‘ForcingonthesalinitydistributioninthePanganiEstuary’
Final report
June 2008
Student
Wouter Sotthewes
1092383
Committee
Prof.dr.ir H.H.G Savenije
Ir. M. Mul
Dr.ir. A.D. Nguyen
Dr.ir. Z.B. Wang
CT5060
Final thesis
Forcing on the salinity distribution in the Pangani Estuary
Final Report
Final Report
June 2008
Student
W. Sotthewes 1092383
[email protected]
Committee
Prof.dr.ir H.H.G Savenije
Ir. M. Mul
Dr.ir. A.D. Nguyen
Dr.ir. Z.B. Wang
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‘Forcing on the salinity distribution in the Pangani Estuary’
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CT5060
Final thesis
Preface
In May 2007 I discussed the possibilities for my graduation project with my professor, Hubert
Savenije. Referring to our common interest to estuaries, I asked him sarcastically why he did
not choose to promote a sustainable village near an estuary, instead of the landlocked
Makanya. “The water there also flows into the ocean somewhere” was his response, and one
minute later we were checking Google Earth what it looked like. Despite the poor resolution of
Google Earth in the area, the estuary caught my interest. One hour later, I discovered a paper
suggesting increasing salinity levels in this Pangani Estuary, and my research was born.
Now it is one year later, of which four months of field campaign were spent in Pangani Town,
Tanzania, at the estuary mouth. I look back on a very turbulent period. During my fieldwork I
experienced the springtide of life, high points but also the lowest ebb. This quote should not be
taken with a grain of salt.
During my whole graduation I was supported by many people in many different ways. First I
would like to thank my graduation committee. Hubert Savenije, Nguyen Anh Duc, Marloes Mul
and Zheng Bing Wang gave me the opportunity to set up a research in an entirely unknown
area, showed their enthusiasm during the whole process and provided me with feedback.
During my field campaign in Pangani I had a lot of support from researchers that already
visited the area. Sylvand Kamugisha, Barry Clark and Hans Beuster, thanks for the support with
data and ideas. Mussima Makunga and Stephen Selelya of TANESCO, thanks for the essential
discharge data and the fantastic tour over the Pangani Falls hydropower plant. The people of
the Agricultural Office in Pangani for the precipitation data and hospitality. Wahid Suleiman,
without your boat, your experience and extensive knowledge of the Pangani river this research
would not have been possible. Without our discussions and your inexhaustible supply of
madafu and mananasi it would not have been so much fun.
In tougher times during my stay in Tanzania, I learned that people who are both literally and
figuratively close to you, are the ones that make you survive. Lisa Riedner, Ronald Bohte,
Danielle Hofboer and Tom Kopp, I do not want to know where I was without your care, and the
altruistic help of so many other people who luckily always were around me somehow.
Back in Delft, my roommates in the graduation room, thanks for the encouragement, support
and inspiring coffee breaks and lunches.
This thesis would be full of mistakes without my co-read team consisting of Pelle van der Heide,
Lisa Riedner and Jennifer Haas, thanks for all the very useful critics.
My parents and sister, I am very grateful that you each time were capable from a distance of
resigning to my decision to stay in Tanzania.
Wouter Sotthewes
Delft, June 2008
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‘Forcing on the salinity distribution in the Pangani Estuary’
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Summary
The Pangani Estuary is suggested to have been exposed to an increasing level of salt intrusion.
Research is done on the Pangani river, which drains North Eastern Tanzania from the slopes of
the Kilimanjaro and Mount Meru and mouths in the Indian Ocean. The estuary itself is however
an ungauged area.
Measurements of the salinity profile were done by means of the moving boat method. This
method measures the salinity of the water along the estuary in exactly the same tidal phase:
the boat travels with the wave celerity. Each time, the moving boat method was executed both
during high water slack and low water slack, when the salt intrusion is in its two utmost
positions.
The salinity profile in the estuary is well mixed under all conditions, however a partly stratified
profile can occur during neap tide. During springtide, the salt intrudes up to 28 kilometres
upstream. Under all tidal conditions, the first ten kilometres are saline.
Increased salinity in the estuary is suggested to be caused by a discharge decrease, erosion of
the estuary mouth, precipitation decrease, sea level rise, El Niño and tsunami events. The
influence of discharge decrease and erosion is by far the largest. Both are related to the water
use upstream. Due to hydropower dams river sediments no longer reach the estuary section.
The salt intrusion is described with a steady state model. The model unveils a phenomena that
influences the salt intrusion considerably. The estuary flows through plains with palm
plantations. These plantations start ten kilometres upstream. During high springtides these
plantations inundate partially, causing a growth in tidal prism and therefore a salt intrusion
increase under high water slack conditions. Because a lot of water does not return from the
plains but is stored in the soil, in puddles or is evaporated, also the salinity profile during low
water slack is shifted upstream. The salt intrusion length caused by inundation can be up to
twenty percent, which is even forty percent of the dynamic part of the salt intrusion.
The model results were validated by obtaining a reasonable correlation of the calibrated
dispersion from the model with the empirical dispersion relation. By means of relations of
friction, tidal damping and wave celerity it was proven that the measurements were made with
the correct velocity.
Model results confirm that the balance between tidal dynamics and morphology is broken. The
main reason for this unbalance is the lack of sediment inflow from upstream. Erosion is
expected to proceed in the future, but discharge decrease is expected to stop. The hydropower
dam guarantees a minimum flow during all seasons, preventing extreme salt intrusion due to
low discharge.
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‘Forcing on the salinity distribution in the Pangani Estuary’
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List of Symbols
A
A0
A1
Âi
a
a2
B
B0
B
C
c
c0
D
D
D0
E
E0
E
f’
g
h
h0
H
H0
Hr
Hres
Ht
K
K
LO
NR
Pt
Q
Qf
R’
rs
S
S0
Sf
t
T
Tf
Cross-sectional area
Cross-sectional area at the estuary mouth
Cross-sectional area at start 2nd bathymetry reach
Inundated surface area
Cross-sectional convergence length
Cross-sectional convergence length 2nd bathymetry reach
Stream width
Width at the estuary mouth
Convergence length of the stream width
Coefficient of Chézy
Wave celerity
Classical wave celerity
Longitudinal dispersion
Damping term
Longitudinal dispersion at the estuary mouth
Tidal excursion
Tidal excursion at the estuary mouth
Convergence length of the tidal excursion
Adjusted friction factor
Acceleration due to gravity
Stream depth
Constant tidal average stream depth
Tidal range
Tidal range at the estuary mouth
Reference water level
Water level conceptual reservoir
Threshold water level for inundation
Dimensionless Van den Burgh‘s coefficient
Strickler’s coefficient
Salt intrusion offset
Estuarine Richardson number
Tidal prism
Discharge
Fresh water discharge
Resistance term
Storage width ratio
Salinity
Ocean salinity
Fresh water salinity
Time
Tidal period
Flushing time scale
[L2]
[L2]
[L2]
[L2]
[L]
[L]
[L]
[L]
[L]
[L1/2T-1]
[LT-1]
[LT-1]
[L2T-1]
[-]
[L2T-1]
[L]
[L]
[L]
[-]
[LT-2]
[L]
[L]
[L]
[L]
[L]
[L]
[L]
[-]
[L]
[L]
[-]
[L3]
[L3T-1]
[L3T-1]
[T-1]
[-]
[ML-3]
[ML-3]
[ML-3]
[T]
[T]
[T]
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‘Forcing on the salinity distribution in the Pangani Estuary’
x
x1
Į
ǃ
įH
İ
dž
Ǐ
Ǒ
ǔ
Distance
Length of first bathymetry reach
Tidal Froude number
Dispersion reduction rate
Damping rate of tidal range
Phase lag between HW and HWS, or LW and LWS
Tidal amplitude
Density of the water
Tidal velocity amplitude
Angular velocity
Abbreviations
HW
HWS
LW
LWS
TA
High water
High water slack
Low water
Low water slack
Tidal average
Imeasures
In this thesis imeasures are used. Imeasures are images that explain
a parameter in a schematic way. In the field of estuary dynamics,
many parameters are used. Imeasures prevent confusion and enable
quick reading. All imeasures used in this thesis are based on a
schematic top and side view of an estuary.
viii
[L]
[L]
[-]
[-]
[L-1]
[-]
[L]
[ML-3]
[LT-1]
[T-1]
CT5060
Final thesis
Table of contents
PREFACE..............................................................................................................................III
SUMMARY............................................................................................................................V
LISTOFSYMBOLS................................................................................................................VII
ABBREVIATIONS.................................................................................................................VIII
IMEASURES........................................................................................................................VIII
TABLEOFCONTENTS............................................................................................................IX
1. INTRODUCTION..............................................................................................................1
2. PROBLEMANALYSIS......................................................................................................3
3. OBJECTIVE.....................................................................................................................3
4. RESEARCHQUESTIONS...................................................................................................3
5. CHARACTERISTICSOFTHEPANGANIESTUARY................................................................5
5.1 INTRODUCTION................................................................................................................5
5.2 THEPANGANICATCHMENT.................................................................................................5
5.3 GEOLOGYANDMORPHOLOGY.............................................................................................7
5.4 BATHYMETRY.................................................................................................................10
5.5 TIDALCONDITIONS..........................................................................................................13
5.6 DISCHARGE...................................................................................................................15
5.7 PRECIPITATION...............................................................................................................16
5.8 EVAPORATION...............................................................................................................18
5.9 SALINITY.......................................................................................................................19
5.10 MIXINGPROCESSES.......................................................................................................20
5.11 SEALEVELFLUCTUATIONS:SEALEVELRISEANDELNIÑO........................................................22
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‘Forcing on the salinity distribution in the Pangani Estuary’
6. METHODOLOGYOFMEASUREMENTSANDDERIVATIONS............................................25
6.1 INTRODUCTION...............................................................................................................25
6.2 MEASUREMENTMETHODSOFTIDALPARAMETERS..................................................................25
6.3 MEASUREMENTMETHODSOFBATHYMETRYPARAMETERS........................................................35
7. MODELLINGTHESALTINTRUSION................................................................................39
7.1
7.2
7.3
7.4
7.5
7.6
7.7
7.8
INTRODUCTION...............................................................................................................39
STEADYSTATESALINITYDISTRIBUTIONMODELSETUP.............................................................39
CALIBRATIONSTEPS.........................................................................................................41
RESULTS........................................................................................................................44
VERIFICATIONOFDETERMINEDINITIALDISPERSION.................................................................46
VERIFICATIONOFTIDALEXCURSION.....................................................................................47
VERIFICATIONOFSALTINTRUSIONOFFSET.............................................................................48
FORCINGONTHESALINITYDISTRIBUTIONINTHEPANGANIESTUARY...........................................51
8 CONCLUSIONS................................................................................................................53
9 RECOMMENDATIONS.....................................................................................................55
REFERENCES........................................................................................................................57
APPENDICES........................................................................................................................59
APPENDIXI LOCATIONOFMEASUREMENTS.....................................................................61
APPENDIXII EXAMPLEOFTHETIDALWAVE......................................................................63
APPENDIXIII MOVINGBOATMEASUREMENTS.................................................................65
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Final thesis
Introduction
In this thesis the salt intrusion in the Pangani Estuary in Tanzania is studied. Salt intrusion is a
dynamic process that is influenced by forcing which find its origin both inland and in the ocean.
This makes salt intrusion complex and interesting. Changes in salt intrusion affects the
environment and the economic activities in areas of the world where water is a scarce resource.
Estuaries accommodate the most populated places on earth, since they are important links
between land and ocean and an important source of food. Also estuaries hold a special
ecosystem, due to the brackish and tidal conditions, which are found nowhere else. The
multiple use made by both nature and mankind of estuaries and the fact that salinity is the key
parameter for the environment in this region, explains that salinity changes can have farreaching effects. In Africa, where water use upstream increases, and river mouths are subject
to erosion due to less runoff, estuaries are more exposed to salinity changes. In addition, the
old continent is hardly subjected to uplift, which results in less sediment availability compared
to other continents. Understanding these processes is an essential step in determining
consequences before interference in an estuarine system, and in determining causes and
solutions once salinities have changed.
This graduation work tries to get insight in all processes that influence salinity, in such a way
that their contributions can be scaled. It is a step in understanding the forcing of salinity
intrusion, and a first glimpse of how salinity intrusion can be managed.
This study focuses on an estuary that has not yet been studied thoroughly before. However the
study is applied to the Pangani Estuary, the research on salt intrusion forcing can be put in a
global context.
This report consists of nine chapters: It provides the problem analysis, the objective and the
research questions in respectively chapter 2, 3 and 4. Chapter 5 deals with an overall
description of the characteristics of the Pangani Estuary. Next, in the Methodology of
measurements and derivations chapter all measurements done during the field campaign are
discussed. In chapter 7 the salinity distribution is modelled and sensitivities on the salinity
profile are analysed. Finally, the Conclusions can be found in chapter 8 and the
Recommendations in chapter 9.
