Dynami movement history of the Iiyama slope failure revealed from seismi data
Masumi Yamadaa, Yuki Matsushia , Takanori Matsuzawaba Disaster Prevention Resear h Institute, Kyoto University

b National Resear h Institute for Earth S ien e and Disaster Resilien e

Abstra t

The Iiyama slope failure o urred in the early morning of May 19, 2017, in Nagano Prefe ture, entral Japan. It aused a debris
ow in the Idegawa River, resulting in the eva uation of the residents of the neighboring areas for half a year. Sin e the sour e waslo ated in a mountainous area, the ause of the debris ow was not dis overed immediately.
To investigate the me hanism of this slope failure, we performed a eld survey and obtained aerial photos of the slope failureusing an unmanned aerial vehi le. Additionally, we analyzed seismi data re orded by the surrounding stations, to identify theground motion generated by the mass movements.
We found that the Iiyama slope failure involved two major mass movements: a large landslide and a subsequent debris ow
triggered by the landslide. The movement of the landslide was re orded with long-period seismi waveforms, and the estimatedfor e history showed a unidire tional movement from north to south for 50 s, rea hing a maximum velo ity of about 6.6 m/s.
Following, debris ew for about 5 km from the top of the landslide sour e area. The initial ollapse produ ed a large shaking witha short-period omponent, and the signal gradually de ayed as the debris ow traveled along the river.
Our study shows that the two mass movements in the Iiyama slope failure generated ground motions with ompletely di erent
frequen ies. This suggests that the ground motions re orded by the seismometer are signi ant for understanding the movement
me hanism of slope failure. The seismi signal, ombined with the aerial photos, helps us to understand the dynami movement
history of the landslide.
Highlights

 A omplex me hanism of the slope failure was laried byseismi data and UAV images

 Two mass movements were re orded in high- and lowfrequen y seismograms, respe tively

 Seismi signals are useful for the dete tion and dis rimination of slope failures

Keywords:

Iiyama City, seismi signal, seismi waveform inversion, UAV image, debris ow, slope failure

1. Introdu tion

Slope failures are ontrolled by geologi stru ture and sometimes involve a ompli ated me hanism of ollapse, as was thease of the slope failure that o urred in Iiyama City, Nagano
Prefe ture, Japan in 2017. The hillslope failure o urred in theearly morning on May 19, 2017 (times in this paper are basedon Japan Standard Time). Aerial photographs of the area show
the tra e of the debris ow and a large mass movement asso iated with the debris ow. The debris ew for about 5 km, andit was rst observed by a lo al resident of the downstream area.
The failure generated a shaking of the ground, whi h was
re orded by the surrounding seismi stations (Resear h Centeron Landslides, 2017; Yamada et al., 2017). In general, seismi
data are re orded ontinuously at a high sampling rate, so they
are useful for estimating the timing and movement histories ofslope failures (e.g. Hasegawa and Kanamori, 1987; Kawakatsu,
Preprint submitted to Engineering Geology

1989). In addition, seismi sensors re ord signals at a great
distan e, and thus their overage is mu h wider (in the order oftens of kilometers) than those of other types of sensors, su h as
opti al sensors or wire sensors (in the order of tens of meters).
Seismi data of mass movements an be analyzed following
the deterministi approa h or the sto hasti approa h. Longperiod seismi waveforms (in general, longer than the periodof mi roseisms, or about 10 s) are analyzed using the deterministi approa h. The seismi waveform inversion te hniqueestimates a for e history of the mass movement by minimizing the di eren e between the syntheti waveform and the observed waveform. This approa h provides information on the
movement history, su h as the time history of the for e a tingon the surfa e, velo ity, mass, and the oeÆ ient of fri tion(e.g. Brodsky et al., 2003; Favreau et al., 2010; Moretti et al.,2012; Allstadt, 2013; Yamada et al., 2013; Ekström and Stark,June 24, 20202013; Yamada et al., 2018). On the other hand, short-period
seismi waveforms are analyzed using the sto hasti approa h,sin e the waveforms are greatly a e ted by the small-s ale seismi stru ture along the propagation path and it is diÆ ult toal ulate reliable syntheti waveforms. This approa h uses theenvelope of waveforms, arrival times, spe trograms, and power
spe tral density to obtain the lo ation and size of an event, andthe ow me hani s (e.g. Surina h et al., 2005; Yamada et al.,2012; Burtin et al., 2013, 2016; Chen et al., 2013; Chao et al.,2015; Walter et al., 2017; Lai et al., 2018). In this study, we
ombined these two approa hes to extra t information fromseismi signals on the failure movement. We also performeda eld survey and obtained aerial images using an unmanned
aerial vehi le (UAV). By ombining the seismi data with theaerial images, we investigated the omplex me hanism of the
Iiyama slope failure.

