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At least 307 records · Page 17Linked to original sources
USGS2009

Landsliding in partially saturated materials

Rainfall‐induced landslides are pervasive in hillslope environments around the world and among the most costly and deadly natural hazards. However, capturing their occurrence with scientific instrumentation in a natural setting is extremely rare. The prevailing thinking on landslide initiation, particularly for those landslides that occur under intense precipitation, is that the failure surface is saturated and has positive pore‐water pressures acting on it. Most analytic methods used for landslide hazard assessment are based on the above perception and assume that the failure surface is located beneath a water table. By monitoring the pore water and soil suction response to rainfall, we observed shallow landslide occurrence under partially saturated conditions for the first time in a natural setting. We show that the partially saturated shallow landslide at this site is predictable using measured soil suction and water content and a novel unified effective stress concept for partially saturated earth materials.

Geophysical Research Letters↗
USGS2020

Landslide disparities, flume discoveries, and Oso despair

Landslide dynamics is the branch of science that seeks to understand the motion of landslides by applying Newton's laws. This memoir focusses on a 40‐year effort to understand motion of highly mobile—and highly lethal—landslides such as debris avalanches and debris flows. A major component of this work entailed development and operation of the U.S. Geological Survey debris flow flume, a unique, large‐scale experimental facility in Oregon. Experiments there yielded new insights that informed development of mathematical models that were aimed not only at explaining landslide dynamics but also at evaluating landslide and debris flow hazards. The most sophisticated of these models, called D‐Claw, found its first practical application during investigations of the 2014 Oso, Washington, landslide disaster. That event provided indelible lessons about the utility and sociology of science in the real world.

Washington↗
USGS2019

Assessing the feasibility of satellite-based thresholds for hydrologically driven landsliding

Elevated soil moisture and heavy precipitation contribute to landslides worldwide. These environmental variables are now being resolved with satellites at spatiotemporal scales that could offer new perspectives on the development of landslide warning systems. However, the application of these data to hydro-meteorological thresholds (which account for antecedent soil moisture and rainfall) first need to be evaluated with respect to proven, direct measurement-based thresholds that use rain gauges and in situ soil moisture sensors. Here, we compare ground-based hydrologic data to overlapping satellite-based data before, during, and after a recent season of widespread shallow landsliding in the San Francisco Bay Area (California, USA). We then explore how the remotely sensed information could be used to empirically define hypothetical thresholds for shallow landsliding. We find that the ground-based thresholds developed with a single monitoring station show superior performance because the in situ soil saturation data better reflect the gravity-dominated subsurface flow conditions that are characteristic of hillslopes during the rainy season. Although the satellite-based thresholds can identify most of the landslide days, they include a greater number of false alarms due to overestimates of soil moisture between major storm events. To avoid the type of false alarms that are characteristic of our satellite-based thresholds, further post-processing of the near-surface hydrologic response data to better reflect gravity-dominated drainage should be integrated into satellite-based model outputs. Our results encourage further deployment of ground stations in landslide-prone terrain and cautious exploration of satellite-based hydro-meteorological thresholds where in situ networks are nonexistent.

California↗
USGS2020

Abundant spontaneous and dynamically triggered submarine landslides in the Gulf of Mexico

Submarine landslides that occur offshore are common along the U.S. continental margins. These mass wasting events can trigger tsunamis and hence potentially devastate coastal communities and damage offshore infrastructure. However, the initiation and failure processes of submarine landslides are poorly understood. Here, we identify and locate 85 previously unknown submarine landslides in the Gulf of Mexico from 2008 to 2015. Ten of these landslides failed spontaneously while the remaining 75 were dynamically triggered by passing seismic surface waves from distant earthquakes with magnitudes as small as ∼5. Our observations demonstrate ongoing submarine landslide activity in the Gulf of Mexico where dense energy industry infrastructure is present and that the region is prone to secondary seismic hazard despite the low local seismicity rate. Our results should facilitate future investigations to identify unstable offshore slopes, to illuminate dynamic processes of landslides, and perhaps to apply remote detection technology in tsunami warning systems.

