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1. Modelling of the tsunami from the December 22, 2018 lateral collapse of Anak Krakatau volcano in the Sunda Straits, Indonesia

   https://doi.org/10.1038/s41598-019-48327-6  

   Grilli, Stephan T. ; Tappin, David R. ; Carey, Steven ; Watt, Sebastian F. L. ; Ward, Steve N. ; Grilli, Annette R. ; Engwell, Samantha L. ; Zhang, Cheng ; Kirby, James T. ; Schambach, Lauren ; et al ( August 2019 , Scientific Reports)

   On Dec. 22, 2018, at approximately 20:55–57 local time, Anak Krakatau volcano, located in the Sunda Straits of Indonesia, experienced a major lateral collapse during a period of eruptive activity that began in June. The collapse discharged volcaniclastic material into the 250 m deep caldera southwest of the volcano, which generated a tsunami with runups of up to 13 m on the adjacent coasts of Sumatra and Java. The tsunami caused at least 437 fatalities, the greatest number from a volcanically-induced tsunami since the catastrophic explosive eruption of Krakatau in 1883 and the sector collapse of Ritter Island in 1888. For the first time in over 100 years, the 2018 Anak Krakatau event provides an opportunity to study a major volcanically-generated tsunami that caused widespread loss of life and significant damage. Here, we present numerical simulations of the tsunami, with state-of the-art numerical models, based on a combined landslide-source and bathymetric dataset. We constrain the geometry and magnitude of the landslide source through analyses of pre- and post-event satellite images and aerial photography, which demonstrate that the primary landslide scar bisected the Anak Krakatau volcano, cutting behind the central vent and removing 50% of its subaerial extent. Estimated submarine collapse geometries result in a primary landslide volume range of 0.22–0.30 km³, which is used to initialize a tsunami generation and propagation model with two different landslide rheologies (granular and fluid). Observations of a single tsunami, with no subsequent waves, are consistent with our interpretation of landslide failure in a rapid, single phase of movement rather than a more piecemeal process, generating a tsunami which reached nearby coastlines within ~30 minutes. Both modelled rheologies successfully reproduce observed tsunami characteristics from post-event field survey results, tide gauge records, and eyewitness reports, suggesting our estimated landslide volume range is appropriate. This event highlights the significant hazard posed by relatively small-scale lateral volcanic collapses, which can occuren-masse, without any precursory signals, and are an efficient and unpredictable tsunami source. Our successful simulations demonstrate that current numerical models can accurately forecast tsunami hazards from these events. In cases such as Anak Krakatau’s, the absence of precursory warning signals together with the short travel time following tsunami initiation present a major challenge for mitigating tsunami coastal impact.

    

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2. A review of magnetite geochemistry of Chilean iron oxide-apatite (IOA) deposits and its implications for ore-forming processes

   Pamla, G. ( September 2020 , Ore geology reviews)

   null (Ed.)