ure 3(b)). The deposit of this landslide blo ked the right-handstream of the Idegawa River and reated a landslide dam.
The material of the eastern blo k, whi h moved from west
to east, supplied a debris ow that traveled along the left-handstream of the Idegawa River. The sour e of the mass was about
100 m in width and 400 m in length. Most of the debris stopped
at a debris barrier dam about 4 km downstream from the sour e,
but some debris overowed the dam, rea hing the Chikuma
River (Hiramatsu et al., 2017).
In Figure 3( ), we an observe owlines (arrows) on the
ground surfa e in the dire tion of the debris ow, so the upper
right portion whi h is en losed by the dotted line owed as adebris ow. Figure 3(d) shows that the eastern part of the landslide was eroded and entrained by the debris ow, suggestingthat the western blo k ollapsed prior to the debris ow.
We estimated the total mass of the landslide by omparing
the digital elevation models (DEMs) before and after the event.
For this purpose, we used a three-dimensional DEM with 0.5-m
grid spa ing reated from airborne Light Dete tion and Ranging (LiDAR) topographi surveys done by Nagano Prefe ture
after the slope failure (Figure 4), and a 5-m DEM made by photogrammetry before the slope failure (Geospatial Information
Authority of Japan, 2017). Based on the mass thi kness information shown in Figure 5, the sour e volume was estimatedat 1.2106 m3 and the total mass of the displa ed material at
3109 kg, assuming an average ro k density of 2.5103 kg/m3(Iwaya and Kano, 2005). Based on these DEMs and the envelopes shown in Figure 3(a), the volume of the western blo k
was estimated at about 75% of the total volume.

2. Site Des ription

The slope failure lo ation is in the northern part of Nagano
Prefe ture, lose to the boundary with Niigata Prefe ture (Figure 1). A nearby resident found that the downstream area of the
Idegawa River be ame muddy and reported this to the lo al authorities at 7:53 AM on May 19, 2017 (Iiyama City, 2017). The
authorities onrmed that there was a large-s ale hillslope failure in the upstream area of the river. There were no human asualties or property damage, but the downstream residents wereordered to eva uate for half a year (Iiyama City, 2017). Hiramatsu et al. (2017) analyzed the snow depth and pre ipitation
data in this area and on luded that the ause of the landslide
was most likely water originating from snowmelt.
The bedro k in the study area onsists of Pleisto ene volani s, espe i ally andesiti pyro lasti ro ks and lavas inter alated with layers of felsi tu (Yanagisawa et al., 2001).
This bedro k is overed by old and new landslide debris and aseries of uvial terra e deposits (Figure 2). The studied landslide o urred on a hillslope underlain by pyro lasti ro ks andaused a subsequent debris ow, whi h traveled down about 5
km along the Idegawa River.
We performed a eld survey on June 7-8, 2017, about three
weeks after the slope failure o urred, and obtained aerial
photos of the slope failure using an UAV. We made an orthophoto with ommer ial modeling software (Pix4Dmapper)that is shown in Figure 3(a).
The Iiyama slope failure onsisted of two major mass movements. The western blo k (Figure 3(a)) moved from northnorthwest to south-southeast and was deposited at the end of
the slope (hereafter referred to as the landslide). The width ofthe mass was about 150 m and its length was about 400 m. Thisblo k was relatively undisturbed, and trees remained standingon the mass, whi h suggests its translational motion. Hiramatsu
et al. (2017), based on the displa ement of the ontrol points on
the undisturbed mass, estimated that the mass ew for a lateral
distan e of about 70 m. Note that there is a sharp verti al edgein the eastern boundary of the western landslide blo k, whi hinterse ts with the mountain ridge at an angle of about 10Æ (Fig-The failed masses were a part of larger landslide body thatan be identied on the pre-event topography. The lo al hillslope shows a low in lination (< 20Æ ) and rugged topography
as a result of the repeated movements of this long-lived landslide. A depression formed at the top of the slope before thefailure event (Figure 4(b)), suggesting the pre eding deformation of the sliding mass. The fra tured and partly pulverized
bedro k layers formed by the re ent landslide a tivities overed the wide area of the hillslopes and they are des ribed as
younger landslide debris in Figure 2.
Boreholes had been drilled along a length prole of the western landslide body to understand its subsurfa e stru tures. Figure 5 shows the proles of the boring ores drilled at six loations on the main body of the landslide. The lo al bedro konsists of tu bre ia, in luding andesite gravels in tu a eousmatrix, and inter alated tu beds dipping southeast. The upper part of the bedro k had been hemi ally weathered, and it
has been only slightly a e ted by the gravitational deformationof the entire hillslope. This bedro k was overed by massive
landslide deposits, with heavily damaged stru tures due to therepeated landslide movements. The sliding surfa e of the 2017
failure event was formed at the base of these landslide deposits,with a maximum depth of 48 m below the ground, and it an
be identied by the ontrasting stru tures between the sliding
mass and the immobile substrate.
2

