A large fraction of volcanic eruptions do not expel magma at the Earth’s surface. Although less known than magmatic eruptions, gas-driven eruptions expel fragments of preexisting rocks, volcanic gases, and steam, causing substantial casualties. The destructive potential of these eruptions lies in the difficulty in identifying clear warning signals. Some gas-driven eruptions have been preceded by some physicochemical changes, but these were extremely short-term (from minutes to hours), and no long-term trends have been clearly evidenced so far. Here, we show that unheralded gas-driven eruptions can be forecast in the long term using seismic signals recorded at nearby active craters. In particular, we have found that the most recent gas-driven eruptions at Kawah Ijen (Indonesia) and Ruapehu and Tongariro (New Zealand) volcanoes were all preceded by a systematic relative increase in lower-frequency (4.5–8 Hz) seismic amplitude compared to higher frequencies (8–16 Hz) over time scales of months to years. We show that this precursory activity reflects significant increases in seismic attenuation affecting preferentially high-frequency travelling waves; this probably results from the accumulation of volatiles in the shallow crust, which increases pore pressure in small-scale rock heterogeneities and eventually leads to gas-driven eruptions. Our results highlight the feasibility of better constraining the onset and the end of an unrest episode, which is of paramount importance for agencies in charge of volcano monitoring.

This study investigates phreatic eruptions at two similar volcanoes, Kawah Ijen (Indonesia) and White Island (New Zealand). By carefully processing broadband seismic signals, we reveal seismic signatures and characteristics of these eruptions. At both volcanoes, the phreatic eruptions are initiated by a very-long-period (VLP) seismic event located at shallow depths between 700 and 900 m below the crater region, and may be triggered by excitation of gas trapped behind a ductile magma carapace. The shallow hydrothermal systems respond in different ways. At Kawah Ijen, the stress change induced by VLPs directly triggers an eigenoscillation of the hyperacidic lake. This so-called seiche is characterized by long-lasting, long-period oscillations with frequencies governed by the dimensions of the crater lake. A progressive lateral rupture of a seal below the crater lake and/or fluids migrating toward the surface is seismically recorded ∼ 15 min later as high-frequency bursts superimposed to tilt signals. At White Island, the hydrothermal system later (∼ 25 min) responds by radiating harmonic tremor at a fixed location that could be generated through eddy-shedding. These seismic signals shed light on several aspects of phreatic eruptions, their generation and timeline. They are mostly recorded at periods longer than tens of seconds further emphasizing the need to deploy broadband seismic equipment close to active volcanic activity.

Volcanoes with crater lakes and/or extensive hydrothermal systems pose significant challenges with respect to monitoring and forecasting eruptions, but they also provide new opportunities to enhance our understanding of magmatic-hydrothermal processes. Their lakes and hydrothermal systems serve as reservoirs for magmatic heat and fluid emissions, filtering and delaying the surface expressions of magmatic unrest and eruption, yet they also enable sampling and monitoring of geochemical tracers. Here, we describe the outcomes of a highly focused international experimental campaign and workshop carried out at Kawah Ijen volcano, Indonesia, in September 2014, designed to answer fundamental questions about how to improve monitoring and eruption forecasting at wet volcanoes.

Although most of volcanic hazard studies focus on magmatic eruptions, volcanic hazardous events can also occur when no migration of magma can be recognized. Examples are tectonic and hydrothermal unrest that may lead to phreatic eruptions. Recent events (e.g., Ontake eruption on September 2014) have demonstrated that phreatic eruptions are still hard to forecast, despite being potentially very hazardous. For these reasons, it is of paramount importance to identify indicators that define the condition of nonmagmatic unrest, in particular for hydrothermal systems. Often, this type of unrest is driven by movement of fluids, requiring alternative monitoring setups, beyond the classical seismic‐geodetic‐geochemical architectures. Here we present a new version of the probabilistic BET (Bayesian Event Tree) model, specifically developed to include the forecasting of nonmagmatic unrest and related hazards. The structure of the new event tree differs from the previous schemes by adding a specific branch to detail nonmagmatic unrest outcomes. A further goal of this work consists in providing a user‐friendly, open‐access, and straightforward tool to handle the probabilistic forecast and visualize the results as possible support during a volcanic crisis. The new event tree and tool are here applied to Kawah Ijen stratovolcano, Indonesia, as exemplificative application. In particular, the tool is set on the basis of monitoring data for the learning period 2000–2010, and is then blindly applied to the test period 2010–2012, during which significant unrest phases occurred.

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