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Title

Resistivity characterisation of Hakone volcano, central Japan, by threedimensional magnetotelluric inversion

Authors

Ryokei Yoshimura, Yasuo Ogawa, Yohei Yukutake, Wataru Kanda,
Shogo Komori, Hideaki Hase, Tada-nori Goto, Ryou Honda, Masatake
Harada, Tomoya Yamazaki, Masato Kamo, Shingo Kawasaki, Tetsuya
Higa, Takeshi Suzuki, Yojiro Yasuda, Masanori Tani, Yoshiya Usui

Citation

Earth, Planets and Space, Vol. 70, ,Pub. date

2018, 4Creative Commons

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Yoshimura et al. Earth, Planets and Space (2018) 70:66
https://doi.org/10.1186/s40623-018-0848-yOpen Access

EXPRESS LETTER

Resistivity characterisation of Hakone
volcano, Central Japan, by three‑dimensional
magnetotelluric inversion
Ryokei Yoshimura1*, Yasuo Ogawa2, Yohei Yukutake3, Wataru Kanda2, Shogo Komori4,5, Hideaki Hase2,6,
Tada‑nori Goto7, Ryou Honda3, Masatake Harada3, Tomoya Yamazaki1, Masato Kamo1, Shingo Kawasaki1,
Tetsuya Higa8, Takeshi Suzuki8, Yojiro Yasuda9, Masanori Tani7 and Yoshiya Usui2

Abstract
On 29 June 2015, a small phreatic eruption occurred at Hakone volcano, Central Japan, forming several vents in the
Owakudani geothermal area on the northern slope of the central cones. Intense earthquake swarm activity andgeodetic signals corresponding to the 2015 eruption were also observed within the Hakone caldera. To complement
these observations and to characterise the shallow resistivity structure of Hakone caldera, we carried out a threedimensional inversion of magnetotelluric measurement data acquired at 64 sites across the region. We utilised an
unstructured tetrahedral mesh for the inversion code of the edge-based finite element method to account for the
steep topography of the region during the inversion process. The main features of the best-fit three-dimensionalmodel are a bell-shaped conductor, the bottom of which shows good agreement with the upper limit of seismicity,beneath the central cones and the Owakudani geothermal area, and several buried bowl-shaped conductive zones
beneath the Gora and Kojiri areas. We infer that the main bell-shaped conductor represents a hydrothermally alteredzone that acts as a cap or seal to resist the upwelling of volcanic fluids. Enhanced volcanic activity may cause volcanic
fluids to pass through the resistive body surrounded by the altered zone and thus promote brittle failure within theresistive body. The overlapping locations of the bowl-shaped conductors, the buried caldera structures and the pres‑ence of sodium-chloride-rich hot springs indicate that the conductors represent porous media saturated by highsalinity hot spring waters. The linear clusters of earthquake swarms beneath the Kojiri area may indicate several weakzones that formed due to these structural contrasts.
Keywords: Hakone volcano, Magnetotellurics, Resistivity structure, Three-dimensional inversion
Introduction
Hakone volcano is located at the northern end of the
Izu–Mariana volcanic arc in Central Japan, 100 km westof Tokyo (index map in Fig. 1a). On 29 June 2015, a small
phreatic eruption was observed in the Owakudani geothermal area, which is located on the northern slope ofthe central cones of Hakone volcano, forming several
vents, although there is no prior historical record of magmatic eruptions there. However, long-term fumarolic*Correspondence: ryokei@eqh.dpri.kyoto‑u.ac.jp
1
Disaster Prevention Research Institute, Kyoto University, Gokasyo, Uji,
Kyoto 611‑0011, Japan
Full list of author information is available at the end of the article

activity has been observed across this geothermal area.
Ahead of these phreatic events (from the end of April2015), the seismicity had increased around the central
cones (Fig. 1a; after Yukutake et al. 2017), with several
distinct geodetic signals. Inside Hakone caldera, several
similar earthquake swarm activities have occurred without an associated eruptive event. These swarm activities were detected by a modern seismic network, which
has captured the distribution of earthquake hypocentres
for swarm activities in 2001, 2006, 2009 and 2013 (e.g.
Yukutake et al. 2010, 2011, 2015; the epicentral distributions of some of these swarms are plotted in Additional
file 1: Fig. S1). Such swarm activities could be summarised as being predominantly beneath the central cones© The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made.

