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Randall W. Jibson

Publications and source records attributed to Randall W. Jibson.

At least 37 records · Page 2Linked to original sources
USGS2016

USGS approach to real-time estimation of earthquake-triggered ground failure - Results of 2015 workshop

The U.S. Geological Survey (USGS) Earthquake Hazards and Landslide Hazards Programs are developing plans to add quantitative hazard assessments of earthquake-triggered landsliding and liquefaction to existing real-time earthquake products (ShakeMap, ShakeCast, PAGER) using open and readily available methodologies and products. To date, prototype global statistical models have been developed and are being refined, improved, and tested. These models are a good foundation, but much work remains to achieve robust and defensible models that meet the needs of end users. In order to establish an implementation plan and identify research priorities, the USGS convened a workshop in Golden, Colorado, in October 2015. This document summarizes current (as of early 2016) capabilities, research and operational priorities, and plans for further studies that were established at this workshop. Specific priorities established during the meeting include (1) developing a suite of alternative models; (2) making use of higher resolution and higher quality data where possible; (3) incorporating newer global and regional datasets and inventories; (4) reducing barriers to accessing inventory datasets; (5) developing methods for using inconsistent or incomplete datasets in aggregate; (6) developing standardized model testing and evaluation methods; (7) improving ShakeMap shaking estimates, particularly as relevant to ground failure, such as including topographic amplification and accounting for spatial variability; and (8) developing vulnerability functions for loss estimates.

Open-File Report↗
USGS2016

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↗
USGS2015

Geotechnical effects of the 2015 magnitude 7.8 Gorkha, Nepal, earthquake and aftershocks

This article summarizes the geotechnical effects of the 25 April 2015 M 7.8 Gorkha, Nepal, earthquake and aftershocks, as documented by a reconnaissance team that undertook a broad engineering and scientific assessment of the damage and collected perishable data for future analysis. Brief descriptions are provided of ground shaking, surface fault rupture, landsliding, soil failure, and infrastructure performance. The goal of this reconnaissance effort, led by Geotechnical Extreme Events Reconnaissance, is to learn from earthquakes and mitigate hazards in future earthquakes.

Gorkha↗
USGS2015

Assessment of existing and potential landslide hazards resulting from the April 25, 2015 Gorkha, Nepal earthquake sequence

Introduction On April 25, 2015, a large ( M 7.8) earthquake shook much of central Nepal and was followed by a series of M >6 aftershocks, including a M 7.3 event on May 12, 2015. This earthquake and aftershocks, referred to as the &ldquo;Gorkha earthquake sequence,&rdquo; caused thousands of fatalities, damaged and destroyed entire villages, and displaced millions of residents. The earthquakes also triggered thousands of landslides in the exceedingly steep topography of Nepal; these landslides were responsible for hundreds of fatalities, and blocked vital roads and trails to affected villages (fig. 1). Landslides caused by the Gorkha earthquake sequence continue to pose both immediate and long-term hazards to villages and infrastructure within the affected region. Some landslides blocked rivers and thus created another potential concern for villages located downstream. With the support of the United States Agency for International Development (USAID), Office of Foreign Disaster Assistance (OFDA), and in collaboration with earthquake-hazard organizations from both the United States (for example, U.S. National Science Foundation Geoengineering Extreme Event Reconnaissance [GEER] Team) and Nepal (International Centre for Integrated Mountain Development [ICIMOD]), the U.S. Geological Survey (USGS) responded to this crisis by providing landslide-hazard expertise to Nepalese agencies and affected villages. In addition to collaborating with an international group of remote-sensing scientists to document the spatial distribution of landsliding in the first few weeks following the earthquake, the USGS conducted in-country landslide hazard assessments for 10 days beginning May 24, 2015. Much of the information obtained by the USGS during their time in Nepal was conveyed directly to affected villages and government agencies as opportunities arose. Upon return to the United States, data organization, interpretation, and synthesis began immediately to provide a rapid assessment of landslide hazards for use by Nepalese agencies during the 2015 summer monsoon (typically occurring from June through September). This report provides a detailed account of assessments performed in May and June 2015 and focuses on valley-blocking landslides because they have the potential to pose considerable hazard to many villages in Nepal. First, we provide a seismological background of Nepal and then detail the methods used for both external and in-country data collection and interpretation. Our results consist of an overview of landsliding extent, a characterization of all valley-blocking landslides identified during our work, and a description of video resources that provide high resolution coverage of approximately 1,000 kilometers (km) of river valleys and surrounding terrain affected by the Gorkha earthquake sequence. This is followed by a description of site-specific landslide-hazard assessments conducted while in Nepal and includes detailed descriptions of five noteworthy case studies. Finally, we assess the expectation for additional landslide hazards during the 2015 summer monsoon season.

