Geology topics

Kate E. Allstadt

Publications and source records attributed to Kate E. Allstadt.

At least 37 records · Page 2Linked to original sources

USGS2022

Insights on multistage rock avalanche behavior from runout modeling constrained by seismic inversions

Inversion of low-frequency regional seismic records to solve for a time series of bulk forces exerted on the earth by a landslide (a force-time function) is increasingly being used to infer volumes and dynamics of large, highly energetic landslides, such as rock avalanches and flowslides, and to provide calibration information on event dynamics and volumes for numerical landslide runout models. Much of the work to date using landslide runout modeling constrained by seismic data has focused on using single-phase models with frictional or velocity-weakening rheologies. Awareness of multistage landslide initiations is increasing, with discrete failures separated in time contributing to the final impact of an event. Our work utilizes a method for incorporating seismic data as a calibration constraint for landslide runout models, considering variable rheologies and different initiation conditions. This study presents a systematic examination of multiple rheologies and initiation conditions, and shows how these factors affect the force-time function derived from the landslide runout model. Our work confirms that, while rheology and fragmenting or initially coherent initiations affect the force-time function, multiple collapses separated by tens of seconds have the greatest impact on the shape and amplitude. We apply this method to the analysis of three real rock avalanches to better constrain plausible initiation conditions and rheology parameters using both seismic and field data. This study provides insights on how assumptions about the initiation dynamics of the source zone and the runout model definition can aid in the interpretation of seismic inversions for multistage rock avalanches.

Journal of Geophysical Research: Solid Earth↗

USGS2022

Seismometer records of ground tilt induced by debris flows

A change in surface loading causes the Earth’s surface to deform. Mass movements, such as debris flows, can cause a tilt large enough to be recorded by nearby instruments, but the signal is strongly dependent on the mass loading and subsurface parameters. Specifically designed sensors for such measurements (tiltmeters) are cumbersome to install. Alternatively, broadband seismometers record translational motion and also tilt signals, often at periods of tens to hundreds of seconds. Their horizontal components are thereby the most sensitive to tilt. In this study, we show how to obtain tilt caused by the passing by of debris flows from seismic measurements recorded within tens of meters of the flow and investigate the usefulness of this signal for flow characterization. We investigate the problem on three scales (1) large‐scale laboratory experiments at the U.S. Geological Survey debris‐flow flume, where broadband seismometers and tiltmeters were installed for six 8 – 10    m 3 "> 8 – 10 m 3 experiments, (2) the Illgraben torrent in Switzerland, one of the most active mass wasting sites in the European Alps, where a broadband seismometer placed within a few meters of the channel recorded 15 debris‐flow events with volumes up to 10 5    m 3 "> 10 5 m 3 ⁠ , and (3) Volcán de Fuego, Guatemala, where a broadband seismometer recorded two lahars. We investigate how the tilt signals compare to debris‐flow parameters such as mean normal stresses, usually measured by expensive force plates, and debris‐flow height. We model the elastic ground deformation as the response of an elastic half‐space to a moving surface load. In addition, we use the model with some simplifications to determine the maximum debris‐flow heights of Volcán de Fuego events, where no force plate measurements are available. Finally, we address how and under what assumptions the relatively affordable and straightforward tilt measurements may be utilized to infer debris‐flow parameters, as opposed to force plates and other complicated instrument setups.

