Geology topics

Michael E. West

Publications and source records attributed to Michael E. West.

15 recordsLinked to original sources

USGS2026

A 481 m-high landslide-tsunami in a cruise ship-frequented Alaska fjord

Early in the morning of 10 August 2025, a >64 × 10 6 –cubic meter landslide struck Tracy Arm fjord in Alaska. The landslide was preconditioned by glacial retreat caused by climate change. The resulting 481-meter runup megatsunami followed an initial 100-meter-high breaking wave traveling at >70 meters per second. The landslide was preceded by several days of microseismicity, which increased in rate and magnitude until ~1 hour before failure. The landslide produced globally observed long-period seismic waves equivalent in size to a moment magnitude 5.4 earthquake. A long-period (~66 second) global seismic signal, produced by a landslide-induced seiche trapped within the fjord, persisted for up to 36 hours, the second time a days-long seiche had thus been observed. With fjord regions increasingly visited by cruise ships, and climate change making similar events more likely, this unanticipated, near-miss event highlights the growing risk from landslides and tsunamis in coastal environments.

Alaska↗

USGS2026

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗

USGS2026

Earthquake catalog for the Fairbanks region of central Alaska, 2014–2024, based on waveform cross-correlation

The Fairbanks region of central Alaska is part of a broad zone of intraplate crustal deformation, situated north of the Denali fault and north of the ongoing collision and flat‐slab subduction of the Yakutat oceanic plateau. Seismicity in the Fairbanks region occurs both in diffuse areas as well as in well‐defined lineaments, such as the left‐lateral Salcha fault, which hosted the 1937 M 8 7.3 earthquake. Starting with the regional seismicity catalog, we perform waveform cross‐correlation, network‐matched filtering, and relative relocation to obtain an enhanced seismicity catalog over the time period 2014–2024. Based on the relocated catalog, we interpret a set of 15 fault segments, including two conjugate faults and two new faults east of the previously documented fault system. Considering the combined seismicity in the Minto and Fairbanks regions, the median depth of seismicity decreases from east (6 km) to west (20 km). Our interpreted faults provide guidance for future tectonic modeling and assessment of seismic hazards in this region.

Alaska↗

USGS2025

Searching for seismic precursors - The Barry Landslide hazard clean up

The Barry Landslide, located in Barry Arm of Prince William Sound, Alaska, poses a major hazard due to its steep, unstable slopes and the potential for a massive landslide-generated tsunami. With an estimated volume of 500–700 million cubic meters, the Barry Landslide could trigger highly destructive waves. In this study, we focus on seismic signals from the Barry Landslide, which are critical for providing timely tsunami warnings. Since the summer of 2020, the region has been instrumented to monitor the landslide, but the seismic record is complicated by the presence of nearby glaciers and frequent regional earthquakes. Among these signals, we analyze a specific class of short-duration, high-frequency seismic events that exhibit strong seasonal variability, increasing in rate from late summer to mid-winter before ceasing abruptly in late winter or early spring. Our analysis suggests that the source of these signals is likely near or beneath Cascade Glacier, adjacent to the landslide, rather than within the landslide mass itself. We apply detection algorithms to construct a time history for this signal type, which we then compare with environmental factors like precipitation, temperature, and slope displacement data from ground-based radar and remote sensing. Correlations indicate that these seismic events may be driven by seasonal hydrological changes, particularly the freeze-up of subglacial water pathways. While these events are not directly linked to landslide motion, they serve as indirect markers of subsurface hydrological conditions that influence slope stability. Our findings highlight the complex interplay between glaciers, groundwater, and landslide dynamics, emphasizing the need for multi-parameter monitoring to assess evolving geohazards in the region.

