ORIGINAL PAPER
A method for quick assessment of earthquake-triggered landslide
hazards: a case study of the Mw6.1 2014 Ludian, China earthquake
Xiaoli Chen
1
&
Chunguo Liu
2
&
Mingming Wang
3
Received: 24 October 2017 / Accepted: 21 May 2018
#
Springer-Verlag GmbH Germany, part of Springer Nature 2018
Abstract
Rapid assessment of the distribution of earthquake-triggered landslides is an important component of effective disaster mitiga-
tion. The effort should be based on both seismic landslide susceptibility and the ground shaking intensity, which is usually
measured by peak ground acceleration (PGA). In this paper, we address this issue by analyzing data from the Mw6.1 2014
Ludian, China earthquake. The Newmark method of rigid-block modeling was applied to calculate the critical acceleration of
slopes in the study area, which serve as measurement of slope stability under seismic load. The assessment of earthquake-
triggered landslide hazard was conducted by comparing these critical accelerations with the distribution of known PGA values.
The study area was classified into zones of five levels of landslide hazard: high, moderate high, moderate, light, and very light.
Comparison shows that the resulting landslide hazard zones agree with the actual distribution of earthquake-triggered landslides.
Nearly 70% of landslides are located in areas of high and moderately high hazard, which occupy only 17% of the study region.
This paper demonstrates that using PGA, combined with the analysis of seismic landslide susceptibility, allows a reliable
assessment of earthquake-triggered landslides hazards. This easy-operation mapping method is expected to be helpful in emer-
gency preparedness planning, as well as in seismic landslide hazard zoning.
Keywords Earthquake-triggered landslides
.
Critical acceleration
.
SEISMIC landslide susceptible
.
Landslide hazard zonation
.
The Mw 6.1 2014 Ludian earthquake
Introduction
Earthquake-triggered landslides can greatly increase the de-
structive impact of earthquakes in mountainous regions. In
many cases, triggered landslides account for a significant pro-
portion of the total earthquake damage because of destruction
to buildings and the impacts landslides pose to lifelines and
transportation networks that are crucial to rescue efforts (Legg
et al. 1982; Bommer et al. 2002;Biondietal.2004;Jibson
2007). Therefore, rapid assessment of the distribution of
earthquake-triggered landslides and the intensity of the
landslides is important for effective mitigation of disasters
(Idriss 1985; Gallen et al. 2016).
In current seismic slope-stability analyses, there are two
basic approaches. One is the stress-strain analysis, which an-
alyzes a complete progressive failure of stress and strain. The
second slope-stability analysis is the conventional pseudo-
static method (Bishop and Morgenstern 1960; Ambraseys
and Sarma 1967; Makdisi and Seed 1979;Seed1979).
Although the pseudo-static analysis is applied more frequent-
ly, it is too crude to predict the behavior of a slope under
seismic loading conditions (Chang et al. 1984). Moreover,
the failure mechanism, or the failure surface geometry, influ-
ences the results of the pseudo-static analysis (Chang et al.
1984; Cetin et al. 2004;Prestietal.2009). For example, the
yield acceleration factor of the rotational logspiral failure
mechanism generally gives a lower value than that of the
plane failure mechanism (Chang et al. 1984).
In order to rapidly assess earthquake-triggered landslides
across a large region, an effective approach mainly depends on
the data needed for evaluation. It is important to consider what
data can be obtained quickly after an earthquake, and also to
* Xiaoli Chen
chenxl@ies.ac.cn
1
Key Lab of Active Tectonics and Volcano, Institute of Geology,
China Earthquake Administration, Beijing 100029, China
2
China Earthquake Networks Center, Beijing 100045, China
3
Sichuan Earthquake Administration, Chengdu 610041, China
Bulletin of Engineering Geology and the Environment
https://doi.org/10.1007/s10064-018-1313-7
@Phil_Robichaud
@deepthiw
@JoseServera