FACULTEIT WETENSCHAPPEN

Opleiding Master of Science in de geologie

Academiejaar 2013–2014

Scriptie voorgelegd tot het behalen van de graad

Van Master of Science in de geologie

Promotor: Prof. Dr. Marc De Batist

Co-promotor: Dr. Dimitri Vandenberghe Begeleider: Philipp Kempf

Leescommissie: Florias Mees, Dr. Vanessa Heyvaert

Luminescence dating of tsunami sand in south central Chile – a feasibility study

Ferdinand Messens

1

Acknowledgements

First of all I wish to express my thanks to my two supervisors Dr. Dimitri Vandenberghe and Philipp

Kempf for their efforts and good guidance throughout this study. I learned a great deal from them

about the subject of luminescence dating, writing and most of all general scientific research. I am

gratefull for the effort and dedication they putted into this work.

I want to thank Ann-Eline Debeer for her help in the laboratory and preparation of my samples.

I also thank Jasper Van Nieuland for his help with the measurements.

I thank Florias Mees for his help with analysing the thin section.

I also have to thank Stephanie Eeckhout for her help and company during the last semester.

Finally I have to thank Marc De Batist for letting me do his thesis at his department.

2

Nederlandse samenvatting Deze studie is een haalbaarheidsstudie voor luminiscentie datering van tsunami afzettingen in Zuid -

Centraal Chili. Zuid-Centraal Chili is een tectonisch actief gebied waar zich megathrust aardbevingen

voordoen. De zwaarste aardbeving ooit gemeten ( 22 mei 1960) vond hier plaats en had een

magnitude van 9.5 Mw en de breukzone van 1000km. De voorschokken en hoofdschok richtte

enorme schade aan, de meeste slachtoffers vielen evenwel door de daaropvolgnde ts unami. De

enorme oceaanbodem verschuiving leidde tot een 25 m hoge tsunamigolf op de Chileense kust. De

golven bereikten heel de Stille oceaan, met slachtoffers en schade tot in Hawaii, Honshu (Japan), en

de west kust van de VS. Het totaal aantal slachtoffers is geschat op 1600 doden en 3000 gewonden.

Op 27 februari 2010 deed zich een nieuwe aardbeving voor juist ten noorden van ditzelfde gebied.

Deze had een breukzone van ongeveer 500-600 km lang en ook gevolgd door een tsunami. In totaal

zijn erdaarbij rond de 500 mensen om het leven gekomen.

Recente aarbevingen in Chili en andere locaties, onder andere deze in 2004, met een kracht van 9.2

Mw op Sumatra-Andaman en die van 2011, 9.0 op Tohoku-Oki, hebben het belang benadrukt om

de mechanismen achter deze enorme seismiek wetenschappelijk te benaderen. Risico inschatting is

een belangrijk aspect. Dit zal zeker de sociaal economische schade van zulke gebeurtenissen

beperken.. Hiervoor is een betrouwbare inschatting van periodiciteit der seismische gebeurtenissen

onmisbaar. Historische bronnen over aardbevingen en gerelateerde tsunamis in dit gebied zijn

beperkt in de tijd. Aldaar historisch geregistreerde aardbevingen kwamen voor 1960, 1837, 1737 en

de eerst geraporteerde aardbeving was in 1575. Datering van afzettingen die met zulke

gebeurtenissen te maken hebben zijn nodig om dit tijdskader uit te breiden. Voorlopig zijn zulke

dateringsgevens beperkt. Er is nood aan meer numerische wetenschappelijk betrouwbare gegevens

om een statistisch correcte herhaling te bekomen .

Verschillende sedimentaire archieven kunnen worden gebruikt om aardbevingen te dateren. In deze

studie gebruiken we sedimenten uit het kustnabije meer Lago Huelde. Zulke kustnabije meren zijn

overspoeld door tsunamis in het verleden. Dit is bevestigd door verschillende ooggetuigen (Weisner,

2003). Daardoor vormt dit een veelbelovend archief voor seismische gebeurtenissen.

Luminiscentie datering is een manier om bepaalde mineralen van een sediment rechtstreeks te

dateren. Het is gebasserd op de accumulatie van een luminiscentie signaal terwijl het sediment

begraven ligt. Dit gebeurt onder invloed van alomtegenwoordige radioactiviteit. Wanneer het

sediment in aanraking komt met licht wordt de luminiscentie geactiveerd en wordt het signaal op nul

gesteld (gebleekt).

Het mechanisme achter dit proces ligt in het feit dat electronen uit de valentieband worden

geëxiteerd in de mobiele conductieband waaruit ze dan worden gevangen in zogenaamde

electronenvallen. Electronenvallen zijn defecten in het kristalrooster waarin electronen zich

bevinden in een intermediaire energietoestand. Wanneer het mineraal in aanraking komt met licht

zullen de electronen in de gevangen toestand dit licht absorberen en in de conductieband

terechtkomen waarna ze de diferentiele energie zullen uitzenden in de vorm van licht en terug

terecht komen in de valentieband. Dat licht dat hierbij uitgezonden wordt is het luminescentie

signaal.

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De sterkte van het luminescentie signaal is afhankelijk van de totale radioactiviteit geabsobeerd door

het sediment en dus van de totale tijd sinds dat het sediment laatst in aanraking gekomen is met

licht. Daardoor kan uit de sterkte van het luminescent signaal de totale dosis geabsorbeerd door het

sediment onder de vorm van een equivalente dosis in het laboratorium bepaald worden. Om dan de

totale begravingstijd af te leiden moet ook de jaarlijkse stralingsdosis bepaald worden. Dit is de

radioactiviteit geabsorbeerd door het sediment per tijdseenheid. Dit wordt afgeleid uit radionuclide

concentraties, vochgehalte en begravingsdiepte.

Dosimeters die luminiscentie vertonen zijn kwarts en veldspaat. Kwarts wordt gestimuleerd met

optisch licht (OSL) en velspaat met infra-rood (IRSL). In deze studie worden beide getest op de

mogelijkheid om tsunami afzettingen te dateren.

Voor de bemonstering werd een composiet kernboring met een totale lengte van 5m gebruikt. Hierin

werden vier van de zes zandige lagen bemonsterd voor datering. Voor elke laag werd er een staal

genomen voor luminiscentie analyse en omgevende stalen voor de jaarlijkse stralingsdosis te

verkrijgen.

Omdat de lagen zich bevinden in niet uniforme omgeving werden vier verschillende scenarios

toegepast om de jaarlijkse dosis per laag te berekenen. Het meest accurate scenario is waar de beta

contributie berekend wordt uit de radionuclide activiteiten van het zand en waar de gamma

contributie wordt berekend volgens Aitken (1985, Appendix H). Deze methode is gebaseerd op

gradienten gamma dosis, en met verschillen in vochtegehalte en radionuclide concentraties van het

zand en van de omgevende lagen. Een eenvoudiger model welke deze gamma gradienten niet in

rekening brengt geeft een afwijking van niet meer dan 5%. Dit betekent dat voor de stalen in deze

studie geen significante fout kan gerelateerd zijn aan zulke gamma gradienten. Een andere eventueel

belangrijkere fout is het effect van het vochtgehalte. De mogelijkheid bestaat dat er gedeeltelijke

uitdroging plaatsvond gedurende het transport en opslag van de kernen. Het in-situ vochtgehalte kan

dan niet met zekerheid worden bepaald.

De luminiscentie karaktiristieken van kwarts werden in een eerste fase van deze studie bepaald met

het SAR protocol (Murray and Wintle, 2000) met extra IR (infra rood) zuiverheidstest (post-IR OSL) .

Doch, bij nader inzien kon er geen zuiver kwarts bekomen worden, er bleef met name een

contaminatie van veldspaat bestaan. Bijgevolg werd er een dubbele SAR-protocol toegepast, daarbij

werd het IR signaal op voorhand gestimuleerd opdat het niet het opvolgende OS L signaal zou

contamineren. Maar het post IR-OSL signaal was dof, niet gedomineerd door een snelle component

en had een slecht gedrag in het SAR-protocol , dit werd aangetoond door recuperatie, recyclage en

dosis herstel. Een microscopische studie toont ons dat het slechte gedrag kan gelinkt worden aan het

feit dat de kwarts zich in onzuivere polykristallijne lithische fragmenten bevindt. De algemene

conclusie is dat kwarts zich in feite niet goed leent om op deze locatie tsunami afzettingen te

dateren.

Het onderzoek moest zich hierdoor toegespitsen op K-veldspaat als dosimeter. Een nadeel van K-

veldspaat als dosimeter is dat het lijdt onder anomaal signaal verlies. Voor dit te remedieren werden

er metingen van anomaal signaal verlies (fading) gedaan en werden de waarden gecorrigeerd volgens

de methode van Huntley and Lamothe 2001. Voor de equivalente dosis bepalingen werd een IR

stimulatie gebruikt op 50°C (IR50) en de luminiscentiekaraktiristieken werden bestudeerd met het

SAR protocol.

4

Het K-veldspaat had een helder IR signaal en vertoonde een goed gedrag in het SAR protocol, in

termen van recyclage en recuperatie. We hebben ook de afhankelijkheid van equivalente dosis, en

van fading, en van gecorrigeerde ouderdommen tegenover voorverhitting, geanalyseerd voor twee

stalen. Een lage voorverhittingstemperatuur van 80°C bleek de meest aangewezen methode omdat

deze minimaal lijdde onder ongewilde thermische transfer. Deze laatste die leidt tot overschatting

van equivalente dosissen en ouderdommen. Er zijn geen hogere temperatuurs stabiele signalen

gevonen zoals aangewezen door eerdere studies.

De distributies van equivalente dosis, fading en gecorrigeerde ouderdom werden bestudeerd voor al

de stalen. Brede distributies werden waargenomen. De gecorrigeerde ouderdom van de oudste twee

stalen leken buiten de outliers uit één populatie te bestaan. De spreiding, 20% in deze stalen, is de te

verwachten spreiding voor een goed gebleekt ongecontamineerd staal. De jongste stalen vertoonden

een duidelijke asymetrie in de ouderdoms spreiding met een extensie naar hogere ouderdommen.

Hogere ouderdommen werden hier uitgesloten tot men voor het gross der stalen een distributie

overhield van jongere ouderdommen met een spreiding van 20%. Dan is de gemeten ouderdom min

of meer consistent met de stratigrafische positie van de samples en gaan deze van 0.174 ka tot 1.64

ka. De twee onderste stalen vertonen een ouderdoms inversie. Dit zou kunnen door door een

onderschatting van de onzekerheid, bepaalde transport en depositie processen of verkeerde

assumpties rond dosimetrie.

Er was ook een kort onderzoek over het potentieel van het p-IRIR290 signaal (Buyleart et al., 2012). Dit

signaal is niet geaffecteerd door anomaal signaalverlies. Het werd aangetoont dat de samples zich

goed gedragen in een p-IRIR SAR procedure en dat het anomaal signaalverlies inderdaad

verwaarloosbaar is. Ondanks deze eigenschappen is deze procedure niet toepasselijk voor de stalen

van deze studie. De ouderdom had een overschatting van ca. 6 ka en de standaard fout was groot.

Dit zou kunnen geïnduceerd zijn door thermale transfer of de hoge mate van onvolledige bleking.

Onvolledige bleking is aannemelijk omdat het p-IRIR signaal minder snel gebleekt wordt door zonlicht

(Buyleart et al., 2012). Daardoor is de p-IRIR methode waarschijnlijk niet goed toepasbaar op

Holoceen sediment.

In het algemeen kan er geconcludeerd worden dat het IR50 methode op K-veldspaat zich heel goed

leent om jonge tsunamigene sedimenten te dateren. Deze conclusie is aangesterkt door e en

vergelijking met algemene ouderdomsinformatie. De dateringen van de twee bovenste stalen komen

overeen met historisch gedocumenteerde en eerder gedateerde seismische activiteiten en met een

correlatie naar een 14C gedateerde boorkern, ook uit Lago Huelde. Deze studie geeft ook het eerste

sedimentologische bewijs voor een tsunami getriggert door de 1837 AD aardbeving die wordt

beschreven in historische bronnen.

5

Contents

1. Introduction ...........................................................................................................................7

2. Setting ...................................................................................................................................9

3. Geological framework .............................................................................................................9

4. Historical Valdivia Segment earthquakes................................................................................ 12

5. Core description and independent age information ................................................................ 17

6. The Luminescence dating method. ........................................................................................ 20

6.1 Introduction ................................................................................................................. 20

6.2 Principles ...................................................................................................................... 20

6.3 Stimulation and signals.................................................................................................. 23

6.3.1 Feldspar IRSL and Quartz OSL ................................................................................. 24

6.4 De determination: SAR protocol..................................................................................... 25

6.5 Annual dose determination ........................................................................................... 27

6.6 errors in young samples................................................................................................. 29

6.6.1 Partial bleaching .................................................................................................... 29

6.6.2 Thermal transfer .................................................................................................... 31

6.6.3 Alteration of sedimentary enviroment .................................................................... 32

6.6.4 Other errors .......................................................................................................... 32

6.7 Thermal and a-thermal stability ..................................................................................... 32

6.7.1 pIRIR dating method .............................................................................................. 37

7. Luminescence dating of tsunami deposits .............................................................................. 39

8. Thin sections ........................................................................................................................ 44

8.1 observations ................................................................................................................. 44

8.2 interpretations.............................................................................................................. 49

9. Luminescence investigations ................................................................................................. 51

9.1 Sampling ...................................................................................................................... 51

9.2 Sample preparation and analytical facilities .................................................................... 52

9.3 Dosimetry..................................................................................................................... 56

9.4 Quartz OSL.................................................................................................................... 58

9.4.1 Experimental details .............................................................................................. 58

9.4.2 Luminescence characteristics ................................................................................. 59

9.4.3 Discussion ............................................................................................................. 61

9.5 Feldspar IRSL ................................................................................................................ 62

9.5.1 Experimental details .............................................................................................. 62

6

9.5.2 IR50: Luminescence characteristics .......................................................................... 62

9.5.3 IR50: Distributions and ages..................................................................................... 69

9.5.4 pIRIR290: Luminescence characteristics .................................................................... 83

9.5.5 pIRIR290: ages ......................................................................................................... 85

10. Dating results: Discussion .................................................................................................. 87

11. Summary and Conclusion. ................................................................................................. 92

12. references ........................................................................................................................ 94

7

1. Introduction

South-central Chile is a tectonically active region where large megathrust earthquakes frequently

occur. The largest earthquake that was recorded during the past century took place in this particular

region, on 22 May 1960. It had a magnitude of 9.5 Mw and the rupture zone stretched over ca. 1000

km. The main and foreshocks caused major destruction but most of the casualties were caused by

the following tsunami. The enormous seafloor shift caused the tsunami to rise up to 25 m on the

Chilean coast. The wave extended over the whole Pacific Ocean. Casualties and major damage was

also reported at distant locations (Hawaii, Honshu (Japan), Pacific coast of US). The total death toll by

this event is estimated at approximately 1600 people and about 3000 people were injured. On

27/02/2010, another earthquake occurred just north of the region that was ravaged by the 1960

earthquake. The rupture zone stretched over 500-600 km and this earthquake was also followed by a

tsunami. Together, the 2010-earthquake and tsunami were responsible for more than 500 deaths.

The recent earthquakes and tsunamis in Chile, as well as along other subduction zones (e.g. 2004 Mw

9.2 Sumatra-Andaman and 2011 Mw 9.0 Tohoku-Oki), emphasise the importance of understanding

the mechanisms underlying such megathrust seismic events. In order to reduce the social, economic

and environmental damage induced by such destructive events, risk assessments must be made.

Knowledge on recurrence times is essential to such risk assessments. However, historical records

provide only limited information on the occurrence and timing of earthquakes and associated

tsunamis (Lomnitz, 1970), while dating studies of prehistoric events in this region are few. There is

thus a clear need for more numerical age information on palaeoseismic events in order to obtain

meaningful and statistically reliable recurrence times.

A variety of archives have been used to date past seismic events in the region. (Moernaut et al.,

2007; Moernaut et al., 2014) used lacustrine seismoturbidites, which were dated by varve counting.

Cisternas et al. (2005) used radiocarbon dating of co-seismically subsided and drowned trees in

combination with diatom assemblages in the Rio Maullín estuary to obtain recurrence times of

seismic events. It is also possible to constrain past tsunami events in time by distinguishing and

dating tsunami deposits in near coastal lakes (Kempf et al., 2013). This approach is based on the

assumption that past tsunamis inundated coastal lakes and deposited course grained sediment. The

coastal lakes are a potentially very valuable archive of past tsunami-laid sands, as sediments in this

environment tend to be buried and remain preserved over time.

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Luminescence dating offers a means to directly date the tsunami-laid sands. The method is based on

the time-dependent accumulation of a luminescent signal in sedimentary mineral grains, as a result

of their exposure to natural radioactivity. The luminescent signal is zeroed when the mineral grains

are exposed to light. The method can be thus used to estimate the time that has elapsed since buried

sediment grains were last exposed to sunlight and to establish sediment deposition chronologies.

One important advantage of luminescence dating is that it does not use associated material but the

constituent mineral grains (such as quartz and feldspar) of the sedi ment itself. Equally as important is

the wide time span covered by luminescence dating techniques, which ranges from hundreds of

thousands of years to decades or even years. In recent decades, luminescence dating has gone

through considerable technological and methodological developments and it is, at present, probably

the most widely used Quaternary radiometric method after radiocarbon (Duller, 2012).

This study aims at assessing the potential of luminescence dating for establishing meaningful

chronologies for tsunami-laid sands in near coastal lakes in south central Chile. The sediments that

were investigated in the frame of this feasibility study were taken from a core that was drilled in Lake

Huelde on Chiloé Island.