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Fig. 1 Topographic map of the study area and computational mesh used in the three-dimensional resistivity inversion. a Topographic map ofHakone volcano, Central Japan, highlighting the spatial distribution of the magnetotelluric observation sites used in this study. The blue, green
and red plus symbols indicate the 2011 AMT observations, the 2013 AMT observations and the 2010 and 2011 WMT observations, respectively. The
topography was extracted from a 10-m DEM provided by the Geospatial Information Authority of Japan. The epicentres of the earthquake swarms
from April to October 2015, as determined by Yukutake et al. (2017), are plotted as black dots. The black dotted line indicates the caldera rim ofHakone volcano. The orange diamonds mark the Owakudani geothermal area, central cones (Mts. Kamiyama and Komagatake) and Mt. Kintoki. The
surface extent of Lake Ashinoko is shown in blue. b Subsurface computational domain without air elements. The origin of the mesh was set at thesea level just beneath Mt. Kamiyama. The tetrahedral lattice in the central portion of the computational domain, covering the core region of Hakone
volcano and encompassing all the MT/AMT sites, was made at a finer resolution. The green, red and blue colours indicate the elements located inland, seawater and lake water, respectively. c Surface mesh around the core region. The tetrahedral lattice was subdivided into an even finer mesharound the AMT/WMT sites

and partially beneath nearby areas, namely the Kojiri area
(located at the northern end of Lake Ashinoko) and thesouthern extent of Mt. Kintoki (located at the northernpart of the caldera rim), although the 2009 swarm activity
was only detected beneath the Kojiri area. These earthquake swarms, which occurred beneath the Kojiri areaand nearby Mt. Kintoki, showed clear planar distributions (e.g. Yukutake et al. 2010, 2011). In addition, immediately after the occurrence of the 2011 great Tohoku
Earthquake, seismicity inside the caldera was remotely
triggered (Yukutake et al. 2013), with an earthquake distribution that included areas of previously low seismicity, as well as the frequent swarms mentioned above (seeAdditional file 1: Fig. S1). Although the geophysical properties around the individual seismogenic zones of theabove-mentioned swarm activities have improved ourunderstanding of the 2015 eruption and the other activities, little is known about the shallow structure beneath
Hakone caldera.
The purpose of this study is to map the three-dimensional electrical resistivity structure, discuss the volcanic
system and characterise the structure of Hakone caldera.
Since resistivity is sensitive to temperature (including
thermal alteration) and the presence of fluids, it is commonly applied to infer the structural setting in volcanicand geothermal environments (e.g. Nurhasan et al. 2006;
Kanda et al. 2008; Komori et al. 2013; Yamaya et al. 2013;
Gasperikova et al. 2015; Seki et al. 2015, 2016; Usuiet al. 2017). In our study area, we obtained magnetotelluric (MT) data in the dense site array (Ogawa et al.
2011; Yoshimura et al. 2012, 2013) to infer the structure of Hakone volcano, with a focus on shallow caldera

Yoshimura et al. Earth, Planets and Space (2018) 70:66

structures. The topographic effects due to the relief ofHakone volcano within the survey area are accounted forin the inversion by applying the code developed by Usui(2015), which treats the model as a series of unstructured
tetrahedral elements, to achieve a realistic representation of surface topography and subsurface resistivity
structures.

