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At least 235 records · Page 13Linked to original sources
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↗
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↗
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

Asynchronous landslide seasonality across the United States

Mid-range landslide outlooks can facilitate weather-related landslide preparedness and disaster response planning, but seasonal landslide activity remains poorly quantified at continental scales. Leveraging >55,000 reported landslides from across the United States (U.S.), we used circular statistics to quantify landslide seasonality in 67 National Weather Service County Warning Areas (CWAs). We found regional differences in landslide season timing and duration, with transitions between domains variably corresponding to climate class or river basin. We assessed differences in seasonality by movement type for slides, flows, and falls, detecting apparent, but uncertain, differences between slide and fall seasonalities in 27 of 35 (77%) of CWAs with both types reported. In the Pacific Northwest, where long records exist, we found a credible shift toward a later mean landslide season in western Washington from 1990 to 2020, but no trend in western Oregon. Our results can provide emergency planners a resource to assess seasonal landslide probability nationwide.

Geophysical Research Letters↗
USGS2020

Rainfall triggers more deep-seated landslides than Cascadia earthquakes in the Oregon Coast Range, USA

The coastal Pacific Northwest USA hosts thousands of deep-seated landslides. Historic landslides have primarily been triggered by rainfall, but the region is also prone to large earthquakes on the 1100-km-long Cascadia Subduction Zone megathrust. Little is known about the number of landslides triggered by these earthquakes because the last magnitude 9 rupture occurred in 1700 CE. Here, we map 9938 deep-seated bedrock landslides in the Oregon Coast Range and use surface roughness dating to estimate that past earthquakes triggered fewer than half of the landslides in the past 1000 years. We find landslide frequency increases with mean annual precipitation but not with modeled peak ground acceleration or proximity to the megathrust. Our results agree with findings about other recent subduction zone earthquakes where relatively few deep-seated landslides were mapped and suggest that despite proximity to the megathrust, most deep-seated landslides in the Oregon Coast Range were triggered by rainfall.

Oregon↗
USGS2008

A prototype system for forecasting landslides in the Seattle, Washington, area

Empirical rainfall thresholds and related information form the basis of a prototype system for forecasting landslides in the Seattle area. The forecasts are tied to four alert levels, and a decision tree guides the use of thresholds to determine the appropriate level. From analysis of historical landslide data, we developed a formula for a cumulative rainfall threshold (CT), P 3 = 88.9 − 0.67 P 15 , defined by rainfall amounts in millimeters during consecutive 3 d (72 h) periods, P 3 , and the 15 d (360 h) period before P 3 , P 15 . The variable CT captures more than 90% of historical events of three or more landslides in 1 d and 3 d periods recorded from 1978 to 2003. However, the low probability of landslide occurrence on a day when the CT is exceeded at one or more rain gauges (8.4%) justifies a low-level of alert for possible landslide occurrence, but it does trigger more vigilant monitoring of rainfall and soil wetness. Exceedance of a rainfall intensity-duration threshold I = 82.73 D −1.13 , for intensity, I (mm/hr), and duration, D (hr), corresponds to a higher probability of landslide occurrence (30%) and forms the basis for issuing warnings of impending, widespread occurrence of landslides. Information about the area of exceedance and soil wetness can be used to increase the certainty of landslide forecasts (probabilities as great as 71%). Automated analysis of real-time rainfall and subsurface water data and digital quantitative precipitation forecasts are needed to fully implement a warning system based on the two thresholds.

Washington↗
USGS2019

Landslides triggered by Hurricane Maria: Assessment of an extreme event in Puerto Rico

Hurricane Maria hit the island of Puerto Rico on 20 September 2017 and triggered more than 40,000 landslides in at least three-fourths of Puerto Rico’s 78 municipalities. The number of landslides that occurred during this event was two orders of magnitude greater than those reported from previous hurricanes. Landslide source areas were commonly limited to surficial soils but also extended into underlying saprolite and bedrock. Slope failures occurred before, during, and after flooding, and many transitioned into long runout debris flows. Steep slopes in hilly and mountainous regions were particularly impacted by landslides due to antecedent soil moisture levels that were 11%–13% higher than average and rainfall totals of at least 250 mm within a 48 h period. High landslide densities were especially widespread across some geologic formations (e.g., granodiorite of the Utuado batholith); however, bedrock geology alone did not determine the location and distribution of landslides caused by Hurricane Maria. While rainfall data collected during Hurricane Maria were inconsistent, satellite-based soil moisture data were correlated with the distribution of landslides. In the future, the use of soil moisture data could enable assessments of regional landslide susceptibility prior to hurricanes or extreme precipitation events.

