Geology topics

Kate E. Allstadt

Publications and source records attributed to Kate E. Allstadt.

At least 55 records · Page 3Linked to original sources

USGS2019

A physical model of the high-frequency seismic signal generated by debris flows

We propose a physical model for the high‐frequency (>1 Hz) spectral distribution of seismic power generated by debris flows. The modeled debris flow is assumed to have four regions where the impact rate and impulses are controlled by different mechanisms: the flow body, a coarser‐grained snout, a snout lip where particles fall from the snout on the bed, and a dilute front composed of saltating particles. We calculate the seismic power produced by this impact model in two end‐member scenarios, a thin‐flow and thick‐flow limit, which assume that the ratio of grain sizes to flow thicknesses are either near unity or much less than unity. The thin‐flow limit is more appropriate for boulder‐rich flows that are most likely to generate large seismic signals. As a flow passes a seismic station, the rise phase of the seismic amplitude is generated primarily by the snout while the decay phase is generated first by the snout and then the main flow body. The lip and saltating front generate a negligible seismic signal. When ground properties are known, seismic power depends most strongly on both particle diameter and average flow speed cubed, and also depends on length and width of the flow. The effective particle diameter for producing seismic power is substantially higher than the median grain size and close to the 73rd percentile for a realistic grain size distribution. We discuss how the model can be used to estimate effective particle diameter and average flow speed from an integrated measure of seismic power.

Earth Surface Processes and Landforms↗

USGS2019

Earthquake-induced chains of geologic hazards: Patterns, mechanisms, and impacts

Large earthquakes initiate chains of surface processes that last much longer than the brief moments of strong shaking. Most moderate- and large-magnitude earthquakes trigger landslides, ranging from small failures in the soil cover to massive, devastating rock avalanches. Some landslides dam rivers and impound lakes, which can collapse days to centuries later, and flood mountain valleys for hundreds of kilometers downstream. Landslide deposits on slopes can remobilize during heavy rainfall and evolve into debris flows. Cracks and fractures can form and widen on mountain crests and flanks, promoting increased frequency of landslides that lasts for decades. More gradual impacts involve the flushing of excess debris downstream by rivers, which can generate bank erosion and floodplain accretion as well as channel avulsions that affect flooding frequency, settlements, ecosystems, and infrastructure. Ultimately, earthquake sequences and their geomorphic consequences alter mountain landscapes over both human and geologic time scales. Two recent events have attracted intense research into earthquake-induced landslides and their consequences: the magnitude M 7.6 Chi-Chi, Taiwan earthquake of 1999, and the M 7.9 Wenchuan, China earthquake of 2008. Using data and insights from these and several other earthquakes, we analyze how such events initiate processes that change mountain landscapes, highlight research gaps, and suggest pathways toward a more complete understanding of the seismic effects on the Earth’s surface.

Reviews of Geophysics↗

USGS2019

Inundation, flow dynamics, and damage in the 9 January 2018 Montecito Debris-Flow Event, California, USA: Opportunities and challenges for post-wildfire risk assessment

Shortly before the beginning of the winter rainy season, one of the largest fires in California history (Thomas Fire) substantially increased the susceptibility of steep slopes in Santa Barbara and Ventura Counties to debris flows. On January 9, 2018, before the fire was fully contained, an intense burst of rain fell on the portion of the burn area above Montecito, CA. The rainfall and associated runoff triggered a series of debris flows that mobilized approximately 680,000 m3 of sediment (including boulders >4 m) at velocities up to 4 m/s down urbanized alluvial fans. The resulting destruction (including 23 fatalities, at least 167 injuries, and 408 damaged homes) underscores the need for improved understanding of debris-flow runout in the built environment, and the need for a comprehensive framework to assess the potential loss from debris flows following wildfire. We present observations of the inundation, debris-flow dynamics, and damage from the event. The data include field measurements of flow depth and deposit characteristics made 12 days after the event (before ephemeral features of the deposits were lost to recovery operations); an inventory of building damage; estimates of flow velocity; information on flow timing; soil-hydrologic properties; and post-event imagery and lidar. Together, these data provide rare spatial and dynamic constraints for testing debris-flow runout models, which are needed for advancing post-fire debris-flow hazard assessments. Our analysis also outlines a framework for translating the results of these models into estimates of economic loss based on an adaptation of the Federal Emergency Management Agency’s Hazus model for tsunamis.

