NUMO-TR-13-03

Spatial and Temporal
Distribution of Future
Volcanism in the Chugoku Region
A partial application of NUMO’s ITM and Topazprobabilistic tectonic assessment methodology

July 2013
Nuclear Waste Management Organization of Japan (NUMO)

NUMO-TR-13-03

Spatial and Temporal
Distribution of Future
Volcanism in the Chugoku Region
A partial application of NUMO’s ITM and Topazprobabilistic tectonic assessment methodology

Charles Connor1, Laura Connor1, Olivier Jaquet2, Laura Wallace3, Koji
Kiyosugi1, Neil Chapman4, Steve Sparks5, and Junichi Goto6
1

University of South Florida, USA
In2Earth Modelling Ltd, Switzerland
3
GNS Sciences, New Zealand
4
MCM Consulting, Switzerland
5
University of Bristol, UK
6
NUMO, Japan
2

July 2013
Nuclear Waste Management Organization of Japan (NUMO)

2013 年 7 月

初版発行

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各章の和文要約
1

序論
NUMO は，火山活動や断層活動などの自然現象の地層処分システムに対する影響を確率論的に評価するための手法として，ITM1手法(Chapman, et al., 2009)と TOPAZ2手法(Chapman, et al., 2012)を開発してきた。ITM 手法は主に将来 10 万年程度の期間を対象とし，火山の位置や地球物理データなどの情報やモデルに基づき，広域的な領域中の 5km 四方の領域で生じる事象の発生確率を評価する。TOPAZ 手法は不確実性が大きくなる将来 10 万年を超える超長期を対象とし，プレート運動や広域テクトニクスの
変遷シナリオ(RES 3 )，それに伴い 5km 四方のサイトで生じる事象の変遷シナリオ(SES4)，地層処分システムへの影響に関するシナリオ(IS5)を構築する。それらのシナリ
オをロジックツリーに集約し確率論的な評価を行う。これらの手法の信頼性をより高めるため，単成火山を含む多様な火山活動が生じている中国地方を対象に， 手法の一部である RES の構築や火山発生確率の評価方法に関する検討を行った。
2

テクトニクスと火山活動
既存文献に基づき，中新世から現在までの中国地方のテクトニクスと火山活動の特徴

について取りまとめた。日本海拡大後の 12Ma 頃から，中国地方全域でアルカリ玄武岩の単成火山群の活動が生じた。約 4Ma から現在までの火山活動は，フィリピン海プレートの先端付近に限定され，アルカリ玄武岩とアダカイトを生じている。これには，プ
レートの沈み込みに伴いマントルの上昇流が遮られアルカリ玄武岩の火山活動の場が限定されるとともに，プレートの先端が融解しアダカイトが生じたとの解釈がある。第四紀には，大山，三瓶，大江高山などの複成火山や，阿武，神鍋，横田‐松江，青野山などの単成火山群が活動した。これらの分布は，地震活動が比較的活発な領域や，重力データから解釈される中央部の厚い地殻が北に向って薄くなる遷移帯と整合的である。
3

広域変遷シナリオ(RES)の構築
フィリピン海プレートの運動と火山活動の関連性に基づき，将来 100 万年までの時間枠における三つの RES を構築した。RES1 は，フィリピン海プレートの運動様式が現在と変わらず先端部が融解し続けることにより，プレートの位置・形状が現在と変わらず，火山活動の傾向も変わらないというシナリオである。RES2 は，フィリピン海プレートが現在と同じ運動様式で沈み込み続けることにより，プレートの先端位置が北上・沈降し，火山活動の場も北に移動するというシナリオである。RES3 は，マントル上昇
流の減衰あるいはマントルウェッジとの粘性摩擦の低下によりフィリピン海プレート

1 International Tectonics Meeting（日本のテクトニクス関連事象の調査・評価に関する国内外の専門家の認識共有・

情報発信の場として NUMO が主催してきた会議体）の略。

2 Tectonics Of Preliminary Assessment Zones の略。
3 Regional Evolution Scenario の略。
4 Site Evolution Scenario の略。
5 Impact Scenario の略。

i

の沈み込み傾斜が急になり，日本海沿岸域で火山活動が活発化するシナリオである。
4

単成火山群の活動頻度
中国地方の単成火山群の活動の期間やピークはそれぞれ異なることから，確率論的評

価に際しては，火山群ごとに活動頻度を設定する必要がある。このため，活動年代デー
タの量・品質および解釈・選択に伴う不確実性を考慮に入れた活動頻度の評価方法を考案した。この手法では，誤差範囲を考慮した年代値の選択，噴出物の年代設定，活動史の整合性確認，活動頻度の算出という四つのプロセスのモンテカルロ・シミュレーショ
ンを通じて，活動頻度の時間変遷と不確実性の幅を示す。この手法により阿武，神鍋，
横田‐松江，青野山の単成火山群の活動頻度を算出し，平均値は 2 オーダー程度の差があること，活動の時間変遷のパターンがそれぞれ異なることがわかった。
5

将来の火山発生確率
上述の RES1 のもとに SES が生じる可能性を設定するために必要な火山発生確率を，

ITM 手法のカーネル法6とコックスプロセス法7により算出した。カーネル法では，将来10 万年までについては，単成火山群ごとに設定した活動頻度に基づき発生確率マップを作成した。発生確率が 10-4～10-2 の阿武‐青野山，神鍋，横田‐松江の三つのクラス
ターが認識され，前者二つが後者に比べてより高い発生確率を示す。将来 10 万年～100
万年については，単成火山群の発生頻度が変動する可能性を考慮し，複成火山も含む全ての火山の広域的な活動頻度に基づき発生確率を算出した。北東方向に伸びる確率の高い幅広いゾーンが存在する。この発生確率は，RES2 では活動場の北上に伴い減少し，RES3 では日本海沿岸域における活動頻度の上昇に伴い増加すると考えられる。コック
スプロセス法では，将来 10 万年までの期間について，重力と磁気のデータを考慮した
火山発生確率マップを作成した。カーネル法と同様に三つのクラスターが認識され，それ以外の大部分の領域の発生確率は 10-4 以下であることが示された。
6

評価方法の検討
諸外国の安全規制や放射線以外の安全評価の事例を参考に，処分事業のリスクとして受け入れられない確率の目安値を仮設定し（例えば，将来 1 万年間は 10-5， 10 万年間
は 10-4 など），上述の火山発生確率マップの評価を行った。その結果，第四紀火山の周辺以外の地域は，将来 1 万年間は火山活動によるリスクは極めて低いことが示された。
10 万年間についても概ねリスクは低いが，様々な不確実性を考慮するとより詳細な検討が必要な地域が存在すること，そして 10 万年以降については，多くの地域で目安値を超えると評価された。以上の検討から，ITM 手法と TOPAZ 手法の結果に適切な目安
値を適用することにより，より客観的・定量的なサイト評価が行える見通しが得られた。

6 周囲の火山までの距離や活動頻度に基づき発生確率を算出する米国ユッカマウンテン等で用いられた手法。
7 火山の分布密度と地球物理データ等との関連性を考慮に入れたシミュレーションに基づき発生確率を算出する手法。

ii

Contents
1

Introduction ..........................................................................................................................1
1.1

The ITM methodology: probability – the likelihood of future tectonic impacts on arepository ................................................................................................................................1
1.2
2

3

Background to and objective of the Chugoku study ......................................................5

Tectonics and Volcanism of the Chugoku Region ...............................................................7
2.1

Tectonic and volcanic history of the Chugoku region from Early Miocene to 2 Ma ......7

2.2

Tectonics from 2 Ma to the present day ......................................................................11

2.3

Quaternary volcanism in the Chugoku region .............................................................14

2.4

Origin of Quaternary magmas and temporal patterns of activity .................................18

2.5

Relationship of gravity and magnetic data to Quaternary volcanism ..........................21

Regional Evolution Scenarios for Chugoku .......................................................................28
3.1

RES 1: The locus of the northern edge of the subducting PSP stays in its present-day

location..................................................................................................................................29

4

5

3.2

RES 2: The PSP maintains its geometry and present-day NNW migration ................30

3.3

RES 3: The subducting PSP steepens with time ........................................................32

3.4

Implications of all RES for future rock deformation and volcano/fault interactions .....34

Recurrence Rates of Monogenetic Volcanism in Chugoku ...............................................35
4.1

Sources of uncertainty.................................................................................................35

4.2

Procedure for estimation of recurrence rate ................................................................37

4.3

Results of recurrence rate estimation .........................................................................39

Spatial Likelihood of Future Volcanism ..............................................................................44
5.1

Kernel density estimation of spatial likelihood.............................................................44

5.1.1

Procedure for estimating probability in Chugoku ..................................................45

5.1.2

Results ..................................................................................................................47

5.1.3

Relationship of spatial models to RES models .....................................................51

iii

5.2

5.2.1

Conceptualisation .................................................................................................52

5.2.2

Model development ..............................................................................................52

5.2.3

Datasets ................................................................................................................54

5.2.4

Hazard estimation .................................................................................................55

5.2.5

Perspectives and recommendations ....................................................................59

5.3
6

Estimation of spatial density using a Cox process that assimilates geophysics .........51

Hazard assessment including polygenetic volcanoes .................................................59

Commentary.......................................................................................................................64
6.1

10,000 year high hazard period...................................................................................65

6.2

100,000 year period ....................................................................................................66

6.3

1 Myr period.................................................................................................................66

6.4

Conclusions .................................................................................................................67

References ...............................................................................................................................68
Appendix: The Chugoku Volcanism Database.........................................................................74
1

Relationship between radiometric age determinations and volcano clusters ...............752

Abu monogenetic volcano group ...................................................................................75

3

Aono-yama monogenetic volcano group.......................................................................76

4

Yokota-Matsue region ...................................................................................................76

5

Kannabe-Genbudo-Mikata-Oginosen region ................................................................76iv

1 Introduction
NUMO is responsible for the siting, development and operation of deep geologicalrepositories for high-level waste (HLW) and transuranic wastes (TRU) in Japan. The
process is expected to take at least 15 years to reach the point of repository
construction. During the period before this, NUMO will need to evaluate sites thatemerge from the ‘volunteer process’ (whereby local communities have been invited tovolunteer to be considered as potential hosts for the repository) and select a preferredsite. This evaluation will initially involve surface-based and then underground sitecharacterisation work. Underground characterisation work will only take place at thepreferred site.
Prior to the surface-based investigations, volunteer sites will first have to pass a test ofgeneral suitability and NUMO will then carry out a detailed, literature-based
preliminary evaluation of suitability prior to accepting the sites as ‘Preliminary
Investigation Areas’ (PIAs). Because Japan lies in such a tectonically active region of
the world on the Pacific Rim (the so-called ‘ring of fire’), a key aspect of all thesesteps is consideration of the susceptibility of a site to future tectonic activity andtectonically driven processes and events. For repository safety evaluation, long-term(thousands of years) post-closure tectonic processes leading to progressive
perturbations of the repository environment, and possibly to the initiation of
disruptive tectonic events at repository depth, are the focus of these evaluations,although potential impacts of other tectonic events during the multi-decade, initial
operational period also have to be taken into account in many locations. The
importance of this requirement was dramatically reinforced by the impacts of the
March 2011 Tohoku post-earthquake tsunami on the coastal Fukushima nuclear
power plant.
The present study is concerned with repository susceptibility to post-closure tectonic
impacts over many thousands of years. In this respect, the potential for long-term
volcanic and rock deformation impacts on a repository site needs to be considered inparticular, at each stage of NUMO’s siting programme. While the nationwide
evaluation factors for qualification (EFQs) for PIA acceptance are designed to remove
clearly unsuitable sites from consideration, they cannot guarantee that, over the nexttens of thousands of years, the risks of tectonic hazard for a chosen PIA will be
acceptable. This is because large parts of Japan that are potentially suitable for siting
are directly affected to varying extents by rock deformation, the peripheral impacts of
volcanic activity or the possibility of new magma intrusion or volcanic activity. The
EFQs were only intended as preliminary screening guidelines to prevent obviously
poor candidates from entering the siting process.

1.1 The ITM methodology: probability – the likelihood of
future tectonic impacts on a repository
NUMO recognised that an integration of additional and more refined techniques
would be required to evaluate sites that pass the EFQ test, so that they could have aclear idea of the likelihood and potential impacts of tectonic events and processes foreach PIA. NUMO’s ITM project developed such a methodology (the ‘ITM
methodology’), based on state-of-the-art approaches used internationally and1developed and extended for the specific purposes of NUMO and the specificconditions of Japan.
The ITM methodology is essentially probabilistic in nature. A probabilistic approach
was seen by the ITM expert group as the only realistic means of addressing theuncertainties in predicting possible hazards when there is marked variability in thespatial distribution, timing, intensity and style of the volcanic and deformational
events and processes being evaluated (for convenience, in this report we frequently
group these together within the general term ‘tectonic events and processes’). The
consequences of not applying probabilistic hazard assessments to siting and design
considerations for tectonic hazards were highlighted by the Fukushima disaster.
During the course of the ITM project, both NUMO and the Japanese regulatory
agencies were considering how best to handle the evaluation of low probability
disruptive events (e.g. volcanic intrusion, fault rupture) and deformation processes
that are discontinuous in time and magnitude in response to continuous regional strain,when carrying out safety assessments of geological repositories for radioactive waste.
Essentially, two approaches have been adopted internationally to address thissituation:
To calculate the health risk 1 to people in the future by combining the probabilityof a disruptive event occurring with its radiological consequences in terms of
releases from a repository: simply, risk = probability x consequence. With thisapproach, regulatory standards or targets can be defined in terms of risk to anindividual.



To consider the impacts of a disruptive event and calculate the radiological doses 2
to people in the future and then, separately, to discuss the likelihood that thismight happen (the so-called ‘disaggregated’ approach). With this approach,separate regulatory targets for radiation doses might be set for events (orscenarios) with different degrees of likelihood (often expressed qualitatively, e.g.
‘likely’, ‘less likely’, ‘highly unlikely’).

In either approach, an appreciation of probability is essential: in the first ‘risk
approach’, a sound quantitative estimate will provide a more confident estimation ofrisk; in the second, some form of quantification of ‘likelihood’ is needed to decide
which category to place an event or scenario into.
The probabilistic approach developed by the ITM is based on, and strongly supportedby, deterministic models of the underlying tectonic processes that lead to magma
intrusion, volcanism and rock deformation.
The ITM methodology can be applied at three important stages of NUMO’s
repository siting programme:


SITING STAGE 1: during the literature survey (LS) stage when potential
PIAs are being assessed. The ITM methodology will use currently available
information to allow comparison of sites in terms of confidence that they arelikely to prove acceptable with respect to tectonic impacts.

1

Health risk is normally defined as the risk of death or serious genetic effects.
Of course, a radiological dose can also be expressed in terms of health risk, by applying accepted
dose-to-risk conversion factors.
2

2



SITING STAGE 2: during the planning of the PIA site investigations, toidentify geoscientific information that will be needed to refine the Stage 1
analysis.



SITING STAGE 3: at the point where PIAs are being evaluated and comparedin order to select a preferred site (or sites) for detailed investigation (as DIAs).

The ITM project was mainly concerned with Stages 1 and 2 and focused on
evaluating comparative hazards of small (25 km2) areas within a regional or subregional context of 100,000 to 10,000 km2. This is partly because the project
originally developed to compare several possible alternative volunteer sites that mightarise within a region. However, it is clear that regional to sub-regional scaleassessment of tectonic hazard will also be required even for single sites.
Application of the methodology in Siting Stage 3 will be several years in the futureand it is expected that it will be most efficient to carry out any necessary
updates/refinements on a region-specific basis during the PIA investigations when
NUMO has narrowed down to a group of sites. The overall structure of the ITM
methodology is described in Chapman et al. (2008) and consists of:

assembling nationally available data and alternative models of the nature,causes and locations of tectonic processes and events;using probabilistic techniques to evaluate the likelihood and scale of futuretectonic processes and events, shown as a function of their type andgeographical distribution;feeding information on these potential likelihoods and impacts to NUMO’s
performance assessment team so that feedback can be provided on repository
performance under tectonic stress;

providing clearly justified and traceable input to decision-making onconsequent site suitability.

For convenience, the methodology for rock deformation and volcanic hazard
assessment has been applied as two parallel tasks. This recognises the fact that,
although the concept of each approach as shown above is similar, in some parts of themethodology they differ significantly in detail. Consequently, it was found that two
teams with different specialities (structural, geophysics and tectonics specialists;
volcanologists) worked efficiently in parallel. At the time of the ITM methodology
development it was noted that the two ‘discipline’ teams would need to integrate theirwork efficiently, as there are clear overlaps in the processes being evaluated (e.g.
magma intrusion has an impact on rock stress regimes and vice versa). It wasconsequently advised to ensure that such integration be carried out effectively whenthe methodology is applied to ‘real’ sites.
The methodology was first tested during its development by means of a Case Study of
the Tohoku region of northern Honshu (Chapman et al., 2009a) and then further
developed and tested by application to a second Case Study region covering the wholeof Kyushu (Chapman et al., 2009b). The complete methodology is described in thelatter report and is not presented again here in detail. The Tohoku Case Study looked
into the varied strain response of the crustal plate to subduction of the Pacific Plate(the key current tectonic driver for much of Japan) and the mechanisms that underlie
the apparent clustering of Quaternary volcanoes in much of Honshu. The Kyushu
3Case Study region is among the more dynamic and rapidly changing plate boundaries
in the world, with the tectonic situation being intrinsically more complex than in
Tohoku. The various modes of strain accommodation in Kyushu are not yet fully
understood and the style of volcanism and geochemistry of the magmas varies
considerably across Kyushu, compared to the reasonably simple arc volcanism in
Tohoku. Predictability of future volcanism and faulting in Kyushu is less certain
because the geological setting is evolving more rapidly. The fundamental assumption
in Tohoku that the plate boundary configurations and plate motions influencing rockdeformation and volcanism are relatively stable over periods up to a million years are
not appropriate in Kyushu. Consequently, these two Case Studies allowed
development and testing of the ITM methodology under significantly different
tectonic conditions.
Following the completion of the ITM project, NUMO asked the expert team involved
to look at the possibilities and constraints of making forecasts of the likelihood andnature of tectonic impacts for longer periods into the future, from 100,000 years out toone million years. The ‘TOPAZ’ project was developed to see how the ITM
methodology could be extended for this purpose. The approach being developed is anextension of the concepts developed in the preceding ITM project. Although aimed at
looking at very long times into the future, it is important to recognise that theapproach is not limited to this period and can be deployed for the whole period overwhich hazard assessment is required. The main steps of the TOPAZ methodology (seeFigure 1.1) involve the development of alternative conceptual models of how thetectonic situation in a region might develop in the future and attaching expert degrees
of belief to these alternative ‘Regional Evolution Scenarios’ (RES) using a formal
expert elicitation methodology. These, in turn, are used to develop ‘Site Evolution
Scenarios’ (SES), which describe how an RES might ‘play out’ at a specific location
within the region being evaluated.

Figure 1.1: The main steps of the TOPAZ methodology.
4

The ITM Kyushu Case Study (KCS) illustrated the importance of considering
alternative framework models of evolution, especially in complex regions. In the KCS,
the time period being assessed was 100,000 years but, owing to the complexity of thetectonic regime (compared to Tohoku, for example), regional evolution scenarios
were considered, even for this timeframe. Thus, the KCS initiated thinking on the
RES approach for TOPAZ and also led the expert team to consider that the TOPAZ
methodology could be especially useful for regions with complex tectonics when
considering any period of time in the future.
The likelihood of monogenetic volcanism in the Chugoku region of SW Honshu wasselected for applying the ITM methodology and developing the TOPAZ methodology
in a tectonically complex region. The ITM project had already looked at part of thisregion (the Abu volcanic field) in a preliminary manner and had touched on themargins of the area in the region considered in the KCS. Monogenetic volcanism has
been considered a particularly difficult issue with respect to forecasting, owing to theisolated, single eruptive events that occur in one place without necessarily any repeat
activity – compared to the spatially focused eruptions of polygenetic volcanism.

1.2

Background to and objective of the Chugoku study

Monogenetic volcanoes form when magma ascends along fractures through the crust,
forming dikes and surface eruptions. These volcanoes are characterised by a single
episode of eruptive activity that may last from weeks to years and, in rare cases, for
hundreds of years. During this activity a volcano is formed, such as a cinder cone,maar, tuff ring, dome or fissure-fed lava flow. In rare cases, shield volcanoes may
also be monogenetic. Unlike polygenetic volcanoes, once eruptive activity ceases atmonogenetic volcanoes, these volcanoes never erupt again. Rather, renewedmagmatic activity involves the propagation of a new dike or dike swarm through thecrust and formation of a new monogenetic volcano. Thus, over time, groups ofmonogenetic volcanoes are created. These monogenetic volcano groups, also referred
to as volcanic fields, typically consist of tens or hundreds of volcanoes distributed
over thousands to tens of thousands of square kilometres.
In general, average eruption rates in monogenetic volcano groups are very low
compared to single polygenetic volcanoes. Individual eruptions commonly involve<0.1 km3 magma and eruption rates are commonly 10-4 to 10-3 eruptive events per
year. From a volcanic hazard perspective, the problem is one of forecasting thepotential for new monogenetic volcanoes to form in the site region during a longassessment period, accounting for the dispersed nature of monogenetic volcanism andits generally low recurrence rate. This is different from issues associated withpolygenetic volcanism, which involves eruptions from existing volcanoes affecting
the site, and the extremely rare formation of new polygenetic volcanoes.
Monogenetic volcanism has received a great deal of attention in HLW siting
investigations in the US, because Yucca Mountain, the once proposed site for a HLW
repository, is located at the margins of an active volcanic field. A variety of methods
for assessing monogenetic volcanic hazards at Yucca Mountain were developed overdecades of siting activities. In addition, volcanologists worldwide have consideredmonogenetic volcanic hazards, particularly to urban areas such as Mexico City andAuckland, which are built in monogenetic volcanic fields.
The objective of this study has been to use elements of the combined ITM and
TOPAZ methodologies and the specific development work carried out on assessing
5monogenetic volcanism to estimate volcanic hazards due to monogenetic volcanismin the Chugoku region. This involves estimating the probability that monogenetic
volcanism will occur within the region, expressed as the ‘spatial density of volcanism’,and estimating the probability that monogenetic volcanism will occur within different
timeframes of interest.
Estimation of these probabilities involves using a variety of different models and sitespecific information about the volcanic field of interest, starting with the developmentof RES for the region. The goal of estimating spatial density in the context of volcanic
hazard assessments for a HLW repository site is to determine the likely locations of
future igneous events, or the probability of an igneous event at a specific location,
given that such events occur within the region. This report describes how suchforecasts have been made for the Chugoku region and the results of these assessments.
This project was not intended as a complete application of the two ITM-TOPAZ
methodologies. Nevertheless, the exercise is considered sufficiently robust to give areasonable forecast of the likelihood and consequent importance of monogenetic
volcanism in the Chugoku region, particularly in the critical first 10 kyr period after
repository closure, when HLW has its highest hazard potential. It will thus assist
NUMO in extending any siting decisions that would otherwise be based solely on the
EFQs. The elements of the methodologies that have not been deployed include:

spatial density modelling for all of the RES identified;

complete integration with rock deformation and strain field controls of
volcanism;use of formal expert elicitation to identify preferred RES models;

SES have not been developed for specific sites within the region:a full appraisal of how the spatial density and recurrence rate of volcanism
might evolve over periods of 100 kyr to 1 Myr.

