A review of methods used to estimate initial landslide failure surface depths and volumes

Jaboyedoff, Michel; Carrea, Dario; Derron, Marc-Henri; Oppikofer, Thierry; Penna, Ivanna; Rudaz, Benjamin

doi:10.1016/j.enggeo.2020.105478

Cited by 89 publications

(43 citation statements)

References 51 publications

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“…Longstanding efforts have been made to predict the slip surface of slopes, and some methods have been proposed in recent decades based on surface displacements and morphology [45][46][47][48][49]. The computational process of those methods is complicated and involves many assumptions [49].…”

Section: Discussionmentioning

confidence: 99%

Investigation on Surface Tilting in the Failure Process of Shallow Landslides

Qiao

Feng

et al. 2020

Sensors

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In recent decades, early warning systems to predict the occurrence of landslides using tilt sensors have been developed and employed in slope monitoring due to their low cost and simple installation. Although many studies have been carried out to validate the efficiency of these early warning systems, few studies have been carried out to investigate the tilting direction of tilt sensors at the slope surface, which have revealed controversial results in field monitoring. In this paper, the tilting direction and the pre-failure tilting behavior of slopes were studied by performing a series of model tests as well as two field tests. These tests were conducted under various testing conditions. Tilt sensors with different rod lengths were employed to investigate the mechanism of surface tilting. The test results show that the surface tilting measured by the tilt sensors with no rods and those with short rods located above the slip surface are consistent, while the tilting monitored by the tilt sensors with long rods implies an opposite rotational direction. These results are important references to understand the controversial surface tilting behavior in in situ landslide monitoring cases and imply the correlation between the depth of the slip surface of the slope and the surface tilting in in situ landslide monitoring cases, which can be used as the standard for tilt sensor installation in field monitoring.

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Section: Discussionmentioning

confidence: 99%

Investigation on Surface Tilting in the Failure Process of Shallow Landslides

Qiao

Feng

et al. 2020

Sensors

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“…Data availability. Data used for this study are available on Data-verseNO: https://doi.org/10.18710/47DXWT (Oppikofer et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…A thorough reanalysis of the different landslide dam inventories using a common approach would likely improve the reliability of the semiempirical relationships proposed in this study. A promising technique to assess the volume of landslide deposits is the sloping local base level technique (Jaboyedoff et al, 2004(Jaboyedoff et al, , 2020 that uses a digital elevation model and the extent of the landslide deposits to compute the possible pre-landslide topography. Jaboyedoff et al (2020) review different techniques that can be useful to assess volumes of landslides and their deposits.…”

Section: Measured or Modelled Dam Characteristicsmentioning

confidence: 99%

Semi-empirical prediction of dam height and stability of dams formed by rock slope failures in Norway

Oppikofer

Hermanns

Jakobsen

et al. 2020

Nat. Hazards Earth Syst. Sci.

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Abstract. Based on an inventory of 69 dams formed by rock slope failures in southwestern Norway and published inventories from other parts of the world, we developed semi-empirical relationships linking the maximum dam height (HD.max in metres) to dam volume (VD in 106 m3) and other relevant parameters such as valley width (WV in metres) or dam area (AD in square kilometres). Power laws are obtained for HD.max=f(VD) and HD.max=f(VD, WV), while a linear relationship links HD.max to the ratio VD∕AD. For dams in southwestern Norway, the linear relationship HD.max=1.75×VD/AD has the least uncertainties and provides the best results when comparing predicted dam heights with a validation dataset composed of existing dams in northern Norway and numerically modelled dams for possible rock slope failures. To assess the stability of future dams, we use the predicted dam heights in the dimensionless blockage index (DBI) and relating this index to the probability of dam failure derived from our dataset and other published databases on landslide dams. This study underlines the potential of semi-empirical relationships for assessing dam height and stability that needs to be included in preliminary hazard and risk assessment for unstable rock slopes, because damming of a river is an important secondary effect of landslides due to upstream flooding and possible outburst floods in the case of dam failure.

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“…This error is mainly influenced by the assumption that the potential sliding surfaces are planar. In contrast, the real ones are wavy and irregular because of the presence of rock bridge and minor discontinuities that can make the failure surface complex [41].…”

Section: Uncertainty Evaluation and Analysismentioning

confidence: 99%

Reliability and Uncertainties of the Analysis of an Unstable Rock Slope Performed on RPAS Digital Outcrop Models: The Case of the Gallivaggio Landslide (Western Alps, Italy)

2020

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A stability investigation based on Digital Outcrop Models (DOMs) acquired in emergency conditions by photogrammetric surveys based on Remote Piloted Aerial System (RPAS) was conducted on an unstable rock slope near Gallivaggio (Western Alps, Italy). The predicted mechanism of failure and volume of the unstable portion of the slope were successively verified on the DOMs acquired after the rockfall that effectively collapsed the May 29th, 2018. The comparison of the pre- and post-landslide 3D models shows that the estimated mode of failure was substantially correct. At the same time, the predicted volume of rock involved in the landslide was overestimated by around 10%. To verify if this error was due to the limited accuracy of the models georeferenced in emergency considering only the Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU)-information of RPAS, several Ground Control Points (GCPs) were acquired after the failure. The analyses indicate that the instrumental error in the volume calculation due to the direct-georeferencing method is only of the 1.7%. In contrast, the significant part is due to the geological uncertainty in the reconstruction of the real irregular geometry of the invisible part of the failure surface. The results, however, confirm the satisfying relative accuracy of the direct-georeferenced DOMs, compatible with most geological and geoengineering purposes.

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A review of methods used to estimate initial landslide failure surface depths and volumes

Cited by 89 publications

References 51 publications

Investigation on Surface Tilting in the Failure Process of Shallow Landslides

Investigation on Surface Tilting in the Failure Process of Shallow Landslides

Semi-empirical prediction of dam height and stability of dams formed by rock slope failures in Norway

Reliability and Uncertainties of the Analysis of an Unstable Rock Slope Performed on RPAS Digital Outcrop Models: The Case of the Gallivaggio Landslide (Western Alps, Italy)

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