Chapter 2, 3 and 4 present repectively the setting, geological framework of the study area and an

overview of historically recorded earthquakes in this region. In Chapter 5 a brief description of the

sampled core is given and a tentative correlation to another core is introduced. Chapter 6 briefly

introduces the basic principles of the luminescence dating method. Previous studies have shown that

luminescence dating may offer a powerful means to date tsunami deposits; these are d iscussed in

Chapter 7 and illustrate the underlying assumptions with respect to resetting of the luminescence

clock in this particular depositional environment. Chapter 8 reports on a microscopic study of the

deposits using thin sections, with particular relevance to luminescence investigations and

observations presented in Chapter 9. The final age results are discussed in Chapter 10. Where

possible, the results are compared with independent age information for regional seismic events.

Conclusions are then drawn both with respect to the use of luminescence methods to date past

tsunamis in this region, and the chronology of these events as recorded in the study area. A summary

and conclusion is given in Chapter 11.

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2. Setting

The sediment cores were obtained out of the coastal Lake Huelde (42.596313 °W, 74.114826 °S;

Figure 2-1). It is located at the south central part of Chile on Chiloé Island. It is maximum 11 m deep.

The barrier between the ocean and the lake’s western shoreline is ca. 1,1 km. Between the lake and

the Ocean there are shrubs, ancient dunes, which used to be mobile but are now overgrown,

anthropogenic grazing grounds and beach (Figure 2-1). The lake is mostly surrounded by thick forest

which is located on a higher terrace of glacifluvial sediment. The lake has an outflow to the sea and

two inflows from the inland. The core location is in a deeper part near the mouth of the drainage

channel (red dot Figure 2-1). Eye witness reports from the village of Cucao close to Lake Huelde

suggest high-energetic tsunami inundation during the 1960 AD event (Weisner, 2003).

Figure 2-1: the location of the study site on the map of South America. B: the location of the study site on the m ap of the

island Chiloé. C: the land fill of the area around Lake Huelde. The red dot is the sampled location of the studied core.

(Kempf, P)

3. Geological framework

The western coast of South America (Figure 3-1) is near an active continental margin. The oceanic

Nazca plate is subducted under the continental South American plate. The fault where the two

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lithospheric plates touch is a megathrust and is the origin of earthquakes like the one in 1960 (Plafker

and Savage, 1970). Where an oceanic plate is subducted an oceanic trench is formed, in this case the

Peru Chile trench. Here the oceanic trench has a thick sediment layer (1 - 1.5 km) due to the fast

denudation of the Andes and the glacial activity since the Pliocene. On the continental side of the

trench there is an accretionary wedge. Secondary splay faults emerge from the deformation of the

megathrust. They form landward dipping fault planes that propagate trough the accretionary prism

(Park et al., 2002). These influence the seismic behaviour of the subduction zone. Their location

seems to mark the updip limit of megathrust earthquake rupture propagation (Collot et al., 2008).

They can restrain propagation of earthquakes by inelastic deformation (Melnick et al., 2012).

The mid oceanic ridge that forms the border between the Antarctic and the Nazca plate i s called the

Chile Rise. New oceanic lithosphere is formed here. The point where the Antarctic, the Nazca and the

South American plate meet is called the Chile Triple Junction (CTJ). This boundary constrains seismic

events. (Figure 3-1)

Figure 3-1: : Plate tectonic setting of the Southern Andes. Abbreviations: LOFZ = Liquiñe-Ofqui Fault Zone,

MFZ = Magellanes Fault Zone, CTJ = Chile Triple Junction (dots indicate the northward migration of

the CTJ during the Neogene), SVZ = Southern Volcanic Zone of the Andes. Stars mark the locations of

historic earthquakes (associated with volcanic eruptions in the SVZ). Arrows indicate horizontal

displacements. Dark shaded continental areas are higher than 2000 m. (Rosenau, 2004). B:

11

In the vicinity of Chiloé Island there is the Liquiñe-Ofqui Fault Zone (LOFZ) (Figure 3-1). It is the strike

slip expression of the oblique convergence of the Nazca and the South American Plate. It delineates

the Chiloé microplate with the South American Plate.

The megathrust and splay fault rupture zones del imit seismic segments on this continental margin.

Earthquakes are bound to these segments and occur at different times in different segments. These

segments do not seem to overlap (Thatcher, 1990). Three features are proposed to give rise to the

segmentation (Melnick et al., 2009): bathymetric anomalies of the subducting oceanic plate,

sediment thickness in the oceanic trench and discontinuities within the upper continental plate. This

study area is located on the Valdivia segment, which extends from 36°S to 45°S. The extend of the

Valdivia segment equals that of the continental Chiloé block (Melnick et al., 2009).

Along the Valdivia segment the recent frontal accretionary prism (FAP) is =< 10 km wide and the

subduction channel is 1,5 km thick (Melnick et al., 2009; Contreras-Reyes et al., 2008). The

lithosphere subducted along the Valdivia segment is comparatively young (0 – 35 Ma). However,

within the Valdivia segment there are several fault zones within the oceanic plate which separate

oceanic lithosphere of different ages (Chiloe FZ, Valdivia FZ). In the sector of Chiloé Island the shelf

has a large width of 60 to 100 km.

Figure 3-2: Geological map of the area. The red arrow marks the study area. Q1g1 = Pleistocene holocene glacifluvial

deposits. PzTr4 = Paleozoic Triassic metapelites, metabasanites, metachert. Q1g2 = Pleistocene, Holocene, alluvial and

glacifluvial deposits. M1m = transgressive Miocene sediments (Geologica digital, No. 4, 2003)(Geología, 2003)

12

The active continental margin of South America produced volcanic, metamorphic and igneous rock

formations in association with subduction mechanisms. The geomorphology is profoundly influenced

by past glaciations, especially the Last Glacial Maximum (LGM) (Glasser et al., 2008; Heusser and

Flint, 1977). Although there is not much information on the geological history of that specific region

we can suspect that Lake Huelde is a remnant of a proglacial lake, just like the nearby Lake Cucao

(Villalobos et al., 2003). Lake Huelde is surrounded by glacifluvial sediment which rests on igneous

and metamorphic bedrock (Figure 3-2).

The metamorphic bedrock is a part of a metamorphic complex that extends along the continental

margin from 34°S to beyond 50°S (Glodny et al., 2005). This complex is considered to be formed in a

paleo-accretionary wedge on the active margin of Gondwana (Herve, 1988). The metamorphic

formations on Chiloé are part of the “western series” as described by Aguirre et al. (1972). Which

often contain highly recrystallized chert, clastic, mafic volcanic and ultramafic rocks with pervasive

lower grade (greenschist) assemblages. The fragmentary remains of pillow lavas suggest a deep

marine origin of the western series (Herve, 1988). The metamorphic rocks on Chiloé Island contain

highly recrystallized schists which are in the greenschist facies (Watters and Fleming, 1972). Quartzo-

feldspathic schist and locally greenschists are present (Watters and Fleming, 1972).

On the Island itself there is no active volcanism. Onshore east and north-east of the island volcanoes

are presently active (Figure 3-2 black arrows). The island Chiloé is separated from the main land by

the submarine continuation of the Great Central Valley of Chile (Watters and Fleming, 1972).

4. Historical Valdivia Segment earthquakes

The mean recurrence time of megathrust earthquakes on the Valdivia segment based on the

historical record starting around 1540 AD is 128 years (Lomnitz, 2004). However Cisternas et al.

(2005) found with a combination of radiocarbon dates on sediments and ages of, due to co-seismic

subsidence, drowned trees a recurrence time of 285 years. However there is still not enough data for

solid estimations of recurrence times on the Valdivia segment.

Historically recorded earthquakes occurred on the Valdivia segment in 1575 AD, 1737 AD, 1837 AD

and 1960 AD (Lomnitz, 1970; Lomnitz, 2004).

-The earthquake of 1575 AD is reported by Spanish conquistadores at the time. The descriptions

suggest a major earthquake with a tsunami just like the 1960 event (Lomnitz, 2004).

Paleoseismological studies on mass transport deposits in lakes in south central Chile confirm the

13

similarity between the signal of the 1575 AD and 1960 AD earthquake (Moernaut et al., 2014). This

suggests that the 1575 event was a giant earthquake that caused major co-seismic tectonic

movement (Mw > 8.5).

-The 1737 AD event is reported fragmentary based on witnesses. A magnitude of ca. 7.5 Mw is

assumed (Lomnitz, 2004). It was a megathrust earthquake with no historically and so far no

geologically recorded tsunami (Lomnitz, 2004; Cisternas et al., 2005). This earthquake produced little,

if any, subsidence at the Rio Maullín estuary (location on the mainland north of Chiloé) (Cisternas et

al., 2005). It is fragmentarily observed in landfall sediments (Moernaut et al., 2007). It caused only

isolated damage in Valdivia and Chiloé (Lomnitz, 2004). The minor damage and the absence of a

reported tsunami led Garrett (2013) to propose a rupture zone of 500 km in a less populated area

from the northern part of Chiloé to the Chile triple junction (Figure 4-1). Moernaut et al. (2014)

however suggests, according to observed lacustrine turbidites, that the 1737 earthquake rupture

zone was between ca. 39°S and 41°S (further north) (Figure 4-1).

-The next historically recorded earthquake was in 1837. It had a magnitude of 8 Mw (Lomnitz, 2004)

to 9 Mw (Moernaut et al., 2014). The seismic activity is reported from Valdivia to the most southern

outpost at the time (Castro, Chiloé). The accompanying tsunami inundated flat land in northern

Chiloé to a distance of 900 m, but caused little damage (Lomnitz, 1970). Also here there is a notable

absence of this event in the sedimentary record (Cisternas et al., 2005). This earthquake produced

only minor subsidence at the Rio Maullín estuary (Cisternas et al., 2005). In fact there is very little

evidence for deformation from this event in all the so far studied areas in the northern half of the

Valdivia segment. Based on information at the time Reed et al. 1988 proposed a seismic slip of 15m

from Valdivia to the Chile triple junction (Figure 4-1) (750 km). However there is still too little

information to confirm this and there is lack of evidence for co-seismic subsidence in the northern

part of Chiloé (Chucalen, Maullín) (Garrett, 2013). Moernaut et al. (2014) concludes out of lacustrine

turbidites that the rupture area of the 1837 event was significantly south of the 1737 rupture area.

The large tsunami resulting from this minor earthquake argues for a rupture area near the oceanic

trench (Moernaut et al., 2014).

14

Figure 4-1: The range of the historical rupture zones. The blue line is the extend of the 1960 AD EQ rupture zone. The

dashed orange line is the rupture zone of the 1837 AD EQ as proposed by Reed et al. (1988). The red line is the 1837 AD

rupture proposed by Moernaut et al. (2014) with the possible extend of the dashed orange line. The green line is the

rupture zone of the 1737 EQ as proposed by Moernaut et al. (2014). The purple line is the rupture zone of 1737 AD

proposed by Garret (2013). The black line is the probable rupture zone of the 1575 AD EQ.

-The earthquake of 1960 AD was the strongest ever recorded (9,5 Mw). This earthquake resulted in a

tsunami from which the deposits are preserved in the sediment record (Cisternas et al., 2005). In the

43 years after this event less than half the seismic events with MW > 8 occurred compared to the

same period before. This, and the longer historical record lead Lomnitz (2004) to formulate the

hypothesis of earthquake clustering on the South American margin. Plafker and Savage (1970)

studied the deformation that resulted from this earthquake. The deformation was a roughly

sinusoidal deformation with onshore synclinal subsidence bordered by offshore and inland anticlinal

uplift (Figure 4-3). At Lago Huelde there was a subsidence of ca. 1m (Figure 4-3). Plafker and Savage

(1970) concluded that there was co-seismic slip of 20 m along a 1000 km long megathrust near the

continental margin. (Figure 4-1)

15

Figure 4-2: The deformation induced by the 1960 earthquake. A clear synclinal/anticlinal pattern is visible. (Plafker and

Savage, 1970)

Figure 4-3: The amount of co-seismic subsidence induced by the 1960 EQ on Chiloé island. The red arrow marks the study

site. (Plafker and Savage, 1970)

16

17

5. Core description and independent age information

The investigated core (“Pos12”; fig 1) is a composite core from one location with a total length of 5

m. Line scan core images, a lithographic log, the locations of sub-sampling, a magnetic susceptibility

log and a gamma ray attenuation density log are given in Figure 5-2.

Sandy layers are present throughout the core. The sand layers have a high magnetic susceptibility

and density (Figure 5-2). In core “pos12”, six sandy deposits were recognised on the basis of their

lithological and magnetic properties, which are labelled in Figure 5-2 as 12A to 12F. They are

interpreted as event deposits.

The uppermost layer (12A) is not sampled. It contains a mud cap on top which is distinguished by its

lighter color.

The luminescence dating starts from layer 12B (Figure 5-2 dating nr1) (GLL-133402). This is a 14 cm

thick sand layer.

The underlying sand layer 12C is also sampled for luminescence dating (Figure 5-2 nr2) (GLL-133406)

and is interpreted as a sandy event deposit of 32cm thick with 10 cm mud rip-up clasts intercalated

in the middle. These rip-up clasts are recognised by their muddy content in the otherwise sand

surrounding and a lamination in non-horizontal directions. An erosional basis is observed on the

bottom of the layer

The 12D event deposit (Figure 5-2 nr3) (GLL-133410) consists of two sandy layers of 1cm.

The underlying event deposit 12E contains again mud clasts (Figure 5-2 nr4) (GLL-133413). It is 13 cm

thick and the bottom 5 cm consists out of mud rip up clasts.

The lowermost sampled event deposit 12F (Figure 5-2 nr 5) (GLL-133417) is a 6 cm thick sand layer.

Plant fragments can be found throughout all the sand layers. Despite the presence of volcanos in the

area no distinct tephra layers were found.

In this study the sandy deposits are interpreted as tsunami laid sands. The sandy layer in combination

with mud rip-up clasts, erosional lower contacts and a content of ground plant fragments are

diagnostic features for tsunamigenic sediments (Goff et al., 2004; Kortekaas and Dawson, 2007).

However no exclusion can be given about the exact forming conditions.

The investigated core in this study “pos12” is tentatively correlated to a nearby core “pos15” (Figure

5-2) based on lithological and magnetic features. The sampling locations are given in Figure 5-1. Core

18

“pos15” is dated with 14C (calibrated to calendar ages with the SHcal04 calibration curve) and

137Cs/210Pb by Kempf et al. (2013). The ages are represented in Figure 5-2. All the 14C datings on core

“pos15” are performed on plant fragments.

The core “pos15” also contains sandy deposits with occasionally mud rip up clasts (Kempf et al.,

2013). The upper sand layer is dated with 137Cs/210Pb (Kempf et al., 2013) with the method of Pinglot

and Pourchet (1995) and linked to the event of 1960 AD. This layer shows fini ng upward and contains

a clear mud cap with a low organic content (Kempf et al., 2013). Due to the similarities of this mud

cap it can be correlated to the uppermost layer (12A) of “pos12”.

The overall background sediment of both cores consists of low dens ity, organic rich, clayey silt.

(Kempf et al., 2013). Sporadically, the background sediment is finely laminated on a mm scale. The

lamination consists of light / dark coloured couplets; it is not clear whether these can be interpreted

as varves.

At some depths, grey-coloured layers are present in both cores that contain less organic material

(Kempf et al. 2013). In terms of density or magnetic susceptibility, they cannot not be distinguished

from the surrounding mud. Similar layers have been identified in other cores that were taken in the

lake (Kempf, priv. comm.); it is not clear what they represent.

Figure 5-1: locations of core samplings “pos 12” (red) and “pos 15” (yellow).

19

Figure 5-2: : Litholog of core pos 12 with location of luminescence datings, magnetic susceptibility log, density log and a tentative correlation to core pos 15. Data from MSCL sca nner.

20

6. The Luminescence dating method.

6.1 Introduction

Luminescence dating consists of a family of numerical dating methods that can be used to determine

the time that has elapsed since mineral grains (such as quartz and feldspar) were last exposed to

heat or light. The methods can be applied in different archaeological and environmental settings and

cover an age range from a few years to several hundred thousands of years. Early developments in

the nineteen sixties and seventies mainly concerned heated ceramics and burnt flint and stone. Over

the past twenty year or so, however, the main focus of fundamental and applied luminescence

dating research was on Quaternary sediments. Around the turn of the century, luminescence dating

had gone through major technological and methodological developments, which resulte d in

significant improvements in precision and accuracy. At present, it is probably the most widely used

Quaternary radiometric method after radiocarbon (Duller, 2012; Buylaert, priv. comm. ). The

following present a brief and general introduction to the main principles underlying the use of

luminescence phenomena for dating. For more detailed and specialised accounts, reference can be

made to Aitken (1985; 1998), Bøtter-Jensen et al. (2003), Duller (2004), Duller (2008), Madsen and

Murray (2009), Murray and Olley (2002), Vandenberghe (2004) and Wintle (2008).

6.2 Principles

When sediment gets buried luminescent signal starts accumulating in quartz and feldspar minerals

under influence of omnipresent radioactivity. When exposed to heat or light the minerals get

stimulated and exhibit radiation in the form of light. When this occurs the luminescent signal gets

“zeroed”. In this way the amount of built up luminescence is a measure for the received radioactive

energy over time and thus of the time that has elapsed since the last exposure to heat or light. In this

study we focus on the methods that measure the last exposure to daylight for quartz (optical ly

stimulated luminescence: OSL) and feldspar (infa-red stimulated luminescence: IRSL). When the

zeroing agent is daylight the zeroing of the signal is called bleaching. This exposure to daylight can

happen when the sediment is eroded and transported. When the sediment gets buried the zeroing

agent isn’t operative anymore and the luminescent signal can start building up. This goes on until the

21

luminescence is measured in the laboratory (Figure 6-1).

Figure 6-1: representation of the age defined by luminescence build up. (Vandenberghe D., 2004)

The absorbed radioactive energy (α, β, γ) that builds up over time since the last exposure (in nature)

is called the burial dose. The unit of absorbed dose is Gray (Gy), it is determined as Joule/kg. The rate

of radioactive stimulation (e.g. while buried) is called the annual dose. It is a measure for annually

absorbed radiation per unit of mass and has a unit of Gy/a. The annual dose can be determined by

measuring the radioactivity of the sample area. Out of the burial dose and annual dose the time since

last exposure to the zeroing agent can be determined:

Age = burial dose/annual dose.

