Geology topics

Randall W. Jibson

Publications and source records attributed to Randall W. Jibson.

At least 19 recordsLinked to original sources

USGS2021

The US Geological Survey ground failure product: Near-real-time estimates of earthquake-triggered landslides and liquefaction

Since late 2018, the US Geological Survey (USGS) ground failure (GF) earthquake product has provided publicly available spatial estimates of earthquake-triggered landslide and liquefaction hazards, along with the qualitative hazard and population exposure-based alerts for M > 6 earthquakes worldwide and in near real time (within ∼30 min). Earthquake losses are oftentimes greatly aggravated by the impacts due to ground failure, yet those particular events with dramatic additional losses have not, heretofore, been rapidly identifiable. The GF product now provides situational awareness about the potential extent and severity of ground failure in the crucial time period before direct observations are available. We describe our implementation of the GF product and the lessons learned from the earthquakes that have occurred since the GF product was released. We describe the product design process, the underlying GF models, the methods we have developed for modeling uncertainty, and the development of the alert levels. The GF product has been produced in near real time for 320 events over the 2-year period since its public implementation in late 2018 through early 2021. The majority of these events yielded the lowest level (green) alerts for all ground-failure types, with 25 resulting in elevated hazard or exposure to landslides and 47 for liquefaction. In a qualitative comparison between the GF product alerts and GF occurrence information, we found that the product succeeds at assigning appropriate alert levels in the majority of cases. Based on our experience with the product, we have identified the following priorities for future improvements: (1) refinements of the underlying probabilistic models to incorporate severity and explicitly model the type of landslide/liquefaction; (2) development of models for fatalities and economic losses due to ground failure; and (3) estimation of the impacts of ground failure on infrastructure.

Earthquake Spectra↗

USGS2020

Progress and lessons learned from responses to landslide disasters

Landslides have the incredible power to transform landscapes and also, tragically, to cause disastrous societal impacts. Whereas the mechanics and effects of many landslide disasters have been analyzed in detail, the means by which landslide experts respond to these events has garnered much less attention. Herein, we evaluate nine landslide response case histories conducted by the U.S. Geological Survey over the past two decades and summarize the event history, the response conducted, and the lessons learned from each event. We group the responses into three categories—providing event context from past events, addressing ongoing hazards, and acquiring data for the future—and present the nine case studies accordingly. We also summarize the progress in landslide response that has been made over the past two decades, including insights and advancements on the preparation for such events, the use of new technologies, and the importance of clear communication between all parties during disasters. We believe that exchanging and sharing experiences such as these will promote more clear and successful approaches for responses to landslide disasters in the future.

Book chapter↗

USGS2020

Ground failure triggered by shaking during the November 30, 2018, magnitude 7.1 Anchorage, Alaska, earthquake

We developed an initial inventory of ground failure features from the November 30, 2018, magnitude 7.1 Anchorage earthquake. This inventory of 153 features is from ground-based observations soon after the earthquake (December 5–10) that include the presence or absence of liquefaction, landslides, and individual crack traces of lateral spreads and incipient landslides. This is not a complete inventory and simply shows general trends and examples of types and distribution of ground failures documented. Overflight observations (December 1–6) documented landslide and liquefaction presence or absence within the Chugach Mountains and along Cook Inlet in regions inaccessible to vehicles, which greatly expanded the geographic scope of this reconnaissance. Field-mapped ground-failure observations have been augmented with a set of 565 georeferenced and annotated images from both field and overflight reconnaissance cataloging additional ground-failure presence or absence from the Anchorage earthquake. Tidal erosion, fresh snowfall, limited daylight, and adverse flying conditions contributed significantly to the uncertainty and incompleteness of ground-failure observations during this reconnaissance. Notably, substantial liquefaction features at the mouths of the Little Susitna River (December 1) and Ingram Creek (December 5) were absent during subsequent overlapping missions (December 6 and 9, respectively) because of tidal action. A large rockfall observed on December 1 on Rainbow Peak was not observed during a subsequent December 5 overflight because of snow cover, which suggests that the general lack of observations of landsliding within the Chugach Mountains is uncertain.