6

2 Tectonics and Volcanism of the Chugoku Region
This section introduces the tectonic and volcanic setting of the Chugoku region toprovide the context for the subsequent analyses.

2.1 Tectonic and volcanic history of the Chugoku region
from Early Miocene to 2 Ma
Tectonic deformation and volcanism in the Chugoku region since the Miocene havebeen strongly influenced by NNW subduction of the Philippine Sea Plate (PSP)beneath the southwest Honshu region at the Nankai Trough (Fig. 2.1). The details of
past rock deformation and volcanism in that region appear to depend on theconfiguration and convergence direction of the subducting PSP. Chugoku also has anumber of pre-existing bedrock structures that were probably formed during Late
Cretaceous-Palaeocene times (Kanaori, 1990; Fabbri et al., 2004); these structures
have reactivated with varying senses of motion depending on the regional tectonic
boundary conditions at the time. These bedrock structures are distributed across muchof the Chugoku region (Fig. 2.2).

Figure 2.1: Regional plate tectonic setting of the Chugoku area. Black linework on shore shows theactive faults in southwest Japan from the Japan active faults database(http://www.aist.go.jp/RIODB/activefault/index_eng.html).

7

Early Miocene tectonics of Chugoku was dominated by back-arc opening of the Japan
Sea from either 30-12 Ma (Tamaki et al., 1992) or 16-14 Ma (Otofuji et al., 1991)(Fig. 2.1). Palaeomagnetic studies suggest ~45º degrees of clockwise rotation ofsouthwest Honshu from 16-14 Ma to the present (Otofuji et al., 1991, 1994).
Volcanism in Chugoku during the early stages of the Japan Sea opening was
dominated by eruption of low alkaline tholeiitic (LAT) mafic magmas near thenorthern coast (Kimura et al., 2005; Fig. 2.3). The geochemistry of the LAT magmas
has affinities with rift zone lavas erupted through thick continental crust.
During the main phase of the Japan Sea opening (17-12 Ma), alkali basalts began toerupt in the Oki region. The geochemistry of alkali basalts is typical of oceanic island
basalt (OIB). The origin of this volcanism is controversial and several models havebeen suggested to explain it (asthenospheric mantle plume, melting of lithosphericmantle as a result of heating or secondary convention associated with the Japan Sea
opening; see discussion in Kimura 2005). During the Japan Sea opening, the preexisting bedrock structure in southwest Honshu (Fig. 2.2) was reactivated —structures trending approximately NE slipped left-laterally while conjugate structures
trending approximately NW slipped in a dextral sense (Fabbri et al., 2004). Duringmuch of the Miocene through to ~5-6 Ma, the Philippine Sea Plate was converging on
the SW Japan region in a NNE to N direction (Hall et al., 1995a, b; Itoh and Nagasaki,1996), consistent with reactivation of left-lateral slip on NE-trending structures, whileright-lateral slip is expected on the conjugate NW-trending features during this time.
Following the Japan Sea opening, volcanism in Chugoku from 12-4 Ma wasdominated by eruption of monogenetic alkali basalt complexes across the entire
Chugoku region (see review in Kimura et al., 2005; Fig. 2.3).

Figure 2.2: The western Chugoku fault system mapped from a 1976 Landsat image (scale about
1:700000). C: cloudy area, H: Hiroshima, M: Masuda, Y: Yamaguchi, MTL: Median Tectonic Line. From
Fabbri et al. (2004).

8

Figure 2.3: Volcanic history of the Chugoku region since the Miocene from Kimura et al. (2005). MTL:Median Tectonic Line, BTL: Butsuzo Tectonic Line, LAT: low alkali tholeiite, ALK: alkali basalt, HMA:
high magnesium andesite, ADK: adakitic dacite, MORB: Mid-ocean ridge basalt. Thin lines withnumbers in (D) show the present depth of the PSP slab surface in km. The thick line in (D) marks thearcuate distribution of current adakitic centres.

The alkali basalts (some are transitional between LAT and alkali basalt) have a
predominant OIB character but some have chemical signatures of arc magmas(suggesting the presence of fluids from the PSP, sediment melt from the Pacific Plateor remnant subcontinental lithospheric mantle metasomatised by slab fluids (seereview in Kimura et al., 2005). In contrast, from 4 Ma to the present the volcanism (acombination of alkali basalt and adakitic volcanism) has been restricted to an arcuatezone above the leading edge of the subducting PSP (Kimura et al., 2005).
Geochemical studies suggest that volcanism in this period has a typical OIB characterwith an increasing influence of the PSP (by addition of fluids generating some
HFSE(High field strength element)-depleted alkali basalt and by slab melting
generating adakites). Seismic tomography studies reveal some evidence for a regionof mantle upwelling beneath southwest Japan; this upwelling is identified as apotential source for the alkali basalts in Chugoku by Nakajima and Hasegawa (2007a;Figs. 2.4, 2.5). The seismic tomography images suggest that the mantle upwelling isdiverted around the leading edge of the slab, leading to restriction of volcanism to thenorth coast of Chugoku (Fig. 2.5). Nakajima and Hasegawa (2007a) suggest that the
mantle upwelling may cause melting of the leading edge of the young subducting PSP
and that this could provide an explanation for the Quaternary adakitic volcanism
observed there (cf. Morris, 1995). Overall, there seems to have been a general
northward migration of volcanism in Chugoku since 12 Ma, probably related to the9northward migration of the leading edge of the shallowly subducting PSP and therelationship of this to a possible upwelling mantle flow (Fig. 2.4).

Figure 2.4: Schematic cross-section across the Chugoku region illustrating postulated upwelling
mantle flow interpreted from seismic tomography and the interaction of this upwelling feature with thePhilippine Sea slab; from Nakajima and Hasegawa (2007a). Based on interpretation of tomographic
data in Figure 2.5.

Figure 2.5: Cross-sections of S-wave velocity perturbations beneath southwest Japan from Nakajima
and Hasegawa (2007a). This illustrates a large mantle anomaly that is interpreted as upwelling beneaththe PSP slab in the Chugoku region, as well as the high-velocity anomaly associated with thesubducting Philippine Sea Plate.

From ~8-5 Ma, there was a period of strong north-south-directed shortening along thesouthern margin of the Japan Sea, just offshore of the northern coast of southwest
Honshu (Itoh and Nagasaki, 1996). Itoh and Nagasaki attribute this to resumption of
subduction of the PSP beneath southwest Japan (after a postulated hiatus from 10-6
Ma; Kamata and Kodama, 1994). The shortening direction is consistent with north10

south to north-northeast-directed relative plate motion during this time. At ~5-6 Ma,
PSP motion relative to Eurasia shifted from being northerly-directed to a more
northwesterly orientation almost normal to the margin (Seno and Maruyama, 1984;
Seno, 1989; Hall et al., 1995a).

Figure 2.6: Seismicity in the Chugoku region. Earthquake hypocentres (circles colour coded by depth)
in Chugoku. Note the prominent band of shallow (< 35 km depth) hypocentres along the northerncoastline of Chugoku, indicating the approximate position of the northern Chugoku shear zone. Much of
the elevated seismicity near the north coast between the Sanbe and Daisen areas is in the region of theMw 6.8 west Tottori earthquake in 2000 and may, in part, be related to aftershocks of that event. Data
are from the Japan Meteorological Agency database. Quaternary volcanoes are indicated by triangles(polygenetic volcanoes as red triangles, monogenetic volcanoes as orange triangles). The distribution ofolder monogenetic volcanism is indicated by the yellow squares; these usually indicate the position ofradiometric age determination sampling of lavas and vent locations for these lavas are not known.
Green lines indicate active faults. Shaded relief digital elevation model is based on SRTM(Shuttle Radar
Topography Mission) data.

2.2

Tectonics from 2 Ma to the present day

PSP motion relative to Eurasia shifted even further in an anti-clockwise direction (by~12º) at ~2 Ma, resulting in WNW-directed motion of the PSP in the SW Japanregion (Seno, 1985; Fig. 2.1) at ~6-7 cm/year, which continues today (Fig. 2.1;
Wallace et al., 2009; DeMets et al., 2010). This shift in plate motion led to activationof the Median Tectonic Line as a dextral strike-slip fault (Itoh et al., 1998) and led toa second reactivation of many of the pre-existing bedrock structures throughout
Chugoku (Figs. 2.1, 2.2). Since 2 Ma, the N45E Chugoku bedrock faults have beenslipping with a dextral sense, while the conjugate set slip in a sinistral sense (Fabbri etal., 2004), consistent with a more westerly orientation of relative plate motion. This11

reactivation is also consistent with the modern-day WNW orientation of the
maximum horizontal compressive stress axis (Townend and Zoback, 2006). In
general, the modern-day active faulting in Chugoku can be characterised as a low-rate(<0.3 mm/year), fairly diffuse combination of right-lateral (NE-trending) and leftlateral(conjugate,
NW-trending)strike-slip
faulting(http://www.aist.go.jp/RIODB/activefault/index_eng.html). The large landward extent ofplate boundary deformation and its transpressional nature in SW Honshu is related inlarge part to the shallow subduction angle of the subducting Shikoku Basinlithosphere. This is in contrast to rock deformation in the Kyushu region, which isdominated by back-arc extension related to the steep subduction angle of the west
Philippine Basin crust and likely slab rollback (Mahony et al., 2011).
The modern-day seismicity in Chugoku has a diffuse pattern (Figure 2.6), with asomewhat lower level of activity than the regions further to the south that are closer tothe trench (e.g. compared to Shikoku Island). However, some distinct seismic zones
are apparent, which may represent the primary features that are accommodating
deformation in that region. Note, for example, the NE-trending band of seismicity insouthern Chugoku starting close to the Aono-yama Volcano and continuing NE
towards the north coast close to Sanbe and Daisen (note that some of the seismicity
near Sanbe and Daisen is related to the Mw 6.8 west Tottori earthquake in 2000).
Some authors also suggest that a right-lateral strike-slip zone is developing justoffshore of the northern coast of southwest Honshu, although the exact location andrate of motion along this feature is under debate (Gutscher and Lallemand, 1999; Itohet al., 2002). Interpretation of GPS data suggests that up to 2-3 mm/year of rightlateral strike-slip may be occurring either off the north coast of Chugoku or as
distributed dextral deformation throughout Chugoku (Wallace et al., 2009). However,GPS data indicate much lower overall strain rates in the Chugoku region compared tosome other more tectonically active areas of Japan (Fig. 2.7).

Figure 2.7: Residual shear strain in southwest Japan from GPS after removal of elastic strain due tointerseismic coupling on the Nankai Trough (using the best-fitting model of Wallace et al., 2009). Notethe high strain area near the west Tottori earthquake of 2000. This high strain zone is related todeformation from that event and is not representative of the overall background strain rate there. Asidefrom the west Tottori area, GPS strain rates in Chugoku are low compared to Shikoku Island andKyushu.

12

Strain partitioning between the northern Chugoku shear zone and the Median
Tectonic Line produced by the response of the crust to subduction of the Philippine
Sea Plate may then result in rotation of crustal blocks between the two shear zones,
manifest in distribution of hypocentres, faults and gravity anomalies (e.g. Kanaori,
1990; Gutscher, 2001; Kudo et al., 2004). This is analogous to book-shelf faulting that
accompanies oblique subduction in the Central America volcanic arc (La Femina etal., 2002). Although these models are not certain, it is clear that there is a spatial
relationship between the northern Chugoku shear zone and the occurrence of
Quaternary volcanism, as all of the Quaternary monogenetic volcanic fields (with thepossible exception of the adakitic Aono-yama cluster) and polygenetic volcanoes lie
along the northern Chugoku shear zone defined by earthquake hypocentres. In thebookshelf faulting model, crustal extension and basins develop where crustal blocks
rotate adjacent to bounding faults (here the northern Chugoku shear zone). It is
possible that one explanation for the distributed nature of the volcanism of northern
Chugoku is that ascending magmas interact with structures (faults, basins) associatedwith possible book-shelf faulting and which acted as preferred pathways. However,this model is likely overly simplistic and complicated by additional factors discussed
later in this report.
Overall, a major factor influencing the distribution and style of volcanism and rockdeformation in southwest Japan is the strong along-strike variation in the age andgeometry of the subducting Philippine Sea Plate (Fig. 2.8). The Eocene-Cretaceouswest Philippine Basin subducts at a steep angle at the Ryukyu Trench adjacent tosouthern Kyushu; at the Nankai Trough, the 27-15 Ma Shikoku Basin lithosphere
subducts at a shallow angle beneath southwest Honshu. Seismic tomography(Nakajima and Hasegawa, 2007a) and receiver function studies (Ueno et al., 2008)
suggest that the leading edge of the PSP is at ~60-70 km depth near the north coast ofsouthwest Honshu, while the PSP has subducted more deeply beneath southern
Kyushu, up to ~180 km depth (Fig. 2.8; Nakajima and Hasegawa, 2007b). The
surface expression of active arc volcanism in Kyushu is located above the ~100 km
depth contour of the top of the subducting PSP slab. The lack of well-established arc
volcanism in southwest Honshu is likely due to the fact that the PSP has not yet
subducted deeply enough (the slab will need to reach ~100 km depth below southwest
Honshu to generate a well-developed volcanic arc). The volcanism in the Chugoku
region is located just beyond the leading edge of the PSP slab according to Nakajima
and Hasegawa (2007b). However, receiver function studies of the PSP slab
configuration (Ueno et al., 2008) place the leading edge of the slab slightly to thenorth (near the north coast of Chugoku) and interpret the interface to be slightly
shallower (with the 60 km contour beneath the active volcanoes in Chugoku) than isshown in Figure 2.8. Adakitic volcanism in Chugoku is consistent with melting of theleading edge of the very young PSP (Nakajima and Hasegawa, 2007a; Kimura et al.,2005).

13

Figure 2.8; Contours of the subduction interface (in 10 km intervals) beneath southwest Japan asdetermined from tomographic studies by Nakajima and Hasegawa (2007b). Red triangles show
locations of active volcanoes. Heavy dark blue dashed line shows current leading edge of subducted
Philippine Sea Plate.

2.3

Quaternary volcanism in the Chugoku region

Chugoku has a long history of volcanism, with Miocene-Pliocene lava flows coveringmuch of the central part of the region. Quaternary volcanism in Chugoku has included
eruptions from polygenetic volcanoes and development of new monogenetic
volcanoes and volcanic fields. These Quaternary volcanoes are all located in thenorthern part of Chugoku and the Japan Sea, with the exception of the Aono-yama
volcanoes that are located in westernmost Chugoku (Figure 2.9).
Three long-lived polygenetic volcano complexes are located in Chugoku: Daisen,
Sanbe and Oetaka-yama. Daisen is one of the youngest and most active polygenetic
volcanoes in Chugoku. This basaltic-dacitic composite volcano consists of clusteredand overlapping lava domes (> 10 named domes) distributed over an area ofapproximately 30 km2, with associated lava flows, pyroclastic density currents andtephra fallout deposits (Tsukui, 1984). K-Ar radiometric age determinations indicatethat these vents formed between 1.3 Ma and 12 ka (Tsukui et al., 1985). In addition tothese centres, older distributed volcanism occurs to the east of the Daisen volcano
proper, in an area known as the Hiruzen volcano group, suggesting that the locus of
volcanic activity has migrated westwards with time. The most recent known activity
at Daisen consists of lava dome eruptions, including pyroclastic flows, which
occurred approximately 12 ka. Daisen experienced a large-volume Plinian eruption
approximately 50 ka. Tephra from this eruption has been mapped in Tohoku,
hundreds of kilometres northeast of Daisen. This eruption truncated the main cone ofthe volcano complex.

14

Figure 2.9: Location of volcanoes in Chugoku, SW Japan. Quaternary polygenetic volcanoes areindicated by large triangles, monogenetic volcanoes are indicated by smaller orange triangles and aregrouped into volcano clusters (monogenetic volcano groups). The distribution of older, MiocenePliocene lavas is also indicated (solid squares), corresponding to points where these lavas have beensampled. The exact location of vents that fed these Miocene-Pliocene lava flows is unknown, due toerosion. Active faults are indicated by green lines. The Median Tectonic Line is the prominent rightlateral strike-slip fault that transects northern Shikoku. Shaded relief digital elevation model is based on
Shuttle Radar Topography Mission (SRTM) data.

Tamura et al. (2003) found that Daisen is bimodal in composition. Thus, basalts andandesites-dacites have erupted from closely spaced lava domes and craters.
Furthermore, with the notable exception of the 50 ka Plinian eruption, most activity
appears to have consisted of small-volume eruptions. Tamura et al. (2003) suggested
that geochemical trends, the bimodal nature of the volcanism and the small-volume
eruptions can be explained by the presence of distributed small-volume magma
chambers that can experience partial to total re-melting in response to renewedmagma injection. In this case, Daisen, although classified as a polygenetic volcano, isin some ways transitional between distributed monogenetic volcanism and centralvent dominated composite volcanoes.
15

Although Daisen has not experienced Holocene eruptions, abundant Late Pleistocene
activity suggests that this volcano has a credible potential for future eruptions. Recent
tomographic studies by Zhao et al. (2011) support the notion that Daisen is potentially
active. They identified low velocity zones by Vp and Vs tomography beneath theDaisen volcano. Furthermore, low frequency events occur to the west of the Daisen
volcano in the lower crust. The west Tottori earthquake (Mw 6.8; October 2000)
occurred about 20 km southwest of the Daisen volcano and low frequency eventsoccurred both before and after this earthquake (Ohmi and Obara, 2002; Zhao et al.,2011). These associations between tomographic anomalies, low frequency events andtriggering of low frequency events by the Tottori earthquake indicate that Daisen is anactive magmatic system (Zhao et al., 2011).
Together with Daisen, the Sanbe volcano is one of the most active volcanoes in
Chugoku. Sanbe is an andesite to dacite composite volcano cut by a small (1 km
diameter) caldera. The O-Sanbe dacite dome forms the highest point on the volcano.
This lava dome is the most recently active volcanic vent on Sanbe and likely in all of
Chugoku. A date of 1350 BP +/- 50 years (14-C age determination) has beenmeasured on soil just beneath tephra on the summit of the Sanbe volcano (Machida
and Arai, 1992). The most voluminous recent eruptive activity occurred during the
Taihei-zan eruption approximately 3600 BP. This eruption was also from a lava dome
and produced pyroclastic flows that reached 9 km down the Hayamizu river.
According to Machida and Arai (1992), there may be additional younger eruptions
from the Sanbe volcano, making this a persistently active volcano during the
Holocene. Zhao et al. (2011) identified seismic tomographic anomalies (low velocity
zones), low frequency earthquakes and shallow crustal microearthquakes at Sanbe,
providing further evidence that this volcanic system remains active.
Oetaka-yama is a polygenetic volcano located west of Sanbe. Like the otherpolygenetic volcanoes in Chugoku, Oetaka-yama comprises several lava domes.
These lava domes are predominantly dacitic in composition. Oetaka-yama appears tohave been active from 1.8 Ma to 0.8 Ma. During this one million year period of
activity, the volcano hosted an active hydrothermal system. Consequently, precious
metals have been mined from the lava domes of Oetaka-yama. There is no evidenceof Holocene activity or unrest at Oetaka-yama.
Although in terms of volume and explosivity, the Sanbe and Daisen volcanoes are thedominant active volcanic systems in Chugoku, a substantial number of volcanic vents
are also located in several distinct monogenetic volcanic fields. In total, and as
discussed in the following, there are at least 134 Quaternary monogenetic volcanoes
in Chugoku. These are not distributed in a spatially random manner, but instead form
distinctive clusters, for the most part on the northern margin of Chugoku near theJapan Sea. Older counterparts to these Quaternary monogenetic volcanoes werelocated in central Chugoku, mostly known from radiometric age determinations on
Pliocene-Miocene lavas. Usually the vents associated with these older lava flows are
not recognisable (or definitively mapped).
The two most active monogenetic volcano groups in Chugoku are Abu, located in thewest, and Kannabe, located in the east. The Abu monogenetic volcano group consistsof alkaline basalt and calc-alkaline andesite and dacite lavas and pyroclastic rocks
distributed over an area of approximately 400 km2 (Kiyosugi et al., 2010). Some of
the 56 volcanoes comprising the Abu monogenetic volcano group are located within
the Japan Sea (The Maritime Safety Agency of Japan 1996a, b) and are known
primarily from bathymetry. Considering the Abu monogenetic group as a whole, K16

Ar age determinations suggest a range of volcanic activity from 2.3 Ma toapproximately 10 ka (Uto and Koyaguchi, 1987; Kakubuchi et al., 2000; Kimura et al.,2003). The youngest volcano in this group, Kasa-yama, is dated at 10 ka using
radiometric age determinations and at approximately 8800 BP using
thermoluminescence methods.
There was apparently a quiescent period from approximately 1.6 to 0.8 Ma(Kakubuchi et al., 2000), during which very few volcanoes formed, if any. This
quiescent period also divides petrologically distinct volcanoes in this group.
Kakubuchi et al. (2000) classified the volcanic activity into an alkaline basaltdominated early period (2−1.6 Ma) and a calc-alkaline andesite-dacite-dominated lateperiod (<0.8 Ma) and suggested that these distinct episodes originated from different
mantle diapirs. Koyaguchi (1986) concluded that geochemical trends observed in Abu
lavas were produced by the magma mixing of primitive alkali basalt magmas anddacite magmas, which were in turn created by the partial melting of the lower crust
caused by induced heating from repeated intrusion of basalt.
Thus, the onset of calc-alkaline magmatism at 0.8 Ma corresponds to an increase inbasaltic magma flux into the lower crust (Kakubuchi et al., 2000), with possible
progressive response of the lower crust to continuous heating. In the following
discussion, we use an extended quiescent period from approximately 1.7 to 0.5 Ma
because the volcano dated at 0.8 Ma also has a more recent K-Ar age determination of
approximately 0.3 Ma (Kakubuchi et al., 2000), acknowledging that there is someuncertainty in the total span of this quiescent period. To our knowledge, this increasein the rate of volcanic activity around 0.5 Ma does not coincide with any major plate
tectonic changes that might account for the resurgence of magmatism in this area.
Kiyosugi et al. (2010) identified anomalously slow mantle beneath the Abu
monogenetic volcanic field, suggesting that the deep Abu magmatic system remains
active.
The ten scoria cones and domes of the Kannabe monogenetic group range in age from2.76 Ma to 0.05 Ma, a very similar time span, although considerably lower volume, tothat represented by the Abu monogenetic volcanic group. Like Abu, compositions
vary in the Kannabe monogenetic group from alkaline basalts to dacites. In addition,
two older Quaternary volcanic groups are located in relative proximity to the Kannabe
monogenetic volcano group. These are the Mikata and Oginosen monogenetic
volcanic groups, located west of Kannabe. The Mikata group consists of 8 mappedalkaline basalt vents, ranging in age from 1.6 Ma 0.216 Ma. The Oginosen groupconsists of 11 alkaline basalt and andesite vents, radiometrically dated by K-Ar torange between 1.138 Ma and 0.442 Ma. In the following, the Kannabe, Mikata andOginosen monogenetic volcano groups are referred to collectively as the Kannabe
monogenetic volcano group, due to their close proximity, while acknowledging thatvarious authors have subdivided this cluster further (Martin et al., 2003).
The Yokota-Matsue monogenetic volcano group lies roughly between the Abu andKannabe monogenetic volcano groups. This cluster consists of 19 scoria cones andlava domes, together with their lava flows; all are of alkaline basalt to andesite
composition. The age distribution of some of these volcanic vents is problematic. One
vent is dated using K-Ar methods at 37 Ma and a second is dated at 12 Ma. However,these ages are questionable, given the youthful geomorphology of the volcanic ventsand may reflect xenolith age or analytical error. Based on other K-Ar age
determinations, it appears that all of the volcanoes in this cluster are older thanapproximately 0.12 Ma, with peak activity between approximately 1.5 Ma and 1.0 Ma.
17

Therefore, it is uncertain if this cluster remains active, with a comparatively low
recurrence rate, or if generation of magmas in the mantle beneath this cluster hasceased altogether. Nevertheless, this volcano cluster is close to the Daisen volcano
and to the low frequency earthquake swarm and tomographic anomalies recognised
by Zhao et al. (2011).
The Aono-yama monogenetic volcano group is distributed in a roughly N-S elongate
cluster extending south of the eastern edge of the Abu volcano group. A total of 26
vents, including lava domes and a possible cinder cone, make up the Aono-yama
volcano cluster. K-Ar age determinations on vents bound activity between 0.110 and
2.077 Ma. Several lava flows are mapped in this cluster that cannot be definitively
linked to vents. K-Ar ages on some of these lava flows all fall within the range ofages measured for the vents. Aono-yama magmas are distinct from others in Chugoku
in that they are adakites. One explanation for the adakite magmas is that they form
from direct melting of the subducted Philippine Sea Plate (Kimura et al., 2003). This
explanation appears to be consistent with the anomalous position of this volcano
cluster, the only Quaternary volcanism not located along the northern margin of
Chugoku and the projected position of the subducted corner region of the Philippine
Sea Plate.
Two other very small volcano clusters occur in Chugoku. The Oki-Dogo islands,
north of the coast of Chugoku, contain numerous alkaline basalt lava flows and two
mapped vents. These two vents have been dated (K-Ar) at 0.55 Ma and 0.936 Ma,
respectively. In addition, there are many age determinations on Oki-Dogo lava flows
not associated directly with the two vents by mapping. The range of age
determinations on these lavas is 0.42 Ma – 4.61 Ma. Interestingly, there are oldreports of Holocene volcanic activity on Oki-Dogo. Tomita (1969) reported lava
flows burying alluvium that contains pottery fragments (Seibert et al., 2011). This
report appears to be unverified by more recent work. The Shimonoseki group is acluster of only 2 mapped vents located on the westernmost edge of Chugoku (west ofAbu). These two vents consist of alkaline basalt and K-Ar age determinations on thetwo vents are 2.63 Ma and 1.24 Ma, respectively.
In addition to these Quaternary volcano clusters, Miocene and Pliocene volcano
clusters are located over a broad region of Chugoku. In general, most of these clusters
are eroded, vent locations are difficult or imprecisely determined and less mapping
has been conducted on these clusters than the Quaternary groups. Some of theseclusters, such as the Tottori monogenetic group (a Pliocene alkaline basalt cluster),are located on the northern margin of Chugoku, in similar settings to Quaternary
volcanism. Other clusters are located in the central part of Chugoku, far from current
locations of volcanism. Sample locations of dated lava flows associated with theseolder groups are shown in Figure 2.9, but it is emphasised that, in general, exact ventlocations are unknown.

