Contents lists available at ScienceDirect

Engineering Geology

journal homepage: www.elsevier.com/locate/enggeo

Topographic and near-surface stratigraphic amplification of the seismicresponse of a mountain slope revealed by field monitoring and numericalsimulationsYonghong Luoa,b, Xuanmei Fana,⁎, Runqiu Huanga, Yunsheng Wanga, Ali P. Yunusa,H.B. Havenithba State Key Laboratory of Geo-Hazard Prevention and Geo-Environment Protection, Chengdu University of Technology, Chengdu 610059, Chinab University of Liege, Department of Geology, Georisk and Environment, Belgium

A R T I C L E I N F O

Keywords:Seismic monitoringWenchuan aftershockSeismic amplification2D and 3D numerical simulationsStandard spectral ratio (SSR)

A B S T R A C T

The evaluation of seismic site amplification and its relationship with geological structures play a vital role inearthquake engineering and hazard assessment. This study presents an analysis of topographic and geologic siteamplification effects observed in the Qiaozhuang region, Sichuan Province, China. Seismic recordings at severalmonitoring stations installed on two slopes located at a distance of about 1 km in the study area after the 2008Wenchuan earthquake provide evidence of strong and variable amplifications. To assess the combined effect oftopographic and geological controls in slope response to seismic motions, we built 2D and 3D dynamic numericalmodels using monitoring data as inputs. Four layers with different P-wave velocities, based on geophysicalsurvey in the study area, are considered in the numerical models. Models that only consider topography give anamplification factor of< 3, which is much lower than the amplification factor of 5–6 from the monitoring data,while those models that considered both the topographic variation and four layers agree well with the mon-itoring data. The 3D modeling results show that the subsurface amplification factor is less than that on the slopesurface even at the same elevation. This is also consistent with the monitoring data and further indicates that thecombined topographic and geological amplification effect on the slope surface is more significant than the solegeological amplification effect inside the slope. Our numerical simulation results suggest that it is important toconsider the combined topographic and geological amplification effects in the hazard assessment of seismicallyinduced slope failures.

1. Introduction

The seismic amplification effects of mountain slopes have beenknown for decades (e.g., Boore, 1972; Bouchon, 1973; Davis and West,1973; Çelebi, 1987； Ashford et al., 1997). In one of the first studies,Leonov (1960) reported that topographic amplification effects at thetop of slopes caused many coseismic landslides at ridge crests duringthe Mw 7.4 Khait earthquake of 1949 in northern Tajikistan. Recentcase studies also demonstrate that the seismic amplification effect ofslopes is a common phenomenon (Paolucci, 2002; Lee et al., 2009;Buech et al., 2010; Hough et al., 2010; Barani et al., 2013; Ma et al.,2019).

The main factors that influence the seismic amplification effect are:size and shape of topography (e.g., Boore, 1972; Luo et al., 2013), highimpedance contrast between surface materials and substratum (e.g., Del

Gaudio and Wasowski, 2011), surface morphology and the presence ofa low-velocity layer (e.g., Havenith et al., 2002, 2003; Graizer, 2009),and the combined effect of stratigraphy and topography (Hailemikaelet al., 2016). Geology (rock type, fractures) also contributes to seismicamplification (e.g., Gischig et al., 2015).

Seismic monitoring can provide direct evidence of slope amplifica-tion effects, but most studies comprise short-term (several months toone year) field observations (e.g., Griffiths and Bollinger, 1979; Hartzellet al., 1994, 2014; Caserta et al., 2000; Massa et al., 2010; Gallipoliet al., 2013). Long-term (over years) monitoring of slope seismic re-sponse is relatively scarce. Del Gaudio and Wasowski (2007) and Luoet al. (2014) have done long-term monitoring to study seismic sloperesponses in the same study area as this study. Ambient noise mea-surements may also be used to analyze ground shaking resonance ef-fects (Panzera et al., 2011; Del Gaudio et al., 2013, 2014).

https://doi.org/10.1016/j.enggeo.2020.105607Received 6 December 2018; Received in revised form 21 March 2020; Accepted 22 March 2020

⁎ Corresponding author.E-mail address: fxm_cdut@qq.com (X. Fan).

Engineering Geology 271 (2020) 105607

Available online 23 March 20200013-7952/ © 2020 Elsevier B.V. All rights reserved.

T

Numerical simulation methods have also been applied to under-stand the role of different factors in controlling the seismic amplifica-tion effect, although most models are two-dimensional and lack fieldvalidation (e.g., Geli et al., 1988; Bourdeau and Havenith, 2008;Rizzitano et al., 2014). At the laboratory scale, shaking table tests havebeen used to analyze factors influencing amplification (e.g., Lin andWang, 2006; Xu et al., 2010; Liu et al., 2013; Shinoda et al., 2013).

This study employed field monitoring and numerical modeling tounderstand the role of topography, geological structure, and theircombined effects on slope seismic amplification. Data from long-termfield monitoring stations installed after the 2008 Wenchuan earthquakewere analyzed using the standard spectral ratio (SSR) method. 2D and3D numerical models were created using a UVA (Unmanned AerialVehicle) measured high resolution digital elevation model, and geolo-gical properties were obtained by geophysical survey. The results of thenumerical simulations were validated by the field monitoring data. Thestudy findings may have important implications for hazard assessmentof seismically induced slope failures.

2. Study area

The study area is located in the tectonically active Longmenshanmountain belt in Qingchuan County, Sichuan Province, China (Fig. 1).The Qingchuan-Pingwu (QC-PW) fault, one branch of the Longmenshanfault zone, is composed of three steep NW-dipping sub-faults (Fig. 2)displaying both thrusting and strike-slip deformation mechanisms, with

a displacement of about 0.6 to 1.2 mm/ year (Liu et al., 2009). Mt.Dong is located between the central and southern sub-faults. There is noevidence that any of the sub-faults were activated during the 2008Wenchuan earthquake (Mw 7.9); the nearest coseismic surface rupturewas approximately 30 km southeast of the study area. Within a year ofthe main shock, the study area experienced more than 2000 aftershockswith a maximum magnitude (Ms) of 6.3 (Liu et al., 2009).

