Uncertainty Analysis of the Prediction of Massive Ash Fallout From a Large Explosive Eruption at Sakurajima Volcano

Volcanic ash hazards present life-threatening dangers to populations near volcanoes during large explosive eruptions. Vulnerable infrastructures demand a comprehensive disaster risk reduction strategy to protect residents from enormous ashfall accumulations. To prepare for the next large eruption of Sakurajima volcano, authorities in Kagoshima City are developing a countermeasure plan utilizing ash dispersal prediction 24 hr before an eruption. However, the absence of large eruptions in the last century makes it challenging to confirm the accuracy of predictions for hazard area designation. To ensure established protocols are effective, uncertainties in ashfall predictions must be addressed, enabling authorities to make appropriate responses. We simulated the previous large eruption of Sakurajima volcano using multiple wind forecast lead times as historical predictions from July 2018 to December 2022. The uncertainty in prediction results was evaluated by comparing simulation outputs with validation data from the ash dispersal data set. We examined uncertainty in hazard area assignment and its variation depending on risk items, wind field states, and the influences of seasonal patterns and events. Updating ashfall predictions with improved wind forecasts reduces uncertainty for all risk items and increases the precision of identified hazard zones. Furthermore, uncertainty levels are influenced by seasonality and can shift significantly with varying wind strengths controlling ash dispersal process. Providing uncertainty information is vital for decision-making during ash fallout events, and it is recommended to update response decisions 12 hr after the initial prediction. This study's outcomes will aid in developing better disaster risk management strategies, focusing on volcanic ash hazards. Massive ash fallout during a large eruption requires an effective disaster response to protect people living near the volcano. Currently, the authorities are working on a response plan to reduce damage and losses from ash fallout during a large eruption at Sakurajima Volcano. This plan uses ashfall prediction to select high-risk areas for warning and evacuation one day before an eruption. However, large eruptions are rare and it is difficult to verify that the prediction system can correctly predict the entire affected area. Therefore, it is important to evaluate how accurate the ashfall prediction is when a large eruption occurs. We carried out the simulation of a large eruption of Sakurajima volcano to evaluate the performance of ashfall prediction. We calculated the uncertainty in the prediction result by matching it with validation data, and found the general uncertainty in the prediction results and how it can change based on various conditions. The uncertainty information provided in this study can increase the utility of volcanic disaster risk management by providing effective early warning and evacuation plans. We clarify the spatio-temporal uncertainties in the ashfall prediction system at Sakurajima volcano under various weather conditionsWe analyzed how the uncertainty can change given the risk items considered and the prediction interval from the start of the eruptionThe timing of an eruption also influences the uncertainty in ashfall prediction due to seasonal patterns and high precipitation events