2.4 Origin of Quaternary magmas and temporal patterns ofactivity
Iwamori (1991) concluded that upwelling of a plume from the deep mantle below the
back-arc of southwest Japan caused zonation of Cenozoic basaltic volcanism, which
is characterised by an exponential increase in eruption volume of olivine-bearing
basalt toward the back-arc and systematic across-arc variations of chemical
18

compositions (increase in SiO2 and Al2O3 and decrease in FeO*, MgO and CaO) of
relatively undifferentiated basalts. Melting experiments suggest that the pressure andtemperature of magma segregation decrease towards the back-arc of Chugoku. These
P-T conditions define a trend that can be interpreted as a P-T path for adiabatic
upwelling of the postulated mantle plume. There are other explanations, however,which are also consistent with these trends, such as a decrease in the upper plate
lithosphere or crustal thickness towards the back-arc, coupled with development ofcorner flow as the PSP penetrates the mantle.
Iwamori (1992) estimated the degree of melting for primary magmas, weight fractionsof the residual phase and incompatible element concentrations of the source zone of
Cenozoic basalt in southwest Japan. His calculations indicate an increase in the
degree of melting towards the postulated back-arc upwelling centre, where the sourceis anomalously enriched in incompatible elements. He explained these variations byaddition of fluid (flux melting) and subsequent upwelling of enriched material fromthe deep mantle. The flux melting model also explains the low potential temperatureof the upwelling mantle. He concluded that the Cenozoic volcanism might have beencaused by a plume with abundant volatile and incompatible components rather than aplume of anomalously high temperature. Alternatively, recent onset of subduction
could have caused mantle circulation unrelated to a mantle plume.
Kimura et al. (2003) studied temporal-spatial variations in Late Cenozoic volcanic
activity in the Chugoku area and derived a broadly similar model to that of Uto (1995)(Figure 2.10). In their model, fore-arc expansion of the volcanic arc between 20 - 12
Ma may be related to the upwelling and expansion of the asthenosphere, whichcaused the opening of the Japan Sea. Narrowing of the volcanic zone after 3 Ma may
have been caused by progressive Philippine Sea Plate subduction. Adakitic dacite firstoccurred approximately 1.7 Ma in the middle of the arc and spread to the centre partof the Quaternary volcanic arc. Deeper penetration of the subducted slab may havecaused melting of the slab and resulted in adakites. Alkali basalt activity ceased in thearea where adakite volcanism occurred. Volcanic history in the Late Cenozoic wasprobably controlled by the history of evolution of the upper mantle structure,
coinciding with back-arc basin opening and various phases of subduction.
The models shown in Figure 2.10 are not the only possible explanations for the Late
Cenozoic volcanism and both reflect a currently favoured view held by many (but notall) in Japan of the importance of mantle diapirs in subduction zones. There are othermodels of magma generation in subduction zones that place more emphasis on
decompression of the mantle related to corner flow and back-arc spreading as well aschannelised flow of fluids and melts from the slab within the mantle wedge (e.g.
Iwamori, 1998; Kelemen et al., 2003). These models are equally able to explain thegeochemical characteristics of the Chugoku volcanism.

19Figure 2.10: Two models of the evolution of volcanism in Chugoku, from Kimura et al. (2003) and Uto(1995). These models are broadly similar. Uto (1995) suggests that the subduction of the Philippine Sea
Plate is the reason for rear-arc narrowing of the volcanic zone and that the location of the slab front isimportant for recognising the area of volcanism. Kimura et al. (2003) emphasise the distribution ofadakite, which they interpret as being formed when the slab had subducted into mantle hot enough tomelt the leading edge of the slab.

20

2.5 Relationship of gravity and magnetic data to Quaternary
volcanism
Several features of the complete Bouguer gravity anomaly map of Chugoku provide
constraints on crustal thickness and perhaps on the lateral extent of the flat-slab
Philippine Sea Plate and location of the volcanic arc. Western Chugoku is dominatedby a large amplitude (approximately 40 mgal) negative gravity anomaly (Figures
2.11a and b). Oda et al. (2005) interpreted this anomaly as a thickening of the crust in
western Chugoku to approximately 40 km, a value consistent with their modelling of
P-wave velocity structure of the Chugoku crust and mantle (Figure 2.12). A Pliocene
volcano cluster is located in the central part of this gravity anomaly. The anomaly
persists east of this location, albeit with reduced amplitude (20 mgal). In this area,
Oda et al. (2005) interpret crustal thickness to be >=34 km, again based on seismic Pwave velocity and relationship to Bouguer gravity anomalies. This area contains two
additional Miocene-Pliocene volcano clusters. Oda et al. (2005) suggest that thecrustal thickening is an isostatic effect, as this area corresponds to elevatedtopography (in the order of 500 masl). Given the correlation of these anomalies withthe area of Miocene-Pliocene distributed volcanism, we suggest that magmatismplayed a role in thickening the crust during this time, noting that other elevated areas(e.g. Shikoku) do not have anomalous seismic velocities, Bouguer gravity anomalies
and thickened crust is likely absent from these amagmatic zones. Here, we note thatadakitic characteristics of magmas can develop in thickened arc crust exceedingaround 35 km thick with stabilisation of garnet. Thus, adakitic magmas can also be
explained by partial melting of garnet-bearing lower crust or fractionation of arc
basalt intrusions into the deep crust. Thus, there is an alternative explanation foradakitic magmas to melting of the PSP.

21

Figure 2.11a: Complete Bouguer gravity map of Chugoku and surrounding areas (contour interval 2mgal). Gravity varies by approximately 140 mgal across the map area. Contours produced from gridded
gravity values at 1 km spacing from the Komazawa (2004) and the Geological Survey of Japan (2004)
databases. Offshore gravity anomalies are also shown, faded relative to onshore anomalies. Quaternary
volcanoes are indicated by triangles (polygenetic volcanoes as large black triangles, monogenetic
volcanoes as small black triangles). The distribution of older monogenetic volcanism is indicated by thesmall gray squares; these usually indicate the position of geochemical or radiometric age determination
sampling of lavas and vent locations for these lavas are not known. Black dashed lines indicate active
faults.

22

Figure 2.11b: Complete Bouguer gravity map of Chugoku and surrounding areas (contour interval 2mgal) as shown in Figure 2.11a, superimposed on a shaded relief digital elevation model (SRTM data).
All map symbols as in Figure 2.11a.

23

Figure 2.12: Depth to the Conrad (top) and Moho (bottom) discontinuities derived from delays in Pwave arrival time from Oda et al. (2005) (contour interval is 2 km). Uncertainty in this estimate isrepresented by the dashed line contours of 0.5 km and 1 km.

In addition to these broad, long wavelength features of the gravity map, several otherfeatures warrant attention, particularly with regard to the distribution of volcanoes.
Steep gravity gradients occur across northern Chugoku, coinciding with the area of
Quaternary volcanism and the approximate location of the northern Chugoku shear
zone. This gradient, with relatively high gravity values in the north, may coincidewith the lateral extent of the subducted Philippine Sea Plate and also with the thinningof the crust in transition to ocean crust to the north. The observed gravity gradient ismuch too steep to be solely a mantle feature and therefore crustal structure likely
marks this transition. If so, the northern Chugoku shear zone appears to exploit thistransition. North of the coastline, the crust is characterised by very steep gravity
gradients and linear zones that delineate faults. These faults are similar in trend to thenorthern Chugoku shear zone and, given their great lateral extent and steep gravity
gradients, represent major crustal structures. Onshore, less prominent gravity
anomalies are often, but not always, associated with mapped structures, such as theMedian Tectonic Line.
Aeromagnetic data provide an additional perspective on the nature of the northern
Chugoku shear zone and its relationship to volcanism. Aeromagnetic maps (Figure
2.13a and b) reveal broadly positive aeromagnetic anomalies in a band acrossnorthern Chugoku and steep magnetic gradients associated with some individual24

faults, especially in eastern Chugoku. In general, magnetic anomalies reflect shallow
or upper crustal features, as opposed to gravity and earthquake hypocentre data,
which tend to reflect deeper structures, at least when viewed on the regional scaletaken here. With this in mind, it is notable that volcano clusters in Chugoku areuncorrelated with magnetic anomalies. The Abu monogenetic volcanic field lies
within a zone of relatively high magnetic values that characterise much of the northcoast. The Yokota volcano cluster extends from a zone of relatively high magnetic
values in the south to low magnetic values in the north part of the cluster. Kannabe isin a relatively complex zone of magnetic anomalies, as are many of the older
monogenetic volcano groups. This indicates that, regionally, shallow crustal
structures appear to have very little influence on the locations of monogenetic volcanogroups. Similarly, broad regional magnetic anomalies in northern Chugoku are
oblique to the northern Chugoku shear zone, as characterised by gravity anomalies
and earthquake hypocentres. That said, of the tens of volcanoes in Chugoku there areseveral examples where volcanoes lie along steep magnetic gradients associated withfaults. It appears that the magmas feeding these volcanoes exploited shallow crustal
structures during their emplacement. However, there are only a few of these cases andthey do not appear to influence the overall pattern of volcanism.
In summary, Quaternary volcanism is concentrated in this transition zone from thickcrust in the south, comprising the main part of Chugoku, to thinner crust to the north.
This zone correlates with a band of elevated seismicity (Fig. 2.13). This situation
appears to contrast with Miocene and Pliocene distributed volcanism, which occurred
predominately in the central part of Chugoku, in a region now characterised byanomalously thick crust.
While volcanism shows a general correlation with hypocentre distributions andgravity anomalies of the northern Chugoku shear zone, shallow crustal structures,
evinced by magnetic anomalies and the mapped distribution of active faults, have avery limited and only local influence on volcano distribution in Chugoku region.

25

Figure 2.13a: Aeromagnetic map of Chugoku with contour interval20 nT from flightlines collectedacross the entire region and gridded at 1 km interval (Nakatasuka et al., 2005; Geological Survey ofJapan, 2005). Offshore magnetic anomalies are also shown, faded relative to onshore anomalies.
Quaternary volcanoes are indicated by triangles (polygenetic volcanoes as large black triangles,
monogenetic volcanoes as small black triangles). The distribution of older monogenetic volcanism isindicated by the small gray squares; these usually indicate the position of geochemical or radiometricage determination sampling of lavas and vent locations for these lavas are not known. Black dashedlines indicate active faults.

26

Figure 2.13b: Aeromagnetic map of Chugoku and surrounding areas (contour interval 20 nT) as
shown in Figure 2.13a, superimposed on a shaded relief digital elevation model (SRTM data). All map
symbols as in Figure 2.13a.

27

3 Regional Evolution Scenarios for Chugoku
Based on the correlation between the leading edge of the subducting Philippine Sea
Plate (PSP) and the location of active volcanism within Chugoku (Nakajima andHasegawa, 2007a, b; Ueno et al., 2008) as well as the adakitic composition of muchof the recent volcanism Regional Evolution Scenarios (RES) were developed.
Irrespective of whether the adakitic magmatism is caused by melting of the young
PSP crust (Kimura et al., 2003) or interaction of hydrous arc basalts with thickened
arc crust, the location of the slab edge is likely to exert a major control on the locationof future volcanism within Chugoku. Thus, we considered three RES that account fordifferent scenarios of migration of the PSP slab, depending on the future evolution of
the slab geometry.
Numerous studies suggest that an asthenospheric upwelling is the source of alkali
basalts that have been present in the Chugoku region since the Miocene opening of
the Japan Sea (Iwamori, 1991, 1992; Kimura et al., 2003; Nakajima and Hasegawa,2007a, among others; Figs. 2.4 and 2.5). The onset of adakitic magmatism since ~2
Ma might be attributed to melting of the leading edge of the subducting PSP by the
postulated asthenospheric source (Kimura et al., 2003) or alternatively underplating ofhydrous arc magma in thick arc crust in the garnet stability field. Gradual restrictionof active volcanism to the north coast of Chugoku (compared to 12-4 Ma when alkali
basaltic volcanism was more widespread in Chugoku) is thought to be due toprogressive subduction of the PSP beneath Chugoku, which eventually formed abarrier between most of Chugoku and the postulated asthenospheric source ofmagmatism beneath the region. Our RES are largely based on these alternativemodels for development of volcanism within the Chugoku region.
In all three RES, we assume that the modern-day WNW-directed relative motion
between the PSP and the Eurasia Plate is maintained and, in addition to northwardmigration of the slab edge, these relative plate motions will also cause the current slab
geometry to migrate southwest along the strike of the margin (at a rate of ~25-30
km/Myr) relative to the upper plate. In such a scenario (i.e. if current plate motions
are maintained), the region of flat slab subduction will eventually migrate beneath
northern Kyushu. Moreover, as the PSP continues to be subducted beneath southwest
Honshu, the slab will deepen and eventually reach ~100 km depth. In response to slab
deepening, it is expected that magma flux would increase in Chugoku. The timescalesof this evolution are unknown, but may be in the order of one to a few million years.
An increase in magma flux would lead to the formation of new polygenetic volcanoes,
possibly in areas of northern Chugoku currently free of volcanic activity.
In order to assess the future potential for volcanism throughout Chugoku over the next
1 Myr timeframe, we have developed three plausible Regional Evolution Scenarios.
The RES we consider are as follows: (1) the leading edge of the PSP and the locationof volcanism in Chugoku remain in the same location for the next 1 Myr; (2) the
leading edge of the PSP migrates NNW relative to the upper plate, leading to a NNW
migration of volcanism in Chugoku; (3) the PSP slab steepens over the next 1 Myr,
leading to more rapid deepening of the subducting PSP slab beneath northern
Chugoku.
These scenarios are based on plausible future geometric configurations of the PSP and
we make predictions for how volcanism will evolve within these scenarios. It is also
possible to include additional alternative evolution scenarios within any of the
proposed RES, such as changes in the kinematics of the PSP or temporal evolution of28

fault systems. For the purposes of this report, we show RES for 10 - 100 kyr and 100
kyr - 1 Myr timeframes. We anticipate that the regional tectonic evolution over the 0- 10 kyr time period will be similar to what is observed today, so it is not shown here
for the sake of brevity.
The most important factors to be considered in the different RES are the positions of
the leading edge of the subducting slab, including the location of the 100 km slab
contour beneath southwest Japan as subduction of the PSP progresses. In thefollowing description of our proposed RES, we will emphasise the location of thesefeatures relative to the upper plate. For the modern-day starting-point of the slab
leading edge, we define an envelope for this based on the locations inferred fromtomographic studies (Nakajima and Hasegawa, 2007b; Fig. 2.8) and receiver function
studies (Ueno et al., 2008). The receiver function studies place the leading edge of theplate slightly further north compared to the interpretation of the tomographic data; an“envelope” for the leading edge is used to encompass the uncertainties in the slabedge location.

3.1 RES 1: The locus of the northern edge of the subducting
PSP stays in its present-day location

Figure 3.1: RES 1 for the entire time period of interest (out to 1 Myr in the future). Heavy green andred dashed lines show the leading edge of the subducting Philippine Sea Plate for different stages from
Ueno et al. (2008) and Nakajima and Hasegawa (2007b), respectively. The heavy black line shows theapproximate location of the 100 km contour to the top of the slab beneath Kyushu. Red triangles show
the locations of current active volcanoes and the greenish-yellow shaded area outlines the potential
location of the leading edge of the slab, given the range of seismological models proposed. The yellow
rectangle outlines the Chugoku study region.

29

This scenario could be driven by melting of the edge of the PSP by the postulated
asthenospheric plume, preventing the position of the PSP slab edge from deepening or
migrating northwards. This RES assumes that the probability of volcanism remains
unchanged in the Chugoku region from the present-day out to 1 Myr in the future (Fig.
3.1). The fact that the location of active volcanism over the last 4 Ma in Chugoku has
not changed dramatically from what we see today (Fig. 2.3) suggests that this scenario
is certainly possible. It is also possible that there is some structural control within theupper plate on the location of volcanism in Chugoku, which could encourage thecontinuation of volcanism in its current location for the time period of interest. For
example, much of the volcanism seems to cluster along a zone of active seismicity
and faulting coincident with the postulated north Chugoku shear zone.

3.2 RES 2: The PSP maintains its geometry and present-day
NNW migration
We expect that this RES is the most plausible one. In this RES, we assume that therelative motion between the PSP and the Amurian Plate remains the same as it istoday, with 6-7 cm/year of convergence oriented at about N60W. We assume that the
subducting PSP maintains its ~15° dip throughout this time period and use thisassumption and the relative plate motions to track the position of the leading edge ofthe subducting slab throughout the 10 - 100 kyr and 100 kyr - 1 Myr timeframes, as
shown in Fig. 3.2. We use two alternative scenarios for the current slab leading edge
positions (Nakajima and Hasegawa, 2007b and Ueno et al., 2008) and construct anenvelope for the region beneath which the leading edge of the PSP slab might exist
during this timeframe.
Due to the westerly component of PSP/Eurasia Plate relative motion, the overall
geometry of the slab beneath Chugoku migrates along the strike of the southwest
Japan plate boundary, at ~25-30 km/Myr. Moreover, due to progressive subductionof the PSP slab, the leading edge of the slab will become significantly deeper withtime. We expect that the leading edge of the subducting PSP beneath Chugoku will
gradually deepen from ~55-70 km depth to 70-85 km depth at around 1 Myr (Fig. 3.2),
assuming that a constant dip of 15° is maintained. If the location of the slab leadingedge controls the position of volcanism in Chugoku, we would expect a northwardmigration of volcanic activity with time throughout most of Chugoku, with most of
the volcanism occurring in the Japan Sea just offshore of Chugoku by ~1 Myr fromtoday. The exception to this is the western part of Chugoku (Yamaguchi Prefecture)
where, due to the configuration of the slab and relative plate motions, we expect anoverall westward migration of the slab leading edge, which could be accompanied bya westward sweep of active volcanism in Yamaguchi with time.

30

Figure 3: RES 2 for the time periods (10 - 100kyrs and 100kyrs - 1Myrs in the future). The heavy
green, blue, purple and red dashed lines show the leading edge of the subducting Philippine Sea Plate
for different stages from Ueno et al. (2008) and Nakajima and Hasegawa (2007b), respectively (seeinset for key). The heavy black line shows the approximate location of the 100 km contour to the top of
the slab beneath Kyushu. Red triangles show the location of current active volcanoes and the greenishyellow shaded area outlines the potential location of the leading edge of the slab, given the range ofseismological models proposed. The yellow rectangle outlines the Chugoku study region.

31

3.3

RES 3: The subducting PSP steepens with time

In RES 3, we explore the possibility that the angle of subduction of the PSP slab
steepens over the next 1 Myr. This is a plausible scenario for several reasons. For
example, it is possible that the asthenospheric upwelling postulated to occur beneath
Chugoku (Iwamori, 1991, 1992; Nakajima and Hasegawa, 2007a, among others) is
providing buoyant support for the subducting PSP, leading to the unusually shallow
subduction of the PSP beneath Chugoku. One scenario to consider is that theasthenospheric plume could become weaker over the next 1 Myr, which would reducethe buoyant support of the PSP slab and allow the subducting slab to steepen withtime. An alternative possibility is that the mantle wedge between the subducting PSP
and the overriding Chugoku region could become less viscous with time, possibly due
to influx of material from the asthenospheric upwelling related to the postulated
mantle plume or development of corner flow in the mantle wedge. These processes
would reduce the viscous coupling between the subducting plate and the upper plate,allowing the PSP slab to founder and begin to subduct more steeply. Additionally, or
alternatively, the ongoing subduction of the PSP will increase the negative buoyancyof the PSP slab, eventually allowing the slab to subduct more steeply.
For this RES, we assume that the slab dip gradually increases by 20° over the next 1
Myr, from its current 15° dip to 35°. We maintain the modern-day relative platemotions in this scenario, as assumed for RES 2. The results of this RES are shown in
Fig. 3.3. Our calculations indicate that the horizontal position of the leading edge of
the PSP plate does not change substantially in this RES compared to RES 2.
However, a major difference between this RES and the previous ones is that the PSP
subducts more deeply, to 85-100 km depth by the end of the 1 Myr timeframe. Deeper
subduction of the PSP would increase the likelihood of full-blown volcanic arc
development in the Chugoku region and would substantially increase the probabilityof volcanism along the entire north coast area of Chugoku. If this scenario occurs, arc
volcanism could potentially occur anywhere within the envelope we define for thelocation of the slab leading edge on a 1 Myr timeframe (Fig. 3.3). Similar to RES 2,
volcanism is also expected to migrate westwards across the Yamaguchi region, due tothe motion of the subducting PSP beneath Chugoku.
Although the slab is steepening with time in this scenario, the slab leading edge still
undergoes northward migration due to the motion of the PSP relative to Chugoku.
We suggest that this scenario indicates that volcanism south of the current area ofactive volcanism may be highly unlikely, as the PSP will still provide a barrier to any
supply from the postulated asthenospheric upwelling to the southern Chugoku region.

