10th Asian Regional Conference of IAEG (2015)

Preliminary Deterministic Seismic Landslide Hazard Maps of Tandikat Area
Ruly RESFIANDHI(1), Galih W. SWANA(1),Imam A. SADISUN(1) and SUMARYONO(2)(1) Bandung Institute of Technology, Indonesia
E-mail: rresfiandhi@gmail.com(2) Centre for Volcanology and Geological Hazard Mitigation, Indonesia

Abstract
The earthquake with magnitude of 7.6 shook the West Sumatra area and cause oflandslides with widespread distribution, therefore needed to conduct a regional analysis ofevaluating seismic landslide hazard. Seismic landslide hazard analyses are used to identify,
evaluate and assess area hazard of landslides caused by earthquake. These analyses are basedon estimates Newmark displacement use deterministic approach with applications ofgeographic information system tools. The deterministic approach generates different levels ofcoseismic landslide displacement for given ground motion and critical acceleration, although
they are ignoring the uncertainty in these conditions. The expressed of displacements that are
predicted via empirical relations equations from combine corresponding of arias intensity andcritical acceleration values. The deterministic analysis applied to the Tandikat Quadrangle in
Padang Pariaman to develop seismic landslide hazard maps. These maps indicate that
deterministic methodology can be applied to define hazard categories.
Keywords: Deterministic, Newmark displacement, seismic landslide, hazard, Tandikat

1. Introduction

2. West Sumatra earthquake

The 2009 West Sumatra earthquake had amagnitude 7.6 (M) and epicenter at 99.8°E, 0.79°S witha depth of 74 km in Mentawai Strait, Indonesia. This
earthquake caused extensive damage and led to 1,117
fatalities, 2 persons missing, 2,902 person injured, and249,833 badly damage homes (Bappenas, 2009). The
earthquake induced 253 landslides in covering an area
1,500 km2 (Ueno and Shiiba, 2013) and directly caused
at least 130 fatalities (Nakano and Chigira, 2014).
After southern Sumatra earthquake, research on
landslide distribution and characteristics was carried out
by various authors (e.g., Wang et al., 2010; Ueno andShiiba, 2013; Faris and Wang, 2014; and Resfiandhi etal., 2014), but, no researchers have mapped andanalyzed coseismic landslide in this area. Several
methods are used to estimate slope stability during
earthquakes, and one of the popular is rigid block(Newmark displacement) analysis which havecommonly use deterministic approach.
The medium rainfall event on September 29-30,
2009 (Faris and Wang, 2014), and provided one of thecontribution to trigger landslides. Landslides
distribution were established by interpretating SPOT
image taken after the event. This research is to knowing
the estimate Newmark displacement from the West
Sumatra earthquake.

Earthquake with 7.6 Mw shook West Sumatra areaon 30 September 2009, at 5:16 pm (fig. 1). McCloskey
et al. (2010) said that the earthquake did not cause
rupture on Sunda megathrust and did not significantly
relax stress accumulation on the Mentawai segment thatindicates tsunamigenic earthquake is unabated. The
focal mechanism appears an oblique thrust event, but,when viewed in the plane of the plate interface as aslightly oblique strike-slip event.
Wiseman et al. (2012) conducted an investigation
withgeodeticdata
andregional
seismic
that earthquake event is an intraslab earthquake which
initiated in the slab subduction process and continuous
until 80 km depth, near the plate interface, andproduces a ruptured primarily downdip and to thesouthwest. Based on aftershock distribution andgeological context favours to north-south rupture aligns
well with the fracture zones on the subducting seafloor.

1

3. Landslides characteristic
West Sumatra earthquake triggered many landslides inlarge scale over a wide area. According to Ueno andShiiba (2013), based on the analysis of satellite imagery
using TerraSAR-X, coverage area 1500 km2 in Padang
Pariaman and Agam District show that 253 landslides