Open-File Report↗
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↗
USGS2014

Maps showing seismic landslide hazards in Anchorage, Alaska

The devastating landslides that accompanied the great 1964 Alaska earthquake showed that seismically triggered landslides are one of the greatest geologic hazards in Anchorage. Maps quantifying seismic landslide hazards are therefore important for planning, zoning, and emergency-response preparation. The accompanying maps portray seismic landslide hazards for the following conditions: (1) deep, translational landslides, which occur only during great subduction-zone earthquakes that have return periods of =300-900 yr; (2) shallow landslides for a peak ground acceleration (PGA) of 0.69 g, which has a return period of 2,475 yr, or a 2 percent probability of exceedance in 50 yr; and (3) shallow landslides for a PGA of 0.43 g, which has a return period of 475 yr, or a 10 percent probability of exceedance in 50 yr. Deep, translational landslide hazards were delineated based on previous studies of such landslides, with some modifications based on field observations of locations of deep landslides. Shallow-landslide hazards were delineated using a Newmark-type displacement analysis for the two probabilistic ground motions modeled.

Alaska↗
USGS2013

The effect of complex fault rupture on the distribution of landslides triggered by the 12 January 2010, Haiti earthquake

The M W 7.0, 12 January 2010, Haiti earthquake triggered more than 7,000 landslides in the mountainous terrain south of Port-au-Prince over an area that extends approximately 50 km to the east and west from the epicenter and to the southern coast. Most of the triggered landslides were rock and soil slides from 25°–65° slopes within heavily fractured limestone and deeply weathered basalt and basaltic breccia. Landslide volumes ranged from tens of cubic meters to several thousand cubic meters. Rock slides in limestone typically were 2–5 m thick; slides within soils and weathered basalt typically were less than 1 m thick. Twenty to thirty larger landslides having volumes greater than 10,000 m 3 were triggered by the earthquake; these included block slides and rotational slumps in limestone bedrock. Only a few landslides larger than 5,000 m 3 occurred in the weathered basalt. The distribution of landslides is asymmetric with respect to the fault source and epicenter. Relatively few landslides were triggered north of the fault source on the hanging wall. The densest landslide concentrations lie south of the fault source and the Enriquillo-Plantain-Garden fault zone on the footwall. Numerous landslides also occurred along the south coast west of Jacmél. This asymmetric distribution of landsliding with respect to the fault source is unusual given the modeled displacement of the fault source as mainly thrust motion to the south on a plane dipping to the north at approximately 55°; landslide concentrations in other documented thrust earthquakes generally have been greatest on the hanging wall. This apparent inconsistency of the landslide distribution with respect to the fault model remains poorly understood given the lack of any strong-motion instruments within Haiti during the earthquake.

Book chapter↗
USGS2013

SLAMMER: Seismic LAndslide Movement Modeled using Earthquake Records

This program is designed to facilitate conducting sliding-block analysis (also called permanent-deformation analysis) of slopes in order to estimate slope behavior during earthquakes. The program allows selection from among more than 2,100 strong-motion records from 28 earthquakes and allows users to add their own records to the collection. Any number of earthquake records can be selected using a search interface that selects records based on desired properties. Sliding-block analyses, using any combination of rigid-block (Newmark), decoupled, and fully coupled methods, are then conducted on the selected group of records, and results are compiled in both graphical and tabular form. Simplified methods for conducting each type of analysis are also included.