The burial dose can’t be determined directly. It is determined by an equivalent dose of e.g. β

radiation that produces the same luminescence signal as the burial dose. The equivalent dose has the

symbol De. The equivalent dose is determined by:

Equivalent dose = Natural Luminescence signal/Luminescence sensitivity

Luminescence sensitivity is a measure of the luminescence arising from an amount of absorbed

radiation (photons/Gy).

The luminescence build up mechanism occurs due to natural radiation from radioactive decay that is

omnipresent in nature. Dosimeter minerals such as feldspar and quartz capture that energy in so

called “electron traps” in an imperfect crystal structure. In a perfect crystal there are 2 electron

energy states (bands): the conduction and the valence band. These are respectively a mobile and an

immobile energy state. In between there is an energy gap. This is “the forbidden zone” where in a

22

perfect crystal no electrons are located. Omnipresent radiation from radioactive decay in the

subsurface can increase the energy state of electrons from the local valence band into the

conduction band, leaving an electron charge hole behind (Figure 6-2).

Figure 6-2: schematically representation of trapping and recombination of electrons. In (a) the electron and hole get

trapped. In (b) the electron is in a trapped state. Notice the depth of the trap E below the conduction band. In (c) the

electron gets evicted by stimulation (heat or light) and re-joined with the hole. The differential energy gets emitted in

the form of light. (Aitken, 1998).

Just as the electron in the conduction band the corresponding electron hole is free to move in the

crystal. Where there are defects (missing atoms, substitutions and impurities) (electron traps) in the

crystal structure, the electrons in the conduction band and the holes can get trapped into an

intermediate immobile energy state (localised energy levels). Due to ongoing natural radiation over

time more and more electrons will get excited into the conduction band and trapped in the defects.

This goes on until the traps are saturated.

The energy that this intermediate state is below the conduction band is called the depth of the trap E

(Figure 6-2, Aitken 1998). The bigger E, the more stable the trap is. The traps are emptied as the

crystal gets exposed to heat or light. With this process the trapped electrons absorb energy E from

the light or heat so they can go from the trapped energy state into the conduction band. Once in the

conduction band the electrons can be trapped again or re-joined with the electron holes in

“recombination defect centres”. These are other defect centres where recombination takes place. By

the re-joining the electrons from the conduction band go into the valence band. The differential

energy gets emitted in the form of light (radiative recombination) or heat. The wavelength (colour) of

the radiation is indicative for the type of recombination centre. The recombination defect centres

23

where radiative recombination occurs are called luminescence centres. The luminescent radiation is

the signal measured in the laboratory after heating (TL) or optically stimulating (OSL).

6.3 Stimulation and signals

For measuring the luminescence intensity the sample first has to be stimulated by light or heat. With

OSL and IRSL the rate of luminescence signal depends on the stimulating light intensity and the light

sensitivity of the traps. The light sensitivity is a measure of how easily the traps get evicted by the

stimulating light. This doesn’t seem to correlate with the trap depth but is dependent on the

wavelength, trap characteristics and temperature (Aitken, 1998). Choosing the right wavelength

allows the selection of a specific mineral. Short stimulating wavelengths (higher energies) and longer

exposure times are generally more effective for eviction in Quartz (Godfrey-Smith et al., 1988). Care

has to be taken in the laboratory that the stimulating light doesn’t dilute the luminescence signal.

Therefore the wavelength of the stimulating light and the signal should be clearly separated (e.g.

stimulating at 647nm and signal at 365nm in quartz (Huntley et al., 1996)). The wavelength of the

signal should be shorter than that of the stimulating light. This is to avoid measuring the lower

energy luminescence from the non-evicted electrons. Optical light from blue to green spectrum seem

to be very effective in stimulating traps in quartz (OSL), while the infrared spectrum is more effective

in stimulating traps in feldspar (IRSL).

Figure 6-3: the shine down curve of Quartz OSL

With stimulation (bleaching) time the luminescence intensity (brightness) decays. The decaying

luminescence intensity curve is called the shine down curve (Figure 6-3). The integral (surface below)

of the shine down curve is the total luminescence count. When measuring the luminescence signal

the first part of the shine down curve is considered the foreground and a following part is considered

as the background. Net luminescence signal is the foreground minus the background.

The luminescence signal from arising from different grains that received the same radiation dose

varies substantially. This is due to the varying luminescence sensitivities and saturation doses

24

(Murray and Roberts, 1997). The overall signal obtained from a large amount of grains (e.g. 1000)

comes primarily from a small fraction of super-bright grains (Huntley et al., 1993). When using small

aliquots (ca. 100 grains) the signal arises theoretically from only 1 grain, this is called a single grain

measurement. This results in varying luminescence intensities from different measurements. A

specific statistical approach is required to obtain an accurate dating.

6.3.1 Feldspar IRSL and Quartz OSL

The total amount of signal that can build up is limited by the amount of light sensitive traps. Quartz is

known to be saturated at much lower doses than feldspar. Therefore feldspar can provide dating’s up

to 1 Ma while Quartz luminescence has a dating limit of 100-200 ka. This of course depends on the

amount of natural radioactivity. Low radioactivity extends the time range for dating.

The luminescence arising from a certain received dose is greater for feldspar than for quartz.

Therefore for a sample of certain age the signal to noise ratio for feldspar will be bigger than for

quartz.

Despite the advantages mentioned above luminescence dating of feldspar is less widely used

because it suffers from anomalous fading (see section6.7). To account for this a fading correction can

be introduced or a p-IRIR treatment can be performed (see 6.7.1).

The different OSL and IRSL have different beaching rates under normal daylight condition ( Figure

6-4). This means that with short exposure times overestimations or partial bleaching will be more

significant with IRSL on feldspar and certainly with the p-IRIR290 method.

25

Figure 6-4: Sensitivity corrected luminescence intensity vs. stimulation time in a solar simulator for the OSL on quartz, for

the regular IR50 treated feldspar IRSL, for the IR50 treatment with a preheat of 250°C on feldspar and for the p-IRIR290

signal. (Buylaert et al., 2012)

6.4 De determination: SAR protocol

Nowadays generally a standard SAR protocol is used which was proposed by Wintle and Murray

(2000)a for quartz and feldspar Wallinga et al. (2000). In the SAR (single aliquod regenerative dose)

technique the luminescence signal is measured for subsequent regenerative cycles for a single

aliquot (sample platform). In the first measurement cycle the natural (burial) dose is measured, in

the following cycles a signal from a regenerated dose is measured.

The regenerative dose can be changed throughout the measurement cycles. In the SAR protocol of

Murray and Wintle (2000a) the regenerative dose is raised each cycle to observe the corresponding

growth curve of received radiation dose v.s. luminescence signal change. This is used to interpolate

the natural luminescence to an equivalent dose (Figure 6-5)

The sensitivity of the luminescence signal for the given dose will change with each heating and

stimulation. Therefore a test dose is used each cycle to monitor the sensitivity changes. The

luminescence from the regenerated and natural dose is usually written as Lx and the luminescence

arising from the test dose as Tx. After correcting the regenerative luminescence signal by normalising

it to the corresponding test dose signal (Lx/Tx), a corrected signal growth curve with increasing dose is

obtained (dose response curve) (Figure 6-5). By interpolating the corrected measured natural

luminescence signal to the corrected growth curve the equivalent dose is obtained ( Figure 6-5). An

26

uncorrected growth curve with regenerative OSL signals and test dose OSL signals is shown in figure

16a. A corrected grow curve is shown in Figure 6-5 B.

Figure 6-5: in A) the uncorrected growth curve (filled circles) and the growth curve of the test signal (open circles). B) The

corrected growth curve with determination of the real De.

Two corrected luminescence signals that arise from the same regenerative dose should be the same.

The ratio between two corrected signals from the same regenerative dose is called the recycling ratio

and is ideally one. When the deviation is too high the aliquot can be rejected. In Figure 6-5 the

repeated dose is given by the diamond dots.

Another test is if a regenerative dose of zero Gy indeed gives a response signal of zero. Usually there

is still a small signal. This is because of the thermal transfer effects during preheating. The remaining

signal is called the recuperation of the signal (triangles figure a). Based on the recuperation an

aliquot can also be rejected.

The SAR-protocol has proven very successful for the dating of quartz, where a stimulation heat of

160°C is common. It is also commonly used for the dating of feldspar with a stimulation heat of 50°C.

The lower part of the corrected growth curve is practically linear. With feldspar IRSL the saturation

doses are much higher and the linear part of the growth curve is more significant. By knowing this

A)

B)

27

the natural signal from young samples can be interpolated to an equivalent dose with only one

regenerative dose.

6.5 Annual dose determination

Techniques for indirectly determining the annual dose are: the neutron activation analysis, the

inductively coupled plasma mass spectrometry (ICP-MS), alpha counting, beta-counting and gamma-

spectrometry. These techniques are indirect because the annual dose is determined out of the

radionuclide concentration (NAA, ICP-MS, gamma-spectrometry). These values need to be converted

to absorption rates per unit mass over time (Gy/a). This conversion can be done by nuclear data

tables (Adamiec and Aitken, 1998). In this study we use the indirect method of gamma-spectrometry.

The radiation comes from radioactive decay of elements in the area of the sample. The radiation

consists of α, β and γ radiation. γ rays have high luminescence stimulation efficiency and high

penetrating power, a large volume contributes to the radiation of γ rays. Therefore a model should

be used to estimate the contribution of the sampled layer and adjacent layers (Aitken, 1985,

Appendix H). A much smaller volume however contributes to the β radiation because it is less

penetrating. β radiation has also a high efficiency. α rays have such a small penetration that in large

(quartz) grains (>100µm) only the outer shell is affected. Due to their ionising nature they have a low

efficiency. With coarse grain techniques the outer shell of the grain is removed by etching with HF so

the effect of α-rays is removed (Figure 6-6).

Figure 6-6: schematic representation of a grain and the influence of irradiation. The outer skin is removed by etching to

remove the effect of α-radiation

28

Most radioactivity comes from decay of U and Th. These have a very long lifetime and the radiation

will therefore be effectively constant. In radionuclides with long half -lives equilibrium is reached

after a certain time period. This means that the rate of production of a daughter isotope by decaying

mother isotope equals the rate of decay of that daughter isotope. The radioactivity then remains

constant.

A condition for obtaining the right annual dose is that system is closed. This means that there is no

escape of radioactive daughter or mother isotopes causing disequilibrium. In the decay chain of U238,

Rn222 is gaseous and prone to escape. Other isotopes that cause disequilibrium are Ra226 (due to its

solubility), U234 (weaker binding) and Pb210 that is enriched in surface layers due to the decay of

constant inflowing Rn222 from deeper layers. The half-lives of mobile radionuclides in the Th232 chain

are short and therefore unimportant for possible disequilibria. The disequilibria of the U235 decay

chain are unimportant because of the low abundance.

When the mother isotope concentrations are being determined to calculate the annual dose, the

assumption is made that the decay chain has always been in equilibrium. Another assumption is that

the dose rate measured at present has remained constant throughout the dated period. This

assumption is made with radioactivity measurements.

There can also be accounted for cosmic radiation. This depends on the latitude, altitude and the

depth of the sample. Expressions to calculate cosmic radiation can be found in (Prescott and Hutton,

1994; Prescott and Hutton, 1988). Determining the received cosmic radiation becomes complex

because it changes over time with burial depth. Fortunately the contribution of cosmic radiation is

little when the total dose rate is not too small. In this study the sediment is deposited on the bottom

of a lake, therefore the depth of the lake contributes to the attenuation of cosmic radiation. It should

therefore be added in the calculations.

Another correction to the measurements is the effect of water in the pore space. This attenuates the

radioactivity. Compared to silicates the attenuation efficiency of water is 50% higher for α -radiation,

25% higher for β radiation and 14% higher for γ-radiation (Zimmerman, 1971). The dose rate in wet

sediment is consequently lower than in dry sediment. If this effect isn’t taken into account there will

be an age underestimation. It is the average water content during burial that is important and not

just the measured water content during sampling. The water content changes over time due to

different processes such as varying water saturation and porosity decrease due to compaction and

cementation. A good knowledge of the sample site is required in order to make accurate estimations.

Knowing the water content is a fundamental limitation on accuracy and precision of the dating. The

wet dose can be determined out of the dry dose by knowing W (average porosity during burial time)

29

and F (average fraction of water saturation during burial time). The dose rate can then be adjusted

by:

(6)

(7)

(8)

Quartz grains are considered free of radioactive elements. All the radioactive stimulation therefore

comes from outside of the grains. The radioactive β and α rays however get partially attenuated by

the grain while passing through. This results in less received radiation for the overall grain than is

derived from the annual dose measurements. This effect will be more important if the grains are

larger. The effects of the fast attenuating α radiation are removed by etching. Because of the

attenuation of β-rays a part of the total received β dose will be removed by etching too. This will give

rise to a difference of ca. 2% (Bell, 1979). Therefore the age must be calculated with the properly

attenuated dose.

It is generally assumed that the internal radioactivity of quartz grains is negligible. This is because

there are a small proportion of radioactive elements present in quartz. In K-feldspar however the K is

12.5+-0.5% (Huntley and Baril, 1997) and the Rb content is 400+-100 µg/g (Huntley and Hancock,

2001). Both have a radioactive fraction which contributes to the internal α and β radiation dose. The

internal β radiation increases with increasing grain size of K-feldspar.

6.6 errors in young samples

When dating young sediments as in this study a number of problems can arise. In the next sections

an overview is given of likely problems that can occur when dating the samples of this study.

6.6.1 Partial bleaching

Errors might occur by the effect of partial bleaching. This is the incomplete resetting of the

luminescence signal during erosion and transport before deposition. This is due to insufficient light

exposure and must be considered in non-aeolian deposits. In this study the sand was probably not

completely bleached during the erosion and transport of the tsunami but on the beach itself. The

sand was likely to be shifted enough by wind driven saltation so that it was completely bleached over

a relative short time scale. Earlier studies of e.g. Banerjee et al. (2001), Ballarini et al. (2003), Murari

et al. (2007) and Brill et al. (2012) confirmed a good bleaching of beach sands prior to deposition by a

tsunami. However when dealing with IRSL on feldspar this might not be the case. In Figure 6-4 it is

30

clear that the bleaching sensitivity to daylight is far less with feldspar IRSL than with quartz OSL.

Therefore will the IRSL signal be more prone to partial bleaching than the OSL signal. Ollerhead et al.

(1994) and Wolfe et al. (2002) found an IRSL age of dune sands of over a decade. This can give rise to

a systematic error when dating young sediments.

Partial bleaching can be recognised by heterogeneous distribution of residual doses (Murray and

Olley, 1999). The resulting burial doses will then be heterogeneous and there will be a scatter in

measured De’s. This heterogeneity is better visible with small aliquot sizes (single grain). However

one must know that the luminescence signal intensity varies from grain to grain. It is also worth

mentioning that different minerals can have different bleaching behaviour. It is necessary to have

single mineral subsamples. Out of the standard deviation possible assumptions can be mad e about

partial bleaching. The scatter of De can be visualised with a histogram (Figure 6-7). If there is an

extension of the histogram to higher De values partial bleaching can be assumed. This is because

with incomplete resetting older signals with higher De will still be present. The lower part of such a

histogram is probably the true De of the dated event. The sharpness of the rise of the lower part of

the histogram (leading edge) represents the likelihood that this lower part is indeed the true De

(Lepper et al., 2000). It can however be still an overestimate.

Figure 6-7: The histograms of De’s. Note the scatter due to partial bleaching in the fluvial sand (disturbed light spectrum

in water) and the sharp peak with aeolian sand (no partial bleaching)

31

Figure 6-8: : Radial plot. If the measurements remain in the marked zone it remains reliable.

In a histogram the variation of the precision of each measurement is not visualised. For this a radial

plot can be used (Figure 6-8). With a radial plot the precision is shown on the x-axis. In this way it is

easy to determine if a variation is real or is caused by a lack in intrinsic precision of the measurement.

Statistical approaches can be used to obtain a correct age out of scattered De values of small aliquot

(single grain) measurements. The minimum age model and the central age model of Galbraith et al.

(1999) are commonly used in luminescence dating. The MAM (minimum age model) can be used to

calculate the age of a sample that shows partial bleaching. The CAM (central age model) can be used

for equally bleached samples.

6.6.2 Thermal transfer

In the standard SAR protocols (see section 6.4) a preheat is used. This preheat can cause unwanted

thermal transfer. This is the transfer of charge from shallow light insensitive traps to deeper light

sensitive traps. This will lead to equivalent dose (De) overestimations and consequently age

overestimations. When the sample ages are young the relative effect caused by this will be important

(Madsen and Murray, 2009). The occurrence of thermal transfer can often be observed by the

presence of a preheat plateau in a preheat versus De measurement. When preheats exceed the

plateau thermal transfer will start to affect the datings (Madsen and Murray, 2009). The refore a

preheat must be chosen that is within this plateau. On younger samples the effect of thermal

transfer will have a relatively larger effect than on older samples. Therefore preheat versus De

measurements must be done on the youngest samples in order to choose the right preheat.

32

6.6.3 Alteration of sedimentary enviroment

The dose rate (annuals dose, Da) is determined by measuring the dose rate today. In the simplest

assumption is that this dose rate remained the same over the dated timespan. However since the

dose rate is dependent on water content, burial depth and radionuclide concentrations this can vary

over time. Obviously the burial depth did not remain the same over the dated time span. This will

affect the cosmic radiation dose. Madsen et al. (2005) estimated, with assumption of linear

sedimentation rate, that the error induced by this is ca. 3%. The water content is also prone to

change over time since it is linked to porosity and therefore burial depth. Chemical reaction might

also cause cementation and change the porosity. However when dating young sediments it is more

safe to assume that the present conditions are applicable over the hole dated timespan. This is not

the case for radionuclide concentrations. Post bomb concentrations of 137Cs/210Pb have a relatively

larger effect on young water saturated samples (Madsen and Murray, 2009). Since the sediments

that are less deeply buried will be more enriched by nuclear fallout a gradient will occur. Despite this

larger effect it is still safe to neglect this (Madsen and Murray, 2009).

