variations in sedimentological properties in lake challa...

FACULTY OF SCIENCES

Master of Science in geology

Academic year 2015–2016

Master’s dissertation submitted in partial fulfillment of the requirements for the degree of Master in Science in Geology

Promotor: Dr. I. Meyer Tutor: Drs. M. Dumon Jury: Prof. Dr. T. Vandenbroucke, Prof. Dr. S. Bertrand

Variations in sedimentological properties in Lake Challa, East Africa: Understanding the

source to sink processes

Jonas Eloy

Picture cover sheet: View on Lake Challa (source: www.tanzania-experience.com).

ACKNOWLEDGEMENTS

The completion of this thesis would never have been possible without the help and support

of numerous people during the last few months. Therefore, I would like to thank all of them

personally on this page, as they have been very important.

First of all, I would like to thank my promotor Dr. Inka Meyer for giving me the opportunity

to investigate this inspiring topic. Her overall guidance, knowledge, dedicated time and

enthusiasm were very much appreciated and helped me a lot in finalizing this thesis. I really

enjoyed our collaboration and I wish her the best for the future.

A sincere thank you also goes to my tutor Drs. Mathijs Dumon for dedicating a lot of his time

in answering my questions and for guiding me through the theoretical part of the X-ray

diffraction analyses.

I also want to thank Veerle Vandenhende for helping and guiding me in the Laboratory of

Soil Science of the Geology and Soil Science Department. Always smiling, she gave me many

insights into the practical aspects of the X-ray diffraction method.

More gratitude also goes to Maarten Van Daele, Sébastien Bertrand, Carmen Juan

Valenzuela and Evelien Boes of the RCMG Department for explaining the various software

packages I worked with and for all sorts of small advice and contributions.

An enormous thank you must also be dedicated to all my friends and classmates during the

last five years. All those joyful moments were amazing and made my student life something

to cherish forever and to be never forgotten!

Last but not least, I want to thank my girlfriend Sara and my parents for their more than

endless motivating support and love throughout the thesis period and moreover during my

entire academic career. Without them, I would not stand where I am now!

TABLE OF CONTENTS

1 INTRODUCTION ......................................................................................................... 1

1.1 State-of-the-art and research objectives .................................................................... 1

1.2 Thesis outline ............................................................................................................... 3

2 STUDY AREA .............................................................................................................. 4

2.1 Geological setting ........................................................................................................ 4

2.2 Geographical setting .................................................................................................... 5

2.2.1 Sedimentology ...................................................................................................... 7

2.2.2 Hydrology ............................................................................................................. 7

2.3 Present day East African climate ................................................................................. 8

3 MATERIALS AND METHODS ..................................................................................... 10

3.1 Onshore samples ....................................................................................................... 10

3.1.1 Sample acquisition ............................................................................................. 10

3.1.2 Grain-size measurements ................................................................................... 10

3.1.3 Quantitative X-ray diffraction ............................................................................ 12

3.2 Short cores ................................................................................................................. 14


3.2.2 Core opening, core photography and macroscopic core description ................ 14

3.2.3 Multi-Sensor Core Logging ................................................................................. 15


3.3 Surface samples ......................................................................................................... 16




4 RESULTS .................................................................................................................. 18

4.1 Onshore samples ....................................................................................................... 18



4.2 Short cores ................................................................................................................. 29


4.2.2 Multi-Sensor Core Logging ................................................................................. 29

4.3 Surface samples ......................................................................................................... 32



5 DISCUSSION ............................................................................................................ 34

5.1 Controls on sedimentological properties .................................................................. 34

5.1.1 Onshore grain-size distributions and their spatial variations ............................ 34

5.1.2 Short core grain-size distributions and inter-core comparison ......................... 37

5.1.3 Surface grain-size distributions and their spatial variations .............................. 38

5.2 Controls on mineralogical properties ........................................................................ 41

5.2.1 On- and offshore XRD patterns and their spatial variations .............................. 41

5.3 Terrestrial source areas and source-to-sink processes at Lake Challa ...................... 46

6 CONCLUSIONS ......................................................................................................... 47

7 REFERENCES ............................................................................................................ 49

8 APPENDICES ............................................................................................................ 54

Chapter 1 – Introduction

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1 INTRODUCTION

1.1 State-of-the-art and research objectives

As the concept of climate change is becoming more and more important every year,

our society desires to understand past and recent climate changes in all its aspects.

According to Ruddiman (2008), there are plenty of ways to study climatic variations on Earth

as these are stored in various natural archives such as tree rings, ice cores, peat deposits,

coral reefs and on- and offshore sedimentary deposits. Regarding the investigation of the

latter archive, a plurality of research methods are available. Deposits of terrestrial material

in sedimentary basins can be used to reconstruct paleoclimatic and/or paleoenvironmental

conditions (Holz et al., 2007; Prins et al., 2000; Stuut et al., 2002). However, in order to be

able to validate paleo records, it is of uttermost importance to comprehend the modern

conditions and the evolution of terrigenous particles. Those calibrations are very useful in

defining Earth’s past, modern and future surface processes and in performing provenance

studies (Allen, 2008a; Visher, 1969). As such, one of the aspects scientists aim to understand,

are modern “source-to-sink” processes in various on- and offshore environments at different

latitudes.

The term “source-to-sink” comprises everything that is related to sediment dynamic

processes such as erosion, transport and deposition. These processes take place on various

spatial (and temporal) scales, for example from long-distance transport between continents

and ocean basins to meter-sized features (e.g. small gullies and ditches) (Allen, 2008b).

From the erosional point of view (i.e. the ‘source’), sedimentary geologists primarily aim to

answer questions as: ‘How are erosional processes affected by climatic factors? Can climate

changes be derived from long- and/or short-term evolutions of eroding surfaces?

What determines the exact location and timing of for example the erosion of a clastic

sedimentary particle?’ (Allen, 2008a). From the depositional point of view (i.e. the ‘sink’),

following questions are attempted to be answered: ‘Where is the clastic particle originating

from? Via which transport mechanism has a terrestrial particle been transported to its final

site of deposition (i.e. a lake, a river, an ocean basin)?’ (Allen, 2008a).

The origin of terrestrial sediment particles from several on-land sources can be linked to

physical (e.g. cold/arid conditions) and/or chemical (e.g. warm/wet conditions) weathering

of the initial bedrock. Whether physical or chemical (or both) weathering dominantly occurs,

depends on the latitude (i.e. tropics vs. poles) and the geological setting (i.e. mountains,

glaciers, deserts, fluvial plains). These weathering processes result in the erosion of the

bedrock and clastic particles are subsequently transported to their final site of deposition

through various mechanisms (Figure 1). On a global scale, fluvial processes are responsible

for the largest quantities of terrestrial sediment transport, followed by aeolian processes in

more arid environments (Milliman and Syvitski, 1992).


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Figure 1: Various transport mechanisms of terrestrial sediment particles originating from different on-land sources into a basin, i.e. a lake in this case. 1A) Fluvial transport by rivers, 1B) Fluvial transport through alluvial fans in mountainous regions, 2) Aeolian transport from e.g. deserts, 3) Sediment transport by ice in glaciers (modified from Tanghe, unpublished Msc thesis).

Investigations on source-to-sink systems have already been executed in several

environments and at different latitudes (e.g. the Danube Basin-Black Sea system (Matenco

and Andriessen, 2013), a dryland fluvial regime in Kachchh (Western India) (Prizomwala et

al., 2014), the Po Plain-Adriatic Sea system (Amorosi et al., 2016), in glaciated systems

(Jaeger and Koppes, 2016) and on lacustrine deposits of Lake Bosumtwi, Ghana (Shanahan et

al., 2013)) and have repeatedly proven the importance of these type of studies, namely that

basins are not isolated systems and that different transport processes and geological units

yield different products (i.e. mineralogy and grain size). Ultimately, as suggested in a poem

of William Blake, one can eventually “see a world in a grain of sand”.

Although the interest in the study of geologically-recent source-to-sink systems around the

globe is growing, a minority of these studies have so far been executed in lacustrine

environments at equatorial latitudes (10°N – 10°S), in particular due to the low abundance of

equatorial lakes worldwide. This is where this study attempts to fill a part of the existing gap.

As Lake Challa, a relatively small freshwater lake located on the border between Kenya and

Tanzania (3°19’ S, 37°42’ E), lies close to the equator, it is an ideal site to study variations in

the Northern and Southern Hemisphere (i.e. inter-hemisphere) climate systems, which on

their turn can affect the modern dynamics of terrestrial sediment transport. Moreover,

reflection seismic data of Moernaut et al. (2010) has indicated that Lake Challa has never

dried out during the past 25,000 years, contrary to other lakes in equatorial East Africa such

as Lake Victoria (Johnson et al., 1996). This is of great importance as Lake Challa thus

provides one of the few continuous and high-resolution sedimentary records that can be

used for paleoenvironmental and provenance studies since before the Last Glacial Maximum

(LGM) on the East African continent.


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In order to identify and quantify modern dynamics of terrestrial sediment input into Lake

Challa, and to map out variations in sedimentological and mineralogical properties,

the clastic fraction of sediments from in- and outside Lake Challa are investigated in this

study. As such, a combination of samples from short cores and lacustrine surface sediment

samples as well as onshore samples from several locations around the lake and in the further

catchment will be analysed here with the aim in solving following research questions:

1. Through which transport mechanism(s) are onshore clastic particles transported towards

or into Lake Challa?

2. Can onshore clastic sediment characteristics be traced back in the lacustrine sediments?

3. Can distinct source areas be derived from the obtained results?

In order to answer these questions, detailed and high-resolution grain-size analysis together

with mineralogical analysis on the clastic sediments will be executed in this research,

with the purpose to understand the origin of terrigenous particles and to understand the

modern transport mechanisms at our study site. By investigating spatial variations in grain

size and mineralogy, information about distinct terrestrial source areas can be obtained.

To conclude, as James Hutton (1726 – 1797) once said ‘The present is the key to the past’,

it is essential to comprehend and quantify modern and geologically-recent (e.g. late-

Pleistocene-Holocene) transport mechanisms and source-to-sink systems in order to

understand ancient ones. By applying the results of the modern conditions on the downcore

record of Lake Challa, information about changes in sediment provenance and terrestrial

sediment input in the lake over time can be derived (Tanghe, unpublished Msc thesis).

1.2 Thesis outline

In the following chapter a concise summary of the geological and geographical setting as

well as the climatological background of the study area is given. Chapter 3 provides a

complete sequence of the used materials and methods and is divided according to the three

different types of sedimentary material: onshore samples, short cores and surface sediment

samples. Depending of the type of material, various sedimentological and geophysical

analysis techniques as well as the X-ray diffraction (XRD) technique will be explained.

Chapter 4 comprises a report of the obtained results of the three sediment groups.

In chapter 5 the results will be interpreted and discussed with the purpose to evidence links

between the three different sedimentary groups. Finally, the main conclusions of this

research are summarized in chapter 6. A few words will also be spent on future research,

since this study is rather exploring.

Chapter 2 – Study area

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2 STUDY AREA

2.1 Geological setting

The geological history of East Africa is closely linked to the rise of the East-African Rift

System (EARS), also known as the Afro-Arabian Rift Valley, which represents an

approximately 4,500 km geographic trench that runs from the Afar Triple Junction in

northern Ethiopia through eastern Africa towards Mozambique in the south (Figure 2).

According to Baker et al. (1971), this is a classic example of an active continental rifting

system. The EARS consists of two branches, a western and an eastern one, which are still

tectonic and magmatic active. The more volcanically active eastern branch consists of

several segments, of which one is called the Kenya Rift. This segment (app. 600 km) extends

from Lake Turkana (northwest Kenya) to northern Tanzania (Figure 2) and started rifting in

the early Miocene around Lake Turkana in the north and subsequently further southwards

during the middle and late Miocene (Omenda, 2007). During the initial rifting phase up

doming and volcanism were the predominant processes, whereas during the early

Pleistocene a full graben system was formed (Omenda, 2007). The substrate consists of

erupted lava flows of basaltic and trachytic composition that were intercalated with tuffs.

Several large shield volcanoes of silicic composition were formed in the axis of the Kenya rift

during Quaternary times (Omenda, 2007). As such, the Mt. Kilimanjaro complex in northern

Tanzania started forming approximately 2.5 Ma ago and nowadays consists of three extinct

eruption centres: Shira, Mawenzi and Kibo. The last one went extinct about 150,000 years

ago. Due to numerous volcanic eruptions in the past, several craters were formed in the

proximity of this massive volcanic complex.

Lake Challa developed by filling up a caldera of Pleistocene age. As the lake lies on the

southeastern slope of Mt. Kilimanjaro, it is surrounded by igneous rocks (predominantly

trachy-basalts) of the tertiary Kilimanjaro complex (Bear, 1955). These basalts are covered by

“calcareous tuffaceous grits”, which is a calcite-cemented tuffaceous breccia that is probably

related to the formation of the Challa crater (Downie and Wilkinson, 1972). As observed by

Kristen (2010), these “calcareous tuffaceous grits” form the southeastern crater walls of

Lake Challa, whereas the rest of its crater rim mainly consists of trachy-basalts from the

Mt. Kilimanjaro complex. Finally, this volcanic complex is underlain by metamorphic rocks

(predominantly gneisses) that outcrop east and south of Lake Challa to the Indian Ocean

coast (Petters, 1991).


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Figure 2: Left: simplified geological setting of the African continent. The East African Rift System has a Cenozoic age and is indicated with yellow. The red dot indicates the position of the Mt. Kilimanjaro complex (modified from Kampunzu and Popoff (1991)). Right: the Kenya-rift segment, which runs from Lake Turkana in the northwest of Kenya to Tanzania in the south (Omenda, 2007).

2.2 Geographical setting

Lake Challa is a small freshwater lake, located at 880 m altitude on the southeastern slope of

Mt. Kilimanjaro on the border between Kenya and Tanzania (3°19’ S, 37°42’ E) (Figure 3).

The lake has a surface area of approximately 4.5 km² and the maximum water depth varied

between 92 and 98 m during the period 1999 – 2010 (Wolff et al., 2014). The crater

catchment is rather small (1.38 km²) and consists entirely of steep crater walls, which reach

up to 170 m above the modern lake surface (Buckles et al., 2014). Additionally, during

periods of exceptionally heavy rainfall, the crater catchment can be marginally enlarged to

1.43 km² when a small creek of ca. 300 m located in the NW corner (Figure 3) of the lake is

temporarily active (Sinninghe Damsté et al., 2009; Verschuren et al., 2009).


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Figure 3: Satellite image showing the geographic location of Lake Challa (3°19’ S, 37°42’ E) and its catchment on the southeastern slope of Mt. Kilimanjaro on the border between Kenya and Tanzania. The blue star in the figure below indicates the position of the 300 m small creek. Depth contours (Moernaut et al., 2010) are drawn at 10 m intervals to 90 m depth and at 94 m depth.


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2.2.1 Sedimentology

In 2003 a detailed reflection seismic survey on the lake revealed an approximately 210 m

thick sedimentary infill of predominantly horizontal deposits, which is estimated to cover the

last ~250,000 years (Moernaut et al., 2010). In general, the sediments of Lake Challa are

nicely laminated, but the degree of lamination depends on the location within the lake.

Sediments in the centre of the lake are more laminated than sediments closer to shore.

The sediments have an autochthonous character since they are mainly composed of organic

matter, biogenic silica from diatoms and endogenic calcite. Nonetheless, fine-grained clastic

particles are also present in low, yet varying amounts. According to Kristen (2010), 10 to 40%

of the sediments consists of siliciclastic material. A closer study of the laminations indicates

the presence of light and dark laminae. According to Wolff et al. (2011), light laminae are

dominated by diatom frustules that are deposited during drier and windier months of

southern hemisphere winter (June – October). During this period a diatom bloom is initiated

by an increase in the amount of available nutrients due to upwelling processes.

During southern hemisphere summer (November – March), when the lake is biologically

productive, darker laminae are deposited. These are mainly composed of organic matter,

calcite crystals and terrestrial siliciclastic material. Sediment trap data of Wolff et al. (2011)

confirm that light-dark lamination couplets in Lake Challa reflect the seasonal delivery of

diatom-rich material during winter months and diatom-poor material during summer

months.

