Abstract

The primary goal of operational volcano monitoring is the timely identification of volcanic unrest. This provides critical information to decision makers tasked with mitigating the societal impacts of volcanic eruptions. Volcano deformation is recognized as a key indicator of unrest at many active volcanoes and can be used to provide insight into the depth and geometry of the magma source. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique that has detected deformation at many volcanoes globally, but most often with hindsight. To date, the use of InSAR for operational volcano monitoring has been limited to a few cases and only in high income countries. Yet a vast number of active volcanoes are located in low- and middle-income countries, where resources for operational monitoring are constrained. In these countries, InSAR could provide deformation monitoring at many active volcanoes, including those that have no existing ground monitoring infrastructure. Several barriers combine to make uptake of InSAR into operational volcano monitoring difficult in most countries, but particularly in resource-constrained environments. To overcome some of these limiting factors, we propose a simplified processing chain to better incorporate InSAR and Global Navigation Satellite Systems (GNSS) data into the decision-making process at volcano observatories. To combine the InSAR and GNSS data we use a joint modelling procedure that infers volume changes of a spherical source beneath the volcano. The benefits of our approach for operational use include that the algorithm is computationally lightweight and can be run quickly on a standard desktop or laptop PC. This enables a volcano observatory to interpret geodetic data in a timely fashion, and use the information as part of frequent reporting procedures. To demonstrate our approach we combine ALOS-PALSAR InSAR data and continuous GNSS data from the Rabaul Caldera, Papua New Guinea between 2007 and 2011. Joint inversion of the two datasets indicates volume loss of ~1x107 m3 (deflation) occurring between February 2008 and November 2009, followed by volume gain of ~2.5x106 m3 (inflation) until February 2011 in a magma body situated ~1.5 km beneath the caldera.

Highlights

  • A disproportionately high number of volcanoes that were active in the Holocene are located in low- and middle-income countries (LMICs) (Chester, 2005)

  • Stations “SDA,” “SPT,” and “VIS” show variations in all three components of displacement at the level of 10 cm whereas, station “Rabaul Volcano Observatory (RVO)” is stable during the observed time period. This implies that surface deformation imparted by the magma source or other shallow features is concentrated in the central region of the Rabaul Caldera close to the three Global Navigation Satellite System (GNSS) stations and does not permeate as far north as station “RVO.” This observation enables constraints to be made on the maximum size of the magma source

  • In interferogram #9 (Figure 5) a dominant signal is seen at, and to the east of Tavuvur. It is not clear whether this signal is caused by volcano deformation, atmospheric artefact, or potentially even a volcanic gas plume emanating from Tavuvur at the time of one of the Synthetic Aperture Radar (SAR) image captures

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Summary

Introduction

A disproportionately high number of volcanoes that were active in the Holocene are located in low- and middle-income countries (LMICs) (Chester, 2005). Compounding this volcanic risk, LMICs typically have the densest populations living in proximity of active volcanoes whilst experiencing sustained population growth (Small and Naumann, 2001). Our increasing connectivity and globalization of transportation, communications and economies (e.g., Miller et al, 2016) means that we are more vulnerable to distant volcanic eruptions, for example via aviation routes passing close to active volcanoes (e.g., Alexander, 2013). The ability to detect changes in behaviour at a volcano that may be precursory to an eruption, in a timely manner, can significantly improve the decision-making process (for example regarding local evacuations and aviation alerts)

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