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‘Forcing on the salinity distribution in the Pangani Estuary’
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Final thesis
Problem analysis
The Pangani Estuary has been exposed to an increasing level of salt intrusion over the last
decades. Decreasing runoff from upstream due to more irrigation in the catchment and an
increasing number of hydropower dams contributed to further penetration of salinity in the
estuary mouth. Decreasing sediment supply, caused by both decreasing runoff and storage
behind hydropower dams causes erosion of the coast and estuary mouth, resulting in more
salinity intrusion too. Over the last decades the sea level of the Indian Ocean along the
Tanzanian coast rose. Extreme sea level fluctuations occurred due to El Niño, which did not
reach this region before. The (temporally) sea level rises increase the salt intrusion as well.
3.
Objective
The salinity distribution in an estuary is subject to complex forcing. From upstream, the salinity
is influenced by the discharge, from downstream by the tide. The tidal influence in an estuary is
influenced by water level, shape, friction and again discharge. The Pangani estuary is a
relatively small estuary which receives a decreasing discharge from upstream, and deals with
significant erosion and sea level changes from downstream. This research determines the
impact of these changes on the salinity distribution, and the result of that on the ecosystem.
More important, it will determine which mechanisms leading to a salt intrusion increase are
dominant. A general theory on salt intrusion will be applied to define and predict the salinity
profile.
4.
Research questions
This master thesis attempts to answer the following questions:
x
x
x
What is the current salinity profile in the Pangani Estuary and how does it vary in time?
Which forcing drives the salinity distribution what is their relative influence?
How will the Pangani Estuary respond to changes in future forcing due to mankind, and how
can the salinity intrusion be managed?
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‘Forcing on the salinity distribution in the Pangani Estuary’
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5.
Characteristics of the Pangani Estuary
5.1
Introduction
Structure of this chapter
The current situation of the Pangani Estuary characteristics are described briefly and general.
This introductory chapter is therefore formula-free and does not contain information on how
data is measured/modelled . This context is discussed in the chapters that follow: methodology
and modelling. The first paragraph contains general information on the location and definition
of the project area. Next, the estuary and surroundings will be described more precise in the
paragraphs Geology and morphology, and Bathymetry. Then the dominant tidal conditions in
the area will be described. After description of this oceanic influence, the riverine influence will
be discussed: Discharge. The paragraphs Precipitation and Evaporation follow, which together
with discharge cover all parameters for a decent water balance. The next paragraph will
introduce the salinity distribution in the estuary, logical followed by a description of the mixing
processes. Finally, several sea level fluctuations will be discussed in the last paragraph.
Estuaries can be classified on the basis of shape, tidal influence, river influence, geology and
salinity (Savenije, 2005). In each of these paragraphs this classification will be discussed,
considering the Pangani Estuary.
Except for the paragraph on the project area description, all other paragraphs describe
parameters that have their influence on the salt intrusion. Each paragraph will qualitatively
describe this influence on the salt intrusion.
5.2
The Pangani catchment
Overview
The Pangani catchment covers an area of 43,650 km2, lying mostly in Tanzania, and a small
area in Kenya. The Pangani has two main tributaries. One has its source on the slopes of the
Kilimanjaro, the other on the slopes of Mount Meru. Both these tributaries join at Nyumba ya
Mungu, a reservoir of 140km2. The Pangani River drains the reservoir, following a course of 432
kilometres to the Indian Ocean. (IUCN, 2003). In figure 5.1, the location of the Pangani
catchment is shown.
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‘Forcing on the salinity distribution in the Pangani Estuary’
Figure5.1:
ThePanganicatchment.
(editedimagesofhttp://www.multimap.com)
Primary study area
The primary study area of the estuary has a clear upstream boundary. In the river a
hydropower dam is situated at New Pangani Falls (72 kilometres upstream from the estuary
mouth). Downstream of this point no significant runoff is generated. The New Pangani Falls
plant has a drop of 170 metres, and is placed on the position of the original waterfall. It’s the
exact spot where the river flows from the highlands on the coastal plain. The hydropower
scheme of the Pangani catchment can be seen in figure 5.2.
The location of this hydropower plant makes the Pangani an ideal research area for an estuary,
because the water balance usually is not bounded this easily downstream a river.
Downstream, the Indian Ocean acts as boundary, on a distance where the interaction with the
estuary is negligible. Along the banks the whole area that still drains into the estuary is part of
the primary study area.
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Final thesis
Figure5.2:
5.3
HydropowerschemeofPanganicatchment(IUCNͲPBWO,2002).
Geology and morphology
Estuary
Although bounded by a ridge on the south side, the estuary can be considered as an alluvial
one, since shape and discharge can interact freely. This is mainly because the northern bank is
a flat plain. An alluvial estuary consists of sediments that have been deposited by both water
bodies that feed it: the river and the sea (Savenije, 2005). The north side of the river is a low
lying plain of 2500 metres wide, which becomes narrower going further upstream, also
bounded by a ridge. The ridges on both sides of the river have their influence on the position of
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‘Forcing on the salinity distribution in the Pangani Estuary’
the river, but not on its bathymetry, therefore the estuary can be considered as a coastal plain
type, however a real coastal plain is lacking.
Figure5.3&5.4: Viewonthenorthernplainoftheestuaryandthe
northernterraceoverPanganiTownandthe
northernbay(above),andthesouthernridgeand
Bwenivillage(left).
Historical information indicates that both the bay and the estuary have undergone significant
changes during the last 60 years. While the growth of the estuary has been influenced mainly
by the reduced fresh water discharges, the bay has been influenced mainly by shore erosion
induced by the high wave activity (Shaghude, 2004). The estimated rate of erosion at the
Pangani river mouth is about 7 to 20 metres per year and the observed erosion is attributed to
anthropogenic activities related with the upstream damming, by mainly the Nyumba ya Mungu
dam (see figure 5.2), which is said to stock at least half of the available sediment flux. Since
not enough sediment is replenished from upstream, the high wave activity in the estuary
results in erosion (Shaghude, 2004, 2005).
Erosion is clearly visible all along the estuarine section of the river. Since erosion is taking place
on both sides of the meandering channel, it can clearly be distinguished from a natural
rejuvenation meander process. It is in particular visible due to palms standing uprooted in the
water, some of them ‘drowned’. Erosion is here associated with increasing tidal flow due to the
enlargement of the river mouth and decreased discharges. People working on the river over the
last decade confirm rapid changes.
According to Shaghude (2004, 2005), a footpath crossing the river between Pangani and Bweni
existed sixty years ago, which was accessible during low tide. Nowadays it is impossible to walk
under any tidal conditions, since the channel is always at least three metres deep. Even
crossing the river swimming is a perilous undertaking and only possible during slack, as can be
confirmed by the author.
Widening of the channel and mouth results in deeper tidal penetration and therefore increasing
salt intrusion.
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Figure5.5&5.6: Treesunderinfluenceofbankerosion.
Figure5.7:
ElevationmapestuaryuntilNewPanganiFalls,rivernorseaonelevationscale.
(EditedDigitalElevationMapoftheCGAIRͲCSI,withrivercontoursobtainedfrom1:50.000
maps,DepartmentofLandandSurveysoftheUnitedRepublicofTanzania.Coordinatespartly
frompersonalcommunicationwithB.Clark,UniversityofCapeTown.)
ImagecanbefoundmagnifiedinAppendixI.
Coast
The coast around Pangani Bay can be described as a patched reef coast, with fossil reef
terraces and islands. An exception is the beach south of Pangani Bay, which is a cliffed patch
reef coast. Wave-cut terraces are common along the cliffed section of the shore, indicating high
wave activity (Alexander, 1966). Generally, the sand sediments dominate the 3 - 5 km coastal
strip and further offshore the silt sediments tend to be dominant. The Pangani estuary is the
largest sediment supplier in the coastal region. Therefore, the surrounding coast suffers from
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‘Forcing on the salinity distribution in the Pangani Estuary’
the reduction of sediment transport, resulting in erosion. During the fieldwork, the 28th
September 2007 springtide affected the coast in a way that it will not be restored in years. A
layer of half a metre with far developed vegetation disappeared over a width of ten metre at
least.
According to Shaghude (2004, 2005), in the 1960’s there still was one kilometre of coast in
front of the Pangadeco Hotel, with mangroves standing in between. Now, this is reduced to
about 70 metres. Since Pangadeco is located at the end of the beach, near the river mouth, this
erosion does not only affect the bay, but also the estuary it self.
Figure5.8:
5.4
CoastalerosioninPanganiBayduringspringtide.
Bathymetry
Introduction
The estuary lies in a very narrow coastal plain between a patched reef coast. The Pangani
estuary has a pronounced funnel shape. The banks converge in upstream direction. More
upstream, where tidal influence is negligible, the banks are parallel to each other. The estuary
discharges into a bay.
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Figure5.9:
Final thesis
SatelliteimageofthePanganiestuary.
(EditedimagefromNASAWorldwind,LandSat7PseudoColor)
Estuary mouth
The estuary mouth and Pangani bay have suffered from erosion over the last decades. A shore
retreat of seven up till twenty metres per year is suggested at Pangani Bay (Shaghude, 2004).
Correct and recent bathymetry is therefore hard to estimate. Available hydrographical charts
(C-Map 1996) show a mean depth of 3 metres during lowest astronomical tide. The location of
the estuary mouth is here determined as the point where on both banks the intertidal area is
immediately adjacent to non-tidal area, perpendicular to the flow. This is shown in figure 5.10
with a red line. The width of the mouth, when the bay is not included, is 330 metres. This
results in an approximate cross section of 1070m2.
The estuary mouth downstream from this defined point constantly experiences changes. The
sand bar that splits the estuary from the northern part of Pangani bay changes location due to
wind transport: constant wind from the north makes the mouth significant smaller. The spring
and neap tide cycles create different flood channels in this sand bar, resulting in totally
different stream widths when ebb an flood or spring and neap are considered.
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‘Forcing on the salinity distribution in the Pangani Estuary’
Figure5.10:
HydrographicalchartofthePanganiestuarymouth.
(EditedimagefromCͲMapWorldforWindows,Copyright©1996CͲMapNorway.)
Bathymetry along the estuary
The whole estuary section is dominated by meanders. The width of the river is converging over
the whole stretch where tide isn’t negligible. The estuary has no significant slope over its first
50 kilometre from the estuary mouth, the next 20 kilometres are characterised by little slope,
until New Pangani Falls is reached. In this section before New Pangani Falls the tide is
dampened rapidly: tidal absence results in parallel banks.
The depth is rather constant over the length of the river in the tidal area, however there are
significant local differences, but in general, there is no in- or decrease of depth over the estuary
course. This can be seen in figure 5.11. The depth over the width is very variable, since there is
a pronounced channel in the profile, which changes between banks following the river due to
its meandering. During the first moving boat measurement on the 5th of October 2007 the
location of the channel in the river was not known. That resulted in to measurements beside
the channel, explaining the deflections in figure 5.11.
TAdepthsderivedfromHWSandLWSmeaurements
Depthinmetres[m]
7
6
5
4
3
2
1
0
0
2
4
6
8
10
12
14
16
Distancefromestuarymouthinkilometres[km]
neaptide5thOctober2007
Figure5.11:
12
springtide27thOctober2007
springtide11thDecember2007
Depthsofthetidalaveragesderivedfrommovingboatmeasurements.
AveragedepthTA
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Final thesis
The stream width of the channel can accurately be obtained from satellite images. At some
points on the river the cross section was determined approximately with field measurements.
From figure 5.12 can be seen that the convergence of the stream width in both the bay and the
river can be described exponentially (see section 6.3). Also, it can be seen that the cross
section has approximately the same exponential decrease as the width in the estuary indicating
a constant depth, which can be proved analytically.
Figure5.12:
Definedwidthsfromsatelliteimagesandmeasuredcrosssectionsoftheestuary.
Creeks
Creeks connected to the main channel are generally not wider than 10 meters, although some
have a significant tidal prism, especially under spring tidal conditions when low lying plains are
submerged. People have dug smaller creeks in the palm plantations, to use them for transport
during LW of coconuts: at the mouth of the creek the nuts are collected for transport by boat.
The generally larger natural creeks are mostly found in the mangrove zone but also in lower
areas of the plantations. They are wider, sometimes navigable and of reasonable length:
creating quite a tidal prism.
Storage width
The storage width is rather constant under all tidal conditions, but during high springtides the
low lying palm plantations that start around 12 kilometres upstream are inundated, changing
the flow conditions considerably. More storage width results in a larger tidal prism, which
induces an increase in salt intrusion.
5.5
Tidal conditions
Characteristics of the tidal wave
The tidal wave that occurs in the vicinity of Pangani is very variable. At every influencing time
scale, variations are large. The tide is of the semidiurnal type. There is quite a large diurnal
inequality, the difference between spring and neap tide is enormous, because the lunar
component is dominant in the area, as can be seen in figure 5.13. The occurring wave is much
larger, due to the low depth of the reef in front of the coast. Around the equinoxes the
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‘Forcing on the salinity distribution in the Pangani Estuary’
amplitude is much larger, so also on a half year time scale variations are large. An example of
the irregular shape of this wave can be seen in figure 5.14 and magnified in appendix II.