   Magnetite is the most important iron ore in iron oxide-apatite (IOA) deposits which represent the Cu-poor endmember of the iron oxide-copper–gold (IOCG) clan. Magnetite chemistry has been used as a petrogenetic indicator to identify the geological environment of ore formation and as a fingerprint of the source reservoir of iron. In this study, we present new textural and microanalytical EPMA and LA-ICP-MS data of magnetite from Carmen, Fresia, Mariela and El Romeral IOA deposits located in the Cretaceous Coastal Cordillera of northern Chile. We also provide a comprehensive summary and discussion of magnetite geochemistry from Andean IOAs including Los Colorados, Cerro Negro Norte, El Romeral (Chilean Iron Belt) and the Pliocene El Laco IOA deposit located in the Central Volcanic Zone of the Chilean Andes. Microtextures coupled with geochemical data were used to define and characterize the occurrence of different magnetite types. Magnetite exhibits a variety of textural features including oscillatory zoning, colloform banding, re-equilibration textures, exsolution lamellae and symplectites. The magmatic vs. hydrothermal origin of the different magnetite types and the evolution of IOA deposits can be assessed using diagrams based on compatible trace elements. However, magnetite is very susceptible to hydrothermal alteration and to both textural and compositional re-equilibration during magmatic and superimposed hydrothermal events. Based on the data presented here, we conclude that V and Ga are possibly the most reliable compatible elements in magnetite to trace ore-forming processes in the Andean IOA deposits. Magnetite chemistry reveals different conditions/events of formation for each IOA deposit ranging from high-temperature, low-oxygen fugacity (ƒO2), purely magmatic (> 600 °C) conditions; to lower temperature and higher ƒO2 magmatic-hydrothermal (300–600 °C) to low-temperature hydrothermal (< 200–300 °C) conditions. Specifically, a continuous transition from high-temperature, low- ƒO2 conditions in the deepest portions of the deposits to low-temperature, relatively higher ƒO2 conditions towards surface are described for magnetite from El Laco. The new and compiled magnetite data from IOA deposits from the Chilean Iron Belt and El Laco are consistent with a transition from magmatic to hydrothermal conditions. The flotation model plausibly explains such features, which result from the crystallization of magnetite microlites from a silicate melt, nucleation and coalescence of aqueous fluid bubbles on magnetite surfaces, followed by ascent of a fluid-magnetite suspension along reactivated transtensional faults or through fissures formed during the collapse of the volcanic structure (El Laco). The decompression of the coalesced fluid-magnetite aggregates during ascent promotes the continued growth of magnetite microlites from the Fe-rich magmatic-hydrothermal fluid. As with any general genetic model, the flotation model allows variation and the definition of different styles or subtypes of IOA mineralization. The deeper, intrusive-like Los Colorados deposit shows contrasting features when compared with the Cerro Negro Norte hydrothermal type, the pegmatitic apatite-rich deposits of Carmen, Fresia and Mariela, and the shallow, subaerial deposits of El Laco. These apparent differences depend fundamentally on the depth of formation, the presence of structures and faults that trigger decompression, the composition of the host rocks, and the source and flux rate of hydrothermal fluids. 

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3. Searching for Hidden Microearthquakes using Data-based, Physics-based, and Hybrid Models: Implications for Salt Dome Monitoring

   Omojola, Joses ; Persaud, Patricia ; Catchings, Rufus ; Goldman, Mark ( January 2021 , Southern California Earthquake Center 2021 Conference)

   Earthquakes in stable salt domes are few, with a notable increase in the rate of seismicity prior to catastrophic events, such as the collapse of salt caverns used to store hydrocarbons. Cavern collapse, subsequent gas leakage, and the formation of sinkholes pose a significant hazard for local communities, given that they can disrupt normal societal functions, have various socio-economic impacts, and may result in the evacuation of residents. In Louisiana, one such event was the Bayou Corne collapse in 2012. Following reports of unusual ground tremors, we began monitoring seismicity at the Sorrento salt dome in February 2020. The goal of this study is to improve our understanding of the subsurface processes and their impact on the mechanical integrity of salt domes; we do this by examining the spatio-temporal evolution of the seismicity. We deployed an ~5 km x 4 km nodal array of 12-17 stations, with interstation distances of 0.2 km to 1.9 km, across the dome and recorded eight months of data that were sampled at 500 Hz. Sorrento dome events are usually low in magnitude, often with emergent P-wave onsets, as well as P-waves shrouded in the coda of preceding events, during swarms. Such characteristics make the events difficult to identify using standard automatic detection and location procedures. We first evaluate current methods using an STA/LTA algorithm, coincidence event detectors, and pre-trained, deep-learning detectors and pickers. We find that detection of consistent P-wave phases across several stations for the same event is challenging and poses a major problem for event association and location. To address this problem, we initiate a manual review of all initial event associations to eliminate false positives that could incorrectly inflate the number of events in the catalog. We, therefore, developed a custom-trained detector and picker that outperformed other methods, and it identified multiple events that were recorded by >70% of the stations in the array. Our approach is well-suited for identifying events with emergent P-wave onsets and short durations (~2-10 s), and our method correctly identified a spike in seismicity in the days leading up to a well failure at the dome. Our methodology can be easily adapted for similar types of studies, such as volcano, mine and dam monitoring, and geothermal exploration. 