Oregon↗

USGS2022

Ground failure triggered by the 7 January 2020 M6.4 Puerto Rico earthquake

The 7 January 2020 M 6.4 Puerto Rico earthquake, the mainshock of an extended earthquake sequence, triggered significant ground failure. In this study, we detail the ground failure that occurred based largely on a postearthquake field reconnaissance campaign that we conducted. We documented more than 300 landslides, mainly rock falls that were concentrated in areas where peak ground acceleration (PGA) exceeded 30% g ; sparse smaller landslides occurred in highly susceptible areas more than 50 km from the epicenter and at PGA values <10% g . Though some of the largest mass movements were in natural slopes, rock falls in road cuts had more impact because they caused widespread transportation disruption. Some structures also were damaged by landslides, but no landslide‐related fatalities were reported. Liquefaction and related lateral spreading were severe in some areas, causing damage to residential and commercial structures and a power plant. Most of the liquefaction occurred in coastal areas where shaking exceeded 50% g , though some of the most damaging instances were in Ponce, where shaking estimates were as low as 20% g . In this article, we summarize the most notable ground failures and detail the overall patterns that we observed. The observations and compiled inventory datasets presented here are valuable because no island‐wide hazard maps for earthquake‐triggered landslides or liquefaction have been developed for Puerto Rico, and postevent inventories are vital for such an effort. In general, the datasets presented here contribute to a global understanding of coseismic ground‐failure hazard by presenting detailed observations for a relatively moderate ground‐failure event with well‐constrained shaking estimates; current models and expectations are biased by the tendency to collect detailed datasets mainly for exceptional events.

Puerto Rico↗

USGS2022

Integrated strategies for enhanced rapid earthquake shaking, ground failure, and impact estimation employing remotely sensed and ground truth constraints

Estimating earthquake impacts using physical or empirical models is challenging because the three components of loss estimation-shaking, exposure, and vulnerabilities-entail inherent uncertainties. Loss modeling in near-real-time adds additional uncertainties, yet expectations for actionable information with a reasonable level of confidence in the results are real. The modeling approaches described herein augment inherently uncertain prior hazard and loss models with an integrated strategy for updating these priors with ground-truth observations, thereby greatly reducing their uncertainties. Two strategies are employed. Early reports of casualties are used in a Bayesian updating fashion to constrain the possible range of fatalities and to lower the prior models' uncertainties. Additionally, remotely sensed satellite radar data, in the form of a Damage Proxy Map (or DPM), are used in a Bayesian causal graph framework combined with machine learning to optimize the mapping among the physical processes that cause shaking-based building damage, landslides, and liquefaction to prior expectation models. The casual graph framework also affords the potential for removing anthropogenetic noise contained in the imagery. Ultimately, our two-fold model updating strategy will accommodate key ground-truth observations such as fatality reports, locations of building damage, and ground failure reports to converge on actual losses more rapidly.

Conference Paper↗

USGS2021

Landslides triggered by the August 14, 2021, magnitude 7.2 Nippes, Haiti, earthquake

The August 14, 2021, magnitude 7.2 Nippes, Haiti, earthquake triggered thousands of landslides on the Tiburon Peninsula. The landslides directly caused fatalities and damage and impeded response efforts by blocking roads and causing other infrastructure damage. Adverse effects of the landslides likely will continue for months to years. This report presents an assessment of potential postearthquake landslide-related geologic hazards for the Tiburon Peninsula and a preliminary map of the landslides triggered by the earthquake. This hazard assessment is based on an emergency analysis of the currently available, postearthquake satellite imagery. In this report, we highlight specific areas of concern that may benefit from more detailed assessment and longer-term monitoring. Our mapping efforts revealed that at least 4,893 landslides were triggered across the Tiburon Peninsula by the earthquake and subsequent rainfall from Tropical Cyclone Grace. We also observed hundreds of landslide deposits potentially restricting flow in rivers and streams. In addition, we observed landslides that likely affected roads by rendering them impassable or susceptible to subsequent damage from existing landslides. Because of the preliminary nature of this report and the limits of remote analyses, additional investigation and monitoring would be beneficial to accurately determine the threat posed by these hazards to people and infrastructure.