Several slope failures that have occurred mountainous regions of thestudy area (Mt. Dong and Weigan hill) since the 2008 Wenchuanearthquake were likely caused by amplified shaking induced by theevent. Aftershocks and ambient noise data recorded after 2008 at Mt.Dong and adjacent slopes have been used to assess local amplificationeffects (Luo et al., 2014; Del Gaudio et al., 2018). However, the data onsubsurface geology were insufficient to make an attempt to assess therespective contribution of topographic and geological surface proper-ties(Del Gaudio et al., 2018).

The bedrock lithology of the study area is mainly composed oflimestone and phyllite that is intensely fragmented due to the long-termtectonic activity (Fig. 2). The local structural setting is complex (DelGaudio et al., 2018). At Mt. Dong, in addition to approximately E-Wstrike-slip faults, limestone strata are affected by NW-NNW and NNEstriking fractures. At Weigan hill, phyllite outcrops are weathered anddisplay sub-vertical schistosity, apparently subparallel to the directionof the ridge (NW).

A geophysical investigation by Luo et al. (2020) showed that thenear-surface rock layer at Mt. Dong vary in thickness from 5 to 25 m,

Fig. 1. (a) Location map showing Sichuan province, China, including the City of Chengdu, and the study area in Qingchuan County. (b) Epicenter of the main shockof the 2008 Wenchuan earthquake (red star), the coseismic fault rupture (bold red lines), and the study area at Qingchuan (green triangle) in the Longmenshanmountain range. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Y. Luo, et al. Engineering Geology 271 (2020) 105607

2

and are characterized by P-wave velocities of 724 to 1024 m/s, whiledeeper limestone and phyllite layer have P-wave velocities of 1470 m/sto 3760 m/s. The variable geological conditions at Mt. Dong andWeigan hill are likely to influence the site amplification effects. A highresolution (1 m) digital elevation model (DEM) obtained by UAV surveywas used to construct 2D and 3D numerical models with homogeneouslithology in order to model the amplification effect of topographyalone. Models with varying subsurface lithology, using informationfrom the geological and geophysical survey, were created to simulatethe combined topographic and geological amplification effect.

3. Monitoring site effects on slopes

Accelerometer records were collated from nine monitoring stationson Mt. Dong and Weigan hill (Fig. 3). Three stations, Q3, Q4, and Q6,were installed inside short tunnels on Mt. Dong between 2009 and2014, at horizontal distances of 6, 15, and 20 m, respectively, from thetunnel entrance (Fig. 3a). Stations Q5, Q10, and Q11 were setup on theslope surface (Fig. 3a). In a previous study, Luo et al. (2014) processedrecordings from Q3 and Q4 in terms of peak ground acceleration, polardiagrams of normalized Arias intensity, the horizontal-to-verticalspectral ratio, and the SSR. This analysis indicated a pronounced di-rectivity to the seismic amplification at Q3 and Q4, with shakingmaxima oriented in an EW direction that is subparallel to the strike ofthe Mt. Dong ridge. In this study, alongside the data for stations Q3 andQ4 from Luo et al. (2014), we used strong motion records from stationsQ3, Q4, Q5, Q10, and Q11. We chose earthquakes with stronger am-plitudes and fewer interference waves for SSR processing, and stationQ3 was selected as the reference station (Fig. 3). Earthquakes recordedat all monitoring stations are listed in Table 1.

At Weigan hill, monitoring stations Q0, Q1, and Q2 were installedon the surface (Fig. 3b), as detailed in Luo et al. (2014). Recordingsfrom the stations were reprocessed to calculate the mean SSR curve. Q0is located on relatively flat loose deposits (alluvial terrace) overlyingphyllite bedrock and is considered the reference station (Fig. 2 and

Fig. 3b). Q0 is still subject to some amplification effects due to its lo-cation on an alluvial terrace, but the amplification occurs only at re-latively high frequencies (around 12 Hz) and has no obvious directionalcharacter, whereas directional resonance occurs at lower frequencies(Del Gaudio et al., 2018). The full criteria used in the selection of re-ference stations are discussed in Luo et al. (2014).

As each recording involves three components (two horizontalcomponents and one vertical component), only the quadratic meanof the horizontal SSR calculated by the formula SSR =((SSREW2 + SSRNS2)/2)1/2, was used for comparing the site amplifica-tions. The mean SSR was applied in this study because each recordinghas a different propagation path to the monitoring site as shown inFig. 4. The peaks of amplifications were determined at the resonancefrequency. An amplification factor of 2.4 was recorded at 6.5–7.0 Hz forQ4 and 5.2 at 9–9.2 Hz for Q5. Amplification factors of 3.8, 6.0, and 5.3were recorded at 2.8–6 Hz for Q6, Q10, and Q11, respectively. Wefound that recorded site amplifications at stations located on the surfaceof the hillslope (i.e., Q5, Q10, and Q11) were higher than those atstations located in the short subsurface tunnels (i.e. Q4 and Q6, Fig. 4);this is consistent with the ambient noise results of Del Gaudio et al.(2018).

At Weigan hill, there were two amplification peaks of 3.5 and 4.6 at2.9 and 4.5 Hz for Q1 and one peak of 2.8 at 3 Hz for Q2 (Fig. 4). Thestronger site amplification effect at Q1 can be attributed to near hilltoptopographic amplification and schistosity in the phyllite bedrock, asexplained by Luo et al. (2014).

Our analysis of the seismic monitoring data recorded at Mt. Dongand Weigan hill shows strong site amplification effects at a frequencyrange of 2–10 Hz along the slope. However, the role of different factorsin controlling the highly variable amplification effects is still unclear, asit is not possible to separate the topographic and geological effectsusing seismic monitoring data (they show the combined effect). Hence,we applied a numerical modeling approach to study the roles of topo-graphy and geology, separately and in combination, in seismic ampli-fication.

Fig. 2. Geological map of the Qiaozhuang area, Qingchuan County. Section 1 is an E-W oriented profile along the ridge on Mt. Dong, and Section 2 is a NE-SWoriented profile across Weigan hill and part of Mt. Dong (modified after Liu et al., 2009).