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4. A Joint Seismic and Space‐Based Investigation of the 2016 Lamplugh Glacier and 2017 Wrangell Mountains (Alaska) Landslides

   https://doi.org/10.1029/2022JF006903  

   Luo, Xinyu ; Fan, Wenyuan ; Fialko, Yuri ( March 2023 , Journal of Geophysical Research: Earth Surface)

   Landslides commonly occur in areas with steep topography and abundant precipitation and pose a significant hazard to local communities. Some of the largest known landslides occur in Alaska, including several that caused local tsunamis. Many landslides may have gone undetected in remote areas due to lack of observations. Here, we develop a semiautomated workflow using both seismic and geodetic observations to detect, locate, validate, and characterize landslides in Alaska. Seismic observations have shown promise in continuously monitoring landslide occurrence, while remote sensing techniques are well suited for verification and high‐resolution imaging of landslides. We validate our procedure using the 28 June 2016, Lamplugh Glacier landslide. We also present observations of a previously unknown landslide occurred on 22 September 2017 in the Wrangell Mountains region. The Wrangell Mountains landslide generated a coherent surface wavefield recorded across Alaska and the contiguous United States. We used Sentinel‐1 Synthetic Aperture Radar and Sentinel‐2 optical imagery to map the respective mass deposit. To investigate the landslide dynamics, we inverted regional seismic surface wave data for a centroid single force failure model. Our model suggests that the Wrangell Mountains landslide lasted for about 140 s and had two subevents involving at least five distinct stages. We estimate that the landslide had displaced 3.1–13.4 million tons of rocks over a distance of ∼2 km. Our results suggest that combining seismic and geodetic observations can vastly improve the detection and characterization of landslides in remote areas in Alaska and elsewhere, providing new insights into the landslide dynamics.

    

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5. QUANTIFYING LANDSCAPE CHANGE AT VERMONT’S LARGEST LANDSLIDE USING TIME-LAPSE SPATIAL DIFFERENCING OF 3D SURFACE MODELS FROM DRONE AND FIELD SURVEY DATA, WATERBURY, VERMONT

   https://doi.org/10.1130/abs/2023SE-385477  

   Klepeis, Keith ; Kim, Jonathan ; Juozelskis, Siga ; Springston, George ; Myrick, Emma ( March 2023 , Geological Society of America Abstracts with Programs)

   On May 31, 2019, a landslide near Waterbury in central Vermont removed >200,000 m3 of glacial lake deposits from a hillside in the Mt. Mansfield State Forest and transported the material across Cotton Brook, creating a dam near its toe. In the months following the slide, the brook breached the toe, removing ≥54, 000 m3 of sediment and transporting it ~1.3 km downstream into the Waterbury reservoir where it formed a large sedimentary delta. The delta grew 243% by Fall, 2020 until it began to erode into the reservoir in 2021. A collaborative team from the Vermont Geological Survey, the Vermont Agency of Transportation, Norwich University, and the University of Vermont team began a yearly monitoring of these events in 2019 using field-based mapping of bedrock and surficial geology, photogrammetry using annual drone surveys, and two LiDAR data sets. The first LiDAR data set was collected in 2014 prior to the slide by the Vermont Center for Geographic Information and the second after the slide in 2021 by the U.S. Army Corp of Engineers. Time-lapse spatial differencing allowed us to (1) quantify changes in surface topography over time, (2) calculate sediment budgets from source (landslide) to sink (delta), and (3) determine how mechanisms of mass wasting changed over time. Through this study we have also documented the following: (a) a second slip event in 2020 that removed ~25, 000 m3 of additional material from the hillside and contributed to growth of the Waterbury reservoir delta, (b) bedrock basins defined by the intersection of bedrock foliation and orthogonal fracture sets that appear to control slip location and geometry, (c) bedrock structures that influence the subsurface hydrology of the slip, which is expressed by oxidized groundwater seeps and a preferential deepening of rills into gullies on one side, and (d) how horizontal variations in the type and thickness of glacial lake sediments influenced mass-wasting mechanisms, including catastrophic failure of the hillside, the slumping of landslide sidewalls, the formation of crescent-shaped earth fractures, channeling around slumps, and the removal of material in deepening gullies. This study shows how a large landslide evolves from a major failure phase through later erosional and colluvial adjustments and supplies sediment at an episodic rate to the surface water system. 

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