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Ground motions at the outermost limits of seismically triggered landslides

Over the last few decades, we and our colleagues have conducted field investigations in which we mapped the outermost limits of triggered landslides in four earthquakes: 1987 Whittier Narrows, California ( M 5.9), 1987 Superstition Hills, California ( M 6.5), 1994 Northridge, California ( M 6.7), and 2011 Mineral, Virginia ( M 5.8). In an additional two earthquakes, 1976 Guatemala ( M 7.5) and 1983 Coalinga, California ( M 6.5), we determined limits using high‐resolution aerial‐photographic interpretation in conjunction with more limited ground investigation. Limits in these earthquakes were defined by the locations of the very smallest failures (<1&thinsp;&thinsp;m 3 ) from the most susceptible slopes that can be identified positively as having been triggered by earthquake shaking. Because we and our colleagues conducted all of these investigations, consistent methodology and criteria were used in determining limits. In the six earthquakes examined, we correlated the outermost landslide limits with peak ground accelerations (PGAs) from ShakeMap models of each earthquake. For the four earthquakes studied by field investigation, the minimum PGA values associated with farthest landslide limits ranged from 0.02 g to 0.08 g . The range for the two earthquakes investigated using aerial‐photographic interpretations was 0.05&ndash;0.11 g . Although PGA values at landslide limits depend on several factors, including material strength, topographic amplification, and hydrologic conditions, these values provide an empirically useful lower limiting range of PGA needed to trigger the smallest failures on very susceptible slopes. In a well‐recorded earthquake, this PGA range can be used to identify an outer boundary within which we might expect to find landsliding; in earthquakes that are not well recorded, mapping the outermost landslide limits provides a useful clue about ground‐motion levels at the mapped limits.

Bulletin of the Seismological Society of America↗

Seafloor observations eliminate a landslide as the source of the 1918 Puerto Rico Tsunami

The 11 October 1918 devastating tsunami in northwest Puerto Rico had been used as an example for earthquake‐induced landslide tsunami hazard. Three pieces of evidence pointed to a landslide as the origin of the tsunami: the discovery of a large submarine landslide scar from bathymetry data collected by shipboard high‐resolution multibeam sonar, reported breaks of submarine cable within the scar, and the fit of tsunami models to flooding observations. Newly processed seafloor imagery collected by remotely operated vehicle (ROV) show, however, pervasive Fe–Mn crust (patina) on the landslide walls and floor, indicating that the landslide scar is at least several hundred years old. C 14 "> 14 C dates of sediment covering the landslide floor verify this interpretation. Although we have not searched the region systematically for an alternative tsunami source, we propose a possible source—a two‐segment normal‐fault rupture along the eastern wall of Mona rift. The proposed fault location matches the published normal faults with steep bathymetry and is close to the International Seismological Center–Global Earthquake Model catalog locations of the 1918 mainshock and aftershocks. The ROV observations further show fresh vertical slickensides and rock exposure along the proposed fault trace. Hydrodynamic models from an M w "> M w 7.2 earthquake rupture along the eastern wall of the rift faithfully reproduce the reported tsunami amplitudes, polarities, and arrival times. Our analysis emphasizes the value of close‐up observations and physical samples to augment remote sensing data in natural hazard studies.

Puerto Rico↗

Some observations of landslides triggered by the 29 April 1991 Racha earthquake, Republic of Georgia

On 29 April 1991 an M s 7.0 earthquake occurred in the Racha region of the Great Caucasus Mountains in north-central Republic of Georgia. The earthquake occurred on a thrust fault striking roughly east-west and dipping about 20° to 45° northward; focal depth was 17 ± 2 km. We observed no surface fault rupture, but the earthquake caused extensive structural damage to the many unreinforced stone buildings in the area, and at least 114 people were killed. Many landslides were triggered in a 2500-km 2 epicentral area, and they caused much of the structural damage and at least half the fatalities. We observed the following six types of landslides (in order of decreasing abundance): rock falls, debris slides, slumps, earth slides, rock block slides, and rock avalanches. The types of landslides triggered by the earthquake are controlled primarily by lithology and geologic structure. Enigmatic landslide processes associated with this earthquake include (1) delays of several days between earthquake shaking and significant landslide movement, probably caused by changes in groundwater conditions; (2) small co-seismic displacement of landslides active at the time of the earthquake, a possible result of viscoplastic damping of the seismic shaking; and (3) somewhat unusual failure geometries related to local topography and geologic structure.