6.6.4 Other errors

Variations might also occur due to microdosimetry. This is the small scale variations in annual dose.

This will result in a De variation. The presence of small radioactive minerals might cause this (e.g.

zircon). The radiation that causes biases is the β radiation. The γ ray attenuation is too low to cause

microdosimetric variations and the effects of α radiation are removed by etching. In the study of

Murray and Roberts (1997) some aeolian quartz grains were surrounded by attenuating carbonate.

The radiation received by these grains was much lower.

Another error that might occur on the De is the post depositional mixing. This is the mixing of

sediments of different ages after deposition. It gives rise to a De variability. Erosion of overlying rock

or bioturbation can cause the mixing. Other variations in De might be from heterogen eity in

dosimetry or just from analytical scatter.

A common error with luminescence dating of tsunami deposits is the mixing with older sediments. In

the studies of Ollerhead et al. (2001), Bishop et al. (2005) a long run-up distance trough a channel

and old dunes (as is the case in this study) resulted in a mixing of sand from different ages. The

scattered De distribution could be wrongly interpreted as partial bleaching.

6.7 Thermal and a-thermal stability

33

The luminescence that can be accumulated is limited by the amount of traps and another process

called thermal fading. With thermal fading electrons are spontaneously evicted from their traps. The

rate of this depends on the (burial) temperature. The thermal fading is an important factor for

defining the mean lifetime of the electrons in the traps (3). It is important only to measure the

luminescence of the very stable (deep) traps with a high E and a mean lifetime over a few million

years. In this way there is a negligible loss of trapped electrons during the timespan that the sample

is buried. Protocols for OSL account for this by preheating the sample so the shallow traps are

emptied. However even in deep traps there is still a chance of eviction of the electrons. It can be said

that the amount of trapped electrons at a specific time n(t) with a constant certain temperature

decays exponentially over time:

( ) ( ) (1)

With = the mean lifetime of an electron in a trap with a certain temperature and t2-t1 = the time

interval (age). The study of Aitken, (1985) concludes that in order to avoid an age underest imation of

5 % the lifetime of an electron in a trap ( ) must be at least 10 times higher than the dated age of the

sample. Therefore there is still a limited timespan over which a sample can be dated. is the

temperature dependent lifetime. It can be defined as:

(2)

With s = the frequency factor, this can be interpreted as the frequency that an electron is in the

possibility to escape. E = the depth of the trap. T is the temperature (K). k is the Boltzmann constant

(8,6173*10-5 eV/K).

With TL measurements the luminescence signal can be obtained as a function of the temperature

(glow curve). This gives an estimate of the depth (E) and stability of the traps that are emptied.

The mean lifetime is given by:

(3)

With = a decay constant taking into account the limited amount of traps (saturation

characteristic), = the mean lifetime of electrons in a certain trap with a certain temperature (long

term stability).

Taking both thermal fading and the amount traps into account the luminescence intensity at a

certain (burial) time is I(t):

34

( ) ̇ (

) (4)

With S = the sensitivity; the amount of luminescence build up per received dose unit, ̇ = the dose

rate; the radiation dose received per unit of time (first derivate of burial dose), = the apparent

mean lifetime of an electron in a trap taking into account the thermal fading and amount of traps (3),

t = the time span of the signal accumulation (Vandenberghe, D. 2004). In this formula ̇ refers to

the rate of increase in luminescence intensity over time due to the filling of the traps. (

)

is the term that accounts for the saturation of the limited amount of traps and the thermal fading.

Knowing this the maximum intensity (saturation intensity) can be determined as ̇ .

Equation (4) can then be simplified to

( ) (

) (5)

When determining the burial age of feldspar with IRSL (infra-red stimulated luminescence)

anomalous fading is a major problem. Anomalous fading is a process where electrons re -join from in

a trapped position without stimulation. This leads to an age underestimation. Anomalous fading can

be explained by a process called quantum-mechanical tunnelling (Visocekas, 1985). With quantum

mechanical tunnelling electron pairs re-join without excitation in the conduction band. In this way an

energy barrier is bypassed. With higher received doses (longer burial) and more trapped electrons

the anomalous fading becomes more abundant.

After a certain time period (e.g. 1 Ma) the amount of newly trapped electrons equals the amount of

anomalous recombined electrons and the luminescence build-up ceases. This is called “field

saturation” (Huntley and Lian, 2006).

On short timescales the anomalous fading can be described as a logarithmic decay expressed as a

signal loss per decade (Aitken, 1985 Appendix F). Aitken (1985) based the descriptions of anomalous

fading on the assumption the tunnelling is a random decaying process with a mean lifetime ( ) of an

electron in a trap. This gives the standard formula:

(9)

With s = the frequency factor (see (2)), = a constant determined by Thomas et al. (1965) and Riehl

(1970) (also expressed as 1/R0). r = the distance between trap and recombination centre.

35

After a certain time all the trapped electrons with a recombination centre within a certain distance

(rc) will be tunnelled out. This distance is defined as the critical distance (rc). Out of equation 9 rc can

be defined as:

( ) (10)

With t = the (burial) time. An assumption for this formula is that the lifetimes don’t deviate much

from the mean lifetime ( ).

Assuming that the traps and recombination centres are randomly distributed with a density N, that

N*rc3<<1 and (L2 - L1) << L1 with L1=number of detrapped electrons at t1 (time 1), L2=number of

detrapped electrons at t2 (time 2). Aitken (1985) defined the anomalous fading as:

( ) (

) (11)

The correction can be based on the extrapolation of this logarithmic decay (Aitken, 1985). The faded

luminescence at time t is:

[ (

)] (12)

I is the luminescence intensity at a time t (t2) after irradiation. Ic is the luminescence intensity at an

arbitrary time tc (t1) (e.g. prompt measurement after irradiadiation). K is the fractional decrease in

luminescence intensity during a time interval of tc to 2.30 tc. It is a constant that is dependent on the

sample.

Because the decay is logarithmic the signal loss between 1h and 10h after irradiation is the same as

between 10h and 100h and between 100h and 1000h. This leads to an expression of fading that is

the signal loss per factor 10 time increase. It is expressed as g:

( ) (13)

This gives a new expression for signal loss:

[

(

)] (14)

From this expression the g value can be obtained from the luminescence intensity at certain delay

times. In the laboratory the g value is obtained from the slope of a linear regression fit through the

delayed luminescence signals versus a logarithmic timescale. The g value is slightly dependent on the

time delay between irradiation and the first IRSL measurement (e.g. t c: prompt measurement).

Therefore the g value should be normalised to a specified time delay in order to compare. Generally

36

the g-values are normalised to a delay of 2 days in order to compare with Huntley and Lamothe

(2001).

By differentiating and integrating equation (12) over a time interval, the luminescence signal of a

sample that is irradiated and faded over a time T (e.g. during burial time) is obtained:

{ [ (

) ]} (15)

With If the final intensity after burial and I0 the intensity if there would be no fading. Knowing that

the luminescence intensity is proportional to equivalent dose and therefore also with burial time

equation (15) can be written as:

{ [ (

) ]} (16)

Here the Def is the equivalent dose calculated out of the measured I f. Tf is the burial time calculated

out of Def. T is the real burial time. The g value can be obtained by linear regression of the faded

doses on a logarithmic time scale (Figure 6-9). With equation (13) and (16) the real burial time T can

be obtained.

Figure 6-9: Equivalent dose v.s. delay time.

This gives age estimations that agree with independent age information of relatively young samples

(younger than 20-50ka) (Huntley and Lamothe, 2001) and for the linear part of the dose-response

curve (SAR protocol). This technique is however not valid for very young an d very old samples

(Huntley and Lamothe, 2001);(Kars et al., 2008). In this work ages are starting from 50 years so the

dating should be practical for short time ranges.

37

6.7.1 pIRIR dating method

An ideal method to date feldspar is to find a

signal which is not affected by anomalous fading

over the dated time range. An overview of

methods and a physical explanation prior to

appliance is given by Buylaert et al. (2012).

Tomsen et al. (2008) concluded that the most

promising feldspar signal with the lowest fading

rates arises from elevated temperature IRSL

stimulation. This signal is in the blue wavelength

spectrum and is called the post-IR IRSL (pIRIR) signal. An adapted SAR protocol is developed for

measuring the p-IRIR signal (Table 6-1). With this method first the sample is stimulated with IR at

50°C, and then the sample is stimulated again with IR at a higher temperature. The resulting post-IR

IRSL signal has been shown to yield lower anomalous fading rates than the conventional IRSL signal

(Buylaert et al., 2009). The temperature used by Buylaert et al. (2009) for the second stimulation was

225°C. This reduced the anomalous fading correction by 61%. They used a preheat of 250°C for 60 s.

Because the temperature on which the IRSL traps empty is above 400°C (Murray et al., 2009) the

preheating can be done up till temperatures of 320°C (Thiel et al., 2011). Therefore the temperature

of the second IR stimulation can go up to 290°C (pIRIR290). The dose response curves of an “infinitely

old” sample of Buylaert et al. 2011a, Thiel et al. 2011b and Thomsen et al. 2011 of the p -IRIR signal

are very similar in shape and the obtained natural signal is 99% of the saturation level. This suggests

signal stability over geological time scales.

A physical model for the increased stability of the pIRIR290 signal is given by Buylaert et al. (2012). It is

based on the probability of tunnelling of electrons in the ground state (anomalous fading). This

decreases exponentially with distance between trap and recombination centre (Aitken, 1985;

equation 9). When stimulating the sample with IR50 the trapped electrons go in to an excited state in

the electron trap. The probability of tunnelling thus the rate of recombination increases in the

excited state. This can be explained by the extended electron wave function (Poolton et al., 2002; Li

and Li, 2011). In the excited state recombination over close distances happens on laboratory time

scales (laboratory tunnelling). The result is that with the IR50 stimulation trapped electrons with a

high probability of recombination during burial get recombined in the laboratory. In the next step the

sample is stimulated by IR290. The higher energy of this stimulation enables the electrons to go into

the conduction band. Once in the conduction band the electrons are free to move over large

Table 6-1 SAR protocol for p-IRIR measurements

38

distances thus can recombine with recombination centres far away. In this way the signal of the IR290

stimulation arises from electrons that had a low chance of recombination during burial.

The pIRIR290 signal can also be explained by the existence of different trap depths. Where shallower

traps get evicted by the IR50 stimulation and deeper traps by the IR290 signal (Li and Li, 2011). Buylaert

et al. (2012) used the SAR protocol with preheat of 320°C and an additional IR stimulation step on

290°C (200 s) after the IR stimulation of 50°C (200 s). They found a more stable signal with the

pIRIR290 method than with the conventional IRSL method. They compared the results with

independent age control (radiocarbon dating, stratigraphic correlation and OSL on quartz). Although

there was a small age overestimation the dating with the p-IRIR technique was more accurate than

the dating with the conventional 50°C IRSL method.

It is known that bleaching of feldspar is slower than bleaching of quartz (Godfrey-Smith et al. 1988;

Thomsen et al. 2008). Elevated temperature IRSL signal bleaches also more slowly than low

temperature IRSL (Poolton et al. 2002b). Buylaert et al. (2012) concluded that both signals from the

pIRIR290 method (IR50 and IR290) bleached an order of magnitude slower than the quartz OSL signal

and slower than the signal of a conventional IR50 signal. Although the IR290 signal bleaches slowly it

still probable to happen in nature (Buyleart et al., 2012).

39

7. Luminescence dating of tsunami deposits

The following presents a chronological overview of luminescence dating studies of tsunami deposits.

Huntley and Clague (1996) reported on luminescence dating of tsunami-laid sands at four sites in

Washington State (USA) and British Columbia (Canada). They used infrared stimulated luminescence

signals from K-feldspar. For the sediments in Washington state, they obtained an age of 1285 ± 95

years. Within 2σ, this age was consistent with the range obtained through a combination of high-

precision radiocarbon dating of imbedded detrital and living-positioned plant fragments, and

stratigraphic correlation. Tsunami-laid sands at three sites in British Columbia were dated at 260 ±

20, 325 ± 25 and 335 ± 45 years, consistent with a time range between 150 and 400 years as derived

from historical records and radiocarbon dating. Huntley and Clague (1996) point out that their study

did not fully deal with two potentially serious sources of error, namely partial bleaching (leading to

age overestimation) and anomalous fading (leading to age underestimation), and that there might be

some degree of compensation of these two effects in their work. From the good agreement with

independent age information, however, they concluded that the method is applicable to sandy

tsunami deposits, provided that these were well -exposed to daylight before the tsunami (such as

tidal-flat and tidal-channel sands, beach and aeolian sands, and shallow subtidal sediments), and

remained undisturbed and shielded from light following deposition.

Price et al. (1999) explored the use of the thermoluminescence (TL) signature of sand-sized quartz

and polymineral fine grains to identify tsunami-laid sediments, as an additional tool to conventional

sedimentological techniques. They also point out that, in some cases, TL age reversals may provide

additional supporting evidence for tsunami activity. This approach relies on the fact that the TL signal

is less rapidly and completely reset by sunlight than OSL signals. They conclude that the latter may

therefore provide more reliable depositional ages (as demonstrated by Huntley and Clague, 1996).

IRSL-signals from K-feldspar were also used by Ollerhead et al. (2001) to establish a chronology for

tsunami-laid sands in a coastal lake in Oregon (USA). As a test of accuracy, the IRSL-ages were

compared with radiocarbon dates of imbedded detrital plant fragments. Two samples yielded ages in

agreement with the 14C ages (~ 3.1 ka and ~ 4.3 ka), provided that a correction was made for

anomalous fading. They interpreted this agreement as indicative of the accuracy of the correction

procedure. Three other samples yielded ages that were significantly older than the 14C ages.

Ollerhead et al. (2001) deduced that these samples consist of a mixture of sand grains of at least two

well-defined ages, rather than consisting of incompletely reset grains. This was based on the

40

relatively flat plots of equivalent dose versus stimulation time, which was suggested by Huntley et al.

(1985) as a means to detect partial bleaching. They concluded that the tsunami eroded both young

and old sand deposits before dropping them in the lake, e.g. owing to its passage through a narrow

inlet channel through older dunes.

Banerjee et al. (2001) used OSL signals from quartz in combination with the SAR protocol to date

deposits in coastal lagoons on Scilly Island (UK) that were thought to result from a tsunami created

by the Lisbon earthquake of 1755 AD. Ages of 230 ± 40 and 380 ± 60 years were obtained, consistent

with an expected age of 244 years. They also obtained an OSL age of 6 ± 3 years for a sub-aqueous

beach deposit, which suggests complete resetting of the likely sand source for the tsunami deposit

and that optical dating is thus applicable to these sediments. Additional evidence for the reliability of

the age results was provided by their internal stratigraphic consistency and their consistency with a

14C date for an underlying peat horizon at a similar site less than 100 m from their study site.

Nichol et al. (2003) used IRSL signals from polymineral fine grains to date a tsunami laid gravel in a

dune on a coastal barrier in Whangapoua Bay, Great Barrier Island, New Zealand. Sands below and

above the gravel were dated, providing a an age constraint for the tsunami in between 4.7 ka and the

present.

Eipert (2004) performed a dating study of the 1960 tsunami deposit in south central Chile (Maullin)

using OSL signals from sand-sized quartz. The tsunami-laid sand was dated at 40 ± 15 years,

consistent with the expected age. This was taken as evidence for complete resetting, rapid burial and

undisturbed preservation of the sand sheet.

Bishop et al. (2005) examined the problems of partial bleaching and mixing of sediment during

tsunami-erosion and transport using the deposits from the 26 December 2004 Indian Ocean

Tsunami. Eye witnesses and photographs demonstrate that the tsunami had a high turbidity, and is

thus unlikely to provide an environment in which transported sediment grains receive sufficient

sunlight for their luminescence clock to be completely reset. Bishop et al. (2005) examined the

luminescence of about 200 tsunami sediment samples using a portable OSL measuring instrument.

Their qualitative analyses showed that all investigated sediments have a residual age, often of only

about ten years, but sometimes also up to hundreds and even thousands of years. They also

observed that the residual ages (or the age overestimation) increased the further inland the

sediments were deposited. While several interpretations of these data are possible, the main

conclusion by Bishop et al. (2005) is that future use of luminescence dating of ancient tsunami

deposits must take careful account of both the source and the depositional setting of the sediment

that is to be dated.

41

Switzer et al. (2005) used both conventional and AMS 14C and TL and OSL dating methods to

constrain the age of two possible tsunami deposits. While their dataset did not allow drawing firm

chronological conclusions with respect to tsunami activity, the observed inversion in TL-ages is taken

as evidence for incomplete resetting of this signal. The single OSL date was stratigraphically

consistent with an underlying 14C age, although it could not be excluded that it is also affected by

incomplete resetting.

Murari et al. (2007) present another study into the main assumptions underlying the application of

luminescence dating techniques to tsunami-laid sands. Similar to Bishop et al. (2005), they

investigated the residual equivalent doses in sediments transported by the 2004 Indian Ocean

Tsunami. Murari et al. (2007) used the SAR protocol and quartz OSL signals; equivalent doses were

calculated either using the integration limits of the OSL decay curves as proposed by Murray and

Wintle (2000), or using the amplitude of the fast component as obtained through deconvolution of

the OSL decay curves. On average, both methods yielded consistent results, with equivalent doses in

the range of 0.5 ± 0.2 to 0.7 ± 0.1 Gy; this was interpreted as suggesting that the samples were well -

bleached before deposition by the tsunami. Given that tsunamis represent short-lived high-energy

sediment-transport events, Murrari et al. (2007) suggest that the tsunami only picked up the near-

surface intertidal sediments which are well-bleached. Finally, the authors conclude that component-

specific analysis may allow dating tsunami events with an error (i.e. age-overestimation) of less than

50 years.