10th Asian Regional Conference of IAEG (2015)previous night medium rainfall intensity had been going(Faris and Wang, 2014).
4. Location
Determined the location in accordance with area
covered of analyzed satellite imagery by Nakano andChigira (2014) which contain large concentrations oftriggered landslides. The rectangle area measured about
94.5 km2 (fig. 1). The area included northern Padang
Pariaman district with flat until moderate slopes areas
and Agam district with steep slopes. This areasurrounded by Maninjau Lake and Tandikat-Singgalang
Volcanoes in northern area and Pariaman City insouthern area.
In 2003, the magnitude 3.3 Agam earthquake
occured in inland and about 26 km east of location area.
That event caused minor damaged homes but theearthquake did not induce landslides.
Fig. 1 The 2009 West Sumatra earthquake. The blue
rectangle indicates the location area. The focal
mechanism (blue-white ‘beach ball’) is in map view
had occured with total 70 million m3 of collapsed
sediment. Large scale landslides (volume of sediment >1 million m3) are concentrated in Padang Pariaman
District which represents 60% of the total volume of
sedimentary material that collapsed.
Based on the field investigation, the most common
types of landslides triggered by the earthquake wereflows and slides of rocks, extending over throughout
area and numbered in the hundreds. More disrupted,
falls and debris flow, steeper, numbering perhaps tens
and occured primarily in the cliff of Maninjau Lake andAnai valley (Photo. 1). The landslides caused moredamage and road closures. The most landslides occured
primarily on pumice tuff material. According Kastowo
et al. (1996), the lithology is hornblende hypersthene
pumiceous tuff (Tephra from Tandikat Volcano)consists of pumice lapilli, commonly diameter ranging
from 2 to 10 cm, which contain hornblende,
hypersthene, and or biotite, moderately compacted,
slightly consolidated, loose, easyly collapsed anderoded. The Pumice layers are easily fall, when erodedby rainfall, V-shaped gullies form, the pores are large
and interconnected, and hence the permeability of thepumice layer is high (Wang et al., 2010). In addition,
there is a hydrothermal alteration process that producesswelling clay effect of clay minerals in the lower part ofpumice (Warmada et al., 2010).
Wang et al. (2010) conducted three types of ringshear tests on pumice tuff in the dry and saturated
conditions, concluded that the slopes with pumice layer
can remain stable in a strong earthquake or during
intense rain, but it becomes very unstable when the two
events occur simultaneously. It is known that moderateintensity rain occurred several hours before theearthquake event occurred, even recorded that in the the2

5. Method
Newmark displacement method is commonly used
to analyzed seismic landslide hazard maps. Newmark(1965) introduced model to assess performance slope toestimate displacement. This model as a rigid block thatmoving downslope when earthquake shaking exceed
the block’s critical acceleration, and continues until thevelocity reach 0. The velocity of rigid block is
integrated to result the cumulative displacement. Used
deterministic approach to used predicting field
displacement for developed seismic landslide hazard
maps.
5.1. The static factor of safety
First, computed the static factor of safety which
derived from an infinite slope approximation. Static
factor of safety can be described aswhere FS is the static factor of safety, c’ is theeffective cohesion, θ’ is effective friction angle, α isslope angle, t is slope normal thickness of failuresurface, m is percentage of failure thickness that issaturated, γ is material unit weight, and γw is unit weightof water. The shear strength values obtained from field
investigation and laboratory test and assigned based on
geologic units, although difficult to characterize on aregional basis (Jibson and Michael, 2009). Tabel 1
show the shear strength in the area. For strength data
available of each geologic unit, were computed average.
Because landslides occured during rainfall conditions,the material on slopes reach saturation. Based on field
investigation, the slope thickness of failure surface
range from 0.6 to 4.4 m, while saturated thickness from0.49 to 1.87 m.

10th Asian Regional Conference of IAEG (2015)

(a)

(b)

(c)

(d)

Photo 1. Landslides triggering by the 2009 West Sumatra earthquake. (a) flow slide, (b) translational slide, (c)debris flow, and (d) rock falls.
We derived slope angle values from 30 m digital
elevation model data, although too many topographic
irregularities are lost (Jibson et al., 1998, 2000), then,generated in the area has slope angle range from 0° to
62°.
By inserting of shear strength, slab and saturated
thickness, and slope angle data, then combining andcalculated to get the static of factor safety, We obtained
values of static factor of safety range from 0.378 to 10.
For further analyzed to model be stable, we assigned
factor of safety greater than 1 (fig. 2).
5.2. The critical acceleration
Newmark (1965) showed that critical acceleration
can be determined as3

where ac is the critical acceleration, FS is static
factor of safety, g is the acceleration of gravity, and α isslope angle. The critical-acceleration map is also
seismic landslide susceptibility map, which portrays ameasure of intrinsic slope properties independent of any
ground-shaking scenario (Jibson et al., 1998, 2000).
Critical acceleration in map area until 0.87 g (fig. 3).
5.3. Arias intensity
Arias (1970) intensity measures the total
acceleration content of strong motion record. With thelack of data to assigned Arias intensity values in map
area, used empirical function from other regions
inevitable. Select empirical relationship based on
similiar geologic and tectonic of the regions where theequation were made. In this analysis, we used Hsieh etal. (2014) equation. Hsieh et al. developed the Arias
intensity equation from subduction earthquakes in10th Asian Regional Conference of IAEG (2015)
Table 1 Shear strength of geologic units
No.