3. Seismi

Signals

4. Seismi

Waveform Inversion

Long-period ground motion is less inuen ed by subsurfa esoil stru ture than short-period motion, and this helps extra ting long-period sour e information on the landslide movement.
In order to determine the landslide me hanism, we performed
seismi waveform inversion (Kawakatsu, 1989; Brodsky et al.,
2003; Yamada et al., 2013). The inversion te hnique estimates
the for e history a ting on a xed lo ation by minimizing thedi eren e between observed and syntheti waveforms. The
syntheti waveforms are a onvolution of the pre- omputed
Green's fun tion and the for e history. We performed a gridsear h in spa e to nd the optimal lo ation for explaining theobserved seismi waveforms. The grid sear h was performed
in an area of about 30 km  30 km with a 5 km spa ing (Figure1).
We al ulated Green's fun tions at ea h node using the disrete wavenumber method (Bou hon, 1979) and the Japan Meteorologi al Agen y's (JMA) one-dimensional velo ity stru ture model (Ueno et al., 2002). Based on the method of Nakano
et al. (2008), we performed a seismi waveform inversion in
the frequen y domain and determined the best tting threeomponent sour e time fun tion of a single-for e me hanism,
assuming lo ations at ea h grid point. Then, the normalized
residual of equation (7) found in Nakano et al. (2008), whi h is
the di eren e between observed and syntheti waveforms normalized by the amplitude of the observed waveforms, for ea hnode is used to determine the sour e lo ation. Figure 1 shows
the residual ontour of this grid sear h whi h suggests that thebest-t sour e lo ation is very lose to the Iiyama slope failuresite.
Sin e the spatial resolution of the grid sear h is rather oarse(5 km), in the next step we xed the exa t lo ation of the sour eat the site of the Iiyama slope failure (36.99ÆN, 138.42ÆE) andrepeated the waveform inversion. Figure 8 shows the optimalfor e history and the waveform t. There is good agreement
between observed and syntheti waveforms with a normalized
residual of 0.07.
The for e history in Figure 8(a) shows a lear harmoni signal at 55-100 s. This orresponds to a typi al sour e time fun tion for the landslide movement with relatively short travel distan e (Brodsky et al., 2003; Yamada et al., 2013, 2018). It ree ts the a eleration and de eleration pro ess of the landslide
movement. The Green's fun tions are dominated by surfa e
waves and the verti al omponent of the for e ontributes signi antly to the shape and amplitude of the (horizontal omponent) Rayleigh waves. Therefore, horizontal waveforms ontain information about the verti al for e, and with enough numbers and azimuthal overage of stations, these data an be used
to estimate the verti al for e. To evaluate how well the verti alfor e was resolved from our dataset, we omputed the model
resolution matrix (Menke, 2018). We onrmed that they wereidentity matri es in all the frequen y and the rank of the Green's
fun tion matri es was equal to the number of the unknown parameters (i.e., 3). This supports that all omponents were wellresolved in our analysis.
The maximum for e in the ve tor sum is estimated as