32

Figure 3.3: RES 3 for the time periods 10 - 100kyr and 100kyrs - 1Myrs in the future). The heavy
green, blue, purple and red dashed lines show the leading edge of the subducting Philippine Sea Plate
for different stages from Ueno et al. (2008) and Nakajima and Hasegawa (2007b), respectively (seeinset for key). The heavy black line shows the approximate location of the 100 km contour to the top of
the slab beneath Kyushu. Red triangles the location of current active volcanoes and the greenish-yellow
shaded area outlines the potential location of the leading edge of the slab for the two timeframes, given
the range of seismological models proposed. The yellow rectangle outlines the Chugoku study region.

33

3.4 Implications of all RES for future rock deformation andvolcano/fault interactions
Given that the plate kinematic boundary conditions remain the same in these RES, we
do not expect rock deformation patterns to change substantially from what is
occurring at present. However, the Chugoku region seems particularly susceptible toslow, diffuse deformation of pre-existing bedrock structures (e.g. Fabbri et al., 2004),
so that any pre-existing bedrock faults could be reactivated during the time periods ofinterest. Some authors have suggested that there is a newly developing fault zone
located off the north coast of Chugoku along the southern margin of the Japan Sea(Sea of Japan Fault Zone, SJFZ; Itoh et al., 2002; Gutscher and Lallemand, 1999) that
may be starting to accommodate a larger proportion of the margin-parallel componentof plate motion currently absorbed by the more active Median Tectonic Line
(Gutscher and Lallemand, 1999). If this strike-slip zone becomes a more significant
tectonic feature, then it is possible that the distributed zone of faulting across
Chugoku could become more active as more plate boundary stresses are transferredfrom the subduction boundary to the north coast of southwest Honshu.
There is also potential for interaction between volcanic and tectonic processes as theplate boundary evolves. For example, increased volcanic activity related to eventual
volcanic arc development may weaken the crust near the north coast of Chugoku andmake it more favourable for fault systems to develop and accommodate a larger partof the plate motion budget. Such a scenario could involve increasing localisation of
deformation to the north coast region. Moreover, the ubiquitous pre-existing bedrock
structure and the current state of stress in the Chugoku region may also influence thespatial distribution of volcanism.

34

4 Recurrence Rates of Monogenetic Volcanism in
Chugoku
From the discussion of the volcanic history of Chugoku, it is clear that different
volcano clusters have different rates of volcanic activity and that these clusters reachpeak activity at different times. For example, the Yokota-Matsue volcano cluster
appears to have decreased in activity during the last few hundred thousand years,
whereas the Abu and Kannabe volcano clusters have either increased their rate ofactivity or remained steady over the same period of time. Therefore, it is inappropriate
to think of the region as a whole with a uniform recurrence rate of volcanic activity.

4.1

Sources of uncertainty

What is the rate of change of volcanism within any one of these volcano clusters?
This question is complicated by several factors. Radiometric age determinations are
the primary means of determining the timing of past volcanic activity in monogenetic
volcano groups. All available radiometric age determinations in Chugoku are basedon the K-Ar method. Although analytical errors are assumed to be Gaussian, wholerock K-Ar age determinations commonly yield older estimated ages than Ar-Ar age
determinations and there seems to be a mismatch between reported K-Ar age andvolcano morphology in some instances in the region.
The potential for bias in radiometric age determinations cannot be overstated. A few
volcanoes in Chugoku have been dated multiple times. Sometimes, mean radiometricage determinations from individual samples overlap significantly, lending confidence
to the estimated age. Unfortunately, there are also cases in which multiple ages on thesame volcano vary considerably, with errors larger than analytical uncertainties. One
example from Chugoku is the Kasa-yama volcano. We know of at least 10
radiometric age determinations on the Kasa-yama volcano, thought to be the youngest
monogenetic volcano in the Abu volcano cluster. These age determinations include:
0.007 +/- 0.003 Ma, 0.011 +/- 0.015 Ma, 0.034 +/- 0.022Ma and 0.039 +/- 0.024 Ma.
In addition, some age determinations for this young volcano yield negative ages (e.g.
-0.034 +/- 0.005
Ma), indicating the difficulties with accuracy in K-Ar age
determinations of young volcanic rocks.
A second factor complicating estimation of the recurrence rate is that no volcano
cluster has radiometric age determinations on all of its volcanoes. For example, in the
Abu volcano cluster, 31 volcanoes have K-Ar radiometric age determinations.
Although this is extensive, it means that 25 volcanoes in the cluster have noradiometric age determinations. Of course, this lack of data contributes to theuncertainty in recurrence rate and there is potential bias if there is a tendency to dateyounger volcanoes rather than older volcanoes, or vice-versa. However, there are
additional sources of potential age information other than radiometric age
determinations. These potential sources include stratigraphic information. For
example, in some cases lava flows from an undated volcano are bounded by lava
flows from dated volcanoes. In such cases we know that the age of the undated
volcano must be between the estimated ages of the older and younger bounding lava
flows. Similarly, a lava flow may be known to be older or younger than a dated lava
flow, by stratigraphic correlation. Palaeomagnetic data are another source of age
information. The magnetic polarity of the lava flow may help bound its age,35

particularly if other stratigraphic relationships can be identified that can be used toconstrain the volcano to a specific magnetic polarity epoch.
Unfortunately, particularly in monogenetic groups, stratigraphic information may beentirely absent and the ages of some volcanoes can be completely unknown. In suchcases, some assumptions are usually justified about the ages of the volcanoes. For
example, it can be safely assumed that these volcanoes are not historically active,
otherwise some historical record of activity should exist. Sometimes, the oldest lavas
in volcanic fields are radiometrically dated, bounding the maximum possible ages ofundated units. In other cases, the volcanoes are mapped as Quaternary in age, based
only on their geomorphology or spatial association with dated Quaternary volcanoes.
In the following, we assume that undated volcanoes that are lacking additional
stratigraphic information are Quaternary in age if they are associated with dated
Quaternary volcanoes, acknowledging that in some cases these volcanoes may
actually be Pliocene in age.
A third factor complicating recurrence rate estimates is that recurrence rates inindividual volcano clusters are non-stationary, that is they vary with time. Volcano
clusters often go through waxing or waning phases of activity, during which times therecurrence rate of activity may change by one order of magnitude or more over a
period of a few tens of thousands of years (e.g. Condit and Connor, 1996; Bebbington
and Cronin, 2011). For relatively short-term forecasts (e.g. 10,000 years into the
future), it is necessary to obtain best estimates and uncertainties for the current
recurrence rate, using our understanding of activity over the last few hundred
thousand years. For longer-term forecasts associated with long-term performance of a
HLW repository, say in the order of 100,000 years to 1 Myr, it is necessary to assess
possible changes in recurrence rate based on the frequency and magnitude of suchchanges in the past.

36

Figure 4.1: Generalised procedure for estimating recurrence rate as a function of time, applied toindividual volcano clusters in Chugoku.

4.2

Procedure for estimation of recurrence rate

As part of the TOPAZ project, we have developed a new procedure for estimating thechange in recurrence rates of activity in volcano groups as a function of time, using
all of the available information that constrains the ages of individual units(radiometric age determination, rock stratigraphic and palaeomagnetic data) andaccounting directly for uncertainties in ages (e.g. uncertainty in radiometric age
determination, lack of any age determination) as best as possible, while37

acknowledging that additional uncertainties (e.g. bias in individual radiometric age
determinations) may yet be unaccounted for. This procedure is described in Figure 4.1.
In essence, this is a Monte Carlo procedure that uses all available age data to forecast
recurrence rate of activity as a function of time and uncertainty in the recurrence rate
given the uncertainties associated with each input data type.
Input data types are best visualised as hierarchical categories of information about
each volcano. We have the best understanding of volcanoes that have multiple
radiometric age determinations. Ideally, mean ages found by independent radiometricage determinations will be close to one another relative to the analytical uncertainty
associated with the age determinations. As noted previously, however, this is notalways the case. Some independent age determinations on the same volcano or
volcanic unit may have little overlap. Nevertheless, even if these independent age
determinations on the same volcanic unit yield substantially differing age estimates,
these additional data give an improved sense of the uncertainty about the true age ofthe volcano. Therefore, we regard multiple age determinations on the same volcano asproviding the best information about the age and uncertainty in the age of the volcano.
We consider volcanoes with only one radiometric age determination to be a second
category of data, as there is potential for bias in the age determination that is notquantified through the use of multiple, independent analyses. Most dated samples
from volcanoes in Chugoku fall into this latter category.
In the Monte Carlo simulation, both of these classes are randomly sampled based on
the analytical uncertainty identified by the laboratories performing the radiometricage determination. In the case where multiple age determinations are available on thesame unit, this is a two-stage process. First, one of the set of radiometric age
determinations made on the same volcano or volcanic unit is randomly selected. Thenan age is sampled from the error distribution based on reported analytical error for the
randomly selected sample. This procedure assures that the full range of age
uncertainty, represented by the multiple samples each with analytical error, will be
represented in the analysis.
A third category comprises those volcanoes that are bounded stratigraphically bydated units. In an ideal situation, the stratigraphically bounded unit is alsoradiometrically dated, in which case the age can be bounded. In other cases, the unit
has no radiometric age but is nevertheless bounded by units that are radiometrically
dated. For this latter case, it is assumed that the age of the volcano is best estimated asa uniform random distribution between the ages of the two bounding units. This isactually a rare case for volcanoes in Chugoku because few volcanoes havestratigraphic information but are not dated using radiometric age determination
methods.
Similarly, a fourth category consists of those volcanoes and volcanic units that have
one stratigraphic relationship known, that is the minimum or maximum age (but notboth) of the volcano relative to other dated units is known. This is a comparatively
common situation in Chugoku. For example, in Kannabe eight volcanic units have aknown stratigraphic relationship that constrains the maximum or minimum age of theunit, but not both. Only two units in Kannabe are constrained stratigraphically interms of both maximum and minimum ages.
Finally, a fifth category comprises volcanoes for which there is no radiometric age
and no bounding stratigraphic information. These volcanoes are simply known tohave erupted prehistorically. Based on geomorphology, because the location of the38

vent is well known and often the morphology of the volcano is well preserved, it isassumed that these volcanoes formed in the Quaternary or uppermost Pliocene. We
assume that these volcanoes may have formed at any time during this interval withequal probability.
The structure of these data and relationships between categories suggest a relatively
straightforward sampling procedure, as illustrated in Figure 4.1, steps 1 and 2. First,
volcano units with radiometric age determinations are randomly sampled from the
distribution of analytical errors, as discussed previously. Second, undated units withknown stratigraphic order are randomly sampled using the new distribution of ages
based on radiometrically dated units. These relationships, both among radiometrically
dated and undated samples, are checked to make sure that known stratigraphic orderis maintained. If stratigraphic order is not maintained, then the entire sample set isdiscarded and a new sample is drawn randomly from the distributions. This samplingis repeated until a set of ages is found that preserves stratigraphic order. For thosevolcanic units with no radiometric age determinations and no stratigraphic
relationships, a random sample is drawn between maximum and minimum ages
(usually any time from the latest Pliocene or Quaternary to the start of the historic
period, taken in Japan to be 2000 years BP).
Once this set of sampled volcano ages is determined to be faithful to the known
stratigraphic sequence, recurrence rates as a function of time are determined. There
are various ways to estimate change in recurrence rate with time. Here we use a
simple method proposed by Ho (1991), using the maximum likelihood estimate ofrecurrence rate:
λ = (N-1)/(to-ty)
where λ is the estimated recurrence rate based on N samples, ty is the sampled
estimated age of the youngest of the N samples and to is the estimated age of theoldest of the N samples. As illustrated in step 4 of Figure 4.1, the recurrence rate maythen be estimated for any time. Different results are obtained depending on thenumber of samples, N, selected. Generally, the larger the value of N, the smoother thevariation in recurrence rate, whereas small values of N emphasise abrupt or short-termchanges in recurrence rate. In practice, we selected values between N=2 and N=6.
This entire procedure is then repeated 10,000 times in order to sample the
distributions of all inputs fully. Following this Monte Carlo simulation, the procedure
outputs the mean recurrence rate and percentiles of the distribution illustrating
confidence in recurrence rate estimates, given the data uncertainties discussed above.

4.3

Results of recurrence rate estimation

We consider the four largest clusters of monogenetic volcanoes in Chugoku
separately for the purpose of recurrence rate estimation. These clusters are: Abu,
Aono-yama, Yokota-Matsue and Kannabe, where Kannabe includes the Genbudo,
Mikata and Oginosen monogenetic volcano groups. Variations in recurrence rate ineach of these volcanic fields during the last 3 Ma, using N=2 to N=6, are shown in
Figure 4.2.
For the Abu volcano cluster, the Monte Carlo simulation indicates that the recurrence
rate of volcanism in the field is currently approximately 10 events per 100 ka, or 1 x
10-4 events per year (mean rate) and is between 3.3 x 10-5 and 2.4 x 10-4 events per
year with 95% confidence. This one order of magnitude uncertainty occurs primarily
39because 25 of the 56 mapped volcanoes in the Abu volcano cluster have noradiometric age determinations and no stratigraphic information. Therefore, as
discussed previously, it is assumed that these 25 volcanoes may have formed at any
time during the last 2 Ma, prior to 2000 years BP. The effect of this assumption isclear in Figure 4.2, as it appears that the rate of volcanism increased abruptly at 2 Ma
to about 1 x 10-5 per year. Of course, given the uncertainties, this increase in the rateof volcanism was likely more gradual. Nevertheless, it is clear from dated volcanoes
and stratigraphic relationships that the recurrence rate of activity increased
considerably around 0.5 Ma and is near its highest rate of activity today.
The nearby adakitic Aono-yama volcano cluster has a similar pattern of recurrence
rates to Abu. Like Abu, because approximately 50% of the volcanoes in the cluster
are not radiometrically dated, it is assumed that the undated volcanoes in the cluster
may have erupted at any time to 2 Ma. Therefore, the increase in recurrence rate atabout 2 Ma (Figure 4.2) reflects uncertainty in age estimates and the assumption thatnone of the undated volcanoes is older than 2 Ma. On the other hand, the increase inrecurrence rate at approximately 0.75 Ma (Figure 4.2) appears to be reasonably welldefined by the available data. The recurrence rate in the Aono-yama cluster appears tohave decreased slightly since peak activity between 0.5 and 0.25 Ma, although thisapparent decrease is within the uncertainty of recurrence rate and may be an artefactof data uncertainty. The current mean recurrence rate is estimated to be approximately
1.8 x 10-5 events per year (N=4) and to be between 6 x 10-6 and 3 x 10-5 events per
year with 95% confidence. Thus, rates in the Aono-yama volcano cluster areapproximately one order of magnitude less than estimated recurrence rates in the Abu
volcano cluster.

40

Figure 4.2: Estimated recurrence rates of monogenetic volcanism in the four largest volcano clusters
in Chugoku. Recurrence rates as a function of time are estimated using the methods outlined in Figure5.1, for N=2, 4 and 6 volcanoes in each of the volcano clusters. Shading shows percentiles of
uncertainty and lines indicate mean recurrence rates. Mean recurrence rates for all four volcano clusters
are compared in the lowermost panel.

41

The Yokota-Matsue volcano cluster appears to have gone through a well-defined peakin activity at approximately 1.25 Ma, during which time activity reached recurrence
rates similar to those currently observed in Abu. The current mean recurrence rate in
the Yokota-Matsue volcano cluster is estimated to be approximately 2.9 x 10-6 events
per year (N=4) and to be between 2.6 x 10-6 and 3.3 x 10-6 events per year with 95%
confidence. Thus, rates in the Yokota-Matsue volcano cluster are nearly one order ofmagnitude less than estimated for the Aono-yama volcano cluster and approximately
two orders of magnitude less than estimated recurrence rates in the Abu volcano
cluster.
The Kannabe volcano cluster has the best constrained recurrence rates of all the
volcano clusters in Chugoku because 40 of the 47 volcanoes have radiometric age
determinations. Activity appears to have increased in the Kannabe volcano cluster atapproximately 1.6 Ma and has increased gradually since that time. The current mean
recurrence rate in the Kannabe volcano cluster is estimated to be approximately 2.3 x
10-5 events per year (N=4) and to be between 1.7 x 10-5 and 3.0 x10-5 events per yearwith 95% confidence. Thus, recurrence rates in the Kannabe volcano cluster areapproximately the same as those in the Aono-yama cluster.
In summary, the four largest volcano clusters in Chugoku vary considerably inrecurrence rates, by nearly two orders of magnitude. Furthermore, recurrence rates do
not vary synchronously in the four clusters, with the Yokota-Matsue volcano clusterin particular experiencing peak activity before the other three clusters. A notablefeature of monogenetic volcanism in the Abu, Aono-yama and Kannabe volcano
clusters is that recurrence rates, although varying among the three clusters, are at theirhighest levels during the last 0.25 Ma.
Based on RES 1, we expect recurrence rates of volcanism to continue atapproximately their current levels for the next 1 Myr. As illustrated by the analysis ofindividual monogenetic volcanic fields, this means that fluctuations in recurrence rate
up to one order of magnitude within the monogenetic fields is certainly possible. Suchfluctuations have been observed during the past several million years and are likely tocontinue. In addition, in 1 Myr it is possible that new monogenetic volcanic fields will
form in northern Chugoku.
Similarly, RES 2 allows for a shift in the location of volcanism with time, but therecurrence rate of this volcanic activity within the arc remains within the ranges
currently observed in the Chugoku monogenetic volcanic fields. In RES 2, it isassumed that changes in plate geometry will shift volcanism to the north during thenext one million years. Overall, this would lead to a reduction in recurrence rates of
volcanism in northern Chugoku (as the locus of activity shifts north of the current
coast). Over a few million years, it is possible that this activity would manifest itself
in two ways: either current monogenetic fields will develop spatio-temporal trends,
with youngest volcanism in the north, or the currently active volcanic fields will wanein activity in favour of new volcanic fields that will form in response to the changing
position of the PSP. These new monogenetic fields would not necessarily be locatedimmediately north of the existing fields, but would be positioned to reflect new
magma source regions, depending on the productivity of the mantle, nuances of plategeometry and, possibly, structure of the crust.
In RES 3, it is expected that the recurrence rate of volcanism would increase innorthern Chugoku in response to the deepening of the subducted PSP. The increase inmagma flux would potentially have several effects. First, the overall rate of42

magmatism within currently active volcanic fields (e.g. Abu, Kannabe) and at
polygenetic volcanoes (e.g. Daisen) would increase. Second, increased magma flux
might lead to conditions promoting the growth of magma chambers at intermediateand shallow depths in the crust. This would result from a transition from monogenetic
to polygenetic volcanism. Thus, the overall style of volcanic activity and associatedhazards would change in northern Chugoku. Third, it is anticipated that such changes
would most likely be in the areas of current monogenetic and polygenetic volcanism.
Nevertheless, it is also reasonable to assume that increased magma flux would
increase the probability of new volcano formation (either monogenetic, polygenetic,or both) in parts of northern Chugoku that are currently free of volcanic activity.

43

5

Spatial Likelihood of Future Volcanism

Site-specific hazard assessments require that hazards be estimated long before newmonogenetic volcanoes begin to erupt. In the ITM methodology, two parallel andcomplementary approaches were developed and tested for producing forecasts ofspatial likelihood of volcanism – the kernel method and the Cox process method.
Both methods have been used to evaluate the Chugoku region and the results aredescribed in this section.

5.1

Kernel density estimation of spatial likelihood

Kernel density estimation is a non-parametric method for estimating the spatial
density of future volcanic events based on the locations of past volcanic events(Connor and Connor, 2009; Kiyosugi et al., 2010; Bebbington and Cronin, 2011).
Kernel density estimation has previously been developed as part of ITM and TOPAZ
activities and applied in Tohoku and Kyushu. Therefore, the methodology will only
be briefly described here.
Two important parts of the spatial density estimate are the kernel function and its
bandwidth, or smoothing parameter. The kernel function is a probability density
function that defines the probability of future vent formation at locations within aregion of interest. The kernel function can be any positive function that integrates toone. A two-dimensional kernel function can be used to estimate the spatial density ofthe sources of hazardous events. Spatial density estimates using kernel functions are
explicitly data-driven. A basic advantage of this approach is that the spatial density
estimate will be consistent with known data: the spatial distribution of past volcanic
events. A potential disadvantage of these kernel functions is that they are notinherently sensitive to geological boundaries. One might hope that a complete
understanding of the geology would result in a modification of the density estimate
derived from a mathematical function. Connor et al. (2000) and Martin et al. (2004)
discuss various methods of weighting density estimates in the light of geological or
geophysical information, in a manner similar to Ward (1994). A difficulty with suchweighting is the subjectivity involved in recasting geological observations as density
functions. Furthermore, geological insight is not always consistent with event
distributions.
A two-dimensional radially symmetric Gaussian kernel for estimating spatial density
is given by (Silverman,1978; Diggle, 1985; Silverman, 1986; Wand and Jones,1995):ˆ s  N
 1  di 2 
1exp   2h 2 N i 1
 2  h  

The local spatial density estimate is based on N total events and depends on the
distance, di, to each event location from the point of the spatial density estimate, s,
and the smoothing bandwidth, h. The rate of change in spatial density with distancefrom events depends on the size of the bandwidth, which, in the case of a Gaussian
kernel function, is equivalent to the variance of the kernel. In this example, the kernel
is radially symmetric, that is h is constant in all directions. Nearly all kernel
estimators used in geological hazard assessments have been of this type. The
bandwidth is selected using some criterion, often visual smoothness of the resulting
spatial density plots, and the spatial density function is calculated using thisbandwidth.
44

A two-dimensional elliptical kernel with a bandwidth that varies in magnitude anddirection is given by (Wand and Jones, 1995):ˆ s  
where

N
 1

 exp  bT b

1
i
 2

2N H

1

b  H 1/ 2 x .