Y. Luo, et al. Engineering Geology 271 (2020) 105607

3

Fig. 3. Representative seismogram recordings at Mt. Dong and Weigan hill monitoring stations for different aftershocks (see Table 1). (a) Mt. Dong stations foraftershock recordings of ML 2.7 (06-05-2014, ①), ML 3.2 (08-11-2014, ②) and ML 3.8 (08-22-2014, ③). (b)Weigan hill stations for three different aftershock recordingsof ML 3.4 (04-17-2009, ①), ML 3.4 (04-30-2009, ②) and ML 3.1 (05-06-2009, ③) (after Luo et al., 2014).

Y. Luo, et al. Engineering Geology 271 (2020) 105607

4

4. Numerical modeling

Two- and three-dimensional numerical models were constructedusing the high resolution DEM (1 m) and information on the geologicalproperties of different layer obtained by the geophysical survey (Luoet al., 2020). Although two different lithologies, phyllite and limestone,outcrop in the study area (Fig. 2), the Vp values of near-surface layersare similar. This is probably because the Vp parameter depends on thedegree of weathering and the density of rock mass fractures (Lee andYoon (2017) and Nourani et al. (2017)). For simplification purposes,the numerical simulations in this study do not distinguish between thetwo lithologies.

4.1. 2D models

2D models were constructed using the Universal Distinct ElementCode developed by Itasca (UDEC, version 4.0.1). UDEC can simulate thequasi-static or dynamic response of media containing multiple inter-secting joint structures to loading (UDEC Manual, 2006). The hillslopeis represented as an assemblage of rigid discrete blocks, while dis-continuities are introduced as boundary conditions between blocks. Themodels allow simulation of seismic energy propagation in differentlayers with various dynamic parameters (e.g., acceleration, velocity,displacement, etc.).

Seven 2D models were created, as listed in Table 2. The thickness ofsubsurface layers was derived from geophysical survey results (Luoet al., 2020), and material properties were estimated using measuredseismic characteristics (P-wave velocity, Vp and S-wave velocity, Vs)and information from previous studies (e.g., Sheng and Wang, 2009; Xuet al., 2009). The three-layer models for Mt. Dong and Weigan hill areshown in Fig. 5.

The cell size of the finite difference (FD) zones in the models was setas 10 × 10 m in order to meet the criterion that it should be less than 1/10 to 1/8 of the minimum wavelength of the input seismic wave, asproposed by Kuhlemeyer and Lysmer (1973). For the minimum velocity

(Vs) of 727 m/s, the 10 × 10 m FD zones can correctly propagateseismic energy up to the frequency of 11 Hz. Natural seismic waveswith a duration of 10.2 s were used as the input (from an earthquake ofML3.8 on May 30, 2010). The spectrum of the seismic wave shows largeamplitudes over a wide range of frequency, especially between 2.5 and5.5 Hz and between 8 and 15 Hz (Fig. 6).

4.2. 3D models

To simulate 3D topographic amplification at Mt. Dong, 3D modelswere built using three-dimensional Distinct Element Code (3DEC, ver-sion 5.0), discontinuum numerical modeling software based on thedistinct element method. Four 3D models were designed (Models 9–12as shown in Fig. 7a-d), with the same thickness and material propertiesfor the different layers as in the 2D models (Table 2). The length (Xdirection) and width (Y direction) of the 3D model were set at 600 m,with height (Z direction) ranging from 100 to 320 m. We requested themodels to record amplifications at twelve locations, marked as receiversR18-R29 in Fig. 7d. Eleven receivers were located on the hillslopesurface and three were below the surface of the model, one as the re-ference (R18) and two (R22(In) and R27(In)) located at the bottom ofthe horizontal tunnels at stations Q4 and Q6 (Fig. 3). Two of the re-ceivers were set to coincide with the location of monitoring stations forcomparison purposes.

Three-dimensional meshes were constructed so that each of themodels were filled with tetrahedral-shaped FD zones with a cell size of40 m. As for the 2D case, the models adhere to the criterion that the cellsize is smaller than 1/8 to 1/10 of the minimum wave length of theinput seismic wave (Kuhlemeyer and Lysmer, 1973). FD zones at thebase can, in theory, correctly propagate seismic energy up to 3–9 Hz tooverlying layers with lower velocities.

Free-field conditions were set to minimize wave reflections alonglateral boundaries using free-field boundary blocks and a viewing gap.Nonreflecting boundaries were applied at the bottom to prevent re-flection of outward-propagating waves back into the model. Gravity

Table 1List of earthquakes recorded at monitoring stations Q3, Q4, Q5, Q6, Q10, and Q11 (cf. Fig. 3a). Source parameters were derived from the China Earthquake DataCenter.

No. Magnitude Date Lat (°) Long (°) Hypocenter depth (km) Distance (km) Azimuth (°)

Earthquakes recorded at stations Q3, Q4, and Q61 ML5.2 09-19-2009 32.90 105.56 8 45.54 40.302 ML3.1 09-06-2009 32.52 105.14 17 12.37 232.23 ML2.7 09-07-2009 32.49 105.14 17 14.61 221.84 ML2.4 09-07-2009 32.59 105.31 16 6.18 87.95 ML3.3 09-12-2009 32.49 105.13 23 15.25 224.56 ML2.8 09-19-2009 32.59 105.32 5 7.12 88.27 ML2.8 09-22-2009 32.47 105.11 16 18.15 223.88 ML2.3 09–24–2009 32.55 105.26 15 4.48 160.59 ML4.1 10-14-2009 32.58 105.37 23 11.83 94.310 ML3.8 10-18-2009 32.43 104.99 10 29.57 233.711 ML2.9 10-27-2009 32.58 105.36 16 10.89 94.612 ML3.1 11-23-2009 32.56 105.28 18 4.59 132.713 ML3.4 12-08-2009 32.51 105.09 18 16.83 239.014 ML3.3_1 01-24-2010 32.61 105.35 22 10.22 76.115 ML3.3_2 01-24-2010 32.56 105.26 17 3.45 154.316 ML3.0 02-06-2010 32.59 105.29 17 4.31 87.017 ML3.9 02-15-2010 32.29 104.88 22 11.47 211.518 ML3.8 03-10-2010 32.56 105.27 8 3.95 141.919 ML4.3 04-28-2010 32.52 105.12 20 13.86 237.020 ML3.8 05-30-2010 32.54 105.28 20 6.31 147.721 ML3.9 06-26-2010 32.64 105.37 16 13.13 63.9