2.2.2 Hydrology

Lake Challa contains no surface in- or outflows, as water transport is limited by the presence

of steep crater walls, which confine the crater catchment. Instead, the water budget of

the lake is largely controlled by sub-surface in- and outflow, together with the local

precipitation (app. 600 mm/yr.) and evaporation (app. 1700 mm/yr.) balance (Payne, 1970).

The sub-surface inflow (app. 80% or 12.5 x 106 m³) to Lake Challa derives from the

percolation of precipitation falling in the forests on the upper slopes of Mt. Kilimanjaro.

This inflow, mainly coming from the northwest, most likely also includes melt water of the

seasonal snow falling on the Mawenzi peak of Mt. Kilimanjaro (Figure 3) (Payne, 1970).

The remaining 20% of water input is due to local rainfall (app. 20% or 3 x 106 m³).

On the other hand, approximately 55% (8.2 x 106 m³) of the water output is due to

sub-surface outflow, which represents about 2.5% of the lake volume. The remaining 40% is

due to evaporation (Payne, 1970).


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2.3 Present day East African climate

The local climate around Lake Challa is tropical and semi-arid, resulting in a dry scrub

savanna landscape with relatively open grasslands and communities of trees (Figure 4).

According to Schüler et al. (2012), the modern surrounding savanna vegetation includes

Acacia, Terminalia, Grewia and Combretum woodlands.

Figure 4: Two photographs showing the dry scrub savanna landscape around Lake Challa with open grasslands (left) and communities of trees (right) (Photos by Dan L. Perlman, http://ecolibrary.org).

On a broader scale, the East African climate is largely controlled by the seasonal north-south

migration of the Intertropical Convergence Zone (ITCZ), which is associated with the

changing zenith position of the sun. As such, the ICTZ shifts northward during Northern

Hemisphere’s summer whereas the opposite movement occurs during Southern

Hemisphere’s summer (Figure 5A). This results in a bimodal rainfall pattern for tropical East

Africa, including Lake Challa, as Indian Ocean monsoonal winds bring precipitation to East

Africa twice per year (Figure 5B). The so called ‘long’ rains are produced by the southeasterly

monsoon from March to May/June and are responsible for the main amount of

precipitation, whereas the more variable ‘short’ rains, produced by the northeasterly

monsoon, are predominantly present from October to December (Figure 5A) (Nicholson,

1996). Both rainy seasons are separated by pronounced dry seasons in January – February

and mid-May through October (Figure 5B). The lowest mean daytime temperatures

(app. 26°C) occur during southern hemisphere winter (June – August), whereas the highest

temperatures (app. 30°C) occur during southern hemisphere summer (November – March).

In contrast to the temperature, seasonal wind speeds show the opposite pattern, with

weaker northeasterly trade winds prevailing from November to April and stronger

southeasterly winds from May to October when the ITCZ is displaced northward (Figure 5A)

(Kristen, 2010).


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Figure 5: A) Seasonal migration of the Intertropical Convergence Zone (ITCZ) over East Africa, including Lake Challa (yellow dot), for four representative months. Monthly precipitation (shaded green, contours at 50 mm intervals) is based on rain gauge data over land and satellite precipitation estimates over sea. Wind directions for the 925 hPa pressure level are indicated with arrows, whereas wind speeds are proportional to the arrow length. Weaker northeastern monsoonal winds are visible in January, whereas stronger southeastern monsoonal winds are observed in August (http://iridl.ldeo.columbia.edu, from Verschuren et al., 2009). B) Climatogram for Lake Challa and its surroundings. Monthly rainfall data for Taveta (1978-2005, n = 20, 7 km southwest of Lake Challa); monthly rainfall data and minimum, maximum and daily surface air temperatures for Voi (1957-2007, n = 51, 90 km east of Lake Challa) (modified from Verschuren et al., 2009).

Chapter 3 – Materials and methods

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3 MATERIALS AND METHODS

In order to gain a better understanding of the modern-day source to sink processes of

lacustrine deposits preserved in Lake Challa, three different sources of sedimentary material

were investigated: onshore samples, short cores and surface sediment samples. In this

chapter these three groups are introduced and the different methods that were applied on

each of them are explained.

3.1 Onshore samples

3.1.1 Sample acquisition

During two field campaigns in 2006 and 2010 multiple sediment samples originating from

several locations around Lake Challa and in its further catchment were retrieved.

Twenty-nine samples (called ‘Potsdam samples’ in the following) were obtained in

September 2006 by Kristen (2010), whereas the remaining thirty-seven samples (called

‘Utrecht samples’ in the following) were obtained in late January and early February 2010 by

the University of Utrecht (Buckles et al., 2014). Consequently, sixty-six onshore samples

were obtained and these are available to be investigated within this research (Appendix A).

As described by Kristen (2010), the ‘Potsdam samples’ consists of various surficial soil

samples that were randomly collected from grits and ditches, in addition to some volcanic

and metamorphic pebbles and rocks (e.g. basalts and gneisses). Three sampling locations

have been sampled twice, once for a pure rock sample and once for a corresponding soil

sample surrounding the rock (Appendix A). According to Buckles et al. (2014), the ‘Utrecht

samples’ purely consists of surficial soil samples that are further categorised as either red

(lateritic1) or grey (volcanic) types. The samples were retrieved from the lakeshore (L),

the crater rim (C), the hinterland (H), a small ravine in the NW corner of the lake (R) or from

combinations of these origins (Appendix A). They were randomly sampled from the 0 – 10

cm depth interval using a trowel, after removal of vegetation and litter (Buckles et al., 2014).

3.1.2 Grain-size measurements

As it is meaningless to determine grain-size distributions for rock samples or similar,

a sample selection has been done beforehand. As a consequence, ten samples out of

the twenty-nine ‘Potsdam samples’ were excluded for grain-size analysis as they represent

basalts, gneisses or other rocks (Appendix A). On the other hand, all thirty-seven ‘Utrecht

samples’ were retained for grain-size analysis as they consisted of fine-grained particles.

Grain-size measurements were executed for the remaining fifty-six samples (Figure 6) using

a Malvern Mastersizer 3000 at the University of Ghent (Laboratory for Sedimentology).

1 Rich in iron and aluminium, commonly originating in hot and wet tropical areas.


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Figure 6: Satellite images of Lake Challa (zoom) and its surrounding landscape, showing the spatial distribution of the three different sources of sedimentary material. The peculiar positioning of onshore samples LBK77, LBK78 and LBK81 within the lake instead of on the lakeshore is due to inaccurate GPS measurements. The yellow line represents the border between Kenya (E) and Tanzania (W) (source: Google Earth).

Prior to measuring, the terrigenous fraction was isolated first in three steps by successively

removing fine- and coarse-grained organic matter, carbonates and biogenic silica. Fine- and

coarse-grained organic matter was removed using loss-on-ignition (LOI; Heiri et al., 2001),

whereas carbonates and biogenic silica were dissolved by treating the samples (20 – 75 mg

in 10 ml DI water) with HCl (1 ml, 10%) and NaOH (1 ml, 2N) respectively.

These two chemical reactions were sped up by boiling the mixture for a few minutes on a

hot plate at 200°C. Finally, prior to analysis, 1 ml sodium hexametaphosphate ([NaPO3]6, 2%)

was added to the boiling mixture to ensure complete disintegration of particle aggregates.

Shortly after cooling, all fifty-six samples were successively inserted into the Malvern

Mastersizer 3000, using a Hydro Volume. The instrument measures grain-size distributions

based on the principle of laser diffraction. As a red and blue laser beam are propagating

through the dispersed sample in the sample measurement cell, they are being scattered due

to the interaction with a particle (Figure 7). As the red laser has a larger wavelength

(633 nm), it has difficulties in detecting the finer fraction. To solve this problem, a blue laser

(470 nm) is added for the more accurate detection of finer particles. Also, larger particles

scatter light at small diffraction angles, whereas smaller particles scatter light at large

diffraction angles. Diffracted rays are eventually detected by different detectors (Figure 7).


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Figure 7: The principle of laser diffraction, as occurring in the Malvern Mastersizer 3000. The red and blue laser pathways are shown, as well as the different detectors.

The angular variation in intensity of both scattered beams is measured and the scattering

pattern is afterwards converted to grain-size distributions ranging from 0.01 – 3500 µm.

Each sample was measured six to nine times, using the standard operating procedure (SOP2)

of S. Bertrand, in order to prevent random operator errors and to ensure reproducibility and

accuracy of the measurements. Finally, the Malvern Mastersizer 3000 data were exported

and subsequently used to calculate numerous descriptive grain-size distribution statistics

(e.g. mean, median, %sand, %silt,…) with the Excel macro-program GRADISTAT Version 8.0

(Blott and Pye, 2001), using the Folk and Ward graphical method (Folk and Ward, 1957).

3.1.3 Quantitative X-ray diffraction

The purpose of quantitative XRD (QXRD) analysis is to determine relative weight fractions for

every mineral phase present in a sample. In this study, twenty-six ‘Utrecht samples’ and

fourteen ‘Potsdam samples’ were carefully selected for quantitative analysis (Chapter 4,

Appendix E). The selection procedure was based on the sample location as well as on the

sample description. As such, distant samples and a few nearly coinciding samples were

excluded, based on their description. Similar to the grain-size measurements,

the terrigenous fraction was isolated in a first treatment phase by successively removing all

fine- and coarse grained organic matter and carbonates using the LOI procedure of Heiri et

al. (2001). In addition, four Potsdam samples were excluded from this procedure as they

consist of pure rocky material, which contains no organic matter or carbonates (Appendix E).

2 Measurement duration: 12 s, stirrer speed: 2500 RPM, ultrasonic sound: 10% of maximum power.


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In a second treatment phase, the coarse terrigenous fraction was converted to a perfect

powder sample in several extensive steps. In a perfect powder sample, all crystals are

randomly oriented and of sufficiently small size (< 10 µm). As a consequence, every atomic

plane in a crystal has an equal chance of producing a diffraction maximum compared to the

other atomic planes. To assure a complete random orientation of all particles in a powder

when packed in an XRD sample holder, all samples were spray-dried as this approach has

proven to be best technique and results in highly reproducible data (Hillier, 1999; Kleeberg

et al., 2008). Thus for spray-drying, a slurry suspension of finely ground material is necessary,

as it will result in the formation and randomly packing of very fine spherical aggregates.

In a first step, the sample’s crystal size was reduced by crushing them in a Pulverisette,

so that it passes a 50 µm sieve. Secondly, the crushed sample was transferred to a McCrone

micronizing mill, where 7 ml of ethanol was added as a grinding fluid. After milling for three

minutes, the obtained slurry suspension was poured into a centrifuge tube in a third step

and then centrifuged at 2600 RPM for six minutes. After decanting the clear supernatant,

a small amount of ethanol (1 ml) was added again to obtain a slightly viscous slurry

suspension. Fourthly, this slurry suspension was poured into an airbrush jar and spray-dried

at 10-15 psi in an oven operated at 50°C (Hillier, 1999). In a final step, the spray-dried

powder was recovered at the bottom of the oven on a large paper and subsequently poured

in an XRD sample holder. The sample was then evenly distributed across the cavity, after

which any excess of material was removed using a razor blade.

Prior to milling, 5 wt% (0.1 g) of zincite (ZnO) was added as an internal standard for

quantitative XRD analysis to every spray-dried sample. The powder XRD patterns were

collected on a Bruker D8 ECO Advance system at the University of Ghent (Laboratory for

Mineralogy and Petrology). The machine is equipped with a Cu tube anode, an energy-

dispersive position-sensitive LynxEye XE detector and a 6x15 positions automated sample

changer. The incident beam was automatically collimated to an irradiated length of 17 mm.

The Cu tube was operated at 40 kV and 25 mA, and the patterns were collected in a θ-2θ

geometry from 3.00° 2θ onwards with a step size of 0.010° 2θ, and a count time of 48

seconds per step. Eventually, the obtained XRD patterns were interpreted qualitatively using

the DIFFRAC.EVA software and the COD database (Gražulis et al., 2009; Gražulis et al., 2012)

for reference patterns, and quantitatively using the BGMN Rietveld model (Bergmann et al.,

1998) and Profex (Doebelin and Kleeberg, 2015) as user interface.

Ideally, the measured wt%’s of the internal standard (i.e. zincite) should be (near to)

identical to the wt% that was added prior to analysis (5%). As will be discussed in Chapter 5

however, this is rarely the case as the wt%’s of zincite are varying between 5.02 and 10.43%

(Appendix E). This deviation (i.e. 0.02 – 5.43%) can arise by several reasons. For example,

minor mineral phases might have been missed during the quantitative analysis in Profex,

which results in the stretching of the other phases’ wt%’s to 100% and as such yields higher

wt%’s for the internal standard. Another plausible reason is the presence of amorphous


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material3, which scatters X-rays in many directions leading to one or more ranges with

increased background intensity instead of high intensity narrower peaks (Cullity, 1956).

These ‘humps’ in the background are fitted during the Rietveld refinement, but not

considered in the obtained weight percentage for the crystalline phases, which are always

scaled to 100%. This also results in wt%’s that are deviating from the ideal situation,

i.e. where no amorphous material is present. The amount of amorphous material can be

estimated by rescaling the obtained wt%’s using the known amount of the internal standard.

This rescaling is performed by multiplying each wt% by S/S’, where S is the known wt%

of zincite (5%) and S’ the obtained wt% of zincite (Appendix E, column 2). The amorphous

content is then calculated as follows: 100% * (1 - S/S’) (Appendix E, column 15).

Since the precision of quantitative X-ray analysis is not very high (deviations of at least a few

wt%’s are expected as repeatedly shown by international round-robin competitions (Madsen

et al., 2001; Omotoso et al., 2006; Ottner et al., 2000), the amorphous content must be

treated as a very rough estimation. The internal standard and amorphous material are not of

direct interest, so in order to ease comparison between the crystalline fraction of samples,

these were dropped from Appendix E and the remaining wt%’s are rescaled to 100%.

(Chapter 5, Table 1).

3.2 Short cores


To investigate lateral changes in sedimentological and geophysical properties of lacustrine

deposits of Lake Challa, five short cores of 19 to 36.2 cm length were retrieved with a

UWITEC gravity corer during a coring campaign in February 2005 by Kristen (2010).

They were taken along a horizontal transect from water depths ranging from 90 m near the

centre of the lake to 61 m near the shoreline of the northeastern crater rim (Appendix C.2,

Figure 6).

3.2.2 Core opening, core photography and macroscopic core description

At the University of Ghent (Geotek laboratory) the short cores were opened, photographed

and afterwards macroscopically described. Immediate imaging is necessary since rapid

oxidation of the sediment might occur, resulting in colour changes. The photographs were

taken by the Geotek GEOSCAN IV line scan camera, which is part of the Geotek Multi-Sensor

Core Logger (Figure 8). Afterwards, a virtual ruler was added onto the Geotek core images

using the Add Ruler v1.3 software. These precise depth-registered core images enable inter-

core comparison and are thus useful when describing the core.

3 Non-crystalline solids in which atoms and molecules are not organized in a definite lattice pattern e.g. glass.


15

3.2.3 Multi-Sensor Core Logging

In order to obtain a high-resolution, downcore data set of the magnetic susceptibility (MS),

all short cores were scanned with a Geotek Multi-Sensor Core Logger (MSCL, Figure 8).

This geophysical property is of interest since changes in MS often correspond with changes

in mineralogy and sedimentary provenance (Loizeau et al., 2003; Maher, 2011).

The magnetic susceptibility was measured with a Bartington MS2E point sensor at a

precision of 10-5 SI. In addition, drift of the MS-sensor was monitored by executing

measurements in air after every 10th reading on the sediments. This drift value was then

automatically subtracted from the MS data by linear interpolation (Nowaczyk, 2001).

All magnetic susceptibility measurements were executed over discrete steps of 0.2 cm along

a central pathway on the core. Prior to analysis, the core halves were wrapped in a

protecting transparent foil since the MS-sensor was set to touch the sediment surface.

Figure 8: General set-up of a standard Multi-Sensor Core Logger (MSCL-S). In this study, only line-scan core imaging and magnetic susceptibility measurements were performed (Kempf, 2016).


After carrying out the above-mentioned non-destructive methods, the sediment was

sampled in order to perform grain-size measurements with the Malvern Mastersizer 3000.

The sampling intervals were carefully selected based on a closer visual study of the core

images in Corel PHOTO-PAINT. The contrast was adjusted for every core image by executing

a histogram equalization, as this facilitated inter-core comparison. Additionally, MS data was


16

superimposed on the core images to highlight zones with higher magnetic susceptibility

values, thus reflecting zones of interest (Chapter 4, Figure 13). Eventually, thirty-seven

sampling intervals from five short cores were selected for grain-size analysis (Figure 13).