California↗

USGS2019

Exotic Seismic Events Catalog (ESEC) Data Product

Nonearthquake seismic events from sources such as landslides, debris flows, dam collapses, floods, glaciers, and avalanches are rarely included in traditional earthquake catalogs. The new Incorporated Research Institutions for Seismology (IRIS) Data Management Center Exotic Seismic Events Catalog data product provides information on such events to help accelerate research in the area of environmental seismology. This catalog initially offers information on 113 events in four general categories consisting of flows, lahars, debris flows and outburst floods (17 events); rock or debris falls (23 events); rock, ice, or debris avalanches and slides (68 events); and snow avalanches (5 events). This database will be expanded as information regarding new recent and historical events becomes available. This catalog is now available to the research community at IRIS (see Data and Resources ).

Seismological Research Letters↗

USGS2019

Seismic and acoustic signatures of surficial mass movements at volcanoes

Surficial mass movements, such as debris avalanches, rock falls, lahars, pyroclastic flows, and outburst floods, are a dominant hazard at many volcanoes worldwide. Understanding these processes, cataloging their spatio-temporal occurrence, and detecting, tracking, and characterizing these events would advance the science of volcano monitoring and help mitigate hazards. Seismic and acoustic methods show promise for achieving these objectives: many surficial mass movements generate observable seismic and acoustic signals, and many volcanoes are already monitored. Significant progress has been made toward understanding, modeling, and extracting quantitative information from seismic and infrasonic signals generated by surficial mass movements. However, much work remains. In this paper, we review the state of the art of the topic, covering a range of scales and event types from individual rock falls to sector collapses. We consider a full variety of volcanic settings, from submarine to subaerial, shield volcano to stratovolcano. Finally, we discuss future directions toward operational seismo-acoustic monitoring of surficial mass movements at volcanoes.

Journal of Volcanology and Geothermal Research↗

USGS2019

Real-time monitoring of debris-flow velocity and mass deformation from field experiments with high sample rate lidar and video

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. This process is readily observed, but difficult to study or quantify because of the speed at which it occurs. Many methods for studying debris flows consist of point measurements (e.g., of flow height or basal stresses), which are inherently limited in spatial coverage and fail to fully capture the spatiotemporal evolution of a flow. In this study, we use a terrestrial lidar to measure debris-flow profiles at high sample rates to examine debris-flow movement with high temporal and spatial precision and accuracy. We acquired measurements during gate-release experiments at the USGS debris flume, a unique experimental facility where debris flows can be simulated at a large scale. In this study, the laser scanner was placed at the bottom of the steep flume and recorded topography of the entire flume bed and debris flow at a rate of 60 Hz along a very narrow profile (~1mm in width), providing a detailed, two-dimensional cross-section of the debris flow through time. The high-resolution profiles enable us to quantify flow front and surge velocities of the debris flow and provide an unprecedented record of the development and evolution of the flow structure over time. The profiles also preserve a record of the highly variable deposition pattern of the debris flow on a downstream fan with a time resolution of hundredths of a second. In addition, video imagery from the experiment was used to track debris flow movement through time. By acquiring high-resolution topographic data and video imagery during a controlled experiment, we have been able to obtain unusually complete quantitative measurements of debris-flow movement. Such measurements may help constrain future modeling efforts.

Conference Paper↗

USGS2019

Overcoming barriers to progress in seismic monitoring and characterization of debris flows and lahars

Debris flows generate seismic signals that contain valuable information about events as they unfold. Though seismic waves have been used for along-channel debris-flow and lahar monitoring systems for decades, it has proven difficult to move beyond detection to more quantitative characterizations of flow parameters and event size. This is for two primary reasons: (1) our limited understanding of how the radiated wavefield relates to debris flow characteristics and dynamics, and (2) difficulties quantifying the effects of heterogeneous shallow earth structure on the observed wavefield. The latter issue, essentially our inability to sufficiently separate seismic path effects from source information, is a barrier to improving our understanding of the first issue. We review the progress that has been made toward establishing the theory, models and methods required to use seismic observations to make quantitative measurements of flows and summarize the practical, social, and scientific barriers to progress. We discuss some specific ongoing efforts to overcome some of these barriers, with a focus on how we are using large-scale seismic experiments at the U.S. Geological Survey debris-flow flume to develop methods for directly measuring path effects and to develop and validate theoretical debris flow seismicity models.