Geophysical Research Letters↗
USGS2026

Impacts of transient critical zone evolution on landslide susceptibility and hazard Across the Utuado batholith, Puerto Rico

Landscapes in humid climates often experience rapid chemical and mechanical weathering that can change groundwater fluxes, drainage pathways, and frictional strength via alterations in subsurface mineral composition and matrix porosity. These changes to hillslope critical zone structure and strength should control landslide susceptibility, size, and failure style. Here we test the impact of differential weathering on landslide failure processes by exploiting a natural experiment along the dioritic Utuado batholith in Puerto Rico's Cordillera Central, where a sharp weathering gradient follows an upstream-propagating knickzone into an uplifted shoreline platform that was affected by Hurricane Maria in 2017. Through a combination of landslide mapping, field geophysical and geotechnical surveys, topographic analysis, calibrated stream profile inversion, 3D back-analysis of hillslope strength, and debris-flow inundation assessments, we show that differential weathering induces changes to critical zone structure and consequently landslide susceptibility and hazard. Our mapping reveals that the hurricane-induced landslides preferentially cluster along less weathered hillslopes despite a marked increase in frictional strength. Jointly inverted seismic refraction and electrical resistivity profiles show that the frictionally weak, heavily weathered hillslopes are highly porous and dry, which we posit acts to stabilize slopes through limiting deeper hydrologic connectivity that can produce shallow water tables with destabilizing lateral seepage forces during storms. Debris-flow inundation mapping and analysis reveals that major contributors to debris-flow growth, channel steepness and landslide coalescence, scale linearly with hillslope friction angle. This leads to higher-mobility debris flows along knickzone reaches, which disproportionately affects communities at the base of the plateau.

Puerto Rico↗
USGS2002

Volcanic breccia and hyaloclastite in blocks from the Nuuanu and Wailau landslides, Hawaii

Steep slopes of giant landslide blocks in the Nuuanu and Wailau landslides expose fragmental volcanic rocks subdivided into monomict and polymic t hyaloclastite and breccia. The various samples form as 1) secondary slopemantling unlithified polymict breccia consisting of clasts set in a mud matrix; 2 ) monomict and polymict hyaloclastite and polymict breccia, with zeolite cement, that form downslope of the shoreline where lava flows enter the sea; and 3 ) monomict breccia formed by tectonic fragmentation of glassy submarine-erupted pillow basalt. Lavas erupted from single volcanoes are highly variable in major-element composition, even during their tholeiitic shield stage, making it difficult to identify which landslide block was derived from which volcano. Low-temperature fluids circulate through the fragmental deposits on the flanks of the volcanoes, partially altering the glass to palagonite and cementing the volcaniclastic rocks with Na- and K-rich zeolites. Volcano spreading along low-angle thrust faults laterally transports deep early submarine pillow lava out to the flank of the volcano where it crops out as tectonic monomict breccia. The faults underlying the landslide blocks are within this tectonized core of the volcano, not simply within the shallow slope deposits of hyaloclastite and breccia. The Nuuanu landslide predates the 1.5 Ma Wailau landslide.

Hawaii↗
USGS2009

Landslide movement in southwest Colorado triggered by atmospheric tides

Landslides are among the most hazardous of geological processes, causing thousands of casualties and damage on the order of billions of dollars annually. The movement of most landslides occurs along a discrete shear surface, and is triggered by a reduction in the frictional strength of the surface. Infiltration of water into the landslide from rainfall and snowmelt and ground motion from earthquakes are generally implicated in lowering the frictional strength of this surface. However, solid-Earth and ocean tides have recently been shown to trigger shear sliding in other processes, such as earthquakes and glacial motion. Here we use observations and numerical modelling to show that a similar processatmospheric tidescan trigger movement in an ongoing landslide. The Slumgullion landslide, located in the SanJuan Mountains of Colorado, shows daily movement, primarily during diurnal low tides of the atmosphere. According to our model, the tidal changes in air pressure cause air and water in the sediment pores to flow vertically, altering the frictional stress of the shear surface; upward fluid flow during periods of atmospheric low pressure is most conducive to sliding. We suggest that tidally modulated changes in shear strength may also affect the stability of other landslides, and that the rapid pressure variations associated with some fast-moving storm systems could trigger a similar response. ?? 2009 Macmillan Publishers Limited. All rights reserved.