Magnetotelluric data
We conducted the audio-frequency magnetotelluric(AMT; 0.35–10,400 Hz) surveys at 39 sites, covering thewhole of Hakone caldera, in December 2011 (Fig. 1a). We
also acquired complementary AMT measurements at
15 sites (including remeasurement sites; Fig. 1a) aroundthe summit area of the central cones (Mts. Kamiyama
and Komagatake) in April 2013. We calculated the MT
responses using only nighttime data (00:00–04:00 localtime) to avoid artificial noise due to electrical power lines,
buildings and leakage currents from DC electric railways.
Furthermore, we applied the remote reference technique(Gamble et al. 1979) to further reduce the noise, where
we selected a simultaneous operation site for each MT
measurement location within the study area as a reference. This ‘mutual’ referencing approach was undertaken
within the survey area because we did not have a dedicated reference site during our AMT campaigns, which
resulted in many ‘reference’ sites (the maximum, minimum and average distances to each reference are 14.3,
1.8 and 7.5 km, respectively). We also included wideband
magnetotelluric (WMT) data from 12 sites (Fig. 1a) thatwere previously acquired across the study area. Although
WMT data have the potential to estimate the MT
responses from 320 Hz to 3000 s, the longer response
periods (< 0.35 Hz) were too noisy in this field, even after
careful treatments for noise reduction. The MTU-5A
and MTU-5 systems (Phoenix Geophysics) were used toacquire the electromagnetic data for the AMT and MT
surveys. The details of these AMT and WMT campaigns
were reported by Ogawa et al. (2011), Yoshimura et al.
(2012) and Yoshimura et al. (2013). Figure 1a shows the
distribution of the sites used in this study, comprising 52
AMT sites and 12 WMT sites. We utilised 20 frequencies, ranging from 0.43 to 320 Hz, for the three-dimensional inversion of all 64 sites, since the frequency rangeof AMT and WMT surveys overlaps from 0.35 to 320 Hz,
and the penetration depth of the higher parts of the AMT
responses (> 320 Hz) is too shallow to be dealt with in thepresent computational mesh. After manual inspectionof data to remove all observations that exhibited large
errors and artificial jumps, 8904 data observations (realand imaginary parts of the responses) were selected forthe inversion.

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Three‑dimensional inversion and modelledresistivity structure
We inverted the full components of the impedance tensors by applying the code developed by Usui (2015). This
inversion code employs the edge-based finite element
method, which uses unstructured tetrahedral elements toincorporate the actual topography into a computationalmesh, and then estimates the subsurface resistivity structure and the distortion tensor of each site. If the standard deviation of the data was less than 5% of the largest
value of the off-diagonal components (error floor), it wasforced to be the error floor value to avoid over-fitting.
We set the computational domain as a
80 km × 80 km × 120 km (including a 40-km air layer)
mesh, with the origin of the mesh set at the sea level, justbeneath Mt. Kamiyama. We gave special consideration to
three inner surfaces within this computational domain,
namely the solid surfaces (land surface, seafloor surface
and bottom of Lake Ashinoko), the seawater surface andthe surface of Lake Ashinoko. During the mesh generation, we first discretised the flat surface and preserved
the lakefront and coast, following the Delaunay triangulation algorithm. Here, the discretised triangles were created at a higher density towards the origin of the domain
and the locations of MT observation sites. The nodes
corresponding to the seafloor and lake were then duplicated and preserved along the Z-axis in reference to theactual depth information. This actual depth information
was taken from the 250-m-bathymetric-mesh data (Kisimoto 2000) and digitised from map image of the Geospatial Information Authority of Japan (GSI). The nodes thatshould be located above sea level (ASL) were then shifted
upward along the Z-axis and adjusted according to the
10-m digital elevation model produced by GSI. The outersurfaces of the computational domain (top, bottom andsides) were also discretised to triangles. The final threedimensional mesh was generated using the TetGen meshgenerator (Si 2015), with the produced mesh shown in
Fig. 1b, c. The mesh in the central portion of the domain,which includes Hakone volcano and the MT site locations, is finer, as mentioned above. We call the central
finer portion, ranging from − 10 to 10 km in the x-direction, − 7 to 7 km in the y-direction and 5 km to the solid
surface in the z-direction, the core region. The total number of nodes and elements in this mesh is 222,716 and1,359,179, respectively. The elements, excluding thoselocated in the air and water regions of the mesh, weregrouped into 27,547 parameter cells, which defined our
unknown model parameters, following the algorithm
described by Usui (2015).
In the initial model, the resistivity values were set to100 Ωm for land, 0.25 Ωm for seawater, 137 Ωm for lakewater, which is the measured value of Hirano et al. (1982),

