Automated System for Anomalous Volcanic Crustal Deformation Detection and Source Estimation by Using Real Time Observation Data of NIED

Volcanic disaster mitigation based on a short-term prediction of a volcanic eruption requires rapid detection of underground magma movement just before the anticipated eruption. We developed an automated system for detection of anomalous volcanic crustal deformation and estimation of underground magma movement by using the real-time data of the observation networks of NIED deployed in Mt.Fuji, Izu-Oshima Island, Miyakejima Island, and other volcanoes in Japan. The system makes it possible to detect and monitor underground magmatic activity in real-time. It detects an anomalous crustal deformation by using borehole tiltmeter data with high accuracy and high temporal resolution, and searches an appropriate pressure source model for the tilt changes, displacements at GPS stations and earthquake distribution around the volcano. The detection of anomalous tilt changes and the model selection are automatically processed on the basis of objective criterions every hour. After the beginning of its operation, the system succeeded to detect a small dike intrusion event associated with earthquake swarm activities at the east Izu Peninsula in 2009 and a temporal acceleration of inflation of a pressure source beneath the caldera of Izu-Oshima Island in 2010. We expect the system to be able to monitor pressure changes of magma chambers beneath the volcanoes and detect magma rising just before the future eruptions. The processing results are displayed on Google Maps in a Website and exported to KML files for GIS tools to share the monitoring information and to consider it in connection with earthquake activities, lava flow simulations, volcanic hazard maps and other geographical information. The integration of the real-time estimation results of underground magma movement just before eruptions with simulations of various volcanic disasters on the ground after the eruption will provide practical information for volcanic disaster mitigation based on the real-time monitoring data.