Nature Geoscience↗
USGS2020

Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing

Landslides modify the natural landscape and cause fatalities and property damage worldwide. Quantifying landslide dynamics is challenging due to the stochastic nature of the environment. With its large area of ~1 km 2 and perennial motions at ~10–20 mm per day, the Slumgullion landslide in Colorado, USA, represents an ideal natural laboratory to better understand landslide behavior. Here, we use hybrid remote sensing data and methods to recover the four-dimensional surface motions during 2011–2018. We refine the boundaries of an area of ~0.35 km 2 below the crest of the prehistoric landslide. We construct a mechanical framework to quantify the rheology, subsurface channel geometry, mass flow rate, and spatiotemporally dependent pore-water pressure feedback through a joint analysis of displacement and hydrometeorological measurements from ground, air and space. Our study demonstrates the importance of remotely characterizing often inaccessible, dangerous slopes to better understand landslides and other quasi-static mass fluxes in natural and industrial environments, which will ultimately help reduce associated hazards.

Colorado↗
USGS2018

Tropical storm-induced landslide potential using combined field monitoring and numerical modeling

When heavy rainfall, such as that associated with tropical storms, falls on steep hillsides, shallow landslides are often one of the damaging consequences. To assess landslide potential from heavy rainfall, a strategy of combined numerical simulation and field monitoring of variably saturated hillslope conditions is developed. To test the combined method, hillslope hydrologic data from paired field monitoring sites in western North Carolina are examined. The hydrologic data collected from the field monitoring site where no shallow landslide has occurred is used to identify and calibrate the hydromechanical parameters used in a numerical ground water flow model. The identified parameters are then used to simulate landslide potential at the two hillslopes during heavy rainfall associated with hurricanes Frances and Ivan (HFI) that impacted western North Carolina in 2004. Results identify the timing of instability at the shallow landslide site and show that the stable site remains stable during rainfall associated with the HFI tropical storms. Thus, the results demonstrate the effectiveness of combined numerical modeling and field monitoring to evaluate landslide potential under variably saturated conditions.

North Carolina↗
USGS2022

Constructing a large-scale landslide database across heterogeneous environments using task-specific model updates

Preparation and mitigation efforts for widespread landslide hazards can be aided by a large-scale, well-labeled landslide inventory with high location accuracy. Recent smallscale studies for pixel-wise labeling of potential landslide areas in remotely-sensed images using deep learning (DL) showed potential but were based on data from very small, homogeneous regions with unproven model transferability. In this paper we consider a more realistic and practical setting for large-scale heterogeneous landslide data collection and DL-based labeling. In this setting, remotely sensed images are collected sequentially in temporal batches, where each batch focuses on images from a particular ecoregion, but different batches can focus on different ecoregions with distinct landscape characteristics. For such a scenario, we study the following questions: (1) How well do DL models trained in homogeneous regions perform when they are transferred to different ecoregions, (2) Does increasing the spatial coverage in the data improve model performance in a given ecoregion (even when the extra data do not come from the ecoregion), and (3) Can a landslide pixel labeling model be incrementally updated with new data, but without access to the old data and without losing performance on the old data (so that researchers can share models obtained from proprietary datasets)' We address these questions by extending the Learning without Forgetting framework, which is used for incremental training of image classification models, to the setting of incremental training of semantic segmentation models (e.g., identifying all landslide pixels in an image). We call the resulting extension Task-Specific Model Updates (TSMU). TSMU semantic segmentation framework consists of an encoder shared by all ecoregions to capture the similarities between them, and ecoregion-specific decoders to capture the nuances of each ecoregion. This framework is continually updated using a threestage training procedure for each new addition of an ecoregion without having to revisit data from old ecoregions and without losing performance on them.

