition to supporting decision making during the current unrest, our work presents key advancements in volcanic risk assessment that may be applied to other locations worldwide. Copyright

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Cite This Study

Tennant et al. (2026) studied this question.

synapsesocial.com/papers/69f177d6575b4760c5abc399https://doi.org/10.1016/j.ijdrr.2026.106040
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