Earthquakes recorded at stations Q3, Q4, Q5, Q10, and Q111 ML2.7 06-05-2014 32.60 105.24 21 1.11 0.02 ML3.2 08-11-2014 32.57 105.15 14 8.72 255.33 ML2.2 08-12-2014 32.59 105.25 8 0.94 904 ML3.8 08-22-2014 32.56 105.27 19 2.81 90

Y. Luo, et al. Engineering Geology 271 (2020) 105607

5

Fig. 4. Mean standard spectral ratio (SSR) for Q4, Q5, Q6, Q10, Q11, Q1, and Q2 at Mt. Dong (Q3 is the reference) and Weigan hill (Q0 is the reference). The boldblack line shows the mean SSR, and the gray line shows the quadratic mean of the horizontal SSR of each earthquake.

Table 2Summary of parameters and material properties used in the 2D numerical models.

Model Type Section Material† Thickness of layers (m)

Model 1 Three layers E-W (Mt. Dong) Mat_1*, Mat_2, Mat_3, Mat_4 25, 10, 20Model 2 Homogeneous E-W (Mt. Dong) Mat_1* /Model 3 One layer E-W (Mt. Dong) Mat_1*,Mat_2 55Model 4 Two layers E-W (Mt. Dong) Mat_1*,Mat_2,Mat_3 35, 20Model 5 Three layers NE-SW (Mt. Dong- Weigan hill) Mat_1*,Mat_2,Mat_3, Mat_4 25, 10, 20Model 6 Homogeneous NE-SW (Mt. Dong- Weigan hill) Mat_1* /Model 7 One layer NE-SW (Mt. Dong- Weigan hill) Mat_1*,Mat_2 55Model 8 Two layers NE-SW (Mt. Dong- Weigan hill) Mat_1*,Mat_2,Mat_3 35, 20

Material properties used in the models

Material† Density (kg/m3) P-wave velocity, Vp (m/s) S-wave velocity (m/s), Vs‡ Poisson's ratio, v

Mat_1* 2600 5000 2886 0.25Mat_2 2500 3148.5 1683 0.30Mat_3 2400 2448 1233 0.33Mat_4 2200 1514 727 0.35

† Mat_1* is the underlying homogenous bedrock; Mat_4 to Mat_2 represent layers from the surface to the interior.‡ Vs was calculated using Vs = ((ν-0.5)/(ν-1))1/2 × Vp.

Y. Luo, et al. Engineering Geology 271 (2020) 105607

6

and initial stress (major principal stress/minor principal stress = 3/1)(Liu et al., 2009) were applied to the model and preliminarily cycled toobtain the initial stress state.

Because of the nonreflecting boundary, the velocity or accelerationinput signal is nullified at the bottom, and we therefore converted thevelocity wave to a stress wave as the input signal using the followingformulas:

= C V2 ( )n n n (4-1)

= C V2 ( )s s s (4-2)

where σn and σs are the normal stress and shear stress, respectively; ρ isdensity, Cn and Cs represent the P- and S-wave velocity; and Vn and Vs

are the vertical and horizontal velocity, respectively. A three-compo-nent stress wave was used as the seismic signal input along the base ofthe 3D model, as in the 2D simulation. To reduce the impact of theinput signal on the 3D simulation results, we applied the same ampli-tude stress wave in the horizontal directions of X and Y, and half theamplitude for the normal stress in the Z direction.

All 2D and 3D numerical simulations were carried out with purelyelastic models, using a frequency-independent damping value of 0.025

Fig. 5. Three-layer models used in the 2D numerical modeling. (a) Section 1, oriented E-W along the ridge of Mt. Dong. (b) Section 2, oriented NE-SW across Weiganhill and part of Mt. Dong. See Fig. 2 for section locations. R1 to R17 denote receivers and mark locations where we request the models to record amplifications. Fromsurface to interior, the three layers have thicknesses of 25, 10, and 20 m and comprise materials Mat_4, Mat_3, and Mat_2, respectively. Mat_1* represents theunderlying bedrock and is used for the homogeneous models.

Fig. 6. Natural seismic wave used as input in 2D modeling. (a) NS horizontal component of the natural seismic wave of a ML3.8 earthquake recorded at station Q4(May 30, 2010), and (b) its Fourier spectrum. The solid black line in (b) represents the mean spectrum, and the dashed lines represent the confidence intervals.

Y. Luo, et al. Engineering Geology 271 (2020) 105607

7

for the geological materials (Biggs, 1964; 3DEC 5.0 Manual), which wasapplied to model the effect of material viscosity and related wave at-tenuation. We applied the classic SSR approach to process the data (seethe detailed description in Borcherdt, 1970), which assumes that thereference station is subject to the same seismic source and propagationeffects as other nearby stations. Thus, the Fourier amplitude spectralratio expresses the dynamic effect of a specific site.

5. Simulation results

5.1. Topographic amplification effects

Homogeneous models were used to simulate the topographic effectsof seismic amplification. The 2D simulation results for homogeneousModels 2 and 6 are shown in Fig. 8a and b. The mean SSR curve forModel 2 (Fig. 8a) shows a distinct amplification in the frequency range5–7 Hz, but the peak is below 2 (maximum SSR of 1.75 at R5). Moreminor amplifications are also observed at frequency ranges of 1–2,8–10, and 15–18 Hz. At the foot of the slope (R2), SSR is close to 1. Thelargest amplification is not located at the mountain top (R11), but isobserved mid-slope, near a break of slope (R5). The results indicate thattopography alone only produces low amplification effects, and thatchanges in slope seem to affect the variability of the topographic am-plification.