Conference Paper↗

USGS2019

Taking the pulse of debris flows: Extracting debris-flow dynamics from good vibrations in southern California and central Colorado

The destructive nature of debris flows makes it difficult to quantify flow dynamics with direct instrumentation. For this reason, seismic sensors placed safely away from the flow path are often used to identify the timing and speed of debris flows. While seismic sensors have proven to be a valuable tool for event detection and early warning, their potential for identifying other aspects of debris flows (such as sediment concentration) is less studied. Here we use two monitoring sites to investigate the extent to which debris-flow dynamics can be decoded from ground vibrations. One site is a bedrock channel in a steep semiarid basin in central Colorado (Chalk Cliffs), and the other is in a debris-flow channel incised in alluvium in a recently burned area in southern California (Van Tassel). At both sites, seismic data are measured with geophones (4.5 Hz) mounted next to the channels and sampled at high frequencies (500-1000 Hz). Independent constraints on flow dynamics are provided by laser distance meters to record flow stage (at 10 Hz) and high-definition video cameras to record flow velocity and sediment concentration. The observed debris flows at Chalk Cliffs typically consist of a series of short-duration (~30 second) surges with total durations of <40 minutes and have coarse-grained fronts and fluid-rich tails. In contrast, the events at Van Tassel are longer duration flows (>40 minutes) that begin as debris flows and transform into more steady debris floods. The arrangement of sensors at both sites allow us to identify correlations between vertical ground velocity, frequency, flow stage, and qualitative estimates of sediment concentration.

California, Colorado↗

USGS2018

Factors controlling landslide frequency-area distributions

A power‐law relation for the frequency–area distribution (FAD) of medium and large landslides (e.g. tens to millions of square meters) has been observed by numerous authors. But the FAD of small landslides diverges from the power‐law distribution, with a rollover point below which frequencies decrease for smaller landslides. Some studies conclude that this divergence is an artifact of unmapped small landslides due to lack of spatial or temporal resolution; others posit that it is caused by the change in the underlying failure process. An explanation for this dilemma is essential both to evaluate the factors controlling FADs of landslides and power‐law scaling, which is a crucial factor regarding both landscape evolution and landslide hazard assessment. This study examines the FADs of 45 earthquake‐induced landslide inventories from around the world in the context of the proposed explanations. We show that each inventory probably involves some combination of the proposed explanations, though not all explanations contribute to each case. We propose an alternative explanation to understand the reason for the divergence from a power‐law. We suggest that the geometry of a landslide at the time of mapping reflects not just one single movement but many, including the propagation of numerous smaller landslides before and after the main failure. Because only the resulting combination of these landslides can be observed due to a lack of temporal resolution, many smaller landslides are not taken into account in the inventory. This reveals that the divergence from the power‐law is not necessarily attributed to the incompleteness of an inventory. This conceptual model will need to be validated by ongoing observation and analysis. Also, we show that because of the subjectivity of mapping procedures, the total number of landslides and total landslide areas in inventories differ significantly, and therefore the shapes of FADs also differ considerably.

Earth Surface Processes and Landforms↗

USGS2018

Community for Data Integration fiscal year 2017 funded project report

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 11 projects funded in fiscal year 2017, outlining their goals, activities, and outputs.

Open-File Report↗

USGS2018

A global empirical model for near real-time assessment of seismically induced landslides

Earthquake-triggered landslides are a significant hazard in seismically active regions, but our ability to assess the hazard they pose in near real-time is limited. In this study, we present a new globally applicable model for seismically induced landslides based on the most comprehensive global dataset available; we use 23 landslide inventories that span a range of earthquake magnitudes and climatic and tectonic settings. We use logistic regression to relate the presence and distribution of earthquake-triggered landslides with spatially distributed estimates of ground shaking, topographic slope, lithology, land-cover type, and a topographic index designed to estimate variability in soil wetness to provide an empirical model of landslide distribution. We tested over 100 combinations of independent predictor variables to find the best-fitting model, using a diverse set of statistical tests. Blind validation tests show the model accurately estimates the distribution of available landslide inventories. The results indicate that the model is reliable and stable, with high “balanced accuracy” (correctly vs. incorrectly classified pixels) for the majority of test events. A cross validation analysis shows high balanced accuracy for a majority of events as well. By combining near-real time estimates of ground shaking with globally available landslide susceptibility data, this model provides a tool to estimate the distribution of co-seismic landslide hazard within minutes of the occurrence of any earthquake worldwide for which a USGS ShakeMap is available.