Nippes↗

USGS2021

The US Geological Survey ground failure product: Near-real-time estimates of earthquake-triggered landslides and liquefaction

Since late 2018, the US Geological Survey (USGS) ground failure (GF) earthquake product has provided publicly available spatial estimates of earthquake-triggered landslide and liquefaction hazards, along with the qualitative hazard and population exposure-based alerts for M > 6 earthquakes worldwide and in near real time (within ∼30 min). Earthquake losses are oftentimes greatly aggravated by the impacts due to ground failure, yet those particular events with dramatic additional losses have not, heretofore, been rapidly identifiable. The GF product now provides situational awareness about the potential extent and severity of ground failure in the crucial time period before direct observations are available. We describe our implementation of the GF product and the lessons learned from the earthquakes that have occurred since the GF product was released. We describe the product design process, the underlying GF models, the methods we have developed for modeling uncertainty, and the development of the alert levels. The GF product has been produced in near real time for 320 events over the 2-year period since its public implementation in late 2018 through early 2021. The majority of these events yielded the lowest level (green) alerts for all ground-failure types, with 25 resulting in elevated hazard or exposure to landslides and 47 for liquefaction. In a qualitative comparison between the GF product alerts and GF occurrence information, we found that the product succeeds at assigning appropriate alert levels in the majority of cases. Based on our experience with the product, we have identified the following priorities for future improvements: (1) refinements of the underlying probabilistic models to incorporate severity and explicitly model the type of landslide/liquefaction; (2) development of models for fatalities and economic losses due to ground failure; and (3) estimation of the impacts of ground failure on infrastructure.

Earthquake Spectra↗

USGS2021

A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides

Coseismic landslides are a major source of transportation disruption in mountainous areas, but few approaches exist for rapidly estimating impacts to road networks. We develop a model that links the U.S. Geological Survey (USGS) near-real-time earthquake-triggered landslide hazard model with Open Street Map (OSM) road network data to rapidly estimate segment-level obstruction risk following major earthquake activity worldwide. To train and validate the model, we process OSM data for 15 historical earthquakes and calculate the average segment-level landslide hazard from the USGS model for each event. We then fit a multivariate adaptive regression spline model for the probability of road obstruction as a function of road segment length and landslide hazard, using a training and validation dataset derived from the intersections of road networks with earthquake-triggered landslide inventories. The resulting probabilistic model is well calibrated across a range of earthquake events, with estimated obstruction probabilities matching the relative frequency of potential road obstructions. The model runs quickly and is capable of producing road segment-level obstruction estimates within minutes to hours of a major earthquake. However, in near-real-time application, the accuracy of the obstruction estimates will be dependent on the quality of the ShakeMap shaking estimates, which often improves with time as more information becomes available after the earthquake. By providing a rapid first-order translation of landslide hazard into potential infrastructure impacts, this model helps provide emergency responders with tangible information on initial areas of concern.

Earthquake Spectra↗

USGS2021

Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake

Earthquake-induced landslide inventories can be generated using field observations but doing so can be challenging if the affected landscape is large or inaccessible after an earthquake. Remote sensing data can be used to help overcome these limitations. The effectiveness of remotely sensed data to produce landslide inventories, however, is dependent on a variety of factors, such as the extent of coverage, timing, and data quality, as well as environmental factors such as atmospheric interference (e.g., clouds, water vapor) or snow and vegetation cover. With these challenges in mind, we use a combination of field observations and remote sensing data from multispectral, light detection and ranging (lidar), and synthetic aperture radar (SAR) sensors to produce a ground failure inventory for the urban areas affected by the 2018 magnitude (M w ) 7.1 Anchorage, Alaska earthquake. The earthquake occurred during late November at high latitude (∼61°N), and the lack of sunlight, persistent cloud cover, and snow cover that occurred after the earthquake made remote mapping challenging for this event. Despite these challenges, 43 landslides were manually mapped and classified using a combination of the datasets mentioned previously. Using this manually compiled inventory, we investigate the individual performance and reliability of three remote sensing techniques in this environment not typically hospitable to remotely sensed mapping. We found that differencing pre- and post-event normalized difference vegetation index maps and lidar worked best for identifying soil slumps and rapid soil flows, but not as well for small soil slides, soil block slides and rock falls. The SAR-based methods did not work well for identifying any landslide types because of high noise levels likely related to snow. Some landslides, especially those that resulted in minor surface displacement, were identifiable only from the field observations. This work highlights the importance of the rapid collection of field observations and provides guidance for future mappers on which techniques, or combination of techniques, will be most effective at remotely mapping landslides in a subarctic and urban environment.