This is a simplification of a more general case, whereby the amount of smoothing by
the bandwidth, h, varies consistently in both the N-S and E-W directions. The
bandwidth, H, on the other hand, is a 2 x 2 element matrix that specifies two distinct
smoothings, one in a N-S trending direction and another in an E-W trending direction.
This bandwidth matrix is both positive and definite, important because the matrix
must have a square root; x is a 1 x 2 distance matrix, b is the cross product of x and H1/2
. The resulting spatial density at each point location, s, is usually distributed on agrid that is large enough to cover the entire region of interest.
Bandwidth selection is a key feature of kernel density estimation and is particularly
relevant to hazard assessments for monogenetic volcanic fields. Bandwidths that are
narrow focus density near the locations of past events. Conversely, a large bandwidth
may over-smooth the density estimate, resulting in unreasonably low density
estimates near clusters of past events, and overestimate density far from past events.
This dependence on bandwidth can create ambiguity in the interpretation of spatial
density if bandwidths are arbitrarily selected. A further difficulty with ellipticalkernels is that all elements of the bandwidth matrix must be estimated, that is themagnitude and anisotropy of smoothing. Several methods have been developed for
estimating an optimal bandwidth matrix based on the locations of the event data
(Wand and Jones, 1995) and have been summarised by Duong (2007). Here we use amodified asymptotic mean integrated squared error (AMISE) method, developed byDuong and Hazelton (2003), termed the SAMSE (Sum of the Asymptonic Mean
Square Error) pilot bandwidth selector, to optimally estimate the smoothing
bandwidth for our Gaussian kernel function. These bandwidth estimators are found in
the freely available R~Statistical Package (Hornik, 2007). Bivariate bandwidth
selectors like the SAMSE method are extremely useful because, although they aremathematically complex, they find optimal bandwidths using the actual data locations,removing subjectivity from the process. The bandwidth selectors used in this hazard
assessment provide global estimates of density, in the sense that one bandwidth or
bandwidth matrix is used to describe variation across the entire region.
5.1.1 Procedure for estimating probability in Chugoku
The main issue here is estimation of the probability of new monogenetic volcanism
occurring in Chugoku during some time period in the future and over some area, say
the footprint of a repository. Here, probability is estimated for four different time
periods in the future: 1 kyr, 10 kyr, 100 kyr and 1 Myr. It is assumed that the area ofthe repository of interest is 25 km2. This footprint is large enough to accommodate
most repository designs and a buffer area around the repository in the event ofhydrothermal circulation or similar processes operating around the volcano.
The issue leaves estimation of the spatial density of volcanism. That is the conditional
probability that volcanism will occur in a specific area, given an eruption in the
Chugoku region and the recurrence rate of volcanism. A complication arises in
Chugoku because it is clear from the recurrence rate analysis that different
45monogenetic volcano clusters have different rates of volcanic activity. Therefore, atleast for short time periods in the future, it is inappropriate to use a constantrecurrence rate across the entire region. For example, it appears from recurrence rateestimates that the rate of monogenetic volcanism is much greater in the Abu volcano
cluster than in the Yokota-Matsue volcano cluster. This difference needs to be taken
into account in the volcanic hazard assessment.
Therefore, for timescales of 100,000 years or less, we analyse the recurrence rates andspatial densities of monogenetic volcanism within individual volcano clusters. Spatial
density is estimated by applying the SAMSE bandwidth estimator, discussed
previously, to individual clusters. Recurrence rate is estimated from the Monte Carlosimulation of age distribution, also described previously, for individual volcano
clusters. The Monte Carlo simulation produces a range of recurrence rates because of
the uncertainty inherent in radiometric age determinations and because somemonogenetic volcanoes are not dated. For probability estimates involving the next
1000 years, we use the mean recurrence rate for each volcano cluster estimated using
the Monte Carlo simulation. For probability estimates for the next 10,000 and 100,000
years, we use the upper 95th percentile of recurrence rate, understanding that this is
likely to provide a conservative estimate of the recurrence rate. The use of the upper
95th percentile is justified because, as our analysis has shown, recurrence rate mayvary considerably on timescales of 10,000 to 100,000 years within individual volcano
clusters. With the exception of the Abu monogenetic volcano group, the upper 95th
percentile of recurrence rate is greater than all estimates of the mean recurrence rates
in Chugoku volcano clusters for the last 1 Ma.
On the other hand, it is also clear that, on a timescale of hundreds of thousands ofyears to one million years, individual volcano clusters wax and wane and new clusters
may form. For example, the Yokota-Matsue volcano cluster experienced a peakrecurrence rate approximately 1 Ma, during which time rates of activity werecomparable to those of today in the Abu volcano cluster. However, during the last 1
Ma, rates of activity in the Yokota-Matsue volcano cluster have waned considerably.
In contrast, rates of activity in the Abu volcano cluster have increased by 1-2 ordersof magnitude since 1 Ma. So, in order to forecast monogenetic volcanism in Chugoku
on timescales of hundreds of thousands to millions of years, it is necessary for themodel to be sensitive to broad regional patterns of volcanism. Local recurrence rates,
estimated for individual volcano clusters, may change entirely on these longer
timescales. Therefore, for forecasting recurrence rates of monogenetic volcanism one
million years into the future, we use average regional recurrence rates. Furthermore,
we use spatial density calculated using all volcanoes in the region to estimate aregional kernel bandwidth. This latter analysis includes polygenetic volcanoes in
Chugoku, simply because the likelihood of future monogenetic volcanism is increasedaround these volcanoes on long timescales. For example, if rates of activity wane at
the Daisen volcano over a long period of time, volcanism may transition from central
vent-dominated activity to distributed flank activity.
Once these model parameters are estimated, the probability of monogenetic volcanism
is calculated using:P[new monogenetic volcano] = 1 – exp{-λt Δt λs A}
where λt is the estimate of the recurrence rate, Δt is the time period of interest, λs isthe estimate of the spatial density and A is the area of the repository footprint. These
probabilities are contoured across the Chugoku region as logarithms to illustrate order46

of magnitude changes in probability over the region and for different performance
periods.
5.1.2 Results
For a time period of Δt = 1000 years, we use the mean recurrence rate estimated forthe four active volcano clusters. These are: 1.0 x 10-4 events per year for Abu, 1.8 x
10-5 events per year for Aono-yama, 2.9 x 10-6 events per year for Yokota-Matsue and2.3 x 10-5 events per year for Kannabe. Probability estimates are contoured in Figure5.1. Note that although the Aono-yama and Abu clusters are treated separately in theanalysis, have different recurrence rate estimates and different geochemistries, on thisplot and in subsequent plots these two clusters essentially merge into a single cluster.
Overall, the three clusters (Abu-Aono-yama, Yokota-Matsue and Kannabe) arecompact and well defined. Only a single monogenetic volcano forms an outlier on thisplot, associated with the easternmost part of the Kannabe volcano cluster.
Annual probabilities of new monogenetic volcanoes forming in a 5 km x 5 km area
within these three groups are in the order of 10-5 to 10-3. Probabilities are higher in the
Abu and Kannabe clusters and lowest within the Yokota-Matsue cluster. Although the
Yokota-Matsue volcano cluster has a similar spatial density to the other clusters, its
current recurrence rate is lower.
The Shimonoseki and Oki-Dogo volcanoes are not included in the probability
estimate for the time period of Δt = 1000 years. This is because these fourmonogenetic vents are old, current recurrence rates are essentially zero and spatial
density associated with two vents in each cluster is very low. Also, polygenetic
volcanoes are not included in this analysis.
Figures 5.2 and 5.3 illustrate the contoured probabilities for periods of interest of Δt =10,000 and 100,000 years, respectively. These maps are highly similar to the 1000year case because the spatial density used in all three models is the same. For the Δt =10,000 years and Δt = 100,000 years maps, higher recurrence rates, reflecting greater
uncertainties and longer performance periods, are assumed. For each cluster, theserecurrence rates are: 2.4 x 10-4 events per year for Abu, 3.0 x 10-5 events per year for
Aono-yama, 3.3 x 10-6 events per year for Yokota-Matsue and 3.0 x 10-5 events per
year for Kannabe. As a result, annual probabilities within the three clusters range
from 10-4 to 10-2.

47

Figure 5.1: Probability of a new monogenetic volcano forming within a 25 km2 area during the next 1
kyr (1000 years) contoured as the logarithm of probability to illustrate order of magnitude changes
across the Chugoku region. The map is based on spatial density estimation and recurrence rateestimation individually for the Abu, Aono-yama, Yokota-Mitsue and Kannabe volcano clusters. The 134
monogenetic volcanoes included in the spatial density estimate are shown as white triangles.
Polygenetic volcanoes are shown as yellow triangles; Miocene-Pliocene(?) volcano units are shown as
solid squares and active faults are indicated by green lines.

48

Figure 5.2: Probability of a new monogenetic volcano forming within a 25 km2 area during the next
10,000 years contoured as the logarithm of probability to illustrate order of magnitude changes acrossthe Chugoku region. All symbols as in Figure 5.1.

Figure 5.3: Probability of a new monogenetic volcano forming within a 25 km2 area during the next
100,000 years contoured as the logarithm of probability to illustrate order of magnitude changes acrossthe Chugoku region. All symbols as in Figure 5.1.

49

The probability plot changes dramatically for the 1 Myr case because different
assumptions are made about the spatial density (Figure 5.4). First, the Shimonoseki
and Oki-Dogo vents are included in the regional analysis for the long-term (1 Myr)case. Second, polygenetic volcanoes are included in the analysis. Third, a regional
spatial density is estimated using the SAMSE method and considering all volcanoes
together. In this analysis, a regional recurrence rate of 66 events per million years is
assumed. That is, it is expected that 66 new monogenetic volcanoes will form in the
Chugoku region during the next one million years.

Figure 5.4: Probability of a new monogenetic volcano forming within a 25 km2 area during the next
1,000,000 years contoured as the logarithm of probability to illustrate order of magnitude changes
across the Chugoku region. Here, regional spatial density is estimated using all known Chugoku
Quaternary volcanoes, including polygenetic volcanoes. Regional recurrence rate is assumed to be 66
events per million years, based on the average Quaternary recurrence rate. All symbols as in Figure 5.1.

Note that this probability map is less sensitive to the compactness of the volcano
clusters. Instead, spatial density, and hence probability, creates an overall elongatezone, parallel to the northern Chugoku shear zone and tectonic features that werepreviously discussed. Thus, the change in timescale of consideration from 100,000
years to 1 Myr causes a change in probability for three main reasons: (a) the compact
Quaternary volcano clusters are expected to persist on a timescale of 100 kyr, but notnecessarily on a timescale of 1 Myr, (b) regional patterns of volcanism and theirrelationship to plate tectonic features are emphasised in the 1 Myr model and (c)average long-term rates of volcanism are expected to best characterise volcanism onvery long timescales.
Naturally, these models can be combined and values for different parameters can bereassessed as additional information becomes available. We emphasise that ouranalysis is limited by the information available in the literature. Given the available
information, we conclude that volcanism is best characterised in terms of existing50

compact clusters of events for relatively short assessment periods. In contrast, ongeological timescales of 1 Myr or more, the expected pattern of volcanism is much
more uncertain and perhaps is best characterised in terms of regional patterns andtheir relationships to tectonic features, such as the location of the leading edge of the
subducting slab, which appears to exert a control on the locus of modern-day
volcanism.
5.1.3 Relationship of spatial models to RES models
Consider the relationship between these spatial density and probability models underassumptions made in RES 1. In RES 1, it is assumed that there is little change in thepresent configuration of plates and hence magmatism remains broadly unchanged.
This means that order of magnitude changes in recurrence rate are possible within
existing volcanic fields and there is a potential for new volcanic fields to form within
northern Chugoku. The probability model for a 1 Myr performance period (Figure5.4) best reflects RES 1. Note that, although existing volcano clusters are the most
likely locus of activity in this model, the probability of volcanism is elevated along allof northern Chugoku compared to adjacent regions.
In RES 2, volcanic activity is thought to shift north and may shift off the northerncoast of Chugoku altogether. In this case, the main effect on HLW sites potentiallylocated in northern Chugoku is a decrease in the recurrence rate of volcanism by 1
Myr in areas that are currently experiencing volcanic activity. The main effect on
probability, therefore, is to decrease the probabilities shown for northern Chugoku on
Figure 5.4. The magnitude of this decrease would reflect assumptions about the speedof migration of the subducted slab (and consequently rate of migration of magmatism).
Nevertheless, all of the elements shown in Figure 5.4 would persist (e.g. higher spatial
density in existing volcanically active areas, elevated probability along all of northern
Chugoku), albeit at lower recurrence rates. Note that, of course, spatial density of
volcanism would increase offshore in RES 2, but this increase is not necessarily
relevant to HLW repository siting. Again, the main effect of RES 2 would be
generally lower rates of volcanism in northern Chugoku and consequently generally
lower probabilities of volcanism than shown in Figure 5.4.
Similarly, RES 3 mostly impacts recurrence rate and magnitude of volcanism rather
than spatial density. Thus, the spatial density model illustrated in Figure 5.4 isapplicable to RES 3. However, the probabilities would increase to reflect theincreased potential recurrence rate. As noted previously, volcanism may shift frompredominantly monogenetic to polygenetic in this scenario, with an accompanying
shift in the nature of volcanic hazards in northern Chugoku. This potential change inmagnitude of eruptions is a major consequence of RES 3.

5.2 Estimation of spatial density using a Cox process that
assimilates geophysics
The Cox process constitutes the second stochastic model that was applied for theestimation of volcanic hazard in Chugoku. The idea of this model is to enable thecharacterisation of the uncertainty associated with the potential of volcanism (Jaquet
et al., 2008; Chapman et al. 2009; Jaquet et al., 2009), considered as a random
intensity function. By choosing a doubly stochastic model with a random potential,
the distribution of volcanic events can be described as well as the correlation with
relevant geophysical information. In comparison, when applying kernel density
51

methods, the potential is considered as a deterministic function and the model is a
non-homogeneous Poisson process.
First, the conceptual elements are given that constitute the basis for the model
development and the stochastic model is then briefly presented, followed by theestimation of volcanic hazard for the Chugoku region.
5.2.1

Conceptualisation

For this volcanic hazard assessment, RES 1 is selected as the scenario for Chugoku
evolution. This means that “the locus of the northern edge of the subducting PSP
stays in its present-day location”. In other words, for the region and the period ofinterest, the future distribution of volcanic events is assumed to remain stationary inthe space-time domain.
The following additional hypotheses are incorporated within the conceptual model:(1) the distribution of volcanic events presents spatial patterns describable using arandom potential of volcanism; it represents current geological and tectonic
knowledge and uncertainty related to processes and parametrisation; (2) the spatial
distribution of volcanic events is expected to be statistically correlated to the gravity
and magnetic signature of geological structures and (3) future events are likely to belocated in zones of past activity and their location presents some degree of statisticalcorrelation with geophysical data.
The incorporation of geophysical data into the potential means that the samegeological processes that generate magnetic and gravity anomalies give rise tovolcanism.
5.2.2 Model development
The probability of new volcanic events occurring within a small domain of the regionof interest is estimated using the Cox process (Lantuéjoul, 2002):

  Z i Z in P  N i = n= E  en!
The volcanic region of interest is partitioned into small domains, where the random
potential of domain Ai is denoted by Z i and E   is the mean. The potential
corresponds to the mean number of volcanic events in domain Ai and is interpreted
as a realisation of a random intensity function. The potential for volcanism, being
unknown, is considered as randomly structured within the context of the stochastic
model. In addition, the numbers of volcanic events within disjoint domains are nolonger independent, due to the structured behaviour of the random potential modellingthe observed patterns.
Using the potential for volcanism allows for the description of volcanic events interms of statistical distribution, scale of spatial patterns and for the integration of
additional relevant information, e.g. geophysics. The Cox process is a generalisationof the non-homogeneous Poisson process (cf. kernel density methods) characterisedby a smooth deterministic intensity function and a number of volcanic events thatremains independent within disjoint domains.
The multivariate character of the random potential is modelled by introducing thefollowing dependence relation between the Gaussian potential Yi Z and additional data52

Yi G1 and Yi G2 , expressed in Gaussian space, under the assumption that the correlations
for the potential prevail:Yi Z = ρZ G1 Yi G1 + ρZ G2 Yi G2 + 1  ρZ2 G1  ρZ2 G2 Yi R

where
represents the correlation between potential and geophysical dataset oftype 1.
corresponds to the correlation between potential and geophysical datasetof type 2. In the developed model, the potential for volcanism assimilates multiple
statistical correlations, since it presents dependencies with past volcanic activity as
well as with geophysical data.
The estimation of volcanic hazard is performed by simulating the distribution of
volcanic events likely to occur during a certain period of time in the future within theregion of interest. In addition, the simulation has to deliver volcanic events that are
more likely to be located in zones of past activity. Therefore, the simulation requires
to be conditioned to the number of past volcanic events known in each domain Ai .
The idea is to simulate the potential for volcanism conditioned on the number of
volcanic events and on the geophysical data known for the analysed region. Based on
the iterative algorithm given in Jaquet et al. (2009), the following extended algorithm
is applied for the multivariate conditional simulation of the potential:(i) generate Yi R ~ Gaussian0,1 for each Ai ;(ii) select an index i at random;(iii) generate y0 ~ D Yi R Y jR ＝y Rj , j  i  ;(iv) compute yiG1  oG11 g1,i , yiG 2  oG12 g 2,i  and





2
~2
z0  oz n~ZG1 yiG1  n~ZG 2 y1G 2  1  n~ZG
1  nZG 2 y 0 ;~(v) generate n0 ~ Noisson z 0  ;(vi) if n0 = ni ; then put yiR = y 0 and zi = z 0 ;(vii) go to (ii).
In its design, the algorithm runs forever. In practice, it is stopped when each potential
z i has been effectively updated 500 times.
At this stage, only the potential z i of the past volcanic events has been generated.
This potential is representative only of the period of timefrom which all data
originate. The aim is the simulation of volcanic events likely to occur during thefuture period of time t f , thus the future potential z if is required. Given that thepotential varies very slowly in time, past and future potentials are assumed to be
proportional. This leads to the following algorithm to simulate the future volcanic
events nif :(i) compute zif  zi  t f t p  for each Ai ;53~(ii) generate nif ~ Noissonzif  for each Ai .

The conditional simulation algorithm allows the estimation of volcanic hazard foreach domain of the region of interest during the period of time considered. A Monte
Carlo approach is performed using several thousand simulations in order to derivestable probability estimates for the future volcanic events:

PN i f  1 

1 K sim1k nif  1
K sim k 1where K sim is the total number of simulations and 1k nif  1 equals 1 when the k th
simulation assigns the domain Ai one or more volcanic events, and is 0 otherwise.
5.2.3 Datasets

For the estimation of volcanic hazard for the region of Chugoku, the following
datasets are applied:

131 monogenetic volcanic events are selected with age below 2.6 Ma(Quaternary); these events are taken from the vent locations of the 134
volcanic units, of which 94 are radiometrically dated (cf. appendix).

Bouguer gravity data from the regional digital gravity map of Chugoku thatwas established by the Geological Survey of Japan (AIST, 2002).

Magnetic data from the regional digital aeromagnetic map of Chugoku
prepared by Nakatasuka et al. (2005) and the Geological Survey of Japan(2005)

The first two datasets are shown in Figure 5.5. The aeromagnetic data applied for the
analysis are shown in Figure 2.13.

Figure 5.5: Bouguer gravity map of Chugoku (AIST, 2002). Volcanic events are indicated by triangles
and active faults by red lines.
54

5.2.4 Hazard estimation

The aim is to estimate the volcanic hazard for the region of Chugoku over proposed
assessment periods of 0.1 Myr and 0.01 Myr. The size of the domains
discretising the region of Chugoku is 5 km x 5 km; this corresponds to therepresentative area selected by the ITM methodology to include a geologicalrepository.
For the estimation of volcanic hazard, the potential for volcanism assimilates thefollowing spatial distributions: (a) Quaternary volcanic events, (b) gravity data and (c)magnetic data.
All of these datasets were sampled on a 5 km x 5 km scale for the whole region of
Chugoku. A negative binomial distribution was fitted to the experimental distributionof the number of volcanic events and the distribution for the potential is thenmodelled by a gamma distribution according to theory (Lantuéjoul, 2002). The
correlation coefficients between the potential and the geophysical datasets requiredfor hazard simulation were estimated using the methodology described in Jaquet et al.
(2009). Determination of the correlation scale was based on expert considerations
and analogue values from other regions of Japan (Jaquet et al., 2009; Chapman et al.,2009). This procedure was dictated by theoretical difficulties that have prevented thedevelopment of a general method for the estimation of the correlation scale in themultivariate case. The correlation values for Chugoku are given in Table 5.1.

Table 5.1: Cases and parameters for the Chugoku region: correlation coefficients, correlation scale
and time period.
Case

ñ Z G1 *ñ Z G2 **Variogram correlation scale [km]Time period

I

-0.33

̶

50

0.1

II

-̶

0.40

50

0.1

III

-0.33

0.40

50

0.1

IV

-0.33

0.40

50

0.01

* G1: gravity data; ** G2: magnetic data.

The estimated correlation coefficients between potential and the two types ofgeophysical data differ remarkably; for the gravity data, the value of the correlation isnegative and for the magnetic data it is positive. Since low-gravity anomalies arelikely to provide evidence for zones of preferential magma generation, some negative
correlation can be expected between volcano location and gravity data. However, in
the Chugoku region, uncertainty remains as to the geophysical interpretation of thesegravity anomalies and their relation to the volcanism. Regarding magnetic data, theobserved anomalies are more likely to reflect shallow crustal structures. A positive
correlation is no surprise, since volcanic rocks are known to produce significant
magnetic anomalies due to their mineralogical composition.
Past and future potential in time were assumed to be proportional, corresponding to
the application of a recurrence rate value of 5.0 x 10-5 events per year for the region of
Chugoku. In comparison with the variable recurrence rates applied by the kernel
55density method, this value is similar to the mean value of the recurrence rates
considered for the time periods 10,000 and 100,000 years.
10,000 Monte Carlo simulations were carried out to obtain stable probability
estimates for each of the four cases. These results are displayed in the form of
volcanic hazard maps for the region of Chugoku. The first three cases analyse theeffect of various combinations of geophysical datasets on the estimated volcanic
hazard (see Table 5.1): Case I investigates the correlation between volcanic event andgravity data; Case II the correlation between volcanic event and magnetic data andCase III the correlation between volcanic event, gravity and magnetic data. Finally,
Case IV mirrors Case III in terms of parameters and datasets, but considers theshorter time period of 10,000 years.
When considering probability values above 10-3, the hazard maps for Cases I, II and
III (Figures 5.6, 5.7 and 5.8) show roughly similar patterns for the Chugoku areas
centred on the volcano clusters of Abu (southwest), Yokota (central north) and
Kannabe (east). This is explained by the conditioning effect due to the volcanic events
when simulating the potential.
Moving away from the clusters enables the potential to be influenced by geophysics.
Remarkable differences are observed between the Abu and Yokota volcano clusters
when comparing the maps for Cases I, II and III. In particular, for the map for Case
III that uses gravity and magnetic data, a linear feature - with probability values
between 10-4 and 10-3 - is displayed that connects the two volcano clusters. Thisfeature appears to be related to the north Chugoku shear zone, which may influence
the locus of volcanism (or vice versa). However, these preliminary results highlightthe need for estimating volcanic hazard while assimilating multiples sources of data.
One difficulty remains: what types of data are more likely to provide valuable
information related to the location of future volcanism in Chugoku? Further
conceptual modelling and investigations are needed to answer these questions.
Finally, the hazard map for Case IV (Figure 5.9) shows the results when decreasing
the time period to 10,000 years. This change of timescale corresponds to forecasting
less volcanic events and consequently leads to a decrease in the simulated probability
values. This effect is particularly observable between the volcano clusters, asprobability values are dominantly below 10-4.

56

Figure 5.6: Volcanic hazard map using gravity data for the region of Chugoku displaying theprobability of one or more volcanic events for the next 100,000 years using a 5 km x 5 km domain (CaseI).

Figure 5.7: Volcanic hazard map using magnetic data for the region of Chugoku displaying theprobability of one or more volcanic events for the next 100,000 years using a 5 km x 5 km domain(Case II).

57

Figure 5.8: Volcanic hazard map using gravity and magnetic data for the region of Chugoku displaying
the probability of one or more volcanic events for the next 100,000 years using a 5 km x 5 km domain(Case III).

Figure 5.9: Volcanic hazard map using gravity and magnetic data for the region of Chugoku displaying
the probability of one or more volcanic events for the next 10,000 years using a 5 km x 5 km domain(Case IV).