The tidal wave has a meso-tidal influence on the shores of the estuary (Hayes, 1975). Hayes
classified the influence of the tide on the morphology compared to waves. In other words, the
high tidal range points to a dominant influence of the tide. The high wave activity is considered
to be influenced by the narrowness of the continental shelf and the presence of reef platforms
which tend to concentrate wave energy in some parts due to the effect of wave refraction and
diffraction (Shaghude, 2004).
Figure5.13:
14
Influenceofthelunartidalconstituent.Amplitudeisindicatedbycolour,andthewhitelinesare
cotidaldifferingby1hr.Thecurvedarcsaroundtheamphidromicpointsshowthedirectionof
thetides,eachindicatingasynchronized6hourperiod.
(ObtainedfromNASAGoddardSpaceFlightCentrefromtheTOPEX/Poseidonspacecraft.)
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Final thesis
Figure5.14:
Exampleofthetidalwave,during28thSeptember2007springtide.
(EditedimagesfromTotalTide™)
ImagecanbefoundmagnifiedinAppendixII.
Maximum wave
The maximum tidal wave of the year occurs at equinoctial springtide. At equinox (21st March,
23rd of September) when the earth lies in zero inclination to the sun. Then the tidal reach is
approximately 4.2 metres. This wave occurred at the 28th of September 2007, during the
measurement campaign. Since discharge is usually low in this time of the year, the tidal
penetration in the estuary is expected to be maximum as well.
Damping of the tide along the estuary
The tidal wave is hardly damped over the first downstream part of the estuary. The tidal
penetration is not expected to go further than 50 kilometres inland, as can be derived from the
bathymetry. Due to a slow elevation of the land from 40 kilometres upstream, the tide is
damped rapidly.
5.6
Discharge
Stream flow gauge
As can be seen from figure 5.2, the most downstream stream flow gauge is found near Hale:
Hale 1D17. This station is not really representative for the actual runoff in the Pangani estuary,
since the New Pangani Falls hydropower dam is lying in between. At station Hale, the mean
annual runoff is 1201 Mm3/year, based on observations over the period 1967- 1989. This
results in an average of 38 m3/s. The annual standard deviation of the flow is 431 Mm3/year,
so there are very variable flow conditions (Beuster, 2006). Recently, this discharge station was
relocated upstream the Hale hydropower plant, making it now even less representative for the
downstream area.
Changes in runoff upstream
The discharge of the Pangani has undergone quite some changes due to the construction of
hydropower dams and increase of water use for irrigation in the basin. Inspection conducted by
15
‘Forcing on the salinity distribution in the Pangani Estuary’
the Pangani Water Basin Office between 1992 and 1993 showed that the actual water
extraction for irrigation purpose is about 48 m3/s or even more (Mbonile, 2005). This number
compared with the runoff downstream shows that major changes in runoff have occurred over
the last decades. More representative discharge data can be obtained from the turbine
discharge of the Pangani hydropower plant, which was constructed in 2001. Over the last three
years (2005-2007) the average discharge was 21 m3/s: considerably less. Besides less
discharge since the establishment of the hydro power plant, the seasonal effects are flattened.
This is caused due to storage at the Nyumba ya Mungu hydropower dam, which now also
guarantees that the more efficient 170 metres drop of New Pangani Falls plant has flow all
seasons as this plant has no storage itself.
Averagedischarge Q[m3 sͲ1 ]
Dischargebeforeandafterhydropowerplant
100,00
80,00
60,00
40,00
20,00
0,00
jan
feb
mar
apr
PanganiFalls2005Ͳ2007
Figure5.15:
may
jun
jul
aug
sep
oct
nov
dec
Halemodelledflow1929Ͳ2004
DischargedataHaleandNewPanganiFalls.
(HaledataobtainedfrompersonalcommunicationwithH.Beuster,UniversityofCapeTown,
PanganidataobtainedfromTANESCO,HaleOffice.)
5.7
Precipitation
Introduction
Since the studied area is located near the equator in the Inter Tropical Convergence Zone
(ITCZ) precipitation is dominated by two monsoon seasons. The south-east monsoon (Kusi)
lasts from April to September, the north-east monsoon (Kaskazi) lasts from November to
March. The Kusi brings the strongest wind and rainfall (UN 2001). In contradiction to the
mainland, precipitation is present during the whole year along the coast. The two rainy seasons
are dominant. The Vuli (short rainy season) starts half October until December and the Masika
(great rainy season) lasts from April to May.
Precipitation analysis
In the research area two rainfall measuring stations are available. One is located in Pangani
itself, near the river mouth. The other one is in Hale, just upstream the New Pangani Falls
plant, forty kilometres from the ocean in a straight line. The locations of the precipitation
stations can be found in figure 5.7.
16
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Final thesis
Yearlyprecipitationwithtrends
Yearlyprecipitation[mm]
2400
2000
1600
1200
800
400
0
HalePlantations 1940Ͳ 1970
PanganiAgriculture1971Ͳ 2007
HalePlantations 1971Ͳ 2007
Lineair(PanganiAgriculture1940Ͳ 1970)
Lineair(HalePlantations 1940Ͳ 1970)
Lineair(PanganiAgriculture1971Ͳ 2007)
Lineair(HalePlantations 1971Ͳ 2007)
y=2,078xͲ C
y=2,785xͲ C
y=Ͳ7,814x+C
monthlyaverageprecipitation
monthlystandarddeviationprecipitation
300,0
bivariatelinearcorrelation
1943Ͳ 1961
250,0
200,0
150,0
100,0
50,0
1
140,0
0,9
120,0
correlationcoefficient [r]
monthlySDprecipitaiton [mm]
160,0
100,0
80,0
60,0
40,0
20,0
0,0
0,0
jan feb mar apr may jun jul aug sep oct nov dec
PanganiAgriculture
Figure5.16:
HalePlantations
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
jan feb mar apr may jun jul aug sep oct nov dec
PanganiAgriculture
HalePlantations
0
year
jan
feb
mar
apr
may
jun
jul
aug
sep
oct
nov
dec
y=Ͳ10,41x+C
averagemonthlyprecipitaiton[mm]
2005
2000
1995
1990
1985
1980
1975
1970
1965
1960
1955
1950
1945
1940
PanganiAgriculture1940Ͳ 1970
PrecipitationdataPanganiEstuary1940–2007.
From the precipitation analysis in figure 5.16 of the two stations can be concluded that the
rainfall is even distributed over the catchment downstream of New Pangani Falls. These two
stations situated at the outer corners of the area have a rather good linear correlation, while
the coastal area here is known for its high variability of rainfall. With a double mass analysis
can be seen that the stations correlate over the whole time series. Both stations show a trend
of decreasing precipitation over the measured period 1940 - 2007. The Spearman’s rank test
over the full series shows that this trend is significant. When the series are cut in 1970, as
shown in the figure, even a stronger trend can be observed over the period 1940 - 1970. In
1970 a reverse of the El Niño Southern Oscillation anomalies in the Atlantic and Western Indian
Ocean occurred, leaving a relative warmer Western Indian Ocean and a different precipitation
pattern (Trzaska 1996, Valimba 2005). If trends are analysed on these time scales, a much
stronger downward trend is seen until 1970, even with decreases of 10mm per year. After 1970
however, precipitation is rather stable. This shows a different expectation for the near future:
on yearly basis no trend is present.
On a yearly time scale the seasonality is clearly visible, especially the Masika. Monthly trend
research show that especially outside the raining seasons the precipitation decreases:
February- March and August – September are responsible for the rainfall decrease. Further it
must be noticed that the precipitation is very variable, as can be seen from the standard
deviation. The peak of October at the Pangani station is due to the El Niño event in 1997, there
are no measurements from Hale of this year.
17
‘Forcing on the salinity distribution in the Pangani Estuary’
Influence on the estuary
The precipitation has only direct influence on the estuary when falling directly in the catchment
downstream of New Pangani Falls. Otherwise, it will only be considered as discharge. Even with
the current low discharges at New Pangani Falls and the relative big catchment of the estuary,
precipitation does not generate a significant discharge on a longer timescale in the estuary. It
does however, when shorter rainfall events are analysed: heavy rain showers result in
significant discharge in the estuary, and influences salt intrusion.
5.8
Evaporation
Introduction
Evaporation is not measured in the region. Since evaporation depends on many variables which
are not measured in the direct region either, it is hard to determine the correct evaporation.
Here two methods are used to give a reasonable estimation.
Penman
The Penman equation makes use of the maximal day temperature, the minimum, the humidity
and the hours of sunshine. Most of this data is not available, but estimates can be made.
The Food and Agriculture Organisation of the UN has average global estimates for reference
evaporation per month over the period 1961 - 1990. This data is based on spatial information
for prediction that is calibrated afterwards with measurements on land.
Monthlyprecipitation/evaporation [mm]
The results of filling in the Penman equation with estimated parameters and the outcome for
the region from the FAO is plotted in figure 5.17. Both lie more or less in the same range.
Further can be noticed that only during the Masika, precipitation exceeds potential evaporation.
Monthlyevaporation
300,0
250,0
200,0
150,0
100,0
50,0
0,0
jan
feb mar
averageprecipitation
Figure5.17:
18
apr may jun
Penmann
Estimatedevaporation.
jul
aug sep
oct
nov dec
FAOglobal1961Ͳ 1990
CT5060
5.9
Final thesis
Salinity
Introduction
All the estuary characteristics that have been discussed until now, have effect on the change of
salt intrusion. Since many of these characteristics cannot be considered constant, both over
(long) time and space, the salt intrusion is expected to change as well. The ocean salinity
ranges between 34 until 35.2‰ in the area (Nyandwi, 2001). During the measurement
campaign, no higher salinity than 32‰ was measured inside the estuary. Going further
upstream the estuary, the salinity decreases.
Current salinity distribution in the estuary
The salinity distribution in the estuary is dynamic, since it depends on the tidal condition
especially, but also on the runoff and precipitation. Overall during spring tide the salinity profile
is well mixed, while during neap tide the salinity shows a partly stratified profile. Examples can
be seen in figure 5.18 of the neap tide of October 5th 2007 and the spring tide of October 27th
2007.
Figure5.18:
Measuredhaloclinesintheestuaryduringresp.LWSandHWSatOctober5th2007neaptideand
th
LWSandHWSatOctober27 2007springtide,xͲaxiscontainsstation#asshowninfigure5.7.
19
‘Forcing on the salinity distribution in the Pangani Estuary’
During well-mixed conditions (non-neap tide conditions), the salt intrusion curve can be
classified as a bell shape. According to (Savenije, 2005) this curve belongs to an estuary with a
trumpet shape. The dome shape is the ‘type 2’ shape in the figure below.
Figure5.19:
Typesofsaltintrusioncurvesscaledtosaltintrusionlengthandoceansalinity.
Change in salt intrusion
The main direct indication on changing salt intrusion on long term that is available now is the
retreat of crocodiles in the river. They cannot withstand brackish conditions and therefore
moved upstream in the estuary, from Kimu up to Kumba Mtoni, over the past 60 years
(Shaghude, 2004). Measured by means of satellite images, this is a distance of 16 kilometres
upstream, along the axis of the river. On the scale of the total estuary, this is a significant
distance.
Another example is the pumping station, Masjini Maji, at Kibinda. This water pumping station,
built in colonial times for the plantations lying on the southern ridge of the river, is lying 16
kilometres upstream, and would be taking saline water 50% of the time, in case it still worked.
At the banks near Kibinda, the German settlers planned a sugarcane plantation before they
were replaced by English colonialists, of which some buildings remain. Sugarcane does not
withstand the saline environment that the region experiences now.
5.10 Mixing processes
Introduction
In an estuary various mixing processes create the actual salt intrusion as it is. Mixing of water
is the mechanism through which salt travels upstream. Without mixing, the same amount of
salt entering during high tide would leave the system during low tide.
Causes of mixing
Mixing in an estuary is caused by three main driving forces: the tide, the river and the wind:
The tide
The tide is probably the most important source of mixing. Savenije (2005) described seven tidal
mechanisms that induce mixing:
x Turbulent mixing at small spatial and temporal scales.
x Tidal shear between streamlines with different velocities.
x Spring-neap interaction.
x Trapping of water on tidal flats and in dead ends.
x Residual currents in the cross section.
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x
Final thesis
Residual currents over tidal flats and shallows.
Exchange between ebb and flood channels that meet and mix at cross-over points.
Savenije (2005) also states that the last mechanism is dominant in the downstream part of
estuaries with a dome-shaped salt intrusion curve. This is also valid for the Pangani Estuary. By
means of floats and by checking the location of foam lines, one can distinguish ebb and flood
channels during the period of HWS and LWS. Pictures of the foam lines can be seen in figure
5.20 and 5.21.