Bulletin of the Seismological Society of America↗

Ribbon Cliff landslide Washington, and the earthquake of 14 December 1872

Estimates of the epicentral location and maximum intensity of the earthquake of 14 December 1872, the largest and oldest historic earthquake documented in the Pacific Northwest, are controversial largely because the estimates are based on ground effects. The Ribbon Cliff landslide is one of the more critical ground effects used to argue that the epicenter was in the vicinity of Lake Chelan in central Washington. Sketchy historical accounts link the Ribbon Cliff landslide to the 1872 earthquake, but a subsequent study disputed the historical accounts and, on the basis of dendrochronology, concluded that the landslide occurred more than 100 yr prior to the earthquake. However, Quaternary stratigraphic relations and the results of multiple dating techniques reported here indicate that the main Ribbon Cliff landslide probably occurred within a 14-yr period that includes the time of the 1872 earthquake. Although our study supports the historical accounts that link the landslide to the December 1872 earthquake, it does not prove that seismic shaking triggered the landslide.

Washington↗

Terrestrial lidar data of the February 14, 2019 Sausalito Boulevard Landslide, Sausalito, California

On February 14, 2019, just before 2:56 am local time (Pacific Standard Time), a landslide initiated from the hillslopes above the Hurricane Gulch section of the City of Sausalito, Marin County, California. The landslide, specifically classified as a debris flow, overran a road (Sausalito Boulevard) immediately below the landslide source area and impacted a residential structure that subsequently toppled downslope and collided with another residential structure. The second structure then crossed a lower road (Crescent Avenue) that runs along the base of the slope before the mixture of soil and structural debris came to rest in and near the valley axis that drains the lower area of Hurricane Gulch. The U.S. Geological Survey responded to this event within hours of the landslide and provided situational awareness of possible secondary landslide hazards associated with the unstable slope. The USGS also rapidly mobilized its topographic surveying capabilities (specifically, GPS and terrestrial lidar devices) and collected a three-dimensional point cloud model of the landslide source area and surrounding terrain to capture the as-failed condition of the slope for use in potential future studies. This report summarizes the methods and available data collected during this response.

California↗

Real-Time Monitoring of Active Landslides

Landslides threaten lives and property in every State in the Nation. To reduce the risk from active landslides, the U.S. Geological Survey (USGS) develops and uses real-time landslide monitoring systems. Monitoring can detect early indications of rapid, catastrophic movement. Up-to-the-minute or real-time monitoring provides immediate notification of landslide activity, potentially saving lives and property. Continuous information from real-time monitoring also provides a better understanding of landslide behavior, enabling engineers to create more effective designs for halting landslide movement.

Fact Sheet↗

Maps Showing Locations of Damaging Landslides Caused by El Nino Rainstorms, Winter Season 1997-98, San Francisco Bay Region, California