Yoshimura et al. Earth, Planets and Space (2018) 70:66

and ­109 Ωm for air. The resistivity value of each elementthat was situated in sea, lake and air was fixed during theiterations. The inversion code seeks the model vector thatminimises the objective function, which is a weighted
sum of the data misfit, model roughness and strength of
the galvanic distortion. The trade-off parameters α2 andβ2 are constant factors of the model roughness and thestrength of the galvanic distortion, respectively. Here,
we used a fixed value of β2 = 0.01 since several reports
had demonstrated that such a small trade-off parameter
was sufficient for the MT inversion (e.g. Sasaki and Meju
2006; Avdeeva et al. 2015; Usui et al. 2017). However, we
ran six inversions with various values of α2 (100, 31.6, 10,
3.16, 1.0 and 0.316) and determined the performance ofeach model in terms of both its fit to the various parts ofthe dataset and the differences with the other models. We
chose α2 = 1.0 as the preferred trade-off parameter basedon this analysis. After 14 iterations, the objective function changed by less than 1% of the previous iteration
value, yielding our best-fit model to the MT observations,with an RMS (root-mean-square) misfit that decreased
from 52.14 (initial model) to 4.95 (final model: iteration
14). Figure 2 compares the apparent resistivity and phasemaps of the observed data and the calculated responses
from the best model. The apparent resistivity and phasewere calculated from the sum of the squared elements’invariant impedance (Szarka and Menvielle 1997). Thereis a good agreement between observed and calculated
responses.
To evaluate the sensitivity of the best model, we analysed the absolute sensitivity and sensitivity density distributions. The absolute (AS) was defined by
N sensitivity∂d Usui (2015) as si = j d  σ1j ∂ logj ρi , where dj, σj and ρidenote the jth data observation, the standard deviationof the jth data observation and the log-resistivity of theith parameter cell, respectively. The absolute sensitivity
is essentially the summation of each column of the sensitivity (Jacobian) matrix. To reduce the bias due to large
elements, Schwalenberg et al. (2002) divided AS by thevolume of the respective element, and we call the resulting sums the absolute sensitivity density (ASD). The AS
and ASD histograms are shown in Fig. 3, which reveals
characteristic distributions, with a trend change at ­101.2
in the AS histogram and a bimodal distribution whose
two peaks are sectioned at ­10−7.5 in the ASD histogram.
Most of the elements inside the core region (grey columns in Fig. 3) have a relatively high sensitivity. We thus
defined the lower limits of the acceptable sensitivity as­101.2 in AS and ­10−7.5 in ASD. All elements above thesesensitivity limits were visualised in the results as sensitiveand considerable parts.
Figure 4 shows vertical cross sections through the bestfit three-dimensional resistivity model along several N–S

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and E–W profiles. The locations of the cross sections aredenoted at the top of each panel according to the coordinate grid shown in Fig. 1a. Several horizontal slices of
the resistivity structure are also shown in Fig. 5, with thesea level altitude denoted at the top of each panel. Four
clearly defined conductors are present in the final model.
One is a bell-shaped structure that is located just beneaththe central cones. Two conductors exist either near thebell-shaped conductor or laterally protrude from its base.
The fourth conductor is located beneath the northernedge of the caldera. We discuss the implications of thesefour conductors in the following section. While we recognise that there are also several small conductive patches
in the outer part of the core region, these four conductors meet our current goal of characterising the shallow
structure beneath Hakone caldera and are thus the focus
of our discussion and interpretation.

