Understanding volcanic eruption triggers is critical towards anticipating future activity. While internal magma dynamics typically receive more attention, the influence of external processes remains less understood. In this context, we explore the relationship between seasonal snow cycles and eruptive activity at Ruapehu, New Zealand. This is motivated by apparent seasonality in the eruptive record, where a higher than expected proportion of eruptions (post-1960) occur in spring (including the two previous eruptions of 2006 and 2007). Employing recent advancements in passive seismic interferometry, we compute sub-surface seismic velocity changes between 2005–2009 using the cross-wavelet transform approach. Opposite trends in velocities are identified on and off the volcano, with stations closest to the summit recording a winter high closely correlated with the presence of snow. Inverting for depth suggests these changes occur within the upper 200–300 m. Reduced water infiltration (as precipitation falls as snow) is considered the likely control of seasonal velocities, while modeling also points to a contribution from snow-loading. We hypothesise that this latter process may play a crucial role towards explaining seasonality in the eruptive record. Specifically, loading/unloading may influence the volcanic system through increased degassing, thereby increasing the likelihood of small, gas-driven, eruptions. Our findings shed light on the complex interactions between volcanoes and external environmental processes, highlighting the need for more focused research in this area. Pursuing this line of inquiry has significant implications towards improved risk and hazard assessments at not just Ruapehu, but also other volcanoes globally that experience seasonal snow cover.

We developed an eruption forecasting model using data from multiple sensors or data streams with the Bayesian Network method. The model generates probabilistic forecasts that are interpretable and resilient against sensor outage. We applied the model at Whakaari/White Island, an andesite island volcano off the coast of New Zealand, using seismic tremor recordings, earthquake rate, and CO2, SO2, and H2S emission rates. At Whakaari/White Island, our model shows increases in eruption probability months to weeks prior to the three explosive eruptions that were recorded since 2012. We also observe that explosive eruptions consistently occurred after the cumulative probability exceeded at least 80%. Although developed for Whakaari/White Island, our model can be easily adapted to other volcanoes, complementing existing forecasting methods that rely on single data streams.

Prolonged volcanic activity can induce surface weathering and hydrothermal alteration that is a primary control on edifice instability, posing a complex hazard with its challenges to accurately forecast and mitigate. This study uses a frequently active composite volcano, Mt Ruapehu, New Zealand, to develop a conceptual model of surface weathering and hydrothermal alteration applicable to long-lived composite volcanoes. The rock samples were classified as non-altered, supergene argillic alteration, intermediate argillic alteration, and advanced argillic alteration. The first two classes have a paragenesis that is consistent with surficial infiltration and circulation of the low-temperature (40 degree C) neutral to mildly acidic fluids, inducing chemical weathering and formation of weathering rims on rock surfaces. The intermediate and advanced argillic alterations are formed from hotter (100 degree C) hydrothermal fluids with lower pH, interacting with the andesitic to dacitic host rocks. The distribution of weathering and hydrothermal alteration has been mapped with airborne hyperspectral imaging through image classification, while aeromagnetic data inversion was used to map alteration to several hundred meters depth. The joint use of hyperspectral imaging complements the geophysical methods since it can numerically identify hydrothermal alteration style. This study established a conceptual model of hydrothermal alteration history of Mt Ruapehu, exemplifying a long-lived and nested active and ancient hydrothermal system. This study highlights the need to combine mineralogical information, geophysical techniques and remote sensing to distinguish between current and ancient hydrothermal and supergene alteration systems, to indicate the most likely areas of future debris avalanche initiation.

The rhyolite-producing Laguna del Maule volcanic field (LdMVF) records magma-induced surface inflation rates of ~ 25 cm/year since 2007. During the Holocene, ~60 meters of cumulative surface uplift is recorded by paleoshorelines of the Laguna del Maule, located on the southeast edge of the LdMVF (Chile-Argentina border) near the Barrancas volcanic complex. Rhyolites from the Barrancas complex erupted over ~14 ka including some of the youngest (1.4 ± 0.6 ka) lava flows in the field. New gravity data collected on the Barrancas complex reveals a Bouguer low (-6 mGal, Barrancas anomaly) that is distinct from the pronounced gravity low (-19 mGal; Lake anomaly) associated with present-day deformation and magma intrusion to the north. Three-dimensional inversion of the Barrancas anomaly indicates the presence of a magma body with a maximum density contrast of -250 kg/m3 centered at a depth of ~ 3 km below surface. Comparison of model densities with measured densities from nearby silicic plutons suggest that a magma body, containing < 30 % melt phase and a low volatile content, exists beneath the Barrancas complex. The Barrancas and Lake gravity lows represent magma in different physical states, associated with past and present-day storage beneath the LdMVF. The gravity model mirrors existing geochemical observations which independently indicate that at least two distinct rhyolites were generated and stored as discrete magma bodies within the broader LdMVF. Small temperature changes of these discrete bodies could reverse crystallization and viscous lock-up and propel magma toward a crystal-poor eruptible state.