58

5.2.5 Perspectives and recommendations

Within the framework of RES 1, volcanic hazard calculations were performed for theregion of Chugoku. The application of the Cox process with a multivariate potential
for volcanism has enabled the assimilation of Quaternary geological information(events and ages) as well as gravity and magnetic data. This methodology has allowed
the estimation of volcanic hazard for non-excluded domains located between volcano
clusters, away from recent and current volcanic activity. For these Chugoku domains,
the probability of one or more volcanic events in the next 100,000 years remains
below 10-3.
However, large uncertainty remains with respect to the conceptual model ofmagmatism for the Chugoku region. Further investigations are needed to reduce thisconceptual uncertainty; they will provide support to the selection of relevant
geophysical data that will provide valuable information for the estimation of future
locations of volcanism in Chugoku. In particular, seismic tomographic data from
Nakajima and Hasegawa (2007b) should be applied for hazard calculations, if
evidence of a statistical correlation can be found between these geophysical data andthe location of volcanic events.
For time periods up to 100,000 years, the application of the Cox process is based on
the following assumptions (cf. section 5.2.1): 1) for the region and the period ofinterest, the future distribution of volcanic events is assumed to remain stationary inthe space-time domain of interest and 2) future events are likely to be located in zones
of past activity. These assumptions are no longer valid when considering time periods
up to 1 Myr, e.g. new clusters of volcanoes may form away from the volcanic clustersof the Chugoku region. Therefore, the current formulation of the Cox process cannot
be used for hazard estimation for time periods beyond 100,000 years. In order toestimate hazard for migrating volcanic fronts, additional data are needed in relation tovolcanic events with ages beyond the Quaternary and new developments of thestochastic model (Cox process) are required for describing trends in the location of
future volcanism.
Finally, developments are also needed in order to include various types of volcanic
activity in the form of selected scenarios in order to estimate their specific hazards as
input to impact assessment studies.

5.3

Hazard assessment including polygenetic volcanoes

Methods developed in this report have focused on monogenetic volcanism and thetectonic setting of monogenetic volcanism in Chugoku. However, Chugoku is aregion of polygenetic volcanoes, which are dominated by central vent systems,
distributed monogenetic volcanic fields and transitional volcanic systems that are notunambiguously classified as distributed or central-vent-dominated. Distributed
volcanic fields actually have a huge range in average output rate and productivity, but
a relatively limited range in spatial intensity. Conversely, polygenetic volcanic
systems are characterised by high spatial intensity (closely spaced vents).
Characterising volcanism in this way allows us to further identify a transitional groupof volcanoes that is characterised by intermediate spatial intensity. These volcanoes(e.g. Daisen and Kirishima, Japan; Mt Adams, USA; Gegham Ridge, Armenia) arenovel because they have persistent activity from multiple vents over a broad area,
relatively high eruption rates and markedly different morphologies from classical59

central-vent-dominated volcanoes (Walker, 1993; Connor et al., 2000; Canon-Tapia etal., 2004).
It appears, from spatial distribution and time-volume relationships, that monogenetic
vent distribution reflects the lateral extent of the magma source region and the lack ofmagma focusing mechanisms (Connor et al., 2000; Valentine and Perry, 2007;
Wetmore et al., 2009). That is, distributed monogenetic volcanic fields seem to form
by individual batches of magma ascending in thin dikes vertically from a relatively
low productivity source region. In contrast, magma is focused through a uniqueconduit system for polygenetic volcanoes (Davidson and de Silva, 2000; Ida, 2009;
Annen, 2009), provided by a thermally and mechanically favourable pathway towards
the surface that is maintained by frequent eruptions (Fedotov,1981; Wadge,1982;
Walker, 1993; Annen, 2011) and favourable stress conditions (Takada, 1994; Muller
and Martel, 2001; Meriaux and Lister; 2002; Gudmundsson, 2002; Rivalta et al.,2005; Karlstrom et al., 2009; Paulsen and Wilson, 2010; Maccaferri et al., 2010).
Because favourable stress and thermal conditions appear to be a requirement forsustained polygenetic volcanism, high magma productivity is required. There areabundant examples of transitional behaviour between the end members of distributedand central-vent-dominated volcanoes (Karakhanian et al., 2002; Poland et al., 2008;
Corazzato and Tibaldi, 2006). Some systems change from one type to another overtime (Hasenaka, 1994; Goko, 2000; Hasebe et al., 2001). Furthermore, distributed
volcanism can show geochemical trends consistent with the development ofintermediate reservoirs (Umino et al., 1991; Strong and Wolff, 2003; Riggs andDuffield, 2008; Kiyosugi et al., 2010). Viewed comprehensively, these observations
suggest that we can better understand Chugoku volcanism and estimate hazards if we
consider polygenetic and monogenetic volcanism jointly in probability models.
As previously noted (see section 2), several transitional or central-vent-dominatedvolcanic systems are located in Chugoku. These include Sanbe and Daisen, the mostactive volcanic systems in this part of Japan, and Oetaka-yama. Daisen, in particular,
is characterised by multiple vents and the eruption of small batches of magma overtime. Furthermore, vents appear to have migrated at Daisen during the Quaternary.
These are hallmarks of a transitional style volcanic system. Additional Quaternary
polygenetic volcanoes are located in northernmost Kyushu (Himeshima and Futago).
Together, these five polygenetic volcanic systems create an arc that extends fromwestern Chugoku into Kyushu. The question arises: what is the change inprobabilistic hazard assessments for Chugoku if these additional systems are
considered? NUMO policy is that potential repository sites will not be consideredwithin 15 km of existing Quaternary volcanic systems. Therefore, the probability of
volcanic activity in the immediate vicinity of these existing polygenetic volcanoes
will not be considered further, nor need the effects of eruptions from these volcanoes
be considered for the performance of an underground facility at this level of analysis.
Nevertheless, the distribution of these volcanoes suggests there is some possibility offormation of new polygenetic volcanoes in the Chugoku region during theperformance period of the repository.
The event modelled in these probabilistic hazard models is the formation of a new
volcano or new volcanic system. In previous sections, for distributed monogenetic
volcanic fields, individual fields were modelled using a kernel density function. Thisis useful because the different monogenetic volcanic fields have different recurrence
rates of volcanic activity and different spatial intensities of volcanism. Consequently,
the probability maps were constructed using individual kernel functions determined60

for each monogenetic volcanic field and were summed to give a complete hazard map
for the probability of new monogenetic volcanism in the region. To forecast theprobability of formation of a new polygenetic volcano, a kernel function is fit using
SAMSE bandwidth optimisation to the distribution of existing polygenetic volcanoes
in Chugoku and northernmost Kyushu. The resulting map is then summed together
with the maps of monogenetic volcanic fields to yield a total probability of formationof a new volcano or volcanic system in the region.
Although the same statistical techniques are used, the maps for monogenetic fields
and polygenetic volcanoes are quite different because the spatial intensity ofpolygenetic volcanic systems is much lower than for individual monogenetic volcanic
fields. Instead, the spatial intensity of polygenetic volcanism reflects the wide spacingof volcanoes along the arc. Furthermore, the recurrence rate of polygenetic volcanism
is undoubtedly low in Chugoku. Here, the average rate of five new volcanoes during
the Quaternary (2 million years) is used. It is noted that the hazard rate will bestrongly affected by the assumption of the recurrence rate, which deserves moredetailed attention. For example, polygenetic volcanoes may form in a relatively brief
period of time associated with arc reorganisation, with much lower rates otherwise.
These assumptions would need to be explored further in a more detailed model, if
necessary.
Figures 5.10 to 5.12 illustrate the summed probability maps for performance periodsof 1 kyr, 10 kyr and 100 kyr, respectively. Comparison with Figures 5.1 to 5.3
demonstrates that the main effect of including the probability of renewed polygenetic
volcanism on the maps is to increase probability over a broad area of Chugoku. This
reflects the broad nature of the volcanic arc and the wide spacing of polygenetic
volcanoes. On the other hand, the probability level associated with polygenetic
volcanism is low, about two orders of magnitude less than probabilities in the Abu
volcanic field, for instance, primarily because of the very low recurrence rate ofpolygenetic volcano formation.

61

Figure 5.10: Probability of a new volcano or volcanic system forming within a 25 km2 area during thenext 1000 years contoured as the logarithm of probability to illustrate order of magnitude changes
across the Chugoku region. The map is based on spatial density estimation and recurrence rateestimation individually for the Abu, Aono-yama, Yokota-Mitsue and Kannbe volcano clusters (white
triangles) and for polygenetic volcanoes plotted on the map (orange triangles). Symbols as in Figure 5.1.

Figure 5.11: Probability of a new volcano or volcanic system forming within a 25 km2 area during thenext 10 kyr contoured as the logarithm of probability to illustrate order of magnitude changes across the
Chugoku region. Symbols as in Figure 5.1.
62

Figure 5.12: Probability of a new volcano or volcanic system forming within a 25 km2 area
during the next 100 kyr contoured as the logarithm of probability to illustrate order ofmagnitude changes across the Chugoku region. Symbols as in Figure 5.1.

63

6Commentary

The spatial density maps of volcanic hazard presented in section 5 are based on thebest available data on the age and distribution of Quaternary volcanism in Chugoku.
This distribution, together with the association of magnetic and gravity anomalies, canbe rationally explained by the current understanding of the tectonic setting of theregion and alternative models of melt generation. Thus, in the short term (considered
to be up to 10 kyr), the areas that have experienced monogenetic volcanism in the past
are likely to be those where the hazard is high, based on our analysis. This analysis
could be improved with better and more comprehensive dating, in particular using the
Ar-Ar method, but we think it unlikely that this will change the broad distribution of
estimated volcanic hazard. Although we have considered three alternative regional
evolution scenarios, none of them would change this assessment, based on the recordof Quaternary volcanism and its analysis using statistical techniques.
Moving to the longer time period of 100 kyr, the past becomes a less reliable guide to
the future. We note that volcanic clusters have developed in the region and it isentirely plausible that a new cluster might form in the region. The location of existingclusters is likely controlled by tectonic factors, but these remain poorly understood,
except that the existing clusters are quite well correlated with the inferred position of
the leading edge of the PSP. Thus, the likelihood of a new monogenetic cluster inregions that are above this leading edge is greater than in other areas; this includes
places with no record of Quaternary volcanism. The PSP leading edge will not change
its position significantly over a 100 kyr time period.
The potential question facing NUMO is to define what predicted likelihood of
volcanism would constitute an unacceptable programmatic risk for them. The EFQ
volcanism criterion is simply a first, rough cut to remove clearly unsuitable sites, butthere will be other locations where the risk of selecting a site would cause major
problems in constructing a safety case. The discussion below considers this further.
First, it must be said that this is not an exact science. The actual radiological risks that
could be calculated associated with volcanism at or near any site will vary, depending
not only on the style and magnitude of volcanism but also the geological andgeographical environment, the repository design and waste inventory and the time atwhich an impact occurs. Consequently, even if we were to fix time and magnitude,using the forecasts of likelihood generated in this study on their own does notnecessarily lead to comparable radiological risks for any two sites with equivalent
mapped hazard values. Thus, the probability values used for what is effectively a‘sub-EFQ’ second level screening need to be seen as indicators. Of course, in aprobabilistic safety assessment, the values could be used to generate the actual
radiological risks in order to evaluate a site fully, or compare two sites, but NUMO is
not yet at this level of analysis.
What, then, might be seen as constituting this second-level screening limit – thewindow of probability values that would cause NUMO concern over proceeding witha site if it lay within it? Some relevant arguments and possible quantitative limits are
as follows:
1. Some national programmes have used a lower probability cut-off value. If theannual probability of an event occurring at a repository site is less than this, itwill not be analysed in a safety assessment. A value of 10-9 per year has been
discussed. Applied to the spatial density mapping here, this would equate to64

10-4 in the 100,000 year period and 10-5 in the 10,000 year period. This figure
is extremely conservative, however, and estimated radiological risks for eventswith higher probability may still be acceptable.
2. Given that the HLW is at its most hazardous in the first few thousands of years
after disposal, a disruptive event occurring in the 10,000-year window should
be regarded as a considerably greater hazard potential than one in the next
90,000 years. This needs to be factored in when using the spatial probability
maps. On the other hand, confidence in the spatial density maps as a measureof hazard decreases for longer periods.
3. The maps have been generated for 5 x 5 km squares, about the same size as
the repository and its access zone, and thus effectively show the likelihood of
direct volcanic intrusion into the wastes. If there is concern about significant
peripheral effects of volcanic intrusion, then a larger area needs to beconsidered, up to about 15 km from the edge of the 5 x 5 km square. Thismeans that locations and possible volunteer sites also need to be evaluated interms of the surrounding squares on the maps: an area represented by a further
48 of the 5 x 5 km squares (roughly 50 times larger area) needs to beconsidered. Seen in its simplest sense, this could be done by increasing
probability values shown on the maps presented here by 1.5 orders ofmagnitude or, conversely, by using the presented mapped values that are 1.5
orders of magnitude lower probability as the indicator.
4. A completely different approach could be to regard the non-radiologicalimpacts of a volcano intersecting a repository to have such great peripheral
health and social effects that the radiological impacts could be ignored. Thisapproach seems reasonable, provided intrusion did not occur in the first few
thousands of years. Following this argument, a probability value often used asa lower cut-off for calculating health effects of 10-6 per year might be adapted
to the likelihood of volcanism – a figure of 10-6 over the total high hazard
potential period, rounded outwards to 10,000 years, might be appropriate.
These considerations give us a range of indicator values of ‘unacceptable likelihoods’(using the mapped probability contours) of:First 10,000-year period: 10-5 (from 1); 10-6.5 (from 1 and 3); 10-6 (from 4).
100,000-year period: 10-4 (from 1); 10-5.5 (from 1 and 3).

Applying these notional indicator values and considering the maps in section 5, thefollowing conclusions can be drawn.

6.1

10,000 year high hazard period

Looking first at the Cox process results in section 5.2 (Figure 5.9), it can be seen thatthe most conservative indicator of 10-6.5 tells us very little. However, even theconservative indicator of 10-5 leaves most of the region appearing to present relatively
little programme risk from monogenetic volcanism, were a site to emerge within it.
The kernel density models return results (Figure 5.2) that are even less restrictive,
with most of the region having a probability of monogenetic volcanism considerably
less than even the most conservative value of 10-6.5 in this period. These results also
allow us to consider a shorter period of 1000 years, the core period over which HLWloses much of its hazard potential. There are strong arguments for focusing mostattention on this next 1000 years. Using the most conservative value (which would be65

10-7.5 for this period, by analogy with the arguments above), it can be seen that only
locations within a few kilometres of the three main monogenetic volcanism clusters
would be eliminated.
As discussed in section 5.3, adding polygenetic volcanoes to the spatial density
analysis generates an overall increase in the likelihood of volcanism across the entire
region, owing to the widely spaced nature of these volcanoes. Applying the same
indicator values to Figure 5.11 suggests that a large area between the monogenetic
clusters would begin to challenge the acceptability test, with annual probabilities
lying between 10-5 and 10-4. For the critical first 1000 year period (see Figure 5.10) a
similar picture emerges, with most of the region having annual probabilities of new
volcanism higher than the most conservative (10-7.5) indicator level and large areas
being higher than the conservative indicator of 10-6.

6.2

100,000 year period

The kernel results present a similar story for monogenetic volcanism for this period as
for the earlier 10,000-year period, with no area outside the immediate vicinity of theclusters failing to pass the indicator test. However, the Cox process results formonogenetic volcanism (Figures 5.6 to 5.8) show that there are numerous locations
that fail the indicator tests (even the least conservative) by more than an order ofmagnitude. The elevated annual probabilities across most of the region resulting from
inclusion of polygenetic volcanoes (Figure 5.12) reinforce these conclusions. If,
however, argument (2) above is invoked for this far distant period, it can be argued
that all such sites should not be excluded but are worth considering on their individual
merits. We also note for time periods beyond 100,000 years that a more rigorous
assessment of the probability of volcanism must be performed in the context ofplausible future tectonic Regional Evolution Scenarios (RES). In particular, thelikelihood of formation of new volcanic clusters in the region would require further
investigation.

6.3

1 Myr period

Over very long periods of time, up to 1 Myr, there is considerable uncertainty inmapping out volcanic hazard. However, our analysis of the three RES indicates that,even in this time period, the hazard can be constrained. All three RES suggest themost likely prognosis to be a continuation of back-arc volcanism and development ofsome arc (adakitic) volcanism, with no major shifts in the locus of potential future
volcanism across the region. The kernel results for this period (Figure 5.4) are basedon different assumptions about controls on spatial density and also include
polygenetic volcanoes. The results suggest that tens of new monogenetic volcanoes
could form over the next million years, but this is highly contingent on the assumptionthat the system is stationary, and this is questionable. In particular, onset of significant
arc-related volcanism in the region is plausible in all three RES. Additionally, thecontrols on magma generation rates and volcano recurrence rates are too poorly
understood to have confidence in these forecasts to a million years. Although theindicator values used for the 10,000 and 100,000-year periods are therefore notconsidered to be reasonable out to 1 Myr, it can be seen from Figure 5.4 that applying
a conservative indicator value of 10-4.5 would exclude almost the whole region.
Essentially, there is a high probability that any location in Chugoku would be affectedby new volcanic activity over the next million years.

66

Over this period, major clusters of monogenetic volcanoes might develop in areas
away from the existing ones (with spatial density models thus breaking down). Thereis also the prospect (particularly in RES 3) for arc volcanism to develop, withformation of a much more defined and extensive volcanic front, with formation ofpolygenetic volcanoes. The recurrence rates of volcanism, and hence volcanic hazard,
from such a new development have not been quantified, but might approach rates
seen in Tohoku and Kyushu by 1 Myr.

6.4

Conclusions

This study has indicated that the likelihood of disruptive monogenetic volcanism inmost of the Chugoku region in the time period of central concern for radiologicalhazards from a HLW repository (up to 10 kyr) is extremely low. Only potential sitesthat are within a few kilometres of the margins of the existing monogenetic clusters ofAbu, Yokota and Kannabe appear to present unacceptably high levels of programmerisk. The hazard potential likely remains very low up to 100 kyr, but more analysis
would be needed to quantify this using the RES values, with some further
development in the probabilistic modelling of spatial density likely to be necessary. In
particular, formation of a new monogenetic cluster with relatively high hazard in anarea of currently very low hazard needs addressing. However, inclusion ofpolygenetic volcanoes in the spatial density analysis suggests annual probabilities of
volcanism that begin to challenge the ‘indicator levels of acceptability’ that have beenused as illustrations in this study, even in the first 10 kyr, highlighting the marginaland uncertain nature of this region with respect to volcanic hazard. Over the longest
time periods of interest to the safety case (1 Myr), the region will become increasingly
problematic, as it is evolving rapidly and the formation of a major volcanic front is
plausible.
In reaching these conclusions, we have applied quantitative forecasts of probability as
indicators of acceptability. Clearly, these indicators are open to discussion and others
may choose different values, or even prefer to take a largely qualitative view ofspatial likelihood maps in reaching their conclusions. We emphasise that the actual
suitability of any site should be based on site-specific risk assessment thatincorporates probabilistic data in an integrated fashion.
Nevertheless, there are uncertainties associated with this simple analysis. Additional
work is needed to narrow the current uncertainty related to the conceptual models formagmatism. These problems need to be investigated in a second phase in which
seismic tomographic datasets should be included to condition the Cox process models,
as well the relevant correlated information and datasets for forecasting the location of
future volcanism.
Finally, we emphasise again that this study has involved only a partial application of
the ITM-TOPAZ methodologies and the more in-depth evaluations suggested above
should also include the elements of the methodology mentioned in the introductionthat have not been fully incorporated here.

67

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APPENDIX: The Chugoku Volcanism Database
A database of monogenetic volcanoes in the Chugoku region has been compiled byWest Japan Engineering Consultants Inc. (West Jec). It contains latitude andlongitude of volcanic units, radiometric age determinations and chemical composition.
A volcanic unit is an outcrop or area of outcrops that are of volcanic origin, such asvents and vent complexes and lava flows (sometimes with unknown vent location). In
the original database, radiometric ages and chemical compositions were compiled
from published papers, although latitude and longitude of volcanic units were
determined independently of published sources using topographic features (e.g.
highest topographic elevation of unit) without necessarily considering the effects oferosion of volcanic units and related processes. Therefore, the number of volcanic
units identified in the West Jec database overestimates the total number ofmonogenetic volcanic events in Chugoku because each rock stratigraphic unit may
include more than one volcanic unit in the sense used in the original database.
Similarly, the number of vents mapped in Chugoku is fewer than the number of
volcanic units in the original database. Especially for pre-Quaternary volcanoes,
vents may be completely buried or eroded. In these cases, the rock stratigraphic unit
can be mapped and radiometrically dated, but the exact vent location is uncertain.
As part of the current project, the original West Jec database was revised. This wasdone primarily by returning to original geological sources and published maps tocheck the locations of rock stratigraphic units. Our main goal in this activity was todetermine the locations of monogenetic vents in Chugoku as closely as possible using
the available literature. Where rock stratigraphic units are mapped, but no ventlocation could be identified, information about these volcanic units was retained in the
database. Therefore, a volcanic unit in the revised database refers to a rockstratigraphic unit of volcanic origin that has been mapped. These volcanic units
include vents, with and without radiometric age determinations, and other rockstratigraphic units such as lava flows. A total of 360 volcanic units are included in our
database (see attached tables).
Volcano name and ID
The first columns of the Chugoku database provide regional information about the
volcano. These data include designation of the volcano cluster, region name, name ofthe volcano cluster used in the available literature, an ID assigned to the volcano or
volcanic unit and name of the volcano, if known.
Volcano location
These columns are followed by notes about the nature of the volcanic unit and its
location. For monogenetic vents with known location, the note ‘volcano (xy = vent)’
is given in the column. This note indicates that the vent location is known for thisparticular volcanic unit. Other designations indicate that the precise vent location is
unknown and the location information provided indicates the known location of the
volcanic units (not equivalent to the vent location) or of a sample point forgeochemical analysis or radiometric age determination.