The SSR analysis of Model 6 (Fig. 8b) shows amplification peaks at3.5 Hz and 4.5 Hz of below 3 at the hilltop receivers (maximum SSR of

2.6 at R17 on Weigan hill and maximum SSR of 1.9 at R12 on Mt.Dong), and at 10 Hz of just above 3 (R17 at Weigan hill). The topo-graphy of Section 2 features a flat region in the middle (urban area), amountain (Mt. Dong) in the NE and a smaller hill (Weigan) in the SW(Fig. 5). The amplification at resonance frequency 3.5 Hz is likelycaused by the lower topography of Weigan hill, and that at 4.5 Hz bythe higher elevation of Mt. Dong. The significant peak amplificationfactor at 10.5 Hz is likely caused by the aggregate topographic relief ofSection 2.

For the homogenous 3D model (Model 9), the value at R18 (65 mbelow the surface) was multiplied by a factor two as a reference for theSSR calculation. The mean of the horizontal components was calculatedusing the same formula as for the 2D analysis. As shown in Fig. 8c, inthe low frequency range (< 10 Hz), there are two resonance fre-quencies, at 5 and 8 Hz, with R25 and R22 exhibiting the largest am-plifications. In addition, topographic amplification is greater at theupper part of the mountain slope (e.g., R29) than at the toe of the slope(R19, R20), but the site effects do not increase linearly. Like the 2Dsimulation, the 3D simulation shows that topography alone only con-tributes minor amplifications (< 3), and along slope site effects areinfluenced by local variations in topography and morphology (such asthe slope convexity at R22). The topographic amplification obtained bythe 3D model (Model 9) is slightly greater than that of the 2D models(maximum SSR < 2), probably because the lateral crest morphology ofthe 3D model produces polarization effects in the horizontal direction,which enhances topographic amplification.

Fig. 7. 3D models for Mt. Dong. (a) Model 9, homogeneous; (b) Model 10, one layer; (c)Model 11, two layers; and (d) Model 12, three layers. In (d), yellow starsindicate receiver locations; 11 are at the surface, and 3 are subsurface. R18(In) is an internal receiver located 65 m below the surface, which is used as the reference;internal receivers (In) at R22 and R27 are located in horizontal tunnels at stations Q4 and Q6, as indicated in Fig. 3. Material properties are detailed in Table 2. (Forinterpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Y. Luo, et al. Engineering Geology 271 (2020) 105607

8

5.2. Geological amplification effects

5.2.1. 2D numerical simulation results.The 2D numerical simulations with one layer (Models 3 and 7), two

layers (Models 4 and 8), and three-layers (Models 1 and 5) are shown inFig. 9. The three-layer models for both Mt. Dong (Fig. 9a-d) and Weiganhill (Fig. 9e-f) show the largest amplification effects, and amplificationappears to increase with the number of near-surface layers. The pre-sence of Mat_4 in the three-layer Model 1 (based on Section 1) causes apeak amplification of approximately 8 at 5.5 Hz at R4, which is muchlarger than the amplifications in Models 3 and 4. Amplification valuesfor the three-layer Model 1 of the Mt. Dong (receivers R4, R10, andR11) are in the frequency range 5–6 Hz, which is consistent with theresonance frequency shown by the homogeneous Model 2. While loweramplification values (1.4 to 1.5) are observed at the toe of the slope(R2), interestingly, we found that the maximum amplification was notat/near the top of Mt. Dong (R11), but at a convex slope (R4). Thisindicates that the amplification effect does not increase linearly withelevation and that local morphology also plays an important role.

The simulation results for Section 2 show that receivers at the upperpart of the slope (R12 and R17) have strong amplifications at a fre-quency of 3–4 Hz, with a maximum value of 6.6 for R17 on the top ofWeigan hill (Fig. 9e-f). A lower amplification factor (2.2) is observednear the foot of the slope at R15. The resonance frequency of layeredmodels (Models 5, 7, and 8) is consistent with the homogeneous Model6. Additionally, in the high-frequency range of 9.5–15 Hz, the observedamplification effect is also high, with a maximum value of 5–7.

5.2.2. 3D numerical simulation results.The results of the 3D simulations are shown in Fig. 10; as with the

2D simulations, increasing the number of layers significantly enhances

the amplification effects. However, unlike the 2D case, the 3D simula-tions show two peak frequencies, at approximately 5 Hz at R22 (breakof slope) and 8 Hz at R29 (near the hilltop), in the three-layer Model 12.This difference is probably caused by the combined effects of 3D surfacemorphology and subsurface layers. At the foot of the mountain, re-ceivers R19 and R20 exhibit a slight amplification (less than 4 and at alower frequency). Two internal receivers (R22(In) and R27(In)) haveamplification factors of 2.1 and 4.0, which are much lower than those atthe slope surface (6.2 at R22(S) and 6.5 at R27(S)). This agrees wellwith the field data obtained from monitoring stations inside the hor-izontal tunnels (see Fig. 3).

6. Discussion and conclusions

Field monitoring can provide valuable data for study slope seismicresponse. With the help of numerical simulations, the topographic,geological and their combined amplification effects can be studied.However, lack of long-term monitoring data hampers a better under-standing of slope seismic response (Gischig et al., 2015). Advancednumerical modeling methods require high resolution and good qualityinput data to guarantee realistic outputs (Wasowski et al., 2011). Toovercome this challenge, this study has conducted a more than fiveyears continuous monitoring in the Mt.Dong, and obtained high re-solution topography by UAV survey. Different weathering subsurfacebedrock (limestone) was investigated by the geophysical survey (Luoet al., 2020), providing reliable input data to numerical simulations.

Few studies have done 3D numerical simulations with hetero-geneous models (Glinsky et al., 2019). Paolucci et al. (1999) applied 3Dnumerical simulations of an instrumented hill site to study amplifica-tion of seismic waves in the presence of topographic irregularities. Theyfound observed amplification is significantly higher than that obtained

Fig. 8. Topographic amplification simulation results for homogenous models. (a) 2D simulation results for Model 2 (Section 1, Mt. Dong). (b) 2D simulation resultsfor Model 6 (Section 2, Mt. Dong-Weigan hill). (c) 3D simulation results for Model 9. (d) Simplified surface morphology of Mt. Dong showing receiver locations.