Kennedy et al. (2007) performed an OSL study of sand and silt surrounding boulders deposited by a

tsunami. They used IRSL signals of polymineral fine grains in combination with a multiple -aliquot

additive-dose method to date the overlying loess deposits; the underlying sand was dated using the

SAR protocol and IRSL signals from Na-feldspar. A stratigraphically consistent set of ages was

obtained, indicating two phases of loess deposition at 28.9 ± 4.4 ka and 78.6 ± 4.2 ka; the sand was

dated at 81.9 ± 11.7 ka. From this, the authors conclude that the boulders were the result of tsunami

deposition during MIS5a and represent the oldest such deposits described within New Zealand.

Erginal et al. (2009) applied SAR-OSL dating of quartz to coastal dunes in the Kavak Delta (Saros Gulf,

NW Turkey) as well as to a possible tsunamigenic pumice layer intercalated in the sands. An age of

0.34 ± 0.04 ka was obtained for the pumice layer, consistent with the age obtained for overlying

(0.22 ± 0.03 ka) and underlying sands (0.34 ± 0.03 ka). Based on its unusual occurrence and its OSL

age, the authors suggest that the pumice was presumably transported landward along tide channels

on the delta during a tsunami event that occurred in 1672 near Bozcaada and Kos islands according

to tsunami history of the Aegean Sea.

42

Another quartz-based SAR-OSL dating study of tsunami-laid sands generated by the 1755 Lisbon

earthquake was performed by Cunha et al. (2010). For two sites on the Algarve coast in Portugal,

they tested the applicability of standard (large-aliquot) methods for dating the sediments. They

obtained a remarkably reproducible set of OSL ages, but overestimate the event by several tens to a

few hundreds of years. The overestimation is attributed to the incorporation of older material that

was not reset during transport by the tsunami. Cunha et al. (2010) also applied the 4 parameter

minimum age model of Galbraith et al. (1999) to small-aliquot dose distributions. They obtained

apparently correct ages for 2 out of 3 samples, suggesting that the tsunami also picked up modern

sediments. It is worth noting that the study by Cunha et al. (2010) also illustrates the problems and

errors with 14C chronologies for this type of sedimentary sequences.

Kunz et al. (2010) used luminescence methods to establish a chronology for young coastal events on

the Andaman Islands (Bay of Bengal). As quartz did not exhibit suitable luminescence characteristics

(e.g. low single to noise ratio), they used IRSL signals from potassium-rich feldspar in combination

with the SAR protocol. Luminescence ages of 10 ± 2 years and 63 ± 8 years were obtained, which

were interpreted as evidencing a deposits generated by the 2004 Indian Ocean tsunami and a recent

storm event, respectively.

Prendergast et al. (2012) dated a number of tsunami-laid sands sheets in swales and beach ridges of

Phra Thong Island (Andaman Islands, Thailand) using quartz-based SAR OSL dating. They first

examined resetting in sands deposited by the 2004 Indian Ocean tsunami using both single and

multiple-grain methods. They observed that multiple-grain single-aliquot analyses overestimated the

age of the sand-sheet by about 100 years. Analyses of single-grains showed that 70 – 76 % of the

grains has a near-zero age. Therefore, Prendergast et al. (2012) used the minimum age model

(Galbraith et al., 1999) to estimate the burial dose of the tsunami-laid sand layers in the swales. The

central age model (Galbraith et al., 1999) was used for dating well -bleached samples from beach

ridges. The approach was then applied to three comparable sand sheets underlying the 2004 deposit

and yielded ages of 380 ± 50, 990 ± 130, 1410 ± 190 and 2100 ± 260 years. This implies an average

tsunami recurrence interval in this region of around 550 years.

A luminescence-based tsunami chronology for Phra Thong Island was also reported by Brill et al.

(2012a,b). Their study used quartz-OSL signals from small (1 mm diameter) aliquots and the SAR

protocol. Equivalent doses were calculated using the central age model (CAM) for well -bleached

deposits and the minimum age model (MAM) in case of incomplete resetting (i.e. the tsunamigenic

deposits). The reliability of the approach was verified by comparison with independent age control,

consisting of the historically recorded 2004 event and radiocarbon data for the tsunamigenic and

43

well-bleached deposits, respectively. While a good agreement was found for the well -bleached

deposits, the age of the sediments deposited by the 2004 event was overestimated by about 40

years when analysed with MAM; based on CAM, maximum age offsets were obtained in the range of

53 to 83 years. Such residual ages are comparable to earlier finds (see higher) and quickly become

unimportant when dating samples of more than a several hundreds of years old. Brill et al. (2012a,b)

then established a consistent luminescence-based chronology for several tsunami-events that

occurred over the past 3000 years.

Spiske et al. (2013) report on luminescence dating of deposits by Late-Holocene tsunamis along the

coast of Peru. The quartz-OSL signal showed unsatisfactory luminescence characteristics in terms of

brightness, signal composition and behaviour in the SAR protocol. These observations are in line with

earlier finds for Andean quartz (Steffen et al., 2009; Robinson et al., 2005; Spencer and Robinson,

2008). The main cause seems to be the formation age of the quartz and its provenance. CL analysis

revealed that the quartz investigated by Spiske et al. (2013) resembles the regional geology and

mainly has a metamorphic origin, with a minor content of volcanic quartz. They concluded that the

poor OSL properties can be explained by the relatively short transport paths (100 - 150 km) and a

lack of multiple sedimentary cycles that are thought to sensitise the quartz OSL fast component.

Spiske et al. (2013) therefore used IR50 signals from either K-feldspar or polymineral fine grains to

date the event sediments. A SAR protocol was used for measuring the equivalent dose and the fading

rate, and the ages were corrected for anomalous fading following the method proposed by Huntley

and Lamothe (2001). Ages were obtained of 0.17 ± 0.04 ka, 0.37 ± 0.03 ka, 1.98 ± 0.23 ka and 2.26 ±

0.37 ka. Assuming that the sediments were accurately interpreted and dated, the three oldest layers

would evidence events that, so far, were not listed in tsunami catalogues.

44

8. Thin sections

Part of the sand collected for bulk annual dose measurement was used for optical microscopy using

thin sections. The sand was imbedded in glass and cut into thin sections.. An overview of the

assemblages in the thin sections of the dated layers is given under plane polarised light and crossed

polars (resp. PPL and XPL) in Figure 8-1.

8.1 observations

45

Figure 8-1: Overview of the assemblages in PPL and XPL of dated layers 12B, 12C, 12E, 12F with resp. code GLL-133403,

GLL-133407, GLL133414, GLL-133418 (resp. luminescence samples GLL-133402, GLL-133413, GLL-133413, GLL-133417).

Overall the assemblages are very comparable. There is an abundance of opaque minerals which are

possibly oxides. Other abundant minerals are orthoclase, plagioclase, quartz and hornblende. There

is a large fraction of volcanic and quartzite lithic fragments present.

Plagioclase is easily recognised by twinning (XPL) (fig 2). It is abundant in all the samples.

Figure 8-2: A plagioclase grain under PPL (a) and XPL (b). (X200, GLL-133407, 12C)

Orthoclase is very abundant. It can be distinguished by low relief, sub-to euhedral elongated crystals,

low interference colours, slightly visible cleavage and sporadically by twinning. It has often a more

weathered appearance (fig 3).

46

Figure 8-3: Thin section with PPL (a) and XPL (b, c, d). Orthoclase in the middle. (GLL-133407, 12C)

Hornblende is very common in all the thin sections. It is recognised by its brown colour, high

interference colours, cleavage and pleochroism (fig 4).

Figure 8-4: Thin section GLL-133403, 12B. The pictures in (a) and (b) are taken under PPL. Note the difference in colour due to pleochroism. In (c) the high interference colours are visible under XPL. Just next to the hornblende crystal another mineral is present. This is possibly epidote.

Quartz is present in all the samples but less abundant than the feldspars. It is recognised by its low

relief (PPL) and first order white-grey to slightly yellow interference colours (XPL). It also lacks

47

cleavage, twinning and alteration. It is distinguished from orthoclase by its anhedral form. Undulose

extinction is recognised under XPL (fig 5c). It is present as single grains but more often as an

aggregate in a quartzite lithic fragment (fig 5d)

Figure 8-5 In (a) the quartz (Q) is shown with PPL. In (b) the quartz (Q) is shown with XPL. In (c) the quartz is shown with

XPL and undulose extinction is visible. In (d) an lithic fragment with quartz is visible. The pictures are taken from GLL-

133407 (12C).

A lot of polymineral lithic fragments are present in all the thin sections. A lot of fragments contain

elongated feldspar (plagioclase) (fig 6, 7). Others show a variety of minerals (fig 8).

48

Figure 8-6: Common lithic fragment with elongated micro-crystalline plagioclase. Note the swallow tale end of the

plagioclase. This is typical for fast cooled volcanic rocks (Vernon, 2004). (PPL, GLL-133403, 12B)

Figure 8-7: Common lithic fragment. Lithic fragment with elongated and orientated plagioclase minerals. (a:PPL, b: XPL, ,

GLL-133403, 12B).

49

Figure 8-8: Common polymineral lithic fragment with quartz. (a:PPL, b: XPL, GLL-133414, 12E)

Other accessory minerals are epidote, garnet and zircon.

The grain sizes vary from 100 to 400 µm and the grains are sub angular with a low sphericity

8.2 interpretations Overall there is a high content of feldspars and lithic fragments with the absence of a matrix.

According to the classification of Pettijohn et al. (1987) this sand is considered an arkosic arenite

Figure 8-9.

Figure 8-9: Classification of Pettijohn

Plagioclase and orthoclase are abundant throughout all sections. Feldspars are also abundant in lithic

fragments, where they are elongated and imbedded in a very fine grained matrix. There is also a high

abundance of oxides. This indicates a dominant volcanic provenance of the sands, which is quite

plausible given the active vulcanism in the region. The presence of hornblende (possibly partly

altered to epidote) argues for a metamorphic or igneous provenance. The quartzite lithic fragments

50

suggest a deformed and recrystallized origin. This is very plausible since paleo-accretionary

metamorphic bedrock is present in the area. On Chiloé Island quartzites are formed out of

interbedded quartsitic sandstones recrystallized in a paleoaccretionary wedge (Watters and Fleming,

1972). Out of the presence of sharp edged grains, lithic fragments and plagioclase, low mechanical

and chemical weathering can be assumed. This could suggest a nearby provenance.

The oxides are possibly hematite and magnetite. The extreme high magnetic susceptibility of the

sand observed in the core logs (see Chapter 5) argues for a large proportion of ferrimagnetic minerals

such as magnetite.

In theory the provenance of the sand can be very diverse and can come from a large inland region.

This is because during the LGM a large amount of glacifluvial sediments are deposited in the region

(Glasser et al., 2008). It is very likely that these form an important provenance for the sand.

51

9. Luminescence investigations

9.1 Sampling The composite cores were drilled using transparent PVC tubes of 60 cm inner diameter and 3m long,

which were subsequently cut in sections of 1 m (for ease of handling). In the laboratory, the co res

were split on two thirds of the core thickness under subdued light conditions . Samples for

luminescence analyses were collected from the sandy layers interpreted as tsunami deposits. The

outer 1 cm of the cores was not sampled, as this material may be disturbed and/or was exposed to

some light. Samples for dose rate determination were collected from the sandy tsunamite deposits,

as well as from the finer-grained deposits above, below, and intercalated in the sand layers. The

location of the samples is indicated in Figure 9-1 (see alsoTable 9-1).

Figure 9-1: Sample areas within lithology for luminescence analyses and dose rate determination (see Table 9-1 for details)

52

Table 9-1: Sample identifications and depth within the sampled cores. BULK samples are the samples used for dose rate determination, the luminescence samples for luminescence analysis.

layer sample core and depth within core

12B GLL-133401 HUEL 01A 42-54cm; BULK: mud above

GLL-133402 HUEL 01A 55-69; luminescence: sand

GLL-133403 HUEL 01A 55-69; BULK: sand

GLL-133404 HUEL 01A 70-80cm; BULK: mud under

12C GLL-133405 HUEL 02A 0-32cm (10-22cm); BULK: mud intercalated

GLL-133406 HUEL 02A 0-32cm; luminescence: sand

GLL-133407 HUEL 02A 0-32cm; BULK: sand

GLL-133408 HUEL 02A 33-43cm; BULK: mud under

12E GLL-133412 HUEL 02B 16-27cm; BULK: mud above

GLL-133413 HUEL 02B 27-34cm; luminescence: sand

GLL-133414 HUEL 02B 27-34cm; BULK: sand

GLL-133415 HUEL 02B 35-45cm; BULK: mud intercalated + sand under

12F GLL-133416 HUEL 02B 61-71cm; BULK: mud above

GLL-133417 HUEL 02B 72-78cm; luminescence: sand

GLL-133418 HUEL 02B 72-78cm; BULK: sand

GLL-133419 HUEL02B 79-82cm; BULK: mud under

9.2 Sample preparation and analytical facilities The samples for luminescence analyses were prepared in the conventional manner. The samples

were first treated with 10% HCl to remove carbonates, and subsequently with 10% and 30% H2O2 to

remove organic matter. After each treatment with chemicals the samples were rinsed three times

with demineralised water. The chemical pre-treatment was followed by wet and dry sieving. The

most abundant grain-size fraction (125-180 µm) was retained.

The minerals were then separated based on their difference in density using heavy liquids (solutions

of sodium polytungstate, a heavy inorganic salt; Na6[H2W12O40].xH2O). Solutions were used with

densities of 2.75 g/cm³, 2.62 g/cm³ and 2.58 g/cm3 to remove the heavy minerals (> 2.75 g/cm³),

isolate quartz and plagioclase grains (2.75 g/cm³ - 2.62 g/cm³), and a K-rich feldspar-fraction (< 2.58

g/cm3). The quartz-enriched fractions were then etched for 40 minutes in 48% HF, while K-rich

feldspar was etched for 40 minutes in 10% HF. After etching, the samples were washed for 1 hour in

diluted HCl to remove precipitated fluorides, rinsed with demineralized water, dried and re -sieved to

125 µm.

For luminescence measurement, a monolayer of quartz grains was mounted on the inner 8 mm of

9.8 mm diameter stainless steel discs using silicon spray as adhesive. Grains of K -feldspar were

mounted in stainless steel cups, using a spray mask with a 1 mm diameter annulus.

53

Luminescence measurements were performed using either a Risø TL-DA-12 (for quartz) or TL-DA-15

reader (for quartz and feldspar). Both readers are equipped with blue (470 ± 30 nm) LEDs.

Stimulation with infrared light was through IR diodes (875 nm; TL-DA-15) or an IR laserdiode (830

nm; TL-DA-12). Details on the measurement apparatus can be found in (Bøtter-Jensen et al., 2003).

Irradiations were carried out using calibrated 90Sr/90Y beta sources mounted on the readers. The

luminescence emissions of quartz were detected through a 7.5 mm thick Hoya U-340 UV filter. The

luminescence emissions of K-feldspar were detected through a Schott BG39 / Corning 7-59 filter

combination (Buylaert et al.,2008).

The samples for dose rate determination were dried at 110 °C until constant weight, pulverised and

homogenised. This material was then cast in wax (see e.g. (De Corte et al., 2006)) and stored for at

least one month before being measured on top of a low-level extended energy-range gamma-ray

spectrometer.

54

Table 9-2: The specific activities of radionuclides in the samples. This is obtained by a low-level extended energy-range gamma-ray spectrometer. Da samples are the samples used for dose rate determination. The dose rates are used to obtain an age for the De samples (luminescence analysis samples).

layer Resp. De sample

Da sample

specific activities (Bq/kg)

40K 234Th 226Ra 210Pb 235U 232Th

12B GLL-133402

GLL-133401

367.2 ± 4.5 19.7 ± 1.8 19.1 ± 0.5 21.1 ± 1.7 0.9 ± 0.1 22.8 ± 0.3

GLL-133403

274.4 ± 4.2 14.9 ± 1.7 12.7 ± 0.6 14 ± 1.1 0.7 ± 0.1 20.5 ± 0.3

GLL-133404

357.6 ± 5.4 17.4 ± 1.7 20.6 ± 0.7 22.1 ± 1.4 0.8 ± 0.1 25.4 ± 0.4

12C GLL-133406

GLL-133405

401.9 ± 6.2 22.4 ± 3.3 20.0 ± 0.7 18.9 ± 2.4 1.0 ± 0.2 24.3 ± 0.7

GLL-133407

277.3 ± 3.1 11.5 ± 1.2 12.5 ± 0.4 12 ± 1.4 0.5 ± 0.1 16.8 ± 0.3

GLL-133408

486.7 ± 6.9 28.3 ± 2.1 28.2 ± 0.8 30.2 ± 1.8 1.3 ± 0.1 29.1 ± 0.6

12E GLL-133413

GLL-133412

399.9 ± 5.3 43.9 ± 2.2 20.8 ± 0.7 19.3 ± 1.6 2.0 ± 0.1 26.7 ± 0.4

GLL-133414

265.8 ± 3 13.5 ± 1.4 13.7 ± 0.3 12.5 ± 1.2 0.6 ± 0.1 19.2 ± 0.2

GLL-133415

294.9 ± 2.4 13.2 ± 1.5 15.3 ± 0.3 11.6 ± 1.4 0.6 ± 0.1 21.5 ± 0.3

12F GLL-133417

GLL-133416

435 ± 6.2 38.4 ± 2.6 24.3 ± 1 20.4 ± 2.3 1.8 ± 0.1 29.5 ± 0.5

GLL-133418

267.4 ± 4.1 15.5 ± 1.9 15.2 ± 0.4 11.7 ± 1.1 0.7 ± 0.1 21.3 ± 0.4

GLL-133419

462.3 ± 6.6 30.2 ± 2.1 24.7 ± 1 26.2 ± 3 1.4 ± 0.1 29.4 ± 0.5

55

Table 9-3: The measurements of the water content. And the extrapolations of the F and W values. The values of GLL-133419 are extrapolated from GLL-133416.

layer

dated

sample sample

natural

weight

dry

weight water content F-value W-value F*W

g g

% of dry

weight

fraction of time at full

saturation

average porosity over

time %

12B GLL-

133402

GLL-133401 239.67 96.26 149% 0.97 ± 0.03 153% 1.49 ± 0.04

GLL-133403 133.12 103.06 29% 0.97 ± 0.03

30% 0.292 ±

0.008

GLL-133404 268.8 102.84 161% 0.97 ± 0.03 166% 1.61 ± 0.05

12C GLL-

133406

GLL-133405 177.95 68 162% 0.84 ± 0.16 192% 1.6 ± 0.3

GLL-133407 452.66 361.37 25% 0.84 ± 0.16 30% 0.25 ± 0.05

GLL-133408 185.47 59.43 212% 0.84 ± 0.16 252% 2.1 ± 0.4

12E GLL-

133413

GLL-133412 226.87 60.42 275% 0.73 ± 0.27 376% 3 ± 1

GLL-133414 139.56 114.41 22% 0.73 ± 0.27 30% 0.22 ± 0.08

GLL-133415 317.22 202.09 57% 0.73 ± 0.27 78% 0.6 ± 0.2

12F GLL-

133417

GLL-133416 201.54 58.17 246% 0.89 ± 0.11 277% 2.5 ± 0.3

GLL-133418 121.54 95.96 27% 0.89 ± 0.11 30% 0.27 ± 0.03

GLL-133419 245 71.16 244% 0.89 ± 0.11 277% 2.5 ± 0.3

56

9.3 Dosimetry

The specific radionuclide activities are tabulated in Table 9-2. These specific activities were converted

to dose rates using factors derived from the nuclear energy releases tabulated by Adamiec and

Aitken (1998). A factor of 0.9 (± 5 % relative uncertainty) was adopted to correct the external beta

dose rates for the effects of attenuation and etching (Mejdahl, 1985). The internal beta dose rate to

K-feldspar was calculated using a 40K content of 12.5 ± 0.5 % (Huntley and Baril, 1997) and a 87Rb

content of 400 ± 100 mg kg-1 (Huntley and Hancock, 2001); a small internal alpha contribution of

0.10 ± 0.05 Gy ka-1 was added (Mejdahl, 1988), and is unlikely to represent a significant source of

inaccuracy.

