USGS Science⌕ Search

USGS · 70222943

On the use of statistical analysis to understand submarine landslide processes and assess their hazard

Abstract

Because of their inaccessibility, submarine landslides are typically studied individually and at great effort and expense to provide knowledge of the specific site conditions where these landslides occur. Statistical analysis of submarine landslide scars can offer generalized perspectives on the processes that initiate submarine landslides and can help toward hazard assessment in areas that have not been studied in detail. The following review discusses more than a decade of development of statistical approaches to studying submarine landslides. Landslides were previously viewed together with other natural hazards, such as earthquakes and fires, as a phenomenon whose size distribution obeys an inverse power law. Inverse power law distributions are the result of self-organized avalanche processes, in which the final hazard size cannot be predicted at the onset of the disturbance. We find that volume and area distributions of submarine landslides along the U.S. Atlantic continental slope and along nine other margins worldwide do not follow an inverse power law. Rigorous statistical tests of several different probability distribution models indicate that the lognormal model is most appropriate for these siliciclastic environments. Lognormal distributions can be simulated by assuming that the area of slope failure depends on earthquake magnitude, in other words, failure occurs simultaneously over the area affected by horizontal ground shaking and does not cascade from nucleating sources. Therefore, the maximum landslide size can be predicted from the earthquake magnitude and the distance from the rupturing fault. Moreover, earthquakes <~M4.5 cannot generate significant submarine landslides. We further demonstrate that empirical, offshore landslide hazard curves can be developed from these lognormal landslide size distributions, if the duration of mapped landslide activity is known. In addition to hazard estimation, scaling relationships can yield insights on the physical processes associated with landslide failure. For example, the log-log relationship between volume and area of landslide scars in siliciclastic margins is observed to be almost linear implying that most landslides are translational. Carbonate margins, in contrast, show a power-law distribution of scar volumes and their volume to area relationship is ~1.3. These results suggest that landslides in carbonate margins are governed by the random distributions of existing fissures, and they act like rock falls on land. Although earthquakes are the principal trigger of submarine landslides, the effects of earthquake frequency on slope stability can be counterintuitive. The average size of landslide scars decreases non-linearly with increasing frequency of earthquakes and increases with increasing sedimentation rate. The effect is interpreted as evidence for densification and shear strength increase of margin sediment, induced by repeated seismic shaking.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Uri S. ten Brink, Eric L. Geist. 2020-12-22. On the use of statistical analysis to understand submarine landslide processes and assess their hazard. https://doi.org/10.1007/978-3-030-60196-6_23

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Ground failure resulting from earthquake ground motions

The ground failure resulting from an earthquake, at all scales, is ultimately controlled by the details of near-surface earthquake ground motions, the spatially distributed mechanical characteristics of surface materials and how the two interact. This chapter introduces the aspects of ground-motion seismology that are most relevant to the triggering of different types of ground failure, such as landslides and liquefaction. In particular, the chapter focuses on different sources of local modification (e.g. amplification) of earthquake ground motions in the shallow subsurface, known as site effects. The chapter ends with an overview of the controls on, general spatial patterns of, and approaches to regional modelling of the manifestation of ground failure that may be triggered by an earthquake.

Book chapter↗

Loma salmonae and related species

Loma salmonae is a microsporidium that infects Pacific salmon and causes a gill inflammatory syndrome known as microsporidial gill disease of salmon. This disease has been mostly associated with netpen-farmed Chinook salmon ( Oncorhynchus tshawytscha ) in British Columbia, Canada. Clinical, diagnostic, pathological aspects of disease, as well as approaches for disease avoidance in salmon aquaculture are discussed. A laboratory infection model in rainbow trout was used to determine life cycle-stages, transmission dynamics, pathophysiology, influence of temperature, and to test therapeutics applicable to aquaculture. This experimental model has been informative on various approaches of disease control, including the development of a promising vaccine. In addition to improving fish health in salmon farming in North America, this L. salmonae model will be applicable to other microsporidial diseases that may be encountered in emerging aquaculture regions.

Book chapter↗

Cumulative effects of multiple stressors on marine mammals: Elephant seals as a model system

Noise exposure is a potential stressor for free-ranging marine mammals and is often studied in the absence of other environmental factors. Here, a multi-investigator, interdisciplinary effort was undertaken to examine the response of elephant seals to multiple stressors. An integrated physiological and ecological approach was taken, including immunology, stress physiology, toxicology, animal behavior, population biology, and life history theory, to examine the cumulative effects of exposure to multiple stressors in elephant seals. While we measured the response of individual animals, a population response can be predicted by incorporating these results into the long-term data on elephant seal demographics.

Book chapter↗