Alaska↗

USGS2025

High-precision earthquake catalog for Minto Flats fault zone, central Alaska, reveals complex and conjugate faulting

The Minto Flats fault zone (MFFZ) in central Alaska is a left‐lateral strike‐slip fault system situated between the continental‐scale right‐lateral Denali and Kaltag‐Tintina faults. The MFFZ has the potential to generate magnitude 7 earthquakes, and it hosted a magnitude 6 earthquake in 1995. It has also produced exotic events, such as very‐low‐frequency earthquakes and nucleation signals. We use network‐matched filtering and relative earthquake relocation techniques to derive a detailed catalog of earthquake locations for the MFFZ. The catalog spans from August 2014 to December 2019, a time period including 13 temporary seismic stations in the region. Our results provide the most complete catalog for the MFFZ and include deeper events, clusters of shallow seismicity, and a complex and segmented fault structure not observed in the original regional catalog. We document right‐lateral strike‐slip faulting, conjugate to the main northeast‐striking left‐lateral faults of the MFFZ. Below Nenana basin, the relocated seismicity reveals northwest‐dipping left‐lateral faults, supporting the inference that deep crustal active faulting is associated with recent basin deformation.

Alaska↗

USGS2025

2024 Surprise Inlet landslides: Insights from a prototype landslide‐triggered tsunami monitoring system in Prince William Sound, Alaska

Alaska's coastal communities face growing landslide hazards owing to glacier retreat and extreme weather intensified by the warming climate, yet hazard monitoring remains challenging. As part of ongoing experimental monitoring in Prince William Sound, we detected three large landslides (0.5–2.3 M m 3 ) at Surprise Inlet on 20 September 2024, within the span of an hour. These events were identified in near real-time through seismic data and later confirmed using satellite imagery, tidal records, and infrasound. The landslides generated a modest tsunami, and a 4 cm wave was recorded by a tide gauge 18 km away, marking the first recorded landslide to reach water since monitoring began in this region in 2021. Here, we examine the detection and interpretation of these landslides using multiple data sources and modeling. We demonstrate the effectiveness of this regional seismic monitoring system and show how complementary instrumentation, where available, can enhance detection capabilities.

Alaska↗

USGS2025

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

Alaska↗

USGS2023

Kinematic evolution of a large paraglacial landslide in the Barry Arm fjord of Alaska

Our warming climate is adversely affecting cryospheric landscapes via glacial retreat, permafrost degradation, and associated slope destabilization. In Prince William Sound, Alaska, the rapid retreat of Barry Glacier has destabilized the slopes flanking the glacier, resulting in numerous landslides. The largest of these landslides (∼500 Mm 3 in volume) is more than 2 km wide and has the potential to generate a tsunami that could affect nearby recreationists, marine traffic, infrastructure, natural and cultural resources, and the community of Whittier, located 60 km from the landslide. Here, we combine landslide structural and kinematic element mapping with data acquired from bi-yearly airborne lidar, multi-week satellite-based synthetic aperture radar (SAR), sub-hourly ground-based SAR, and seismic monitoring from 2020 to 2022 to characterize this landslide and examine its evolution. While some methods serve as a snapshot in time that is a culmination of events, others emphasize the ever-evolving nature of the landslide and associated hazards. Four major kinematic elements define the overall structure of the landslide, which vary in deformation type and rate, from creep (5 mm per day over several months) to episodic movement (2 m in 30 days) and landslide-wide to localized events. In some areas of the landslide, short-term deformation deviates from structures formed by cumulative movement, implying structural and kinematic evolution associated with glacier retreat. These insights are important for assessing landslide hazards and hazard evolution for large, slow-moving bedrock landslides in actively deglaciating environments.