Heavy rainfall associated with a strong El Nino caused over $150 million in landslide damage in the 10-county San Francisco Bay region during the winter and spring of 1998. Reports of landsliding began in early January 1998 and continued throughout the winter and spring. On February 9, President Clinton declared all 10 counties eligible for Federal Emergency Management Agency (FEMA) disaster assistance. In April and May of 1998, personnel from the U.S. Geological Survey (USGS) conducted a field reconnaissance in the area to provide a general overview of landslide damage resulting from the 1997-98 sequence of El Nino-related storms. Seven scientists from the USGS Landslide Hazards Program based in Reston, Virginia; Golden, Colorado; and Menlo Park, California; and five scientists from the USGS Geologic Mapping Program?s San Francisco Bay Mapping Team based in Menlo Park, California, cooperated in the landslide-damage assessments. The assessments were done for 10 counties in the Bay area: Alameda, Contra Costa, Marin, Napa, San Francisco, Santa Clara, Santa Cruz, San Mateo, Solano, and Sonoma. USGS Maps in this series include: MF-2325-A (Napa County), MF-2325-B (Alameda County), MF-2325-C (Marin County), MF-2325-D (Santa Cruz County), MF-2325-E (Contra Costa County), MF-2325-F (Sonoma County), MF-2325-G (San Francisco City and County), MF-2325-H (San Mateo County), MF-2325-I (Solano County), MF-2325-J (Santa Clara County). In addition to USGS scientists providing data from the field evaluation, each of the counties, many consultants, and others cooperated fully in providing the landslide-damage information compiled here.

Miscellaneous Field Studies Map↗

Terrestrial LIDAR investigation of the December 2003 and January 2007 activations of the Northridge Bluff landslide, Daly City, California

On December 20, 2003 and again on January 1, 2007, landslides occurred along the coastal bluff that forms the west boundary of Daly City, California sending debris as far as 290 meters downhill and 90 meters into the ocean. This area is known for large landslide events where 150-meter tall coastal bluffs extend southward along the west boundary of San Francisco and San Mateo Counties (Fig. 1). The 2003 and 2007 landslide events occurred west of Northridge Drive in Daly City and just south of Avalon Canyon, which bisects the bluffs in this area (Fig. 2). Residential development, utility lines and roads occupy the land immediately east of this location. As part of a comprehensive project to investigate the failure mechanisms of coastal bluff landslides in weakly lithified sediments along the west coast of the United States, members of the U.S. Geologic Survey (USGS) Coastal and Marine Geology (CMG) Program performed reconnaissance mapping of these landslide events including collection of high-resolution topographic data using CMG's terrestrial LIDAR laser scanning system. This report provides a brief background on each landslide event and presents topographic datasets collected following each event. Downloadable contour data, images, and FGDC-compliant metadata of the surfaces generated from the LIDAR data are also provided. LIDAR data collection and processing techniques used to generate the datasets are outlined. Geometric and volumetric measurements are also presented along with high-resolution cross-sections through various areas of the slide masses and discussion concerning the slides present (2007) configuration is provided.

California↗

Pillar Mountain Landslide, Kodiak, Alaska

Pillar Mountain landslide on the southeast face of Pillar Mountain is about 915 m (3,000 ft) southwest of the city of Kodiak, Alaska. The landslide is about 520 m (1,700 ft) wide at its base and extends approximately from sea level to an altitude of about 343 m (1,125 ft). The slide developed on an ancient and apparently inactive landslide. Renewed movement was first detected on December 5, 1971, following removal of about 230,000 m3 (300,000 yd3) of material from the base of the slope. Although movement of the landslide has decreased since December, 1971, movement continues and the possibility exists that it could increase as a result of an earthquake, water saturation of the landslide mass, or other causes. In the most extreme case, as much as 3.8 to 7.6 million m (5-10 million ) of debris could fall into the sea at Inner Anchorage. If this took place suddenly, it could generate a wave comparable in height to the tsunami that damaged Kodiak during the Alaskan Earthquake of 1964. Therefore, we believe that the Pillar landslide is a potential hazard to the city of Kodiak and its environs that merits a thorough investigation and evaluation.

