Thomas R. Walter's research while affiliated with Universität Potsdam and other places

Hydrothermal alteration processes can affect the physical and chemical properties of volcanic rocks and develop via complex degassing and fluid flow systems and regimes. Although alteration can have far-reaching consequences for rock stability and permeability, little is known about the detailed structures, extent, and dynamic changes that take place in hydrothermal venting systems. By combining drone-based remote sensing with mineralogical and chemical analyses of rock and gas samples, we analyzed the structure and internal anatomy of a dynamic evolving volcanic degassing and alteration system at the La Fossa cone, Vulcano Island (Italy). From drone image analysis, we revealed a ~70,000 m2 sized area subject to hydrothermal activity, for which we could determine distinct alteration gradients. By mineralogical and geochemical sampling of the zones of those alteration gradients, we study the relation between surface coloration and mineralogical and chemical composition. With increasing pixel brightness towards higher alteration gradients, we find a loss of initial mineral fraction and bulk chemical composition and a simultaneous gain in sulfur content. Using this approach, we defined and spatially constrained alteration units and compared them to the present-day thermally active surface and degassing pattern. The combined results permit us to present a detailed anatomy of the La Fossa fumarole field, highlighting 7 major units of alteration and present-day diffuse activity that, next to the high-temperature fumaroles, significantly contribute to the total activity.

The rising velocity of an air bubble in a non‐Newtonian shear‐thinning fluid at low Reynolds numbers is generally similar to the Newtonian case given by Stokes' law. However, when the shear‐thinning fluid is subject to mechanical oscillations, the rising velocity could significantly increase. Here, we present a series of experiments quantifying the rising velocity of single bubbles during shaking in very high‐viscosity (2,000–30,000 Pa·s) shear‐thinning silicone oils. Air bubbles (18–30 mm diameter) were injected in a tank mounted on a shaking table. The tank was horizontally oscillated, at accelerations between 0.4 and 2 g. We observed a small increase in the rising velocity of the shaking cases at our experimental conditions. The increase was larger when bubbles were large and accelerations were high. Larger accelerations experienced the largest observational errors and we emphasize the exploratory nature of our results. We also measured the change in bubble diameter during the oscillations and computed the shear rate at the bubble surface. Maximum shear rates were in the range of 0.04–0.08 s⁻¹. At these shear rates, our analysis indicates that shear thinning behavior of our analog fluids is expected to be small and compete with elastic behavior. This transitional viscous/elastic regime helps explain the small and variable results of our experiments. Our results are relevant to the study of earthquake‐volcano interactions. Most crystal‐free silicate melts would exhibit a purely viscous, shear‐thinning behavior in a natural scenario. Seismically enhanced bubble rise could offer an explanation for the observed increased degassing and unrest following large earthquakes.

Volcanic inflation and deflation often precede eruptions and can lead to seismic velocity changes (dv/v $dv/v$) in the subsurface. Recently, interferometry on the coda of ambient noise‐cross‐correlation functions yielded encouraging results in detecting these changes at active volcanoes. Here, we analyze seismic data recorded at the Klyuchevskoy Volcanic Group in Kamchatka, Russia, between summer of 2015 and summer of 2016 to study signals related to volcanic activity. However, ubiquitous volcanic tremors introduce distortions in the noise wavefield that cause artifacts in the dv/v $dv/v$ estimates masking the impact of physical mechanisms. To avoid such instabilities, we propose a new technique called time‐segmented passive image interferometry. In this technique, we employ a hierarchical clustering algorithm to find periods in which the wavefield can be considered stationary. For these periods, we perform separate noise interferometry studies. To further increase the temporal resolution of our results, we use an AI‐driven approach to find stations with similar dv/v $dv/v$ responses and apply a spatial stack. The impacts of snow load and precipitation dominate the resulting dv/v $dv/v$ time series, as we demonstrate with the help of a simple model. In February 2016, we observe an abrupt velocity drop due to the M7.2 Zhupanov earthquake. Shortly after, we register a gradual velocity increase of about 0.3% at Bezymianny Volcano coinciding with surface deformation observed using remote sensing techniques. We suggest that the inflation of a shallow reservoir related to the beginning of Bezymianny's 2016/2017 eruptive cycle could have caused this local velocity increase and a decorrelation of the correlation function coda.