This mixing process works as following: The main channel cuts corners in the meandering
course. During HWS or LWS (in this example HWS is used, see figure 5.22) the flow direction in
the channel turns. But because the velocity profile in the depth is not constant but zero at the
bottom and maximum at the surface, the deeper main channel turns its flow direction later,
since it has a higher starting velocity, and more momentum. Now, while the main channel still
acts as a flood channel, the shallow outer curves already turned their flow direction, and act as
ebb channel. In between two curves of opposite direction the two channels need to cross. This
is where the dominant mixing occurs. The cross over points are clearly visible on the water
because the foam lines are cut off here, on these dead ends of the foam lines a lot of debris is
accumulating.
Figure5.20&5.21:
Figure5.22:
PicturesoffoamlinesseenfromthecliffduringLWS.
CrossͲovermixingduringHWS.
In Pangani Estuary, another mixing process that shows dominant behaviour, and is not
explicitly described in the seven mechanisms of Savenije (2005), is the opposite direction of
flow in creeks during LW. In Pangani Estuary, creeks generally drain in the upstream direction.
21
‘Forcing on the salinity distribution in the Pangani Estuary’
During HW, this causes water to flow ‘around the corner’ which does not cause a lot of extra
mixing. During LW however, the flow directions collide, causing turbulent flow conditions where
a lot of energy is dissipated.
Figure5.23:
CollidingflowsduringLWatacreekdrain.
The river
The river provides the estuary with fresh water, which drives a vertical gravitational circulation.
This is an important mechanism, especially where the longitudinal salinity gradient is large
(Savenije, 2005). For an estuary with a dome shaped salt intrusion, this is in the middle
section. Since the Pangani Estuary usually has low discharge conditions, this mechanism is
expected not to be dominant.
The wind
Wind drives both horizontal and vertical circulation of the water. Due to wind set-up, water is
horizontally replaced over the surface layer with the direction of the wind, under which a
bottom layer returns water due to gravitational flow. In this circulation, the surface water layer,
which is less saline (in case of some stratification) mixes with the more saline bottom layer.
Mixing induced by wind is expected to have its influence on the Pangani Estuary near the
mouth, since all parameters that introduce wind set-up are present: There is during day time a
moderate wind, due to the ever occurring difference in land and ocean surface temperatures.
There is in the direction of the wind (from the ocean) a significant fetch length in the bay and
mouth, and finally, over this fetch length relative shallow water is found. Further upstream no
significant fetch length is reached due to meanders and shelter of vegetation on the bank
Overall mixing by wind is less important than the other two mechanisms, but during neap tidal
conditions in the mouth, when tidal mixing is less present, mixing by wind certainly will be
significant.
5.11 Sea level fluctuations: sea level rise and El Niño
Introduction
Because sea level fluctuations immediately influence the bathymetry and tidal conditions, they
have to be taken in account in this section. Many sea level inducing factors are present in the
Western Indian Ocean, but they have in common that not much is information is available,
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Final thesis
since long time series of sea level data are lacking in the whole region. In this paragraph,
overall sea level rise and temporal rise due to El Niño will be discussed.
Long term sea level rise
For this study, the interest lays in relative sea level rise so the combination of land and water
movement. The only available information as estimate on the current relative sea level rise is
approximately 3mm/year (Gable, 1991). As already stated, a changing sea level has direct
impact on the bathymetry. The impact on salt intrusion is described by Uncles (2003) for San
Francisco Bay, also for a sea level rise of 3mm/year. According to Uncles (2003), the sea level
rise has four possible consequences: Reduced friction on the tidal currents, due to deeper
water, resulting in higher velocities, or decreased tidal currents due to larger cross sections
under a constant tidal prism. The latter is less likely in the Pangani Estuary, since plain levels
upstream are so low that the tidal prism grows at least proportionally with the sea level. As
other consequences Uncles (2003) states an increase of gravitational currents as a
consequence of deeper water which leads to increased salt intrusion. Finally, flooding of low
lying plains due to sea level rise has impact on the salt intrusion.
When of an estuary or inlet the effects of relative sea level are considered, it is essential to
compare the time scale of the sea level rise with the one of the responding sediment regime.
Since the Pangani Estuary already is sediment scarce, and sea level rise leads to an even larger
sediment hunger, effects can be relatively large.
El Niño, new phenomenon along the Tanzanian coast
In 1997 - 1998 El Niño dominated the climate along the Tanzanian coast. It had a major impact
on the coastal morphology, the ocean salinity and the mean sea level, as can be seen in figure
5.24 (Nyandwi, 2001). For this reason, the El Niño effects cannot be neglected in this study.
Along some coastal stretches the El Niño rains caused accretion of the coast, thanks to
sediment supplies of the rivers. At Pangani however, most sediments do not reach the beach,
due to the hydropower dams, but the coast and estuary do have to cope with the periodical sea
level rise, and the erosion associated with it. Extreme precipitation and runoff in 1997 led to an
inundation of the upstream palm plantations of 1.5m, flood marks of brown mud against the
stem were visible for years. Large debris destructed boats in the vicinity of Pangani Town.
Figure5.24:
InfluenceofElNiñoonmeansealevel,asmeasuredatZanzibar(UN,2001)
23
‘Forcing on the salinity distribution in the Pangani Estuary’
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Final thesis
6.
Methodology of measurements and derivations
6.1
Introduction
Structure of this chapter
In this chapter first all tidal parameters and the methods that will be used to measure them will
be introduced in paragraph two, in ranking of how the measurements were done in time. In
paragraph three the parameters on bathymetry will be discussed in the same way. For every
parameter, there is an elaboration of the measurement accuracy.
This chapter uses imeasures, images to explain approximately what the parameter is about, to
enable quick reading. They show a schematic estuary, with the behaviour of the parameter in
it.
6.2
Measurement methods of tidal parameters
Phase lag
The phase lag İ of the tidal wave is the time between respectively HW
and HWS and LW and LWS, or in other words, the time between the
maximum amplitude of the tide and the moment of zero flow. The phase
lag depends on estuary shape and is therefore not necessarily constant
along the estuary. The phase lag in an alluvial estuary lies between 0
and ½ S. If the phase lag is 0, a standing wave occurs, if the phase lag
is ½ Sa progressive wave occurs. The first has the characteristic that
HW coincides with zero flow and TA with maximum flow, the latter that HW coincides with
maximum flow, and TA with zero flow. Both extremes do not occur in alluvial estuaries, a mixed
wave occurs. If the phase lag is known, it is easier to determine the slack moment. This is
practical for the timing of salinity measurements, which have to be done during slack.
The phase lag measurement can be done approximately from a bank by first measuring the
time of the HW or LW moment, and then the HWS or LWS moment.
The HW or LW moment can be measured at a sheltered location where wave activity is low. By
simply placing sticks on the waterline, the moment of high or low water can be defined. This is
done by measuring the horizontal location of the waterline. This has as disadvantage that it is
more sensitive for waves, but when measured in a (artificially created) sheltered location, the
accuracy is larger since, given a normal bank slope, during a tidal period at the bank the
horizontal displacement of the waterline is larger than the vertical. This method only works for
defining the moment of HW or LW, to define the tidal range or amplitude, a different approach
should be used. Here, this simple procedure suffices.
The moment of HWS or LWS is difficult to determine without a bridge. The Pangani estuary has
a large tidal range; therefore the slack moment is easier to see. Since there are buoys in the
estuary, they can be helpful estimating slack, as they change position during slack (Haas 2007).
The large tidal range causes slack to occur not instantaneous over the width. Often foam lines
mark two completely distinct channels flowing in opposite direction. An extra problem that
occurs in the Pangani Estuary, is that there is nearly always wind. Due to temperature
25
‘Forcing on the salinity distribution in the Pangani Estuary’
differences of the ocean and the land, the wind comes from sea during day time and from land
during the night. This causes wind waves and flow, making it difficult to determine the slack
moment accurately by buoy or float.
During slack moments in conditions without wind, the best measurement method from the
bank of the river proved to be a double float system. Betel nuts are yellow, submerge almost
completely (minimizing wind influence) and can be thrown away far, making them ideal floats.
If two floats (or more) are thrown in one line from the observer on different distances,
perpendicular to the flow, not only the movement relative to the observer can be seen, but also
their mutual movement. Since slack occurs first near the banks, and then in the middle of the
stream, more float points give an idea of the flow distribution over the width. The flow can then
approximately be extrapolated, and the average slack moment can be estimated. With this
method, it is important to realize that when the water on the surface slacks, the average slack
over depth already took place. Due to the velocity profile over the depth, slack occurs the latest
on the surface. This is the main reason why the phase lag needs to be known before starting a
moving boat method. If one waits until slack occurs on the surface, and starts to depart then,
the measurement takes place too late.
Figure6.1:
Betelnutmethodfordeterminingslack.
Tidal range
The tidal range (H) is the difference between the ebb and flood level.
The tidal range varies in time. Along the estuary the tidal range can
be amplified and damped due to the bathymetry.
To measure the tidal range a quay with a near-vertical wall is ideal.
Relative to the top of the quay the water level can be measured with
a certain interval, resulting in the tidal range. The quay along Pangani
is not appropriate, since the channel is not deep enough next to it: it falls dry during each tidal
cycle. The only available stable reference points in the water all the time are the leftovers of a
200 years old Omani slave pier. These columns were all marked with a reference level on the
same height. During HW, the last columns cannot be reached, during LW the first fall dry.
During neap tidal conditions, the last pillars keep their feet in the water, and a measuring tape
is sufficient to measure the tidal range. During spring tidal conditions, also the last column falls
26
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Final thesis
dry. Now, the reference level is extended with a horizontal held rope, checked with a spirit
level, and from this rope down, the water level is determined. By doing more measurement at
one time on different locations, it was found that this method is sufficiently accurate.
Figure6.2&6.3: ColumnsduringLWandHWconditions.
Figure6.4:
Referencelevelextensionwitharope.
27
‘Forcing on the salinity distribution in the Pangani Estuary’
Figure6.5:
MeasurementlocationseenfromMashado.
A difficulty with measurements of stage are waves, which are often present due to the constant
wind. The best results are obtained by holding the measuring tape on the expected water level,
check this for the period of at least 30 seconds, to prevent the influence of wave clusters. The
actual water level is fixed at one third of the wave height. Then, the measuring point is
submerged half of the time, when held in correct position. A reasonable accuracy can be
reached, as long as all measurements are done by the same observer. It must be noted
however, that the uncertainty that waves introduce is dealt with much better then when
measuring takes place from a bridge.
The measured results were compared with the Total Tide™ prediction model, as shown in
figure 6.6. It can be noticed that the measured tidal range is consequently smaller than the
predictive model. This is probably due to the fact that the model resembles the tidal range in
the bay, while the measurement location is up to four kilometres upstream from this point, the
tide is then already damped a bit. The difference in the obtained TA levels are probably not due
to the seasonality of the mean sea level but due to the differences in wind set up.
28
CT5060
Figure6.6
6:
Final thesiis
Tidalrangemeasureementscomparredwithapredictivetidalmod
del.
Tidal pe
eriod
The starrt of the field
d campaign was
w affected by a changin
ng tidal perio
od. Until then
n, it was
thought that it was constant,
c
butt it varies witth the spring
g-neap cycle.. During neap
p tide, the
period iss an hour lon
nger than during springtid
de. Due to ch
hanging relative influence of sun and
d
moon co
omponents, the
t tidal period changes. This behaviour is confirm
med by the T
Total Tide™
tidal pre
ediction mode
el, however it
i is overestim
mated here. Results of th
his model are
e shown for a
full fortn
nightly cycle in the figure
e below.
Figure6.7
7:
Durattionoffloodan
ndebbbasedontheTotalTide
e™predictionm
model.
Knowled
dge on the tid
dal period is essential, be
ecause if tida
al periods are
e not known, the tidal
cycle cannot be extra
apolated. Exxtrapolation iss essential fo
or the planning of (nightly)
ement campa
aigns.
measure
29
‘Forcing on the salinity distribution in the Pangani Estuary’
Wave celerity
The wave celerity (c) is the speed of the tidal wave along the
estuary. This celerity is not constant but depending on the damping
rate, so the wave celerity is influenced by the bathymetry.
According to Savenije (2005) the wave celerity can be described with
the following implicit relation:
1
1
c2
gh
rs
1D
(6.1)
Where c is the wave celerity, rs is the storage width and h the average stream depth. The
damping term (D)is defined as following:
X sin H ·
§1
f'
c sin H cos H ¨© b
sin 2H § c
R'·
hc ¸¹
D
¸
¨
1D
2(1 D) © Zb Z ¹
Z
(6.2)
Where İ is the phase lag, ǔ is the angular velocity obtained from the tidal period, b is the
stream width convergence length, f’ is the adjusted friction factor, Ǒ is the tidal velocity
amplitude and R’ the resistance term. The dimensionless Tidal Froude number ɲisdefinedas
following:
2cX sin H
D
gH0
(6.3)
Where H0 is the tidal range at the estuary mouth.