Unit Name

Formationc' (KN/m2)

Ø' (°)

1

Sand/silt

Qhpt

28.34

10.92

2

Mixed layer

Qhpt

11.47

32.53

3

Paleosol

Qpt

10.20

30.89

4

pumice

Qhpt

33.05

23.91

5

Mixed layer

Qhpt

7.65

37.28

6

Paleosol

Qpt

5.10

27.41

7

pumice

Qhpt

5.10

32.96

8

Very fine sand

Qhpt

37.95

22.57

9

Andesite

QTp

11407.03

35.13

10

Andesite

QTp

7194.60

32.48

11

Very coarse sand

Qpt

43.44

25.35

12

Very fine sand

Qpt

28.44

21.72

13

Silt

Qpt

22.75

10.55

14

Lava

Qast

10702.91

36.46

15

Silt

Qast

10.10

10.00

16

mudstone

Qast

22.75

28.91

17

Andesite

Qamj

7072.51

29.38

18

Andesite

Qamj

6861.18

33.48

Fig. 2 The static factor of safety map of location4

10th Asian Regional Conference of IAEG (2015)

Fig. 3 Critical acceleration map of location. This also map of seismic landslide susceptibility
Taiwan based on strong ground motion. Hsieh et al.
defined this equation as

where M is the moment magnitude of earthquake,
R is the hypocentral distance, Vs30 is shear wave
velocity of upper 30 m of material at site, FN and FR are
dummy variables for the fault types (both being 0 for
strike-slip faults, 1, respectively, for normal faults andreverse or reverse oblique faults, and Zt indicates the
subduction zone earthquake type; Zt = 0 for interface
earthquakes, and Zt = 1 for intraslab earthquakes. We
used model based on Wiseman et al. (2012), so themechanism and type of this earthquake appears as a
strike-slip and intraslab, the FN and FR are neglected,
and for Zt value = 1.
Calculated the VS30 values based on Matsuoka et al.
(2005)
methodology,
usedgeomorphologic
classification unit as a proxy. This area has VS30 values
range from 372.1 m/s to 399.9 m/s. According to USGS
site classifications, included in site classes C(760>VS30>360 m/s), were grouped into rock site
category. From calculated those data, then, obtained
values of Arias intensity range from 1.47 m/s to 1.71
m/s (fig. 4).

5

5.4. Newmark displacement
Estimating Newmark displacement method is use
empirical regression equation developed from Hsiehand Lee (2011). Hsieh and Lee used strong motion data
to refine the relationship among critical acceleration,
Arias intensity, and Newmark displacement. The result
analyses is developing a set of empirical equations canbe used in local (Taiwan) and global, also consideredwith soil and rock site empirical equation. Withassuming could be attributable to relatively similar
active orogens or tectonics, the local empirical equation
will be applied for this study. We also used rock site
local empirical equation to compare the result with allsite local empirical equation. Hsieh and Lee defined allsite local empirical equation as

And rock site local empirical equation as

where Dn is Newmark displacement, Ia is Arias
intensity, andis critical acceleration. The goodnessof fit for all site local empirical and rock site local
empirical equation are R2 = 0.837 and R2 = 0.875.

10th Asian Regional Conference of IAEG (2015)

Fig. 4 Contours of Arias intensity map of location. This map generated by Hsieh et al. (2014) equation

Fig. 5 Predicted Newmark displacement map. This map generated by Hsieh and Lee (2011) all site equation.

6

10th Asian Regional Conference of IAEG (2015)

Fig. 6 Predicted Newmark displacement map. This map generated by Hsieh and Lee (2011) rock site local
equation
Estimated Newmark displacement range from 0 to
227.4 cm for all site local equation (fig. 5), and 0 to
257.5 for rock site local equation (fig. 6).
6.

Conclusions

The result declare that relative similiar
displacement between all site and rock site. However,
the rock site result is higher value than the all site result.
This result is appropriate with demonstrated thedeveloped of equation.
The methods ignored the static factor of safety lessthan 1. This constraint in order to be model staticallystable. So, assigning shear strength, material unit
weight data, and determine slab thickness and saturated
slab is subjective process.
Although used simplified approach, this procedure
could be used for analysis seismic landslide hazard if
source of geometry, shear strength data, Vs30 value, are
known. The next step is predicting the probability of
failure using inventories of landslides triggered byearthquake. This is the near future work.
Acknowledgments
The authors are grateful to the Centre for
Volcanology and Geological Hazard Mitigation
provided material shear strengths and VS30 data. Randal
W. Jibson and Chyi-Tyi Lee helpful insights forexpertise regarding the method. Jewgenij Torizin andRandy Kartiko provided helpful insights to modeling.