The ground motion aused by the Iiyama slope failure wasre orded by the surrounding seismi stations. Figure 1 shows
the station distribution around the site of the failure. We used
the F-net broadband seismi stations, short-period seismi stations (Hi-net and Japan Meteorologi al Agen y), and highsensitivity a elerometers ollo ated with the Hi-net shortperiod sensors. The high-sensitivity a elerometers onsistedof two horizontal omponents, while the other sensors had threeomponents.
Figure 6 shows the seismi signal at the losest station(N.MAKH) re orded by a high-sensitivity a elerometer. The
distan e between the station and the lo ation of the failure event
is about 8 km. Both the original a elerogram and displa ement
ltered between 0.01 and 0.1 Hz are shown. There is a lear differen e in the signal arrival times between the two waveforms.
The long-period displa ement signal starts in reasing at 60 s
and re ords a harmoni pulse with a period of about 40 s. Thea eleration signal at this period is relatively small, and it issuddenly amplied at 100 s. The signal is attenuated exponentially as a fun tion of time, but a small signal ontinues foraround ve minutes (see Appendix Figure S1). Most of the energy in the a eleration re ord is ontained in the frequen ies
between 1 and 4 Hz (Figure 6( ))These short-period hara teristi s are also observed at theother surrounding seismi stations as shown in Figure 7. Thisgure shows the velo ity waveforms re orded by the shortperiod seismometers. To remove the high-frequen y noise, weapply a fourth-order Butterworth low-pass lter with a uto
frequen y of 5 Hz. The amplitude of the waveform de ays as
a fun tion of distan e, but the signal of the landslide remains
dete table as far as 40 km away. However, the re ords of distant stations have longer tails than the stations losest to theslope failure site due to the s attering of the short-period signals (Sato, 1977; Wu and Aki, 1988; Jing et al., 2014).
The long-period signals were re orded by the F-net broadband seismometer and the high-sensitivity a elerometers. Figure 8 shows the ltered displa ement waveforms. We pro essed
these re ords a ording to the following pro edure. First, weremoved the mean from the time series and orre ted all waveforms for the instrumental response. A non- ausal fourth-order
Butterworth lter with a orner frequen y of 0.014-0.1 Hz wasapplied. The lter window was sele ted so that mu h of theba kground noise was redu ed without removing the landslide
signal. We used a non- ausal lter to avoid phase distortion in
the shape of the landslide waveform. The data were integrated
in the time domain to obtain the displa ement waveforms. Figure 8 shows the onsistent harmoni pulse in the waveformsof all stations, but the amplitudes of the EW and UD omponents are relatively small. We used these ltered displa ement
waveforms with a duration of 150 s starting from 6:36:40 AM,
May 19, 2017, for the seismi waveform inversion in the next
se tion.
3

2.1109 N. The a eleration history an be obtained by dividing the for e by the mass, and the velo ity history is found byintegrating the a eleration history. Assuming a onstant mass
(i.e., that the whole mass moved uniformly), the maximum estimated a eleration and velo ity were 0.69 m/s2 and 6.6 m/s,
respe tively.

ompared to the migration of the sour e, the amplitude hange
may ree t the ow pro ess. Based on this assumption, thelarge amplitude may orrespond to the initiation pro ess fromthe ollapse to the debris ow, and the long tail of the waveformsuggests that the debris owed along the river. These signals did
not appear in the long-period omponent, sin e the mass of ea hparti le was too small to produ e the ne essary momentum on
the ground surfa e.
We estimated that the landslide started moving at 6:37:35
AM, and ontinued for about 50 s. The debris ow was triggered by the landslide at 6:38:20 AM, the large amplitude of theseismi signal lasted around 3 minutes, and the amplitude wentba k to its original noise level after 5 minutes (see Appendix
Figure S1). Hiramatsu et al. (2017) des ribed the stream proleand hange in the riverbed heights obtained from the airborne
laser surveys before and after the event. There is a substantial
hange in the riverbed between the sour e area and the debris
barrier dam (Figure 2). This suggests that the seismi signals of
the debris ow were produ ed eÆ iently in this 4-km stret h.
Therefore, the average speed of the debris ow in this se tion isestimated at 13 m/s. Hiramatsu et al. (2017) estimated that thevelo ity of the subsequent debris ow at 2:40 PM on May 22
was 11 m/s a ross the lowest 1 km of its ow range. Assuming
the upstream area had a higher slope and larger velo ity, thisnumber is onsistent with our estimated velo ity of the debris
ow. The velo ity may have hanged if the debris ow wasstret hed while traveling or if it o ured su essively.
The omplex me hanism of the Iiyama slope failure was laried by seismi signals and UAV images. The seismi stations in the study area were originally installed for onstru ting an earthquake atalog, but they have also proven useful forthe analysis of geote hni al hazards. By using a UAV, highquality and high-resolution aerial images are easily obtained.
With these aerial images, resear hers an ondu t photogrammetry using sophisti ated stru ture-from-motion software (e.g.
Walter et al., 2009; Niethammer et al., 2012). This resear his unique, be ause the omplex movement of the slope failure
was analyzed using remote sensors at relatively low ost andin a short time, ompared to onventional eld surveys. These
remote tools are expe ted to be very e e tive in the qui k investigation and me hanism lari ation of future geote hni alhazards o urring at ina essible lo ations.