The wave celerity can be obtained in different ways. A good estimation can be made by
determining the time of HW or LW and measure the lag on a place upstream. If the distance is
known between the two points, the wave celerity can be calculated. This demands travelling
along the river with the wave celerity. This measurement can be done in combination with
phase lag measurements. However, measurements at two locations result in only one wave
celerity, so if any information is wanted on the progression of the wave celerity, at least three
measurement locations are needed. When determining the wave celerity, one has to be careful
with the consequences of deformation of the tidal wave. Due to tidal asymmetry, wave
celerities can be obtained that are not representative. This can be prevented by measuring
three moments in a row, for instance LW/LWS, HW/HWS and again LW/LWS. The Pangani
might cause tidal asymmetry due to the relative low depth compared to the tidal range.
Organising a measurement at two points is complex, because another location where a
measurement takes place has to be found, and more people are needed to do the
measurements. In the Pangani Estuary only one good wave celerity measurement was made on
the 12th of December 2007, one day after springtide. On this day measurements took place at
the Omani slave pier in Pangani and 13.4 kilometres upstream near Kumba Mtoni. At this spot,
a straight betel nut palm stem was attached to an enormous mango tree that had fallen into
the water. On the stem a reference was drawn. At both measurement stations, which are
shown in figure 5.7, the moment of HW and LW was determined. From these measurements
the wave celerity during HW and LW was determined. The celerity during HW is higher since
the friction is lower during higher water levels.
Since one measurement is rather uncertain, an attempt was made to derive the wave celerity
from the moving boat measurements. During these measurements, the boat moves upstream
30
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Final thesis
with the wave celerity because all measurements have to be done at all locations during HWS
and LWS. Since all times and locations of the measurements are known the celerity can be
obtained. All these results are plotted in the figure below, together with the actual celerity
measurements.
Some remarks can be made on basis of these plots. First with regard to the measurements of
the author, it can be seen that all HWS and all LWS measurements coincide with each other
clearly, and that the celerity during HWS indeed is higher then during LWS. More important, it
can be seen that the celerity measurements perfectly fit on this line. The measurements of the
estuarine survey team as part of the Flow Assessment Component of the Pangani River Basin
Management Project (IUCN - PBWO, 2007) in May are much slower. This may have to do with
the fact that they made more measurements per depth profile.
Figure6.8:
Wavetraveltimederivedfrommovingboatmethod.
From the wave travel times in figure 6.8 it can be noticed that the measured travel times are
half proportional to the classical wave celerity. If that relation is applied on equation (6.1), and
the storage width ration is considered as unity, a value for D of -3 is found. With equation (6.2)
it is now possible to determine the resistance term R’, since all other variables are known if the
tidal range of the 11 December springtide is used, and the velocity amplitude is estimated on
1 ms-1. With the following equation (6.4) the amplitude to depth ratio adjusted friction factor f’
can be determined. From the equation of the adjusted friction factor (6.5), the Chezy
roughness coefficient C can be determined (Savenije, 2005).
X sin H
Rc
fc
c
hc
(6.4)
fc
g
C2
2
§
§K· ·
¨1 ¨ ¸ ¸
¨
© h ¹ ¸¹
©
1
(6.5)
Where dž is the tidal amplitude.
31
‘Forcing on the salinity distribution in the Pangani Estuary’
By means of this method, a Chezy coefficient C of 55 m1/2s-1 is found, or a Strickler coefficient K
of 42 (-). This is a rather smooth but representative value for a natural channel.
Salt intrusion length
The salt intrusion length is defined as the point upstream where the salinity
still is influenced by the ocean. The salt intrusion length depends on the
phase of the tidal cycle and moves along the estuary with the tidal
excursion. The salt intrusion is also influenced by the discharge.
The salt intrusion length can be measured by measuring the conductivity in the stream. The
salt intrusion length is changing in time, during each tidal cycle with the length of the tidal
excursion, but also due to discharge and water level changes. With trial and error the salt
intrusion can be determined approximately, so that an estimation can be made over which
length of the estuary full salinity profile measurements have to be made. This is however quite
a distance to travel, and these locations can only be reached by boat. Therefore, no indication
was made beforehand. An indication of the salt intrusion length was first obtained with a neap
tide salinity profile measurement by moving boat method.
Tidal damping
The tidal damping (įH) (or amplification) is a measure for the
decrease of the tidal range.
According to Savenije (2005) the tidal damping can be described
with the following relation:
H H0 ˜ exp x ˜ GH (6.6)
Where H is the tidal range, H0 the tidal range at the estuary
mouth.
The tidal damping both has a linear and an exponential component (Savenije, 2005) and its
behaviour is therefore difficult to determine over the whole estuary.
To measure the tidal damping, the tidal range has to be measured at a few locations during
one tidal cycle, since different tidal cycles hardly can be compared due to the diurnal inequality
and large spring- neap tide differences. This happened during the 12th December 2007
springtide which was described for the wave celerity. Over the distance Pangani – Kumba Mtoni
a damping coefficient įH of -10x10-6 m-1 occurred. This is however a point measurement, due to
the geography the tidal damping is not constant. Especially a bottom slope will result in more
rapid damping.
According to Savenije (2005) an ideal (without tidal damping or amplification) the following
relation is valid:
1 R'
b
c
(6.7)
With R’ determined as in the wave celerity section in this paragraph, it follows that the left term
with 74,6x10-6 m-1 is smaller than the right term with 110,9x10-6 m-1, this also indicates small
damping.
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Tidal reach
The tidal reach is the point where the flow of the river is still
influenced by the tide; it is the length that the tide penetrates into the
estuary. The tidal reach depends on the tidal range, so during
springtide the tidal reach reaches its maximum.
The tidal reach is measured most accurate during the tidal phase in
which the highest velocities occur. When the actual tidal range is not
significant anymore and cannot be measured, the flow can still be a
good indicator. The flow still has to be distinguished from the normal river flow. This is easy
during flood with low discharge conditions, but if the flow is only a bit tempered or accelerated
by the tide, it cannot be distinguished. Summarising, the best moment to determine the tidal
reach is during flood when the highest velocities occur. This moment depends on the phase lag
and will be somewhere around TA after LW.
Since the area where the tidal reach takes place is hardly accessible and the parameter does
not have direct influence on the salt intrusion, it was not researched further. Important
information is that if the tidal damping that was measured is extrapolated upstream, this would
mean the tidal wave would reach New Pangani Falls. This is however not the case, the tidal
wave is damped around fifty kilometres upstream, where the bottom slope starts as can be
seen in figure 5.7.
Tidal excursion
The tidal excursion (E) is the distance travelled by a water particle in the
estuary between LWS and HWS. The tidal excursion is inclined to be constant
along the estuary, but in estuaries where a nearly standing wave occurs, the
tidal excursion may decrease further upstream. It is also possible that the tidal
excursion decreases upstream due to friction or water loss outside the
channel. The tidal excursion can be influenced by the bathymetry.
The tidal excursion can be computed by integrating a sinusoidal velocity yielding twice the
velocity amplitude (X) divided over the harmonic constant (Savenije, 2005).
2X
E|
Z
(6.8)
The tidal excursion can be defined with floats, but this is a time consuming procedure. Another
way to determine the tidal excursion is to compare the salinity profile during HWS and LWS,
this procedure will be explained under the header ‘salinity distribution’.
Tidal prism
The tidal prism (Pt) is the flood volume that enters and leaves the
estuary during one tidal cycle.
The tidal prism is the integrated flow over one tidal cycle, which at
the mouth can be approximated with the product of cross section
and tidal excursion.
HWS
Pt
³ Q 0, t dt | A E
0
0
(6.9)
Where Q is the discharge, A0 is the cross-sectional area of the estuary mouth and E0 is the tidal
excursion at the estuary mouth.
LWS
33
‘Forcing on the salinity distribution in the Pangani Estuary’
The tidal prism can also be defined with the tidal range, the tidal damping and the phase lag
(Savenije, 2005).
H0Bb
Pt
cos H 1 GHb
(6.10)
Where B is the stream width.
Both relations should give a comparable result if all parameters are defined in a proper way in
comparable circumstances.
In the Pangani estuary, the tidal prism does not behave linear with the tidal range, since at
certain spring tides conditions the coconut and betel plantations are inundated, which causes
an enormous increase in the storage capacity, and in a variable estuary surface. Integration
over the tidal cycle is not possible because the cross section cannot be measured continuously.
Therefore, an accurate estimation of the tidal prism cannot be made.
Interaction of tidal prism and tidal excursion
Disproportional growth of the tidal prism due to inundation results in a not constant tidal
excursion both in time and space, and for a not constant tidal damping in time and space. The
inundation of storage width results in the bend in the schematic relation between the initial
cross section and the tidal prism in figure 6.9. This means that a reasonable estimate of the
tidal prism cannot be made with the available formulas. Since this now becomes a modelling
problem more than a measurement problem, it will be dealt with in the next chapter.
Figure6.9:
Schematicplotofbehaviouroftheinitialcrosssectionandthetidalprism.
Salinity distribution
The salinity distribution is the salinity profile along the estuary. It
starts with the ocean salinity, and ends where the ocean does no
longer influence the salinity.
The salinity distribution changes during a tidal cycle, therefore a
good profile can only be obtained by measuring the whole estuary
in the same phase of the tidal cycle.
The measurement starts with a fast boat that waits in the estuary mouth at a point that is
defined on beforehand until it is HWS. At this moment, the conductivity meter is lowered to the
34
CT5060
Final thesis
bottom, the depth is measured, and next the vertical salinity profile is measured. After that, the
boat moves quick to further upstream to the next defined point, where it awaits HWS again, to
do the same measurements again. This procedure is repeated until no significant salinity is
measured anymore. Then, the boat returns to the estuary mouth, waits until LWS, and does
this procedure again. When the result is plotted, two similar salinity profiles occur, the plots are
shifted, the distance between them is the tidal excursion.
For the measurement locations the measurement stations of the estuarine survey team as part
of the Flow Assessment Component of the Pangani River Basin Management Project have been
used. As a result the measurements could be easily compared, and the locations are easily
recognisable and well-distributed.
The two most important pitfalls of the moving boat technique both have to do with timing.
First, the moment of actual slack is hard to determine, but a too early or too late start will
immediately lead to a lower salinity value measured at HWS or a higher at LWS, and therefore,
also a shorter tidal excursion will be obtained. The second pitfall is the timing between
observations. As described above, the boat velocity should be the same as the wave celerity.
During springtide, it is a challenge to reach this speed, and to check whether the maintained
velocity is indeed right. Further upstream, where many water hyacinths flow on the water, it is
easier, since flow is easily detected. Combination of the two pitfalls is likely to occur and
problematic for the obtained data. Especially during HWS, if the boat departs too late, the time
error will grow along the way, because once the tide is turning, the boat has to move more and
more against the flow, resulting in even more delay, and with that resulting in a measurement
error of a relatively large tidal excursion convergence length. During LWS, if the boat departed
too late, the boat is supported by the tide that also runs up the river, and may therefore be
able to ‘get back in the race’. This however leads to the diminishing of the tidal excursion
convergence length, except for a wrong initial tidal excursion. The essential indicator for a good
moving boat measurement is a large tidal excursion relative to the tidal range, because all
timing errors lead to smaller tidal excursions.
Other things that may go wrong are depended on the location of the measurement within the
width of the stream. By measuring in the main channel, not only is guaranteed that the full
depth profile is measured, but also it is more likely to have more or less the same flow
conditions (residual flow) as on other locations. Measuring a profile is time consuming,
especially because it takes some time to stop the boat entirely. If the channel is not found on
first location, there is no time for a second trial, because it then is impossible to keep
measuring with the wave celerity.
The measurements of the moving boat method can be found in Appendix III.
6.3
Measurement methods of bathymetry parameters
Parameters to measure
Below, all bathymetry parameters that were measured during the field campaign are described
briefly, and the method of measuring is explained. Since many tidal parameters are very
sensitive to bathymetry, it is essential to define them properly, and their influence on salinity
intrusion.
35
‘Forcing on the salinity distribution in the Pangani Estuary’
Course of width, cross section and depth
The shape of an estuary cannot be adequately described as a prismatic
channel. According to Savenije (2005), alluvial estuaries have a shape
where both width and cross section vary exponentially with the distance.
When the positive x-direction is chosen in upstream direction following the
flow, the following relations can be obtained for the cross section and
width.
B
§ x·
B 0 ˜ exp ¨ ¸
© b¹
(6.11)
A
§ x·
A 0 ˜ exp ¨ ¸
© a¹
(6.12)
In which B and A are respectively the width and cross section, B0 and A0 the width and cross
section in the estuary mouth (x=0) and b and a the (cross sectional) convergence lengths. The
convergence length is defined as the distance from the mouth at which the tangent through the
point (A0, 0) intersects the x-axis (Savenije, 2005).
If the estuary convergence has more than one reach like the Pangani estuary (due to the bay),
different convergence lengths have to be used:
§ x x1 ·
A A1 ˜ exp ¨ ¸
a2 ¹
©
(6.13)
Where A1 is the initial cross section of the second reach, x1 the length of the first reach and a2
the cross-sectional convergence length of the second reach.