Journal of Geophysical Research: Earth Surface↗

USGS2018

Overview of the geologic effects of the November 14, 2016, Mw 7.8 Kaikoura, New Zealand, earthquake

The November 14, 2016, Kaikoura, New Zealand, earthquake (moment magnitude [Mw] 7.8) triggered more than 10,000 landslides over an area of about 12,000 square kilometers in the northeastern part of the South Island of New Zealand. In collaboration with GNS Science (the Institute of Geological and Nuclear Science Limited), we conducted ground and helicopter reconnaissance of the affected areas and assisted in rapid hazard evaluation. The majority of the triggered landslides were shallow- to moderate-depth (1–10 meters), highly disrupted falls and slides in rock and debris from Lower Cretaceous graywacke sandstone in the Seaward Kaikoura Range. Deeper, more coherent landslides in weak Upper Cretaceous to Neogene sedimentary rock also were numerous in the gentler topography south and inland (west) of the Seaward Kaikoura Range. The principal ground-failure hazards from the earthquake were the hundreds of valley-blocking landslides, many of which impounded lakes and ponds that posed potential downstream flooding hazards. Both large and small landslides also blocked road and rail corridors in many locations, including the main north-south highway (State Highway 1), which was still closed in October 2017. As part of our investigation, we compared post-earthquake field observations to the output of models used to estimate near-real-time landslide probabilities following earthquakes. The models generally over-predicted landslide occurrence and thus need further refinement.

Kaikoura↗

USGS2018

Improving near‐real‐time coseismic landslide models: Lessons learned from the 2016 Kaikōura, New Zealand, earthquake

The U.S. Geological Survey (USGS) is developing near‐real‐time global earthquake‐triggered‐landslide products to augment the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system. The 14 November 2016 M w "> M w Mw 7.8 Kaikōura, New Zealand, earthquake provided a test case for evaluating the performance and near‐real‐time response applicability of three published global seismically induced landslide models. All three models obtain shaking estimates from the USGS ShakeMap, which is updated and sometimes changes significantly in the hours to days after an earthquake. The Kaikōura earthquake is a particularly valuable event that helps us better understand how changes to the ShakeMap affect the landslide models because the ShakeMap evolved significantly over several weeks as multifault rupture and seismic data were incorporated. We used the detailed landslide inventory available for this event for qualitative landslide model evaluation. We found that once a point source was replaced with an approximate rupture extent in ShakeMap, the landslide models were all successful at roughly identifying the area of highest hazard. This is notable, given that the models are relatively simple, coarse in resolution, and are based solely on input proxies that are globally available. However, all of the models dramatically overpredicted the hazard level, which indicates that improvements can be made. Subsequent updates to the ShakeMap resulted in improvements to model performance by some metrics and declining performance by others. In all cases, details of the ShakeMap strongly controlled the spatial pattern, even when those details were erroneous, such as the inclusion of a fault segment that did not rupture. If maps of landslide hazard are to be used effectively for rapid response, then we need to understand and clearly communicate the control that ShakeMap has over the models and how that typically evolves with time and is (or is not) reflected in reported uncertainties.

Bulletin of the Seismological Society of America↗

USGS2018

Landslides triggered by the 14 November 2016 Mw 7.8 Kaikōura Earthquake, New Zealand

The 14 November 2016 M w "> M w Mw 7.8 Kaikōura earthquake generated more than 10,000 landslides over a total area of about 10 , 000    km 2 "> 10 , 000 km 2 10,000 km2 , with the majority concentrated in a smaller area of about 3600    km 2 "> 3600 km 2 3600 km2 . The largest landslide triggered by the earthquake had an approximate volume of 20 ( ± 2 )    M   m 3 "> 20 ( ± 2 ) M m 3 20(±2) M m3 , with a runout distance of about 2.7 km, forming a dam on the Hapuku River. In this article, we present version 1.0 of the landslide inventory we have created for this event. We use the inventory presented in this article to identify and discuss some of the controls on the spatial distribution of landslides triggered by the Kaikōura earthquake. Our main findings are (1) the number of medium to large landslides (source area ≥ 10 , 000    m 2 "> ≥ 10 , 000 m 2 ≥10,000 m2 ) triggered by the Kaikōura earthquake is smaller than for similar‐sized landslides triggered by similar magnitude earthquakes in New Zealand; (2) seven of the largest eight landslides (from 5 to 20    M   m 3 "> 20 M m 3 20 M m3 ) occurred on faults that ruptured to the surface during the earthquake; (3) the average landslide density within 200 m of a mapped surface fault rupture is three times that at a distance of 2500 m or more from a mapped surface fault rupture; (4) the “distance to fault” predictor variable, when used as a proxy for ground‐motion intensity, and when combined with slope angle, geology, and elevation variables, has more power in predicting landslide probability than the modeled peak ground acceleration or peak ground velocity; and (5) for the same slope angles, the coastal slopes have landslide point densities that are an order of magnitude greater than those in similar materials on the inland slopes, but their source areas are significantly smaller.