Of a total of 360 volcanic units, the vent locations for 134 volcanic units can be
determined. These volcanic vents are geomorphologically clear. For example, they
have been identified on topographic maps, are mapped on geological maps and /or74

can be identified on aerial photos. A total of 94 of these 134 volcanic units areradiometrically dated. Of these radiometrically dated units, 86 are Quaternary (< 1.8
Ma).
On the other hand, vents could not be identified for the other 226 units in the database.
Most of these units are highly eroded and of course these tend to be pre-Quaternary
volcanic events. Of the 226 volcanic units for which vent locations could not be
determined, 106 have radiometric age determinations. Of these 106 radiometrically
dated units, only 18 are Quaternary. The youngest unit of these 18 Quaternary units
for which vent location could not be determined is on Oki-Dogo Island and is dated at
0.42 Ma. Instead of vent location, latitude and longitude for these units show
sampling point locations of age determinations or simply the topographically highest
points for these units if sample location is unknown.
Rock type
Geochemical analyses, at least whole rock analyses, are available for most of the
volcanic units in Chugoku. In the database, rock type is designated as: A-AND alkali andesite; AB - alkali basalt; CA - calc-alkaline andesite; AND – andesite; BAND - basaltic andesite; TH - tholeiitic basalt.
Radiometric age determinations
As in nearly all monogenetic volcanic fields worldwide, the ages of volcanic units areincompletely known in Chugoku. 200 volcanic units, of the total of 360 units, haveradiometric age determinations that have been reported in the literature. All of these
200 units have been dated with the K-Ar method. To our knowledge, Ar-Ar
radiometric age determinations or age determinations using other techniques have notbeen applied to Chugoku monogenetic volcanoes. Many units, as indicated in the
database, have multiple K-Ar age determinations.
1

Relationship between radiometric age determinations and volcano
clusters

The spatial distribution of monogenetic volcanoes was studied using the 134 volcanic
units with known vent locations. Of these units, 130 are found in four volcano clusters
on Chugoku. These volcano clusters with known vent locations are: Abu (56 volcano
units), Aono-yama (26 volcano units), Yokota-Matsue (19 volcano units) and
Kannabe (29 volcano units). Spatial density and recurrence rate were considered foreach of these volcano clusters. The four remaining volcanic units with known ventlocations are found on Oki-Dogo Island (2 units) and in the Shimonoseki region (2units) of westernmost Chugoku.
As mentioned previously, 94 of the 134 units are radiometrically dated and, of these,
86 units are Quaternary. The K-Ar ages of the eight older units are 1.89, 1.94, 2.08,
2.17, 2.34, 5.90, 7.84 and 37.1 Ma. It appears likely that the age estimates for some ofthese older volcanic units are incorrect because these age determinations areinconsistent with the youthful geomorphology of the volcano vents associated withthese units.
2

Abu monogenetic volcano group

For the Abu monogenetic volcano group, a total of 56 volcanic units with known ventlocations are included. Abu is well mapped and the volcanoes are geomorphologically75

young. There are no volcanic units in the Abu area for which vent locations are
unknown.
Of the 56 volcanic units in Abu, 31 have radiometric age determinations. Of these 31
dated units, 17 have multiple age determinations and 14 have single age
determinations. All of the volcanic units in Abu are widely separated and no
additional stratigraphic information is available to constrain the ages of events.
Therefore, the ages of the 25 undated units are sampled from uniform read on
distribution between 2 kyr and 2 Myr.
3 Aono-yama monogenetic volcano group

A total of 26 volcanic units are mapped in the Aono-yama volcano group. All of these26 volcanic units have clear vent locations. Of these 26 units, 13 have radiometric age
determinations. Of these 13, eight units have multiple age determinations and five
have single radiometric age determinations. Like Abu, no additional stratigraphic
information is available for the Aono-yama monogenetic volcanic group; the 13
undated volcanic units were assumed to have ages between 2 ka and 2 Ma and were
sampled from a uniform random distribution in recurrence rate estimates for thiscluster.
4 Yokota-Matsue region

The Yokota-Matsue region consists of two closely spaced to overlapping areas ofmonogenetic volcanism, with a total of 19 volcanic units with known vent locations
and four units with unknown vent locations. Of these 23 volcanic units, 21 areradiometrically dated. In addition, 10 of these 21 radiometrically dated units havemultiple age determinations. One volcanic unit in the Yokota region and one unit in
the Matsue region have no radiometric age determinations. In the recurrence rateestimation, the ages of these two undated units were sampled from a uniform random
distribution of ages. This age range is 2 ka – 2 Ma for the undated unit in Yokota and2 ka – 10 Ma for the undated unit in Matsue. The difference in age range reflects theage distribution of K-Ar dates of other units in these two regions. No additional
stratigraphic information is available for the Yokota-Matsue volcano cluster.
5 Kannabe-Genbudo-Mikata-Oginosen region

The Kannabe-Genbudo-Mikata-Oginosen region consists of four closely spaced
volcano groups that are collectively referred to here as the Kannabe volcano cluster.
A total of 29 volcanic units in the Kannabe volcano cluster have known vent locations.
In addition to these 29, 18 units are mapped in the Kannabe cluster but have noknown vent location, making a total of 47 volcanic units. Of these 47 units, 40 haveradiometric age determinations, including 12 units that have multiple age
determinations. For the purpose of recurrence rate estimation, the ages of the sevenremaining undated units were sampled from a uniform random distribution between 2
ka – 2.77 Ma on the basis of the known range of K-Ar age determinations in the
Kannabe cluster. Stratigraphic information was used to further constrain recurrence
rate estimates in the cluster. Two units in the cluster are bounded stratigraphicallyabove and below by other dated units. Therefore, this stratigraphic order must be
maintained in recurrence rate calculations. In addition to these two bounded units,
eight volcanic units are bounded statigraphically by dated overlying or underlying
volcanic units, but not both. Because the K-Ar age of one dated unit is not concordant
with the stratigraphic information, the age of the unit is sampled from uniform
76

distribution using the known stratigraphic relationships. In addition, palaeomagnetic
data available for one unit are also used in recurrence rate estimation.

77

Monogenetic Volcanoes
Monogenetic volcanoes in Chugoku
Volcano Cluster Volcano Cluster for spatial distribution analysis
RegionName of Volcano ClusterID
ID number of monogenetic volcano in region (cluster)
Unit Name
Name of monogenetic volcano
Accuracy of location (x and y). volcano (xy=vent)volcano (xy=vent) : Most accurate data in this databaselava (xy=location of the volcanic unit) : Less accurateNotelava (xy=Sampling point) : Less accurate
xy=Around this region : Poor accuracy
xy=From this island : Poor accuracy
x (lon)Longitudey (lat)LatitudeA-AND : Alkali andesite
AB : Alkali basalt
CA : Calc- Alkaline Andesite
Rock type
AND : Andesite
B-AND : Basaltic andesite
TH : Tholeiitic Basalt
date (mean) Mean dete calculated from dates of radiometric age determinations
error (mean) Mean error calculated from errors of radiometric age determinations
date (1)errordate (2)Dates and errors of radiometric age determinations
error
.
.

Polygenetic Volcanoes
Polygenetic volcanoes located in Chugoku and Northern Kyushu
Volcano nameName of polygenetic volcanoxLongitudeyLatitude
Age
Period of volcanci activity
Volcanic feature Topograhic feature
Rock typeRock type of magma78

Monogenetic Volcanoes
Volcano Cluster
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Abu
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
Aono
KannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeRegionID
Unit Name
Abu
Abu-21
Uyama
volcano (xy=vent)Abu
Abu-56
Daiyama
volcano (xy=vent)Abu
Abu-12
Kasayama
volcano (xy=vent)Abu
Abu-47
Higashidai
volcano (xy=vent)Abu
Abu-29Nagasawadai
volcano (xy=vent)Abu
Abu-09Hishima
volcano (xy=vent)Abu
Abu-52Hirayama 2
volcano (xy=vent)Abu
Abu-24
Nanae
volcano (xy=vent)Abu
Abu-22
Hagadai 1
volcano (xy=vent)Abu
Abu-53Oguni
volcano (xy=vent)Abu
Abu-26
Takasakadai
volcano (xy=vent)Abu
Abu-16
Nakanodai
volcano (xy=vent)Abu
Abu-08
Hashima
volcano (xy=vent)Abu
Abu-27
Kamauradai
volcano (xy=vent)Abu
Abu-50Katamata
volcano (xy=vent)Abu
Abu-38
Jyomanvolcano (xy=vent)Abu
Abu-44
Husumayama
volcano (xy=vent)Abu
Abu-54
Kaneuevolcano (xy=vent)Abu
Abu-14
Turuedai
volcano (xy=vent)Abu
Abu-17
Kitunejima
volcano (xy=vent)Abu
Abu-18
Ooshima
volcano (xy=vent)Abu
Abu-30Nabeyama
volcano (xy=vent)Abu
Abu-05
Oshimavolcano (xy=vent)Abu
Abu-25
Utajima
volcano (xy=vent)Abu
Abu-39Gongenyama
volcano (xy=vent)Abu
Abu-41Era
volcano (xy=vent)Abu
Abu-32
Hirawarabidai
volcano (xy=vent)Abu
Abu-28
Shiunzan
volcano (xy=vent)Abu
Abu-48Iraosanvolcano (xy=vent)Abu
Abu-55
Harayama
volcano (xy=vent)Abu
Abu-31
Sugihara
volcano (xy=vent)Abu
Abu-01
Aishima
volcano (xy=vent)Abu
Abu-11
Hitushima
volcano (xy=vent)Abu
Abu-35
Sengokudai
volcano (xy=vent)Abu
Abu-36
Ubukanishi
volcano (xy=vent)Abu
Abu-06
Tubasevolcano (xy=vent)Abu
Abu-45
Rikuji 2
volcano (xy=vent)Abu
Abu-42
Rikuji 1
volcano (xy=vent)Abu
Abu-10Osabaguri
volcano (xy=vent)Abu
Abu-19
Ooshima-nantovolcano (xy=vent)Abu
Abu-15
Oonoguri
volcano (xy=vent)Abu
Abu-02
Okinoshovolcano (xy=vent)Abu
Abu-03
Nishioshima
volcano (xy=vent)Abu
Abu-40
Nishidaihokusei
volcano (xy=vent)Abu
Abu-43
Nishidai
volcano (xy=vent)Abu
Abu-34Nago
volcano (xy=vent)Abu
Abu-37
Komureyama
volcano (xy=vent)Abu
Abu-49Iraosan-minami
volcano (xy=vent)Abu
Abu-20
Hutashimasho
volcano (xy=vent)Abu
Abu-04
Hukasevolcano (xy=vent)Abu
Abu-51
Hirayama 1
volcano (xy=vent)Abu
Abu-13
Hirasesho
volcano (xy=vent)Abu
Abu-07
Hashimasho
volcano (xy=vent)Abu
Abu-23
Hagadai 2
volcano (xy=vent)Abu
Abu-33
Bunjyavolcano (xy=vent)Abu
Abu-46
Andukevolcano (xy=vent)
Aono
Aono-20
Aono
volcano (xy=vent)
Aono
Aono-01
Chojyaga-hara
volcano (xy=vent)
Aono
Aono-06
Kumoi-mine
volcano (xy=vent)
Aono
Aono-13
Nosaka-yama
volcano (xy=vent)
Aono
Aono-22
Chikura-yama
volcano (xy=vent)
Aono
Aono-24
Mitake-san (Kinpo-san) volcano (xy=vent)
Aono
Aono-17
Kareki-yama
volcano (xy=vent)
Aono
Aono-12
Shikuma-dakevolcano (xy=vent)
Aono
Aono-26
Mottaga-dakevolcano (xy=vent)
Aono
Aono-11
Sengoku-dakevolcano (xy=vent)
Aono
Aono-21
Koaonovolcano (xy=vent)
Aono
Aono-15835m
volcano (xy=vent)
Aono
Aono-14
Okage-yama
volcano (xy=vent)
Aono
Aono-23
Nabe-yama
volcano (xy=vent)
Aono
Aono-07
Dake-yama
volcano (xy=vent)
Aono
Aono-09
Shirai-dakevolcano (xy=vent)
Aono
Aono-18
Maru-yama
volcano (xy=vent)
Aono
Aono-25
Tobinoko-yama
volcano (xy=vent)
Aono
Aono-02
Tokusagamine
volcano (xy=vent)
Aono
Aono-04
Funahira-yama
volcano (xy=vent)
Aono
Aono-03
Egusa-yama
volcano (xy=vent)
Aono
Aono-05
Kannon-yama
volcano (xy=vent)
Aono
Aono-08
Mihara-yama
volcano (xy=vent)
Aono
Aono-10Danbara-yama
volcano (xy=vent)
Aono
Aono-16
Ryuboshi-yama
volcano (xy=vent)
Aono
Aono-19
Benten-yama
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-04 Kannabe
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-07 Kiyotaki
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-11 Mesaka
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-06 Tada
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-08 Buri
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-03 Otsukue
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-14 Kamisano
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-17 Takura-yama
volcano (xy=vent)Kannabe-Genbudo Kannabe-Genbudo-02 Nishiki
volcano (xy=vent)Notex (lon)131.45028
131.68161
131.40163
131.60955
131.50789
131.38036
131.63931
131.47733
131.47037
131.64221
131.48925
131.41223
131.37790
131.49094
131.62971
131.58407
131.60034
131.65848
131.40254
131.41650
131.41784
131.51909
131.34019
131.47884
131.58598
131.58975
131.52574
131.50320
131.61723
131.67886
131.52529
131.27848
131.38749
131.56659
131.57034
131.35192
131.60328
131.59823
131.38724
131.41784
131.40965
131.28503
131.32827
131.58846
131.59939
131.55427
131.57671
131.62471
131.44998
131.33808
131.63263
131.40184
131.35759
131.47278
131.54349
131.60784
131.79778
131.66389
131.74500
131.75889
131.81972
131.84194
131.78500
131.75833
131.86056
131.75778
131.80833
131.77167
131.76083
131.84000
131.74528
131.75361
131.78667
131.85583
131.69528
131.73917
131.73750
131.74306
131.74528
131.75444
131.78056
131.78722
134.67500
134.69333
134.72222
134.68167
134.69583
134.67333
134.78889
134.91861134.65917

y (lat)Rock type34.48083
AB
34.48389
CA
34.44964CA
34.50213
CA
34.44012
CA
34.48423
CA
34.56445
CA
34.47961
AB
34.45179
CA
34.49001
CA
34.41365CA
34.43277AB
34.46549
AB
34.41929
CA
34.48753
AB
34.50833
AB
34.45123AB
34.47800
AB34.42444
AB
34.43842
AB
34.50179
CA
34.48106CA
34.50133
CA
34.57339CA
34.48299
AB
34.44882
AB
34.39717CA
34.46547
AB
34.52464
AB
34.59540
AB
34.43630
AB
34.50821
CA
34.51615
CA
34.46796
CA
34.49171AB
34.43500
34.49720
CA
34.49610
CA
34.46900
34.49507CA
34.47017
34.46038
34.49910
34.50558
AB
34.50114
CA
34.54098AB
34.50501
AB
34.51484
AB
34.5925134.48436
34.56727
CA
34.51827
34.48419
34.45619CA
34.42010
AB
34.47669
AB
34.46222
AND
34.27361
AND
34.45028AND
34.43389AND
34.48639
AND
34.19167
AND
34.46167
AND
34.10167
AND
34.37111
AND
34.18944
AND
34.46056
AND
34.25500
AND
34.44500AND
34.48750
AND
34.08306
AND
34.21111
AND
34.27944
AND
34.42694
AND
34.43833
AND
34.42389
AND
34.42833
AND
34.42750
AND
34.43500
AND
34.43944
AND
34.45583
AND
34.47083
AND
35.50556
AB
35.48833
AB
35.52222
AB
35.50028AB
35.49500
AB
35.51333
AB
35.50722
B-AND
35.34639
AB
35.51917
ABdate (mean)
0.01
0.02
0.02
0.04
0.08
0.09
0.10
0.11
0.11
0.11
0.13
0.14
0.16
0.16
0.17
0.18
0.18
0.18
0.19
0.19
0.19
0.19
0.21
0.28
0.29
0.30
0.35
0.46
0.52
1.94
2.34

error (mean) date (1) error date (2) error date (3)
0.01
0.01
0.01 Recent (Kimura et al 2003)
0.02
0.02
0.02
0.01
0.007
0.003
0.011
0.015
0.034
0.03
0.04
0.03
0.04
0.08
0.04
0.21
0.07
0.29
0.1
0.29
0.01
0.09
0.02
0.11
0.01
0.02
0.11
0.02
0.11
0.03
0.04
0.11
0.02
0.11
0.07
0.01
0.11
0.01
0.12
0.08
0.24
0.14
0.27
0.18
0.06
0.11
0.08
0.16
0.08
0.03
0.16
0.03
0.16
0.04
0.03
0.15
0.04
0.17
0.05
0.02
0.16
0.03
0.17
0.05
0.18
0.01
0.18
0.01
0.01
0.18
0.01
0.01
0.18
0.01
0.19
0.01
0.01
0.01
0.19
0.01
0.01
0.19
0.01
0.01
0.19
0.01
0.02
0.19
0.03
0.22
0.03
0.01
0.28
0.01
0.02
0.26
0.04
0.31
0.01
0.31
0.12
0.09
0.01
0.3
0.2
0.5
0.01
0.35
0.01
0.01
0.44
0.01
0.48
0.02
0.01
0.33
0.01
0.34
0.01
0.66
0.04
1.89
0.04
1.99
0.06
0.24
1.56
0.04
1.64
0.04
1.9
Recent (Kimura et al 2003)
Recent (Kimura et al 2003)
-0.04
0.02
-0.08
0.08

error

0.022

date (4)

error

0.039

0.024

0.02

0.76

0.05

0.06

3.1

date (5)errordate (6)-0.034

0.005

0.7

3.5

1

0.23

0.01

-0.022

0.01

0.02

0.05
0.3

no datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno dating
0.12
0.165
0.20
0.46
0.50
0.52
0.54
0.57
0.614
0.67
0.73
0.77
2.077

0.02
0.006
0.06
0.05
0.03
0.10
0.25
0.04
0.02
0.03
0.03
0.02
0.066

0.05
0.055
0.126
0.15
0.173
0.218
0.234
0.35
0.69

0.01
0.007
0.014
0.01
0.009
0.008
0.01
0.01
0.02

0.02
0.06
0.05
0.06
0.141
0.165
0.006 <0.2 (Kamata et al 1987)
0.07
0.03
0.19
0.177
0.352
0.46
0.05
0.095
0.041
0.125
0.042
1.28
0.434
0.006
0.6
0.2
0.51
0.03
0.57
0.5
0.445
0.015
0.7
0.08
0.614
0.02
0.458
0.061
0.548
0.037
1
0.73
0.03
0.335
0.033
0.357
0.024
1.615
2.077
0.066
<0.2 (Kamata et al 1987)

0.009

0.157

0.01

0.062

-0.0570.038 <0.2 (Kamata et al 1987)

0.086

0.014

0.06

0.05
0.055

no datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno dating

79

0.022
0.055
0.126
0.103
0.173
0.218
0.234
0.313
0.635

0.015
0.007
0.014
0.004
0.009
0.008
0.01
0.011
0.033

0.026

0.009

0.072

0.012

0.153

0.015

0.181

0.02

0.365
0.741

0.013
0.024

0.367

0.017

error

0.012

date (7)-0.013

error

0.012

date (8)-0.007

error

0.025

date (9)-0.004

error

0.007

date (10)-0.001

error

0.006

Monogenetic Volcanoes
Volcano Cluster
KannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeKannabeOki-Dogo
Oki-Dogo
Shimonoseki
Shimonoseki
YokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaYokotaRegionID
Unit Name
Kannabe-Genbudo Kannabe-Genbudo-09 Yamanomiya
MikataMikata-09
Midori
MikataMikata-10
Kazurahata
MikataMikata-02
Sonae
MikataMikata-05
NagaitaMikataMikata-03
NukitaMikataMikata-04
Kebioka
MikataMikata-07
Wada
MikataMikata-06
Haruki
Oginosen
Oginosen-09
Oginosen
Oginosen-16
Oginosen
Oginosen-18
Oginosen
Oginosen-19
Oginosen
Oginosen-10
Oginosen
Oginosen-08
Oginosen
Oginosen-06
Oginosen
Oginosen-07
Oginosen
Oginosen-13
Oginosen
Oginosen-02
Oginosen
Oginosen-14
Oki-Dogo
Oki-Dogo-10
MisakiOki-Dogo
Oki-Dogo-09
Saigo
Shimonoseki
Shimonoseki-03
Mutsure-jima
Shimonoseki
Shimonoseki-04
KibuneMatsueMatsue-04
Daikon-jima
YokotaYokota-03
Kami-Abire
YokotaYokota-12
Itaidani-Kita
YokotaYokota-01
YokotaYokotaYokota-08
KasagiYokotaYokota-05
NameraYokotaYokota-04
Sumouniwa
YokotaYokota-15
Koshiki-yama
YokotaYokota-09
Uenodai
YokotaYokota-16
270.5m Mountain
YokotaYokota-18
Neu
YokotaYokota-17
Takatsuka-yama
YokotaYokota-10
Kariyabara-Higashi
YokotaYokota-07
Abire
YokotaYokota-13
Nakatsudani-Kita
YokotaYokota-02
NoroYokotaYokota-14
Okidani-Kita
YokotaYokota-11
Yato
YokotaYokota-06
Mizukibara
Fukuoka
Fukuoka-09
KuroseFukuoka
Fukuoka-03
Keya-no-oto
Fukuoka
Fukuoka-16
Maru-yama
Fukuoka
Fukuoka-17
Mori-yama
Fukuoka
Fukuoka-01
Hime-shima
Fukuoka
Fukuoka-14
Omine-yama
Fukuoka
Fukuoka-15
Yakushi-dake
Fukuoka
Fukuoka-08
Genkai-jima
Fukuoka
Fukuoka-11
Bishamon-yama
Fukuoka
Fukuoka-10
Ima-yama
Fukuoka
Fukuoka-12
Nokono-shima
Fukuoka
Fukuoka-13
Aino-shima
Fukuoka
Fukuoka-04
Kaya-sanFukuoka
Fukuoka-02
Hashira-jima
Fukuoka
Fukuoka-05
Kotsukue-jima
Fukuoka
Fukuoka-06
Otsukue-jima
Fukuoka
Fukuoka-07
Kutabese
HamadaHamada-03
HamadaHamada-01
HamadaHamada-02
Hamasaka
Hamasaka-01
Hamasaka
Hamasaka-02
Hiba
Hiba-01
Hiba
Hiba-02
Hiba
Hiba-03
Hiba
Hiba-06
Hiba
Hiba-07
Hiba
Hiba-10Hiba
Hiba-12
Hiba
Hiba-15
Hiba
Hiba-16
Hiba
Hiba-19
Hiba
Hiba-08
Hiba
Hiba-04
Hiba
Hiba-14
Hiba
Hiba-11
Hiba
Hiba-13
Hiba
Hiba-05
Hiba
Hiba-09
Kanmuri
Kanmuri-13
Kanmuri
Kanmuri-06
Kanmuri
Kanmuri-04
Kanmuri
Kanmuri-03
Kanmuri
Kanmuri-09
Kanmuri
Kanmuri-08
Kanmuri
Kanmuri-07
Kanmuri
Kanmuri-05