Discussion and conclusions
We first compare our model with the two-dimensional
NW–SE image proposed by Ogawa et al. (2011). It isclear that the two results share certain similarities in a
broad sense, particularly the observation of the conductor beneath the northern end of the Hakone caldera thatdips to the northwest, which is further supported by theseismic velocity structure of the region (Yukutake et al.
2015). However, in the central part of our study area,
which corresponds to the southern end of the Ogawa
et al. (2011) profile, a significant and previously unidentified feature was discovered inside the caldera in ourmodel, because the dense array data of the present study
enabled us to resolve the fine and lateral heterogeneouselectrical structure there.
We then interpreted the major above-mentioned conductors that were identified in our model based on thenature of the modelled resistivity anomalies and theresults of previous studies. A significant conductor (< 10Ωm) was detected beneath the central cones (Mts. Kamiyama and Komagatake). This conductor has a cap-likeshape in vertical section (e.g. Fig. 4b, c, f ) and a doughnut
shape in horizontal section (e.g. Fig. 5b), thus possessing a stereoscopic bell shape. This bell-shaped conductor
surrounds a relatively resistive body (10–100 Ωm). Sucha bell-shaped conductor beneath the central cone or geothermal/fumarolic area has been previously detected atother volcanoes (e.g. Nurhasan et al. 2006; Kanda et al.
2008; Komori et al. 2013; Yamaya et al. 2013; Usui et al.
2017). With reference to the conceptual model of a geothermal system described by Pellerin et al. (1996), weinterpret that the bell-shaped conductor and the resistive body represent an impermeable layer consistingof altered clays and a bounded hydrothermal reservoir,
respectively. Ohba et al. (2011) reported a temperature of

Yoshimura et al. Earth, Planets and Space (2018) 70:66

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Fig. 2 Apparent resistivity and phase maps for the observed data (Obs.) and calculated responses (Cal.) from the best-fit resistivity model (Figs. 4, 5)
for four frequencies (1.17, 6.9, 18.8 and 115 Hz). The responses shown here were calculated from the sum of the squared elements’ invariant imped‑
ances. See the text for more details. The dotted line indicates the caldera rim, and the shaded region marks the surface extent of Lake Ashinoko

Yoshimura et al. Earth, Planets and Space (2018) 70:66

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Fig. 3 Histograms of the absolute sensitivities (left panel) and absolute sensitivity densities (right panel) for the core region (grey) and exterior(white). The bins cover 0.1 intervals. The sensitivity density is divided by the volume of the corresponding element to avoid biasing from large
elements. The setup criteria ­(101.2 in absolute sensitivity and ­10−7.5 in sensitivity density) of the lower limit of relatively high-sensitive elements areindicated by thick lines

Fig. 4 Vertical cross sections of the three-dimensional resistivity structure. Only the elements for which the model results exceeded the sensitivity
and sensitivity density criteria (vertical black lines in Fig. 3) are plotted. Only the subsurface elements are shown here. a–d cross the study area inthe E–W direction at x = 2, 1, 0 and − 1 km, respectively. e–h cross the study area in the N–S direction at y = 1, 0, − 1 and − 3 km, respectively. The
inverted black triangles indicate the AMT/MT measurement sites located within ± 1.5 km of each profile. The earthquake hypocentres determinedby Yukutake et al. (2017) that occurred within ± 0.25 km of each profile are also plotted as black dots. See Fig. 1 for the profile locations, AMT/WMT
sites and earthquake hypocentres