The width of the Pangani estuary can be measured by means of LandSat 7 satellite images.
With this method, depending on clouds, each 2 – 4 kilometres the width of the estuary can be
measured. This was done for the first 40 kilometres, starting in the estuary mouth. The bay
was not included in this measurement, since the flow width of the bay is determined with other
satellite images. Measurements at the mouth confirm the width that was determined from the
hydrographical chart. After the first 40 kilometres the banks of the estuary are nearly parallel.
The results can be seen in figure 6.10.
Stream width, obtained from satellite images
360
Stream width [m]
320
280
240
200
Meas ured
160
Exponential trend
120
80
R² = 0,979
40
b
0
Figure6.10:
36
Streamwidth,exponentialestimateandconvergencelengthb.
44000
42000
40000
38000
36000
34000
32000
30000
28000
26000
24000
22000
20000
18000
16000
14000
12000
10000
8000
6000
4000
0
2000
Meters upstream [m]
CT5060
Final thesis
The convergence length b that is found in this way is 14.3 kilometres. This is a relative small
number which indicates that the banks of the estuary converge fast. From figure 6.9 also can
be seen that the exponential estimate is a very good approximation for the estuary width.
When plotted on a log scale, the measurements show a straight line as shown in figure 5.12.
According to Savenije (2005) the convergence lengths a and b cannot differ substantially.
Otherwise, the depth of the estuary would either increase or decrease exponentially. Given this
rule and the cross sectional area of the estuary mouth as defined before, the cross section
along the estuary can be estimated as well.
Cross sections are far more complicated to obtain than widths or depths. To measure one cross
section, one has to measure quite some depths over a width to get a reasonable result.
Therefore, measurements of cross sections are minimized. Some cross sections were measured
completely, and plotted logarithmic together with the obtained widths, in this way a good
estimation is obtained of development of the cross section.
The depth is usually constant in alluvial estuaries, but this rule does not apply to estuaries
where a nearly standing tidal wave occurs. If the depth is not constant, a depth convergence
length should be determined, to be able to consider the effects (Nguyen, 2006).
The depth was measured during the salinity distribution measurements, since the sensor of the
conductivity meter is lowered to the bottom. These depths will have to be corrected for the
tidal phase they were made in. When the depth is both measured at HWS and LWS at the same
location during the same tidal wave, and tidal asymmetry is not too strong, the tidal average
can be considered as the in between value.
Estuary surface
The estuary surface is needed to determine the tidal prism, which is a key factor for checking
the tidal parameters. To model the estuary correctly, the surface is needed to calculate both
the input of precipitation and the outflow of evaporation.
The estuary surface is determined by integration of the width, and by means of maps. If proper
images can be obtained, the surface can accurately be estimated with GIS. This however is the
channel surface of the estuary which, in the Pangani case, has not much to do with the tidal
prism or the surface which is influenced directly by precipitation and evaporation. Since detailed
maps of the area neither are available, the estuary water surface is hard to obtain.
37
‘Forcing on the salinity distribution in the Pangani Estuary’
38
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Final thesis
7.
Modelling the salt intrusion
7.1
Introduction
In this chapter the modelling of the salinity distribution is described. In the next paragraph the
model set up and essential parameter determination will be explained. In paragraph 7.3 the
calibration steps will be discussed. Paragraph 7.4 gives an overview of the model results.
Paragraph 7.5 until 7.7 give an explanation on the parameter behaviour of the dispersion, tidal
excursion and offset respectively. Paragraph 7.8 gives an overview of what conclusions from
the model can be drawn for the future behaviour of the system
7.2
Steady state salinity distribution model set up
Steady state or unsteady state model?
The choice for an unsteady state model or a steady state model is based on the system
response time. This is the time needed for the salinity distribution to adjust to new flow
conditions. If the response time is large compared with the time scale of flow condition change,
an unsteady state model approach is needed.
The Pangani discharge regime is dominated by the New Pangani Falls hydropower dam, which
results in a rather constant discharge. The influence of discharge on the salinity distribution
compared with tidal influence is rather small. The shift in the salinity profile in figure 5.17
caused by the spring- and neap tide difference is much larger than can occur due to discharge,
if El Niño events are not considered.
The flushing time scale of the estuary (Tf) (the time needed to refresh all water in the system)
is an indicator for the system response time. According to Savenije (2005) the flushing time
scale can be expressed as:
A0 a §
§ L ··
Tf
¨1 exp ¨ ¸ ¸
Qf ©
© a ¹¹
(7.1)
Here, the cross section and its convergence length were normalised over the two reaches in
relation to the salt intrusion length. The average discharge was used. This resulted in a flushing
time scale of 16 days.
The system does not have to be flushed entirely to adjust to new flow conditions. From other
estuaries over the world, the system response time is about ten to twenty percent of the
flushing time scale. This would result in about two days for the Pangani Estuary. Hence, a
steady state model can be applied.
39
‘Forcing on the salinity distribution in the Pangani Estuary’
Salinity distribution
According to Savenije (2005) in steady state, the salinity (S) distribution can
be obtained from the overall longitudinal dispersion with the following
relation:
1
S Sf
S0 S f
§ D ·K
¨ ¸
© D0 ¹
(7.2)
Where Sf is the fresh water salinity, S0 is the ocean salinity, D is the
longitudinal dispersion, D0 is the longitudinal dispersion at the estuary mouth and K the
dimensionless Van den Burgh’s coefficient.
The dispersion is proportional to the salinity distribution to the power of the Van den Burgh’s
coefficient K, which lies between zero and unity. Depending on the chosen boundary conditions
S0 and D0 the model can be applied for the TA, HWS or LWS situation.
The estuary axis dependent longitudinal dispersion can be obtained from the geometry of the
estuary and the discharge.
The following formula can be applied for the overall longitudinal dispersion.
§
·
D
§x·
1 E ¨ exp ¨ ¸ 1 ¸
D0
a
© ¹
©
¹
(7.3)
The dispersion reduction rate is defined as following:
KaQf
E
D 0 A0
(7.4)
In case the bathymetry has more reaches, ǃ will have a different value for each reach.
Tidal average
The salt intrusion model used is based on TA conditions. This is done for the practical reason
that during TA the average cross section appears and, more important, it is constant for each
tidal cycle. An HWS or LWS based model would have had different cross sections during springand neap tide and other influencing time cycles, which would introduce a lot of uncertainty on
determining all these cross sections exactly.
During TA, there is a clear relation between the bathymetry reaches, the dispersion and
therefore the salinity profile. The influence of the bathymetry on the salinity profile can be seen
unshifted, which makes calibration easier.
Tidal excursion
With the above mentioned relations, the TA salinity distribution can be
determined. From this salinity profile the profiles of both HWS and LWS can be
derived by means of the tidal excursion: A shift with the profile of half the tidal
excursion in upstream direction results in the HWS profile, in downstream
direction the LWS profile is found.
Due to friction and water storage, the tidal excursion can be damped along the estuary. This
also depends on geometry and has therefore an exponential behaviour:
40
CT5060
E
Final thesis
§ x·
E0 ˜ exp ¨ ¸
© e¹
(7.5)
The tidal excursion along the estuary is related to the tidal prism and the cross section:
HWS
Pt
³ Q 0, t dt | A E
0
0
LWS
(7.6)
This formula shows the necessity to determine the tidal excursion
convergence length in the Pangani Estuary. In many estuaries over the
world the tidal excursion is constant along the estuary axis (Savenije,
2005). This is however depended of whether the cross section of the
mouth increases linear with the tidal prism. If bank levels upstream in the estuary are
exceeded, the tidal prism grows disproportional with the cross section of the estuary mouth. As
a response, channel flow increases, which results in a larger tidal excursion. However, since the
system loses forcing in the area where the additional tidal prism is created, the tidal excursion
here reduces to original values. Tidal excursion convergence is a fact.
Increased channel flow on longer term results in deepening of the channel. This creates an
overall larger cross section, but not one which behaves linear with the tidal prism. A deeper
channel however reduces friction, which results in a decrease of tidal dampening, and therefore
again a (disproportional) larger tidal prism. This unbalanced system can only be compensated
by sediment availability. Sediments are not available from upstream; therefore the river does
consume its outer delta, which results in erosion of the bay, and the estuary mouth.
When defining the convergence of the tidal excursion along the estuary for the model, a
boundary condition has to be considered: over a certain length along the estuary the tidal
excursion can never decrease more than this length, since this is physically impossible. This
comes down to the simple rule that the tidal excursion convergence should always be larger
than the tidal excursion itself.
7.3
Calibration steps
Tidal average salinity distribution
The tidal average salinity distribution can be determined with the equations (7.2) and (7.5).
Information on bathymetry and discharge is available, but four calibration parameters remain:
the dispersion at the mouth, the Van den Burgh’s coefficient and both the tidal excursion and
its convergence. The Van den Burgh’s coefficient is an estuary characteristic and constant over
time. The dispersion is in time depending on the tidal range and the discharge. Calibration can
only be done on available HWS and LWS measurements. The tidal excursion is changing with
the tidal range, but the convergence is expected to be constant.
Tidal excursion shift
To obtain the salt intrusion curve of the HWS and LWS curve, the estuary axis has to be shifted
with half the tidal excursion. Here, calibration is done not only on the tidal excursion, but also
on the convergence length of the excursion. Different tidal conditions result in different tidal
excursions, but the convergence is seen as an estuary characteristic for the upstream shift to
the HWS situation, this means that the first data points from the estuary mouth until half the
41
‘Forcing on the salinity distribution in the Pangani Estuary’
tidal excursion have to be filled up with the ocean salinity. Shifting has to be done for each
point along the estuary axis separately, if the tidal excursion is not constant along the estuary.
Results so far
Although the used salinity intrusion model was tested on estuaries worldwide, it does not lead
to satisfactory results for the Pangani Estuary. For smaller tidal ranges the model performs well,
but with higher tidal ranges the model is not capable to mimic the occurring salt intrusion
curves. The best results are reached with implausible dispersion values, and relative tidal
excursion differences that were found were not realistic.
Figure7.1:
Modelresultsafterfirstcalibration.
The offset theory
If calibration on these higher spring tides is done not by curve fitting but by varying the
calibration parameters, it can clearly be seen that not only a shift should be made to the HWS
and LWS curve according to the tidal excursion, but for some reason the TA curve should be
shifted a certain distance upstream first. This distance will further be referred to as the ‘offset’.
The physical meaning of this offset is the storage of water upstream during HW that does not
return with LW. In this way the salinity distribution is shifted further upstream until the HWS
condition as a result of the increased tidal prism because due to additional storage at HW. The
LWS curve will also be relatively more upstream because the water that is stored does not flow
back and therefore does not move the LWS curve. In other words, the HW tidal excursion is the
offset larger than the LW tidal excursion!
42
CT5060
Final thesis
This kind of storage is present on the banks of the estuary with palm plantations. These
grounds have a system of dug out creeks and whole parts of the plains
submerge during extreme HW. Because these grounds often have dried up since the last
springtide, there is substantial storage is available in the plains.
Figure7.2:
Schematicinundationpatternofthepalmplantations.
Calibration steps with offset.
Calibration is repeated using offset. Now, the model has five calibration parameters. This seems
curve fitting, but it should be realized that the model produces two curves, and their spatial
relation with each other. All calibration parameters have their specific influence on the salinity
profile:
x The boundary condition D0 defines the slope of the salinity profile (discharge also has
important influence on the slope, but is not a calibration parameter).
x The Van den Burgh’s coefficient K defines the curvature of the ‘toe’ of the curve, the
deepest salt intrusion.
x The offset defines the location of the TA curve.
x The tidal excursion defines the spatial difference between HWS and LWS.
x The tidal excursion convergence length defines the gradient difference of the LWS and HWS
curves.
43
‘Forcing on the salinity distribution in the Pangani Estuary’
Figure7.3:
Exampleofflatsthatonlyinundateduringspringtides.
Since each parameter has a clear but different influence on the salinity distribution, the curve
has a unique non-equifinal solution. Per tidal condition, only the initial dispersion, the tidal
excursion and the offset are unique, the other two are considered to be constant over time.
7.4
Results
Origin of used data
For the salt intrusion model, four sets of salinity profiles during HWS and LWS were used. All
four were during a springtide. The new moon springtide of May 28th 2006 and the full moon
springtide of September 9th 2006 were measured by the estuarine survey team as part of the
Flow Assessment Component of the Pangani River Basin Management Project (IUCN - PBWO,
2007). The salinity profiles of the full moon springtide of October 27th 2007 and the new moon
springtide of December 11th 2007 were measured by the author. Further information on the
measurements can be found in paragraph 6.2.
Overview of measurements and model results
The available data set is a small but diverse one. Essential differences that occur are the tidal
range, the discharge, the precipitation, the mean sea level (reference level) and offset. These
variations automatically result in different tidal excursions, salt intrusion lengths and initial
dispersions.