Y. Luo, et al. Engineering Geology 271 (2020) 105607

9

from a homogeneous 3D model, suggesting that local responses isgoverned by soil heterogeneities. They further introduced non-homogeneous soil material under one of the recording stations into themodel, but the numerical results are not significantly improved. Theirresults of the homogeneous 3D model agree well with our finding thattopography alone only produces low amplification effects. However,our three-layer 3D model considering different subsurface rock prop-erties significantly improved the results compared to the homogenousmodel (Fig. 11). The reason for this difference might be that we usedfield measured properties (P-wave velocity) to present different sub-surface layers in the heterogenous 3D model, while the 3D model ofPaolucci et al. (1999) has scarce information on the 3D underground

geological structure. We also observed a large number of rock slopefailures during the Wenchuan earthquake, suggesting that rockweathering heterogeneities may govern the local slope seismic re-sponse.

In this study, we considered different lithological layers as one ofthe geological factors that influence seismic amplification. We areaware that other geological structural factors that have not been in-vestigated here can also contribute to the variability of site amplifica-tions, especially to wave polarization effects (as pointed out by DelGaudio et al., 2018). Nevertheless, our study demonstrates some in-teresting findings that the strongest amplification effect is produced byincluding a relatively thin low-velocity layer (Mat_4 in Table 2) and by

Fig. 9. 2D numerical simulation results for1-, 2-, and 3-layer models. (a)-(f) Standard spectral ratio (SSR) curves for different receivers (R2, R4, R10, R11, R12, andR17) along Sections 1 and 2. See Fig. 5 for locations.

Y. Luo, et al. Engineering Geology 271 (2020) 105607

10

comparatively small surface convexities in the models (near receiversR4 and R5 in 2D simulations, and R22 in 3D, see Figs. 9 and 10).

The numerical simulation results agree well with the field mon-itoring data (Fig. 11). Fig. 11a and b shows that the amplificationfactors for homogeneous models are much smaller than that for datarecorded at monitoring stations Q10 and Q11. Amplifications from thethree-layer models agree with the field data (Fig. 11c-f), although en-ergy is concentrated over a narrower frequency range in the numericalsimulation results. This is probably due to: (1) only a part of Mt. Dongwas modeled, and thus the entire spectrum of topographic amplificationcould not be simulated; (2) the geometric details of the subsurfacelayers may not be correctly represented, as we assumed each layer wasof a homogeneous thickness.

The three-layer 3D model (Model 12) showed close accordancebetween amplification levels at the two internal receivers (R22(In) andR27(In)) and field observations at stations Q4 and Q6 in the tunnels,which are lower than amplifications at the slope surface receivers(R22(S) and R27(S), see Fig. 11g-h). It is worth mentioning that themonitoring data from another site, Mt. Dagang slope along the Daduriver, did not show a significant decrease of the amplification effectfrom outside to inside of the instrumented tunnel, see Del Gaudio et al.(2019). This is probably because that our monitored site is close to theQC-PW fault, causing more intensely fractured and weathered lime-stone compared to the granite at Mt. Dagang. Geophysical survey alsoshowed that there are multi-reflecting interfaces of the bedrock at Mt.Dong (Luo et al., 2020), which may decrease the resonance effect at theinternal receivers (R22(In) and R27(In)).

Furthermore, slope surface cracking and small slope failures (asdescribed by Luo et al., 2014) can be explained by high amplificationeffects at monitoring stations Q5 (corresponding to the locations ofreceivers R6 and R24 in the numerical models), Q10 (R8, R26), andQ11 (R10, R28). Our results have an important implication for hazardassessment of seismically induced slope failures.

This study presents valuable field monitoring data of slope seismicresponses to aftershocks of the 2008 Wenchuan earthquake. Numericalsimulation results are compared with the results of field monitoringdata analysis. The following conclusions can be drawn from this study:

(1) Field monitoring data analysis provides evidence for highly variableamplification effects at different locations along slope, and a higherseismic response of the slope surface in comparison with the sub-surface rock mass. This explains the large number of shallow slopefailures during earthquakes.

(2) 2D and 3D numerical simulation results show that the strongestamplification effects normally appear at breaks of slope (convexslope) where the slope angle changes, at the top of slopes or ridgecrests, and at steep slopes.

(3) The numerical simulation results reveal that the topography am-plification factor alone is less than 3 at 3–8 Hz, much lower thanthat obtained from the field monitoring data. When three subsur-face layers are considered (three-layer models), the 3D simulationsproduce amplification factors that agree well with the field mon-itoring data. This indicates that the combination of topographic andgeologic amplification effects is significant.

Fig. 10. 3D simulation results for Models 10–12 (1-, 2-, and 3-layer models) on Mt. Dong.

Y. Luo, et al. Engineering Geology 271 (2020) 105607

11

Fig. 11. Comparison of field-measured site amplification factors with results of 2D and 3D numerical simulation. (a) and (b) Homogeneous model (topography only)at monitoring stations Q10 and Q11; (c) – (f) Three-layer model at stations Q2, Q5, Q10, and Q11; (g) and (h) 3D simulation (three-layer Model 12) results at stationsQ4 and Q6, using surface and internal receivers (R22 and R27). In all diagrams, the bold black line represents field recordings, the finer black line represents results of3D numerical modeling, and the dashed line 2D modeling.

Y. Luo, et al. Engineering Geology 271 (2020) 105607

12

Declaration of Competing Interest

The authors declared that they have no conflicts of interest to thiswork.

We declare that we do not have any commercial or associative in-terest that represents a conflict of interest in connection with the worksubmitted.