Alaska↗

USGS2020

Types and areal distribution of ground failure associated with the 2019 Ridgecrest, California, earthquake sequence

T he July 2019 Ridgecrest, California, earthquake sequence included the largest earthquake ( M 7.1) to strike the conterminous United States in the past 20 yr. To characterize the types, numbers, and areal distributions of different types of ground failure (landslides, liquefaction, and ground cracking), I conducted a field investigation of ground failure triggered by the sequence around the periphery of the epicentral area (which had limited access). The earthquake sequence triggered sparse and widely scattered landslides over an area of ∼ 22 , 000    km 2 "> ∼ 22 , 000 km 2 ∼22,000 km2 and at a maximum epicentral distance of 114 km; these metrics are within the upper bounds as compared with global averages for earthquakes of similar size. Some rock falls blocked primary and secondary roads, but no other landslide damage was reported. Almost all of the landslides in the peripheral area were small rock falls ( ⁠ ∼ 1 – 10    m 3 "> ∼ 1 – 10 m 3 ∼1–10 m3 ⁠ ), but a few larger ( ⁠ ∼ 100    m 3 "> ∼ 100 m 3 ∼100 m3 ⁠ ) rock slides also occurred. Though there are only informal reports about ground failure in the immediate epicentral area and we lack a detailed survey there, the small number (hundreds) and size of the landslides still seems to be far below global averages for M 7.1. This could be a result of the arid landscape and lack of a deeply weathered zone of soil and regolith. Liquefaction occurred along part of the western margin of Searles Valley. One large ( ⁠ ∼ 0.4    km 2 "> ∼ 0.4 km 2 ∼0.4 km2 ⁠ ) lateral spread caused by liquefaction severely damaged parts of Trona. Minor liquefaction also occurred in a ∼ 100 ‐ m ‐ wide "> ∼ 100 ‐ m ‐ wide ∼100‐m‐wide band along the fault‐rupture zone in some places.

California↗

USGS2020

The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view

Observation, theory, and intuition all suggest that larger earthquakes should trigger larger landslides. Many factors could contribute to this, including depth-dependent shear strength or non-linearity of ground motion in soils and rock, but we hypothesize that the key characteristics of large earthquakes causing this phenomenon are (in addition to magnitude) the frequency and duration of the strong ground motion. Because of the paucity of site-specific data for detailed analysis, we take a regional approach to this question by analyzing strong-motion records and earthquake-induced landslide (EQIL) inventories from six well-documented earthquakes. Ground motion is characterized using earthquake magnitude and the median durations and frequencies (mean periods) of subsets of strong-motion records relevant to landslide triggering. EQIL inventories are characterized using the median landslide area of the entire inventory as well as the median areas of the largest 1% of the landslides and the largest 10 landslides. We then compare ground-motion characteristics with landslide size statistics to determine possible correlations. Comparisons of all earthquake- and landslide-size statistics show strong positive correlations between landslide size and (1) magnitude, (2) ground-motion duration, and (3) mean period. Although all the ground-motion measures yield highly correlated regressions, mean period appears to be the best overall predictor of landslide size. Landslide modeling using Newmark's sliding-block method also shows that longer mean periods and durations and larger magnitudes correlate strongly with increases in modeled displacements. These results support our hypothesis that increasing period and duration of seismic ground motion are the physical factors driving increased landslide sizes for larger earthquakes. Additional studies including data from a much larger set of earthquakes is needed to confirm the results of this initial study.