Alaska↗

USGS2021

lsforce: A Python-based single-force seismic inversion framework for massive landslides

We present an open‐source Python package, lsforce, for performing single‐force source inversions of long‐period (tens to hundreds of seconds) seismic signals. Although the software is designed primarily for landslides, it can be used for any single‐force seismic source. The package allows users to produce estimates of the three‐component time series of forces exerted on the Earth by a landslide with postprocessing options to estimate the trajectory of its center of mass. Green’s functions for a user‐selected 1D Earth model are obtained automatically from the Incorporated Research Institutions for Seismology Synthetics Engine webservice or can be computed for custom 1D Earth models using Computer Programs in Seismology. lsforce implements the two most commonly used source parameterizations: a fully flexible, high‐resolution approach and a more stable but lower‐resolution method of overlapping triangle sources. Regularization options include a blended zeroth‐, first‐, and second‐order semiautomated Tikhonov regularization scheme, as well as additional optional constraints on start times, end times, and on the sum of forces. Uncertainty due to data selection can be assessed using either a leave‐one‐out approach or a modified jackknife technique that randomly excludes subsets of the data for multiple re‐inversions. Numerous built‐in plotting methods allow for easy quality control and assessment of results. In this article, we briefly outline the theory and methodology, describe our implementation, and demonstrate the usage of lsforce using the well‐studied 28 June 2016 Lamplugh rock avalanche in Alaska. Despite the rapidly increasing prevalence of landslide single‐force inversions in the landslide and seismology literature over the past decade, to our knowledge this is the first open‐source code for performing such inversions.

Seismological Research Letters↗

USGS2021

Reconstructing the dynamics of the highly similar May 2016 and June 2019 Iliamna Volcano, Alaska ice–rock avalanches from seismoacoustic data

Surficial mass wasting events are a hazard worldwide. Seismic and acoustic signals from these often remote processes, combined with other geophysical observations, can provide key information for monitoring and rapid response efforts and enhance our understanding of event dynamics. Here, we present seismoacoustic data and analyses for two very large ice–rock avalanches occurring on Iliamna Volcano, Alaska (USA), on 22 May 2016 and 21 June 2019. Iliamna is a glacier-mantled stratovolcano located in the Cook Inlet, ∼200 km from Anchorage, Alaska. The volcano experiences massive, quasi-annual slope failures due to glacial instabilities and hydrothermal alteration of volcanic rocks near its summit. The May 2016 and June 2019 avalanches were particularly large and generated energetic seismic and infrasound signals which were recorded at numerous stations at ranges from ∼9 to over 600 km. Both avalanches initiated in the same location near the head of Iliamna's east-facing Red Glacier, and their ∼8 km long runout shapes are nearly identical. This repeatability – which is rare for large and rapid mass movements – provides an excellent opportunity for comparison and validation of seismoacoustic source characteristics. For both events, we invert long-period (15–80 s) seismic signals to obtain a force-time representation of the source. We model the avalanche as a sliding block which exerts a spatially static point force on the Earth. We use this force-time function to derive constraints on avalanche acceleration, velocity, and directionality, which are compatible with satellite imagery and observed terrain features. Our inversion results suggest that the avalanches reached speeds exceeding 70 m s−1, consistent with numerical modeling from previous Iliamna studies. We lack sufficient local infrasound data to test an acoustic source model for these processes. However, the acoustic data suggest that infrasound from these avalanches is produced after the mass movement regime transitions from cohesive block-type failure to granular and turbulent flow – little to no infrasound is generated by the initial failure. At Iliamna, synthesis of advanced numerical flow models and more detailed ground observations combined with increased geophysical station coverage could yield significant gains in our understanding of these events.

