Seismic and geologic controls on spatial clustering of landslides in
three large earthquakes

Rault, Claire; Robert, Alexandra; Marc, Odin; Hovius, Niels; Meunier, Patrick

doi:10.5194/esurf-2018-82

Cited by 8 publications

(15 citation statements)

References 11 publications

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“…those for which N (a) N (S)) can result in noisy data that are difficult to interpret. We use the approach by Rault et al (2018) to identify the parts of the conditional probability data where our observations are sparse, leading to lower confidence in the results. We compute the confidence interval I p associated with the random drawing of the N (L) landslide cells from the landscape distribution of the predictor variable.…”

Section: Conditional Probability and Landslide Hazardmentioning

confidence: 99%

“…This is particularly true at steeper slopes, since landslide hazard increases exponentially with slope, approximately doubling for every 10 • increase in slope. Given the observation from a number of landslide inventories that coseismic landslides initiate near ridge crests (Densmore and Hovius, 2000;Meunier et al, 2008;Rault et al, 2018), it is perhaps surprising that landslide hazard generally increases with increasing upslope contributing area (i.e. when moving downslope from ridge crests).…”

Section: Rule 3: Minimise the Angle Of The Slope Under Yourmentioning

confidence: 99%

“…Ridges are often considered to be areas of high coseismic landslide probability due to topographic amplification (Densmore and Hovius, 2000;Meunier et al, 2008;Rault et al, 2018), while rivers are by definition areas of flow concentration into which landslides from multiple potential initiation zones may run out. Here we use the upslope contributing area as a continuous estimator of the proximity to a ridgeline (defined here as an area with little or no upslope cells) or a valley in order to assess how hazard may vary with position in the landscape.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simple rules to minimise exposure to coseismic landslide hazard

Milledge

Densmore

Bellugi

et al. 2019

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides constitute a hazard to life and infrastructure and their risk is mitigated primarily by reducing exposure. This requires information on landslide hazard on a scale that can enable informed decisions. Such information is often unavailable to, or not easily interpreted by, those who might need it most (e.g. householders, local governments and non-governmental organisations). To address this shortcoming, we develop simple rules to minimise exposure to coseismic landslide hazard that are understandable, communicable and memorable, and that require no prior knowledge, skills or equipment to apply. We examine rules based on two common metrics of landslide hazard, (1) local slope and (2) upslope contributing area as a proxy for hillslope location relative to rivers or ridge crests. In addition, we introduce and test two new metrics: the maximum angle to the skyline and the hazard area, defined as the upslope area with slope >40∘ from which landslide debris can reach a location without passing over a slope of <10∘. We then test the skill with which each metric can identify landslide hazard – defined as the probability of being hit by a landslide – using inventories of landslides triggered by six earthquakes that occurred between 1993 and 2015. We find that the maximum skyline angle and hazard area provide the most skilful predictions, and these results form the basis for two simple rules: “minimise your maximum angle to the skyline” and “avoid steep (>10∘) channels with many steep (>40∘) areas that are upslope”. Because local slope alone is also a skilful predictor of landslide hazard, we can formulate a third rule as “minimise the angle of the slope under your feet, especially on steep hillsides, but not at the expense of increasing skyline angle or hazard area”. In contrast, the upslope contributing area has a weaker and more complex relationship to hazard than the other predictors. Our simple rules complement but do not replace detailed site-specific investigation: they can be used for initial estimations of landslide hazard or to guide decision-making in the absence of any other information.

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Section: Conditional Probability and Landslide Hazardmentioning

confidence: 99%

Section: Rule 3: Minimise the Angle Of The Slope Under Yourmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simple rules to minimise exposure to coseismic landslide hazard

Milledge

Densmore

Bellugi

et al. 2019

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Preparatory factors, those factors that reduce the stability of a slope over time without leading to failure, such as, for example, glacial cycles (Grämiger et al, 2017; McColl & Davies, 2013), can be studied by combining detailed field observations with advanced numerical modeling at both the regional and site scale. Triggering factors, such as heavy precipitation or strong seismic events, are often studied with detailed investigations at the regional (Meunier et al, 2008; Rault et al, 2018; Valagussa et al, 2019) and site scale (Clayton et al, 2017; Glueer & Loew, 2015).…”

Section: Introductionmentioning

confidence: 99%

Regional‐Scale Investigation of Preconditioning Factors of Rock Slope Instabilities in NW Bhutan

et al. 2020

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We present a new inventory of large rock slope instabilities and an extensive structural data set for northwestern Bhutan. Our data set is largely based on satellite observations, such as optical images and high-resolution digital surface models, complemented with field observations. Kinematic analyses over seven different structural domains recognized in the study region were carried out to investigate structural control over the landslide distribution at a regional scale. In order to account for the sampling heterogeneity in the different data sets, a weighting system to the structural data is proposed. The results show that structural control exists in five out of seven domains, with foliation strongly influencing the sliding mechanisms. A lithological control appears also evident, with sedimentary rocks showing the highest landslide densities in the region. This study demonstrates how methodologies built on remote sensing data are suitable to investigate landslide predisposition at regional scales especially in largely inaccessible areas.

show abstract

Section: Introductionmentioning

confidence: 99%

Response to Anonymous referee 2

Milledge¹

2019

Preprint

View full text Add to dashboard Cite

Landslides constitute a hazard to life and infrastructure and their risk is mitigated primarily by reducing exposure. This requires information on landslide hazard on a scale that can enable informed decisions. Such information is often unavailable to, or not easily interpreted by, those who might need it most (e.g. householders, local governments and non-governmental organisations). To address this shortcoming, we develop simple rules to minimise exposure to coseismic landslide hazard that are understandable, communicable and memorable, and that require no prior knowledge, skills or equipment to apply. We examine rules based on two common metrics of landslide hazard, (1) local slope and (2) upslope contributing area as a proxy for hillslope location relative to rivers or ridge crests. In addition, we introduce and test two new metrics: the maximum angle to the skyline and the hazard area, defined as the upslope area with slope > 40 • from which landslide debris can reach a location without passing over a slope of < 10 • . We then test the skill with which each metric can identify landslide hazard -defined as the probability of being hit by a landslide -using inventories of landslides triggered by six earthquakes that occurred between 1993 and 2015. We find that the maximum skyline angle and hazard area provide the most skilful predictions, and these results form the basis for two simple rules: "minimise your maximum angle to the skyline" and "avoid steep (> 10 • ) channels with many steep (> 40 • ) areas that are upslope". Because local slope alone is also a skilful predictor of landslide hazard, we can formulate a third rule as "minimise the angle of the slope under your feet, especially on steep hillsides, but not at the expense of increasing skyline angle or hazard area". In contrast, the upslope contributing area has a weaker and more complex relationship to hazard than the other predictors. Our simple rules complement but do not replace detailed site-specific investigation: they can be used for initial estimations of landslide hazard or to guide decision-making in the absence of any other information.

show abstract

Seismic and geologic controls on spatial clustering of landslides in three large earthquakes

Cited by 8 publications

References 11 publications

Simple rules to minimise exposure to coseismic landslide hazard

Simple rules to minimise exposure to coseismic landslide hazard

Regional‐Scale Investigation of Preconditioning Factors of Rock Slope Instabilities in NW Bhutan

Response to Anonymous referee 2

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