7

References
Arias, A. (1970): A measure of earthquake intensity. In:
Hansen, R.J. (Ed.), Seismic Design for Nuclear
Power
Plants,Massachusetts
InstituteofTechnology Press, Cambridge, MA, pp. 438–483.
Bappenas. (2009): Rencana Aksi Rehabilitasi dan
Rekonstruksi Wilayah Pascabencana Gempabumi di
Provinsi Sumatra Barat Tahun 2009 – 2011,
Kementerian Negara Perencanaan Pembangunan
Nasional/ Badan Perencanaan Pembangunan
Nasional, 135 p.
Faris, F. and Wang, F. (2014): Investigation of theinitiation mechanism of an earthquake- induced
landslide during rainfall: a case study of theTandikat landslide, West Sumatra, Indonesia,
Geoenvironmental Disaster, 1:4, pp. 1-18.
Hsieh, S.-Y. and Lee, C.-T. (2011): Empiricalestimation of the Newmark displacement from theArias intensity and critical acceleration, Engineering
Geology, 122, pp. 34–42.
Hsieh, P.-S., Lin, P.-S., Cheng, C.-T., and Lee, C.-T.
(2014): New Predictive Equation for Arias Intensityfrom Subduction Earthquakes in Taiwan, Sinotech
Engineering, Vol. 125, pp. 33-43.
Jibson, R.W., Harp, E.L., and Michael, J.A. (1998): A
method for producing digital probabilistic seismic
landslide hazard maps—an example from the Los
Angeles, California, area, U.S. Geological Survey
Open-File Report 98–113, 2 pl., 17 p.
Jibson, R.W., Harp, E.L., and Michael, J.A. (2000): A
method for producing digital probabilistic seismic

10th Asian Regional Conference of IAEG (2015)
landslide hazard maps, Engineering Geology, 58, pp.
271–289.
Jibson, R.W. and Michael, J.A. (2009): Maps showing
seismic landslide hazards in Anchorage, Alaska,
U.S. Geological Survey Scientific Investigations
Map 3077, 2 sheets (scale 1:25, 000), 11 p.
Kastowo, Leo, G.W., Gafoer, S., and Amin, T.C.
(1996): Geological map of the Padang Quadrangle,
Sumatra, Scale 1 : 250,000. Geological Researchand Development Centre.
Matsuoka, M., Wakamatsu, K., Fujimoto, K., andMidorikawa,S.
(2005):
Nationwide
siteamplification zoning using GIS-based Japan
Engineering Geomorphologic Classification Map,
In: 9th International Conference on Structural Safety
and Reliability, Rome, pp. 239-246.
McCloskey, J., Lange, D., Tilmann, F., Nalbant, S.S.,
Bell, A.F., Natawidjaja, D.H., and Rietbrock, A.
(2010): The September 2009 Padang earthquake,
Nature Geoscience,Vol. 3, pp. 70–71.
Nakano, M. and Chigira, M. (2014): Geomorphologicaland Geological Features of the Collapsing
Landslides Induced by the 2009 Padang Earthquake.
Japan Geoscience Union Meeting 2014.
Newmark, N.M. (1965): Effects of earthquakes ondams and embankments. Geotechnique, 15, pp.
139–159.

.

8

Resfiandhi, R., Sumaryono, and Sadisun, I.A. (2014):
Karakteristik
Longsoranyang
Disebabkan
Gempabumi
SumatraBarat
Berdasarkan
Penginderaan Jauh, Proceedings The 43rd IAGI
Annual Convention and Exhibition, Jakarta.
Ueno, T. and Shiiba, S. (2013): Landslides in Padang,West Sumatra, Triggered by the September 2009
Offshore Earthquake, Internasional Journal of
Erosion Control Engineering, Vol. 6, No. 1, pp.3036.
Wang, F., A.N. Wafid, M., and Zhang, F. (2010):
Tandikek and Malalak flowslides triggered by
2009.9.30 M7.6 Sumatra earthquake during rainfall
in Indonesia. Geoscience Rept. Shimane Univ, 29,
pp. 1-10.
Warmada, I.W., Wilopo, W., and Harijoko, A. (2010):
Mineralogical control on landslide in strongly
weathered volcanic terrain. Case study: Padang
Pariaman, West Sumatra, Proceedings of The
International Symposium and 2nd AUN/Seed-Net
Regional Conference on Geo-Disaster Mitigation in
ASEAN 2010.
Wiseman, K., Banerjee, P., Bürgmann, R., Sieh, K.,
Dreger, D.S., and Hermawan I. (2012): Source
model of the 2009Mw 7.6 Padang intraslab
earthquake and its effect on the Sunda megathrust,Geophysical Journal International, 190, pp. 17101722.