Volcanic flanks subject to hydrothermal alteration become mechanically weak and gravitationally unstable, which may collapse and develop far-reaching landslides. The dynamics and trajectories of volcanic landslides are hardly preserved and challenging to determine, which is due to the steep slopes and the inherent instability. Here we analyze the proximal deposits of the 21 July 2014, landslide at Askja (Iceland), by combining high-resolution imagery from satellites and Unoccupied Aircraft Systems. We performed a Principal Component Analysis in combination with supervised classification to identify different material classes and altered rocks. We trained a maximum-likelihood classifier and were able to distinguish 7 different material classes and compare these to ground-based hyperspectral measurements that we conducted on different rock types found in the field. Results underline that the Northern part of the landslide source region is a hydrothermally altered material class, which bifurcates halfway downslope and then extends to the lake. We find that a large portion of this material is originating from a lava body at the landslide headwall, which is the persistent site of intense hydrothermal activity. By comparing the classification result to in-situ hyperspectral measurements, we were able to further identify the involved types of rocks and the degree of hydrothermal alteration. We further discuss associated effects of mechanical weakening and the relevance of the heterogeneous materials for the dynamics and processes of the landslide. As the study demonstrates the success of our approach for identification of altered and less altered materials, important implications for hazard assessment in the Askja caldera and elsewhere can be drawn.

Despite the significant progress in our understanding of Merapi and its activity, as demonstrated by the contributions in this book, fundamental scientific questions about the volcano have remained unanswered and there are significant challenges that lie ahead. In this final chapter, we provide a scientific outlook for Indonesia’s most intensely studied and best monitored volcano and explore some of these open questions and upcoming challenges. These comprise open issues regarding the geology, volcanic history, petrogenesis, eruptive activity, volcano monitoring, early warning system, emergency planning, volcanic crisis management, social and communication changes, international collaboration, and the volcano’s current status of activity following the large-magnitude eruption in 2010.

Monitoring and assessing eruption hazard at Merapi volcano are challenging due to steep slopes, the harsh environment at the summit, and hazardous access during both volcanic crises and quiescent intervals. While passive remote sensing techniques often fail due to cloud coverage, active sensing techniques are increasingly used and bridge fields from mapping to geophysical studies. In particular, synthetic aperture radar (SAR) remote sensing and interferometric products are highly valuable at Merapi and similar volcanoes elsewhere, allowing views of the summit, crater, and dome, even when these are covered by dense rain or ash clouds. SAR and interferometric SAR (InSAR) permit assessment of eruption precursors, quantifying rapid geomorphological changes that occur during dome growth and fracturing, such as those in 2010, 2013–14, and 2018. Radar sensing also allows precisely mapping of volcanic deposits, lahars and damage, monitoring subtle ground displacements, and generating high-resolution digital elevation models. This chapter reviews the benefits of radar investigations conducted at Merapi volcano and discusses future directions.

Boiling mud ponds, hot springs, and geysers are the scenic surface expression of rising thermal fluids, often emerging in clusters. The details on the spatial appearance and structural control of such geothermal objects as well as on the variability of their locations are rarely investigated, however. Here we use Unmanned Aerial Systems (UAS) to acquire close-range optical and thermal infrared data over the El Tatio geothermal field (Chile), one of the largest geyser fields in the world. From high-resolution aerial images, processed using the Structure from Motion (SfM) method, we compute spatial image data at 1.5 to 14.5 cm resolution for a ~ 2 km² area. We identify 1863 objects related to geothermal activity, providing an unprecedented catalog of the geothermal area. Out of these, 148 were classified as topography objects (e.g. cone geysers), 415 showed signs of fluid discharge, and 1091 were characterized by a thermal signature exceeding background temperatures. The geothermal objects were further analyzed regarding their spatial distribution and clustering, suggesting a high degree of organization in 5 main groups on a broader scale, and clustering in specific vent arrangements resembling two main orientations on a smaller scale. The 5 zones show significant differences considering their orientation, types of geothermal objects located within, but also their eruptive characteristics, and thermal energy release. We discuss these, considering the structural setup and hydrological setting of the El Tatio geothermal field. Over 90% of the mapped geothermal objects are located within a 100 m distance to an estimated trend line oriented NE-SW. We thus hypothesize a possible structural arrangement controlling the location and activity of geothermal objects at El Tatio with important implications for other geothermal areas worldwide.