Techniques and Methods↗
USGS2012

Extraordinary distance limits of landslides triggered by the 2011 Mineral, Virginia, earthquake

The 23 August 2011 Mineral, Virginia, earthquake (M w 5.8) was the largest to strike the eastern U.S. since 1897 and was felt over an extraordinarily large area. Although no large landslides occurred, the shaking did trigger many rock and soil falls from steep river banks and natural cliffs in the epicentral area and from steep road cuts along, and northwest of, the Blue Ridge Parkway. We mapped the occurrence of rock falls to determine distance limits that could be compared with those from other documented earthquakes. Studies of previous earthquakes indicated a maximum epicentral distance limit for landsliding of ~60 km for an M 5.8 earthquake; the maximum distance limit for the 2011 earthquake was 245 km, the largest exceedance of the historical limit ever recorded. Likewise, the previous maximum area affected by landslides for this magnitude was 1500 km 2 ; the area affected by landslides in the 2011 earthquake was 33,400 km 2 . These observations provide physical evidence that attenuation of strong shaking for eastern U.S. earthquakes is significantly lower than for plate‐boundary earthquakes. Also, distance limits parallel to the regional structural trend are greater than those that transect the structure, which suggests anisotropic attenuation related to the regional geologic structure. Peak ground acceleration (PGA) at the landslide distance limits is estimated to have been about 0.02–0.04g.

Virginia↗
USGS2009

Maps Showing Seismic Landslide Hazards in Anchorage, Alaska

The devastating landslides that accompanied the great 1964 Alaska earthquake showed that seismically triggered landslides are one of the greatest geologic hazards in Anchorage. Maps quantifying seismic landslide hazards are therefore important for planning, zoning, and emergency-response preparation. The accompanying maps portray seismic landslide hazards for the following conditions: (1) deep, translational landslides, which occur only during great subduction-zone earthquakes that have return periods of =~300-900 yr; (2) shallow landslides for a peak ground acceleration (PGA) of 0.69 g, which has a return period of 2,475 yr, or a 2 percent probability of exceedance in 50 yr; and (3) shallow landslides for a PGA of 0.43 g, which has a return period of 475 yr, or a 10 percent probability of exceedance in 50 yr. Deep, translational landslide hazard zones were delineated based on previous studies of such landslides, with some modifications based on field observations of locations of deep landslides. Shallow-landslide hazards were delineated using a Newmark-type displacement analysis for the two probabilistic ground motions modeled.

Scientific Investigations Map↗
USGS2006

Photographs, correspondence, and presentations related to the La Conchita, California, landslide

This report contains the following photographs and information related to the La Conchita, California, landslide: 1) Digital photographs taken by the author during a visit to the La Conchita landslide on January 14, 2005. 2) Correspondence related to the approval and release of USGS Open-File Report 2005-1067, Landslide Hazards at La Conchita, California. 3) A presentation on the La Conchita landslide that has been given to various organizations and groups since 2005.

Open-File Report↗
USGS2004

Landslides triggered by the 13 January and 13 February 2001 earthquakes in El Salvador

During a one-month period in early 2001 , El Salvador experienced two devastating earthquakes . On 13 January , a M-7.7 earthquake centered ∼40 km off the southern coast in the Pacific Ocean caused widespread damage and fatalities throughout much of the country. The earthquake triggered thousands of landslides that were broadly scattered across the southern half of the country. The most damaging landslide , a rapidly moving mass of ∼130, 000 m 3 , occurred in the Las Colinas neighborhood of Santa Tecla, where ∼585 people were killed. Another large landslide (∼750, 000 m 3 ) near the city of San Vicente blocked the Pan-American Highway for several weeks. One month later, on 13 February , a M-6.6 earthquake occurred ∼40 km east-southeast of San Salvador and triggered additional thousands of landslides in the area east of Lake Ilopango. The landslides were concentrated in a 2500 km 2 area and were particularly abundant in areas underlain by thick deposits of poorly consolidated, late Pleistocene and Holocene Tierra Blanca rhyolitic tephras erupted from Ilopango caldera. Most of the triggered landslides were relatively small, shallow failures, but two large landslides occurred that blocked the El Desagüe River and the Jiboa River. The two earthquakes triggered similar types of landslides , but the distribution of triggered landslides differed because of different earthquake source parameters. The largemagnitude, deep, offshore earthquake triggered broadly scattered landslides over a large region, whereas the shallow, moderate-magnitude earthquake centered within the country triggered a much smaller, denser concentration of landslides . These results are significant in the context of seismic-hazard mitigation for various earthquake scenarios.