Correction for the effect of moisture was performed following the procedure outlined in Aitken

(1985). The water content at present is estimated out of the weight loss by drying. It is expressed as

the fraction of dry weight. The W value can be considered as the porosity of the sediment over the

dated time. It is usually calculated as the ratio of the mass of the water that the sample takes up at

full saturation to the mass of the dry sample. Here the W of the sand is predefined as 30%. The F

value is considered the fraction of saturation corresponding to the average water content over the

dated time interval. In this study we assumed this was the present fraction of saturation. This is a

worthy assumption since the present fraction of saturation is close to unity (100%) and no major

fluctuations are expected since these are young sediments. The error is defined as the difference of F

with unity (100%-F) since this is the maximum deviation of the water content. The F value of the mud

is assumed the same as the F value of the sand for one sample because the conditions for both were

probably the same over the dated time span. The W value of the mud is then the ratio of the present

water content of the mud to the F value. The product F*W is the average water content over the

dated timespan. This can be used for the moist correction outlined in Aitken (1985).

The contribution from cosmic radiation was calculated following Prescott and Hutton (1994), in

which the water column was added to the burial depth, and the weighted average density was used

of the sediment and the water column above the sampled layer; a relative systematic uncertainty of

15 % was associated with this value.

As the samples were collected from non-uniform surroundings (see chapter 5 ), we considered four

different scenarios to calculate the dose rate:

i) in a first scenario, it was assumed that the sand layers are thin enough for the beta and gamma

dose rate to originate entirely from the surrounding “muddy” material;

ii) a second scenario assumed that the beta contribution to the dose rate originates entirely from

within the sand layers, while the gamma component comes entirely from the surrounding mud;

57

iii) in a third scenario, we assumed uniformity of radioactivity in the surroundings of the samples,

with the total dose rate originating from the sand layers;

iv) in a fourth and last scenario, we used the specific radionuclide activities in the sand layers to

calculate the beta contribution, while the gamma component was evaluated according to the

method discussed in Aitken (1985, Appendix H), which allows for layer-to-layer variations in soil

radioactivity.

The calculated total effective dose rates are summarized in Table 9-4 and graphically represented in

Figure 9-2.

Table 9-4: Calculated total effective dose rates according to different scenarios.

layer sample Da (Gy)

scenario i scenario ii scenario iii scenario iv

12B GLL-133402 1.51 ± 0.01 1.77 ± 0.01 1.93 ± 0.01 1.85 ± 0.01

12C GLL-133406 1.61 ± 0.01 1.79 ± 0.01 1.88 ± 0.01 1.82 ± 0.01

12E GLL-133413 1.54 ± 0.01 1.76 ± 0.01 1.92 ± 0.01 1.85 ± 0.01

12F GLL-133417 1.39 ± 0.01 1.7 ± 0.01 1.9 ± 0.01 1.77 ± 0.01

Figure 9-2: The dose rate (Da) calculated using four different scenarios (see text for details). The data are normalised to

the values obtained in scenario (iv), in which the beta contribution originates entirely from within the sand layers, while

layer-to-layer variations in radioactivity were taken into account for calculating the gamma component. The solid line

(eye guide) represent a normalised Da equal to unity; the dashed and dotted lines (eye guides) bracket a 5% and 10%

deviation from unity, respectively.

58

Scenario (iv) takes all variables into account (such as thickness of the layers and layer-to-layer

variations in radioactivity). It represents the most accurate approach for calculating the dose rate;

therefore, these values were used for the final age calculation (see § 9.5.3).

Scenario (ii) is a simplification of scenario (iv), and yields yield values that do not differ by more than

5%. When assuming a uniform gamma dose rate based on the mud the contribution of the gamma

dose rate to the total is ca. 16%. When taking the contribution of the sand to gamma dose rate into

account this increases to ca. 20%. In this case the deviation induced by this will remain under 5%. We

therefore conclude that gamma-gradients are unlikely to represent a significant source of error.

However when the radionuclide activities and/or the water content differ significantly between the

different mud and sand layers, gamma dose gradients must be taken into account.

Scenarios (i) and (iii) represent two extreme cases, with the first being the least realistic, at least for

the samples in this study. Indeed, the sand layers have a thickness of at least 10 cm so it is implicit

that the beta contribution comes from within these sand layers, and not from the surrounding

material. If no information on the radioactivity of the sand layers would have been available, it would

have led to an underestimation of the dose rate by as much as 25%. Scenario (iii) would be

appropriate in case of thick (~30 – 50 cm) sand lenses. Indeed, for sample GLL-133406, which was

collected of an 30 cm-thick interval, the approach yields results that do not differ by more than a few

% than those obtained using scenario (iv); the difference becomes slightly larger as the sampled

layers become less thick. The comparison between scenario (iii) and (iv) illustrates the rather small

contribution to the gamma dose rate from the surrounding mud. This not only reflects the effects

attenuation and layer thickness, but also that of the correction for moisture, which is significantly

higher for the mud (see Table 9-3).

9.4 Quartz OSL

9.4.1 Experimental details

As described in section 9.2, the quartz extracts were obtained using conventional sample preparation

techniques. The purity of these extracts was tested by monitoring the infrared stimulated

luminescence (IRSL) response at 60 °C to a large ( ~ 50 Gy) regenerative -dose. The sensitivity to

infrared stimulation was defined as significant if the resulting signal amounted to more than 10% of

the corresponding blue-light stimulated luminescence signal (Vandenberghe, 2004) or if the OSL IR

depletion ratio deviated more than 10% from unity (Duller, 2003). A significant sensitivity to IR

stimulation was observed, even after three rounds of density separation and HF -etching. We

therefore investigated the luminescence characteristics of the quartz using a double-SAR procedure.

59

In this procedure, each stimulation with blue diodes (for 40 s at 125 °C) was preceded by a

stimulation with IR stimulation for 40 s at 60 °C. The first 0.32 s of the post-IR OSL curve was used in

the calculations, minus a background evaluated from the 0.32-1.12 s interval. A preheat of 180 °C

(10s) and a cutheat to 160 °C was used. After each measurement cycle a high-temperature cleanout

was performed by stimulation with the blue diodes for 40 s at 280 °C. The sequence consisted of

measuring the response to an 3.09-Gy regenerative -dose twice, separated by a measurement to

the response to a 0-Gy dose. Following the purity test, the reliability of the SAR-measurement

procedure was immediately tested using a dose recovery test (Murray and Wintle, 2003). In this test,

natural aliquots were bleached using the blue LEDs at room temperature (2 times for 250 s, with a 10

ks pause in between) and given a dose equal to the estimated De; they were then measured using the

double SAR-protocol outlined in the above.

9.4.2 Luminescence characteristics

Figure 9-3: example of a post-IR OSL decay for an aliquot of quartz extracted from sample GLL-133402.

Figure 9-3 shows a typical post-IR OSL decay curve for an aliquot of quartz extracted from sample

GLL-133402. Apart from a low signal to noise ratio, the decay is slower than expected for a quartz-

OSL signal that is dominated by the fast component.

60

Figure 9-4: example dose response curve for an aliquot of quartz extracted from sample GLL-133402. Note the high

recuperation and poor recycling.

Figure 9-4 shows a dose response curve for the post-IR OSL signal for an aliquot of quartz extracted

from sample GLL-133402. It is clearly demonstrates the poor behaviour of the material in the double

SAR-protocol. The overall recycling ratio differs significantly from unity. Recuperation is difficult to

analyse since the some values yield large uncertainties and are sometimes negative.

An average recovered to given dose ratio for 8 of the 12 samples where De could be analysed (± 1

standard error; n = 8) was obtained of: 15 ± 6. This value is significantly different from unity,

indicating that the measurement procedure is not able to accurately measure a known laboratory

dose that was given to the quartz extracts following optical resetting, but prior to any heat

treatment. Following Murray and Wintle (2003), such behaviour may be indicative of a quartz -OSL

signal that is not dominated by the fast component.

To examine the quartz-OSL signal composition to greater detail, measurements of the l inearly

modulated (LM) OSL signal were performed. Figure 9-5 A shows the regenerated LM-OSL signal for

an aliquot of sample GLL-133402. The shape of the LM-OSL signal differs significantly from that of

calibration quartz (Figure 9-5 B), a material that is generally accepted to be dominated by the fast

component. The quartz-OSL signal from our samples clearly lacks a bright, sensitive fast component.

61

Figure 9-5 A, B: Post-IR LM-OSL curve for an aliquot of quartz extracted from sample GLL-133402 (A). Post-IR LM-OSL

curve for an aliquot of calibrated quartz (B).

9.4.3 Discussion

No pure sand-sized quartz could be extracted from the samples, and the post-IR OSL signal does not

exhibit satisfactory luminescence characteristics; the signal is dim, not dominated by a fast

component, and does not behave well in the SAR protocol (as indicated by the procedural checks). It

is therefore concluded that it is not possible to use quartz OSL signals for dating these deposits.

Our observations confirm earlier studies that have shown that Andean quartz often shows unsuitable

OSL properties (Robinson et al., 2005; Spencer and Robinson, 2008; Ste ffen et al., 2009a,b, 2010;

Spiske et al., 2013). It has been suggested that the main causes for this behaviour relate to formation

age and the provenance of the material. Studies have shown that the quality of the OSL properties

of the quartz often relies on the number of recycling cycles these grains underwent (Aitken, 1998;

Sawakushi et al., 2012). This is because the amount of lattice defects increase with time and recycling

of the grains. Out of the minerals and lithic fragments observed in the thin sections and the

angularity of the grains (see section 8) it can be concluded that the sediment is immature. Therefore

the number of recycling cycles is probably limited.

The presence of quartz in complex, fine-grained lithic fragments suggests young sediment with a

possible metamorphic provenance (see Chapter 8). This could be the cause of the impurity of the

quartz.

62

9.5 Feldspar IRSL

9.5.1 Experimental details

Measurements of feldspar IRSL were made using a single-aliquot regenerative-dose (SAR) protocol

(Murray and Wintle, 2000), with experimental details appropriate to feldspar. Following Huot and

Lamothe (2003) and Blair et al. (2005), the same thermal pretreatment was applied prior to

measuring the response to the regenerative and the test dose; the duration of the preheat was 60 s.

Stimulation with IR was for 98 s at 50 °C (“IR50”). The first 2 s of the decay curve were used, minus a

background evaluated from the last 10 s of stimulation. Following each measurement of the

response to the test dose, a high-temperature cleanout was performed by stimulating with IR for 98

s at 290 °C (Buylaert et al., 2007). As K-feldpar is prone to anomalous fading, laboratory

measurements of the fading rate (or g2days-value) were also made using this SAR-protocol. Essentially

the procedure involved measuring the sensitivity-corrected response after various time-delays

following irradiation and preheating (Auclair et al., 2003; see also Buylaert et al., 2007, 2008; 2012).

The g-values were calculated using Eq. (4) of Huntley and Lamothe (2001) and normalised to a

measurement delay time of 2 days. Fading-corrected ages were calculated using Eq. (5) of Huntley

and Lamothe (2001).

In addition, we briefly investigated a newly developed post-IR IRSL approach, which appears to avoid

signal instability (Buylaert et al., 2012). After a preheat of 320 °C for 60 s, aliquots were stimulated

using IR LEDs for 200 s whilst holding them at a constant near-ambient temperature of 50 °C (IR50).

Subsequent IR stimulation (200 s) occurred at 290 °C (pIRIR290); the dosimetric signal of interest was

recorded during this period. The first 2 s of the decay curve were used, minus a background

evaluated from the last 10 s of stimulation. Natural, regenerative and test-dose responses were all

measured following using the same preheat. After every SAR cycle the samples were IR-stimulated

again at 325 °C for 200 s to minimize any build-up of charge giving rise to a recuperated signal. The

pIRIR290 signal was also tested for fading, using the pIRIR-SAR protocol and the procedure outlined

higher.

All measurements of K-feldspar were made running one aliquot at a time so that the timing between

irradiation, preheat and IRSL measurement were (more or less) the same for each aliquot within a

sample.

9.5.2 IR50: Luminescence characteristics

Figure 9-6 A and B show a typical decay and dose-response curve for the IR50-signal, respectively, for

an aliquot of sample GLL-133402.

63

Figure 9-6: A): Decay curve of the IR50-signal. B) SAR dose-response curve for an aliquot of sample GLL-133402. Note that

the interpolation is in the linear part of the dose response curve. The recuperation point is hardly visible because it is

close to zero. The recycling point (diamond dot) almost entirely overlaps the original dose response.

As commonly observed for K-feldspar, all samples emitted bright IR50-signals that were clearly

distinguishable from the background level. The dose-response curves could be well approximated by

exponential functions. Figure 9-6B also illustrates the good behavior of the samples in the SAR

protocol; the correction for sensitivity changes is working well (i.e. recycling ratios are close to unity)

and the dose response curves pass close to the origin (i.e. recuperation is negligible).

Figure 9-7 shows an example of a measurement of the fading rate for an aliquot of sample GLL-

133402. Shown are the Li/Ti ratios measured after various delays following irradiation and

preheating; the g-value can be obtained from the slope of the fit through the data that document the

loss of signal with time. In the given example, a value of g2days of 6.6 ± 0.8 % per decade was

obtained.

64

Figure 9-7: Fading data for an aliquot of sample GLL-133402

One of the main problems specific to the dating of young material is thermal transfer, which is the

transfer of charge by heating from light-insensitive (or less light-sensitive) but thermally stable traps,

into light-sensitive traps. If significant, it leads to an overestimation of the equivalent dose (De) and

hence the age. To test for thermal transfer in our samples, we measured the De as a function of

preheat temperature for both the uppermost (GLL-133402, layer 12B) and the lowermost sample

(GLL-133417, layer 12F). The results are shown in Figure 9-8.

For sample GLL-133402, a smooth increase in De with preheat is observed for temperatures higher

than 80°C; there is also a clear jump in De when the temperature exceeds 185 °C, after which the De

continues to increase. For sample GLL-133417, there is no dependence of De on preheat

temperatures up to 185 °C; at higher preheat temperatures, the sample behaves as sample GLL-

133402. Figure 9-9 shows the corresponding recycling ratios and values for recuperation (expressed

as percentage of the natural corrected signal). The recycling ratios are well within 5 % from unity and

show no dependence on preheat temperature; the large uncertainties associated with values

obtained for preheats above 300 °C, reflect the small IR50 signal intensity that is commonly observed

after such high temperatures (see e.g. Popov et al., 2012). There is little or no dependence of

recuperation on preheat up to temperatures of ~ 225 °C, with values around 4 % and 1 % of the

corrected natural signal for samples GLL-133402 and -17, respectively. At higher preheats,

recuperation increases with temperature up to about 10 % at 325 °C.

65

Figure 9-8 A,B: Dependence of equivalent dose (De) on preheat temperature for samples GLL-133402 (A) and GLL-133417

(B). The inset in Fig 9a illustrates the rising trend for preheat temperature in excess of 80°C. Each datapoint represents

the average of 6 measurements (± standard error)

66

Figure 9-9 A,B: Recycling ratios and recuperation (expressed as percentage of the natural corrected signal) as a function

of versus preheat for samples GLL-133402 (A) and GLL-133417 (B). Each datapoint represents the average of 6 aliquots;

error bars are 1 standard error. The solid line (eye guide) represents a recycling ratio equal to unity.

