Correlations of earthquake-triggered landslides volume and seismogenic fault

Xu, Chong

doi:10.1201/b15794-16

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…4). Compared with the landslides triggered by the 2008 Wenchuan earthquake (Xu, 2013b; which are 197,481 in number, about 1,160 km 2 in occupying area, about 6 km 3 in landslide volume, and about 110,000 km 2 in landslide distribution area, the landslides triggered by the Lushan earthquake equal to about 1/9 in number, 1/60 in occupying area, 1/150 in volume, and 1/20 in distribution area of those of the Wenchuan event, respectively.…”

Section: Accepted Manuscriptmentioning

confidence: 98%

Database and spatial distribution of landslides triggered by the Lushan, China Mw 6.6 earthquake of 20 April 2013

2015

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On 20 April 2013, an earthquake with Mw 6.6 (Ms 7.0) hit Lushan County, Sichuan Province of China (30.3°N, 103°E), only 85 km southwest of the 2008 Wenchuan Mw 7.9 event. The Lushan shock triggered a large number of landslides with various types, including highly disrupted shallow slides and rock falls, deep-seated landslides and large-scale rock avalanches. Post-earthquake high resolution aerial photographs and satellite images, as well as a series of pre-earthquake high resolution satellite images were collected to construct a detailed, accurate, objective, and complete coseismic landslide database/inventory, which was validated by field investigation in selected areas. Based on the aerial photographs (0.2 or 0.6 m resolution) that partly cover the affected area and pre-earthquake satellite images, 14,580 coseismic landslides were recognized and mapped. In those areas without post-earthquake aerial photographs coverage, we mapped 7,948 more coseismic landslides based on post-earthquake satellite images (Rapideye images with 5 m resolution and ZY-3 images including panchromatic images with 2.1 m resolution and multi-spectral images with 5.8 m resolution) and pre-earthquake satellite images. The 22,528 coseismic landslides, with a horizontal projection area of 18.88 km 2 and an estimated total volume of 41.56×10 6 m 3 , were distributed in a nearly elliptic area of about 5,400 km 2 . Correlations between coseismic landslide abundances and topographic, geologic, and seismic factors were analyzed on 15,546 landslides of area ≥100 m 2 . Scatter plots between regional slope angle and landslide abundances in generalized homogeneous lithology combinations show no obvious relationship is present between them, which challenges the conclusions of previous studies.Combining the Lushan earthquake-triggered landslides with other events on reverse and/or thrust faults such as the 1999 Chi-Chi and 2008 Wenchuan shocks, we found that coseismic landslides tend to occur in areas enveloped by two or more imbricated reverse and/or thrust faults, rather than only along the A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT3 seismogenic fault. The Lushan event shows a higher ability of triggering landslides compared with other earthquakes of similar magnitudes, which is likely due to the steep and rugged topography and fractured and densely jointed lithology resulted from long-term tectonic activity. The blind reverse seismogenic fault is likely also another significant factor. Based on detailed coseismic landslide inventory maps and databases of several recent major earthquakes such as the Wenchuan, 2010 Haiti, 2010 Yushu, and 2013 Lushan temblors, we suggest that the empirical correlations between earthquake magnitude and coseismic landslides need to be updated.

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Section: Accepted Manuscriptmentioning

confidence: 98%

Database and spatial distribution of landslides triggered by the Lushan, China Mw 6.6 earthquake of 20 April 2013

2015

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“…We established a correlation between the resulting probability and spatial extent by assigning sample points at random throughout the study area (Shao et al, 2020). Sample points located within the landslide area were considered sliding samples, while those outside the area were non-sliding samples (Xu et al, 2019). For landslide hazard modelling, six in uencing factors are adopted, including elevation, slope, aspect, Relief, river distance, fault distance and lithology.…”

Section: Landslide Hazard Assessmentmentioning

confidence: 99%

“…Using the calculated seismic peak ground acceleration for a 50-year exceedance probability of 10% in the study area as input parameters (Fig. 9), (Shao et al, 2020;Shao et al, 2021;Xu et al, 2019). The landslide hazard results in the study area were constructed by combining Bayesian probability method and logistic regression model with the landslide data.…”

Section: Landslide Hazard Assessmentmentioning

confidence: 99%

Spatial analysis and hazard assessment of large-scale ancient landslides around the reservoir area of Wudongde hydropower station, China

Shao,

Xu,

et al. 2023

Nat Hazards

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The complex geological environment and strong tectonic movement have led to the development of a large number of ancient landslides along the Jinsha River. These landslides exhibit characteristics of large-scale, complex formation mechanisms, multiple sliding periods, and high potential hazards. In this study, we aim to construct an ancient landslide inventory and conduct potential landslide hazard assessment of the Wudongde hydropower station section and its surrounding areas, which is located in the downstream area of Jinsha River. We used the visual interpretation method to recognize large ancient landslides based on high-resolution remote sensing images on the GoogleEarth platform, and analyzed the correlations between the landslide abundance and different in uencing factors. Our results show that there were 3126 ancient landslides in the study area, covering a total area of 502.64 km 2 . The statistical analysis indicated that the landslide occurrence is closely related to the slope gradient and topographic relief, and the landslide abundance index increases with the increase of above two in uencing factors. In addition, the ancient landslides gradually decreases with the increase of the elevation, indicating that ancient landslides are more likely to occur in lower elevation areas, i.e., lower portion of the hillslopes. In addition, combining with machine learning method, the potential landslide hazard assessment of the study area was calculated by the hypothetical earthquake scenario of 10% exceedance probability in 50 years. The predicted result shows that the extremely high-hazard area of landslides appeared around the hydropower station, and the high-hazard area was mainly distributed within a 5-km range along both banks of the Jinsha River. This study provides basic data and important reference for the distribution characteristics and potential hazard assessment of ancient landslides in the reservoir area of Wudongde hydropower station.

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Preparation of earthquake-triggered landslide inventory maps using remote sensing and GIS technologies: Principles and case studies

2015

Geoscience Frontiers

140

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Correlations of earthquake-triggered landslides volume and seismogenic fault

Cited by 4 publications

References 5 publications

Database and spatial distribution of landslides triggered by the Lushan, China Mw 6.6 earthquake of 20 April 2013

Database and spatial distribution of landslides triggered by the Lushan, China Mw 6.6 earthquake of 20 April 2013

Spatial analysis and hazard assessment of large-scale ancient landslides around the reservoir area of Wudongde hydropower station, China

Preparation of earthquake-triggered landslide inventory maps using remote sensing and GIS technologies: Principles and case studies

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