Open-File Report↗

Landslides triggered by the winter 1996-97 storms in the Puget Lowland, Washington

Snowmelt and rainfall events triggered many landslides and debris flows in the Seattle, Washington, area during late December 1996 and January and March 1997. Landslides caused the deaths of at least four people, millions of dollars in damage to public and private property, lost revenues, traffic diversions, and other direct and indirect losses. Although shallow slides and debris flows were the most common slope failures, many deep-seated slides also occurred. Comparing maps that show distribution of historic landslides with reports of landslides compiled by city and county governments for the winter of 1996-97 and our field reconnaissance of recent landslide deposits and scars indicates that many bluffs and steep hillsides are sites of recurring failures. Investigation of the 1996-97 landslides indicates that houses and other structures built downslope from steep bluffs are in particular danger of impact by debris flows, while those on the benches, slopes, or rim of bluffs are subject to severe damage by deep slides.

Open-File Report↗

Grfin Tools—User guide and methods for modeling landslide runout and debris-flow growth and inundation

The software package, Grfin Tools, can estimate potential runout from landslides or inundation from geophysical mass flows such as debris flows, lahars from volcanoes, and rock avalanches within a digital elevation model (DEM). Grfin is an acronym of gr owth + f low + in undation. The tools within this package apply simple, well-tested, empirical models of runout that are computationally efficient and require minimal parameters. These tools can be used individually (for example, to estimate debris-flow inundation) or in combination to represent a more complete series of linked processes, from landslide source areas, to unchannelized transport, to channelized flows. Grfin Tools can rapidly assess potential runout and inundation over large areas and the results are readily visualized in a geographic information system. Tools for assessing areas affected by runout and flow inundation include a height-to-length ( H / L ) ratio, angle-of-reach approach for estimating open-slope, unchannelized landslide runout, and volume-area scaling relations for assessing flow inundation in channels. Potential landslide areas that constitute the sources of runout or inundation can be delineated with topographic features, such as slope and (or) curvature, derived by the software package, or by employing potential sources derived from other landslide susceptibility models. Grfin Tools also has the capability to assess inundation from flows that grow volumetrically downstream. This is a vital feature, as larger flows commonly result in longer runout and larger inundation. The software uses empirically derived growth factors applied over upslope contributing source areas or upstream channel lengths to integrate the effects of various growth processes, such as channel entrainment, streambank failures, adjacent landslides, and hillslope erosion. Inundation follows a drainage network defined with a separate tool that uses topographic curvature to identify channel initiation locations. This document includes information on using Grfin Tools, the basis and methods underlying the tools and models, detailed descriptions of the software input and output files, and tips for handling special conditions such as roads and large water bodies. Multiple detailed examples illustrating different applications are also presented. Grfin Tools relies on the freely available TauDEM software package (Tarboton, 2005). The Grfin Tools software release is available from Cronkite-Ratcliff and others (2025).

Techniques and Methods↗

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↗

Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska

This map of fractures, scarps, faults, and landslides was completed to identify areas in Glacier Bay National Park and Preserve that may present a landslide-generated tsunami hazard. To address the potential of landslide and tsunami hazards in the park, the National Park Service (NPS) and the US Geological Survey (USGS) partnered to conduct a multi-year hazard assessment of Glacier Bay National Park and Preserve. To produce the map described in this report, we used the newly acquired (2019-2020) light detection and ranging (LiDAR) 0.5 to 1.0 m digital elevation models (DEMs) that cover all the coastal areas of the park and extend up to the ridgetops in places with steep slopes. A bare earth DEM was used to identify and map areas of incipient landslides (i.e., fractures and scarps), fault scarps, and areas where landslides have clearly occurred in the past (i.e., areas where scars and deposits are clearly visible). This map provides a baseline data set that can be used to aid forecasts of where landslides are most likely to occur in the future.

