3:30 PM - 5:00 PM
[SVC35-P07] Outline of Sub Thema C-1 “Development of a Method for Forecasting of Branching in Eruption Event Tree through Analysis of Volcanic Pyroclasts” in INeVRH Project
Keywords:prediction, eruption, magma
In this theme, we are carrying out analyses of volcanic pyroclasts with the aim of developing a method for predicting the type of transition that will follow an eruptive event. Once an anomaly has been detected, we are then faced with a series of decisions, such as: Will there actually be an eruption? Will the eruption be explosive or non-explosive? Will the eruption be large or small? Will the eruption be short-lived or long-lived? Carrying out such judgements is the essence of “Forecasting of Branching in Eruption Event Tree”. The overall aim of this theme is to collect material science data and organize the information so that it can be used at any time. This will allow us to quickly make different judgements about the likely course of the eruption when we observe events that indicate an imminent eruption.
The data obtained from the analysis of volcanic ejecta is diverse. Over the course of the project, we have analyzed recent ejecta from 11 volcanoes to identify factors that may be important in predicting eruptive events. As a result, the following points have become clear. First, the main factors determining whether an eruption is explosive or non-explosive are magma composition (especially water content), magma temperature and ejection rate of the magma. Second, the condition of the magma immediately before the eruption is very important for estimating eruption transitions. For example, cases have been found where magma has accumulated in shallower areas than normal magma storage area before an extensive eruption. In addition, a number of volcanoes have been identified where the supply of magma from deeper parts of the volcano has activated a shallow magma chamber, leading to eruptions. This means that the eruption style depends on the state of the shallow magma chamber before the eruption, in particular its temperature and crystalline content, and the amount of deep magma involved. These findings suggest that careful study of past eruptions and ejecta, as well as real-time knowledge of the state of magmas beneath a volcano, is essential for predicting eruption styles and eruption transitions.
To effectively predict eruptive transitions, it is therefore necessary to quickly analyze the ejecta once an eruption has occurred and to understand the characteristics of the magma involved in the eruption. It is also necessary to know the state of the magma ascent pathways, such as the volcanic vent. In doing so, it is important to keep two things in mind: that large amounts of data can be processed quickly, and that the data obtained must be quantitative. Therefore, we are developing both methods for evaluating volcanic pyroclasts and systems for quantitative analysis for these purposes.
Now, in the final phase of the project, information from past eruptive ejecta is being organized to typify the eruptive process. In addition, a simplified model of the magma supply system is being developed. Based on this model, a method for predicting the divergence of eruptive events will be investigated. The method involves firstly predicting the location and timing of various events in the magma-supply system using the simplified model and information from material studies. Then, when an eruption-related event actually occurs, the observations are compared with the model predictions and the eruption model is modified accordingly. It is planned to combine these predictions with simulations and various quantities derived from past eruptions, ultimately leading to predictions of eruption styles and transitions.
The data obtained from the analysis of volcanic ejecta is diverse. Over the course of the project, we have analyzed recent ejecta from 11 volcanoes to identify factors that may be important in predicting eruptive events. As a result, the following points have become clear. First, the main factors determining whether an eruption is explosive or non-explosive are magma composition (especially water content), magma temperature and ejection rate of the magma. Second, the condition of the magma immediately before the eruption is very important for estimating eruption transitions. For example, cases have been found where magma has accumulated in shallower areas than normal magma storage area before an extensive eruption. In addition, a number of volcanoes have been identified where the supply of magma from deeper parts of the volcano has activated a shallow magma chamber, leading to eruptions. This means that the eruption style depends on the state of the shallow magma chamber before the eruption, in particular its temperature and crystalline content, and the amount of deep magma involved. These findings suggest that careful study of past eruptions and ejecta, as well as real-time knowledge of the state of magmas beneath a volcano, is essential for predicting eruption styles and eruption transitions.
To effectively predict eruptive transitions, it is therefore necessary to quickly analyze the ejecta once an eruption has occurred and to understand the characteristics of the magma involved in the eruption. It is also necessary to know the state of the magma ascent pathways, such as the volcanic vent. In doing so, it is important to keep two things in mind: that large amounts of data can be processed quickly, and that the data obtained must be quantitative. Therefore, we are developing both methods for evaluating volcanic pyroclasts and systems for quantitative analysis for these purposes.
Now, in the final phase of the project, information from past eruptive ejecta is being organized to typify the eruptive process. In addition, a simplified model of the magma supply system is being developed. Based on this model, a method for predicting the divergence of eruptive events will be investigated. The method involves firstly predicting the location and timing of various events in the magma-supply system using the simplified model and information from material studies. Then, when an eruption-related event actually occurs, the observations are compared with the model predictions and the eruption model is modified accordingly. It is planned to combine these predictions with simulations and various quantities derived from past eruptions, ultimately leading to predictions of eruption styles and transitions.