Yoshimura et al. Earth, Planets and Space (2018) 70:66

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Fig. 5 Horizontal slices of the three-dimensional resistivity structure for various depths. Visualised elements are selected in the same manner as
in Fig. 4. a–d show the XY planes at z = − 0.5 km (0.5 km above sea level: ASL), z = 0.0 km (sea level: SL), z = 0.5 km (0.5 km below sea level: BSL)
and z = 1.0 km (1.0 km BSL), respectively. Inverted black triangles represent the locations of the AMT/WMT sites. The earthquake epicentres that
occurred within ± 0.125 km of the cutting-plane are shown as black dots. The present caldera rim of Hakone volcano is indicated by the dottedblack line

Yoshimura et al. Earth, Planets and Space (2018) 70:66

260 °C at the bottom of a borehole (500 m depth) in the
Owakudani geothermal area, which corresponds to the
top of the resistive body inside the bell-shaped conductor, where x = 1, y = 0 and z = − 0.5 km (0.5 km ASL) in
our coordinate system. This temperature estimation supports our interpretation, because the smectite-rich zoneor the transition zone from smectite to illite/chlorite generally occurs in the 100–250 °C temperature range andpossesses both a low resistivity and a low permeability(e.g. Ussher et al. 2000; Gasperikova et al. 2015). Comparison of this resistivity structure with the distributionof earthquake swarms in the region (Yukutake et al. 2017)highlights the good agreement between the upper limitof seismicity beneath the central cones and the bottom of
the low-resistivity bell-shaped conductor (Fig. 4b, c, f ).
While considerable seismic activity occurred below thisconductor (namely inside the relatively high-resistivitybody), there were few earthquakes within the conductive body, which supports the presence of a hydrothermally altered zone here. Furthermore, the fact that mostof the earthquakes were located in the relatively highresistivity body suggests that this body consists of brittle
rock at temperatures below 400 °C. Enhanced volcanic
activity (e.g. increasing heat supply from the deeper part)may cause the volcanic fluids to flow through the resistive body and promote brittle failure of the structure. It ishighly probable that the shallower overlying bell-shaped
conductor plays the important role of acting as a cap orseal that restricts the upwelling of volcanic fluids. Thus,
several observations that target the base of the bellshaped conductor can help us understand the evolutionof Hakone volcanism, particularly the stage of preparation for phreatic eruptions.
Other significant structural aspects within the caldera
region are two large buried conductors: one beneath theGora area (x = 1, y = 3 km in Figs. 1, 5) and the otherbeneath the Kojiri area (x = 1, y = − 3 km in Figs. 1, 5),which either exists near the bell-shaped conductor orlaterally protrudes from its base. The conductor locatedbeneath the Gora area broadens and deepens, possessing
a bowl-like or funnel-like shape. Mannen (2014) reported
a buried caldera structure around the Gora area thatwas filled by lacustrine sediments and porous tuffaceousrock, as evidenced by geological surveys, borehole explorations and a gravity anomaly analysis. Mannen (personalcommunication) suggests that three more small buried
calderas (including the Kojiri area) occur within the present Hakone caldera. Furthermore, there are many hot
springs in the Gora area, whose high-temperature waters
possess high concentrations of sodium chloride. Theselines of evidence lead us to interpret the large conductors
beneath the Gora and Kojiri areas as porous media saturated by high-salinity hot spring waters.

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Earthquake swarm activity in the Kojiri area provides additional insights into the structural significanceof this buried conductor and its immediate surrounds.
Several linear clusters of swarms have been observed in
the Kojiri area between 2001 and 2015, surrounding thebowl-shaped conductor (Fig. 4b, h, and Additional file 1:
Figs. S2b and S2d), whereas few earthquakes have beenrecorded in the Gora area. Furthermore, the seismicity
beneath the southern extent of Mt. Kintoki, which waspossibly remotely triggered by the 2011 great Tohoku
earthquake (Additional file 1: Fig. S1), was also observed
along the edge of the buried conductor in this area (Additional file 1: Fig. S2c, 5 km north of the origin). Yukutake et al. (2011) suggested that the earthquake swarms
observed around the Kojiri area in 2009 were activatedby fluid flow along thin plane-like zones. The earthquake
swarm beneath the southern extent of Mt. Kintoki also
showed clear linear alignments (Yukutake et al. 2010).
Since the bowl-shaped conductor beneath the Kojiriarea is likely indicative of a buried structure containing
saturated fluids, a series of weak zones may have evolved
along the outer boundary of this structural resistivity
contrast. However, the spacing of the observation sites
is insufficient to explore such thin structures. Additional
MT measurements at a closer spacing are required toimage the subsurface structures surrounding the linear
clusters of earthquake swarms beneath Hakone volcano.