As with the onshore samples, the terrigenous fraction was isolated. The samples (± 3 g in 10

ml DI water) were treated with H2O2 (8 ml, 35%) and HCl (3 ml, 10%) at 200°C to remove all

fine-grained organic matter and carbonates respectively. The removal of biogenic silica

(mostly diatoms), could not be established by the standard NaOH (1 ml, 2N) treatment, since

not all diatoms were dissolved. As suggested by Madella et al. (1998), the use of a non-toxic

heavy liquid is preferred for the extraction of diatoms. In this research sodium polytungstate

(Na6(H2W12O40)H2O) is used as heavy liquid with a varying density of 1.0 – 3.1 g/cm3.

The dense solution was diluted to 1.9 g/cm3, as this density was favourable for the

separation of the lighter diatoms (< 1.9 g/cm3) from the heavier clastic particles

(> 1.9 g/cm3).

Prior to the heavy liquid procedure, the fine fraction (< 4 µm) was separated first from the

coarse fraction (> 4 µm) by means of gravity sedimentation based on Stokes law4.

This was established by decanting the fine fraction four times with a time interval of 118

minutes between each decantation. Subsequently, this fraction was left to settle, whereas

the coarse fraction was used in the above-mentioned heavy liquid procedure. The separation

of clays is essential as a high concentration of these particles can obscure the mixture during

the heavy liquid process, leading to an insufficient extraction of diatoms (Madella et al.,

1998). At the end of the procedure, the clay fraction was again combined with the coarse

clastic fraction.

Finally, after adding 1 ml [NaPO3]6 (2%) to the samples, all thirty-seven samples were

successively inserted into the Malvern Mastersizer 3000 until the laser obscuration values

were in range (5 – 20%). Six measurements were performed for every sample, whereafter

the grain-size distributions were averaged and analysed with GRADISTAT Version 8.0

(Blott and Pye, 2001).

3.3 Surface samples


In addition to the above-mentioned Utrecht samples (section 3.1.1), nineteen profundal5

surface sediments were collected during the same field campaign in late January 2010

(Buckles et al., 2014). The sediments were recovered with intact sediment-water interfaces

4 v = g *D² * (density particle – density fluid) / (18 * viscosity), with g = 9.81 m/s² and D = particle size in µm.

5 Area of a lake that is located below the zone of effective light penetration, typically below the thermocline.


17

from water depths ranging from 32.8 to 91.6 m using an UWITEC gravity corer (Appendix D,

Figure 6). In this research the 2-5 cm depth interval samples are investigated.


As described before, the terrigenous fraction was isolated first by treating the samples

(± 2 g in 10 ml DI water) with H2O2 and HCl at 200°C. Due to a high concentration of bacteria

in the samples, a higher amount of H2O2 was added. The dissolution of bacteria is essential

since sediment particles were captivated within the bacteria frustules. As with the short core

samples, diatoms were removed by performing the heavy liquid procedure explained in

section 3.2.4. Afterwards, 1 ml [NaPO3]6 (2%) was added to the samples and subsequently

grain-size distributions were obtained using the Malvern Mastersizer 3000 and analysed with

GRADISTAT Version 8.0 (Blott and Pye, 2001).


All nineteen surface sediment samples were initially selected for quantitative XRD analysis.

Prior measurement, the terrigenous fraction was isolated first using LOI (Heiri et al., 2001).

Since 0.1 gram (5 wt%) of zincite (ZnO) is added as an internal standard to every sample, at

least two gram of sedimentary material is necessary for quantitative XRD analysis. After LOI

however, only one surface sample (11G) remained, since all the other samples had less than

two gram remaining. Consequently, sample 11G is the only surface sample suitable for

quantitative XRD analysis, as described in section 3.1.3.

Chapter 4 – Results

18

4 RESULTS

In this chapter the results of the grain-size measurements and the mineralogical analysis are

reported in detail for every sedimentary group consecutively. To describe grain-size

distributions, four major grain-size classes of the GRADISTATv8 program of Blott and Pye

(2001) will be used in the following chapters: clay (< 2 µm), silt (2 – 63 µm), sand (63 – 2000

µm) and gravel (2 – 64 mm). Throughout this chapter several figures are shown that will also

be used for the discussion. As such, references to these figures will be regularly used in

Chapter 5.

4.1 Onshore samples


As mentioned in the previous chapter, fifty-six onshore samples (nineteen ‘Potsdam’

and thirty-seven ‘Utrecht’ samples) were suitable for carrying out grain-size analysis

(Appendix A, Figure 6). As it would be too extensive to present all fifty-six grain-size

distributions consecutively, a clustering approach is preferably chosen in this research with

the purpose to find along-shore differences in the grain-size distributions. As such, attempts

are made to group the samples based on their geographic location relative to Lake Challa,

together with a visual observation of every grain-size distribution. Although all fifty-six

samples are classified in various groups, they all have one thing in common, namely that

their grain-size distributions are polymodal and as consequence they are poorly sorted.

Yet, clear differences in the grain-size distributions can still be observed at different

locations around Lake Challa. The spatial distribution of the various onshore groups is shown

in Figure 9. The hereby associated grain-size distributions of every group are presented in

Figure 10A-J and consecutively described in the following paragraphs. Additionally, average

grain-size distributions have been plotted on top of the individual grain-size distributions of

each group separately. In Chapter 5 these groups will be further discussed.

The first group represents the sediments on the southern rim of the crater lake and

comprises the ‘Utrecht samples’ LBK76, LBK75, LBK74, LBK72, J12 and the nearby ‘Potsdam

samples’ 8 and 10 (Figure 9). All these samples are categorized as the ‘Southern group’ and

their corresponding grain-size distributions are plotted in Figure 10A. As indicated in the

figure, two average modes are present at app. 38 and 520 µm. As calculated by

GRADISTATv8, the majority of the sediments in every sample fall within the sand and silt

fraction (≥ 96.3%), with an average percentage of 97.8%. The average percentage of clay is

low, whereas gravel can be neglected (Appendix B).


19

Figure 9: Satellite images of Lake Challa (zoom) and its surrounding landscape. The various proximal and distal onshore groups are indicated by different colours. The peculiar positioning of onshore samples LBK77, LBK78 and LBK81 within the lake instead of on the lakeshore is due to inaccurate GPS measurements. The 300 m small creek on the NW crater rim is indicated by a blue dashed line. The yellow line represents the border between Kenya (E) and Tanzania (W) (source: Google Earth).

The second group is representing the sediments on the eastern rim of the crater lake and

comprises the closely-spaced ‘Utrecht samples’ J01, J02, J03, J04 and samples J05 and J06

(Figure 9). As a consequence, these samples are categorized as the ‘Eastern group’ and the

individual grain-size distributions are shown in Figure 10B. Most of the distributions contain

a low frequency ‘plateau’ in the grain-size range of 10 – 200 µm, except for sample J03 which

shows a clear mode at about 20 µm. Secondly, all grain-size distributions show a high

frequency mode between app. 500 and 700 µm, with an average at app. 650 µm.

The average percentage of sand is higher compared to group 1 (66%, Appendix B). Similar to

group 1, the sediments in group 2 are dominated by sand and silt (≥ 92.6%), with an average

amount of 97.3%. Clay and gravel are again present in low and negligible amounts

respectively (Appendix B).

The third group is a small group that comprises the ‘Utrecht samples’ LBK62, LBK63 and

LBK77. As these are located on the crater rim in the northeastern corner of the lake

(Figure 9), they are categorized as the ‘Northeastern group’. Despite lying relatively close to

the ‘Utrecht samples’ J01, J02, J03, J04 of the previous group, their grain-size distributions

are different (Figure 10C). A ‘plateau’ is again present, this time with a slightly higher

frequency and in the grain-size range of 15 – 100 µm. Further, the average mode of the

higher frequency peak has decreased from 650 to app. 380 µm. Although the grain-size

distribution of sample LBK77 somewhat differs from the other two samples, it is classified in

this group as it lies on the lakeshore between sample LBK62 and LBK63. Therefore, LBK77 is

most likely influenced by both samples. Again, sand and silt are equally dominating the


20

sediments (≥ 92.2%), with an average percentage of 94.8% (Appendix B). Since gravel is

completely absent, the remaining sediments are clays, with an average percentage of 5.21%.

The fourth group is also a small group comprising two ‘Utrecht samples’ LBK64 and LBK65

and ‘Potsdam sample’ 16, located on the northern rim of the crater lake (Figure 9).

The samples are categorized as the ‘Northern group’ and their grain-size distributions are

shown in Figure 10D. Samples LBK64 and LBK65 are similar to each other and different from

the previous group regarding the position of the high frequency mode around app. 580 µm.

No second mode is observed, however a ‘plateau’ is present in the grain-size range of

15 – 170 µm. Despite having a slightly different grain-size distribution, sample 16 is

categorized in this group according to its geographic location north of Lake Challa and

because of the presence of the mode around app. 580 µm. Although samples from the

northern group look similar to the ones of group 2, which have a higher frequency mode

between app. 500 and 700 µm (Figure 10B), they are categorized in a different group since

they are geographically separated up to 2 km. Appendix B shows the recurring dominance of

sand and silt (≥ 95.2%), with an average percentage of 96.3%. Finally, clay and gravel are

present in minor and negligible amounts respectively.

The fifth group only comprises two ‘Utrecht samples’ on the western rim of Lake Challa,

sample LBK70 and LBK71 (Figure 9). The grain-size distributions of these ‘Western group’

samples are shown in Figure 10E and are characterized by a high frequency mode between

app. 400 and 580 µm, with an average at app. 490 µm. Both samples are predominantly

sandy with an average percentage of 74.87%. The remaining sediment is mainly composed

of silt and a small amount of clays, with average values of respectively 23.14 and 1.99%.

In addition, gravel is completely absent (Appendix B).

The sixth group is a large group comprising the ‘Utrecht samples’ LBK68, LBK69, LBK79 and

LBK80 and the nearby located ‘Potsdam samples’ 15b, 19 and 32. All these samples are

located on the northwestern rim of the crater lake in the vicinity (< 200 m) of a 300 m small

creek (Figure 9) and are categorized as the ‘Northwestern creek group’. As illustrated in

Figure 10F, all grain-size distributions show at least two modes: an obvious first one with

varying frequency in the sand fraction between app. 350 and 580 µm (490 µm on average)

and another one in the clay fraction at app. 0,1 µm. Contrary to previous groups, a distinct

mode in the clay fraction is observed, which leads to higher percentages of clay in every

sample (Appendix B). Based on this characteristic, and because of the fact that all samples lie

in the vicinity of the small creek, they are categorized in the same group, although having

different grain-size distributions. Despite the higher percentages of clay, sand and silt remain

the main constituents of the sediment (≥ 66.9%, 80.3% on average), whereas gravel is

completely absent (Appendix B).


21

Figure 10: The various grain-size groups and their corresponding grain-size distributions. Average grain-size distributions are plotted in red and main average modes are indicated by a dashed line.


22

The seventh group is another large group representing the ‘Utrecht samples’ J07, J08, J09,

J10, J11 and LBK67 on the northwestern rim of the crater lake (Figure 9).

Contrary to the previous group, these samples do not lie in the vicinity of the 300 m small

creek and therefore the samples are categorized in a different group, namely the

‘Northwestern group’. The grain-size distributions are shown in Figure 10G. As with the

previous group, a clear mode is present at app. 0.1 µm, again resulting in higher percentages

of clay (Appendix B). On the other hand, a consistent mode in the sand fraction is missing as

the position and frequency of the modes are varying. Although remarkable variations are

visible in the silt and predominantly sand fraction, it makes sense to group these samples as

they were sampled along small streams on the NW crater rim during one field trip (Buckles

et al., 2014). Furthermore, Buckles et al. (2014) described these samples as being ‘Ravine-

Hinterland (RH)’ samples (Appendix A), so a similar origin can be assumed. Appendix B shows

the contribution of the different sedimentary constituents present in every sample.

As always, sand and silt are predominantly present (≥ 75.3%), with an average percentage of

82.3%.

The eighth group comprises the coupled ‘Utrecht samples’ LBK82 & LBK83 and LBK84 &

LBK85 and lies further northwest of Lake Challa (avg. 6.6 km), located closest to

Mt. Kilimanjaro of all onshore groups (Figure 9). As a result, the samples are categorized as

the ‘Mt. Kilimanjaro group’, despite lying a few km apart from each other. The grain-size

distributions shown in Figure 10H are all characterized by an obvious and almost consistent

mode at app. 0.075 µm. In comparison with the two previous groups, the frequency of this

mode is much higher, thus resulting in the highest percentage of clays of all onshore samples

(≤ 43.8%, Appendix B). The mode in the sand fraction is less consistent concerning its

position and frequency, yet it clearly indicates the dominance of sand over silt. The average

amount of gravel can be neglected (Appendix B).

The ninth group comprises the ‘Utrecht samples’ LBK81, LBK78 and the ‘Potsdam samples’

17/18, 20 and 21. As can be derived from Figure 9, these samples are located in different

geographic areas around Lake Challa. Therefore, geographical grouping is not the

appropriate approach. Nonetheless, the samples have two things in common: I) their

location on the lakeshore and II) the presence of a high frequency mode between app. 500

and 850 µm (670 µm on average, Figure 10I). As a consequence, they are being categorized

as the ‘Lakeshore group’. Despite the fact that these samples lie in the vicinity of some

samples of the above-mentioned groups, they are categorized differently due to some

differences in their grain-size distributions (Figure 10I). For example, existing modes have

changed in frequency and/or position or new smaller ones are observed. As with most of the

previous groups, the samples in this group are also mainly composed of sand and silt

(≥ 85.5%, 92.2% on average) with only a minor percentage of clays. The average percentage

of gravel is slightly higher, but still in practically negligible amounts (Appendix B).


23

The tenth and final group concerning the onshore samples, comprises the ‘Potsdam

samples’ 38, 39, 209 and 210b that are lying in the hinterland app. 3 to 8.5 km north- to

southeast of Lake Challa (Figure 9). The samples are categorized as the ‘Hinterland group’.

Despite some differences in their grain-size distributions, two modes can be distinguished:

one in the clay fraction between app. 0.07 and 0.1 µm (0.9 µm on average) and one in the

sand fraction between app. 200 and 500 µm (310 µm on average, Figure 10J). Similar to

group 8, a much higher percentage of clay (≤ 38.6%) is present in every sample, next to

predominantly sand particles. The remaining particles are mainly silt, since the average

percentage of gravel lies close to zero (Appendix B).

Figure 10 (cont.): The various grain-size groups and their corresponding grain-size distributions. Average grain-

size distributions are plotted in red and main average modes are indicated by a dashed line


24

The remaining ‘Utrecht samples’ LBK61, LBK66, LBK73 and ‘Potsdam samples’ 23, 24, 25,

27b, 40 and 41 are not categorized in any of the above-mentioned groups (Figure 9).

Firstly, the three ‘Utrecht samples’ are excluded because their grain-size distributions do not

match with the others in their respective geographic areas (i.e. group 5, 7 and 1).

The six ‘Potsdam samples’ are excluded for two reasons: firstly, the samples are lying further

away from each other and from Lake Challa (up to app. 64 km for sample 41), which makes

the grouping approach less appropriate. Secondly, all samples are mainly composed of

coarser material (sand and gravel) and in combination with the large offset to Lake Challa;

it is less likely that these particles leave a major trace behind on the lacustrine sediments,

since they need to be transported over greater distances by e.g. monsoonal winds.

To conclude, these samples will not be discussed anymore in Chapter 5.


As mentioned in section 3.1.3, forty onshore samples (twenty-six ‘Utrecht’ and fourteen

‘Potsdam samples’) were carefully selected for quantitative X-ray diffraction analysis.

The obtained raw weight percentages (wt%’s) of the different minerals present in every

sample are shown in Appendix E, whereas the final, rescaled wt%’s of the crystalline

fraction (i.e. without amorphous content and internal standard) are shown in Table 1.

A brief explanation of every mineral/mineral group is given in Appendix F.