GSA Today↗
USGS2025

Insights into widespread landsliding in southern Appalachia from Hurricane Helene

Between 23 and 27 September 2024, antecedent rain followed by Hurricane Helene produced one of the most damaging weather events in southern Appalachia history. The back-to-back storm events resulted in a maximum cumulative rainfall of 848 mm and hurricane-force wind gusts over 170 km/h in western North Carolina, eastern Tennessee, and southwestern Virginia. The resulting regional flooding, landslides, and tree blowdown caused over 100 fatalities, damaged or destroyed critical infrastructure and thousands of structures, and severed connectivity across the region. Over the next several weeks, a multi-agency landslide response produced a rapid hazard assessment and mapped 2217 landslides, 55% of which damaged infrastructure or property. Orographic uplift enhanced rainfall, resulting in concentrated landsliding along the ~250 km swath of the Blue Ridge escarpment in western North Carolina. Landslides initiated predominantly on windward-facing (southeast-facing) slopes, and localized clustering of initiation points indicated a strong influence of hillslope-scale meteorological and geomorphic factors. Many shallow landslides mobilized into larger, highly mobile, and damaging debris flows that graded into floods. Here, we put our preliminary observations in the context of historical storm-driven landslide events and open new avenues for investigating the nature and extent of landslides and their effects in southern Appalachia and similar environments.

Georgia, North Carolina, South Carolina, Tennessee↗
USGS2003

Shallow landsliding, root reinforcement, and the spatial distribution of trees in the Oregon Coast Range

The influence of root reinforcement on shallow landsliding has been well established through mechanistic and empirical studies, yet few studies have examined how local vegetative patterns influence slope stability. Because root networks spread outward from trees, the species, size, and spacing of trees should influence the spatial distribution of root strength. We documented the distribution and characteristics of trees adjacent to 32 shallow landslides that occurred during 1996 in the Oregon Coast Range. Although broadly classified as a conifer-dominated forest, we observed sparse coniferous and abundant hardwood trees near landslide scars in an industrial forest (Mapleton) that experienced widespread burning in the 19th century. In industrial forests that were burned, selectively harvested, and not replanted (Elliott State Forest), swordfern was ubiquitous near landslides, and we observed similar numbers of live conifer and hardwood trees proximal to landslide scarps. We demonstrate that root strength quantified in landslide scarps and soil pits correlates with a geometry-based index of root network contribution derived from mapping the size, species, condition, and spacing of local trees, indicating that root strength can be predicted by mapping the distribution and characteristics of trees on potentially unstable slopes. In our study sites, landslides tend to occur in areas of reduced root strength, suggesting that to make site-specific predictions of landslide occurrence slope stability analyses must account for the diversity and distribution of vegetation in potentially unstable terrain.

Oregon↗
USGS2026

Landslide volume estimation from seismic waveform features using a global catalog of seismogenic events

Seismic waves generated by large, rapid landslides encode information about the source and can be analyzed rapidly following an event. Even remote landslides can pose hazards to downstream communities, so rapid detection and characterization using existing seismic monitoring networks could be beneficial. In this study, we expand on past regionally limited work by presenting a globally applicable method for estimating landslide volume from seismic features that could be integrated into future landslide seismic monitoring frameworks. We train the model using multivariable linear regression and five seismic features derived from recordings of 129 landslide events of a range of styles and locations with independently estimated volumes. We present two preferred models, one that combines long‐period (LP) and high‐frequency (HF) features and one for use on smaller landslides without observed long‐period signals. We find that our best‐performing model, applicable to landslides larger than 100,000 m 3 with signals containing observable long‐period energy, requires only two features: LP (20–100 s) absolute maximum amplitude and HF (1–5 Hz) rise time (time between the signal start and the maximum envelope amplitude) and has an R 2 score of 0.79. This model predicted volumes within one order of magnitude for 55 out of 58 events. We find that this combination mitigates the trade‐off between mass and acceleration and other variations of landslide style that limit methods based on amplitude alone.

