saline intrusion in gambia river after dam...

Solutions to control saline intrusion while accounting for irrigation

development and climate change

M.P. Verkerk C.P.M. van Rens

Saline intrusion in

Gambia River after

dam construction

Colophon Institutions Department of Water Resources University of Twente p/a: M. Njie p/a: K. M. Wijnberg Hydrology Civil Engineering & Management 7, Marina Parade Postbus 217 Banjul 7500 AE Enschede The Gambia The Netherlands Phone: +22 0 422 8216 Phone: +31 (0) 53 489 4701 Authors M.P. (Maarten) Verkerk E-mail: [email protected] C.P.M. (Chris) van Rens E-mail: [email protected] Date

11 July 2005

Saline intrusion in Gambia River after dam construction

Solutions to control saline intrusion while accounting for irrigation development and climate change

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Summary Saline intrusion in the Gambia River affects agriculture, mangroves and fishing industry. In order to generate power and to stimulate agriculture, a hydroelectric power station at Sambangalou is planned. This dam provides an artificial base flow, which creates opportunities for irrigation and reduces maximum saline intrusion in the dry season. Previous studies on future saline intrusion by the OMVG either have been based on unjust model assumptions or have neglected irrigation or climate change. Saline intrusion is generally dealt with as a side effect of dam management based on power generation. Under the projected dam release scenarios, dam release could be stopped for 0 - 2.5 months. This will turn out to have dramatic impact on saline intrusion. To examine the extent of saline intrusion, the 1-D numerical model SALNST is used. SALNST is based on the advection-dispersion equation to which rainfall and evaporation are added. Results are presented as maximum saline intrusion length (SIL) in wet and dry years during a time period of 2070-2100. The aim to keep saline intrusion downstream of KP170 is derived from the Gambia River Basin Hydraulic Master Plan. Maximum saline intrusion is currently located around KP254. The authors stress that all values of saline intrusion lengths are the results of simplified calculations based on assumed data. Under any circumstances, these results can not be considered as exact predictions of saline intrusion lengths. The aim for irrigation development using water from the Gambia River is set by the OMVG at 17,700 ha. Development of tidal swamps for tidal irrigation is hydraulically efficient, since water is already stored in and on the soils of these swamps and water is already consumed for evapo-transpiration. The area of cultivable tidal swamps is at least 0 and 6,500 ha at most, being located between KP170 and KP300. Pump irrigation is less profitable in comparison to tidal irrigation due to high investment and operational costs. Three irrigation scenarios have been used; one presuming all tidal irrigation areas to be tidal swamps at present, one presuming only pump irrigation and one reference irrigation scenario considering absence of irrigation. Considering saline intrusion by the year 2100, climate change has to be taken into account. Predicting morphological response of the estuary to any sea level rise has many uncertainties. The various theories on this subject move in different directions. Sediment supply is not expected to change substantially and will therefore remain unable to meet the sediment demand. For this, the estuary will not be able to keep pace with a sea level rise of 60 cm/century. Consequently, water depth is considered to increase throughout the estuary. River width will increase, though to a lesser extent upstream KP300, as the river is enclosed by steep river banks. Two geometrical scenarios are based on two different theories and adjusted to the local morphology. A reference geometrical scenario is included in the computations. Local rain and evaporation influence the concentration of salt. This especially applies to the intermediate and higher salinities. The effect on the 1.0 g/l salt front is less, being subordinate to the process of advection-dispersion. Local rain and evaporation are derived from climate data downscaled from the Global Circulation Model HadCM3. Two evaporation scenarios are calculated by using the temperature-based formulas of Thornthwaite and Linacre. SALNST uses the monthly flow at Gouloumbo as input parameter. Four dam release scenarios have been derived from the OMVG, all with power production as the only management parameter. A fifth scenario reconsiders open water evaporation from the artificial lake and integrates water demand resulting from irrigation in Guinea. Rainfall is determined analogous to the estuary rainfall. Naturally, irrigation in this catchment is accounted for.