IEEE Journal of Selected Topics in Applied Earth O↗
USGS2025

Overcoming the data limitations in landslide susceptibility modelling

Data-driven models widely used for assessing landslide susceptibility are severely limited by the landslide and environmental data needed to create them. They rely on inventories of past landslide locations, which are difficult to collect and often nonrepresentative. Furthermore, susceptibility maps are most needed in regions without the means to assemble an inventory. To overcome these challenges, we develop a method for assessing shallow landslide susceptibility based on a probabilistic morphometric analysis of the landscape’s topography, rather than the characteristics of landslides. The model assumes that hillslopes with higher relief and gradient compared to the surrounding landscape are more prone to landslides. We demonstrate the superior performance of this approach over contrasting data-driven models across the northwestern United States. As our morphometric model only requires elevation data, it overcomes the major limitations of data-driven models and facilitates the creation of effective susceptibility models in areas where it was previously unfeasible.

Oregon, Washington↗
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↗
USGS1991

Use of longitudinal strain in identifying driving and resisting elements of landslides

Observations of deformation at the surfaces of landslides in Utah and Hawaii indicate that the upslope parts of the land-slides have stretched and the downslope parts have shortened parallel with the direction of movement. The maximum displacement of each landslide occurs in a relatively undeformed zone between the zones of shortening and stretching. The pattern of deformation at the surface of these landslides may be useful in analyzing their mechanics by helping to constrain the longitudinal forces in limit-equilibrium stability analysis. We used earth-pressure calculations to determine the range of possible longitudinal forces (per unit width) for active failure in the zone of stretching and for passive failure in the zone of shortening of one of the Hawaiian landslides. Longitudinal forces computed by stability analysis, assuming homogeneous strength, exceeded the possible forces in much of the upslope half of the landslide. Consequently, we assumed inhomogeneous strength and adjusted shear-strength parameters at each segment of the slip surface until the longitudinal forces computed by stability analysis agreed with those computed by earth-pressure theory, and the factor of safety approached unity. The distribution of longitudinal forces computed for inhomogeneous strength indicated that the boundary between driving and resisting elements of the landslide is near the thickest part of the slide, in agreement with a simple formula for the location of the boundary.

Geological Society of America Bulletin↗
USGS2008

Shallow landslide hazard map of Seattle, Washington

Landslides, particularly debris flows, have long been a significant cause of damage and destruction to people and property in the Puget Sound region. Following the years of 1996 and 1997, the Federal Emergency Management Agency designated Seattle as a “Project Impact” city with the goal of encouraging the city to become more disaster resistant to landslides and other natural hazards. A major recommendation of the Project Impact council was that the city and the U.S. Geological Survey collaborate to produce a landslide hazard map. An exceptional data set archived by the city containing more than 100 yr of landslide data from severe storm events allowed comparison of actual landslide locations with those predicted by slope-stability modeling. We used an infinite-slope analysis, which models slope segments as rigid friction blocks, to estimate the susceptibility of slopes to debris flows, which are water-laden slurries that can form from shallow failures of soil and weathered bedrock and can travel at high velocities down steep slopes. Data used for the analysis consisted of a digital slope map derived from recent light detection and ranging (LiDAR) imagery of Seattle, recent digital geologic mapping of the city, and shear-strength test data for the geologic units found in the surrounding area. The combination of these data layers within a geographic information system (GIS) platform allowed us to create a shallow landslide hazard map for Seattle.