Similar to the grain-size measurements, it would be cumbersome to discuss the quantitative

XRD results of all forty onshore samples separately. A hierarchical cluster analysis was

instead performed on the weight percentages obtained via QXRD analysis (Table 1) and LOI

at 550°C and 950°C. For every mineral phase, the weight percentages were first normalized

by dividing each value by the standard deviation of the entire dataset. Afterwards,

the cluster analysis was performed using a Ward variance minimization algorithm

(Ward, 1963) as implemented in SciPy v0.16.1 (Jones et al., 2001). The final result of this

process is a XRD dendrogram (Figure 11). Based on the visual inspection of this dendrogram,

a cut-off distance (d) was chosen in order to select and define various clusters. In this case,

a cut-off distance of 7 was selected, resulting in a total of seven clusters (Figure 11).

The spatial distribution of these clusters is shown in Figure 12 and each cluster will be briefly

described in the paragraphs below.


25

Figure 11: XRD dendrogram of forty onshore and one surface sample. The black lines represent the hierarchical clustering of the data. The red line indicates a cut-off distance of 7, resulting in seven clusters that are indicated by different colours below the red line.

Figure 12: Satellite images of Lake Challa (zoom), showing the spatial distribution of the different XRD clusters in colours matching those in the dendrogram (Figure 11). The peculiar positioning of onshore samples LBK78 and LBK81 within the lake instead of on the lakeshore is due to inaccurate GPS measurements. The 300 m small creek on the NW crater rim is indicated by a blue dashed line. The yellow line represents the border between Kenya (E) and Tanzania (W) (source: Google Earth).


26

The first cluster comprises onshore samples 9, 13 and 22 (Figure 11, Table 1). These three

samples are three of the four rock samples that were excluded from the LOI procedure

(see section 3.1.3). Despite lying in different areas around Lake Challa (Figure 12),

the crystalline fraction is mainly characterized by a very high amount of pyroxenes.

Moreover, feldspathoids only occur in these three samples and the amount of hematite is

among the lowest of all samples. Pseudobrookite, cristobalite and carbonates are

completely absent. Remarkably, sample 22 contains a much higher percentage of carbonates

compared to the other two samples and in addition to all the other XRD samples (Table 1)

According to the BGMN Rietveld model of Bergmann et al. (1998), this is due to the presence

of variable calcite. As personally communicated by M. Dumon (Department of Geology,

Ghent University), this represents calcite with multiple Mg-for-Ca substitutions, although not

enough to be a dolomite. Because of the volcanic nature of the sediments around Lake

Challa, these substitutions are not remarkable. Since sample 22 is the only sample where

these high amounts of carbonates are observed, it should be treated with caution.

The second cluster consists of onshore samples J12, 10 and LBK73 (Figure 11, Table 1).

They are located on the southwestern crater rim of Lake Challa (Figure 12).

They predominantly consist of pyroxenes and hematite and have the highest amounts of

forsterite of all samples. Unheated sample 9 - although lying close to the other three

samples and being the sample with the 4th highest amount of forsterite - is not included in

this cluster.

The third cluster comprises onshore samples 21, 20, J01, LBK81, LBK78, 17/18 and J06

(Figure 11, Table 1). All of these samples are located on the lakeshore (Figure 12) and are

characterized by containing ‘higher’ amounts of accessory minerals compared to the other

samples. Yet, the percentages for these accessories are mostly low in comparison to the

predominantly present pyroxenes, plagioclases and hematite.

The fourth cluster only consists of onshore sample 208 (Figure 11, Table 1), being the fourth

rock sample that was excluded from the LOI procedure. Although located in the vicinity of

sample 22 (part of cluster 1, containing the other rock samples - Figure 12), sample 208

contains much more plagioclases than pyroxenes. Contrary to the other unheated samples

of the first cluster, cristobalite and carbonates are present whereas feldspathoids are

completely absent. Similarly, pseudobrookite is completely absent while the amount of

hematite is again among the lowest.

The fifth cluster is the largest cluster comprising onshore samples LBK71, LBK66, LBK70,

LBK63, LBK79, 15b, J04, 16, LBK76, LBK62, LBK64, 19, LBK67, LBK65 and LBK75 (Figure 11,

Table 1). All samples are scattered along the crater rim (Figure 12). As this cluster is centrally

positioned in the dendrogram, the wt%’s of the different mineral phases are differing the

least from the overall average wt%’s (Table 1). Yet, minor variations in the mineralogical


27

composition of a few samples can be witnessed. For example, samples LBK63, LBK64, LBK75

and LBK76 contain higher amounts of forsterite than the overall average (Table 1), whereas

samples LBK70 and LBK71 have the highest amount of hornblende of all samples. Hematite,

pyroxenes and plagioclases are predominantly present, while the remaining mineral phases

are present in low, but varying amounts.

The sixth cluster comprises onshore samples 39, 209 and LBK85 (Figure 11, Table 1).

They are distally located east and west of Lake Challa (Figure 12) and are the only samples

containing a high amount of quartz. Compared to the previous clusters, pyroxenes and

plagioclases are present in lower amounts, whereas hematite is abundantly present.

The seventh and final cluster consists of onshore samples LBK68, LBK82, J07, J09, J08, J10,

32 and LBK69 (Figure 11, Table 1). They are located on the northwestern crater rim, except

sample LBK82 which lies further northwest (Figure 12), and are characterized by containing

the highest amounts of pseudobrookite and cristobalite. Moreover, the wt%’s of hematite

are also among the ten highest, except for sample 32. On the other hand, the wt%’s of

forsterite, pyroxenes and plagioclases are among the lowest of all samples. Despite lying in

the vicinity of some of the above-mentioned samples, samples 15b, 19 and LBK79 are not

included in this group. The only surface sample (11G) is also added to this group, as will be

explained in section 4.3.2.


28

Table 1: Weight percentages (wt%’s) of the different minerals present in forty onshore and one surface sample. All minerals and their abbreviations are listed in Appendix F.

Cluster Sample Psb (%) Qz (%) Crs (%) Fspt (%) Fo (%) Hbl (%) Px (%) Ms (%) Pl (%) Hem (%) Cbs (%) Acc (%)

1

9* - - - 10,65 18,17 - 57,91 7,58 - 5,40 - 0,29

13* - 1,41 - 3,86 7,56 3,40 45,92 4,51 23,46 9,89 - -

22* - 5,46 - 4,31 7,17 2,87 43,19 1,43 9,90 3,86 21,27 0,53

2 J12 5,78 1,23 5,50 - 18,57 - 37,44 - 7,58 23,90 - -

10 4,60 1,23 5,08 - 19,22 - 34,80 3,46 9,28 22,34 - -

LKB73 5,18 1,64 7,09 - 25,21 - 29,01 1,68 7,28 22,91 - -

3

21 2,76 6,64 - - 4,35 4,57 19,62 0,74 35,53 12,60 - 13,18

20 3,14 4,54 - - 4,45 3,63 31,93 3,21 23,82 19,09 0,87 5,34

J01 4,10 3,46 - - 6,34 2,74 27,04 3,49 18,42 30,01 1,10 3,31

LKB81 2,54 3,54 - - 5,63 2,96 32,82 2,68 24,33 22,52 0,71 2,27

LKB78 5,62 5,26 - - 3,27 4,68 24,54 - 21,48 31,46 0,62 3,07

17/18 4,39 4,06 - - 4,06 3,13 30,40 1,80 16,49 26,81 1,55 7,32

J06 2,73 4,33 - - 5,07 5,15 30,22 3,79 17,73 20,54 2,12 8,31

4 208* - - 8,18 - 2,75 2,56 18,58 4,54 49,47 9,29 2,19 2,45

5

LKB71 2,48 1,77 - - 7,09 12,55 22,44 6,18 23,38 24,11 - -

LKB66 2,42 4,10 - - 6,60 8,94 19,62 2,80 24,27 28,00 2,74 0,51

LKB70 2,71 4,03 - - 6,67 9,57 17,71 1,48 28,70 25,80 2,52 0,81

LKB63 4,87 4,34 1,41 - 13,36 5,53 18,07 5,91 17,67 25,50 1,74 1,59

LKB79 5,98 4,59 2,19 - 9,24 2,18 15,89 3,43 18,99 31,03 2,51 3,98

15b 5,28 1,79 1,45 - 9,48 3,45 17,93 4,43 18,75 34,39 3,05 -

J04 4,40 4,31 - - 8,20 3,55 19,76 2,52 21,55 29,66 2,83 3,22

16 3,13 2,04 - - 9,21 4,59 25,12 2,38 26,58 25,48 1,47 -

LKB76 4,58 2,59 1,57 - 14,68 2,60 25,01 2,26 19,23 27,47 - -

LKB62 4,56 6,39 - - 9,12 4,71 24,95 2,13 18,70 27,84 0,80 0,80

LKB64 5,75 4,30 - - 12,43 2,83 21,20 1,57 21,75 26,73 0,75 2,70

19 6,61 4,75 6,67 - 6,33 1,75 20,17 2,63 14,68 33,23 1,49 1,70

LKB67 5,90 5,81 2,68 - 7,55 2,07 20,55 2,15 11,64 39,84 0,95 0,86

LKB65 4,40 2,66 0,91 - 8,66 1,55 31,33 2,50 15,12 30,19 2,02 0,67

LKB75 4,79 2,65 2,74 - 14,94 - 29,65 3,16 14,44 24,43 1,12 2,07

6 39 7,36 19,23 11,83 - 1,16 - 10,02 2,34 6,88 35,20 3,17 2,81

209 7,49 19,38 1,85 - 5,25 - 9,91 - 8,53 45,02 - 2,56 LKB85 6,55 20,90 2,25 - 7,42 1,71 13,36 - 6,63 39,03 0,35 1,80

7

11G 8,82 3,81 11,72 - 0,45 - 5,40 - 11,96 39,81 5,68 12,35 LKB68 12,29 8,81 3,12 - 6,50 - 11,68 - 6,52 47,45 0,73 2,90 LKB82 8,94 6,81 2,31 - 1,88 - 7,18 2,79 2,73 63,48 0,19 3,70

J07 11,35 7,87 11,91 - 1,96 - 5,63 - 6,30 53,28 0,83 0,87 J09 14,06 7,07 8,99 - - - 10,39 - 3,69 52,64 0,73 2,44 J08 11,13 6,42 10,21 - 1,85 - 6,91 3,85 4,54 50,51 2,39 2,20 J10 12,30 8,40 7,95 - 1,99 - 6,95 2,95 4,17 50,49 2,26 2,55 32 9,17 8,71 10,27 - 5,87 - 10,19 - 13,29 36,99 2,68 2,82

LKB69 8,89 4,23 9,42 - 6,46 1,95 13,07 1,17 9,95 40,96 2,01 1,89

Overall average 5,45 5,34 3,27 0,45 7,53 2,51 22,28 2,32 15,84 30,13 2,01 3,39

* Pure rock samples, excluded from the LOI procedure


29

4.2 Short cores


Figure 13 indicates thirty-seven sampling intervals, taken from five short cores in the

northeastern part of Lake Challa (Figure 6), that were selected for grain-size analysis.

The corresponding grain-size distributions of each interval are presented in Figure 14A-E for

every core separately. The average grain-size distribution of every core has been plotted on

top of it and all distributions, except the one of G12, clearly show the presence of a high and

broad frequency mode between app. 6 and 10 µm, accompanied by one and two low

frequency mode(s) in the clay and sand fraction respectively (Figure 14A-D). The frequency

of the main mode decreases from the centre (core G9) towards the shoreline (core G11),

whereas the frequencies of the smaller modes in the sand fraction increase along the same

transect (Figure 14A-D). As indicated in Appendix C.1, intervals with higher percentages of

sand or clay can be observed in every core. Appendix .2 shows the average amounts of clay,

silt, sand and gravel for every core. Sand and silt are clearly dominant and their percentages

show an opposite trend along the transect from core G12 to core G9, whereas those for clay

remain relatively low for every core (≤ 7.99%).

4.2.2 Multi-Sensor Core Logging

The patterns of magnetic susceptibility (MS) of the five short cores are shown in Figure 13.

A first remarkable observation regards the presence of two intervals with clearly elevated

MS values in every core except G9, which generally has very low MS values and only contains

one clear MS elevation at a core depth of approximately 35 – 36 cm. Secondly, elevated MS

intervals seem to occur in darker coloured zones (i.e. blueish intervals) at different core

depths, whereas lower MS values are occurring in brighter coloured zones (i.e. yellowish

intervals) that are located between the darker zones. These differences could possibly be

allocated to changes in sedimentological and/or mineralogical composition. A third and very

remarkable observation concerns the up to ten times higher MS values of core G12, which

could be related to its proximal location to the shore (Figure 13). The reason for the nearly

ten-fold drop in MS between core G12 and G11 (Figure 13) on the other hand,

is unexplainable so far since no quantitative XRD analyses were executed on the short cores.

Concerning the first two observations about the elevated MS values, the general relation

between MS and grain size, i.e. higher MS values for coarser-grained clastic sediments and

vice versa (Loizeau et al., 2003; Maher, 2011), was investigated. However, this relation

was fairly unsatisfying as elevated MS values also occurred in some finer-grained intervals

or even in intervals with neither more coarse or fine-grained material (Figure 13 vs.

Appendix C.1). As this downcore investigation also diverges from the main objectives of this

thesis, no further words on the magnetic susceptibility will be spent in the discussion.


30

Figure 13: Short core images taken by the Geotek GEOSCAN IV line scan camera (Figure 8) and afterwards adjusted by performing a histogram equalization in Corel PHOTO-PAINT. Magnetic susceptibility data is superimposed on the core images (red curves) and the various sampling intervals for grain-size analysis (i.e. thirty-seven) are indicated by orange lines.


31

Figure 14: A-E) Grain-size distributions of each interval within every short core (black curves). Average grain-size distributions are superimposed in red and the main average mode is indicated by a dashed line. F) Location of the short cores near the northeastern corner of Lake Challa. Depth contours (Moernaut et al., 2010) are drawn at 10 m intervals to 90 m depth and at 94 m depth.


32

4.3 Surface samples


As mentioned in Chapter 3, grain-size analyses were executed on nineteen profundal surface

sediments, retrieved from various depths and locations across Lake Challa (Figure 15A,

Appendix D). Contrary to the onshore samples, a clustering approach based on geographical

and/or sedimentological similarities is less appropriate here for two reasons: I) the coverage

of the lakes surface is unsatisfactory as the northern and southern part are not or barely

sampled (Figure 15A) and II) neither one grain-size distribution looks similar, as a wide range

of grain sizes is observed in every sample (Figure 15B). Yet, a broader high frequency mode

around 10 µm can again be seen in seventeen of the nineteen samples. As derived from

Appendix D, sand and silt are dominantly present in all the samples. The amount of clay

remains generally low (≤ 7.8%), except for four samples that are located in the northwestern

corner of the lake (Appendix D, Figure 15A). As always, gravel is not or barely found in these

surface samples.


As mentioned in section 3.3.3, unfortunately only one surface sample (11G) was selected for

quantitative XRD analysis. The obtained raw and rescaled weight percentages (wt%’s) of the

different minerals present in the sample are given in Appendix E and Table 1 respectively.

The sample lies in the NW corner of Lake Challa and is clustered with the onshore samples

on the northwestern crater rim (Figure 11, 7th cluster). It contains higher amounts of

pseudobrookite, cristobalite and hematite and lower amounts of forsterite, pyroxenes and

plagioclases. Additionally, higher amounts of carbonates and accessory minerals are also

present (Table 1).


33

Figure 15: A) Location of nineteen surface sediment samples in Lake Challa. Depth contours (Moernaut et al., 2010) are drawn at 10 m intervals to 90 m depth and at 94 m depth. B) Corresponding nineteen grain-size distributions. Four distributions clearly show a higher frequency in the clay fraction below 0.4 µm.

Chapter 5 – Discussion

34

5 DISCUSSION

5.1 Controls on sedimentological properties

5.1.1 Onshore grain-size distributions and their spatial variations

In the previous chapter, fifty-six onshore samples were clustered into ten groups, each

representing a distinct area around Lake Challa or in its further catchment (Figure 9).

Although being spatially and sedimentologically different, the average grain-size

distributions of all groups are polymodal as they appear to consist of multiple sub

populations (Figure 10A-J). This polymodality is explained by the fact that clastic particles

often represent a mixture of material from different sources and/or from different transport

mechanisms (Holz et al., 2007). This explains the wider range of grain sizes in both the

‘Potsdam’ and the ‘Utrecht’ samples, as they were simply collected from the ground with a

shovel. Still, some remarkable variations were observed in various groups.

