{"title":"Statistical analysis of the ground deformation of Vulcanian explosions at Sakurajima volcano, Japan","authors":"","doi":"10.1016/j.jvolgeores.2024.108185","DOIUrl":null,"url":null,"abstract":"<div><p>The forecast of pulsatory explosions during volcanic unrest periods is an essential issue for the assessment and mitigation of volcanic hazards. Although various precursors are detectable through geophysical and geochemical monitoring, difficulties remain in precisely constraining possible scenarios. A probabilistic approach is effective in assessing risk while considering various uncertainties. Sakurajima volcano characterized by frequent Vulcanian activity is one of the suitable fields for the probabilistic forecast of pulsatory explosions. Their inflation-deflation patterns of ground deformation related to Vulcanian explosions are useful for evaluating the imminence and size of the next event. The large database obtained from its vigorous activity can contribute to statistical analysis. In this study, aiming the probabilistic forecast of the timing and size of explosions, we investigated the duration of inflation and volume changes at the pressure source using strain records of over 5000 events of Sakurajima volcano. Then, a stochastic model was estimated to explain the distribution of these events. The log-logistic distribution was found to be an appropriate model for data distribution, indicating the presence of competing processes, such as pressurization and depressurization, in the conduit. The model parameters of the log-logistic distribution temporally fluctuated reflecting the volcanic activity, especially increasing the magma supply from a deep region. We also suggested a methodology to constrain the probabilities of the likely timing and size of an imminent explosion using real-time strain monitoring and an estimated model distribution. Although some improvements would be needed for practical forecasting, our approach could be useful in predicting possible ash hazards.</p></div>","PeriodicalId":54753,"journal":{"name":"Journal of Volcanology and Geothermal Research","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S037702732400177X/pdfft?md5=360453948044bc002966a28ee2e532de&pid=1-s2.0-S037702732400177X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Volcanology and Geothermal Research","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S037702732400177X","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The forecast of pulsatory explosions during volcanic unrest periods is an essential issue for the assessment and mitigation of volcanic hazards. Although various precursors are detectable through geophysical and geochemical monitoring, difficulties remain in precisely constraining possible scenarios. A probabilistic approach is effective in assessing risk while considering various uncertainties. Sakurajima volcano characterized by frequent Vulcanian activity is one of the suitable fields for the probabilistic forecast of pulsatory explosions. Their inflation-deflation patterns of ground deformation related to Vulcanian explosions are useful for evaluating the imminence and size of the next event. The large database obtained from its vigorous activity can contribute to statistical analysis. In this study, aiming the probabilistic forecast of the timing and size of explosions, we investigated the duration of inflation and volume changes at the pressure source using strain records of over 5000 events of Sakurajima volcano. Then, a stochastic model was estimated to explain the distribution of these events. The log-logistic distribution was found to be an appropriate model for data distribution, indicating the presence of competing processes, such as pressurization and depressurization, in the conduit. The model parameters of the log-logistic distribution temporally fluctuated reflecting the volcanic activity, especially increasing the magma supply from a deep region. We also suggested a methodology to constrain the probabilities of the likely timing and size of an imminent explosion using real-time strain monitoring and an estimated model distribution. Although some improvements would be needed for practical forecasting, our approach could be useful in predicting possible ash hazards.
期刊介绍:
An international research journal with focus on volcanic and geothermal processes and their impact on the environment and society.
Submission of papers covering the following aspects of volcanology and geothermal research are encouraged:
(1) Geological aspects of volcanic systems: volcano stratigraphy, structure and tectonic influence; eruptive history; evolution of volcanic landforms; eruption style and progress; dispersal patterns of lava and ash; analysis of real-time eruption observations.
(2) Geochemical and petrological aspects of volcanic rocks: magma genesis and evolution; crystallization; volatile compositions, solubility, and degassing; volcanic petrography and textural analysis.
(3) Hydrology, geochemistry and measurement of volcanic and hydrothermal fluids: volcanic gas emissions; fumaroles and springs; crater lakes; hydrothermal mineralization.
(4) Geophysical aspects of volcanic systems: physical properties of volcanic rocks and magmas; heat flow studies; volcano seismology, geodesy and remote sensing.
(5) Computational modeling and experimental simulation of magmatic and hydrothermal processes: eruption dynamics; magma transport and storage; plume dynamics and ash dispersal; lava flow dynamics; hydrothermal fluid flow; thermodynamics of aqueous fluids and melts.
(6) Volcano hazard and risk research: hazard zonation methodology, development of forecasting tools; assessment techniques for vulnerability and impact.