44
Salinity[kgm Ͳ3 ]
CT5060
Final thesis
36
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14
12
10
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4
2
0
0
2
4
6
8
10
12
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32
Distancefromestuarymouthinkilometres[km]
Salinity[kgm Ͳ3 ]
27May2006,3mdeep
modelHWS
TA
2
4
6
8
10
12
14
16
18
20
22
Distancefromestuarymouthinkilometres[km]
Salinity[kgm Ͳ3 ]
9september2006,3mdeep
modelHWS
TA
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30
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4
6
8
10
12
14
16
18
20
22
Distancefromestuarymouthinkilometres[km]
11December2007,3mdeep
modelHWS
TA
Figure7.4:
3,8m
14000m
50000m
140m2/s
26500m
10,5m3/s
9,5mm
4,3m
5500m
Tidal range H0
Tidal excursion
Convergence excursion
Longitudinal dispersion
Salt intrusion length
Discharge
Precipitation week
Reference level
Offset
4,2m
19000m
30000m
270m2/s
27500m
14,8m3/s
49,6mm
4,5m
3700m
Tidal range H0
Tidal excursion
Convergence excursion
Longitudinal dispersion
Salt intrusion length
Discharge
Precipitation week
Reference level
Offset
3,0m
15000m
30000m
190m2/s
23500m
11,1m3/s
0,0mm
3,9m
1500m
27October2007,3mdeep
modelLWS
TAshifted
36
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14
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10
8
6
4
2
0
0
Tidal range H0
Tidal excursion
Convergence excursion
Longitudinal dispersion
Salt intrusion length
Discharge
Precipitation week
Reference level
Offset
8september2006,3mdeep
modelLWS
TAshifted
8
10
12
14
16
18
20
22
Distancefromestuarymouthinkilometres[km]
27October2007,3mdeep
modelHWS
TA
Salinity[kgm Ͳ3 ]
24
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
0
3,3m
13000m
50000m
250m2/s
21000m
20,5m3/s
80,9mm
4,2m
1500m
28May2006,3mdeep
modelLWS
TAshifted
36
34
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
0
Tidal range H0
Tidal excursion
Convergence excursion
Longitudinal dispersion
Salt intrusion length
Discharge
Precipitation week
Reference level HW
Offset
24
26
28
30
32
11December2007,3mdeep
modelLWS
TAshifted
Overviewofallmeasuredandmodelledspringtidesalinityprofilesandtheirinfluencing
parameters.
45
‘Forcing on the salinity distribution in the Pangani Estuary’
7.5
Verification of determined initial dispersion
Empirical description of initial dispersion
According to Savenije (2005) the initial longitudinal dispersion can be described empirical with a
relation with the Estuarine Richard’s Number as following:
DHWS
h
0
1400 0 NR0.5
a
X0E0
(7.7)
Where h0 is the constant tidal average stream depth. The left dimensionless term is the
dispersion divided over it the product of its two characteristics: the mixing length and the
velocity amplitude. The Estuarine Richard’s Number (NR) is defined as following:
'U ghQ f T
NR
U A 0E0 X20
(7.8)
Where Ǐ is the density of the water and T the tidal period.
This empirical description has been proven on many estuaries worldwide.
From these relations can be seen that both the square root of the tidal excursion and the
discharge behave proportional with the dispersion. The bathymetry parameters that are
mentioned can be considered constant under all tidal influences. The tidal period and the
density difference however are subjected to change. The tidal period is elementary longer
during neap tide than average and therefore some what shorter during spring tide, resulting in
an amplification of the effect that the tidal range has on the dispersion: large during spring
tide, small during neap. The salinity difference is subjected to seasonal change, as during the
rainy seasons the salinity drops in the Zanzibar channel. Larger salinity differences results in
larger dispersion due to density driven mixing.
Rewrite the TA situation to HWS
Since the initial dispersion in the model is based on the TA situation, but the empirical
description is based on the HWS situation, the TA results from the model have to be rewritten
to HWS. First, the values are rewritten to the HWS dispersion at half a tidal excursion from the
river mouth, so a horizontal shift in the (x, D) plane, with the following relation:
§ E ·
¨ ¸
TA
© 2a ¹
D HWS
(E / 2) D0 ˜ e
(7.9)
Next, the obtained HWS situation is calculated back to the river mouth according:
D HWS
0
D HWS
(E / 2)
§ §¨ E ·¸ ·
1 E ¨ e© 2a ¹ 1 ¸
¨
¸
©
¹
(7.10)
With ǃ as defined in (7.3).
Comparison of empirical relation and model results
The results of the empirical relation and the model are plotted in figure 7.5. The results
correlate very well, but it has to be noticed that the model overestimates the dispersion with
the two events with a significant larger tidal excursion and discharge. It should be considered
however, that the empirical model is based on estuaries that obey entropy principles. Since
convergence of the tidal excursion occurs in the Pangani Estuary, this estuary is not balanced
by entropy. The disproportionality between tidal prism and the cross section of the river mouth
results in higher flows in the mouth, which thus lead to disproportional initial dispersion relative
to the bathymetry.
46
CT5060
Final thesis
Due to the offset the actual (HW) tidal excursion in the mouth may be larger than the one
observed from the HWS and LWS curves. For this reason the calculated empirical dispersion
might be too low.
1200
Empiricalcomputeddispersion[m 2 sͲ1 ]
1000
800
600
27/28Ͳ5Ͳ2006
27Ͳ10Ͳ2007
11Ͳ12Ͳ2007
8/9Ͳ9Ͳ2006
400
200
0
0
200
400
600
800
1000
1200
CalibrateddispersionconvertedtoHWS[m 2 sͲ1 ]
calibratedͲ empirical
Figure7.5:
7.6
lineoftotalcorrelation
Comparisonofthecalibrateddispersionforthemodelandtheempiricallycomputeddispersion.
Verification of tidal excursion
Correlation with other parameters
The tidal excursion is expected to grow with increasing tidal prism. So the tidal excursion
should correlate with the tidal range. Because the initial cross section is influenced by the TA
level, seasonal high TA levels will shorten the tidal excursion, as possibly is the case in the May
27th 2006 measurement. Next, the offset shows an influence on the tidal excursion, it does not
affect the excursion during flood, but the retreat during ebb is diminished. Since in this
research, the tidal excursion is only obtained from the mutual distance of the HWS and LWS
curve, the offset does have effect the measured tidal excursion.
Errors from measurements
The tidal excursion, and especially the tidal excursion convergence length are extremely
sensitive to errors due to wrong timing and velocity of the moving boat measurement. The
accuracy and consequences on model results will be dealt with in the measurements chapter.
47
‘Forcing on the salinity distribution in the Pangani Estuary’
7.7
Verification of salt intrusion offset
Explanation of the process
If a springtide occurs that reaches water levels
higher than the ground level of the coconut
plantations, inundation starts. A part of this water
returns with low tide, and the rest stays behind,
stocked in the soil, or trapped in basins. Basins and
puddles occur, since the bank level of the river is
higher than the level of the plains. Friction does not
play a role here, since the area is covered with dug
out channels, that both transport the coconuts on
tidal flow as that they irrigate the fields. The part of
water that does not flow back, does not flush out
the salt back to the original LWS salinity profile. In
figure 7.8 and 7.9, the effect of the inundation on
the HWS and LWS salinity profile is explained.
The amount of water that is stored, depends on the
amount of water that already is in the basins and the
soil. This amount of water is influenced by the
precipitation and evaporation over the plains.
Threshold
From the available measurements and the physical
situation, it becomes clear that a certain threshold is
needed in the absolute water level to get a strong
offset effect. This is simply the water level that is
needed to inundate the coconut plantation. If the
water is high, significant storage is created, resulting
in a salinity profile offset. This level is reached when
a tidal range of the order of 3.5 metre occurs, which
corresponds with a reference level of about 3.8
metre. The actual level that has to be considered is
the absolute water level compared to the reference
level, in order to take the seasonal TA level
differences into account.
System memory
At the start of a psringtide period the HW is higher
every tidal cycle; so in fact, the inundation is getting
somewhat larger every day. The storage is in reality
filled by more tides. But because each of these
storage moments results in a small offset of the LWS
curve, and this curve is the initial condition for the
next tidal wave, the offset is formed as a sum of
several tides. The salinity distribution is the memory
of the system its storage. Once the water level during
high tide stays below the threshold again, this
memory is erased and the original salt balance will
48
Figure7.6:
Animationoftheinundation
processduringaspringtide,thelast
springtidedefinestheinitialstateofthe
h d l i l it ti
CT5060
Final thesis
gradually establish itself.
Influence of hydrology
The storage in basins and soil can be modelled with a
conceptual model. The storage is then represented as
one reservoir, which has the initial condition that it is
filled completely at the moment of springtide. If from
this moment for each following day the precipitation
is added and the evaporation subtracted a reservoir
level can be determined. Using the available
hydrological data, the resulting reservoir levels are
calculated for each measurement day, from the day
of the last springtide.
Three parameters are indicators for the offset. First
of all the reference springtide level: a larger
springtide corresponds with more offset. Secondly,
the defined reservoir level: a lower reservoir level
results in more offset. Finally, the tidal excursion
convergence: a larger tidal convergence (so a smaller
number!) corresponds with more offset.
A next step is to do a regression analysis on these
parameters. Since the data set only consists of four
reliable results, it can not support an analysis with
Figure7.7:
Animationoftheinundation
three parameters. Because the reference springtide
processduringaspringtide,theredzonesindicate
level is having the most influence on the offset, it is
whichpartsofthewatertablecontributetotidalprism
both combined with the other two in the regression.
andoffsetrespectively.
Adding the convergence does not lead to much better
results than a regression analysis with the reference
level alone. The combination of reference and reservoir level however gives a much larger
correlation: an improvement from 0.39 until 0.86. This correlation is physically correct, since
the suggested parameters in the linear regression are indeed positive for the reference and
negative for the reservoir level. Relatively, the influence of the reference is about one order
larger than the reservoir level. Calibration on the number of days on which the hydrological
reservoir level is determined however shows that the dataset is too small to draw firm
conclusions. The regression is good on a water balance based on ten days (which is physically
correct according to the spring neap cycle) but it also returns good correlation on three days.
Now, single rain events have got a major impact on the total regression, since only four data
points and three days are considered. This leads to spurious data behaviour.
49
‘Forcing on the salinity distribution in the Pangani Estuary’
Figure7.8:
EffectonthetidalprismgrowthontheHWSsalinityprofile.Dottedlineshowseffectwithout
theinundation,arrowsindicatethedisplacedvolumeduetoinundationintheestuary.
Figure7.9:
50
EffectofthevolumethatdoesnotreturninthechannelafterinundationontheLWSsalinity
profile.Dottedlineshowseffectwithouttheinundation,arrowsindicatethedisplacedvolume
duetoinundationintheestuary.Thisistheactualoffset.
CT5060
Final thesis
If the system is described physically, the following relation is obtained:
'L O
Ht Hres ˜  i Hr A0
(7.11)
Where LO is the salt intrusion offset, Ht the threshold level for inundation, Hres the water level in
the conceptual reservoir Âi the inundation surface area, which is a function of the reference
level Hr.
Now, the inundation however is coupled to a certain surface. This leads to new questions: Is
the surface of the area of which precipitation is taken into account the same as the inundation
area, or is there inflow? Can the inundation area be considered as constant if the threshold is
reached or does it differ?
The answer to the first question is no. There is definitely inflow, if the geography of the area is
considered. This could simply be modelled with a rainfall coefficient by which the original
rainfall is multiplied, which can be estimated. The problem is that it has to be calibrated and
there again is no data to support that.
The second question is a definite no as well. For instance consider both the full moon
springtides; the one in September 2006 has a maximum level of 4,3 metre, the one in October
2007 4,5 metre. Twenty centimetres level difference, will lead to an enormous difference in
inundated area, whatever the exact geography is. Here, it is also possible to estimate the
inundated area, but calibration is again impossible.
To check whether the differences that occur in offset are physically possible at all, the last
rainfall event before the October 2007 springtide of 38 mm is expressed in offset. If this rainfall
is taken over the whole downstream New Pangani Falls catchment of 610 km2, and this volume
is divided over than offset of 1630m is found. This is in the same order of the difference in
offset of the two full moon springtides.
7.8
Forcing on the salinity distribution in the Pangani Estuary
Expectations and results
The model results show that the balance of tidal dynamics and morphology is broken. The
unavailability of sediments leads to erosion of banks and of the bay. This results in a shape that
no longer obeys to entropy principles: the offset system leads to a gradient in the tidal flow
velocity. As was shown from the model, the offset can contribute to the salinity distribution as
much as 5.5 kilometres, which is 20% of the total salinity intrusion, and even 40% of the
dynamic section of the intrusion. Lack of upstream sediments will only strengthen this process.
During the field campaign it was noticed that the coastal sediments do not move further than
the first sharp curve to the south, where a sand bank is deposited in the channel in a further
totally muddy environment.