5. Dis ussion

The Iiyama slope failure was a unique landslide with both asubstantial mass movement and a debris ow o urring losely
in time and spa e. Based on the DEM model, there were two
major blo ks. The western blo k moved from NNW to SSE and
was deposited at the valley bottom. The eastern blo k owed
along the river as a debris ow.
The western blo k slid on the bedro k of tu -bre ia, witha thi kness of about 50 m (Nagano Prefe ture, personal ommuni ation). Sin e the sliding surfa e had formed along thepre-existing geologi al stru ture, the mass was likely to move
uniformly as a blo k in the translational dire tion. The moving
dire tion of the landslide oin ided with the dipping dire tionof the bedding lo ally (Figure 2).
The movement of the eastern body, whi h be ame a debrisow, su eeded that of the western blo k, sin e the debris ow
ex avated the slid mass of the western blo k (Figure 3(d)).
Sin e the two movements o urred losely in time and spa e,
we interpreted that the debris ow was triggered by the movement of the western blo k. Hiramatsu et al. (2017) observed
multiple springs owing from the side s arp of this eastern part
immediately after the failure. The abundant supply of subsurfa e water may have promoted the movement of the debris ow.
The for e history estimated from the long-period waveforms
shows a simple unidire tional mass movement. The parti lemotion in the horizontal plane and the se tion along the sliding
dire tion are in good agreement with regard to the dire tion of
movement (Figures 4 and 9). The rst positive pulse in the NS
dire tion (Figure 8(a)) orresponds to the a eleration at the
beginning of sliding, and the se ond negative pulse orresponds
to the de eleration due to the mass blo k rea hing the valley(Yamada et al., 2013).
Signals of debris ows tend to appear in the short-period
ground motions (Burtin et al., 2016). The ground motion isessentially produ ed by the impa t between parti les and theground within the hannel (Lai et al., 2018). The frequen y ofthe signal re orded by the regional network is about 1-5 Hz in
general (Chen et al., 2013; Allstadt et al., 2018), but it may behigher if the station were lose to the sour e (Burtin et al., 2016;
Walter et al., 2017; Lai et al., 2018), due to the larger attenuation in high frequen ies. The seismi signal of the debris ow
tends to have an emergent onset, and the duration is in the order of tens of minutes, depending on the ow distan e (Burtin
et al., 2016; Walter et al., 2017; Lai et al., 2018; Allstadt et al.,2018).
Compared to past studies, the short-period ground motion in
Figure 6(a) shows a sharp peak and de ays exponentially as
a fun tion of time. Sin e the sour e-station distan e is large

6. Con lusions

We investigated the omplex me hanism of the Iiyama slope
failure by obtaining eld data and aerial photos through a eld
survey three weeks after the in ident, and by analyzing the seismi signal of the slope failure. Our aim was to extra t the slope
failure's timing and movement history.
We found that the Iiyama slope failure onsisted of two major mass movements: a large landslide and a subsequent debris
ow triggered by the landslide. These two movements werere orded at the surrounding seismi stations at di erent frequen ies. The ombination of the long-period and short-period
seismi waveforms reveals the timing and types of the re orded4

mass movements. The UAV provides information on the geology and topography of the surfa e pro ess and the aerial photos
an also be used for reating a DEM if a high-resolution DEM
is not available.
Our study shows that the two mass movements in the Iiyama
slope failure generated ground motions with ompletely di erent frequen ies. This suggests that the ground motions re ordedby the seismometer are signi ant for understanding the movement me hanism of the slope failure. The seismi signal, ombined with drone aerial photos, helps us to understand the dynami movement history of the landslide.