A clear mode in the clay fraction at app. 0.1 µm is present in the distal groups

‘Mt. Kilimanjaro’ and ‘Hinterland’ and in the proximal groups on the northwestern crater

rim, i.e. ‘Northwestern creek’ and ‘Northwestern’ (Figure 10F-H, 10J). The reason for the

existence of this clear mode is assumed to be due to fluvial processes. All four samples in the

‘Mt. Kilimanjaro group’ were sampled along two small stream beds (i.e. Lowari and

Lamsanga) that are most likely formed due to precipitation and melt water transport on the

southeastern slopes of the volcano (Buckles et al., 2014). During periods of rainfall, finer

eroded material is more easily picked up and transported via run-off processes and

afterwards deposited when the flow strength has decreased. Since the four samples lie

closest to Mt. Kilimanjaro (Figure 9), they are most affected by run-off processes,

consequently resulting in the highest percentage of clays of all onshore samples (43.8%,

Appendix B). A similar reasoning can be assumed for the samples in the ‘Northwestern

creek’ and ‘Northwestern’ group. The former group is affected by the nearby 300 m small

creek (Figure 9), while the latter group was sampled along several small streams (Buckles et

al., 2014). As mentioned in section 2.2, the creek is temporarily active during periods of

heavy rainfall. Moreover, the sampling area of both groups lies closest to Mt. Kilimanjaro

and is thus probably more affected, yet less than the ‘Mt. Kilimanjaro group’, by the

previously mentioned surficial transport (i.e. run-off) of sediment particles originating from

fluvial transport on the flanks of Mt. Kilimanjaro. Finally, the samples of the ‘Hinterland

group’ east of Lake Challa were sampled along a river bed (i.e. Lumi, Figure 16) and from

some ditches. Both sampling locations are again related to fluvial processes, which result in

the transport and subsequent deposition of very fine clay when currents become less strong.


35

Figure 16 shows the comparison of a vegetation map of Sinninghe Damsté et al. (2011) with

a satellite image of Lake Challa and its surrounding landscape. The map shows that areas

west and northwest of the lake are mainly rainfed, which enhances fluvial transport.

The areas north- to southeast of Lake Challa on the other hand, are characterized by drier

open wood-, bush- and grasslands. These type of landscapes favor aeolian transport over

fluvial transport, yet the presence of the nearby Lumi river is suggested as a reason for the

presence of finer clay particles in the samples of the ‘Hinterland’ group (Appendix B,

Figure 16). River beds namely provide an ideal source of fine-grained material, although

more evidence is necessary here. Eventually, both observations east and west of Lake Challa

confirm the previous assumption that fluvial processes are responsible for the presence of

the app. 0.1 µm mode in the clay fraction in all four groups.

Figure 16: Comparison of a vegetation map of Lake Challa and its surrounding landscape (Sinninghe Damsté et al., 2011) with a satellite image of the same area (source: Google Earth) with the purpose to pinpoint various source areas and define different transport processes. The four onshore groups discussed in the paragraph above are indicated in colours matching those of Figure 9.


36

The remaining six groups (i.e. ‘Southern’, ‘Eastern’, ‘Northeastern’, ‘Northern’, ‘Western’ and

‘Lakeshore’, Figure 9), do not or barely contain clay particles of app. 0.1 µm (Figure 10A-E,

10I). Yet, they do contain a minor amount of larger clay particles (< 2 µm). Two possible

reasons are suggested for these low amounts of clay: I) the absence of fluvial systems

(e.g. rivers, ditches and creeks) on the northern, eastern and southern crater rim and

II) the finest material is more easily picked up and blown off the crater rim or over the

relatively small lake by strong north- and southeastern monsoonal winds (Nicholson, 1996).

As a consequence, clay particles transported through monsoonal winds are barely deposited

on the crater rim and/or barely settle within the lake itself. This provides a possible

explanation for the generally low percentages of fine clay calculated for the short cores and

surface samples in the eastern part of the lake (section 5.1.2 and 5.1.3).

The ‘Southern’, ‘Eastern’, ‘Northeastern’ and ‘Northern group’ are characterized by a higher

amount of silt (2 – 63 µm) (Appendix B). The average grain-size distributions of the last three

groups show a ‘plateau’ comprising a major part of the silt fraction (i.e. 10 – 63 µm) and

particles smaller than 200 µm (Figure 10B-D), whereas the average grain-size distribution of

the ‘Southern group’ clearly shows a mode at app. 40 µm (Figure 10A). These higher

amounts of mainly coarser silt and very fine sand suggest an input of sediments originating

from nearby north- to southeastern areas around Lake Challa by aeolian processes.

This suggestion is strengthened by looking at the vegetation cover Figure 16. Vast areas of

open wood-, bush- and grasslands are located north- to southeast of Lake Challa and these

types of patchy vegetation allow particles to be lifted up more easily by strong north- and

southeastern monsoonal winds. As a consequence, aeolian transport of silty sediments

towards the crater rim and/or into Lake Challa is facilitated. Moreover, river systems in the

areas east of the lake (Figure 16) provide an ideal source for aeolian material (i.e. dust)

during periods of drought (Washington et al., 2003).

The remaining six groups, lying west to northwest of Lake Challa and on the lakeshore, have

low to moderate percentages of silt (Appendix B). Since these areas are generally wetter and

thus covered by more vegetation than the eastern areas (Figure 16), input of silty particles

from the west by aeolian transport is limited. Yet, silty particles coming from the east might

have been blown in and/or over the lake by strong monsoonal winds during drier periods.

To further strengthen this assumption, additional sampling around Lake Challa should be

executed in the future.

Concerning the coarser sediment fraction (i.e. particles larger than 200 µm) of every onshore

group, no evident conclusions regarding their provenance can be drawn. Since the average

grain sizes are varying between 300 and 700 µm (Figure 10A-I), it is suggested that this

fraction is related to tropical weathering of the original bedrock and erosional processes on

the crater rim.


37

5.1.2 Short core grain-size distributions and inter-core comparison

As mentioned in section 4.2.1, the average grain-size distributions of short cores G9, G10, G7

and G11 are characterized by a dominant mode between app. 6 and 10 µm (Figure 14A-D).

Being located near the northeastern corner of the lake, it is suggested that these short cores

are predominantly influenced by the same provenance. Since the samples of the most

nearby onshore groups, i.e. ‘Eastern’ and ‘Northeastern’ group (Figure 9), also contain

particles within that size range (Figure 10B-C), they can be related to the short cores.

Yet, the high frequency of the dominant mode in the short cores cannot solely be explained

by this similar provenance, as the frequency values of the average grain-size distributions of

both onshore groups in the range 6 to 10 µm are at least half as high as those for the short

cores (Figure 10B-C vs. Figure 14A-D). As such, only a part of the high frequency mode is

assigned to a sedimentary origin. The remaining part is concluded to be the result of the

presence of diatoms in most of the short core samples (Milne, 2007). This conclusion is

evidenced by microscope images of an app. 22 meter long composite core taken in the

centre of Lake Challa, as they have in fact revealed the presence of these organisms

(Tanghe, unpublished Msc thesis). Their presence in both the long core and the five short

cores denotes an insufficient working of the heavy liquid separation method discussed in

Chapter 3. According to Milne (2007), two diatom species are dominantly present in Lake

Challa: I) Nitzschia sp. 1 with a size of app. 10 µm and II) Gomphocymbella sp. 1 with a size

larger than 10 µm. Taking this information into account, it is concluded that the clastic grain-

size distribution signal is overprinted by the diatom signal of Nitzschia sp. 1, which explains

the higher frequency around 6 to 10 µm.

A plausible cause for the different (i.e. coarser) average grain-size distribution of core G12,

and the absence of a dominant 6 to 10 µm mode (Figure 14E), could be its proximal location

to the shoreline (Figure 14F), as it is most influenced by coarser sediments of the ‘Eastern’

and ‘Northeastern’ group. This reasoning is further strengthened by a fining trend that is

observed in the average grain-size distributions along the transect G12 towards G9

(Figure 17). In combination with Appendix C.2, a gradual decrease/increase in the average

percentages of sand and silt respectively is witnessed along that transect. Yet, it needs to be

noted that the frequency of the 6 to 10 µm mode also gradually increases along that same

transect (Figure 14A-D and Figure 17), most presumably indicating a decreasing dilution of

the dominant diatom signal by terrestrial material towards the centre of Lake Challa.

According to the expectations, it can be concluded that more centrally positioned short

cores are less influenced by terrigenous crater rim sediments (i.e. eastern onshore samples

in this case), as such clarifying the diatom signal of Nitzschia sp. 1.


38

Figure 17: Average grain-size distributions of the five short cores near the northeastern corner of Lake Challa. Although difficult to deduce from these distributions, a fining trend is present along the transect G12 to G9 (Appendix C.2).

Next to the presence of the dominant 6 to 10 µm mode in nearly all samples, several

intervals with higher percentages than the average values of sand or clay were observed

downcore in every core (Appendix C.1 vs. Appendix C.2). Yet, reasons for their occurrences

are not known so far and should be investigated in the future.

5.1.3 Surface grain-size distributions and their spatial variations

As mentioned in section 4.3.1 and visible in Figure 15B, all nineteen samples possess a large

variety of grain sizes, as such preventing the ease of sedimentological clustering.

Yet, some observations are made that facilitated organizing the samples in some way.

Before explaining these observations, it needs to noted that most of the surface samples

(i.e. 17/19) are characterized by a dominant mode around 10 µm. Similar to the short cores,

this mode is mainly attributed to the presence of diatoms of the type Nitzschia sp. 1.

The remaining part of the mode is allocated to a sedimentary origin.

A first observation concerns the samples 10G, 11G, 20G and 21G, which are all located in

the northwestern corner of Lake Challa in the extension of the 300 m small creek (Figure 18).

Although possessing different grain-size distributions, as shown in Figure 18A, these four

samples contain the highest percentages of clay of all surface samples, with amounts varying

between 13.1 and 27.6% (Appendix D). The higher percentages clearly reflect the influence

of nearby western onshore samples, in particular the ones located in the vicinity of the 300


39

m creek (i.e. ‘Northwestern creek’ group, Figure 9). As derived from Appendix B and shown

in Figure 10F-G, higher amounts of clay were calculated for the ‘Northwestern creek’ and

‘Northwestern’ group. As the creek becomes active during periods of heavy rainfall,

fine sediments are transported and deposited into the lake. Since clays are much less

abundant in the rest of Lake Challa, it is suggested that samples in the northwestern corner

of the lake have an obvious western sedimentary source compared to the remaining surface

samples. This suggestion is further evidenced by quantitative X-ray diffraction data of

surface sample 11G, as explained in section 5.2.1.2.

A second observation concerns the curvy transect comprising sample 9G near the shoreline

(app. 280 m) over samples 8G, 7G and 6G towards sample 2G near the centre of the lake

(Figure 18). Their grain-size distributions show some similarities by possessing a small mode

in the clay fraction between app. 0.4 and 0.7 µm, a distinct mode at app. 6 µm and finally a

varying sand fraction with various smaller modes (Figure 18B). Sample 9G has the fifth

highest amount of clay (7.8%, Appendix D), which is in accordance to its more proximal

location to the 300 m creek as explained above. The other samples contain a lower,

but relatively stable clay content. According to the expectations, a fining trend is observed

along this transect. The percentage of sand is decreasing from sample 9G towards sample

2G, whereas the amount of silt is increasing to a maximum percentage of 90% in the latter

sample (Appendix D). Similar to the short cores in the eastern part of the lake, a decreasing

influence of mainly western onshore samples is concluded to be the reason for this

observation.

A third and final observation includes the surface samples 5G, 14G, 15G, 16G, 17G, 18G,

24G and 25G, which are located towards the eastern border of Lake Challa (Figure 18).

Their grain-size distributions are quite similar to those of the short cores by having a small

and consistent mode at app. 0.7 µm, a broader mode around 10 µm and finally a varying

sand fraction (Figure 18C). As with the short cores, the mode around 10 µm is mainly due to

diatoms of the type Nitzschia sp. 1 and partly due to sediment particles or the ‘Eastern’

group samples (cfr. section 5.1.2). In contrast to the short cores and the expectations,

no fining trend is observed along the arbitrarily-chosen transect from sample 14G over 15G,

25G and 17G towards 16G since the percentages of sand and silt are alternately

decreasing/increasing and increasing/decreasing (Appendix D). Because of their location,

a dominant influence of nearby eastern onshore samples (i.e. ‘Eastern’ group, Figure 9) is

expected. Yet, traces of the dominant mode in the sand fraction observed in the ‘Eastern’

group samples (app. 600 µm, Figure 10B), are barely observed in the grain-size distributions

of above-listed surface samples. Even the samples near the shoreline (i.e. 5G, 14G and 15G)

do not hold a high frequency mode in the sand fraction. It is therefore concluded that the

eastern crater rim induces much less fluvial transport or run-off into the lake, as no small

rivers, streams or creeks can be found there. Since the catchment east of Lake Challa is drier

(Figure 16), more aeolian transport in the eastern part of the lake is expected.


40

Figure 18: A, B and C showing the grain-size distributions of the samples that are discussed in the first, second and third observation respectively. The locations of the samples in the three observations (A, B and C) are indicated in the lower right figure with red, yellow and purple respectively. The curvy transect of observation two is indicated with a yellow dashed line and the 300 m small creek on the NW crater rim by a blue star. Depth contours (Moernaut et al., 2010) are drawn at 10 m intervals to 90 m depth and at 94 m depth.


41

5.2 Controls on mineralogical properties

5.2.1 On- and offshore XRD patterns and their spatial variations

In Chapter 4, forty onshore and one surface sample were separated in seven clusters

(Figure 11, Table 1) after the execution of a hierarchical cluster analysis in SciPy v0.16.1

(Jones et al., 2001). Similar to the various grain-size groups, every XRD cluster represents a

certain area on or near the crater rim of Lake Challa (Figure 12). Prior to interpreting these

different clusters, some critical thoughts must be given to the deviation of the obtained

wt%’s of zincite (Appendix E, column 2) from the percentage that was added prior to analysis

(5%) and to the remarkable presence of some mineral phases.

5.2.1.1 Influence of heating on XRD patterns

As mentioned in section 3.1.3, two plausible reasons were given for this deviation, which

varies between 0.02 and 5.43% (Appendix E). One concerned the occurrence of amorphous

material, which is present in varying amounts in all samples (Appendix E) and which leads to

unsatisfactory wt%’s. As amorphous material has previously been defined as ‘non-crystalline

solids in which atoms and molecules are not organized in a definite lattice pattern’,

past and/or recent heating processes are suggested as a plausible cause for its presence.

When soil samples in particular are being heated, either by volcanic processes in the past or

during the recently executed loss-on-ignition procedure at 550°C and 950°C, crystal lattices

disintegrate or deform, possibly resulting in the formation of X-ray amorphous material.

On the other hand, new mineral phases can be created after the deformation or

recrystallization of the initial mineral phases. For example accessory minerals akermanite

and mayenite, of which the occurrence around Lake Challa (Appendix E) was not expected,

are suggested to be mainly created during the LOI procedure (pers. Com. M. Dumon,

UGent). Moreover, both minerals can be created at high temperatures after the alteration of

siliceous limestones thus suggesting that perhaps calcite-bearing minerals were present

prior to LOI, but that they have disintegrated or recrystallized to akermanite and mayenite

upon heating (Appendix F). As mentioned in section 2.1, calcareous tuffaceous grits are

present at the surface around Lake Challa (Downie and Wilkinson, 1972) and these might act

as a calcite source.

The interpretation above is further strengthened by the relatively strong positive correlation

that is observed between the weight loss after LOI550, LOI950 and the occurrence of

akermanite and mayenite (Figure 19). This figure, also known as a heatmap, represents a

colour matrix of correlation coefficients between two parameters. Higher values (> 50%) are

observed in the lower right corner and evidence a relation between LOI and the occurrence


42

of both accessory minerals. The occurrence of the carbonates magnesite, dolomite and lime

(CaO) can also be linked to LOI, but in lesser extent (Figure 19).

Figure 19: Heatmap representing the correlation coefficients between two parameters. Reddish colours indicate a positive correlation, whereas blueish colours a negative correlation. Striking is the strong positive correlation between both LOI procedures and the occurrence of the mineral phases ‘Akermanite’ and ‘Mayenite’.