Additional file
Additional file 1. Epicentral distributions of swarm activities in 2001,
2009, 2011, 2013 and 2015; and vertical cross sections of the obtained
resistivity structure overlain by the hypocentres of such swarm epochs.

Abbreviations
AMT: audio-frequency magnetotelluric; WMT: wideband magnetotelluric; ASL:
above sea level; SL: sea level; BSL: below sea level; RMS: root-mean-square.
Authors’ contributions
RY led the AMT acquisition, data analysis, inversions and discussions for thisstudy. YO was responsible for the WMT survey. YO, YY, WK, SK, HH, TG, RH, MH,
TY, MK, SK, TH, TS, YY and MT participated in the field work. YU assisted in
the inversions. All authors contributed to preparation of the manuscript. All
authors read and approved the final manuscript.
Author details
1
Disaster Prevention Research Institute, Kyoto University, Gokasyo, Uji,
Kyoto 611‑0011, Japan. 2 Volcanic Fluid Research Center, Tokyo Instituteof Technology, Ookayama 2‑12‑2, Meguro‑ku, Tokyo 152‑8551, Japan. 3 Hot
Springs Research Institute of Kanagawa Prefectural Government, Iriuda 586,
Odawara, Kanagawa 250‑0031, Japan. 4 Aso Volcanological Laboratory, Insti‑
tute for Geothermal Sciences, Graduate School of Science, Kyoto University,
Kumamoto 869‑1404, Japan. 5 Geological Survey of Japan, National Instituteof Advanced Industrial Science and Technology, Tsukuba 305‑8567, Japan.
6
Present Address: Geothermal Energy Research & Development Co., Ltd.,Tokyo 104‑0033, Japan. 7 Graduate School of Engineering, Kyoto University,
Kyoto 615‑8540, Japan. 8 Graduate School of Science, Kyoto University,
Kyoto 611‑0011, Japan. 9 Graduate School of Engineering, Tottori University,
Tottori 698‑8552, Japan.

Yoshimura et al. Earth, Planets and Space (2018) 70:66

Acknowledgements
We thank the landowners who kindly provided access to their properties dur‑ing the AMT surveys, as well as the national, prefectural, city and town offices
for their support. The WMT data used in this work were obtained as part of theintegrated research project for the Kannawa-Kozu-Matsuda fault zone, which
was supported by the Ministry of Education, Culture, Sports, Science andTechnology (MEXT) of Japan. We are grateful to Kazutaka Mannen for valuablecomments on buried structures and the geology of Hakone caldera. Valuablecomments from two anonymous reviewers helped to improve the manu‑
script. We thank the Disaster Prevention Research Institute, Kyoto University,and the Tokyo Institute of Technology for lending the MT equipment used in
the AMT surveys. Most of the figures were prepared with the Generic Mapping
Tools software (Wessel and Smith 1998).
Competing interests
The authors declare that they have no competing interests.
Availability of data and materials
The data that support the findings of this study are available upon requestfrom the corresponding author.
Consent for publication
Not applicable.
Ethics approval and consent to participate
Not applicable.
Funding
This study was partially funded by the Disaster Prevention Research Institute,
Kyoto University.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in pub‑lished maps and institutional affiliations.
Received: 29 December 2017 Accepted: 19 April 2018

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