Alaska↗

Rainfall-induced landslides in Puerto Rico: An overview

Rainfall-induced landslides are common in Puerto Rico (PR). The presence of steep slopes in mountainous terrain, coupled with weathered soils and intense rainfall, leads to severe slope-stability problems throughout the island. Episodic triggering events such as hurricanes and earthquakes further exacerbate these problems. All physiographic provinces of the island have experienced landslides. The stability of natural and man-made slopes is a serious concern for government authorities and the civil engineering community in Puerto Rico. This paper presents an overview of the rainfall induced landslide problem in PR, a summary of literature published on this subject, and proposes a rainfall intensity landslide threshold based on landslide events data from 1959 to 2003. This threshold can be used as part of a potential landslide warning system.

Conference Paper↗

Landslide risk in the San Francisco Bay region

We have used historical records of damaging landslides triggered by rainstorms, and a newly developed Probabilistic Landslide Assessment Cost Estimation System (PLACES), to estimate the numbers and direct costs of future landslides in the San Francisco Bay region. The estimated annual cost of future landslides in the entire region is about US $15 million (year 2000 $). The estimated annual cost is highest for San Mateo County ($3.32 million) and lowest for Solano County ($0.18 million). Normalizing costs by dividing by the percentage of land area with slopes equal or greater than about 10&deg; indicates that San Francisco County will have the highest cost per square km ($7,400), whereas Santa Clara County will have the lowest cost per square km ($230). These results indicate that the San Francisco Bay region has one of the highest levels of landslide risk in the United States. Compared to landslide cost estimates from the rest of the world, the risk level in the Bay region seems high, but not exceptionally high.

California↗

Landslides and engineering geology of the Seattle, Washington, area

This volume brings together case studies and summary papers describing the application of state-of-the-art engineering geologic methods to landslide hazard analysis for the Seattle, Washington, area. An introductory chapter provides a thorough description of the Quaternary and bedrock geology of Seattle. Nine additional chapters review the history of landslide mapping in Seattle, present case studies of individual landslides, describe the results of spatial assessments of landslide hazard, discuss hydrologic controls on landsliding, and outline an early warning system for rainfall-induced landslides.

Washington↗

Failure of a massive earthquake-induced landslide dam in Papua New Guinea

In many areas of the world, landslides dams are both interesting natural phenomena and significant hazards. A few of the these natural blockages attain heights that rival or exceed those of the largest manmade dams. A landslide dam in its natural state differs from a constructed embankment dam in that it is composed of a heterogeneous mass of poorly consolidated earth debris and has no channeled spillway or other protected outlet for its impoundment. Having no outlet, landslide dams upon overtopping very commonly fail by breaching due to erosion by the overflowing stream. Some of the world's largest and most devastating floods have occurred because of the failure of large landslide dams (Schuster and Costa, 1986). This article discusses the recent occurrence of a large earthquake-induced landslide that dammed the Bairaman River in the interior of the island of New Britian, Papua New Guinea, and the subsequent overtopping and failure of this landslide dam.

New Britain↗

Landslides triggered by Hurricane Hugo in eastern Puerto Rico, September 1989

On the morning of September 18, 1989, a category-four hurricane struck eastern Puerto Rico with a sustained wind speed in excess of 46 m/s. The 24-h rainfall accumulation from the hurricane ranged from 100 to 339 mm. Average rainfall intensities ranging from 34 to 39 mm/h were calculated for 4 and 6 h periods, respectively, at a rain gage equipped with satellite telemetry, and at an observer station. The hurricane rainfall triggered more than 400 landslides in the steeply sloping, highly dissected mountains of eastern Puerto Rico. Of these landslides, 285 were mapped from aerial photography which covered 6474 ha. Many of the mapped landslides were on northeast- and northwest-facing slopes at the eastern terminus of the mountains, nearest the hurricane path. The surface area of individual landslides ranged from 18 m2 to 4500 m2, with a median size of 148 m2. The 285 landslides disturbed 0.11% of the land surface in the area covered by aerial photographs. An approximate denudation rate of 164 mm/1000 y was calculated from the volume of material eroded by landsliding and the 10-y rainfall recurrence interval.

Caribbean Journal of Science↗