Bulletin of the Seismological Society of America↗

USGS2018

An updated method for estimating landslide‐event magnitude

Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude ( mLS ), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories ( n =45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating mLS and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing mLS for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods.

Earth Surface Processes and Landforms↗

USGS2017

An open repository of earthquake-triggered ground-failure inventories

Earthquake-triggered ground failure, such as landsliding and liquefaction, can contribute significantly to losses, but our current ability to accurately include them in earthquake-hazard analyses is limited. The development of robust and widely applicable models requires access to numerous inventories of ground failures triggered by earthquakes that span a broad range of terrains, shaking characteristics, and climates. We present an openly accessible, centralized earthquake-triggered groundfailure inventory repository in the form of a ScienceBase Community to provide open access to these data with the goal of accelerating research progress. The ScienceBase Community hosts digital inventories created by both U.S. Geological Survey (USGS) and non-USGS authors. We present the original digital inventory files (when available) as well as an integrated database with uniform attributes. We also summarize the mapping methodology and level of completeness as reported by the original author(s) for each inventory. This document describes the steps taken to collect, process, and compile the inventories and the process for adding additional ground-failure inventories to the ScienceBase Community in the future.

Data Series↗

USGS2017

Presentation and analysis of a worldwide database of earthquake-induced landslide inventories

Earthquake-induced landslide (EQIL) inventories are essential tools to extend our knowledge of the relationship between earthquakes and the landslides they can trigger. Regrettably, such inventories are difficult to generate and therefore scarce, and the available ones differ in terms of their quality and level of completeness. Moreover, access to existing EQIL inventories is currently difficult because there is no centralized database. To address these issues, we compiled EQIL inventories from around the globe based on an extensive literature study. The database contains information on 363 landslide-triggering earthquakes and includes 66 digital landslide inventories. To make these data openly available, we created a repository to host the digital inventories that we have permission to redistribute through the U.S. Geological Survey ScienceBase platform. It can grow over time as more authors contribute their inventories. We analyze the distribution of EQIL events by time period and location, more specifically breaking down the distribution by continent, country, and mountain region. Additionally, we analyze frequency distributions of EQIL characteristics, such as the approximate area affected by landslides, total number of landslides, maximum distance from fault rupture zone, and distance from epicenter when the fault plane location is unknown. For the available digital EQIL inventories, we examine the underlying characteristics of landslide size, topographic slope, roughness, local relief, distance to streams, peak ground acceleration, peak ground velocity, and Modified Mercalli Intensity. Also, we present an evaluation system to help users assess the suitability of the available inventories for different types of EQIL studies and model development.

Journal of Geophysical Research F: Earth Surface↗

USGS2017

Shallow repeating seismic events under an alpine glacier at Mount Rainier, Washington, USA

We observed several swarms of repeating low-frequency (1–5 Hz) seismic events during a 3 week period in May–June 2010, near the summit of Mount Rainier, Washington, USA, that likely were a result of stick–slip motion at the base of alpine glaciers. The dominant set of repeating events ('multiplets') featured >4000 individual events and did not exhibit daytime variations in recurrence interval or amplitude. Volcanoes and glaciers around the world are known to produce seismic signals with great variability in both frequency content and size. The low-frequency character and periodic recurrence of the Mount Rainier multiplets mimic long-period seismicity often seen at volcanoes, particularly during periods of unrest. However, their near-surface location, lack of common spectral peaks across the recording network, rapid attenuation of amplitudes with distance, and temporal correlation with weather systems all indicate that ice-related source mechanisms are the most likely explanation. We interpret the low-frequency character of these multiplets to be the result of trapping of seismic energy under glacial ice as it propagates through the highly heterogeneous and attenuating volcanic material. The Mount Rainier multiplet sequences underscore the difficulties in differentiating low-frequency signals due to glacial processes from those caused by volcanic processes on glacier-clad volcanoes.

Washington↗