Seismogenic fault and topography control on the spatial patterns of landslides triggered by the 2017 Jiuzhaigou earthquake

Wu, Chengyou; Cui, Peng; Li, Yusheng; Ayala, Irasema Alcántara; Huang, Chao; Yi, Shujian

doi:10.1007/s11629-017-4761-9

Cited by 52 publications

(20 citation statements)

References 34 publications

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“…The number of landslides showed a slowly decreasing trend, with an increase in the distance between the landslide and the fault zone, a finding which was consistent with the theory and proved that the fault zone exerted a certain influence on landslide development. As one of the main triggering factors of landslides, earthquakes can not only directly induce landslide failure, but can also reduce the threshold of landslide failure by reducing slope stability [20,46]. Figure 12c shows that the landslide density reached a substantial value when the seismic peak acceleration was 0.3 g and 0.4 g, a finding which proved that it affected the spatial landslide distribution.…”

Section: Controlling Factors Of Spatial Landslide Distributionmentioning

confidence: 84%

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

et al. 2021

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Construction of the 998.64-km Linzhi–Ya’an section of the Sichuan‒Tibet Railway has been influenced by landslide disasters, threatening the safety of Sichuan‒Tibet railway projects. Landslide identification and deformation analysis in this area are urgently needed. In this context, it was the first time that 164 advanced land-observing satellite-2 (ALOS-2) phased array type L-band synthetic aperture radar-2 (PALSAR-2) images were collected to detect landslide disasters along the entire Linzhi‒Ya’an section. Interferogram stacking and small baseline interferometry methods were used to derive the deformation rate and time-series deformation from 2014‒2020. After that, the hot spot analysis method was introduced to conduct spatial clustering analysis of the annual deformation rate, and the effective deformation area was quickly extracted. Finally, 517 landslide disasters along the Linzhi‒Ya’an route were detected by integrating observed deformation, Google Earth optical images, and external geological data. The main factors controlling the spatial landslide distribution were analyzed. In the vertical direction, the spatial landslide distribution was mainly concentrated in the elevation range of 3000‒5000 m, the slope range of 10‒40°, and the aspect of northeast and east. In the horizontal direction, landslides were concentrated near rivers, and were also closely related to earthquake-prone areas, fault zones, and high-precipitation areas. In short, rainfall, freeze–thaw weathering, seismic activity, and fault zones are the main factors inducing landslides along this route. This research provides scientific support for the construction and operation of the Linzhi‒Ya’an section of the Sichuan‒Tibet Railway.

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Section: Controlling Factors Of Spatial Landslide Distributionmentioning

confidence: 84%

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

et al. 2021

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“…The Huya fault is dominated by left-lateral strike slip. Previous studies have pointed out the north-west section of the Huya fault to be the specific seismogenic source of the Jiuzhaigou earthquake (Fan et al, 2018;Yusheng et al, 2017;Wu et al, 2018). More generally, the Jiuzhaigou area is a seismically active hilly mountainous region which is subjected to more than 50 events with M ≥ 5 in the past century (Fan et al, 2018).…”

Section: Geomorphological Settingsmentioning

confidence: 99%

From scenario-based seismic hazard to scenario-based landslide hazard: rewinding to the past via statistical simulations

Luo¹,

Lombardo²,

Westen³

et al. 2020

Preprint

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The vast majority of landslide susceptibility studies assumes the slope instability process to be time-invariant under the definition that "the past and present are keys to the future". This assumption may generally be valid. However, the trigger, be it a rainfall or an earthquake event, clearly varies over time. And yet, the temporal component of the trigger is rarely included in landslide susceptibility studies and only confined to hazard assessment.In this work, we investigate a population of landslides triggered in response to the 2017 Jiuzhaigou earthquake (M w = 6.5) including the associated ground motion in the analyses, these being carried out at the Slope Unit (SU) level. We do this by implementing a Bayesian version of a Generalized Additive Model and assuming that the slope instability across the SUs in the study area behaves according to a Bernoulli probability distribution.This procedure would generally produce a susceptibility map reflecting the spatial pattern of the specific trigger and therefore of limited use for land use planning. However, we implement this first analytical step to reliably estimate the ground motion effect, and its distribution, on unstable SUs.We then assume the effect of the ground motion to be time-invariant, enabling statistical simulations for any ground motion scenario that occurred in the area from 1933 to 2017.As a result, we obtain the full spectrum of potential susceptibility patterns over the last century and compress this information into a susceptibility model/map representative of all the possible ground motion patterns since 1933. This backward statistical simulations can also be further exploited in the opposite direction where, by accounting for scenario-based ground motion, one can also use it in a forward direction to estimate future unstable slopes.

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“…The Huya fault is dominated by left-lateral strike slip. Previous studies have pointed out the north-west section of the Huya fault to be the specific seismogenic source of the Jiuzhaigou earthquake (Fan et al 2018;Yusheng et al 2017;Wu et al 2018). More generally, the Jiuzhaigou area is a seismically active hilly mountainous region which is subjected to more than 50 events with M !…”

Section: Geomorphological Settingsmentioning

confidence: 99%

From scenario-based seismic hazard to scenario-based landslide hazard: rewinding to the past via statistical simulations

Luo

Lombardo

Westen

et al. 2021

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

The vast majority of statistically-based landslide susceptibility studies assumes the slope instability process to be time-invariant under the definition that “the past and present are keys to the future”. This assumption may generally be valid. However, the trigger, be it a rainfall or an earthquake event, clearly varies over time. And yet, the temporal component of the trigger is rarely included in landslide susceptibility studies and only confined to hazard assessment. In this work, we investigate a population of landslides triggered in response to the 2017 Jiuzhaigou earthquake ($$M_w = 6.5$$ M w = 6.5 ) including the associated ground motion in the analyses, these being carried out at the Slope Unit (SU) level. We do this by implementing a Bayesian version of a Generalized Additive Model and assuming that the slope instability across the SUs in the study area behaves according to a Bernoulli probability distribution. This procedure would generally produce a susceptibility map reflecting the spatial pattern of the specific trigger and therefore of limited use for land use planning. However, we implement this first analytical step to reliably estimate the ground motion effect, and its distribution, on unstable SUs. We then assume the effect of the ground motion to be time-invariant, enabling statistical simulations for any ground motion scenario that occurred in the area from 1933 to 2017. As a result, we obtain the full spectrum of potential coseismic susceptibility patterns over the last century and compress this information into a hazard model/map representative of all the possible ground motion patterns since 1933. This backward statistical simulations can also be further exploited in the opposite direction where, by accounting for scenario-based ground motion, one can also use it in a forward direction to estimate future unstable slopes.

show abstract

Seismogenic fault and topography control on the spatial patterns of landslides triggered by the 2017 Jiuzhaigou earthquake

Cited by 52 publications

References 34 publications

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

Landslide Detection in the Linzhi–Ya’an Section along the Sichuan–Tibet Railway Based on InSAR and Hot Spot Analysis Methods

From scenario-based seismic hazard to scenario-based landslide hazard: rewinding to the past via statistical simulations

From scenario-based seismic hazard to scenario-based landslide hazard: rewinding to the past via statistical simulations

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