Tsunamis caused by large volcanic eruptions and flanks collapsing into the sea are major hazards for nearby coastal regions. They often occur with little precursory activity and are thus challenging to detect in a timely manner. This makes the pre-emptive identification of volcanoes prone to causing tsunamis particularly important, as it allows for better hazard assessment and denser monitoring in these areas. Here, we present a catalogue of potentially tsunamigenic volcanoes in Southeast Asia and rank these volcanoes by their tsunami hazard. The ranking is based on a multicriteria decision analysis (MCDA) composed of five individually weighted factors impacting flank stability and tsunami hazard. The data are sourced from geological databases, remote sensing data, historical volcano-induced tsunami records, and our topographic analyses, mainly considering the eruptive and tsunami history, elevation relative to the distance from the sea, flank steepness, hydrothermal alteration, and vegetation coverage. Out of 131 analysed volcanoes, we found 19 with particularly high tsunamigenic hazard potential in Indonesia (Anak Krakatau, Batu Tara, Iliwerung, Gamalama, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang, Serua) and Papua New Guinea (Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun, Bam) but also in the Philippines (Didicas). While some of these volcanoes, such as Anak Krakatau, are well known for their deadly tsunamis, many others on this list are lesser known and monitored. We further performed tsunami travel time modelling on these high-hazard volcanoes, which indicates that future events could affect large coastal areas in a short time. This highlights the importance of individual tsunami hazard assessment for these volcanoes, the importance of dedicated volcanological monitoring, and the need for increased preparedness on the potentially affected coasts.

The physical processes that operate within, and beneath, a volcano control the frequency, duration, location, and size of volcanic eruptions. Volcanotectonics focuses on such processes, combining techniques, data, and ideas from structural geology, tectonics, volcano deformation, physical volcanology, seismology, petrology, rock and fracture mechanics, and classical physics. A central aim of volcanotectonics is to provide sufficient understanding of the internal processes in volcanoes so that, when combined with monitoring data, reliable forecasting of eruptions, vertical (caldera) and lateral (landslide) collapses and related events becomes possible. To gain such an understanding requires knowledge of the material properties of the magma and the crustal rocks, as well as the associated stress fields, and their evolution. The local stress field depends on the properties of the layers that 2 constitute the volcano and, in particular, the geometric development of its shallow magma chamber. During this decade an increasing use of data from InSAR, pixel offset, and structure-from-motion, as well as dense, portable seismic networks will provide further details on the mechanisms of volcanic unrest, magma-chamber rupture, the propagation of magma-filled fractures (dikes, inclined sheets, and sills), and lateral and vertical collapse. Additionally, more use will be made of accurate quantitative data from fossil and active volcanoes, combined with realistic numerical, analytical, and machine-learning studies, so as to provide reliable models on volcano behaviour and eruption forecasting.

Tsunamis caused by large volcanic eruptions and flanks collapsing into the sea are major hazards for nearby coastal regions. They often occur with little precursory activity, and are thus challenging to detect in a timely manner. This makes the pre-emptive identification of volcanoes prone to causing tsunamis particularly important, as it allows for better hazard assessment and denser monitoring in these areas. Here, we present a catalogue of potentially tsunamigenic volcanoes in Southeast Asia and rank these volcanoes by their tsunami hazard. The ranking is based on a Multicriteria Decision Analysis (MCDA) composed of five individually weighted factors impacting flank stability and tsunami hazard. The data is sourced from geological databases, remote sensing data, historical volcano induced tsunami records and our topographic analyses, mainly considering the eruptive and tsunami history, elevation relative to the distance from the sea, flank steepness, hydrothermal alteration as well as vegetation coverage. Out of 131 analysed volcanoes, we found 19 with particularly high tsunamigenic hazard potential in Indonesia (Anak Krakatau, Batu Tara, Iliwerung, Gamalama, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang, Serua) and Papua New Guinea (Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun, Bam), but also in the Philippines (Didicas). While some of these volcanoes, such as Anak Krakatau, are well-known for their deadly tsunamis, many others on this list are lesser known and monitored. We further performed tsunami travel time modelling on these high-hazard volcanoes, which indicates that future events could affect large coastal areas in a short time. This highlights the importance of individual tsunami hazard assessment for these volcanoes, dedicated volcanological monitoring, and the need for increased preparedness on the potentially affected coasts.