Special Paper of the Geological Society of America↗
USGS2004

Map showing susceptibility to rainfall-triggered landslides in the municipality of Ponce, Puerto Rico

The risk of landslides during intense or prolonged rainfall is high in steeply sloping areas such as the municipality of Ponce, where 56 percent of the 301-square-kilometer municipality has slopes 10 degrees or greater. These are areas where the possibility of landsliding increases when triggering conditions such as heavy rainfall or excavation and construction occur. Using a 30-meter digital elevation model to classify hillslope angle, a digital map of bedrock geology, and maps showing the locations of landslides associated with a severe storm in October 1985, the municipality was classified into areas of low, moderate, and high susceptibility to landslides triggered by heavy rainfall. Areas defined by geology as having 0-0.1 landslides per square kilometer were mapped as having low landslide susceptibility, areas having 0.1-0.5 landslides per square kilometer were mapped as having moderate susceptibility, and areas having more than 0.5 landslides per square kilometer were mapped as having high landslide susceptibility. Areas with hillslope angles of 5 degrees or less were not classified as they are considered too flat for significant landslide susceptibility. The result of this classification indicates that 34 percent of the municipality has high susceptibility to rainfall-triggered landsliding, 24 percent has moderate susceptibility, and 9 percent has low susceptibility. Approximately 34 percent of the municipality, mainly areas with slopes of 5 degrees or less and water bodies, was not classified. Because of the uncertainties inherent in the susceptibility classification of extensive landscape areas as well as timing of landslide triggers, landslide susceptibility maps should be used with caution. The results of this study are valid for generalized planning and assessment purposes, but may be less useful at the site-specific scale where local geologic and geographic heterogeneities may occur. Construction in areas of moderate to high landslide susceptibility should proceed only after site evaluation by engineering geologists. Large magnitude earthquakes, which occur rarely in Puerto Rico, are the other major trigger of landslides for Caribbean islands; however, this factor was not considered in the development of this map.

Ponce↗
USGS2003

Java Programs for Using Newmark's Method and Simplified Decoupled Analysis to Model Slope Performance During Earthquakes

Landslides typically cause a large proportion of earthquake damage, and the ability to predict slope performance during earthquakes is important for many types of seismic-hazard analysis and for the design of engineered slopes. Newmark's method for modeling a landslide as a rigid-plastic block sliding on an inclined plane provides a useful method for predicting approximate landslide displacements. Newmark's method estimates the displacement of a potential landslide block as it is subjected to earthquake shaking from a specific strong-motion record (earthquake acceleration-time history). A modification of Newmark's method, decoupled analysis, allows modeling landslides that are not assumed to be rigid blocks. This open-file report is available on CD-ROM and contains Java programs intended to facilitate performing both rigorous and simplified Newmark sliding-block analysis and a simplified model of decoupled analysis. For rigorous analysis, 2160 strong-motion records from 29 earthquakes are included along with a search interface for selecting records based on a wide variety of record properties. Utilities are available that allow users to add their own records to the program and use them for conducting Newmark analyses. Also included is a document containing detailed information about how to use Newmark's method to model dynamic slope performance. This program will run on any platform that supports the Java Runtime Environment (JRE) version 1.3, including Windows, Mac OSX, Linux, Solaris, etc. A minimum of 64 MB of available RAM is needed, and the fully installed program requires 400 MB of disk space.

Open-File Report↗
USGS2002

Anomalous concentrations of seismically triggered rock falls in Pacoima Canyon: Are they caused by highly susceptible slopes or local amplification of seismic shaking?

Anomalously high concentrations of rock falls were triggered in Pacoima Canyon (Los Angeles, California) during the 1994 Northridge earthquake. Similar concentrations were also documented from the 1971 San Fernando earthquake. Using an engineering rock-mass classification that evaluates the susceptibility of rock slopes to seismic failure based on the fracture properties of a rock mass (in terms of a numerical "Q-value" that describes rock quality), the rock slopes in Pacoima Canyon were compared with rock slopes in sorrounding areas where topography and lithology are similar, but rock-fall concentrations from the earthquakes were much lower. A statistical comparison of Q-values from five sites surrounding Pacoima Canyon indicates that seismic susceptibilities are similar to those within Pacoima Canyon; differences in the characteristics of rock slopes between these sites are not sufficient to account for the relatively high concentrations of rock falls within Pacoima Canyon as compared to low concentrations elsewhere. By eliminating susceptibility differences as a cause, the most likely explanations for the differences in rock-fall concentrations is anomalously high shaking levels in Pacoima Canyon, possibly resulting from topographic amplification within the canyon.

Bulletin of the Seismological Society of America↗