Alaska↗

USGS2019

The 30 November 2018 Mw7.1 Anchorage Earthquake

The M w "> M w 7.1 47 km deep earthquake that occurred on 30 November 2018 had deep societal impacts across southcentral Alaska and exhibited phenomena of broad scientific interest. We document observations that point to future directions of research and hazard mitigation. The rupture mechanism, aftershocks, and deformation of the mainshock are consistent with extension inside the Pacific plate near the down‐dip limit of flat‐slab subduction. Peak ground motions > 25 % g "> g >25%g were observed across more than 8000    km 2 "> 8000 km 2 ⁠ , though the most violent near‐fault shaking was avoided because the hypocenter was nearly 50 km below the surface. The ground motions show substantial variation, highlighting the influence of regional geology and near‐surface soil conditions. Aftershock activity was vigorous with roughly 300 felt events in the first six months, including two dozen aftershocks exceeding M 4.5. Broad subsidence of up to 5 cm across the region is consistent with the rupture mechanism. The passage of seismic waves and possibly the coseismic subsidence mobilized ground waters, resulting in temporary increases in stream flow. Although there were many failures of natural slopes and soils, the shaking was insufficient to reactivate many of the failures observed during the 1964 M 9.2 earthquake. This is explained by the much shorter duration of shaking as well as the lower amplitude long‐period motions in 2018. The majority of observed soil failures were in anthropogenically placed fill soils. Structural damage is attributed to both the failure of these emplaced soils as well as to the ground motion, which shows some spatial correlation to damage. However, the paucity of instrumental ground‐motion recordings outside of downtown Anchorage makes these comparisons challenging. The earthquake demonstrated the challenge of issuing tsunami warnings in complex coastal geographies and highlights the need for a targeted tsunami hazard evaluation of the region. The event also demonstrates the challenge of estimating the probabilistic hazard posed by intraslab earthquakes.

Alaska↗

USGS2015

Tidal and seasonal variations in calving flux observed with passive seismology

The seismic signatures of calving events, i.e., calving icequakes, offer an opportunity to examine calving variability with greater precision than is available with other methods. Here using observations from Yahtse Glacier, Alaska, we describe methods to detect, locate, and characterize calving icequakes. We combine these icequake records with a coincident, manually generated record of observed calving events to develop and validate a statistical model through which we can infer iceberg sizes from the properties of calving icequakes. We find that the icequake duration is the single most significant predictor of an iceberg's size. We then apply this model to 18 months of seismic recordings and find elevated iceberg calving flux during the summer and fall and a pronounced lull in calving during midwinter. Calving flux is sensitive to semidiurnal tidal stage. Large calving events are tens of percent more likely during falling and low tides than during rising and high tides, consistent with a view that deeper water has a stabilizing influence on glacier termini. Multiple factors affect the occurrence of mechanical fractures that ultimately lead to iceberg calving. At Yahtse Glacier, seismology allows us to demonstrate that variations in the rate of submarine melt are a dominant control on iceberg calving rates at seasonal timescales. On hourly to daily timescales, tidal modulation of the normal stress against the glacier terminus reveals the nonlinear glacier response to changes in the near-terminus stress field.

Alaska↗

USGS2015

Subglacial discharge at tidewater glaciers revealed by seismic tremor

Subglacial discharge influences glacier basal motion and erodes and redeposits sediment. At tidewater glacier termini, discharge drives submarine terminus melting, affects fjord circulation, and is a central component of proglacial marine ecosystems. However, our present inability to track subglacial discharge and its variability significantly hinders our understanding of these processes. Here we report observations of hourly to seasonal variations in 1.5–10 Hz seismic tremor that strongly correlate with subglacial discharge but not with basal motion, weather, or discrete icequakes. Our data demonstrate that vigorous discharge occurs from tidewater glaciers during summer, in spite of fast basal motion that could limit the formation of subglacial conduits, and then abates during winter. Furthermore, tremor observations and a melt model demonstrate that drainage efficiency of tidewater glaciers evolves seasonally. Glaciohydraulic tremor provides a means by which to quantify subglacial discharge variations and offers a promising window into otherwise obscured glacierized environments.

Alaska↗

USGS2014

Why the 1964 Great Alaska Earthquake matters 50 years later

Spring was returning to Alaska on Friday 27 March 1964. A two‐week cold snap had just ended, and people were getting ready for the Easter weekend. At 5:36 p.m., an earthquake initiated 12 km beneath Prince William Sound, near the eastern end of what is now recognized as the Alaska‐Aleutian subduction zone. No one was expecting this earthquake that would radically alter the coastal landscape, influence the direction of science, and indelibly mark the growth of a burgeoning state.

