Rapidly Evolving Controls of Landslides After a Strong Earthquake and Implications for Hazard Assessments

Fan, Xuanmei; Yunus, Ali P.; Scaringi, Gianvito; Catani, Filippo; Subramanian, Srikrishnan Siva; Xu, Qiang; Huang, Runqui

doi:10.1029/2020gl090509

Cited by 79 publications

(53 citation statements)

References 69 publications

(97 reference statements)

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“…Following this idea, we minimized the chance of interactions among the covariates (see the multicollinearity test in Figure S1 , supplementary information) and chose, for instance, not to use those expressing the SU orientation. We did not consider the bedrock lithology as previous studies found that it had little influence on the coseismic 60 and postseismic 7 pictures in the epicentral region owing to its uniformity (mostly granite). Similarly, available precipitation metrics were not found to exert a prime control on the postseismic evolution of landslide activity 7 , owing to the smooth spatial changes of cumulative values observed in the study area.…”

Section: Resultsmentioning

confidence: 99%

Surface temperature controls the pattern of post-earthquake landslide activity

Loche

Scaringi

Yunus

et al. 2022

Sci Rep

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The patterns and controls of the transient enhanced landsliding that follows strong earthquakes remain elusive. Geostatistical models can provide clues on the underlying processes by identifying relationships with a number of physical variables. These models do not typically consider thermal information, even though temperature is known to affect the hydro-mechanical behavior of geomaterials, which, in turn, controls slope stability. Here, we develop a slope unit-based multitemporal susceptibility model for the epicentral region of the 2008 Wenchuan earthquake to explore how land surface temperature (LST) relates to landslide patterns over time. We find that LST can explain post-earthquake landsliding while it has no visible effect on the coseismic scene, which is dominated by the strong shaking. Specifically, as the landscape progressively recovers and landslide rates decay to pre-earthquake levels, a positive relationship between LST and landslide persistence emerges. This seems consistent with the action of healing processes, capable of restoring the thermal sensitivity of the slope material after the seismic disturbance. Although analyses in other contexts (not necessarily seismic) are warranted, we advocate for the inclusion of thermal information in geostatistical modeling as it can help form a more physically consistent picture of slope stability controls.

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Section: Resultsmentioning

confidence: 99%

Surface temperature controls the pattern of post-earthquake landslide activity

Loche

Scaringi

Yunus

et al. 2022

Sci Rep

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“…For input features derived from topography, we used the 30 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) (Farr et al, 2007). When processing the SAR data, this DEM was resampled to a resolution of 20 m × 22 m using linear interpolation.…”

Section: Topographic Featuresmentioning

confidence: 99%

Integrating empirical models and satellite radar can improve landslide detection for emergency response

Burrows

Milledge

Walters

et al. 2021

Nat. Hazards Earth Syst. Sci.

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Abstract. Information on the spatial distribution of triggered landslides following an earthquake is invaluable to emergency responders. Manual mapping using optical satellite imagery, which is currently the most common method of generating this landslide information, is extremely time consuming and can be disrupted by cloud cover. Empirical models of landslide probability and landslide detection with satellite radar data are two alternative methods of generating information on triggered landslides that overcome these limitations. Here we assess the potential of a combined approach, in which we generate an empirical model of the landslides using data available immediately following the earthquake using the random forest technique and then progressively add landslide indicators derived from Sentinel-1 and ALOS-2 satellite radar data to this model in the order they were acquired following the earthquake. We use three large case study earthquakes and test two model types: first, a model that is trained on a small part of the study area and used to predict the remainder of the landslides and, second, a preliminary global model that is trained on the landslide data from two earthquakes and used to predict the third. We assess model performance using receiver operating characteristic analysis and r2, and we find that the addition of the radar data can considerably improve model performance and robustness within 2 weeks of the earthquake. In particular, we observed a large improvement in model performance when the first ALOS-2 image was added and recommend that these data or similar data from other L-band radar satellites be routinely incorporated in future empirical models.

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“…Few examples of long-runout debris flows triggered by earthquakes have been described on active volcanoes (Schuster et al, 1996;Scott et al, 2001). In Mexico, a M w 6.5 earthquake that occurred in 1920 induced several landslides in the Pico de Orizaba-Cofre de Perote volcanic chain that transformed into debris flows with catastrophic effects for villages along the Huizilapan ravine (Camacho, 1920;Flores, 1922). More recently, several thousands of shallow landslides were triggered by the Tecomán earthquake of 21 January 2003 (M w 7.6) in the volcanic highlands north and northwest of Colima City (Keefer et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Earthquake-induced debris flows at Popocatépetl Volcano, Mexico

Coviello

Capra²,

Norini

et al. 2021

Earth Surf. Dynam.

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Abstract. The 2017 Mw 7.1 Puebla–Morelos intraslab earthquake (depth: 57 km) severely hit Popocatépetl Volcano, located ∼ 70 km north of the epicenter. The seismic shaking triggered shallow landslides on the volcanic edifice, mobilizing slope material saturated by the 3 d antecedent rainfall. We produced a landslide map based on a semi-automatic classification of a 50 cm resolution optical image acquired 2 months after the earthquake. We identified hundreds of soil slips and three large debris flows for a total affected area of 3.8 km2. Landslide distribution appears controlled by the joint effect of slope material properties and topographic amplification. In most cases, the sliding surfaces correspond with discontinuities between pumice-fall and massive ash-fall deposits from late Holocene eruptions. The largest landslides occurred on the slopes of aligned ENE–WSW-trending ravines, on opposite sides of the volcano, roughly parallel to the regional maximum horizontal stress and to volcano-tectonic structural features. This suggests transient reactivation of local faults and extensional fractures as one of the mechanisms that weakened the volcanic edifice and promoted the largest slope failures. The material involved in the larger landslides transformed into three large debris flows due to liquefaction. These debris flows mobilized a total volume of about 106 m3 of material also including large wood, were highly viscous, and propagated up to 7.7 km from the initiation areas. We reconstructed this mass wasting cascade by means of field evidence, samples from both landslide scarps and deposits, and analysis of remotely sensed and rainfall data. Although subduction-related earthquakes are known to produce a smaller number of landslides than shallow crustal earthquakes, the processes described here show how an unusual intraslab earthquake can produce an exceptional impact on an active volcano. This scenario, not related to the magmatic activity of the volcano, should be considered in multi-hazard risk assessment at Popocatépetl and other active volcanoes located along volcanic arcs.

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Rapidly Evolving Controls of Landslides After a Strong Earthquake and Implications for Hazard Assessments

Cited by 79 publications

References 69 publications

Surface temperature controls the pattern of post-earthquake landslide activity

Surface temperature controls the pattern of post-earthquake landslide activity

Integrating empirical models and satellite radar can improve landslide detection for emergency response

Earthquake-induced debris flows at Popocatépetl Volcano, Mexico

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