Seismological Research Letters↗
USGS2000

Map showing recent and historic landslide activity on coastal bluffs of Puget Sound between Shilshole Bay and Everett, Washington

Many landslides occurred on the coastal bluffs between Seattle and Everett, Washington during the winters of 1996 and 1997. Shallow earth slides and debris flows were the most common, but a few deep-seated rotational earth slides also occurred. The landslides caused significant property damage and interfered with rail traffic; future landslides in the area pose significant hazards to property and public safety. Field observations indicate that ground-water seepage, runoff concentration, and dumping at the tops of the bluffs all contributed to instability of the bluffs. Most landslides in the study area occurred in colluvium, residuum, and landslide deposits derived from the Vashon Drift, particularly the advance outwash. In the northern part of the area, colluvium derived from the Pleistocene Whidbey Formation was also involved in shallow landslides. Comparison of recent activity with historic records in the southern part of the map area indicates that landslides tend to occur in many of the same areas as previous landslides.

Washington↗
USGS2000

Preliminary method for anticipating the occurrence of precipitation-induced landslides in Seattle, Washington

Analysis of precipitation data associated with historical landslide events in Seattle has resulted in the identification of precipitation thresholds for the initiation of landslides. Also, an air-temperature index for multiple landslide events is identified, and in conjunction with the precipitation thresholds, is used to develop a method for anticipating the occurrence of landslides during the December-March wet season. The precipitation thresholds are based on 3-day cumulative precipitation that occurred immediately prior to landslide events and antecedent 15-day precipitation that occurred prior to the 3-day amounts. The data indicate that 15-day cumulative precipitation influences the amount of subsequent 3-day precipitation required to initiate landslides. Results of the analysis also indicate that air-temperature data can be used to help identify times when conditions are conducive for the initiation of landslides. It is shown that a high percentage of precipitation-related landslides occurred on days when the daily maximum air temperature was between 46? and 56? F (9? and 13? C) and that nearly all of the slides occurred on days when the daily maximum air temperature was above 43? F (6? C).

Open-File Report↗
USGS2004

Assessment of Hazards Associated with the Bluegill Landslide, South-Central Idaho

The Bluegill landslide, located in south-central Idaho, is part of a larger landslide complex that forms an area the Salmon Falls Creek drainage named Sinking Canyon Recent movement of the Bluegill landslide, apparently beginning sometime in late 1998 or early 1999, has caused a 4.5 ha area of the canyon rim to drop as much as 8 m and move horizontally several meters into the canyon. Upward movement of the toe of the landslide in the bottom of canyon has created a dam that impounds a lake approximately 2 km in length. The landslide is on public administered by the U.S. Bureau of Land Management (BLM). As part of ongoing efforts to address possible public safety concerns, the BLM requested that the U.S. Geological Survey (USGS) conduct a preliminary hazard assessment of the landslide, examine possible mitigation options, and identify alternatives for further study and monitoring of the landslide. This report presents the findings of that assessment based on a field reconnaissance of the landslide on September 24, 2003, a review of data and information provided by BLM and researchers from Idaho State University, and information collected from other sources.

Open-File Report↗
USGS2007

Preliminary Results of Subsurface Exploration and Monitoring at the Johnson Creek Landslide, Lincoln County, Oregon

The Johnson Creek landslide is a translational, primarily bedrock landslide located along the Oregon coast about 5 km north of Newport. The landslide has damaged U.S. Highway 101 many times since construction of the highway and at least two geological and geotechnical investigations of the landslide have been performed by Oregon State agencies. In cooperation with the Oregon Department of Geology and Mineral Industries and the Oregon Department of Transportation, the U.S. Geological Survey upgraded landslide monitoring systems and installed additional monitoring devices at the landslide beginning in 2004. Monitoring devices at the landslide measured landslide displacement, rainfall, air temperature, shallow soil-water content, and ground-water temperature and pressure. The devices were connected to automatic dataloggers and read at one-hour and, more recently, 15-minute intervals. Monitoring results were periodically downloaded from the dataloggers using cellular telemetry. The purposes of this report are to describe and present preliminary monitoring data from November 19, 2004, to March 31, 2007.

Open-File Report↗
USGS2008

Probabilistic Methodology for Estimation of Number and Economic Loss (Cost) of Future Landslides in the San Francisco Bay Region, California

The Probabilistic Landslide Assessment Cost Estimation System (PLACES) presented in this report estimates the number and economic loss (cost) of landslides during a specified future time in individual areas, and then calculates the sum of those estimates. The analytic probabilistic methodology is based upon conditional probability theory and laws of expectation and variance. The probabilistic methodology is expressed in the form of a Microsoft Excel computer spreadsheet program. Using historical records, the PLACES spreadsheet is used to estimate the number of future damaging landslides and total damage, as economic loss, from future landslides caused by rainstorms in 10 counties of the San Francisco Bay region in California. Estimates are made for any future 5-year period of time. The estimated total number of future damaging landslides for the entire 10-county region during any future 5-year period of time is about 330. Santa Cruz County has the highest estimated number of damaging landslides (about 90), whereas Napa, San Francisco, and Solano Counties have the lowest estimated number of damaging landslides (5?6 each). Estimated direct costs from future damaging landslides for the entire 10-county region for any future 5-year period are about US $76 million (year 2000 dollars). San Mateo County has the highest estimated costs ($16.62 million), and Solano County has the lowest estimated costs (about $0.90 million). Estimated direct costs are also subdivided into public and private costs.