Note
volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)volcano (xy=vent)lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)

x (lon)134.69667
134.57254
134.57893
134.51365
134.53782
134.51393
134.51476
134.55337
134.53948
134.44573
134.46853
134.47274
134.47552
134.44988
134.43998
134.42948
134.42994
134.45393
134.41972
134.46342
133.32568
133.32401
130.86389
130.94786
133.17111
133.19564
133.29771
133.08722
133.23925
133.20228
133.19988
133.40176
133.25728
133.41025
133.43046
133.41821
133.26092
133.23018
133.33244
133.18256
133.34138
133.26313
133.20843
130.23194
130.10750
130.46389
130.47028
130.04861
130.44694
130.45083
130.23139
130.26694
130.26306
130.30389
130.36111
130.16083
130.05250
130.21750
130.21917
130.22306
132.03639
131.89917
132.01778
134.43889
134.43889
132.49778
132.55889
132.72028
132.90806
132.91222
132.96778
132.98111
133.03278
133.07472
133.13222
132.94658
132.73111
133.01417
132.97861
132.98444
132.90722
132.95028
132.07583
132.03917
132.03139
132.02806
132.06417
132.05972
132.04306
132.03194

y (lat)Rock type35.49833
AB
35.54343
AB
35.39261
AB
35.39428AB
35.47843
AB
35.43649
AB
35.49649
AB
35.49871
AB
35.50815
AB
35.44202
AND
35.43176
AB
35.43210
AB
35.43229AB
35.41934
AB
35.44674
AB
35.46374AB
35.45324
AB
35.4714035.47443
AND
35.41173
AND
36.18472
AB
36.21972
AB
33.97667
AB
33.97105
AB
35.49583
AB
35.18481
AB
35.19220AB
35.19288AB
35.16316
AB
35.16198
AB
35.27189
AB
35.36587
AB
35.30552
AB
35.35612
AB
35.22799
AB
35.33967AB
35.20567
AB
35.21389
AB
35.25357
AB
35.41373
AB
35.26502
AB
35.17228AB
35.25344
AB
ＡＢ
33.69861
ＡＢ
33.59639
ＡＢ
33.80750
ＡＢ
33.81056
ＡＢ
33.57306
ＡＢ
33.79417
ＡＢ
33.79139
ＡＢ
33.68944
ＡＢ
33.61000
ＡＢ
33.58972
ＡＢ
33.78750
ＡＢ
33.76194
ＡＢ
33.57194
ＡＢ
33.69611
ＡＢ
33.67556
ＡＢ
33.67750
33.67278AB
34.85722
AB
34.71500AB
34.78528
AB
35.55444
AB
35.55528
A-AND
34.97194AB
35.08667
AB
34.94778
AB
35.03972
AB
34.98583
AB
35.08111
AB
35.09528
AB
35.06833
AB
35.04250
AB
35.09528
AB
35.06736AB
34.94778
AB
35.07917
AB
35.05083
AB
35.03278AB
35.01333
AB
35.07417
AB
34.46861
AB
34.51500
AB
34.51278AB
34.51556
AB
34.49778AB
34.49194AB
34.48500AB
34.48361
ABdate (mean)error (mean) date (1)no dating
0.216
0.008
0.216
0.691
0.021
0.691
0.87
0.03
0.87
1.256
0.036
1.256
1.292
0.038
1.292
1.502
0.055
1.502
1.53
0.04
1.47
1.61
0.08
1.504
0.442
0.014
0.442
0.502
0.018
0.502
0.502
0.018
0.502
0.502
0.018
0.502
0.542
0.013
0.542
0.67
0.02
0.663
0.98
0.02
0.974
0.98
0.02
0.974
1.013
0.029
1.013
1.133
0.042
1.133
1.138
0.042
1.138
0.55
0.09
0.55
0.94
0.04
0.63
1.24
0.06
1.18
1.38
0.04
1.26
0.12
0.05
0.05
1.11
0.03
1.01
1.12
0.05
1.1
1.13
0.04
1.13
1.16
0.06
1.16
1.17
0.05
1.17
1.18
0.04
1.15
1.25
0.08
1.21
1.25
0.04
1.17
1.27
0.05
1.27
1.3
0.04
1.3
1.32
0.06
1.32
1.48
0.04
0.72
1.89
0.05
1.57
2.17
0.05
2.17
5.90
0.21
1.09
7.84
0.25
7.84
37.12
0.61
0.97
no dating
1.13
0.12
1.13
3.19
0.16
3.19
3.39
0.11
3.39
3.42
0.12
3.42
3.43
0.25
3.43
3.52
0.15
3.52
3.58
0.07
3.64
3.65
0.10
3.59
3.66
0.11
3.66
3.71
0.11
3.71
3.78
0.10
3.67
4.14
0.11
4
4.5
0.12
4.5
no datingno datingno datingno dating
5.93
0.14
5.75
6.7
0.3
6.7
7.3
0.3
7.3
3.81
0.11
3.81
3.8
0.11
3.8
2.09
0.09
2.09
6.6
0.3
6.6
1.8
0.2
1.8
11.6
0.4
11.6
10.3
0.3
10.3
11.4
0.4
11.4
36.7
0.9
36.7
9.9
0.3
9.9
10.5
0.4
10.5
11.4
0.3
11.4
11.6
0.6
11.6
no datingno datingno datingno datingno datingno dating
8.55
0.21
8.2
no datingno datingno datingno datingno datingno datingno dating

80

error
0.008
0.021
0.03
0.036
0.038
0.055
0.06
0.05
0.014
0.018
0.018
0.018
0.013
0.027
0.028
0.028
0.029
0.042
0.042
0.09
0.09
0.05
0.05
0.23
0.05
0.05
0.04
0.06
0.05
0.04
0.16
0.04
0.05
0.04
0.06
0.12
0.04
0.05
0.19
0.25
0.04
0.12
0.16
0.11
0.12
0.25
0.15
0.11
0.14
0.11
0.11
0.1
0.11
0.12

date (2)

error

1.582
1.65

0.046
0.09

0.67
0.981
0.981

0.026
0.036
0.036

0.69
1.3
1.27
0.07
1.11
1.13

0.04
0.1
0.05
0.12
0.06
0.09

date (3)errordate (4)errordate (5)

error

0.21

0.823

0.048

0.88

0.035

1.29

0.05

1.3

0.2

1.62
0.1
1.21
1.12 -

0.08
0.12
0.06

0.1
1.06 -

0.13

0.1

0.14

0.1

0.15

1.2

0.07

1.19 -

1.94
1.98

0.04
0.12

2.05

0.19

3.87

0.2

0.07
0.04
0.06

1.24 -

1.57
1.88

0.04
0.05

1.67
1.98

0.1
0.07

1.2

0.04

15.4

0.6

39.4

1.4

71

1.2

3.51
3.7

0.1
0.13

3.94
4.07

0.28
0.12

3.64
4.35

0.14
0.28

1.31 -

0.2
6.1
0.19
0.3
0.3
0.11
0.11
0.09
0.3
0.2
0.4
0.3
0.4
0.9
0.3
0.4
0.3
0.6 Location is changed from x=132.950277777778, y=35.0741666666667.

0.3

8.9

0.3

error

1.69

1.18 1.18
1.28
1.33

date (6)date (7)

0.1

error

0.16

date (8)

0.196

error

0.017

date (9)

0.255

error

0.034

date (10)error

Monogenetic Volcanoes
Volcano Cluster

RegionID
Unit Name
Kanmuri
Kanmuri-02
Kanmuri
Kanmuri-01
Kanmuri
Kanmuri-10
Kanmuri
Kanmuri-16
Kanmuri
Kanmuri-17
Kanmuri
Kanmuri-11
Kanmuri
Kanmuri-14
Kanmuri
Kanmuri-15
Kannabe-Genbudo Kannabe-Genbudo-15 Genbudo (Aka-ishi)
Kannabe-Genbudo Kannabe-Genbudo-10
Kannabe-Genbudo Kannabe-Genbudo-01
Kannabe-Genbudo Kannabe-Genbudo-16
Kannabe-Genbudo Kannabe-Genbudo-13
Kannabe-Genbudo Kannabe-Genbudo-05
Kannabe-Genbudo Kannabe-Genbudo-12
Kibi
Kibi-10
Senyo-yama
Kibi
Kibi-33
Kibi
Kibi-30
Kibi
Kibi-13
Kibi
Kibi-18
Kibi
Kibi-21
Kibi
Kibi-07
Kibi
Kibi-14
Kibi
Kibi-15
Kibi
Kibi-19
Kibi
Kibi-20
Kibi
Kibi-23
Kibi
Kibi-27
Kibi
Kibi-31
Kibi
Kibi-32
Kibi
Kibi-34
Kibi
Kibi-28
Kibi
Kibi-26
Kibi
Kibi-17
Kibi
Kibi-16
Kibi
Kibi-06
Kibi
Kibi-05
Kibi
Kibi-01
Kibi
Kibi-02
Kibi
Kibi-22
Kibi
Kibi-29
Kibi
Kibi-25
Kibi
Kibi-09
Kibi
Kibi-08
Kibi
Kibi-03
Kibi
Kibi-11
Kibi
Kibi-12
Kibi
Kibi-24
Kurayoshi
Kurayoshi-07
Kurayoshi
Kurayoshi-01
Kurayoshi
Kurayoshi-05
Kurayoshi
Kurayoshi-19
Kurayoshi
Kurayoshi-20
Kurayoshi
Kurayoshi-22
Kurayoshi
Kurayoshi-23
Kurayoshi
Kurayoshi-21
Kurayoshi
Kurayoshi-16
Kurayoshi
Kurayoshi-14
Kurayoshi
Kurayoshi-10
Kurayoshi
Kurayoshi-08
Kurayoshi
Kurayoshi-06
Kurayoshi
Kurayoshi-04
Kurayoshi
Kurayoshi-18
Kurayoshi
Kurayoshi-13
Kurayoshi
Kurayoshi-12
Kurayoshi
Kurayoshi-17
Kurayoshi
Kurayoshi-15
Kurayoshi
Kurayoshi-11
Kurayoshi
Kurayoshi-09
Kurayoshi
Kurayoshi-02
Kurayoshi
Kurayoshi-03
Kuroiwa
Kuroiwa-07
Kuroiwa
Kuroiwa-03
Kuroiwa
Kuroiwa-02
Kuroiwa
Kuroiwa-05
Kuroiwa
Kuroiwa-09
Kuroiwa
Kuroiwa-08
Kuroiwa
Kuroiwa-04
Kuroiwa
Kuroiwa-06
MikataMikata-01
MikataMikata-08
Oki-Dogo
Oki-Dogo-04
Omine-sanOki-Dogo
Oki-Dogo-06
Oki-Dogo
Oki-Dogo-01
Oki-Dogo
Oki-Dogo-05
Oki-Dogo
Oki-Dogo-07
Oki-Dogo
Oki-Dogo-08
Oki-Dogo
Oki-Dogo-13
Oki-Dogo
Oki-Dogo-14
Oki-Dogo
Oki-Dogo-12
Oki-Dogo
Oki-Dogo-02

Notelava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)

x (lon)132.02583
132.01500
132.06528
132.11222
132.12222
132.07000
132.07944
132.08583
134.80750
134.71111
134.58694
134.81750
134.78639
134.68139
134.72694
133.31750
133.42556
133.40139
133.33000
133.34833
133.36667
133.30944
133.33083
133.33528
133.35306
133.35306
133.37000
133.37694
133.40222
133.40944
133.43944
133.38250
133.37556
133.34167
133.34111
133.30528
133.29667
133.27056
133.27556
133.36778
133.38972
133.37389
133.31444
133.31333
133.28194
133.32361
133.32972
133.37139
133.82750
133.75194
133.82083
133.93583
133.95556
133.99556
134.00361
133.99333
133.91639
133.90861
133.86667
133.86139
133.82639
133.80417
133.92278
133.90722
133.88306
133.91667
133.90944
133.87556
133.86333
133.78806
133.79806
134.12556
134.08389
134.06472
134.11389
134.16250
134.14611
134.10333
134.11694
134.48694
134.56917
133.27833
133.30944
133.25056
133.28333
133.31361
133.31417
133.36556
133.37861
133.36389
133.26111

y (lat)Rock type34.48083
AB
34.47583
AB
34.47722
AB/CA
34.36333
AB
34.40861
AB
34.39111
AB
34.39278AB
34.45472
AB
35.58944
AB
35.34167
AB
35.34444
AB
35.61278
35.58556
AB
35.33056
AB
35.33639
AB
34.74444
AB
34.70917AB
34.68333
AB
34.77583
AB
34.90972
AB
34.93278AB
34.87417
AB
34.92556
AB
34.84444
AB
34.74889
AB
34.87778
AB
34.74139
AB
34.78167
AB
34.85722
AB
34.73722
AB
34.74917AB
34.87417
AB
34.87528
AB
34.86917
AB
34.74500
AB
34.74917
AB
34.73611
AB
34.78806AB
34.79361
ABAB
34.81889
34.78722
AB
34.75639
AB
34.90111
AB
34.90472
AB
34.87667
AB
34.85861
AB
34.83778
AB
34.71361
AB
35.44083
CA
35.45722
CA
35.45222
CA
35.42083
AB/CA
35.49972TH
35.48917
TH
35.49889
TH
35.50639
TH
35.37556
AB/CA
35.42861
AB
35.44389
AB
35.44889AB
35.48667AB
36.49000
AB35.46306CA
35.49083
CA
35.50167
CA
35.40750
CA
35.40333
CA
35.43472
CA
35.46278CA
35.44722
CA
35.47028CA
35.26361
AB
35.23806AB.
35.30139
AB./CA
35.27778
AB
35.21694
AB
35.24417
AB
35.29583
AB
35.28333
AB
35.40528
AB
35.40889AB
36.30833
AB
36.31194AB
36.32417
AB
36.24000AB36.25667AB
36.31806AB
36.26944
AB
36.26556
AB
36.23833
AB
36.29639
ABdate (mean)error (mean) date (1)no datingno datingno datingno datingno datingno datingno datingno dating
1.61
0.04
1.53
2.25
0.12
1.99
2.76
0.06
2.755
no datingno datingno datingno dating
8.28
0.20
6.73
7.62
0.16
7.4
8.17
0.17
8.1
8.21
0.17
7.92
8.20
0.17
8.19
8.07
0.70
6.63
8.37
0.16
8.37
7.42
0.13
7.42
7.76
0.3
7.76
7.89
0.16
7.89
7.54
0.15
7.54
8.24
0.16
8.24
8.2
0.16
8.2
8.09
0.16
8.09
7.57
0.16
7.57
8.21
0.15
8.21
no datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno dating
1.78
0.07
1.73
1.02
0.09
1.02
1.2
0.06
1.2
2.23
0.13
2.23
5.1
0.4
5.1
5
0.4
5
5
0.3
5
no datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno dating
5.23
0.18
5
5.20
0.29
4.7
8.7
1.7
8.7
5.27
0.21
5.27
5.3
0.5
5.3
no datingno datingno datingno datingno dating
4.61
0.21
3.3
2.37
0.10
2.35
4.18
0.38
4.18
1.29
0.11
1.29
4.38
0.23
4.38
2.46
0.05
2.46
0.42
0.04
0.42
3.61 3.61
no datingno dating

81

error

date (2)errordate (3)

error

0.07
0.23
0.08

1.64
2.514
2.769

0.08
0.073
0.08

1.65

0.05

0.14
0.3
0.3
0.15
0.18
0.12
0.16
0.13
0.3
0.16
0.15
0.16
0.16
0.16
0.16
0.15

8.8
7.84
8.23
8.5
8.2
9.5

0.5
0.13
0.18
0.3
0.3
1.4

9.3

0.3

0.07
0.09
0.06
0.13
0.4
0.4
0.3

1.83

0.11

0.3
0.5
1.7
0.21
0.5

5.46
5.7

0.19
0.3

0.6
0.13
0.38
0.11
0.23
0.05
0.04

5.12
2.39

0.09
0.16

5.42

0.18

date (4)errordate (5)errordate (6)errordate (7)errordate (8)errordate (9)errordate (10)error

Monogenetic Volcanoes
Volcano Cluster

Region
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Otsu
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Sera
Shimonoseki
Shimonoseki
Shimonoseki
TsuyamaTsuyamaTsuyamaTsuyamaTsuyamaTsuyamaTsuyamaTsuyamaTsuyamaTsuyamaTsuyamaTsuyamaOki-Dogo
Oginosen
Oginosen
Oginosen
Oginosen
Oginosen
Oginosen
Oginosen
Oginosen
Oginosen
KanmuriMatsueMatsueYokotaKibi
Kuroiwa
Matsue
Hiba
Hiba
Otsu
Otsu
Oki-DogoID
Otsu-02
Otsu-06
Otsu-09
Otsu-13
Otsu-01
Otsu-03
Otsu-04
Otsu-05
Otsu-07
Otsu-12
Otsu-08
Otsu-14
Otsu-15
Otsu-17
Otsu-16
Otsu-18
Sera-21
Sera-10Sera-11
Sera-12Sera-18
Sera-27
Sera-34
Sera-15
Sera-23
Sera-17
Sera-14Sera-01
Sera-02
Sera-09
Sera-05
Sera-07
Sera-04
Sera-03
Sera-08
Sera-06
Sera-13
Sera-16
Sera-25
Sera-22
Sera-19
Sera-20
Sera-24
Sera-28
Sera-32
Sera-33
Sera-31
Sera-30
Sera-26
Sera-35
Sera-29
Shimonoseki-01
Shimonoseki-02
Shimonoseki-05
Tsuyama-01
Tsuyama-02
Tsuyama-06
Tsuyama-07
Tsuyama-11
Tsuyama-12
Tsuyama-05
Tsuyama-03
Tsuyama-10
Tsuyama-09
Tsuyama-08
Tsuyama-04
Oki-Dogo-11
Oginosen-17
Oginosen-03
Oginosen-20
Oginosen-11
Oginosen-12
Oginosen-01
Oginosen-04
Oginosen-05
Oginosen-15
Kanmuri-12
Matsue-01
Matsue-02
Yokota-19
Kibi-04
Kuroiwa-01
Matsue-03
Hiba-17
Hiba-18
Otsu-10
Otsu-11
Oki-Dogo-03

Unit Name

Shiro-yama
Myoken-zan
KatadaKajikosan
Sukumo-yama
MenyamaOnyamaNerigami
Katsumada
Owatari
Kariginu
Nerigami-Nansei
Minai-Kita
Mandai
NakairiMiyagura-yama
Kouzuike
Kirigamine, Ningyosen
wakura-yamaNotelava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=location of the volcanic unit)
lava (xy=Sampling point. I am not sure this is an inlava (xy=Sampling point)
lava (xy=Sampling point)
lava (xy=Sampling point)
lava (xy=Sampling point)
lava (xy=Sampling point)
lava (xy=Sampling point)
lava (xy=Sampling point)
lava (xy=Sampling point)
lava (xy=Sampling point)
xy=Around this region
xy=Around this region
xy=Around this region
xy=Around this region
xy=Around this region.
xy=Around this region.
xy=Around this region.
xy=Around this region. I am not sure this is an inde
xy=Around this region. I am not sure this is an inde
xy=Around this region. I am not sure this is an inde
xy=Around this region. I am not sure this is an inde
xy=From this islandx (lon)130.84611
130.90222
130.94944
130.99111
130.84083
130.87083
130.87111
130.87861
130.90944
130.98028
130.94444
131.05833
131.06361
131.09056
131.08694
131.12611
133.02917
132.91361
132.91694
132.93583
133.02278
133.06083
133.09583
133.01250
133.03361
133.02083
133.00333
132.82000
132.84694
132.90917
132.90333
132.90778
132.90194
132.89556
132.90833
132.90500
132.97722
133.01528
133.05639
133.03028
133.02417
133.02417
133.04333
133.06806
133.09056
133.09417
133.08556
133.08389
133.05694
133.11694
133.08194
130.77333
130.77889
130.97333
133.83472
133.83944
133.93639
133.93639
134.01611
134.12306
133.91750
133.88944
134.01000
133.97417
133.95833
133.91028
133.35789
134.47194
134.42083
134.48139
134.45111
134.45389
134.39278
134.42500
134.42722
134.46667
132.07583
133.09406
133.09539
133.59358
133.29375
133.88594
133.10372
133.07750
133.07750
130.97350
130.97350
133.27736

y (lat)Rock type34.34306AB
34.35972
AB
34.33861
AB
34.40750
AB
34.34750
AB
34.36806AB
34.35861
AB
34.35694
AB
34.35500
AB
34.33417
AB
34.39389
AB
34.39833
AB
34.41639
AB
34.33333
AB
34.40028AB
34.40194AB
34.65750
AB
34.67389
AB
34.69667
AB
34.71694
AB
34.55278AB
34.60194AB
34.75972
AB
34.66667
AB
34.66861
AB
34.69917
AB
34.73778
AB
34.79694
AB
34.78194AB
34.72889
AB
34.66944
AB
34.66083
AB
34.66389
AB
34.66556
AB
34.70222
AB
34.63972
AB
34.60833
AB
34.53528
AB
34.55917
ABAB
34.55778
34.58333
AB
34.61417
AB
34.61861
AB
34.45222
AB
34.66889
AB
34.66500
AB
34.66250
AB
34.65750
AB
34.77417
34.77222
34.75611
AB
33.87028
AB
33.88861
AB
34.00278AB
35.04861
35.04361
35.10000
35.10333
35.00833
35.04361
35.05917
35.07917
35.0013935.09778
35.09111
35.11139
36.29332
AB
35.44417
AND
35.47083
AND
35.44972AB
35.48611
35.42306AND
35.45444
AND
35.46639
AB
35.46583
AB
35.48111
AB
34.46861
AB
35.43610
35.60043
TH
35.18849
34.76813
AB
35.29083
AB./CA
35.47921
AND
34.96878AB
34.96878
34.44224
34.44224
AB
36.25966ABdate (mean)error (mean) date (1)
9.9
0.4
9.9
10.4
0.4
10.4
8.5
0.3
8.5
7.8
0.3
7.8
no datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno dating
9.45
0.29
8.8
9.7
0.3
9.7
9.6
0.4
9.6
9
0.8
9
7.7
0.3
7.7
9
0.3
9
12
0.6
12
no datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno datingno dating
2.63
0.16
2.63
2.49
0.07
2.49
no dating
6.25
0.18
6
5.3
0.3
5.3
4.4
0.3
4.4
5.6
0.2
5.6
4.74
0.21
4.74
no datingno datingno datingno datingno datingno datingno dating
0.79
0.13
0.79
0.565
0.019
0.565
0.671
0.02
0.671
0.743
0.021
0.743
0.938
0.039
0.938
1.076
0.032
1.076
1.091
0.026
1.091
1.149
0.033
1.149
1.184
0.047
1.184
1.225
0.046
1.225
8.9
0.4
8.9
12.1
0.5
12.1
9.7
1.6
9.7
2.38
1.97
2.38
no datingno datingno dating
10.5
0.4
10.5
12.3
1.1
12.3
9.9
0.4
9.9
10.3
0.4
10.3
2.81
0.28
2.81

82

error date (2)
0.4
0.4
0.3
0.3

0.3
0.3
0.4
0.8
0.3
0.3
0.6

error

10.1

0.5

6.5

0.3

date (3)errordate (4)errordate (5)errordate (6)errordate (7)errordate (8)errordate (9)

error

0.16
0.07
0.2
0.3
0.3
0.2
0.21

0.13
0.019
0.02
0.021
0.039
0.032
0.026
0.033
0.047
0.046
0.4 There is a lava flow which has the same location but I am not sure this unit is exactly same with that one. This unit must be around this region though.
0.5
1.6
1.97

0.4 I am not sure that thay are the same volcanic unit or not
1.1 and the location of these two nuits are very rough. These units must be aroud this location.
0.4 I am not sure that thay are the same volcanic unit or not
0.4 and the location of these two nuits are very rough. These units must be aroud this location.
0.28

date (10)error

Poligenetic Volcanoes
Volcano name

x

y

Age

Volcanic feature

Rock type

Chugoku
Daisen volcano
Sanbe volcano
Oetakayama volcano

133.546132.621132.42935.3711 ca. 1Ma - ca.20ka
Lava dome, Cinder cone、Lava flow
Dacite, Andesite
35.1403 Since about 0.1Ma. The last eruption was ca.3600 years agoPyroclastic flow-Caldera, Cinder cone, Lava dome Dacite, Andesite
35.0636 about 1.8Ma-0.8Ma
Lava dome
DaciteNorthern Kyushu
Himeshima volcano
Futago volcano

131.666131.60133.7217 about 0.35-0.2Ma
33.5831 about 1.5-1.1Ma

Lava dome, Cinder cone
Lava dome, Lava flow

83

Dacite, Rhyolite
Andesite, Dacite原子力発電環境整備機構(略称：原環機構)
Nuclear Waste Management Organization of Japan(NUMO)