Alaska↗

USGS2010

Glacier microseismicity

We present a framework for interpreting small glacier seismic events based on data collected near the center of Bering Glacier, Alaska, in spring 2007. We find extremely high microseismicity rates (as many as tens of events per minute) occurring largely within a few kilometers of the receivers. A high-frequency class of seismicity is distinguished by dominant frequencies of 20–35 Hz and impulsive arrivals. A low-frequency class has dominant frequencies of 6–15 Hz, emergent onsets, and longer, more monotonic codas. A bimodal distribution of 160,000 seismic events over two months demonstrates that the classes represent two distinct populations. This is further supported by the presence of hybrid waveforms that contain elements of both event types. The high-low-hybrid paradigm is well established in volcano seismology and is demonstrated by a comparison to earthquakes from Augustine Volcano. We build on these parallels to suggest that fluid-induced resonance is likely responsible for the low-frequency glacier events and that the hybrid glacier events may be caused by the rush of water into newly opening pathways.

Alaska↗

USGS2010

Seismic precursors to volcanic explosions during the 2006 eruption of Augustine Volcano

The 2006 eruption of Augustine Volcano, Alaska, generated more than 3,500 earthquakes in a month-long time frame bracketing the most explosive period of activity. We examine two quantitative tools that, in retrospective analysis, were excellent indicators of imminent eruption. The first tool, referred to as the frequency index ( FI ), is based on a simple ratio of high- and low-frequency energy in an earthquake seismogram. It is a metric that allows us to quantify the differences between the canonical high-frequency, hybrid, and low-frequency volcanic earthquakes. FI values greater than -0.4 indicate earthquakes classically referred to as high-frequency or volcano-tectonic events. FI values less than -1.3 correspond to events usually referred to as low-frequency earthquakes. Because the FI is based on a ratio and not a spectral peak, hybrid earthquakes are successfully assigned FI values intermediate to these two classes. In this eruption, we find a remarkable correlation between events with FI less than -1.8 and explosive eruptions. The second tool we examine is based on repeating seismic waveforms identified through waveform cross-correlation. Although the vast majority of earthquakes during this eruption have unique waveforms, subsets of events exhibiting a high degree of similarity occur and are closely tied to explosive eruption events. Of the 13 large explosion events, seven were preceded by clusters of highly similar earthquakes. We apply the FI and correlation tools together to identify changes in high- and low-frequency earthquake occurrences and examine their relations to the precursory, explosive, and continuous phases of the eruption. We find that earthquakes that have low FI values and earthquakes exhibiting high degrees of similarity occur almost exclusively within hours of explosive eruptions and postulate that they occur as a result of the final ascent of magma in the volcanic edifice. Because neither of these methods requires analyst-reviewed earthquake locations, we believe that they have considerable potential as automated real-time volcano monitoring tools.

Alaska↗

USGS2010

The 2006 eruption of Augustine Volcano - Combined analyses of thermal satellite data and reduced displacement

Augustine Volcano erupted explosively after 20 years of quiescence on January 11, 2006, followed by approximately 2 months of dome building and lava extrusion. This is the best monitored eruption in Alaska to date; the diverse complementary datasets gathered enable an interdisciplinary interpretation of volcanic activity. An analysis of reduced displacement (continuous measure of seismic tremor amplitude) and thermal energy output (from satellite imagery) observed between January 1 and April 30, 2006, shows relationships linked to the type of eruptive activity. Three different types of volcanic behavior can be identified as they show specific patterns in the combined data sets: (1) explosive activity, (2) lava extrusion (dome growth), and (3) cooling of erupted products. Explosive activity was characterized by high reduced displacement values but relatively low radiative thermal flux. Lava extrusion occurred in three distinct sequences characterized by increased values of reduced displacement and increased thermal emissions. Two periods of elevated thermal energy output and reduced displacement coincided with times of deflation, suggesting an increase in extrusion rate. Periods of cooling were marked by decreasing thermal emissions and reduced displacement. This work highlights the value of combined observations, which reveal more about the status of an active volcano than individual methods alone.

Alaska↗