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Irrigating 14,000 ha of rice and 3,700 ha of mixed crops in The Gambia attracts the salt front by 32 – 60 km in dry years and 25 – 47 km in wet years, depending on the surface area of tidal swamp that is cultivated. Changed river geometry due to a sea level rise of 60 cm pushes the salt front 8 – 19 km further upstream, depending on the morphological response of the estuary. Significant difference in saline intrusion cannot be observed between two projections of open water evaporation from the estuary. Combining these scenarios and accounting for future precipitation and evaporation shows the salt front can not be kept downstream of KP170. Under scenario A, the maximum salt front will be between KP190 and KP243; and under scenario B between KP176 and KP230, depending on rainfall and the total area of tidal swamp cultivated. Stopping dam release from the dam’s reservoir for 2.5 months at the end of the dry season could attract the salt front up to KP309, upstream of all the tidal irrigation areas. When ensuring a discharge of 20 m3/s enlarged with the water requirements to fulfil irrigation needs, the salt front is kept at KP228 and 14,000 ha of rice and 3,700 ha of mixed crops can be irrigated. Setting the target of maximum saline intrusion at KP228, a dry area of 12,500 ha can be irrigated under dam release scenario A, apart from the cultivation of tidal swamps. Cultivation of tidal swamps does not substantially influence saline intrusion. Under scenario D, the Sambangalou dam does not stimulate Gambian agriculture development. A survey on cultivable tidal swamp area is recommended, considering the positive hydraulic qualities of tidal irrigation on former tidal swamps. The cultivation of tidal swamps has to be part of irrigation development programs. A yearly water budget has to be agreed on, taking account of irrigation, power production, industry and saline intrusion. This can be done at the end of the wet season, when all amounts of water supply and demand can be determined. In order to facilitate the decision on the water budget, dam release scenarios have to be recalculated. Naturally, all water demands have to be taken into account. The aim to keep saline intrusion downstream of KP170 can be reconsidered, and a decision has to be made within the OMVG whether a minimum base flow for agricultural purposes is preferable or not.



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Table of Content

SUMMARY........................................................................................................... 1

INTRODUCTION.................................................................................................. 5

READING MANUAL.............................................................................................. 7

CHAPTER 1: GAMBIA RIVER SALINE INTRUSION............................................ 8

1.1 SALINE INTRUSION PROCESS .......................................................................... 8 1.2 SURFACE WATER GAMBIA RIVER BASIN.............................................................. 9 1.3 ESTUARINE MORPHOLOGY............................................................................ 10 1.4 DESCRIPTION OF 1-D MODEL SALNST............................................................ 11

CHAPTER 2: ECONOMIC AND ENVIRONMENTAL ISSUES................................ 12

2.1 MANGROVES........................................................................................... 12 2.2 FISHING INDUSTRIES................................................................................. 13 2.3 AGRICULTURE IN THE GAMBIA ...................................................................... 13

CHAPTER 3: CLIMATE CHANGE...................................................................... 17

3.1 SEA LEVEL RISE ....................................................................................... 17 3.2 PRECIPITATION AND EVAPORATION ................................................................. 20

CHAPTER 4: CATCHMENT UPSTREAM GOULOUMBO....................................... 23

4.1 UPPER CATCHMENT: SAMBANGALOU DAM .......................................................... 23 4.2 INTERMEDIATE CATCHMENT.......................................................................... 27 4.3 GOULOUMBO DISCHARGE ............................................................................ 28

CHAPTER 5: SCENARIOS COMPUTED............................................................. 29

5.1 CALCULATION STRATEGY AND INPUT SALNST .................................................... 29 5.2 RESULTS ............................................................................................... 30

CHAPTER 6: ADAPTATION STRATEGIES ........................................................ 36

6.1 TARGET HYDROGRAPH FOR AGRICULTURE .......................................................... 36 6.2 REDUCING IRRIGATION DEVELOPMENT ............................................................. 37

CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS ................................. 38

7.1 CONCLUSIONS ........................................................................................ 38 7.2 RECOMMENDATIONS.................................................................................. 40

ACKNOWLEDGEMENTS...................................................................................... 42

REFERENCES..................................................................................................... 43

LIST OF FIGURES AND TABLES ......................................................................... 44



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APPENDICES..................................................................................................... 46

APPENDIX 1: NOTATIONS................................................................................. 47

APPENDIX 2: SALNST USAGE HISTORY............................................................. 48

APPENDIX 3: STRUCTURE SALNST.................................................................... 51

APPENDIX 4: SENSITIVITY ANALYSIS.............................................................. 52

APPENDIX 5: CUMULATIVE IRRIGABLE AREAS ................................................. 53

APPENDIX 6: PRECIPITATION IN GAMBIAN ESTUARY...................................... 54

DATA ACQUISITION ............................................................................................. 54 IPCC SRES SCENARIOS....................................................................................... 55 DOWNSCALING HADCM3 DATA TO THE GAMBIA ............................................................ 56