Open-File Report↗
USGS2019

Landscape change associated with the upper Scenic Drive landslide, La Honda, California, January 10–June 28, 2017

La Honda, California, is a small town in unincorporated San Mateo County, located on the west edge of the San Francisco Peninsula in the Santa Cruz Mountains, between San Francisco and San Jose. The Scenic Drive area of La Honda has experienced several past episodes of landslide motion, which were documented in 1998, 2005, and 2006. This report documents the movement of the upper Scenic Drive landslide that occurred between January 10 and June 28, 2017. Our mapping provides a snapshot of the 2017 upper Scenic Drive landslide, as imaged from high-resolution terrestrial laser scanner (TLS) survey data (also referred to as terrestrial lidar) that we collected January 27–28, 2017; we mapped the landforms associated with the 2017 upper Scenic Drive landslide motion using a bare-earth TLS shaded-relief base map, in addition to field observations. Our mapping is supplemented by photographs of the mapped landforms, which were taken between January 11 and 31, 2017; these photographs illustrate the development of selected landslide features. The purpose of this report is to make available the maps constructed from three-dimensional TLS data and the photographs that show the landslide morphology of the 2017 upper Scenic Drive landslide. The scope of this report is limited to the motion of the upper Scenic Drive landslide that occurred between January 10 and June 28, 2017.

California↗
USGS1997

Temperature, snowmelt, and the onset of spring season landslides in the central Rocky Mountains

Snow meltwater (snowmelt) that seeps into the subsurface is a major factor contributing to the development of landslides during the spring in mountainous areas of the Rocky Mountain region. An examination of historical temperature data in relation to spring season landslide occurrences reveals an association between the landslide events and intervals of rising temperatures that accelerate the production of snow meltwater. Historical climatic data recorded at local weather stations located near the landslide sites are used to show the association and to identify a temperature threshold that may be useful for forecasting the onset of spring season landslides. Historical daily temperature maximums and minimums for unmonitored landslide sites are estimated by applying an elevation correction factor to historical temperature data from nearby weather stations. The proposed temperature threshold (a 6-day moving average of daily maximum temperature of 58? F) is defined by the number and temporal distribution of snowmelt related landslide events. The results of the study suggest that real-time temperature data recorded at weather stations throughout the Rocky Mountain region is potentially a valuable source of information that may be useful for forecasting the onset of spring season landslides.

Open-File Report↗
USGS1988

Landslides triggered by earthquakes in the central Mississippi Valley, Tennessee and Kentucky

We mapped 221 large (more than 200 ft across) landslides of three morphologically distinct types on the bluffs bordering the Mississippi alluvial plain in western Tennessee and Kentucky Old coherent slides (146 landslides, or 66 percent of the total) include translational block slides and single and multiple-block rotational slumps, all of which are covered by mature vegetation and have eroded features; no active analogs exist in the area. Earth flows (51 landslides, or 23 percent of the total) are also largely revegetated and eroded, though a few active earth flows are present on bluffs that have been cleared of vegetation. Young rotational slumps (24 landslides, or 11 percent of the total) form solely along actively eroding near-river bluffs and are the only active or recently active landslides in the area. Two investigations conducted around 1900 indicate that the old coherent slides, in at least part of the area, formed during the 1811-12 earthquakes. The present investigation uses dendrochronology, geomorphology, historic topographic maps, local historical accounts, and comparisons with landslides triggered by other earthquakes to show that most or all of the old coherent slides and earth flows formed during the 1811-12 New Madrid earthquakes. Evidence clearly indicates that the only large, aseismic landslide activity in the area results from fluvial undercutting of near-river bluffs. This erosion of the base of the bluffs triggers slumps that are morphologically distinct from the old slumps on bluffs away from the river. Our conclusions are consistent with the findings of other recent investigations of the same landslides that indicate extensive seismic triggering of coherent slides and earth flows during the 1811-12 New Madrid earthquakes.

Kentucky, Tennessee↗