Engineering Geology↗

USGS2019

USGS near-real-time products-and their use-for the 2018 Anchorage earthquake

In the minutes to hours after a major earthquake, such as the recent 2018 M w "> M w 7.1 Anchorage event, the U.S. Geological Survey (USGS) produces a suite of interconnected earthquake products that provides diverse information ranging from basic earthquake source parameters to loss estimates. The 2018 Anchorage earthquake is the first major domestic earthquake to occur since several new USGS products have been developed, thus providing an opportunity to discuss the newly expanded USGS earthquake product suite, its timeliness, performance, and reception. Overall, the products were relatively timely, accurate, well received, and widely used, including by the media, who used information and visualizations from many products to frame their early reporting. One downside of the codependence of multiple products is that reasonable updates to upstream products (e.g., magnitude and source characterization) can result in significant changes to downstream products; this was the case for the Anchorage earthquake. However, the coverage of strong‐motion stations and felt reports was so dense that the ShakeMap and downstream products were relatively insensitive to changes in magnitude or fault‐plane orientation once the ground‐motion data were available. Shaking and loss indicators initially fluctuated in the first hour or two after the earthquake, but they stabilized quickly. To understand how the products are being used and how effectively they are being communicated, we analyze the media coverage of USGS earthquake products. Most references to USGS products occurred within the first 48 hr after the event. The lack of coverage after 48 hr could indicate that longer‐term products addressing what actions the USGS is taking or what early reconnaissance has revealed might be useful for those people wanting additional information about the earthquake.

Alaska↗

USGS2019

Ground failure from the Anchorage, Alaska, earthquake of 30 November 2018

Investigation of ground failure triggered by the 2018 M w "> M w Mw 7.1 Anchorage earthquake showed that landslides, liquefaction, and ground cracking all occurred and caused significant damage. Shallow rock falls and rock slides were the most abundant types of landslides, but they occurred in smaller numbers than global models that are based on earthquake magnitude predict; this might result from the 2018 earthquake being an intraslab event. Liquefaction was common in alluvial and intertidal areas; ground deformation probably related to liquefaction damaged numerous houses and port facilities in Anchorage. Ground cracking was pervasive near the edges of slopes in hilly areas and caused perhaps the most significant property damage of all types of ground failure. A complex of slump–earth flows was triggered along coastal bluffs in southern Anchorage where slides also occurred in 1964; the 2018 slides involved both mobilization of new landside material and reactivation of parts of the 1964 landslide deposits. Large translational slides that formed during the 1964 Alaska earthquake showed evidence of deformation along pre‐existing failure surfaces but did not reactivate with new net downslope displacement. Modeling suggests that ground motion in 2018 was of insufficient duration and too high frequency to trigger reactivation of the deep landslides.

Alaska↗

USGS2019

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

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

Reviews of Geophysics↗

USGS2019

Four major Holocene earthquakes on the Reelfoot fault recorded by sackungen in the New Madrid seismic zone, USA

Three sequences of well-documented, major ~M7+ earthquakes (1811-1812 CE, ~1450 CE, and ~900 CE) in the New Madrid seismic zone, USA, contribute significantly to seismic hazard in the region. However, it is unknown whether this <550 yr recurrence interval has been constant throughout the Holocene given limited geomorphic evidence of prior earthquakes. We extend the record of paleoearthquakes along the Reelfoot fault via investigation of ridge-top gravitational failure features, interpreted as sackungen. The sackungen occur in bluffs along the eastern margin of the Mississippi River floodplain and are concentrated near (<15 km) the southwest-dipping Reelfoot reverse fault. A paleoseismic trench excavated across sackungen at the Paw Paw site exposed four packages of colluvial sediment that postdate 30-11 ka Peoria loess. We interpret the colluvial packages to have been deposited following episodic failure of the sackungen as a result of strong ground motions from the following sequence of earthquakes: event 4, 1640 ± 1730 BCE; event 3, 340 ± 670 CE; event 2, 1430 ± 380 CE; and event 1, 1810 ± 50 CE (2-sigma). Event timing corresponds to previously documented earthquakes and represents the longest archive of paleoearthquakes on the Reelfoot fault. If the trenched sackungen record all major Reelfoot fault earthquakes, our observations in combination with prior investigations indicate a period of quiescence from at least 11 – 4.7 ka, followed by four major seismic events culminating in the 1811-1812 CE sequence. This clustered earthquake recurrence helps place bounds on seismic-hazard and geodynamic models in the New Madrid seismic zone.