While in case of quartz OSL an increase in De with preheat is generally attributed to thermal transfer,

the situation is more complex for feldspar because of anomalous fading, which may also be

temperature dependent (see e.g. Murray et al., 2009; Popov et al., 2012). Figure 9-10 presents the

fading rates corresponding to the data presented in Figure 9-9. For both samples, the fading rate

clearly decreases with increasing preheat temperature. Thus, to correctly assess the significance of

67

thermal transfer, it is necessary to examine the dependence of the fading-corrected ages as a

function of preheat temperature. This dependence is shown in Figure 9-11. For sample GLL-133402,

the corrected ages increase with preheat temperature and no clear plateau region can be identified.

For sample GLL-133417, there is no systematic trend in corrected age with temperature across the 50

°C – 185 °C region; at higher preheats, the corrected ages increase with temperature.

Based on the data shown in Figure 9-11, we interpret the rise in corrected age with increasing

preheat temperature as being caused by thermal transfer. For the youngest sample, the magnitude

of thermal transfer is already significant for preheat temperatures of as low as ~ 115 °C. From the

plateau observed over the 50 °C – 185 °C preheat temperature region for sample GLL-133417, we

conclude that there is no strong evidence for a significant contribution from thermally unstable traps

to the regenerative data but not in the natural IR50-signal. If indeed the case, there is no need to use

high preheat temperatures to obtain reliable estimates of De (or age) and it is valid to use a preheat

of as low as 80 °C to minimize the unwanted contribution from thermal transfer. These observations

and conclusions are in line with those reported by, e.g., Murray et al. (2009) and Vandenberghe et al.

(2014). For all further analyses, we therefore adopted a preheat of 60 s at 80 °C for all samples.

68

Figure 9-10 A,B: Dependence of fading rate (g-value) on preheat temperature for sample GLL-133402 (A) and GLL-133417

(B). Each data point represents the average (± 1 standard error) of 6 measurements.

69

Figure 9-11 A,B: Dependence of fading corrected age on preheat temperature for samples GLL-133402 (A) and GLL-

133417 (B). Each datapoint represents the average (± 1 standard error) of 6 measurements.

9.5.3 IR50: Distributions and ages

A second problem specific to the dating of young samples, is incomplete resetting, which causes age

overestimation. In addition, and specific to the dating of tsunami-laid sands, is the possibility that the

deposits may consist of a mixture of material of various age (see section 6.6). The presence of

incomplete resetting and/or mixing can be identified through De (and corrected-age) determination

using a large number of aliquots that consists of a small number of grains (or single grains). As such

measurements are time-consuming, we adopted a simplified procedure, which was based on the

observations reported in the previous section.

At low doses, the dose-response curve is (very close to) linear. For the samples under consideration

in this study, the natural doses are also very low and the natural IR50-signal thus intersects with this

linear part (see Figure 9-12). We also observed that, using a preheat of 60 s at 80 °C, recuperation is

negligible (Figure 9-9). This implies that it is possible to construct a dose response curve by forcing a

straight line through the origin and a single sensitivity-corrected regenerative dose point that is

chosen to be somewhat larger than the natural dose. Individual recycling ratios did not differ by

more than a few % from unity, which we interpret as indicating a generally well behaviour in the SAR

protocol; given that this test is only meaningful when a SAR measurement sequence consists of at

least three or four cycles, we decided to omit it. Hence, the procedure we adopted for D e

70

determination consisted of two cycles only, a measurement of the corrected natural signal and a

measurement of a corrected regenerated signal; the approach is illustrated in Figure 9-12.

Figure 9-12: SAR dose-response curve obtained using the shortened measurement procedure. The dose response curve is approximated by a straight line through the origin and the regenerative dose point. The D e is obtained by interpolation of the natural corrected signal.

Using the shortened measurement procedure, the De was measured in at least 54 small aliquots of

each sample. The results are shown as histograms in Figure 9-13. As histograms do not take into

account the difference in precision by which each value is determined, a plot of De versus uncertainty

is shown above each histogram. The individual uncertainties were assessed using an elementary

Monte Carlo simulation (Press et al., 1986) and includes that arising from counting statistics and an

instrumental uncertainty of 2% per IRSL measurement.

71

72

Figure 9-13: Results from small-aliquot analyses for samples of GLL-133402 (a), GLL-133406 (b), GLL-133413 (c) and GLL-

133417 (d). A plot of De versus uncertainty is shown above each histogram; the median from this uncertainty distribution

was used for binning the data.

Apart from a few outliers, the De values in samples GLL-133413 and -17 appear normally spread

around a mean value, with a relative standard deviation (RSD) of ~ 30 %. For samples GLL-133402

and -06, however, the De’s are spread out over a larger dose range (RSD’s of 86 % and 48 % ) and lead

to asymmetric distributions. While such a spread may be indicative of incomplete resetting or mixing,

it could also reflect a variability in fading rate. The fading-rate of all aliquots that had been used to

construct the De-distributions was therefore measured; these measurements were performed as

outlined earlier and the results are plotted as histograms in Figure 9-14.

73

Figure 9-14: Histograms summarising the measured fading rates (g2days-values) corresponding to the data shown in Fig. X.

The median of the uncertainty distribution was used for binning the data.

For each sample, the g-values more or less cluster symmetrically around a mean value. Taking the

measurement uncertainty into account, the four samples exhibit the same fading rate of about 6%

per decade. There is no clear relation between De and g-value, and high De values are not necessarily

associated with low fading rates. This is further illustrated in Figure 9-15, which plots the fading-

corrected ages as histograms, assuming that the same dose rate is appropriate to each aliquot.

74

Figure 9-15: Distribution of fading corrected ages for samples GLL-133402 (A), GLL-133406 (B), GLL-133413 (C) and GLL-

133417 (D). The median of the uncertainty distribution was used for binning the details. Indicated in black is that part of

75

the distribution that was retained for age calculation (see text for details). The retained values are defined as selected in

(A) and (B) and as inliers in (C) and (D). The un-weighted average, standard error and relative standard deviation (RSD)

are given for the retained values. The RSD is also given for the total distribution.

For samples GLL-133413 and -17, the majority of the results appears to belong to a broad, single

population; a few aliquots yield significantly higher corrected ages, possibly reflecting the presence

of incompletely reset grains or the incorporation of material with a significantly higher age. Rejecting

the obvious outliers (with an age that differs by more than 3 RSD’s), yields normal distributions with

an RSD of 18 % – 22 %. We interpret these distributions as those for samples consisting of grains

from the same age population; this implies that, prior to dose accumulation, these grains were well -

reset and that these particular tsunami-deposits do not consist of a mixture of material with a

significantly different age. The un-weighted average (± 1 standard error) corrected age for sample

GLL-133413 is 1.63 ± 0.05 ka; sample GLL-133417 yields an age of 1.44 ± 0.04 ka .

For samples GLL-133402 and -06, broad asymmetric age distributions were obtained. While it is

possible to remove the obvious outliers with an age than differs by more than 3 RSD’s, it is clear that

the resulting distributions (indicated by the green histograms in Figure 9-15) do not reflect those of

material that consists of coeval grains.

Several statistical approaches have been proposed to deal with dose distributions in incompletely

reset samples (see e.g. Cunningham and Wallinga, 2013). Vandenberghe et al. (2013) previously

suggested a pragmatic procedure, which uses the spread observed for a well -bleached sample with

similar luminescence characteristics (i.e. behaviour in the protocol, brightness etc.) to extract the

population of aliquots with the lowest De’s from a distribution of doses in a less-well bleached

sample; these lower values are more likely to give the true age since burial. In this study, the

approach is applied to the age distributions observed for samples GLL-133402 and -06; assuming that

the deposits were not affected by post-depositional mixing, the population with the lowest ages is

more likely to reflect the time of the tsunami-event, regardless of the precise cause of the

distribution (incomplete resetting and/or mixing during final transport). Rejecting the outlying values,

the spread observed for samples GLL-133413 and -17 (~ 20%) is taken to represent the level of

precision that can be expected for a sample consisting of coeval K-feldspar grains. For samples GLL-

133402 and -06, De values were sorted ascending, and the overall average De and RSD calculated. The

average De and RSD were then recalculated iteratively, each time rejecting the highest dose value

until the RSD approximated that observed for samples GLL-133413 and -17. The procedure is very

similar to the one suggested by Fuchs and Lang (2001), but differs by using the spread observed in a

76

natural sample, instead of that in a sample that was artificially bleached and irradiated. The age

populations thus obtained procedure are graphically represented in Figure 9-15 as the histograms in

black. For sample GLL-133402, an un-weighted average (± 1 standard error) corrected age of 0.174 ±

0.005 ka was obtained; sample GLL-133406 yielded an age of 0.70 ± 0.02 ka.

Now that we have extracted a single age population from the distributions, it makes sense to re -

examine whether there is a relation between equivalent dose and g-value for the aliquots belonging

to these populations. The rationale behind this re-examination is that, should there be a relation

between De and g-value, it might be possible to derive a De that is not affected by fading (i.e. g-value

= 0 % per decade) and hence an age without the need for a fading-correction model (Lamothe et al.,

2012). Figure 9-16 shows the histograms for the De and g-values corresponding to the age

distributions obtained using the procedure outlined in the above; the De values are plotted versus

the g-values in Figure 9-17.

77

Figure 9-16: Histograms De and g-values corresponding to the age population selected using the procedure suggested by Vandenberghe et al. (2013); see text for details.

78

Figure 9-17: Plots of De versus g-values for the data shown in Figure 9-16 (solid symbols); for the sake of completion,

rejected values are indicated by the open symbols.

Figure 9-17 illustrate that, despite the observed variability, no unambiguous relation can be

established that would allow deriving a precise De value through extrapolation to a zero fading rate.

For the sake of completion, it is added that we have also calculated IR50 ages from the distributions

using both the central age model (CAM) and the minimum age model (MAM), which have been used

more widely in the literature (Galbraith et al., 1999). A 3-parameter MAM was used with a

predefined overdispersion of 20 % (based on our observations for samples GLL-133413 and -17; see

higher).The results are included in Table 9-5.

Table 9-5: overview of the obtained ages and results from the used age models of Galbraith et al. (1999). The selected

are the ages obtained by the procedure of Vandenberghe et al. (2013). With CAM an age and an overdispersion is obtained and with MAM the % of completely bleached grains and the standard deviation of the half normal normal distribution is obtained.

layer sample selected CAM MAM

age (ka) age (ka) overdisperdion age (ka) % completely bleached

SD, half normal

12B GLL-133402

0.174 ± 0.005

0.25 ± 0.06

52 ± 5%. 0.136 ± 0.007

0.10%. 0.78

12C GLL-133406

0.70 ± 0.02

0.84 ± 0.07

57 ± 5%. 0.50 ± 0.03

2.56%. 0.65

12E GLL-133413

1.63 ± 0.05

1.58 ± 0.03

15 ± 3%. 1.56 ± 0.05

96.95% 1.14

12F GLL-133417

1.44 ± 0.04

1.45 ± 0.04

20 ± 3%. 1.42 ± 0.05

94.37% 0.58

As expected the ages derived using CAM are always older that those obtained using MAM. For

samples GLL-133413 and -17, the ages are quite comparable, as expected for samples that consist of

79

a single age population. The un-weighted average of the retained ages is in-between the ages

obtained by the CAM and MAM.

Since partial bleaching or contamination is only clearly visible for GLL-133402 and GLL-133406 only

here the MAM (3-parameter minimum age model) would give a reliable result. Since there is a clear

extension to older ages in samples GLL-133402 and GLL-133406 it is unlikely that the CAM would give

a reliable result for these samples. Apart from the outliers, the distribution of the ages of samples

GLL-133413 and GLL-133417 show a good fit with a normal distribution (see section 9.5.3). The

outliers also have a large standard deviation; see Figure 9-15. Therefore a CAM model based on a

weighted average seems suitable to characterise the age of the samples.

The method of Vandenberghe et al. (2013) can be considered reliable because the dataset is large

enough. This means than even if the separate random uncertainties of all the ages are not

introduced the uncertainty will be represented in the scatter of the data. Therefore is the mean of

the selected data and the standard error a reliable measure for the age and uncertainty. This also

means that no separate error assessment of the random uncertainty for each age is needed.

In this study the supposed spread of a completely bleached sample is based on samples that are

assumed completely homogenously bleached. In this case this is sample GLL-133417. The spread is

taken from a sample of this study itself because this sample underwent all the same conditions in

measuring as the other samples. Therefore it is the most reliable measure for analysing the other

samples. This relative spread is extrapolated to partial bleached samples. However partial bleaching

is an absolute effect on the spread of the obtained ages. It will have a re latively larger effect on the

spread of younger samples. Therefore care has to be taken when extrapolating a relative spread.

The advantage of the age models of Galbraith et al. (1999) is that it accounts for the individual

uncertainties of the ages. It is therefore applicable for datasets that are not very large (Arnold et al.,

2009).

A disadvantage of the age models is that we do not know how well the probability density functions

of Galbraith et al. (1999) fits with the distribution of partially bleached grains that are possibly mixed

with older sediment.

Arnold et al. (2009) also mentioned that the age models (MAM, CAM) of Galbraith et al. (1999) are

not reliable when applied to very young samples such as GLL-133402. This is because the logarithmic

functions become unreliable when used with data that contain numbers close to zero. In GLL-133406

one aliquot had a very young age. An adaptation of the overdispersion has therefore a significant

80

effect on the obtained age. The previous method of data selection is not very sensitive to a change in

specified relative standard deviation.

Since the dataset is large enough and the ages are relatively young the method of Vandenberghe et

al. (2013) is considered as the most robust one.

The ages thus obtained are broadly consistent with the stratigraphic position of the samples. A slight

age inversion, however, is observed for samples GLL-133413 and GLL-133417 (eg. Resp. 1.628 ±

0.047 ka & 1.441 ± 0.036 ka not counting the systematic error). With only counting the random

uncertainty they fall outside each other’s uncertainty range. However this might be an

underestimation of the random uncertainty since water content can change over time differently for

different layers. Therefore could the uncertainty of moisture content partly be random. Another

explanation of the age inversion is a wrong assumption made by the interpreting methods. The

normal distribution seems to define the retained ages of GLL-133417 better than the retained ages of

GLL-133413. When looking at the age distribution histogram of the inliers of GLL-133413 (Figure

9-15) it could be interpreted as extended to higher ages instead of completely bleached. The method

of Vandenberghe et al. (2013) could therefore give a wrong estimation for GLL-133413. The correct

estimation might be obtained by further data exclusion. If the age obtained for GLL-133413 should

not be older than the age of GLL-133417 older ages must be excluded from the GLL-133413

distribution until the relative standard deviation is less than 13.4%. The peak frequency in the

distribution of GLL-133413 is located at a younger age than the un-weighted average of the retained

ages (Figure 9-15). The peak frequency of the distribution is therefore at a lower age for GLL-133413

than for GLL-133417. However it is ambiguous to make assumptions based on peak frequencies since

they do not account for uncertainty and the size is defined rather arbitrarily median of the standard

deviations. Another assumption is that there is an actual age inversion ). Assuming that all the

estimations of the annual dose were done correctly few other sources of error could explain an age

inversion. Another possible explanation for the age inversion could be that two tsunamis occurred

within a very short time scale. In this case a tsunami would scrape of a layer of younger well bleached

sediment which is followed by a second tsunami that scrapes off underlying older sediment and

deposits it on top of the previous tsunamite. These two waves could in this case even be linked to

one tsunami since wave periods can be above one hour. However the clear presence of background

sediment between the two layers argues against this hypothesis. Therefore the first assumption of

inaccuracy due to the analysing method and the older age of the lowermost samples is the most

presumable.

81

9.5.3.1 Uncertainties.

As some sources of systematic uncertainty are shared between all samples, only the random

uncertainties have been taken into account to evaluate the internal consistency of the ages. It is

acknowledged that, given the variability in moisture content, these may be somewhat

underestimated (which may partly account for the apparent age inversion). When comparing the

luminescence ages with independent age information, however, it is necessary to also take the

systematic uncertainties into account. Sources of systematic uncertainty include the calibration of

the beta source (2%), conversion of concentration data to dose rates (3%), factors that allow for

attenuation and etching (5%), calibration of the gamma spectrometer (3.5%), and assumptions with

respect to the moisture content (see section 9.3 and Table 9-8) and calculation of the cosmic dose

rate (15%). Uncertainties on the luminescence ages were calculated following the error assessment

system proposed by Aitken and Alldred (1972) and Aitken (1976); the ages and their associated

uncertainties are given in Table 9-6. It can be seen that the systematic uncertainty is dominant in the

overall uncertainty on the ages, which varies in between 6 and 9 % (1 sigma). This illustrates the

time-resolution that can be achieved using the methods used in this work.

Table 9-6: Summary of the optical ages and their random, systematic and total uncertainties.

layer sample dose rate

(Gy/a)

age random

uncertainty

systematic

uncertainty

total uncertainty

moist

corr

total % ka

12B GLL-

133402

1.85 ± 0.01 0.174 ± 0.005 2.9% 0.57% 5.27% 6% 0.01

12C GLL-

133406

1.82 ± 0.01 0.70 ± 0.02 2.9% 3.54% 6.33% 7% 0.05

12E GLL-

133413

1.85 ± 0.01 1.63 ± 0.05 3.1% 6.84% 8.83% 9% 0.15

12F GLL-

133417

1.77 ± 0.01 1.44 ± 0.04 2.8% 3.15% 6.35% 7% 0.1

A possible source of error when dating sediments with luminescence is the changing environment

over time. This will influence the annual radiation dose. When, for example, the height of the water

column and the burial depth changes over time, the cosmic radiation dose over time will change. A

82

(age depth) model can be used in order to obtain a more precise result or to have a better estimate

of the uncertainty. Madsen et al. (2005) calculated the maximum uncertainty induced by this by

comparing a model with an immediate total burial after sedimentation and a model with

instantaneous burial immediately before sampling. The deviation between these two extremes was

ca. 3%. This is the maximum error that can be assumed caused by uncertainty of burial depth. In our

case there is also an uncertainty with the height of the water column. This can change over time.