Washington↗
USGS2008

Numerical modeling of rainfall thresholds for shallow landsliding in the Seattle, Washington, area

The temporal forecasting of landslide hazard has typically relied on empirical relations between rainfall characteristics and landslide occurrence to identify conditions that may cause shallow landslides. Here, we describe an alternate, deterministic approach to define rainfall thresholds for landslide occurrence in the Seattle, Washington, area. This approach combines an infinite slope-stability model with a variably saturated flow model to determine the rainfall intensity and duration that leads to shallow failure of hillside colluvium. We examine the influence of variation in particle-size distribution on the unsaturated hydraulic properties of the colluvium by performing capillary-rise tests on glacial outwash sand and three experimental soils with increasing amounts of fine-grained material. Observations of pore-water response to rainfall collected as part of a program to monitor the near-surface hydrology of steep coastal bluffs along Puget Sound were used to test the numerical model results and in an inverse modeling procedure to determine the in situ hydraulic properties. Modeling results are given in terms of a destabilizing rainfall intensity and duration, and comparisons with empirical observations of landslide occurrence and triggering rainfall indicate that the modeling approach may be useful for forecasting landslide occurrence.

Washington↗
USGS1997

Operation of a landslide warning system during the California storm sequence of January and February 1993

From 1986 to late December 1995, the U.S. Geological Survey and the National Weather Service operated a landslide warning system for debris flows triggered by intense rainstorms in the San Francisco Bay region. The Landslide Warning System tracked storm systems as they approached the region, determined actual rainfall with a network of radio-telemetered rain gauges, compared the rainfall to thresholds for initi-ation of debris flows, and issued the appropriate public advisories. A series of intense rainstorms during January 1993 created hazards from landslid-ing and flooding over much of California. In the San Francisco Bay region, January rainfall was over 200% of normal, triggering debris flows on natural hillslopes and road cuts across Marin, San Mateo, Alameda, Santa Clara, and Santa Cruz Counties. The warning system issued Flash Flood/Debris Flow Watches during the most intense storms on January 13 and 15,1993. Most debris flows in this area were small and widely scattered, so damage was largely limited to several blocked roadways in mountainous areas. Storm damage was much heavier in southern California, where rainfall amounts were over 350% of normal for January, triggering flash floods and many landslides. This damage prompted inquiries about developing a landslide warning system for southern California. A number of elements for a landslide warning system already exist in southern Cal-ifornia, including quantitative rainfall forecasting and a network of radio-telemetered rain gauges. Regional rainfall thresholds for debris flow initiation, consistent with the climate, topography, and geology of the region, remain to be developed. Such thresholds could probably be developed with a modest investment of research effort and resources.

California↗
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↗
USGS2014

Relation of landslides triggered by the Kiholo Bay earthquake to modeled ground motion

The 2006 Kiholo Bay, Hawaii, earthquake triggered high concentrations of rock falls and slides in the steep canyons of the Kohala Mountains along the north coast of Hawaii. Within these mountains and canyons a complex distribution of landslides was triggered by the earthquake shaking. In parts of the area, landslides were preferentially located on east‐facing slopes, whereas in other parts of the canyons no systematic pattern prevailed with respect to slope aspect or vertical position on the slopes. The geology within the canyons is homogeneous, so we hypothesize that the variable landslide distribution is the result of localized variation in ground shaking; therefore, we used a state‐of‐the‐art, high‐resolution ground‐motion simulation model to see if it could reproduce the landslide‐distribution patterns. We used a 3D finite‐element analysis to model earthquake shaking using a 10 m digital elevation model and slip on a finite‐fault model constructed from teleseismic records of the mainshock. Ground velocity time histories were calculated up to a frequency of 5 Hz. Dynamic shear strain also was calculated and compared with the landslide distribution. Results were mixed for the velocity simulations, with some areas showing correlation of landslide locations with peak modeled ground motions but many other areas showing no such correlation. Results were much improved for the comparison with dynamic shear strain. This suggests that (1) rock falls and slides are possibly triggered by higher frequency ground motions (velocities) than those in our simulations, (2) the ground‐motion velocity model needs more refinement, or (3) dynamic shear strain may be a more fundamental measurement of the decoupling process of slope materials during seismic shaking.

Hawai'i↗