Additional evidences for the influence of LOI on the XRD patterns could be derived from the

mineralogical composition of onshore samples 9, 13, 22 (Table 1, cluster 1) and 208 (Table 1,

cluster 4). These four samples consist of pure rocky material Appendix A) and they were

therefore excluded from the LOI procedure. Their mineralogical compositions revealed some

mutual similarities and remarkable differences with the other XRD samples that have

undergone the LOI procedure. For example, pseudobrookite is completely absent in all four

samples. So far, it is not fully understood if this is related to their rocky nature or if this

implies that it has been created in the other samples upon heating. Pseudobrookite can also

naturally occur within the Mt. Kilimanjaro volcanic complex (Anthony et al., 2003;

Appendix F). In contrast to pseudobrookite, feldspathoids only occur in three of the four

unheated samples (i.e. 9, 13 and 22, cluster 1), which thus suggests a link with LOI, although


43

this cannot be proven so far. Further, the wt%’s of hematite of these four samples are the

lowest of all XRD samples. As hematite (Fe2O3) is formed upon heating of goethite (FeOOH)

at app. 300°C, it might have been created in the other soil samples during the LOI procedure.

Thought, caution must be paid as goethite is mainly formed through the weathering of iron-

rich minerals in laterite soils. As a result, the amount of goethite was probably higher already

for all the soil samples, logically resulting in higher amounts of clay-sized hematite after the

LOI procedure. The influence of LOI solely on the wt%’s of hematite can therefore not be

concluded. Finally, the wt%’s of the accessory minerals in samples 9, 13 and 22 are also

among the lowest of all XRD samples, thus strengthening the reasoning in the paragraph

above (i.e. LOI vs. accessories).

Due to above-mentioned examples, the influence of the LOI procedure on the onshore and

surface samples must therefore be considered during the interpretation of the various XRD

patterns. Yet, it needs to be noted that amorphous material or accessory minerals might

have been present in the samples even before LOI was performed as Lake Challa is

surrounded by sediments that possess a volcanic nature (Bear, 1955). The initial

mineralogical composition of every sample also played an important role of course, as every

mineral phase has a different degree of disintegration, deformation or recrystallization at

higher temperatures.

All these parameters must be kept in mind during the interpretation of the various clusters,

because the precision of quantitative X-ray analysis is not very high as proven by Madsen et

al. (2001), Omotoso et al (2006) and Ottner et al. (2000). The various mineralogical

compositions and clusters listed in Table 1 must therefore be treated as a rough estimation.

In the future, additional XRD analyses on unheated samples should be performed to approve

these roughly estimated compositions.

5.2.1.2 Spatial variations of XRD patterns

Although seven clusters have been defined during the hierarchical clustering analysis, it does

not imply that seven distinct source areas can be pinpointed around Lake Challa. First of all,

one must keep the volcanic nature of Lake Challa and its surrounding landscape in mind.

This obviously explains the abundance of pyroxenes, plagioclases and forsterite in nearly all

XRD samples (Table 1), as Lake Challa is surrounded by igneous rocks of the Mt. Kilimanjaro

complex (Bear, 1955) and underlain by metamorphic rocks (i.e. gneisses) (Petters, 1991).

Secondly, it must be mentioned that Lake Challa is a relatively small crater lake compared to

the size of the Tertiary Mt. Kilimanjaro complex. As a result, major differences in the spatial

variation of the various XRD patterns are not expected. Instead, minor variations were

observed between some clusters.


44

Firstly, the unheated samples 9, 13, 22 of cluster 1 and 208 of cluster 4 are characterized by

possessing the highest amounts of pyroxenes and plagioclases respectively (Table 1).

This is in accordance with their rocky nature, as these have been less altered by tropical

weathering. Their different location around the lake (Figure 12) simply approves the fact

Lake Challa is surrounded by igneous rocks. The other differences in their mineralogical

composition have been explained in the section above. Further conclusions are therefore

not drawn from both clusters.

Secondly, the highest amounts of forsterite are observed in samples J12, 10, LBK73

(cluster 2) and 9 (cluster 1) on the southwestern crater rim, followed by samples LBK75 and

LBK76 (cluster 5) on southern crater rim (Figure 20, Table 1). Vertical exaggeration of the

crater rim has revealed that the south and southwestern crater rim protrude more in the

relief (Figure 20). This suggests a lower degree of erosion (by water or wind) and weathering,

as such resulting in higher amounts of forsterite on the south and southwestern crater rim.

The lower degree of erosion could be explained by the fact that monsoonal winds are

predominantly coming from the north- and southeast. As these winds have an erosive action

due to particles in suspension, more rapid erosion of the north- to southeastern crater rim

could have occurred compared to the south and southwestern rim.

Figure 20: Satellite view on Lake Challa from the north to northeast (source: Google Earth). The crater rim is vertically exaggerated (x3) and clearly shows a protruding southern and southwestern crater rim in the relief.


45

Thirdly, the samples of the 7th cluster located on the northwestern crater rim

(Figure 12), all possess a different mineralogical composition compared to the other clusters

(Table 1). They are characterized by low amounts of forsterite, pyroxenes and plagioclases

and high amounts of hematite, pseudobrookite, quartz and cristobalite (Table 1).

The lower amounts of these volcanic minerals are suggested to be the result of enhanced

fluvial erosion and weathering by precipitation and melt water originating on the flanks of

Mt. Kilimanjaro in the northwest. As can be seen in Figure 20, the northwestern crater rim is

almost completely eroded. These observations correspond with the observations made for

the grain-size distributions in that area (i.e. ‘Northwestern’ and ‘Northwestern creek’ group,

section 5.1.1). As mentioned in section 4.3.2, the only surface sample 11G was also clustered

in cluster 7. Similar to the first observation made for the surface samples (section 5.1.3),

it evidences a distinct western sedimentary source as the mineralogical composition of

surface sample 11G largely corresponds with the northwestern onshore samples (Table 1).

Unfortunately, XRD patterns of other surface samples were not available to investigate other

possible source-to-sink processes into Lake Challa. Yet, using sample 11G as a clear example,

other source-to-sink processes might be detected in the remaining parts of Lake Challa if

additional sampling across the entire lake is executed in the future.

Finally, no decisive conclusions regarding provenance can be made based on the samples of

cluster 3, cluster 5 and cluster 6. Cluster 3 represents the samples taken on the lakeshore

(Figure 12) and their mineralogical compositions more or less correspond with the general

abundance of pyroxenes, plagioclases and hematite in the crater rim sediments (Table 1).

This corresponds with the expectations, namely erosion of crater rim material and

subsequent deposition on the lakeshore. Cluster 5 represents the largest cluster and

comprises samples that are scattered across the crater rim (Figure 12). Due to this spatial

scattering and because of the fact that their mineralogical compositions are differing the

least from the overall average, the data is insufficient to detect the exact provenance of the

various mineral phases that are present. Nonetheless, minor variations between some

samples within the cluster are observed, although these are of minor importance.

The distally located samples of cluster 6 eventually, possess similarities with the samples of

cluster 7, i.e. low amounts of forsterite, pyroxenes and plagioclases and higher amounts of

hematite, quartz and pseudobrookite, although the XRD signals are not easily traced back

into Lake Challa or its crater rim. Additional sampling in the future is therefore suggested.


46

5.3 Terrestrial source areas and source-to-sink processes at Lake Challa

In this section, a brief summary of Chapter 5 is given with the eye on identifying distinct

terrestrial source areas and source-to-sink processes. One major finding of this study is that

the identification of distinct terrestrial source areas around Lake Challa is far from being

straight forward. Plenty of factors might have influenced the sedimentological and/or

mineralogical properties of the clastic sediments within and/or around Lake Challa.

For example, it must be reminded in the first place that the onshore samples were sampled

superficially (Appendix A), which complicates modern source-to-sink investigations and

provenance studies, since such samples often represent a mixture of signals originating from

various sources and/or transport mechanisms (i.e. run-off vs. aeolian) (Holz et al., 2007).

Moreover, minor variations in the spatial distribution of samples can lead to large

differences in grain-size distributions and/or X-ray diffraction patterns. This is evidenced by

the significant amount of defined onshore groups and XRD clusters, which was initially not

expected around the relatively small lake. Yet, differences between the groups and clusters

were in many cases not significantly high. Eventually, the most decisive observations in both

the grain-size distributions and the XRD patterns were made for the onshore samples on the

NW crater rim and for the associated surface sediments in the NW corner of the lake.

Both properties evidence the influence of a western sedimentary source and a fluvial

transport regime, compared to the rest of Lake Challa.

Besides difficulties on the source-side of the source-to-sink systems, difficulties were also

present on the sink-side. For example, the grain-size distributions of the lacustrine

sediments of Lake Challa were affected by the presence of diatoms, even though the heavy

liquid separation method was executed. This obstructed the search for a clear connection

between the clastic fraction of the lacustrine and crater rim sediments of Lake Challa.

Research into the mineralogical composition of the lacustrine sediments did not bring forth

much success either, as only one surface sample was available to evidence potential source-

to-sink relationships between the onshore samples and the lacustrine samples.

Chapter 6 – Conclusions

47

6 CONCLUSIONS

In this study an attempt was made to identify modern transport mechanisms of clastic

particles towards Lake Challa (Kenya/Tanzania) and to map out spatial variations in

sedimentological and mineralogical properties with the purpose to define distinct terrestrial

source areas. Therefore, high-resolution grain-size analyses were carried out on the clastic

fraction of three different sources of sedimentary material: onshore samples, short cores

and surface sediment samples. Mineralogical analyses were solely carried out on the

onshore samples and on one suitable surface sediment sample. Grain-size distributions were

obtained using the principle of laser diffraction in a Malvern Mastersizer 3000, after the

removal of abundant diatom frustules in a pre-treatment phase by applying a heavy liquid

separation method. Mineralogical analysis consisted of qualitative and quantitative X-ray

diffraction (XRD) analyses on a Bruker D8 Eco Advance system, after the prior removal of all

non-clastic fractions.

Given the significant amount of obtained grain-size distributions and X-ray diffraction

patterns for the onshore samples, a clustering approach was carried out for both properties

with the purpose to find along-shore differences in the grain-size distributions and in the

mineralogical compositions. Although not expected, ten different grain-size groups and

seven XRD clusters were defined around Lake Challa.

Despite the large amount of grain-size groups and XRD clusters, it does not imply that each

of them represents a distinct source area, since minor differences were observed in most

cases. Nonetheless, significant differences in grain-size distributions were observed

for two onshore groups on the northwestern crater rim (i.e. ‘Northwestern’ and

‘Northwestern creek’ group), one group further northwest closer to Mt. Kilimanjaro

(i.e. ‘Mt. Kilimanjaro’ group) and one proximal group north- to southeast of Lake Challa

(i.e. ‘Hinterland’ group). These four groups were characterized by significantly higher

amounts of clay, which are attributed to fluvial transport regimes (i.e. rivers, creeks, gullies)

west and east of Lake Challa. These regimes have originated due to precipitation and melt

water transport from the southeastern flanks of Mt. Kilimanjaro towards the southwest,

i.e. towards Lake Challa. Moreover, these fluvial regimes have resulted in a higher degree of

erosion and weathering of the northwestern crater rim, consequently also explaining the

significantly different mineralogical composition of the samples in that area (i.e. 7th cluster).

Contrary to the rest of the crater rim, this corner is characterized by low amounts of volcanic

minerals such as forsterite, pyroxenes and plagioclases. Moreover, a positive correlation was

observed between the grain-size distributions and the mineralogical compositions of the

northwestern crater rim sediments and the northwestern lacustrine surface sediments.

This is concluded to be a fluvial source-to-sink system with its origin located in western,

more vegetated and wetter areas.

Chapter 6 – Conclusions

48

The remaining onshore groups on the northern, eastern and southern crater rim on the

other hand, are barely affected by fluvial processes. Instead, these less vegetated and drier

areas are more affected by the erosive action of strong north- and southeastern monsoonal

winds (Nicholson, 1996), which prevent the deposition of very fine material on the rim and

subsequently within the lake. This is also evidenced by the generally low amounts of very

fine material observed in the eastern short cores and surface sediment samples. Aside the

low amounts of very fine material, higher amounts of silt were observed for both the eastern

lacustrine and onshore samples. This points out to an aeolian transport regime and an

eastern sedimentary source, although more evidence is necessary here.

As this study was rather exploratory, it also brought a few difficulties to light that offer

several opportunities regarding future research. For example, it has been pointed out that

most grain-size distributions of the lacustrine sediments (i.e. short cores and surface

sediment samples) of Lake Challa are strongly affected by the presence of diatom frustules

(Nitzschia sp. 1), even though they should have been removed by the heavy liquid separation

method. By improving this method in the future, diatoms will be completely removed, which

will facilitate the search for further possible source-to-sink systems around Lake Challa.

Furthermore, this study has repeatedly proven that the various mineralogical compositions

of heated samples around and within Lake Challa should be treated as a rough estimation,

as heating processes affected the mineralogical assemblages. Additional XRD analyses on

unheated samples should be executed in the future to further approve these roughly

estimated compositions. Finally, additional structured sampling within and around Lake

Challa should be carried out in the future with the purpose to obtain a satisfactory coverage

of both lacustrine and onshore deposits. This will aid in further investigations regarding

spatial variations in the sedimentological and mineralogical properties and in potential

source-to-sink relationships between the onshore and lacustrine samples of Lake Challa.

Chapter 7 – References

49

7 REFERENCES

Allen, P.A., 2008a, From landscapes into geological history: Nature, v. 451, no. 7176, p. 274–276.

Allen, P.A., 2008b, Time scales of tectonic landscapes and their sediment routing systems: Geological Society, London, Special Publications, v. 296, no. 1, p. 7–28.

Amorosi, A., Maselli, V., and Trincardi, F., 2016, Onshore to offshore anatomy of a late Quaternary source-to-sink system (Po Plain-Adriatic Sea, Italy): Earth-Science Reviews, v. 153, p. 212–237.

Anthony, J.W., Bideaux, R.A., Bladh, K.W., and Nichols, M.C., 2003, Eds., Handbook of Mineralogy, Mineralogical Society of America, Chantilly, VA 20151-1110, USA. http://www.handbookofmineralogy.org.

Baker, B.H., Williams, L.A.J., Miller, J.A., and Fitch, F.J., 1971, Sequence and geochronology of the Kenya rift volcanics: Tectonophysics, v. 11, no. 3, p. 191–215.

Bates, R.L., and Jackson, J.A., 1984, Dictionary of Geological Terms: Third Edition (Rocks, Minerals and Gemstones), American Geological Institute. p. 392.

Bear, L.M., 1955, Geology of the Taveta Area, Explanation of Degree Sheet 64 N.E. and 64 S.E. Report No. 32. (Geological Survey of Kenya, Ed.). Government Printer, Nairobi, p. 48.

Bergmann, J., Friedel, P., and Kleeberg, R., 1998, BGMN - a new fundamental parameter based Rietveld program for laboratory X-ray sources, its use in quantitative analysis and structure investigations: CPD Newsletter, Commission of Powder Diffraction, International Union of Crystallography, v. 20, p. 5–8.

Blott, S.J., and Pye, K., 2001, Gradistat: A grain size distribution and statistics package for the analysis of unconsolidated sediments: Earth Surface Processes and Landforms, v. 26, no. 11, p. 1237–1248.

Buckles, L.K., Weijers, J.W.H., Verschuren, D., and Sinninghe Damst, J.S., 2014, Sources of core and intact branched tetraether membrane lipids in the lacustrine environment: Anatomy of Lake Challa and its catchment, equatorial East Africa: Geochimica et Cosmochimica Acta, v. 140, p. 106–126.

Cullity, B.D., 1956, Elements of X-Ray Diffraction, 514 p. Addison-Wesley Publishing Company, Reading (Massachusetts, USA).

Doebelin, N., and Kleeberg, R., 2015, Profex : a graphical user interface for the Rietveld refinement program BGMN: Journal of Applied Crystallography, v. 48, no. 5, p. 1573–1580.

Downie, C., and Wilkinson, P., 1972, The Geology of Kilimanjaro: The Department of Geology, The University of Sheffield, Shefield, pp. 253, p. 373.


50

Folk, R.L., and Ward, W.C., 1957, Brazos river bar: A study in the significance of grain size parameters: Journal of Sedimentary Petrology, v. 27, no. 1, p. 3–26.