Arkansas, Missouri↗

USGS2018

Coseismic sackungen in the New Madrid seismic zone, USA

High‐resolution lidar reveals newly recognized evidence of strong shaking in the New Madrid seismic zone in the central United States. We mapped concentrations of sackungen (ridgetop spreading features) on bluffs along the eastern Mississippi River valley in northwestern Tennessee that likely form or are reactivated during large earthquakes. These sackungen are concentrated on the hanging wall of the Reelfoot reverse fault and show a preferential orientation indicating ground failure normal to fault strike. These observations suggest that the sackungen record one or more earthquakes on the southern Reelfoot fault since the deposition of the ~30‐ to 11‐ka Peoria Loess and potentially constrain the minimum intensity of near‐fault ground motion. This study demonstrates that sackungen can be used to infer fault source and mechanism and, in combination with field‐based techniques, improve paleoseismic records and seismic hazard models.

New Madrid Seismic Zone↗

USGS2018

Factors controlling landslide frequency-area distributions

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

Earth Surface Processes and Landforms↗

USGS2018

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

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

Kaikoura↗

USGS2018

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

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

Bulletin of the Seismological Society of America↗

USGS2018

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

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

Bulletin of the Seismological Society of America↗

USGS2017

An open repository of earthquake-triggered ground-failure inventories

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

Data Series↗

USGS2017

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

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

Journal of Geophysical Research F: Earth Surface↗

USGS2017

Seismic response of soft deposits due to landslide: The Mission Peak, California, landslide

The seismic response of active and intermittently active landslides is an important issue to resolve to determine if such landslides present an elevated hazard in future earthquakes. To study the response of landslide deposits, seismographs were placed on the Mission Peak landslide in the eastern San Francisco Bay region for a period of one year. Numerous local and near‐regional earthquakes were recorded that reveal a complexity of seismic response phenomena using the horizontal‐to‐vertical spectral ratio method. At lower frequencies, a clear spectral peak is observed at 0.5 Hz common to all four stations in the array and is attributed to a surface topographic effect. At higher frequencies, other spectral peaks occur that are interpreted in terms of local deposits and structures. Site amplification from the standard reference site method shows the minimum amplification with a factor of 2, comparing a site on and off the landslide. A site located on relatively homogeneous deposits of loose soils shows a clear spectral peak associated with the thickness of the deposit. Another site on a talus‐filled graben near the headscarp shows possible 2D or 3D effects from subsurface topography or scattering within and between buried sandstone blocks. A third site on a massive partially detached block below the crown of the headscarp shows indications of resonance caused by the reverberation of shear waves within the block. The varied seismic response of different parts of this complex landslide is consistent with other studies which found that, although landslide response is commonly enhanced in the downslope direction of landslide movement, such a response does not occur uniformly or consistently. When it does occur, enhanced site response parallel to the direction of landslide movement would contribute to landslide reactivation during significant earthquakes.

California↗

USGS2016

Map of landslides triggered by the January 12, 2010, Haiti earthquake

The magnitude (M) 7.0 Haiti earthquake of January 12, 2010, triggered landslides throughout much of Haiti on the island of Hispaniola in the Caribbean Sea. The epicenter of the quake was located at 18.44°N., 72.57°W. at a depth of 13 kilometers (km) approximately 25 km southwest of the capital, Port-au-Prince. Although estimates vary widely, the most reliable surveys of casualties indicate that the earthquake caused 158,679 fatalities and more than 300,000 injuries. The U.S. Geological Survey compared publicly available satellite imagery acquired both before and after the earthquake and mapped 23,567 landslides that were triggered by the strong shaking. Our mapping from aerial photography and satellite imagery was augmented by field observations. Most of the landslides triggered by the earthquake were south of the Léogâne fault on the footwall and were fairly shallow falls and slides in weathered limestone (2–5 meters [m] thick) and volcanic rock and soil (generally <1 m thick). Landslides extended from the north to the south coasts of the southwestern peninsula (southwest of Port-au-Prince) and almost 60 km to the east and west of the epicenter. The highest concentration of landslides was on the steep limestone slopes of incised river valleys, but large numbers of landslides also occurred on gentler slopes in weathered volcanic rocks. Although some high landslide concentrations did occur near areas of maximum fault slip, the overall distribution of landslides appears to involve complex interactions between geology, topography, and strong shaking with limited spatial correlation between fault slip and landslides.

Scientific Investigations Map↗