Runout prediction methods

Rickenmann, Dieter

doi:10.1007/3-540-27129-5_13

Cited by 141 publications

(116 citation statements)

References 27 publications

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“…; thus, the height difference (H) of this landslide is about 1100 m, with the runout distance (L) of about 2600 m, corresponding to an angle of reach (fahrböschung) of 22°. These morphometric values fit quite well with the empirical graphs for rock avalanches plotting travel angle against volume (Rickenmann 2005) and area against volume (Li 1983), obtained with historical data from literature. Considering the far distance of the source area and the fact that no road and village was built on the high slope, it would have been very difficult to detect early signs of mass movement, let alone issuing a proper early warning at dawn.…”

Section: Description Of the Maoxian Landslidesupporting

confidence: 78%

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

Intrieri

Raspini

Fumagalli³

et al. 2017

Landslides

325

158

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Section: Description Of the Maoxian Landslidesupporting

confidence: 78%

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

Intrieri

Raspini

Fumagalli³

et al. 2017

Landslides

325

158

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“…Volume, elevation and channel slope have been used to estimate the total travel distance (Rickenmann 1999(Rickenmann , 2005 or have been determined on the basis of the average channel slope (Prochaska et al 2008). Volume balance criteria have been considered that delineate cross-sectional and inundated planimetric areas (Iverson et al 1998;Berti and Simoni 2007).…”

Section: Empiricalmentioning

confidence: 99%

Recommendations for the quantitative analysis of landslide risk

Corominas

Westen

Frattini

et al. 2013

Bull Eng Geol Environ

699

666

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This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

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“…They performed a regression analysis that showed a correlation between the estimated flow volumes and mobility ratios. In another important effort, Rickenmann (1999 and2005) developed a set of empirical relationships to be used to estimate the most important parameters of debrisflow behaviour. Based on these relationships, assessment of a maximum volume can be followed by estimates of the peak discharge and the run-out distance.…”

Section: Methods Using Empirical Approachesmentioning

confidence: 99%

ASCHFLOW - A dynamic landslide run-out model for medium scale hazard analysis

Luna

Blahůt

Asch

et al. 2016

Geoenviron Disasters

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Background: Landslides hazard analyses entail a scale-dependent approach in order to mitigate accordingly the damages and other negative consequences at the respective scales of occurrence. Medium or large scale landslide run-out modelling for many possible landslide initiation areas has been a very difficult task in the past. This arises from the inability of the run-out models to compute the displacement with a large amount of individual initiation areas as it turns out to be computationally strenuous. Most of the existing physically based run-out models have difficulties in handling such situations. For this reason, empirical methods have been used as a practical mean to predict landslides mobility at a medium scale (1: 10,000 to 1: 50,000). They are the most widely used techniques to estimate the maximum run-out distance and affected zones not only locally but also regionally. In this context, a medium scale numerical model for flow-like mass movements in urban and mountainous areas was developed.

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Runout prediction methods

Cited by 141 publications

References 27 publications

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

Recommendations for the quantitative analysis of landslide risk

ASCHFLOW - A dynamic landslide run-out model for medium scale hazard analysis

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