Gražulis, S., Chateigner, D., Downs, R.T., Yokochi, A.F.T., Quiros, M., Lutterotti, L., Manakova, E., Butkus, J., Moeck, P., and Le Bail, A., 2009, Crystallography Open Database - An open-access collection of crystal structures: Journal of Applied Crystallography, v. 42, no. 4, p. 726–729.

Gražulis, S., Daškevič, A., Merkys, A., Chateigner, D., Lutterotti, L., Quirós, M., Serebryanaya, N.R., Moeck, P., Downs, R.T., and Le Bail, A., 2012, Crystallography Open Database (COD): An open-access collection of crystal structures and platform for world-wide collaboration: Nucleic Acids Research, v. 40, no. D1, p. 420–427.

Heiri, O., Lotter, A.F., and Lemcke, G., 2001, Loss on ignition as a method for estimating organic and carbonate content in sediments: reproducibility and comparability of results: Paleolimnology, v. 25, p. 101–110.

Hillier, S., 1999, Use of an air brush to spray dry samples for X-ray powder diffraction: Clay Minerals, v. 34, no. 1, p. 127–135.

Holz, C., Stuut, J.B.W., Henrich, R., and Meggers, H., 2007, Variability in terrigenous sedimentation processes off northwest Africa and its relation to climate changes: Inferences from grain-size distributions of a Holocene marine sediment record: Sedimentary Geology, v. 202, no. 3, p. 499–508.

Jaeger, J.M., and Koppes, M.N., 2016, The role of the cryosphere in source-to-sink systems: Earth-Science Reviews, v. 153, p. 43–76.

Johnson, T.C., Scholz, C.A., Talbot, M.R., Kelts, K., Ricketts, R.D., Ngobi, G., Beuning, K., Ssemmanda, I., and McGill, J.W., 1996, Late Pleistocene desiccation of Lake Victoria and rapid evolution of cichlid fishes: Science, v. 273, no. 5278, p. 1091–1093.

Jones, E., Oliphant, E., and Peterson, P., 2001, SciPy: Open Source Scientific Tools for Python. http://www.scipy.org.

Kampunzu, A.B., and Popoff, M., 1991, Distribution of the main Phanerozoic African rifts and associated magmatism: introductory notes: Magmatism in extensional structural settings, p. 2–10.

Kempf, P., 2016, Tsunamis in south central Chili: evidence from coastal lakes: PhD Thesis; Ghent University (Ghent, Belgium).

Kleeberg, R., Monecke, T., and Hillier, S., 2008, Preferred orientation of mineral grains in sample mounts for quantitative XRD measurements: How random are powder samples? Clays and Clay Minerals, v. 56, no. 4, p. 404–415.

Kristen, I., 2010, Investigations on rainfall variability during the late Quaternary based on geochemical analyses of lake sediments from tropical and subtropical southern Africa: PhD Thesis; Deutsches GeoForschungsZentrum GFZ (Potsdam, Germany), 160 p.


51

Loizeau, J.-L., Rozé, S., Peytremann, C., Monna, F., and Dominik, J., 2003, Mapping sediment accumulation rate by using volume magnetic susceptibility core correlation in a contaminated bay (Lake Geneva , Switzerland): Eclogae Geologicae Helvetiae, v. 96, p. 73–79.

Madella, M., Powers-Jones, A.H., and Jones, M.K., 1998, A simple method of extraction of opal phytoliths from sediments using a non-toxic heavy liquid: Journal of Archaeological Science, v. 25, p. 801–803.

Madsen, I.C., Scarlett, N.V.Y., Cranswick, L.M.D., and Lwin, T., 2001, Outcomes of the International Union of Crystallography Commission on Powder Diffraction round robin on quantitative phase analysis: samples 1 a to 1 h: Journal of Applied Crystallography, v. 34, no. 4, p. 409–426.

Maher, B.A., 2011, The magnetic properties of Quaternary aeolian dusts and sediments, and their palaeoclimatic significance: Aeolian Research, v. 3, no. 2, p. 87–144.

Matenco, L., and Andriessen, P., 2013, Quantifying the mass transfer from mountain ranges to deposition in sedimentary basins: Source to sink studies in the Danube Basin-Black Sea system: Global and Planetary Change, v. 103, no. 1, p. 1–18.

Milliman, J.D., and Syvitski, J.P.M., 1992, Geomorphic/Tectonic Control of Sediment Discharge to the Ocean: The Importance of Small Mountainous Rivers: The Journal of Geology, v. 100, no. 5, p. 525–544.

Milne, I., 2007, Climate and environmental change inferred from diatom communities in Lake Challa (Kenya-Tanzania): Msc Thesis; Queen’s University (Ontario, Canada).

Moernaut, J., Verschuren, D., Charlet, F., Kristen, I., Fagot, M., and De Batist, M., 2010, The seismic-stratigraphic record of lake-level fluctuations in Lake Challa: Hydrological stability and change in equatorial East Africa over the last 140 kyr: Earth and Planetary Science Letters, v. 290, no. 1-2, p. 214–223.

Nicholson, S.E., 1996, A review of climate dynamics and climate variability in eastern Africa, in Johnson, T.C., Odada, E. (eds.), The Limnology, Climatology and Paleoclimatology of the East African Lakes. Gordon & Breach, p. 26–56.

Nowaczyk, N.R., 2001, Logging of magnetic susceptibility, in Tracking environmental change using lake sediments. (W.M. Last, and J.P. Smol, Eds.), p. 155-170 (Ch. 8), Kluwer Academic Publishers, Dordrecht.

Omenda, P.A., 2007, The geothermal activity of the past East African rift, in Presented at Short Course II on Surface Exploration for Geothermal Resources, organized by UNU-GTP and KenGen, at Lake Naivasha, Kenya, 2-17 November, 2007, p. 1–12.

Omotoso, O., McCarty, D.K., Hillier, S., and Kleeberg, R., 2006, Some successful approaches to quantitative mineral analysis as revealed by the 3rd reynolds cup contest: Clays and Clay Minerals, v. 54, no. 6, p. 748–760.


52

Ottner, F., Gier, S., Kuderna, M., and Schwaighofer, B., 2000, Results of an inter-laboratory comparison of methods for quantitative clay analysis: Applied Clay Science, v. 17, no. 5-6, p. 223–243.

Payne, B.R., 1970, Water balance of Lake Challa and its relation to groundwater from tritium and stable isotope data: Journal of Hydrology, v. 11, p. 47–58.

Petters, S.W., 1991, Regional Geology of Africa. Springer-Verlag, Berlin - Heidelberg, p. 722.

Prins, M.A., Postma, G., and Weltje, G.J., 2000, Controls on terrigenous sediment supply to the Arabian Sea during the late Quaternary: The Makran continental slope: Marine Geology, v. 169, no. 3-4, p. 351–371.

Prizomwala, S.P., Bhatt, N., and Basavaiah, N., 2014, Provenance discrimination and Source-to-Sink studies from a dryland fluvial regime: An example from Kachchh, western India: International Journal of Sediment Research, v. 29, no. 1, p. 99–109.

Ruddiman, W.F., 2008, Earth’s climate: Past and future (second edition). W.H. Freeman and Company, New York, 388 pp.

Schüler, L., Hemp, A., Zech, W., and Behling, H., 2012, Vegetation, climate and fire-dynamics in East Africa inferred from the Maundi crater pollen record from Mt Kilimanjaro during the last glacial-interglacial cycle: Quaternary Science Reviews, v. 39, p. 1–13.

Shanahan, T.M., McKay, N., Overpeck, J.T., Peck, J.A., Scholz, C., Heil, C.W., and King, J., 2013, Spatial and temporal variability in sedimentological and geochemical properties of sediments from an anoxic crater lake in West Africa: Implications for paleoenvironmental reconstructions: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 374, p. 96–109.

Sinninghe Damsté, J.S., Ossebaar, J., Abbas, B., Schouten, S., and Verschuren, D., 2009, Fluxes and distribution of tetraether lipids in an equatorial African lake: Constraints on the application of the TEX86 palaeothermometer and BIT index in lacustrine settings: Geochimica et Cosmochimica Acta, v. 73, no. 14, p. 4232–4249.

Sinninghe Damsté, J.S., Verschuren, D., Ossebaar, J., Blokker, J., van Houten, R., van der Meer, M.T.J., Plessen, B., and Schouten, S., 2011, A 25,000-year record of climate-induced changes in lowland vegetation of eastern equatorial Africa revealed by the stable carbon-isotopic composition of fossil plant leaf waxes: Earth and Planetary Science Letters, v. 302, no. 1-2, p. 236–246.

Stuut, J.B.W., Prins, M.A., Schneider, R.R., Weltje, G.J., Fred Jansen, J.H., and Postma, G., 2002, A 300-kyr record of aridity and wind strength in southwestern Africa: Inferences from grain-size distributions of sediments on Walvis Ridge, SE Atlantic: Marine Geology, v. 180, no. 1-4, p. 221–233.

Verschuren, D., Sinninghe Damsté, J.S., Moernaut, J., Kristen, I., Blaauw, M., Fagot, M., and Haug, G.H., 2009, Half-precessional dynamics of monsoon rainfall near the East African Equator.: Nature, v. 462, no. 7273, p. 637–641.


53

Visher, G.S., 1969, Grain Size Distributions and Depositional Processes: Journal of Sedimentary Petrology, v. 39, no. 3, p. 1074–1106.

Ward, J.H., 1963, Hierarchical grouping to optimize an objective function: Journal of the American Statistical Association, v. 58, no. 301, p. 236–244.

Washington, R., Todd, M., Middleton, N.J., Andrew, S., Washington, R., Todd, M., Middleton, N.J., Washington, R., Todd, M., Middleton, N.J., and Goudie, A.S., 2003, Dust-Storm source areas determined by the total ozone monitoring spectrometer and surface observations: Annals of the Association of American Geographers, v. 93, no. 2, p. 297–313.

Wolff, C., Haug, G.H., Timmermann, A., Sinninghe Damsté, J.S., Brauer, A., Sigman, D.M., Cane, M.A., and Verschuren, D., 2011, Reduced interannual rainfall variability in East Africa during the last ice age: Science, v. 333, no. 6043, p. 743–747.

Wolff, C., Kristen-Jenny, I., Schettler, G., Plessen, B., Meyer, H., Dulski, P., Naumann, R., Brauer, A., Verschuren, D., and Haug, G.H., 2014, Modern seasonality in Lake Challa (Kenya/Tanzania) and its sedimentary documentation in recent lake sediments: Limnology and Oceanography, v. 59, no. 5, p. 1621–1636.

Chapter 8 – Appendices

54

8 APPENDICES

Appendix A: List of sixty-six onshore samples. Left: twenty-nine ‘Potsdam’ samples of Kristen (2010). Right: thirty-seven ‘Utrecht’ samples of Buckles et al. (2014), L: lakeshore, C: crater rim H: hinterland, R: ravine in the NW corner of the lake, CL; RH; RCH; RC and LR: combinations of different origins.

POTSDAM UTRECHT

Sample Type Lat (S) Lon (E) Sample Colour Depth (cm) Origin Lat (S) Lon (E)

208 rock* -3,314111 37,717200 J01 grey 0-3 L -3,314229 37,712415

209 soil -3,313944 37,733600 J02 grey 3-10 CL -3,314537 37,712567

210a rock* -3,371222 37,733600 J03 grey 0-6 CL -3,314465 37,712298

210b soil -3,371222 37,733600 J04 grey 0-4 C -3,313968 37,712946

8 soil -3,327479 37,702439 J05 grey 5-10 L -3,320329 37,707763

9 rock* -3,325397 37,687724 J06 grey NA CL -3,321801 37,705817

10 soil -3,324748 37,687204 J07 red 0-10 RH -3,306303 37,689279

11 rock/soil* -3,324539 37,686920 J08 red 0-10 RCH -3,304836 37,687580

13 rock/soil* -3,316342 37,686179 J09 red 0-10 RH -3,303604 37,686547

14 rock/soil* -3,315275 37,686399 J10 red NA RH -3,304635 37,686185

15a rock* -3,307834 37,687891 J11 red NA RH -3,305851 37,689234

15b soil -3,307834 37,687891 J12 red NA C -3,324362 37,686996

16 soil -3,307250 37,695063 LKB61 grey 0-4 L -3,318007 37,689011

17/18 soil -3,310556 37,709722 LKB62 grey 0-7 C -3,311480 37,712319

19 soil -3,309041 37,688550 LKB63 grey 0-6 C -3,309750 37,710063

20 soil -3,326685 37,695352 LKB64 grey 0-6 C -3,308768 37,706419

21 soil -3,324614 37,703077 LKB65 grey 0-6 C -3,308688 37,700453

22 rock* -3,314449 37,716681 LKB66 grey 0-6 C -3,307248 37,692625

23 soil -3,390253 37,730023 LKB67 red 0-6 C -3,306794 37,691006

24 soil -3,391841 37,777466 LKB68 red 0-6 RH -3,307874 37,686775

25a rock* -3,424081 37,638929 LKB69 red 0-8 RC -3,308418 37,687674

25b soil -3,424081 37,638929 LKB70 red 0-6 C -3,314746 37,685866

26 rock* -3,425503 37,647180 LKB71 grey 0-6 C -3,319722 37,686309

27 soil -3,424071 37,645587 LKB72 grey 0-6 C -3,324634 37,687032

32 soil -3,309723 37,686523 LKB73 grey/red 0-6 C -3,327911 37,689313

38 soil -3,254920 37,744909 LKB74 grey 0-6 C -3,328506 37,694757

39 soil -3,291344 37,736331 LKB75 grey 0-6 C -3,328348 37,698447

40 soil -3,394899 37,829334 LKB76 grey 0-6 C -3,327250 37,702463

41 soil -3,509794 38,258455 LKB77 litter 0-5 L -3,311333 37,710799

* Excluded for grain-size analysis LKB78 grey 3-3.5 L -3,310153 37,707668

LKB79 red 0-6 LR -3,308898 37,688681

LKB80 red 0-6 LR -3,308898 37,688681

LKB81 grey 0-6 L -3,308930 37,698635

LKB82 red 0-8 H -3,266870 37,636282

LKB83 red 0-7 H -3,266870 37,636282

LKB84 red 0-8 H -3,295946 37,634632

LKB85 red 0-7 H -3,295946 37,634632


55

Appendix B: Grain-size results of ten defined onshore groups around Lake Challa.

Group Sample Clay (%) Silt (%) Sand (%) Gravel (%) Sand + Silt (%)

Southern

LBK72 2,1 46,9 51,0 0,0 97,9 LBK74 3,1 57,3 39,4 0,2 96,7 LBK75 2,4 49,4 48,2 0,0 97,6 LBK76 1,5 39,7 58,6 0,1 98,4

J12 0,8 44,0 54,9 0,2 99,0 8 1,2 48,5 50,3 0,0 98,8

10 3,7 43,1 53,1 0,0 96,3

AVERAGE 2,13 47,01 50,79 0,08 97,8

Eastern

J01 2,2 29,9 67,9 0,0 97,8

J02 6,3 36,9 55,7 1,1 92,6

J03 0,8 41,7 57,5 0,0 99,2

J04 2,7 29,7 66,6 1,0 96,3

J05 0,5 25,8 73,5 0,2 99,2

J06 0,7 23,8 74,9 0,7 98,6

AVERAGE 2,20 31,29 66,00 0,51 97,3

Northeastern

LKB62 5,1 45,5 49,4 0,0 94,9 LKB63 7,8 47,8 44,4 0,0 92,2 LKB77 2,7 48,2 49,1 0,0 97,3

AVERAGE 5,21 47,18 47,62 0,00 94,8

Northern

LKB64 4,5 39,4 56,0 0,1 95,4

LKB65 4,8 37,0 58,2 0,0 95,2

16 1,5 25,0 73,3 0,1 98,4

AVERAGE 3,60 33,79 62,52 0,09 96,3

Western LKB70 2,5 23,7 73,9 0,0 97,5 LKB71 1,5 22,6 75,9 0,0 98,5

AVERAGE 1,99 23,14 74,87 0,00 98,0

Northwestern creek

LKB68 33,1 25,9 41,0 0,0 66,9 LKB69 22,4 27,4 50,2 0,0 77,6 LKB79 17,2 24,8 58,0 0,0 82,8 LKB80 22,0 17,8 60,2 0,0 78,0

15b 11,5 24,7 63,9 0,0 88,4 19 15,2 14,3 70,4 0,0 84,8 32 16,5 11,2 72,2 0,0 83,5

AVERAGE 19,71 20,87 59,41 0,00 80,3

Northwestern

J07 24,7 29,7 45,6 0,0 75,3

J08 12,4 17,3 70,0 0,3 87,3

J09 22,0 39,0 39,0 0,0 78,0

J10 21,5 22,6 55,9 0,0 78,5

J11 5,3 14,9 79,8 0,0 94,7

LKB67 20,1 31,7 48,2 0,0 79,9

AVERAGE 17,67 25,86 56,43 0,05 82,3

Mt. Kilimanjaro

LKB82 43,8 12,9 43,2 0,0 56,2

LKB83 41,9 21,6 36,5 0,0 58,1

LKB84 35,5 21,1 43,3 0,1 64,4

LKB85 43,1 13,2 43,7 0,0 56,9

AVERAGE 41,09 17,22 41,68 0,01 58,9

Lakeshore

LKB78 13,9 30,7 54,8 0,6 85,5 LKB81 5,0 19,6 74,2 1,2 93,9 17/18 6,8 31,1 60,4 1,7 91,5

20 0,3 18,7 73,9 7,1 92,5 21 1,9 34,0 63,7 0,3 97,7

AVERAGE 5,59 26,83 65,40 2,19 92,2

Hinterland

38 27,1 21,4 51,3 0,2 72,7

39 21,1 26,5 52,4 0,0 78,9

209 34,5 11,2 54,4 0,0 65,5

210b 38,6 23,1 38,2 0,0 61,4

AVERAGE 30,34 20,54 49,07 0,05 69,6


56

Appendix C.1: Grain-size results of thirty-seven sampling intervals in five short cores (cfr. Figure 13).