APPENDIX 7: EVAPORATION IN GAMBIAN ESTUARY ........................................ 57

THORNTHWAITE ................................................................................................. 57 LINACRE .......................................................................................................... 58 VALIDATING FORMULAS THORNTHWAITE AND LINACRE ..................................................... 59

APPENDIX 8: SALNST CODE.............................................................................. 60

APPENDIX 9: INPUT SALNST ............................................................................ 61

PRECIPITATION .................................................................................................. 61 EVAPORATION ................................................................................................... 62 GOULOUMBO ..................................................................................................... 64



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Introduction The Gambia River Basin Development Organisation (French acronym: OMVG) is entrusted with the task to plan the hydraulic development of the Gambia River Basin. In order to fulfil its mission, the OMVG published the Gambia River Basin Hydraulic Master Plan (from now on: Master Plan) in 1999. The Master Plan takes account of the hydroelectric and irrigation factors and their impacts on the physical environment (especially on the mangrove and fish species), the various water uses (irrigation, drinking water, navigation) and on the social environment (health, economic development). The salient points of the Master Plan consist of:

- Hydroelectricity production of 40 MW - Shift of saline intrusion in the dry season from Kilometer Point (KP) 254 to KP170 - Satisfaction of all water demands

The Master Plan suggests compensatory measures for negative impacts on health, agriculture, fish and mangroves, arising from modification of the natural flow regime. [1] In executing these intentions, logically, the ‘Feasibility study Report – Study of electric power generation and transmission in OMVG member countries’ (from now on: Feasibility Study) is the following step. The Feasibility Study gives further insights in the planning of the ‘Hydropower Project’, consisting of a design and construction schedule of the Sambangalou dam and the interconnection lines. Furthermore, it gives insight in the environmental, social and economical impacts of the hydropower generation. Dam design and environmental assessment in the Feasibility Study are based on hydrological studies, done by the Institute for Development Research (French acronym: IRD). These studies are entirely incorporated in the Feasibility Study as Volume 8: Gambia River environmental hydrology and its hydraulic modelling (from now on: Feasibility Study V8). [2] Both Master Plan and Feasibility Study take account of future water management scenarios for the Gambia River Basin. However, in doing so, the two reports turn out to be inconsistent with each other. The maximum projected hydroelectricity generation capacity changes from 40 MW in the Master Plan to 128 MW in the Feasibility Study. Where the Master Plan takes account of three hypotheses for irrigation, the Feasibility Study V8 takes does not take into account irrigation. On the other hand, the Feasibility Study V8 uses two sea level rise scenarios (20 and 50 cm respectively), whereas the Master Plan assumes the sea to remain at the same level. Both reports use historical data to determine rainfall, evaporation and flow regimes. To determine saline intrusion, both reports use the 1-D numerical model SALNST. The objective of the present study is to examine whether saline intrusion can be kept at KP170, with the satisfaction of all water demands, considering climate change and water requirements by the year 2100. In addition, two adaptation strategies are proposed in order to prevent problems resulting from contradicting aims. Results will only be valuable when used in the international context of the Gambia River Basin. Therefore, the Master Plan remains the basis for the present study. The authors hold on to the objective and approach of the Master Plan, which includes the use of the same model SALNST to calculate saline intrusion. Incorporating climate change into saline intrusion modeling involves the acquisition of new hydraulic data. For future precipitation and evaporation in the Gambian estuary, generic data for rain and temperature have been obtained from a Global Circulation Model. The scenarios taking account for the several factors are presented separately:

- 3 Irrigation development scenarios



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- 3 River geometry scenarios - 2 Evaporation scenarios - 5 Dam release scenarios

In order to make the objective and approach concrete, the present study includes eight steps:

- Analyzing literature on the Gambia River Basin and climate change studies for The Gambia

- Review on impact of saline intrusion on agriculture, mangroves and fish - Analyzing driving forces of saline intrusion - Acquiring latest climate change data - Defining scenarios for the factors irrigation development, evaporation and river

geometry - Defining five Gouloumbo dam release scenarios for the period 2070-2099, based

on future precipitation and dam release scenarios - Calculating saline intrusion length for separate and combined scenarios - Describing two adaptation strategies

This study is the first to focus on saline intrusion and provides a framework for updating assessments of climate change, irrigation or discharge scenarios in the Gambian estuary, as it is built up as transparently as possible. It introduces climate change to the Master Plan, as a relevant part of Gambia River Basin planning. It gives recommendations on dam management to fulfil all water requirements in future. In this, the authors hope to contribute to an optimal hydraulic development of the Gambia River Basin.