Hiramatsu, S., Ishida, K., Kanazawa, A., Gonda, Y., Sawa, Y., Tsutsumi, D.,
Nagayama, T., Fukuyama, T., Mantoku, M., Miike, T., Morishita, A., Yajima, K., and Yamada, Y. (2017). Slope failure and subsequent debris owo urren e on May 2017 at Iiyama, Nagano, Japan. Journal of the Japan
So iety of Erosion Control Engineering, 70(3):4150.
Iiyama City (2017).
Response to the slope failure in Teruoka,
http://www.city.iiyama.nagano.jp/soshiki/
Iiyam City.
kikikanribousai/bousaisyoubou/saigaiinfo/20170520sanpuku,(last a essed May 8, 2019).
Iwaya, T. and Kano, K. (2005). Ro k densities for the geologi units in theJapanese islands: an estimate from the database PROCK (Physi al Properties of Ro ks of Japan). Journal of the Geologi al So iety of Japan,
111(7):434.
Jing, Y., Zeng, Y., and Lin, G. (2014). High-frequen y seismogram envelope
inversion using a multiple nonisotropi s attering model: Appli ation to aftersho ks of the 2008 wells earthquake. Bulletin of the Seismologi al So ietyof Ameri a, 104(2):823839.
Kawakatsu, H. (1989). Centroid single for e inversion of seismi waves generated by landslides. Journal of Geophysi al Resear h, 94(B9):1236312,374.
Lai, V. H., Tsai, V. C., Lamb, M. P., Ulizio, T. P., and Beer, A. R. (2018).
The seismi signature of debris ows: Flow me hani s and early warning at
Monte ito, California. Geophysi al Resear h Letters.
Menke, W. (2018). Geophysi al data analysis: Dis rete inverse theory. A ademi press.
Moretti, L., Mangeney, A., Capdeville, Y., Stutzmann, E., Huggel, C., S hneider, D., and Bou hut, F. (2012). Numeri al modeling of the Mount Steller
landslide ow history and of the generated long period seismi waves. Geophysi al Resear h Letters, 39:L16402.
Nakano, M., Kumagai, H., and Inoue, H. (2008). Waveform inversion in
the frequen y domain for the simultaneous determination of earthquake
sour e me hanism and moment fun tion. Geophysi al Journal International, 173(3):10001011.
Niethammer, U., James, M., Rothmund, S., Travelletti, J., and Joswig, M.
(2012). UAV-based remote sensing of the Super-Sauze landslide: Evaluation and results. Engineering Geology, 128:211.
Resear h Center on Landslides, DPRI, Kyoto University (2017). Seismi waveforms produ ed at around the slope failure in Iiyama City, Nagano Prehttp://landslide.dpri.kyoto-u.ac.jp/report/2017/
fe ture.
20170522nagano_landslide.pdf , (last a essed May 8, 2019).
Sato, H. (1977). Single isotropi s attering model in luding wave onversions
simple theoreti al model of the short period body wave propagation. Journalof Physi s of the Earth, 25(2):163176.
Surina h, E., Vilajosana, I., Khazaradze, G., Bies as, B., Furdada, G., and Vilaplana, J. (2005). Seismi dete tion and hara terization of landslides andother mass movements. Natural Hazards and Earth System S ien ., 5:791
798.
Ueno, H., Hatakeyama, S., Aketagawa, T., Funasaki, J., and Hamada, N.
(2002). Improvement of hypo enter determination pro edures in the Japan
Meteorologi al Agen y. Quarterly Journal of Seismology, 65:123134.
Walter, F., Burtin, A., M Ardell, B. W., Hovius, N., Weder, B., and Turowski,
J. M. (2017). Testing seismi amplitude sour e lo ation for fast debrisow dete tion at illgraben, switzerland. Natural Hazards and Earth System
S ien es, 17(6):939955.
Walter, M., Niethammer, U., Rothmund, S., and Joswig, M. (2009). Joint analysis of the Super-Sauze (Fren h Alps) mudslide by nanoseismi monitoringand UAV-based remote sensing. rst break, 27(8).
Wessel, P. and Smith, W. (1991). Free software helps map and display data.
Eos, 72(441):445446.
Wu, R.-S. and Aki, K. (1988). Multiple s attering and energy transfer of seis-

A knowledgements

We a knowledge the National Resear h Institute for EarthS ien e and Disaster Resilien e (NIED) and the Japan Meteorologi al Agen y (JMA) for the use of seismi data. Highresolution DEM data were provided by the Hokushin Constru tion OÆ e, Nagano Prefe ture. We thank the Hokushin Regional Development Bureau, Nagano Prefe ture, for providing
geologi al information, in luding proles of boring ores. We
also thank Dr. Hiroyuki Kumagai in Nagoya university and
Dr. Masaru Nakano in Japan Agen y for Marine-Earth S ien e
and Te hnology (JAMSTEC), who provided us with a omputer
program of the waveform inversion. We used generi mapping
tools (GMT) to draw the gures (Wessel and Smith, 1991).
Referen es