Short core Core depth (cm) Clay (%) Silt (%) Sand (%) Gravel (%) Sand + Silt (%)

7G

0 - 3,5 12,4 82,8 4,8 0,0 87,6

5,5 - 8,5 4,9 81,7 13,1 0,3 94,8

10 - 12,5 4,8 81,1 14,0 0,0 95,2

14 - 16 4,6 78,1 17,3 0,0 95,4

15 - 19 13,4 77,9 8,7 0,0 86,6

9G

1,2 - 5 5,5 88,1 6,5 0,0 94,5

4,6 - 6,6 6,8 90,4 2,8 0,0 93,2

8,5 - 10,5 5,9 88,7 5,3 0,0 94,1

13 - 15,5 4,0 82,2 13,7 0,0 96,0

19 - 21,5 4,4 90,2 5,3 0,0 95,6

23 - 24,5 3,6 89,9 6,5 0,0 96,4

24,5 - 27,5 3,1 91,9 5,0 0,0 96,9

33 - 36,2 6,2 88,8 5,0 0,0 93,8

10G

1 - 3 7,9 67,9 24,2 0,0 92,1

3 - 5,5 10,4 80,1 9,5 0,0 89,6

5,5 - 7,5 5,1 89,8 5,1 0,0 94,9

7,5 - 9,5 11,4 84,0 4,6 0,0 88,6

9,5 -11,5 7,7 75,3 17,0 0,0 92,3

11,5 - 13,5 6,9 76,5 16,5 0,0 93,1

13,5 - 15,5 7,4 77,6 14,9 0,0 92,6

15,5 - 17,5 7,8 84,5 7,7 0,0 92,2

17,5 - 19,5 4,4 89,1 6,5 0,0 95,6

19,5 - 21,5 3,8 89,9 6,3 0,0 96,2

21,5 - 23,5 5,1 86,4 8,5 0,0 94,9

23,5 - 25,5 5,3 86,4 8,3 0,0 94,7

11G

1 - 5 5,8 72,0 22,2 0,0 94,2

8 - 11 5,1 90,3 4,6 0,0 94,9

13,5 - 15 8,0 84,9 7,1 0,0 92,0

15 - 17,5 5,8 73,3 20,9 0,0 94,2

17,5 - 21 6,0 61,6 32,3 0,0 94,0

27 - 30 7,6 80,6 11,8 0,0 92,4

12G

1 - 4 6,5 57,8 35,7 0,0 93,5

4 - 7 4,8 59,6 35,6 0,0 95,2

9 - 10,5 3,1 70,5 26,4 0,0 96,9

12 - 15,5 2,6 61,4 36,1 0,0 97,4

19,5 - 22,5 5,1 67,6 27,3 0,0 94,9

22,5 - 25,5 4,5 72,3 23,2 0,0 95,5

Appendix C.2: Average grain-size results of five short cores. The arrows indicate the decreasing (red) and

increasing (green) trend in the average percentage of sand and silt respectively with increasing depth (black).

Short core Depth (m) Clay (%) Silt (%) Sand (%) Gravel (%) Sand + Silt (%)

12G 61 4,43 64,87 30,70 0,00 95,57

11G 69 6,39 77,12 16,49 0,00 93,61

7G 80 7,99 80,33 11,62 0,06 91,95

10G 85 6,92 82,31 10,77 0,00 93,08

9G 90 4,93 88,78 6,29 0,00 95,07


57

Appendix D: Grain-size results of nineteen profundal surface sediments. The different observations discussed

in section 5.1.3 are indicated by superscripts (1

observation 1, 2

observation 2, 3

observation 3).

Sample Depth (m) Clay (%) Silt (%) Sand (%) Gravel (%) Sand + Silt (%)

2G2

90,7 4,5 90,0 5,5 0,0 95,5

5G3

54,9 4,4 85,4 10,2 0,0 95,6

6G2

91,6 5,9 78,8 15,4 0,0 94,1

7G2

91,3 4,6 71,6 23,8 0,0 95,4

8G2

88,5 4,0 71,3 24,7 0,0 96,0

9G2

75 7,8 49,9 40,7 1,6 90,6

10G1

64,7 13,1 37,3 49,6 0,0 86,9

11G1

32,8 21,6 41,4 37,0 0,0 78,4

12G* 72,7 5,4 67,0 27,1 0,4 94,1

14G3

62 4,7 84,4 11,0 0,0 95,3

15G3

60,8 2,5 68,3 29,2 0,0 97,5

16G3

68,2 2,9 72,5 23,5 1,0 96,0

17G3

89,1 4,0 84,8 11,1 0,0 96,0

18G3

86,1 4,0 86,7 9,3 0,0 96,0

19G* 90,4 3,3 86,0 10,7 0,0 96,7

20G1

89,2 20,3 65,9 13,8 0,0 79,7

21G1

78,7 27,6 60,3 12,1 0,0 72,4

24G3

89 3,9 74,7 21,3 0,0 96,1

25G3

73,4 2,8 78,3 18,8 0,1 97,1

* Not included in any observation


58

Appendix E: Raw weight percentages (wt%’s) of the minerals present in forty onshore and one surface sample. All minerals and their abbreviations are listed in Appendix F.

Sample Znc (%) Psb (%) Qz (%) Crs (%) Fspt (%) Fo (%) Hbl (%) Px (%) Ms (%) Pl (%) Hem (%) Cbs (%) Acc (%) Amf (%)

208* 5,12 - - 7,76 - 2,61 2,43 17,63 4,31 46,95 8,82 2,08 2,32 2,26

209* 6,37 7,01 18,15 1,73 - 4,92 - 9,28 - 7,99 42,16 - 2,40 21,48

9* 5,63 - - - 10,05 17,15 - 54,65 7,15 - 5,10 - 0,27 11,20

10 5,02 4,37 1,17 4,82 - 18,25 - 33,05 3,29 8,81 21,22 - - 0,43 13 5,34 - 1,33 - 3,65 7,15 3,22 43,45 4,27 22,20 9,36 - - 6,40

15b 6,09 4,96 1,68 1,36 - 8,90 3,24 16,84 4,16 17,61 32,29 2,86 - 17,91 16 5,69 2,95 1,92 - - 8,69 4,33 23,69 2,24 25,07 24,03 1,39 - 12,12

17/18 7,62 4,06 3,75 - - 3,75 2,89 28,08 1,66 15,23 24,77 1,43 6,76 34,41 19 7,86 6,10 4,38 6,15 - 5,83 1,61 18,59 2,42 13,53 30,62 1,37 1,57 36,41 20 7,81 2,89 4,19 - - 4,10 3,35 29,44 2,96 21,96 17,60 0,80 4,92 35,94 21 7,68 2,55 6,13 - - 4,02 4,22 18,11 0,68 32,80 11,63 - 12,17 34,90

22* 7,01 - 5,07 - 4,01 6,67 2,67 40,16 1,33 9,21 3,59 19,78 0,49 28,63

32 7,03 8,53 8,10 9,55 - 5,46 - 9,48 - 12,36 34,40 2,49 2,62 28,86 39 7,74 6,79 17,75 10,92 - 1,07 - 9,25 2,16 6,35 32,49 2,93 2,59 35,38 J01 6,45 3,83 3,23 - - 5,93 2,56 25,29 3,26 17,23 28,07 1,03 3,10 22,44 J04 5,98 4,14 4,05 - - 7,71 3,34 18,58 2,37 20,26 27,89 2,66 3,03 16,33 J06 7,95 2,51 3,99 - - 4,67 4,74 27,82 3,49 16,32 18,91 1,95 7,65 37,09 J07 6,70 10,59 7,34 11,11 - 1,83 - 5,25 - 5,88 49,69 0,77 0,81 25,40 J08 7,44 10,30 5,94 9,45 - 1,71 - 6,40 3,56 4,20 46,75 2,21 2,04 32,80 J09 8,24 13,04 6,56 8,34 - - - 9,64 - 3,42 48,83 0,67 2,26 38,74 J10 8,35 11,27 7,70 7,29 - 1,82 - 6,37 2,70 3,82 46,28 2,07 2,34 40,09 J12 6,48 5,40 1,16 5,14 - 17,37 - 35,02 - 7,09 22,35 - - 22,87

LKB62 5,19 4,32 6,06 - - 8,65 4,47 23,65 2,02 17,73 26,39 0,76 0,76 3,73 LKB63 5,99 4,58 4,08 1,33 - 12,56 5,20 16,99 5,56 16,61 23,97 1,64 1,49 16,54 LKB64 7,06 5,35 4,00 - - 11,55 2,63 19,70 1,46 20,21 24,84 0,70 2,51 29,20 LKB65 5,55 4,16 2,51 0,86 - 8,18 1,46 29,59 2,36 14,28 28,52 1,91 0,63 9,96 LKB66 5,86 2,28 3,86 - - 6,21 8,42 18,47 2,64 22,85 26,36 2,58 0,48 14,63 LKB67 6,09 5,54 5,46 2,52 - 7,09 1,94 19,30 2,02 10,93 37,41 0,89 0,81 17,93 LKB68 7,90 11,32 8,12 2,87 - 5,99 - 10,76 - 6,01 43,71 0,67 2,67 36,69 LKB69 6,89 8,28 3,94 8,77 - 6,01 1,82 12,17 1,09 9,26 38,13 1,87 1,76 27,43 LKB70 5,69 2,55 3,80 - - 6,29 9,02 16,70 1,40 27,06 24,33 2,38 0,77 12,20 LKB71 6,22 2,33 1,66 - - 6,65 11,77 21,04 5,80 21,93 22,61 - - 19,59 LKB73 6,48 4,85 1,53 6,63 - 23,58 - 27,13 1,57 6,81 21,43 - - 22,80 LKB75 6,58 4,48 2,47 2,56 - 13,96 - 27,70 2,95 13,49 22,82 1,05 1,94 24,00 LKB76 7,18 4,25 2,41 1,46 - 13,63 2,41 23,22 2,10 17,85 25,50 - - 30,34 LKB78 6,63 5,24 4,90 - - 3,05 4,37 22,90 - 20,04 29,36 0,58 2,86 24,64 LKB79 6,73 5,57 4,28 2,04 - 8,62 2,03 14,82 3,20 17,71 28,94 2,34 3,71 25,69 LKB81 6,42 2,38 3,31 - - 5,27 2,77 30,72 2,51 22,77 21,08 0,66 2,13 22,08 LKB82 7,90 8,23 6,28 2,13 - 1,73 - 6,61 2,57 2,51 58,47 0,17 3,41 36,73 LKB85 5,84 6,17 19,68 2,12 - 6,99 1,61 12,58 - 6,24 36,75 0,33 1,70 14,35 11G 8,70 8,05 3,48 10,70 - 0,41 - 4,93 - 10,92 36,35 5,19 11,27 42,55

* Pure rock samples, excluded from the LOI procedure


59

Appendix F: Explanatory list of different mineral phases found in forty-one XRD samples (Anthony et al., 2003).

Pseudobrookite (Psb): formed by pneumatolytic6 processes in titanium-rich basalts. It can be associated with

i.a. hematite and quartz and occurs i.a. on Mt. Kilimanjaro, Tanzania.

Quartz (Qz): second most abundant and most commonly distributed mineral in Earth’s continental crust, i.a.

occurring in sandstones, granites and less abundant in other rock types. It is part of the silica polymorph

group (i.e. Tridymite, Cristobalite,…) and is associated with many other species e.g. feldspars, carbonates.

Cristobalite (Crs): low- to high-temperature polymorph of silica (< or > 268°C), formed during a late-

crystallizing phase in basaltic igneous rocks or by recrystallization from siliceous sedimentary rocks.

Feldspathoids (Fspt): minerals in this group resemble feldspars, but have a different structure and a much

lower silica content. Their occurrence is limited to rare and unusual types of volcanic rocks and they are also

seldom found in rocks containing primary silica. Analcime and nepheline are examples of feldspathoids.

Forsterite (Fo): magnesium-rich end-member of olivine. It occurs i.a. in mafic and ultramafic igneous rocks

and can be associated with e.g. plagioclase, diopside, augite and several other minerals.

Hornblende (Hbl): consists of two end-members, namely ferrohornblende (Fe2+

-rich) and

magnesiohornblende (Mg-rich). It is generally referred to as a dark amphibole and commonly occurs in

amphibolites formed by metamorphism of basalts. Furthermore, it is also an important constituent in many

igneous rocks such as basalts, andesites and granites. It has a very widespread distribution.

Pyroxenes (Px): this group of important rock-forming minerals is abundantly present in mafic to ultramafic

igneous (e.g. basalts and gabbro’s) and metamorphic rocks. Together with olivine, they are the main

constituents of Earth’s upper mantle. Their distribution is widespread and they can be associated with

amphiboles, olivine and feldspars. Diopside and augite are examples of pyroxenes present around Lake Challa.

Muscovite (Mu): most common and widely distributed mica, occurring in igneous, metamorphic and

sedimentary regimes. It is commonly found in i.a. phyllites, schists, gneisses and granites and is mainly

associated with quartz, plagioclase and potassium-rich feldspars.

Plagioclases (Pl): this large group of minerals is part of the feldspars, which are the most abundant minerals

in Earth’s continental crust. Moreover, plagioclase represents a continuous solid solution series7 that ranges

between end-members albite (Na-rich) and anorthite (Ca-rich). They are widely distributed and occur in

igneous rocks of intermediate silica content such as diorites, andesites, granites and gneisses. Oligoclase and

andesine, both members of the plagioclase feldspar series, are mainly found around Lake Challa.

Hematite (Hem): this mineral is one of several iron oxides that occur widespread in nature. Its formation can

be the result of volcanic activity, but clay-sized hematite crystals can also occur as secondary minerals formed

by weathering processes in soil samples. Along with other iron oxides such as magnetite and goethite,

hematite is responsible for the red (lateritic) to greyish (volcanic) colour of many tropical weathered soils.

Carbonates (Cbs): this group comprises a large amount of crystals, but around Lake Challa only minor

amounts of lime, dolomite and magnesite are found (Table 1). These minerals are associated with each other

and occur in i.a igneous rocks or rocks altered by diagenesis or metamorphism. They are of minor importance

for this study.

Accessories (Acc): as the arbitrary name of this group indicates, the minerals within are accessory, implying

that their presence around Lake Challa cannot clearly be explained. As with the carbonates, they are of minor

importance for this study, yet a remarkable observation is discussed in Chapter 5. The minerals akermanite

and mayenite are included in this group and both can be the result of high-temperature alterations of

siliceous limestones.

6 A process of rock alteration or mineral formation affected by gaseous emissions from solidifying magma

(Bates and Jackson, 1984). 7 Plagioclase feldspar series: Anorthite, Bytownite, Labradorite, Andesine, Oligoclase and Albite.

variations in sedimentological properties in lake challa...

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