Alaska↗

USGS2021

Using high sample rate lidar to measure debris-flow velocity and surface geometry

Debris flows evolve in both time and space in complex ways, commonly starting as coherent failures but then quickly developing structures such as roll waves and surges. These processes are readily observed but difficult to study or quantify because of the speed at which they evolve. Many methods for studying debris flows consist of point measurements (e.g., flow height or basal stresses), which are inherently limited in spatial coverage and cannot fully characterize the spatiotemporal evolution of a flow. In this study, we use terrestrial lidar to measure debris-flow profiles at high sampling rates to examine debris-flow movement with high temporal and spatial precision and accuracy. We acquired measurements during gate-release experiments at the U.S. Geological Survey debris-flow flume, a unique experimental facility where debris flows can be artificially generated at a large scale. A lidar scanner was used to record repeat topographic profiles of the moving debris flows along the length of the flume with a narrow swath width (∼1 mm) at a rate of 60 Hz. The high-resolution lidar profiles enabled us to quantify flow front velocity of the debris flows and provided an unprecedented record of the development and evolution of the flow structure with a sub-second time resolution. The findings of this study demonstrate how to obtain quantitative measurements of debris-flow movement. In addition, the data help us to quantitatively define the development of a saltating debris-flow front and roll waves behind the debris-flow front. Such measurements may help constrain future modeling efforts.

Environmental and Engineering Geoscience↗

USGS2020

Measuring basal force fluctuations of debris flows using seismic recordings and empirical green's functions

We present a novel method for measuring the fluctuating basal normal and shear stresses of debris flows by using along‐channel seismic recordings. Our method couples a simple parameterization of a debris flow as a seismic source with direct measurements of seismic path effects using empirical Green's functions generated with a force hammer. We test this method using two large‐scale (8 and 10 m 3 ) experimental flows at the U.S. Geological Survey debris‐flow flume that were recorded by dozens of three‐component seismic sensors. The seismically derived basal stress fluctuations compare well in amplitude and timing to independent force plate measurements within the valid frequency range (15–50 Hz). We show that although the high‐frequency seismic signals provide band‐limited forcing information, there are systematic relations between the fluctuating stresses and independently measured flow properties, especially mean basal shear stress and flow thickness. However, none of the relationships are simple, and since the flow properties also correlate with one another, we cannot isolate a single factor that relates in a simple way to the fluctuating forces. Nevertheless, our observations, most notably the gradually declining ratio of fluctuating to mean basal stresses during flow passage and the distinctive behavior of the coarse, unsaturated flow front, imply that flow style may be a primary control on the conversion of translational to vibrational kinetic energy. This conversion ultimately controls the radiation of high‐frequency seismic waves. Thus, flow style may provide the key to revealing the nature of the relationship between fluctuating forces and other flow properties.

Journal of Geophysical Research Earth Surface↗

USGS2020

Reconstructing the velocity and deformation of a rapid landslide using multiview video

Noncontact measurements of spatially varied ground surface deformation during landslide motion can provide important constraints on landslide mechanics. Here, we present and test a new method for extracting measurements of rapid landslide surface displacement and velocity (accelerations of approximately 1 m/s 2 ) using sequences of stereo images obtained from a pair of inexpensive, stationary 4K video cameras with nominal frame rates of 29.97 Hz. The method combines elements of Structure from Motion with those of optical flow to extract data on 3‐D evolution of the ground surface during slope failure. We apply the method to an experiment at the U.S. Geological Survey debris‐flow flume in which a high‐speed, liquefying landslide was triggered by gradually adding water to a 6‐m 3 prism of loosely packed sediment on a 31° slope. Strip‐scanning lidar measurements made during the experiment corroborate our video‐based measurements, but the latter encompassed the entire landslide surface and were much lower in cost. Our video‐based measurements enabled computation of depth‐integrated landslide dilation/contraction rates. The range of computed rates was within the ranges inferred from independent measurements of evolving pore water pressures and reasonable estimates of the hydraulic permeability of the sediment. Dilation and contraction rates play a crucial role in landslide mechanics. The dilation and contraction we observe contradict the incompressible flow assumption used in many studies that have employed noncontact methods to infer landslide properties.