Acknowledgments

This study is supported by the Funds for Creative Research Groupsof China (Grant No. 41521002), the National Key Research andDevelopment Program of China (Grant No. 2017YFC1501000), theOpen Fund of the State Key Laboratory of Geo-hazard Prevention andGeo-environment Protection (under Project No. SKLGP2019K024), theNational Natural Science Foundation for the Youth (Grant No.41202211), the State Key Laboratory of Geo-hazard Prevention andGeo-environment Protection Independent (SKLGP2019Z002), and theconstruction plan of Double First-Class of Chengdu University ofTechnology. We thank Wang Fuhai, Liu Yong, Yan Song, and Wang Bofor long-term field monitoring and geological survey. We also thank OuJianfeng and Dr. Zhao Bo for helping to improve some of the figures.We sincerely thank the two anonymous reviewers, the editor Dr. JanuszWasowski, and Dr. Niek Rengers for their insightful comments.

References

Ashford, S.A., Sitar, N., Lysmer, J., Deng, N., 1997. Topographic effects on the seismicresponse of steep slopes. Bull. Seismol. Soc. Am. 87 (3), 701–709.

Barani, S., Massa, M., Lovati, S., Ferretti, G., 2013. Topographic effects in probabilisticseismic hazard analysis: the case of Narni, Central Italy. In: WCEE Proceedings,Lisboa, September 2013.

Biggs, J.M., 1964. Introduction to Structural Dynamics. McGraw-Hill, New York.Boore, D.M., 1972. A note on the effect of simple topography on seismic SH waves. Bull.

Seismol. Soc. Am. 62 (1), 275–284.Borcherdt, R.D., 1970. Effects of local geology on ground motion near San Francisco Bay.

Bull. Seismol. Soc. Am. 60 (1), 29–61.Bouchon, M., 1973. Effect of topography on surface motion. Bull. Seismol. Soc. Am. 63

(2), 615–632.Bourdeau, C., Havenith, H.B., 2008. Site effects modelling applied to the slope affected by

the Suusamyr earthquake (Kyrgyzstan, 1992). Eng. Geol. 97 (3–4), 126–145.Buech, F., Davies, T.R., Pettinga, J.R., 2010. The little red hill seismic experimental study:

topographic effects on ground motion at a bedrock-dominated mountain edifice. Bull.Seismol. Soc. Am. 100 (5A), 2219–2229.

Caserta, A., Bellucci, F., Cultrera, G., Donati, S., Marra, F., Mele, G., Rovelli, A., 2000.Study of site effects in the area of Nocera Umbra (Central Italy) during the 1997Umbria-Marche seismic sequence. J. Seismol. 4 (4), 555–565.

Çelebi, M., 1987. Topographical and geological amplifications determined from strong-motion and aftershock records of the 3 March 1985 Chile earthquake. Bull. Seismol.Soc. Am. 77 (4), 1147–1167.

Davis, L.L., West, L.R., 1973. Observed effects of topography on ground motion. Bull.Seismol. Soc. Am. 63 (1), 283–298.

Del Gaudio, V., Wasowski, J., 2007. Directivity of slope dynamic response to seismicshaking. Geophys. Res. Lett. 34 (12).

Del Gaudio, V., Wasowski, J., 2011. Advances and problems in understanding the seismicresponse of potentially unstable slopes. Eng. Geol. 122, 73–83.

Del Gaudio, V., Wasowski, J., Muscillo, M., 2013. New developments in ambient noiseanalysis to characterise the seismic response of landslide-prone slopes. Nat. HazardsEarth Syst. Sci. 13 (8), 2075–2087.

Del Gaudio, V., Muscillo, S., Wasowski, J., 2014. What we can learn about slope responseto earthquakes from ambient noise analysis: an overview. Eng. Geol. 182, 182–200.

Del Gaudio, V., Luo, Y., Wang, Y., Wasowski, J., 2018. Using ambient noise to char-acterise seismic slope response: the case of Qiaozhuang peri-urban hillslopes(Sichuan, China). Eng. Geol. 246, 374–390.

Del Gaudio, V., Zhao, B., Luo, Y., Wang, Y., Wasowski, J., 2019. Seismic response of steepslopes inferred from ambient noise and accelerometer recordings: the case of DaduRiver valley, China. Eng. Geol. 259, 105197.

Gallipoli, M.R., Bianca, M., Mucciarelli, M., Parolai, S., Picozzi, M., 2013. Topographicversus stratigraphic amplification: mismatch between code provisions and observa-tions during the L’Aquila (Italy, 2009) sequence. Bull. Earthq. Eng. 11 (5),1325–1336.

Geli, L., Bard, P.Y., Jullien, B., 1988. The effect of topography on earthquake groundmotion: a review and new results. Bull. Seismol. Soc. Am. 78 (1), 42–63.

Gischig, V.S., Eberhardt, E., Moore, J.R., Hungr, O., 2015. On the seismic response ofdeep-seated rock slope instabilities-Insights from numerical modeling. Eng. Geol.193, 1–18.

Glinsky, N., Bertrand, E., Régnier, J., 2019. Numerical simulation of topographical andgeological site effects. Applications to canonical topographies and Rognes hill, SouthEast France. Soil Dyn. Earthq. Eng. 116, 620–636.

Graizer, V., 2009. Low-velocity zone and topography as a source of site amplificationeffect on Tarzana hill, California. Soil Dyn. Earthq. Eng. 29 (2), 324–332.

Griffiths, D.W., Bollinger, G.A., 1979. The effect of Appalachian Mountain topography onseismic waves. Bull. Seismol. Soc. Am. 69 (4), 1081–1105.

Hailemikael, S., Lenti, L., Martino, S., Paciello, A., Mugnozza, G.S., 2016. Ground-motionamplification at the Colle di Roio ridge, Central Italy: a combined effect of strati-graphy and topography. Geophys. J. Int. 206 (1), 1–18.

Hartzell, S.H., Carver, D.L., King, K.W., 1994. Initial investigation of site and topographiceffects at Robinwood Ridge, California. Bull. Seismol. Soc. Am. 84 (5), 1336–1349.

Hartzell, S., Meremonte, M., Ramírez-Guzmán, L., McNamara, D., 2014. Ground motionin the presence of complex topography: earthquake and ambient noise sources. Bull.Seismol. Soc. Am. 104 (1), 451–466.