Allstadt, K. (2013). Extra ting sour e hara teristi s and dynami s of the August 2010 Mount Meager landslide from broadband seismograms. Journalof Geophysi al Resear h: Earth Surfa e, 118(3):14721490.
Allstadt, K. E., Matoza, R. S., Lo khart, A., Moran, S. C., Caplan-Auerba h, J.,
Haney, M., Thelen, W. A., and Malone, S. D. (2018). Seismi and a ousti
signatures of sur ial mass movements at vol anoes. Journal of Vol anology
and Geothermal Resear h.
Bou hon, M. (1979). Dis rete wave number representation of elasti wave
elds in three-spa e dimensions. Journal of Geophysi al Resear h,84(B7):36093614.
Brodsky, E., Gordeev, E., and Kanamori, H. (2003). Landslide basal fri tion as
measured by seismi waves. Geophysi al Resear h Letters, 30(24):2236.
Burtin, A., Hovius, N., Milodowski, D. T., Chen, Y., Wu, Y., Lin, C., Chen,
H., Emberson, R., and Leu, P. (2013). Continuous at hment-s ale monitoring of geomorphi pro esses with a 2-D seismologi al array. Journal ofGeophysi al Resear h: Earth Surfa e, 118(3):19561974.
Burtin, A., Hovius, N., and Turowski, J. M. (2016). Seismi monitoring of
torrential and uvial pro esses. Earth Surfa e Dynami s, 4(2).
Chao, W.-A., Wu, Y.-M., Zhao, L., Tsai, V. C., and Chen, C.-H. (2015). Seismologi ally determined bedload ux during the typhoon season. S ienti
reports, 5:8261.
Chen, C.-H., Chao, W.-A., Wu, Y.-M., Zhao, L., Chen, Y.-G., Ho, W.-Y.,
Lin, T.-L., Kuo, K.-H., and Chang, J.-M. (2013). A seismologi al studyof landquakes using a real-time broad-band seismi network. Geophysi al
Journal International, 194(2):885898.
Ekström, G. and Stark, C. P. (2013). Simple s aling of atastrophi landslide
dynami s. S ien e, 339(6126):14161419.
Favreau, P., Mangeney, A., Lu as, A., Crosta, G., and Bou hut, F. (2010). Numeri al modeling of landquakes. Geophysi al Resear h Letters, 37:L15305.
Geospatial Information Authority of Japan (2017). Basemap information download servi e.
Hasegawa, H. and Kanamori, H. (1987). Sour e me hanism of the magnitude 7.2 Grand Banks earthquake of November 1929: Double ouple orsubmarine landslide? Bulletin of the Seismologi al So iety of Ameri a,77(6):19842004.

mi wavesSeparation of s attering e e t from intrinsi attenuation II. Appli ation of the theory to Hindu Kush region, pages 4980. Springer.

Yamada, M., Matsushi, Y., Chigira, M., and Mori, J. (2012). Seismi re ordingsof landslides aused by typhoon Talas (2011), Japan. Geophysi al Resear hLetters, 39(13):L13301.
Yamada, M., Kumagai, H., Matsushi, Y., and Matsuzawa, T. (2013). Dynami
landslide pro esses revealed by broadband seismi re ords. Geophysi al
Resear h Letters, 40(12):29983002.
Yamada, M., Kamo, M., and Matsushi, Y. (2017). Report on the damage
survey for the May 19 2017 Iiyama slope failure. http://www.eqh.
dpri.kyoto-u.ac.jp/~ masumi/eq/iiyama2017/ , (last a essed May
8, 2019).

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Yamada, M., Mangeney, A., Matsushi, Y., and Matsuzawa, T. (2018). Estimation of dynami fri tion and movement history of large landslides. Landslides, 15(10):19631974.
Yanagisawa, Y., Kaneko, T., Akahane, S., Awata, Y. Kamai, T., and Tsu hiya,
N. (2001). Geology of the Iiyama distri t, with geologi al map at 1:50,000.
Geologi al Survey of Japan, 144p, (in Japanese).

Area of Figs.
3(a) and 4(a)IiyamaLandslides and debris
flow by the 2017 event

0.2

0.2
0.2

0.4

Niigata

0.6

0.4

Modern alluvium
Lower terrace deposit
Middle terrace deposit
Higher terrace deposit
Younger landslide debris
Paleo landslide deposits
Felsic tuff
Andesite lava
Andesite pyroclastic rocks

NaganoF-net(BB) used for inversion
Hi-net(acc+SP) used for inversion
Hi-net(acc+SP)
JMA (SP)A debrisbarrier dam

1 km

(m)

Figure 2: Geologi al map of the study area (modied after Yanagisawa et al.
(2001)). The numbers show the strike and dip of the strata.

Gunma
20 km

(a)
(d)

Figure 1: Map with the lo ations of the seismi stations. The star shows thelandslide lo ation, triangles show Hi-net lo ations, the ir le shows a JMA
short-period (SP) seismi station, and the square shows an F-net broadband(BB) station. The lled symbols represent the stations used for the waveform
inversion. The ba kground olor shows the elevation, and thi k solid lines show
the prefe ture boundary. The bla k dots show the lo ations of the grid sear hand the ontour lines show the residuals of the grid sear h. The inset shows themap of Japan and the lo ation of the slope failure.

left-hand stream

(c)

(b)

d streamright-han

250m

(b)

(c)

(d)

Figure 3: Photos taken using UAV images (June 8, 2017). The white solid lines
show the envelope of the landslide, and the white dotted lines show the envelopeof the debris ow. The white arrows show the dire tion of the owline on the
ground surfa e. (a) The orthophoto generated by the software. The lo ations
and dire tions of photos (b)-(d) are indi ated with bla k arrows. (b) Photo of
the s arp at the eastern edge of the landslide. ( ) Photo of the sour e head ofthe landslide. (d) Photo of the s arp made by the debris ow.