Oregon↗

USGS2020

Ground failure triggered by shaking during the November 30, 2018, magnitude 7.1 Anchorage, Alaska, earthquake

We developed an initial inventory of ground failure features from the November 30, 2018, magnitude 7.1 Anchorage earthquake. This inventory of 153 features is from ground-based observations soon after the earthquake (December 5–10) that include the presence or absence of liquefaction, landslides, and individual crack traces of lateral spreads and incipient landslides. This is not a complete inventory and simply shows general trends and examples of types and distribution of ground failures documented. Overflight observations (December 1–6) documented landslide and liquefaction presence or absence within the Chugach Mountains and along Cook Inlet in regions inaccessible to vehicles, which greatly expanded the geographic scope of this reconnaissance. Field-mapped ground-failure observations have been augmented with a set of 565 georeferenced and annotated images from both field and overflight reconnaissance cataloging additional ground-failure presence or absence from the Anchorage earthquake. Tidal erosion, fresh snowfall, limited daylight, and adverse flying conditions contributed significantly to the uncertainty and incompleteness of ground-failure observations during this reconnaissance. Notably, substantial liquefaction features at the mouths of the Little Susitna River (December 1) and Ingram Creek (December 5) were absent during subsequent overlapping missions (December 6 and 9, respectively) because of tidal action. A large rockfall observed on December 1 on Rainbow Peak was not observed during a subsequent December 5 overflight because of snow cover, which suggests that the general lack of observations of landsliding within the Chugach Mountains is uncertain.

Alaska↗

USGS2020

Observations on the May 2019 Joffre Peak landslides, British Columbia

Two catastrophic landslides occurred in quick succession on 13 and 16 May 2019, from the north face of Joffre Peak, Cerise Creek, southern Coast Mountains, British Columbia. With headscarps at 2560 m and 2690 m elevation, both began as rock avalanches, rapidly transforming into debris flows along middle Cerise Creek, and finally into debris floods affecting the fan. Beyond the fan margin, a flood surge on Cayoosh Creek reached bankfull and attenuated rapidly downstream; only fine sediment reached Duffey Lake. The toe of the main debris flow deposit reached 4 km from the headscarp, with a travel angle of 0.28; while the debris flood phase reached the fan margin 5.9 km downstream, with a travel angle of 0.22. Photogrammetry indicates the source volume of each event is 2-3 Mm3, with combined volume of 5 Mm3. Lidar differencing, used to assess deposit volume, yielded a similar total result; although error in the depth estimate introduced large error and masks expected increase due to dilation and entrainment. The average velocity of the rock avalanche-debris flow phases, from seismic analysis, was ~25-30 m/s, and the velocity of the 16 May debris flood on the upper fan, from super-elevation and boulder sizes, was 5-10 m/s. The volume of debris deposited on the fan was ~104 m3, 2-orders of magnitude less than the avalanche/debris flow phases. The 13 May landslide was apparently triggered by rapid snowmelt; with debuttressing triggering the 16 May event. While spring 2019 was warm, it wasn’t unusual. It is likely that progressive glacier retreat and permafrost degradation were the conditioning factors; precursor activity was noted at least 1 yr previous; thus, the mountain was primed to fail and average seasonal snowmelt tipped the balance.