Although the New Pangani Falls hydropower dam and the Hale dam are the cause of this
sediment lack, they prevent extreme salt intrusion in another way. Because the New Pangani
Falls is a very efficient hydro power plant due to it’s 170 metre drop, a minimum discharge is
nearly always guaranteed, mostly using the Nyumba ya Mungu dam, and by means of irrigation
permits. The model shows that this guaranteed flow is as essential for the power supply as it is
for the estuary. Until 10 m3/s discharge the salinity profile is reasonable, but if this is decreased
51
‘Forcing on the salinity distribution in the Pangani Estuary’
until for instance 5 m3/s, salt intrusion immediately climbs up until at least 32 kilometres
upstream. Given the lack of water in the catchment, this would certainly have happened during
the dry season if the New Pangani Falls had not been there.
The situation of the river mouth and bay however is alarming. Because the bay erodes and
joins with the river mouth in one funnel shape, the tide is amplified. In the current situation
overwash over the quays of Pangani and Bweni occurs during equinoctial springtide, which will
eventually lead to collapse. If the constraint of the estuary banks falls, the tide will reach the
plantations less damped. This will lead to an offset growth in two ways: the submerged area
will grow, and the inundation depth will increase.
Whether the Pangani Estuary will reach a sediment stable situation in this situation is
questionable. However, looking over the mouth from the cliff on the Bweni side, it is visible in
the landscape that once the coast was even further inland than it is now, from the sand ridges
that are still visible in the landscape.
Figure7.10:
52
SandridgesfollowingthebeachprofilenorthofPangani,theridgesarealsovisibleinfigure5.9.
CT5060
8
Final thesis
Conclusions
Introduction
The objective of this thesis is to determine the current salt intrusion in the Pangani Estuary,
and to retrieve its forcing. The salt intrusion in the estuary is increasing. This research
determines what causes the current state of salt intrusion and what is to be expected in the
future.
Since this is one of the first researches on the Pangani Estuary, also some general conclusions
about the estuary and some findings on measurement methodology are presented in this
chapter. The conclusions are in line with the structure of the chapters.
Characteristics of the Pangani Estuary
The Pangani Estuarine system is out of balance. The equilibrium between shape, flow and
sediments is disturbed. Over the last decades it has been subjected to erosion, decreased
discharge and increased salt intrusion. These processes are still active, and it is not likely the
estuary will find a new equilibrium in the near future.
At the end of 2007 erosion was taking place along the estuary until at least forty kilometres
upstream and erosion in the estuary mouth was severe. Discharge conditions are low compared
to the period before construction of the New Pangani Falls hydropower dam, but a minimum
runoff is guaranteed during all seasons. Salt intrusion occurs until 28 kilometres upstream
under springtide conditions, the first ten kilometres are saline under all conditions.
The salinity profile has a bell shape and is well mixed, except during neap tidal conditions,
when the salinity profile is somewhat stratified. Two mixing processes occur in the Pangani
Estuary which have a large influence compared to other estuaries. Cross-over mixing due to the
strong meandering of the river during slack, and colliding creek – main channel flows during
LW, due to upstream directed creeks.
Methodology of measurements and derivations
In Pangani Estuary measurements could only take place from the banks, which often turned
out to be an advantage. If waves are present on the measurement location for tidal range,
more accurate results are obtained if stage is measured from a bank. From a quay or dolphin,
the error of waves can be minimised and estimated, which is not possible from a bridge or
boat. Measuring at a dolphin gives a second advantage: the moment of HW and LW can be
determined very precise on the slope of a natural bank, since the horizontal displacement of
the water line is much larger than the vertical.
The tidal period in the Pangani Estuary is variable: it is about one hour longer during neap tide
due to the relative lunar and solar influence on the tide. The phase lag is an hour under all tidal
conditions. Due to wind and waves, it is difficult to determine the moment of slack by buoy. A
successful method to determine the moment of slack from a bank over the whole width is by
throwing more floats in the water in a line perpendicular to the flow. By extrapolation of the
53
‘Forcing on the salinity distribution in the Pangani Estuary’
velocity of the floats, an estimation of the flow velocity in the middle of the channel can be
made.
If a moving boat method is executed well, it can even be a good approximation of the wave
celerity in the estuary. A clear distinction in velocity between HWS and LWS measurements
verifies this. The accuracy of the wave celerity is also proven by its correct relation with friction
and damping in the estuary.
The effect of disproportional storage width along the estuary, which occurs in Pangani Estuary
in the palm plantations, results in non-linear behaviour of the tidal prism with respect to the
tidal range and with the cross section of the mouth. The tidal prism does interact with the tidal
excursion and the tidal damping. The tidal excursion increases in the estuary section between
mouth and the inundation area, and then decreases in the section where the inundation takes
place. This is also the section where tidal damping occurs: due to inundation the wave loses
momentum.
Modelling of the salt intrusion
The salt intrusion in the Pangani Estuary can be described with a steady state model. The time
that the system needs to adapt to a new flow regime is negligible. The salt intrusion in the
Pangani Estuary can however not be modelled adequately with an non-adapted steady state
model during springtide conditions.
Inundation of palm plantations leads to upstream storage of water in the system. An irrigation
and transport system divides the water over the whole plantation and under extreme springtide
whole plains drown. A part of this water does not return, it evaporates from or infiltrates in the
sun-warmed soil, or stays behind in puddles. This volume of water moved through the main
channel but is not transported back, therefore, it results in a shift in the salt intrusion in
upstream direction, for both the HWS as the LWS curve. This shift is referred to as the offset of
the salt intrusion. This offset can be as much as twenty percent of the total salt intrusion, or
forty percent of the dynamic part. The steady state model has to be corrected with the offset to
perform well.
During the development of a springtide, each higher tidal range will create a small offset. Since
each previous offset is the initial condition for the next tidal wave, the offset becomes a sum of
several tides. The shift of the salt intrusion functions as a memory of the amount of water that
is irrigated on the plains, during low tide the original salt intrusion gradually establishes itself
again.
The dispersion that is obtained in a salt intrusion model where the offset is taken into account,
is correlating well with the empirical approximation of the dispersion at the mouth. If the offset
is subjected to a regression analysis with the absolute water level and the hydrology of a
conceptual reservoir that resembles the inundated plains, it performs much better than without
taking the hydrology into account. This conceptual reservoir determines the precipitation and
evaporation between two springtides in the plantation.
Model results confirm that the balance between tidal dynamics and morphology is broken. The
forcing behind this process, a lack of sediment transport from upstream, is still present and will
be present in the future. This is caused by the sediments that are trapped in the upstream
hydropower dams. The hydropower dams do however also have a positive influence on the salt
intrusion. A minimum discharge is guaranteed in all seasons, which keeps the salt intrusion on
reasonable levels. Model runs confirm that discharges below this level results in far more
extreme salt intrusion.
54
CT5060
9
Final thesis
Recommendations
The salt intrusion offset
This thesis shows a likely relation between salt intrusion offset and inundation of plains along
the river. There is a lack of data to proof this relation thoroughly. It is advisable to do more
measurements to draw well-founded conclusions. First of all more data points are needed:
more springtide salinity profiles should be added to the data set. With this data set a much
better regression analysis can be performed. Further, to gain more insight in the process of salt
intrusion offset, it is advisable to do more measurements during one springtide, to see the
offset grow with increasing tidal range, and to see at which threshold tidal range the inundation
starts.
Relation of the offset with tidal parameters
The influence of the palm plantation inundations on the tidal prism and tidal excursion is clear
in a qualitative sense, but much more information can be obtained. During the field campaign,
the impact of the inundation was not fully realized, so quantitative data was not obtained.
Interesting questions are: How large is the area that gets flooded during springtide? How is the
extent of this area influenced by the tidal range? If the progress of the inundation over the tidal
cycle is known, its relation with other tidal parameters can be obtained. In the field, it is tough
to relate to tidal excursion immediately, but it is interesting to measure tidal velocity amplitudes
near the estuary mouth. This is for instance possible from an anchored boat with a float
attached to a rope. Since the cross section is increasing less compared to the tidal prism the
tidal excursion, and with that the velocity amplitude, has to grow. The growth of the velocity
amplitude should coincide with the growth of the inundation surface. If also salinity profiles
during a whole springtide cycle are available as described in the previous paragraph, the tidal
excursion convergence length in the inundation zone may be compared with the progress of
the inundation and velocity amplitude as well. The influence of the inundation on the tidal
excursion convergence requires more research.
Another interesting option is to relate the amount of inundation to the water temperature in the
estuary. During inundation dry, warm, black, non-vegetated soils are inundated with a shallow
layer of water. This causes the water temperature to rise, which can even be noticed in the
river mouth. Measurements on water temperature, and research on what other processes
influence this water temperature may result in an easier way to obtain information on
inundation than by exploring all inaccessible plains.
55
‘Forcing on the salinity distribution in the Pangani Estuary’
56
CT5060
Final thesis
References
Alexander ,C.S.: 1966. - A method of descriptive shore classification and mapping as applied to
the Northeast coast of Tanganyika. Association of American Geographers Annals, 57: 133-154.
Beuster, J., Howard, G.J., Lugomela G.V.: 2006. - The Hydrology of the Pangani River Basin
Status, IUCN Water and Nature Initiative, Pangani Basin Water Office; Pangani Basin Flow
Assessment Initiative, Hydrology and System Analysis, Vol. 1 of 2, 2nd draft, Emzantsi Systems.
Gable, F.J., Aubrey, D.G., Gentile, J.H.: 1991. - Global Environmental Change Issues in the
Western Indian Ocean Region, Geoforum, Vol. 22, No. 4: 401-419
Haas, J.: 2007. - Phase lags in alluvial estuaries, Classification of alluvial estuaries by means of
the phase lag, Final report master thesis, TU Delft 156p.
Hayes, M.O.: 1975 - Morphology of sand accumulation in estuaries. Estuarine research Vol. 2:
3-22, Academic Press, New York.
The World Conservation Union (IUCN), 2003. – Pangani Basin: A situation Analysis, IUCN
Eastern Africa programme, IUCN - EARO Publications.
The World Conservation Union (IUCN) and Pangani Basin Water Office (PBWO): 2002. – The
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Basin Workshop, Moshi, Tanzania, 2002.
The World Conservation Union (IUCN) and Pangani Basin Water Office (PBWO): 2007. –
Pangani River System, State o the Basin Report - 2007 Tanzania, Pangani Basin Water Office IUCN Eastern Africa Regional Office
Mbonile, M.J.: 2005. – Migration and intensification of water conflicts in the Pangani Basin,
Tanzania, Habitat International 29 41-46, Elsevier.
Nguyen, A.D., Savenije H.H.G.: 2006. - Salt intrusion in multi-channel estuaries. Hydrology and
Earth System Sciences, 10: 743-754
Nyandwi, N., Dubi, A.M.: 2001. - Episodic atmospheric changes and their impact on the
hydrography of coastal waters in Tanzania. Climate Research, Vol. 18, 157-162.
Savenije, H.H.G.: 2005. - Salinity and tides in alluvial estuaries. Elsevier, Amsterdam, 197p.
Shaghude, Y.W.: 2004. – Shore Morphology and Sediment Characteristics South of Pangani
River, Coastal Tanzania, University of Dar Es Salaam, Institute of Marine Sciences.
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Shaghude, Y.W.: 2005. – The Study of Sediment Characteristics and Nearshore Sediment
Dynamics in Coastal Tanzania, Western Indian Ocean Marine Science Association.
Trzaska, S., Moron, V., Fontaine, B.: 1996. - Global atmospheric response to specific linear
combinations of the main SST modes. Part I. numerical experiments and preliminary results.
Annales Geophysicae 14: 1066-1077 EGS Springer-Verlag
Uncles, R.J.: 2003 - From catchment to coastal zone: examples of the application of models to
some long term problems. The Science of the Total environment, 314-316: 567-588, Elsevier.
United Nations (UN) Environment Programme: 2001. - Eastern Africa Atlas of Coastal
Resources, Tanzania, A project of the United Nations Environment Programme with the support
of the Government of Belgium. United Nations Environment Programme
Valimba, P., Mkhandi, S.H.: 2005 - Predictability of the short rains in Northeast Tanzania,
unpublished work.
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Final thesis
Appendices
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‘Forcing on the salinity distribution in the Pangani Estuary’
60
CT5060
Appendix I
Final thesis
Location of measurements
61
‘Forcing on the salinity distribution in the Pangani Estuary’
62
CT5060
Appendix II
Final thesis
Example of the tidal wave
63
‘Forcing on the salinity distribution in the Pangani Estuary’
64
CT5060
Appendix III
Final thesiis
Movin
ng boat measure
ements
Neap tiide 5 October 2007
Springttide 27 Octo
ober 2007
65
‘Fo
orcing on the
e salinity disttribution in the Pangani Estuary’
E
Sp
pringtide 11 Decembe
er 2007
Lo
ocation of salinity
s
mea
asurements
s stations
66
6
CT5060
Final thesis
67
‘Forcing on the salinity distribution in the Pangani Estuary’
68