Havenith, H.B., Jongmans, D., Faccioli, E., Abdrakhmatov, K., Bard, P.-Y., 2002. Siteeffect analysis around the seismically induced Ananevo rockslide, Kyrgyzstan. Bull.Seismol. Soc. Am. 92 (8), 3190–3209.

Havenith, H.B., Vanini, M., Jongmans, D., Faccioli, E., 2003. Initiation of earthquake-induced slope failure: influence of topographical and other site specific amplificationeffects. J. Seismol. 7 (3), 397–412.

Hough, S.E., Altidor, J.R., Anglade, D., Given, D., Janvier, M.G., Maharrey, J.Z.,Meremonte, M., Mildor, B.S.-L., Prepetit, C., Yong, A., 2010. Localized damagecaused by topographic amplification during the 2010 M 7.0 Haiti earthquake. Nat.Geosci. 3 (11), 778.

Kuhlemeyer, R. L., J. Lysmer., 1973. Finite element method accuracy for wave propa-gation problems. Journal of Soil Mechanics & Foundations Div. 99, (Tech Rpt).

Lee, J.S., Yoon, H.K., 2017. Characterization of rock weathering using elastic waves: aLaboratory-scale experimental study. J. Appl. Geophys. 140, 24–33.

Lee, S.J., Chan, Y.C., Komatitsch, D., Huang, B.S., Tromp, J., 2009. Effects of realisticsurface topography on seismic ground motion in the Yangminshan region of Taiwanbased upon the spectral-element method and LiDAR DTM. Bull. Seismol. Soc. Am. 99(2A), 681–693.

Leonov, N., 1960. The Khait, 1949 earthquake and geological conditions of its origin. In:Proceedings of Academy of Sciences of the USSR. Geophys. Series 3. pp. 409–424.

Lin, M.L., Wang, K.L., 2006. Seismic slope behavior in a large-scale shaking table modeltest. Eng. Geol. 86 (2–3), 118–133.

Liu, G., Li, Y., Chen, J., Xie, L., 2009. The Problem of Earthquake Fault about QiaozhuangTown in the Qingchuan County after Wenchuan Earthquake. J. Mt. Sci. 4, 17 (inChinese).

Liu, H., Xu, Q., Li, Y., Fan, X., 2013. Response of high-strength rock slope to seismic wavesin a shaking table test. Bull. Seismol. Soc. Am. 103 (6), 3012–3025.

Luo, Y., Wang, Y., Fu, R., Liu, J., 2013. Study on mountain slopes topographic effectinduced by Wenchuan earthquake. Global View Eng. Geol. Environ. 73–80.

Luo, Y., Del Gaudio, V., Huang, R., Wang, Y., Wasowski, J., 2014. Evidence of hillslopedirectional amplification from accelerometer recordings at Qiaozhuang (Sichuan-China). Eng. Geol. 183, 193–207.

Luo, Y., Lei, W., Wang, Y., Zhu, X., Ou, J., 2020. Revealing the geological materialsproperties by a shallow seismic method for investigating slope site effects: a casestudy in Qiaozhuang town, Qingchuan County. Arab. J. Geosci (accepted).

Ma, N., Wang, G., Kamai, T., Doi, I., Chigira, M., 2019. Amplification of seismic responseof a large deep-seated landslide in Tokushima, Japan. Eng. Geol. 249, 218–234.

Manual, U.D.E.C., 2006. Dimensional Distinct Element Code Manual version 4.0.1. ItascaConsulting Group,Inc.

Massa, M., Lovati, S., D’Alema, E., Ferretti, G., Bakavoli, M., 2010. An experimental ap-proach for estimating seismic amplification effects at the top of a ridge, and theimplication for ground-motion predictions: the case of Narni, Central Italy. Bull.Seismol. Soc. Am. 100 (6), 3020–3034.

Nourani, M.H., Moghadder, M.T., Safari, M., 2017. Classification and assessment of rockmass parameters in Choghart iron mine using P-wave velocity. J. Rock Mech.Geotech. Eng. 9 (2), 318–328.

Panzera, F., Lombardo, G., Rigano, R., 2011. Evidence of topographic effects through theanalysis of ambient noise measurements. Seismol. Res. Lett. 82 (3), 413–419.

Paolucci, R., 2002. Amplification of earthquake ground motion by steep topographic ir-regularities. Earthq. Eng. Struct. Dyn. 31 (10), 1831–1853.

Paolucci, R., Faccioli, E., Maggio, F., 1999. 3D response analysis of an instrumented hill atMatsuzaki, Japan, by a spectral method. J. Seismol. 3 (2), 191–209.

Rizzitano, S., Cascone, E., Biondi, G., 2014. Coupling of topographic and stratigraphiceffects on seismic response of slopes through 2D linear and equivalent linear analyses.Soil Dyn. Earthq. Eng. 67, 66–84.

Sheng, J., Wang, Z., 2009. Emergency Governance Project Investigation Report of WeiganHill Unstable Slope in Qingchuan County of Sichuan Province. (in Chinese).

Shinoda, M., Nakajima, S., Nakamura, H., Kawai, T., Nakamura, S., 2013. Shaking tabletest of large-scaled slope model subjected to horizontal and vertical seismic loadingusing E-Defense. In: Proceedings of the 18th International Conference on SoilMechanics and Geotechnical Engineering, pp. 1603–1606.

Wasowski, J., Keefer, D.K., Lee, C.T., 2011. Toward the next generation of research onearthquake-induced landslides: current issues and future challenges. Eng. Geol. 122(1–2), 1–8.

Xu, Q., Zhang, Y., Feng, W., 2009. Emergency Governance Project Investigation Report ofMt. Dong Unstable slope in Qingchuan County of Sichuan Province. (in Chinese).

Xu, Q., Liu, H., Zou, W., Fan, X., Chen, J., 2010. Large-scale shaking table test study ofacceleration dynamic responses characteristics of slopes. Chin. J. Rock Mech. Eng. 29(12), 2420–2428.

Y. Luo, et al. Engineering Geology 271 (2020) 105607

13