6

138.415°

138.426°

36.993°Slope (°)
Y

0

20

40

60

80

Acc. (m/s/s)

1x10-4
Elevation difference (m)−30 −20 −10 0 +10 +20 +30(a) Acceleration

0−1x10-4

Disp. (m)2x10-6(b) Displacement (0.01-0.1Hz)0−2x10-6

Y’

Freq. (Hz)

10

(a)

36.987°

Depression before the event
Altitude (m)Before failure
After failure

BV4

BV5

BV6

5

Y

0

BV3

Y’

BV2

(c) Spectrogram

0

BV9

100

200

×10-12(m/s2)
8
6
4
2

300

Time (s)(b)
Figure 6: Seismi re ords of the Iiyama landslide at N.MAKH station in NS
omponent. The origin time is 6:36:40 AM, May 19, 2017. (a) Original highsensitivity a elerometer re ord, (b) ltered displa ement re ord with a nonausal fourth order Butterworth lter between 0.01 and 0.1 Hz, and ( ) spe trogram of the a eleration re ord. Ea h segment for the fast Fourier transformhas 128 samples and overlaps 112 samples.

Horizontal distance (m)Figure 4: Topography of the Iiyama landslide. (a) Elevation hange at the
Iiyama landslide. The ontours show the DEM after the landslide (July 3,2017). Cir les show the lo ations of the boring ores. (b) Verti al se tion
along the YY' segment before and after the failure. ( ourtesy of the Hokushin
Regional Development Bureau)

BV6
Sliding surface

BV5

0

0

Landslide deposit(a)Tuff layer(b)5x10-6 m/s

BV4Weathered and slightlydeformed tuff breccia
Intact tuff breccia

N.MAKH
N.NZW H

BV3

BV9

20

BV2

Distance(km)20Distance(km)Altitude (m)N.MKOH

NAKAMA
N.NKNHN.MKGHN.KZKF
N.KWNHN.YZWHN.SZW H

40

40

N.TGKH

0

100

200

Time(s)

300

0

100

200

300

Time(s)Figure 7: Seismi re ords of the Iiyama landslide re orded by the Hi-net and
the JMA seismi network in the NS omponent. (a) 5 Hz low-pass lteredwaveforms and (b) normalized envelopes. The origin time is 6:36:40AM, May
19, 2017. Adja ent seismograms are shown alternately in bla k and gray for
larity.

Projected position on the cross-sectional line (m)Figure 5: Proles of six boring ores drilled on the main body of the landslide( ourtesy of the Hokushin Regional Development Bureau). The lo ations areshown in Figure 4.

7

Force (N)(a) 1x10 EW

NS

9

UD

0
-1x109
0

30

60

90

120

150 0

30

60

Time (s)(b)

max = 0.408 µm
min = −0.371 µm

EW

120

90

150 0

30

60

Time (s)max = 1.14 µm
min = −1.16 µm

NS

90

120

150

Time (s)

UD
Obs.
Syn.
Residual=0.07

N.MAKHmax = 0.320 µm
min = −0.282 µm

max = 0.540 µm
min = −0.615 µm

max = 0.277 µm
min = −0.274 µm

max = 0.385 µm
min = −0.403 µm

max = 0.133 µm
min = −0.109 µm

max = 0.160 µm
min = −0.206 µm

max = 0.093 µm
min = −0.076 µm

max = 0.212 µm
min = −0.207 µm

N.NZWH

N.MKOHN.NKNHmax = 0.062 µm
min = −0.063 µm

N.KZKF
0

30

60

90

120

150 0

30

Time (s)

60

120

90

150 0

30

60

Time (s)

90

120

150

Time (s)Figure 8: Seismi waveforms of the Iiyama landslides with a band-pass lter
at 0.014-0.1 Hz. The origin time is 6:36:40AM, May 19, 2017. (a) Estimatedsingle-for e sour e time fun tions for the EW, NS, and UD omponents. (b)Displa ement waveform ts between observed (bla k) and syntheti (red) dataobtained from the sour e inversion. The letters on the left show the stationode, and the numbers at the top right show the largest amplitude of the two
waveforms.

9

9

2x10

(a)

Force in UD (N)Force in NS (N)

2x10

0

0

9

9

-2x10
9
-2x10

(b)

0

Force in EW (N)

9

2x10

-2x10
9
-2x10

0

9

2x10

Force in Y-Y’ section (N)Figure 9: Parti le motion of the sour e time fun tion between 55 and 100 s in
Figure 8(a). Gray arrows show the dire tion of the parti le motion. (a) Horizontal se tion and (b) verti al se tion along the YY' segment (Figure 4(a)).

8