British Columbia↗

USGS2020

An update of USGS bear-real-time earthquake shaking and impact products

We report on advancements in both hazard and consequence modeling that form the core of the U.S. Geological Survey’s (USGS) strategy to improve rapid earthquake shaking and loss estimates. Whereas our primary goal is to improve our operational capabilities of the USGS National Earthquake Information Center, the science, software, and datasets behind these systems continue to advance uses and studies of earthquake shaking and impact by the seismological, engineering, financial, and risk modeling communities. Several important updates to our integrated shaking and impact products are outlined and we introduce new earthquake information products that have recently been brought online, including rapid ground failure estimates and more spatially refined loss estimates domestically (in the U.S). We continue to compile, develop, and refine key openly available models and datasets that contribute to calibrating these systems and report on the collection and storage of new inventories. We also describe some of the basic operational considerations in the current generation of these shaking and loss-estimation systems. A key aspect of the product integration and development is leveraging earthquake-hazard and loss-modeling science done internally (within the USGS) and by external researchers and collaborators. Lastly, we outline new opportunities for further research and development by emphasizing scientific, data, and application gaps and challenges that must be solved in order to improve our shaking and impact information tools.

Conference Paper↗

USGS2019

USGS near-real-time products-and their use-for the 2018 Anchorage earthquake

In the minutes to hours after a major earthquake, such as the recent 2018 M w "> M w 7.1 Anchorage event, the U.S. Geological Survey (USGS) produces a suite of interconnected earthquake products that provides diverse information ranging from basic earthquake source parameters to loss estimates. The 2018 Anchorage earthquake is the first major domestic earthquake to occur since several new USGS products have been developed, thus providing an opportunity to discuss the newly expanded USGS earthquake product suite, its timeliness, performance, and reception. Overall, the products were relatively timely, accurate, well received, and widely used, including by the media, who used information and visualizations from many products to frame their early reporting. One downside of the codependence of multiple products is that reasonable updates to upstream products (e.g., magnitude and source characterization) can result in significant changes to downstream products; this was the case for the Anchorage earthquake. However, the coverage of strong‐motion stations and felt reports was so dense that the ShakeMap and downstream products were relatively insensitive to changes in magnitude or fault‐plane orientation once the ground‐motion data were available. Shaking and loss indicators initially fluctuated in the first hour or two after the earthquake, but they stabilized quickly. To understand how the products are being used and how effectively they are being communicated, we analyze the media coverage of USGS earthquake products. Most references to USGS products occurred within the first 48 hr after the event. The lack of coverage after 48 hr could indicate that longer‐term products addressing what actions the USGS is taking or what early reconnaissance has revealed might be useful for those people wanting additional information about the earthquake.

Alaska↗

USGS2019

Ground failure from the Anchorage, Alaska, earthquake of 30 November 2018

Investigation of ground failure triggered by the 2018 M w "> M w Mw 7.1 Anchorage earthquake showed that landslides, liquefaction, and ground cracking all occurred and caused significant damage. Shallow rock falls and rock slides were the most abundant types of landslides, but they occurred in smaller numbers than global models that are based on earthquake magnitude predict; this might result from the 2018 earthquake being an intraslab event. Liquefaction was common in alluvial and intertidal areas; ground deformation probably related to liquefaction damaged numerous houses and port facilities in Anchorage. Ground cracking was pervasive near the edges of slopes in hilly areas and caused perhaps the most significant property damage of all types of ground failure. A complex of slump–earth flows was triggered along coastal bluffs in southern Anchorage where slides also occurred in 1964; the 2018 slides involved both mobilization of new landside material and reactivation of parts of the 1964 landslide deposits. Large translational slides that formed during the 1964 Alaska earthquake showed evidence of deformation along pre‐existing failure surfaces but did not reactivate with new net downslope displacement. Modeling suggests that ground motion in 2018 was of insufficient duration and too high frequency to trigger reactivation of the deep landslides.

Alaska↗