When comparing the unlikely extreme case of no water being present over whole the dated time

range the deviation for the youngest shallowest sample will be maximum ca. 6%. The deviation of

deeper samples will be less. Since the extremity of this case the uncertainty induced by this will be

much smaller. In this study even with the high amount of data the minimum relative standard error is

6%. It is therefore safe estimation that changes in water depth over time can be neglected. In this

study a relative standard deviation of the cosmic radiation of 15% is incorporated in the systematic

error assessment. This should account for faulty assumptions about the burial and water depth over

time. However since the subsidence is mainly co-seismic, burial and water depth in time are

unpredictable. Garret (2013) obtained a vertical displacement curve for the last 1000 a and

concluded that the position of the shoreline hovered around the present position with a deviation of

2 m. The assumption to use the present conditions for whole the dated time range is therefore

certainly accurate enough.

The water content will also have changed in time under influence of burial depth. This will especially

influence the gamma ray dose. It also has to be considered that drying occurred during transport and

storing of the core tubes. Errors induced by this are far less straight forward to analyse.

In younger sediments as GLL-133402 thermal transfer will have a relatively larger effect than on older

samples (Hong et al., 2003). This could also have biased our results. However the preheat

temperature is kept low enough so that thermal transfer is minimised (section X).

The incomplete bleaching of the source sand is also an important error for young samples since

modern dune sands, as mentioned previously, can retain an IRSL age of over a decade. However in

our selected ages method and MAM already accounts for partial bleaching and will minimise the

error induced by this.

Another error that might occur is the change in radionuclide concentrations with burial depth and

time. This is especially important for sub aqueous young samples as in this study (Madsen and

Murray, 2009). Effects of nuclear fallout will be higher in younger and shallower water penetrated

layers. In this study the radionuclide concentrations are taken in and around each dated layer. The

variation of radionuclides with depth will therefore be accounted for but not the variation in time.

83

However a study of Madsen et al. (2005) showed that the contribution of the depth/time varying

210Pb/137Cs to the total dose rate is negligible.

9.5.4 pIRIR290: Luminescence characteristics

As indicated earlier (§9.5.1), we also briefly looked at the potential of pIRIR290 signals for dating these

tsunami-laid sands.

Figure 9-18 A and B show a typical pIRIR290-decay and dose-response curve, respectively, for an

aliquot of K-feldspar grains extracted from sample GLL-133402.

Figure 9-18 A, B: A) p-IRIR decay curve. B) p-IRIR290 dose-response curve for an aliquot of sample GLL-133402. The dose response-curve can be well approximated by a single saturating exponential function. The recuperation point is hardly visible because it is close to zero. The recycling point (diamond dot) almost entirely overlaps the first mea surement of

the regenerative dose at 3.5Gy.

Figure 9-18 illustrates the good behaviour of the pIRIR290-signal in the SAR protocol; the signal is

clearly distinguishable from the background level, recuperation is negligible and the recycling ratio is

close to unity. This is further illustrated in Figure 9-19, which plots the average recycling ratios and

values for recuperation observed for each sample. Recycling ratios fall within the 1.0 ± 0.1 criterion

suggested by Murray and Wintle (2000), while recuperation remains well below 5% of the natural

corrected pIRIR290-signal.

84

Figure 9-19: Average (± 1 standard error; n=3) recycling ratios (open diamonds) and values for recuperation (expressed as

% of the natural corrected pIRIR290-signal; open circles).

We also examined whether the pIRIR290-signal is subjected to anomalous fading. The g-values were

measured as outlined earlier (see Section §9.5.2) and a representative example of such a

measurement is given in Figure 9-20.

Figure 9-20: representative example of the data obtain in a fading measurement of the p-IRIR290 signal for an aliquot of K-

feldspar grains extracted from sample GLL-133402

Table 1-7 synthesis the average g-values, which range from 0.22 ± 0.81 to 0.93 ± 0.25 % per decade.

These values are comparable to those that were previously reported for the pIRIR290-signal (see e.g.

85

Buylaert et al., 2012). The values are also comparable to fading rates that have been observed for the

quartz OSL signal, which is generally accepted to be stable on time scales covered by lumi nescence

dating methods (Buylaert et al., 2012). It is therefore concluded that there is no convincing evidence

for the pIRIR290-signal to be affected by anomalous fading. Most likely, the low but finite fading rates

of ~ 1 % per decade are an artefact of the measurement procedure, and possibly relate to a small but

systematic error in the correction for sensitivity changes.

Table 9-7: the samples and their average g values. The g values are given with their standard error.

layer sample average g value (%/decade)

12B GLL-133402 0.41 ± 0.09

12C GLL-133406 0.22 ± 0.81

12E GLL-133413 0.61 ± 0.34

12F GLL-133417 0.93 ± 0.25

9.5.5 pIRIR290: ages

Assuming that pIRIR290-signals are not affected by anomalous fading indeed, ages can be derived

directly from the De and the Da, without the need to rely on a fading-correction model. The average

(± 1 standard error) pIRIR290-ages thus obtained are summarised and compared with the IR50-ages

(see 9.5.3) in Table 9-8 and Figure 9-21.

Figure 9-21: Comparison between the p-IRIR290 and IR50 ages. The large uncertainties associated with the pIRIR290-ages

reflects the limited number of measurements (two aliquots per sample).

86

Although only a limited amount of pIRIR290 measurements were made (two aliquots per sample),

Table 9-8 and Figure 9-21 clearly demonstrate that the pIRIR290 ages overestimate the IR50 ages by

about 6 ka. Part of this overestimation may be due to thermal transfer (see 9.5.2, Figure 9-11). It is

known, however, that the pIRIR290-signal is reset significantly more slowly that the IR50-signal (and

about one order of magnitude more slowly than the quartz OSL signal; Buylaert et al., 2012). It is

therefore concluded that, despite its attractive dosimetric properties (no anomalous fading), the

pIRIR290-signal is not likely to be of use for dating Holocene tsunami-laid sands.

Table 9-8: summary obtained ages with the standard errors.

layer sample selected CAM MAM p-IRIR290 ages

(ka)

12B GLL-133402 0.174 ± 0.005 0.251 ± 0.063 ka 0.136 ± 0.007 ka 6.5 ± 0.9

12C GLL-133406 0.70 ± 0.02 0.843 ± 0.070 ka 0.495 ± 0.027ka 6.3 ± 2.3

12E GLL-133413 1.63 ± 0.05 1.567 ± 0.028 ka 1.564 ± 0.053 ka 11.3 ± 2.6

12F GLL-133417 1.44 ± 0.04 1.451 ± 0.035 ka 1.415 ± 0.050 ka 10.5 ± 2.2

87

10. Dating results: Discussion

The distributions of the fading-corrected IRSL ages of GLL-133402 and GLL-133406 show a significant

extension to older ages (Figure 9-15). This indicates that these samples contain grains that have been

incompletely reset and/or consist of a mixture of grains with significantly different ages.

As a tsunami is a short high energetic event, it is unlikely that this transport process will expose

sedimentary grains to sufficient light to fully reset the luminescence signal (if they receive any light at

all). Hence, the issue of incomplete resetting is essentially one that concerns the bleaching history of

the source material that was eroded and re-deposited by the tsunami. Several studies have shown

that this material is not unlikely to have been derived from environments (such as beaches and

shallow-water deposits) that had already been thoroughly light exposed (Banerjee et al., 2001;

Murari et al., 2007). In this work, the ages were obtained using the IR50-signal from feldspar, which is

known to bleach one order of magnitude more slowly than the quartz OSL signal (see e.g. Buylaert et

al., 2012; their Fig. 5). Previous IRSL studies of modern active dunes yielded ages of the order o f a

decade (Ollerhead et al., 1994; Wolfe et al., 2002), which we interpret as indicating either an

unbleachable residual IR50 signal, or a finite age for the investigated deposits. Provided that the

tsunami-laid sands under investigation here were indeed derived from sediments that received

considerable exposure to light, an age offset of the order of ten years can be considered as

acceptable for dating on centennial and millennial timescales.

Other studies considered the possibility that the tsunami-laid sands consist of a mixture of deposits

with significantly different ages (Ollerhead et al., 2001; Cunha et al.,2010). Ollerhead et al. (2001)

postulated that the narrow inlet channel through older dunes led to erosion and deposition of older

sediments by the tsunami. In this study such an inlet channel is also present; it can therefore not be

excluded that the same process happened here. Given the difference in the corrected age -

distribution, this would imply that samples GLL-133402 and – 06 were derived from a different

environment than samples GLL-133413 and -17, which in turn might indicate a change in landscape

morphology in less than ~ 1 ka.

The distributions for samples GLL-133413 and GLL-133417 were interpreted as those for samples

consisting (mainly) of grains with the same age, implying that these sediments were derived from

well-bleached material (small residual doses become progressively less important with increasing

age). If this was also modern (i.e. “zero-age”) material, its luminescence age will accurately reflect

that of the tsunami-event. A large tsunami, however, may feature multiple waves that progressively

88

take up older material. In that case, one would expect age inversions in the record, even though the

sediments were derived from material that had been completely reset.

The aforementioned discussion is based on internal tests and methodological reasoning, and

illustrates the complexity of interpreting luminescence ages for tsunami-laid sands. The ultimate test

of their accuracy therefore consists of a comparison with independent age information.

An overview of all the ages with total errors from the different analysing methods is given in Table

10-1

Table 10-1: overviuw results with total errors.

layer Sample selected (ka) CAM (ka) MAM (ka)

12B GLL-133402 0.174 ± 0.01 0.25 ± 0.06 0.14 ± 0.01

12C GLL-133406 0.70 ± 0.05 0.84 ± 0.07 0.5 ± 0.04

12E GLL-133413 1.63 ± 0.15 1.57 ± 0.15 1.56 ± 0.15

12F GLL-133417 1.44 ± 0.1 1.45 ± 0.1 1.42 ± 0.1

The date of 0.174 ± 0.01 ka (1839 ± 10 AD) that was obtained for sample GLL-133402 falls within the

time range covered by the historical records. The result is consistent with the report of an

earthquake and accompanying tsunami that occurred in 1837 AD (see chapter 4). It is therefore very

likely that this sediment layer was indeed deposited by the 1837 tsunami. Up till now, there is no

published record of tsunami sediments linked to this particular event. That is probably because the

rupture only took place in the less studied southern half of the Valdivia segment (Lomnitz 2004;

Moernout 2014).

Sample GLL-133406 yields an age of 0.700 ± 0.05 ka (1313 ± 50 AD), which is consistent with a

radiocarbon dated event deposit in core “Pos15” (see chapter 5). The result is also consistent with

the age of 1319 ± 9 AD for tsunami deposits in Rio Maullín estuary (Cisternas et al., 2005) and

lacustrine seismoturbidites from multiple lakes (Moernaut et al., 2014). The deposit is interpreted to

represent a megathrust earthquake.

No accurate independent age information is available that would coincide with the dates obtained

for samples GLL-133413 and GLL-133417 (1.63 ± 0.15 ka and 1.44 ± 0.1 ka, respectively). However

these age-results fall within the timespan of minimum ages of possible tsunami deposits at the

Valdivia estuary (Nelson et al., 2009).

89

As discussed in section 9.5.3 The CAM is expected to yield a reliable result only for GLL-133402 and

GLL-133406, while the CAM is expected to yield a more reliable result for GLL-133413 and GLL-

133417.

However the MAM gives for GLL-133402 an age that doesn’t correlate to any historical event (1877 ±

10 AD) and is probably an underestimation induced by the earlier discussed possible biases (section

9.5.3.1). The MAM age of GLL- 133406 (1518 ± 27 AD) also doesn’t correlate directly with any

historical event. There is also no occurrence of this date in dated event deposits for studies in the

region. However, this age can be an overestimation of the 1575 event (Lomnitz, 1970). Since the age

of GLL-133402 is assumed to yield an underestimation it is unlike ly to assume that this MAM date

would be an overestimation.

The reliability of the CAM ages on GLL-133413 and GLL-133417 can’t be analysed since the ages of

these samples are older than the historical record and no event deposits where accurately dated to

this age in the region yet.

As outlined in section X the method of Vandenberghe et al. 2013 is considered the most robust. On

top of this the obtained ages with this method match with events in the historical record and earlier

performed datings.

Based on the luminescence dates, a new correlation is proposed between core “Pos12” and the

radiocarbon-dated core “Pos15” (Figure 10-1).

90

Figure 10-1: New correlation between core pos 12 and core pos 15.

The two lowest layers (12E and 12F) are correlated to a depth of ca 310cm in core pos15, between

two radiocarbon dates. However here is only one thin sand layer present.

The correlation of 12D to core pos15 therefore also shifts upward.

12C (GLL-133406) is dated to an age of 700 ± 50 a. This coincides with the original correlation which

correlated this event deposit to an event deposit in core pos15 where a plant fragment on top yields

a calibrated radiocarbon date of 720 ± 45 a.

Based on the luminescence age the correlation of 12B remains the same.

As a final note, it is pointed out that, throughout this work, the sandy layers have been interpreted as

tsunami-laid sands. It cannot be excluded that (some of) the deposits represent another type of high

91

energy event, such as storm surges (or storms in general). It is often very difficult to distinguish

between these depositional processes based on the sedimentological characteristics of the archive.

However, the presence of rip-up clasts and the high inundation distance argue for very energetic

events. In addition, there is no record of hurricane-like storms hitting the coast of Chile at the

latitude of our study area.

Still, care has to be taken when correlating the age of the sand layers to tsunami events. The fact that

the ages of minimum 2 samples can be correlated to seismic events drastically increases the

likelihood that these are in fact tsunami deposits.

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11. Summary and Conclusion.

One important aspect of tsunami hazard assessments concerns the timing of their occurrence. This

work presents an explorative study into the potential of luminescence dating techniques for

application to tsunami-laid sands in south-central Chile. The investigated sediments come from a

core that was taken in the coastal Lake Huelde; the sequence was about 5 m long and comprised six

sandy layers interpreted as being deposited by tsunami events. In the frame of this work, four of

these layers were examined using luminescence methods.

Given the non-uniformity in the radioactive surroundings of the samples, four different scenarios for

calculating the annual dose were considered. The most accurate results are obtained by using the

specific radionuclide activities in the sand layers to calculate the beta contribution, and evaluating

the gamma component according to the method discussed in Aitken (1985, Appendix H), which

allows for layer-to-layer variations in soil radioactivity. A simplified approach, which neglects these

gradients, yields values that do not differ by more than 5%. This indicates that, at least for the

samples in this study, the evaluation of the gamma-contribution is unlikely to represent a significant

source of error. One aspect that future studies may want to address to greater detail, is the

evaluation of the time-averaged moisture content; no undisturbed sediment samples were available

to evaluate the porosity (or saturation level), and it is not clear to what extent the moisture content

that was measured at the time of sampling is representative for the in-situ water content.

The luminescence investigations initially focussed on quartz. However, no pure quartz could be

extracted from the samples. The luminescence characteristics of the separates were therefore

investigated using a “double-SAR” protocol, which uses a stimulation with IR light prior to the OSL-

measurement, to minimize the contribution from feldspar. The post-IR OSL signals were dim, not

dominated by a fast component, and behaved very poorly in the SAR protocol (as indicated by the

SAR procedural tests: recuperation, recycling ratio and dose recovery). Microscopic observations

using thin sections were used to relate this luminescence behaviour to the mineralogical composition

and provenance of the sediments. It is concluded that OSL signals from quartz are not suitable for

dating these tsunami-laid sands.

The investigations were therefore directed towards an alternative dosimeter, K-feldspar. Stimulation

was with IR at 50°C (IR50) and the luminescence characteristics of this signal were investigated using a

SAR protocol. All samples emitted bright IRSL signals that behaved well in the SAR protocol in terms

of recycling and recuperation. We then examined the dependence of equivalent dose, anomalous

93

fading and fading-corrected age on preheat temperature for two samples. It is concluded that a low

preheat temperature of 60 s at 80 °C is required to minimize significant age overestimation owing to

thermal transfer. In line with earlier finds, we find no evidence that higher preheat temperatures

isolate a signal that is thermally more stable.

The distribution of equivalent doses, fading rates and fading corrected age was then examined in

each of the four samples. Broad distributions were observed for all samples. Apart f rom a few

outlying values, the corrected age distributions in the two lowermost samples, however, appear to

belong to a single population. The spread observed in these samples (RSD: ~20 %) was therefore

taken as a measure for the spread that can be expected for a well-bleached, undisturbed and

unmixed sample. The distributions obtained for the two uppermost samples are clearly asymmetric,

with values extending over a wider and higher age range. Using our estimate of the spread that can

be expected in the ideal situation, the population with the lowest corrected ages was isolated from

these distributions; these values are more likely to approximate the depositional age of the

sediments. The fading-corrected IR50-ages are broadly consistent with the stratigraphic position of

the samples and range from 0.174 ka to 1.64 ka. A slight age inversion was observed for the two

lowermost samples; it remains to be established whether this relates to an underestimation of the

uncertainties, dosimetric issues and/or the specific nature of the erosion and transport process.

Following the investigations using IR50, we also briefly examined the potential of pIRIR290-signals, as

this approach has been shown to circumvent any correction for anomalous fading. The pIRIR 290-signal

behaves well in the SAR protocol, and laboratory measurements of signal stability confirm the earlier

finds with respect to anomalous fading. The pIRIR290-ages overestimate the IR50-ages by ~6 ka, which

may be due to thermal transfer and/or incomplete resetting. It is concluded that, despite its

attractive dosimetric properties, the pIRIR290 signal is unlikely to be applicable to Holocene deposits.

In general, it is concluded that IR50-signals from K-feldspar provide a powerful means for establishing

chronologies for tsunami-laid sands in this region. This conclusion is corroborated through a

comparison of the IR50-ages with the available independent age information (such as historical

records and 14C-dating of comparable sequences in the study region). The study also provides the

first evidence for a tsunami triggered by the 1837 AD seismic event. Finally, our study also

demonstrates the importance of direct numerical age information for tsunami -laid sands to

determine the correlation between palaeoseismological records, even if these are derived from cores

that were taken in the same sediment archive (i.e. Lago Huelde).

94

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