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Reading manual Chapter 1 gives an introduction to the Gambia River Basin. It explains the saline intrusion and hydraulic processes. The explanation of SALNST is given in the last section of this chapter. Chapter 2 to Chapter 4 concentrate on the processes in the Gambia River and deriving the input for the model SALNST. In Chapter 2, the economic and environmental issues are explained. This concerns mangroves, fishing industry and Gambian agriculture (including irrigation requirements). Chapter 3 concentrates on the effect of climate change. The effect of an increasing sea level on the Gambian estuary’s morphology and geometry as well as changing precipitation and evaporation are underpinned. Chapter 4 determines the discharge at Gouloumbo, which is used as upper boundary for the model SALNST. Dam release scenarios drawn up by the OMVG are explained and criticized. Chapter 5 summarizes the choices made for the SALNST input. The effect of different scenarios for irrigation, river geometry, evaporation and dam release are calculated separately. In the end, combined scenarios give an indication of the saline intrusion lengths in the future. As maximum saline intrusion lengths will not suffice the aim set by the OMVG, two adaptation strategies are introduced in Chapter 6. First, dam release scenarios are reconsidered. Minimum discharges needed to control the salt front and satisfy irrigation requirements are determined. The second adaptation strategy determines the salt front for a more conservatively increasing irrigation in The Gambia. Finally, Chapter 7 gives the conclusions and recommendations for future water management in Gambia River Basin.



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Chapter 1: Gambia River saline intrusion The Gambia River, 1150km long, takes its source at 1150m above Mean Sea Level and rubs through three countries: Guinea, where it rises; Senegal, with a catchment area covering the southeastern part of the country and; The Gambia, which the river traverses from end to end. The Gambia River Basin covers an area of approximately 77,054km2 (Figure 1.1). The Gambia River consists of two quite distinct parts of about 500km length, i.e. a continental and a maritime section, the last being influenced by tides throughout the year. In the dry season, the 1.0 g/l salt front intrudes the Gambia River up to 254 km upstream of Banjul (KP254).

1.1 Saline intrusion process To fix some ideas, the salt concentration of ocean water is 35 g/l and of fresh water below 0.1 g/l. In contrast to the estuary to its North; Sine-Saloum, and to its South; Casamance, the Gambian estuary is considered to be a ‘normal’ estuary with a decreasing salinity gradient from the mouth towards the head. The process of salinization and flushing is a yearly recurring dynamic event as a consequence of the distinct dry and wet seasons. At present, under natural conditions and with moderately exploited irrigation areas, the salt front of 1.0 g/l shifts yearly from around KP65 after the wet season, to KP254 at the end of the dry season. The extent of saline intrusion in Gambia River is mainly governed by the balance of outward advective transport by fresh water and inward dispersive salt transport from the Atlantic side, extended with the rainfall rate, which accounts for local rainfall and evaporation. The extent of advection at any location along the river depends on the discharge and the salinity at a particular moment. Likewise, the extent of dispersion at any location along the river depends on the dispersion coefficient, the cross-sectional

Figure 1.1: Gambia River Basin Area

Gouloumbo

Yallal

Sambangalou

KP170 Banjul

KP-13 KP254



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area and the salinity at a particular moment. The impact of local rainfall and evaporation at any location along the river depends on the river width, the concentration of salt and, naturally, on the amount of rainfall or evaporation at a given moment. [3] (Figure 1.2)

These processes can be summarized mathematically. The starting point for saline intrusion modelling is a one-dimensional advection-dispersion equation, averaged over the cross section and over the tidal cycle. This equation is extended with a component for rainfall and evaporation, thus:

0c c c

A Bcr Q ADt x x x

∂ ∂ ∂ ∂ + + − =

∂ ∂ ∂ ∂

A list of the used symbols is presented in Appendix 1: Notations. In this extended advection-dispersion, the term

cA

t

∂

∂ indicates the salt exchange (flux);

Bcr indicates the evaporation or rainfall;

cQ

x

∂

∂ indicates the advection, and;

cAD

x x

∂ ∂

∂ ∂ indicates the dispersion of salt

Note that the x -axis points in the upstream direction. Thus discharge by fresh inflow is normally negative. Further formula analysis done by Savenije is the foundation of SALNST [3].

1.2 Surface water Gambia River Basin Previous saline intrusion studies in Gambia River merely focus on saline intrusion in the river channel. Saline intrusion in contiguous aquifers is generally neglected. This is supported by an amount of base flow, even in the dry season, suggesting net flow from the aquifer to the river. Following the general line of research, this study focuses primarily on surface water. At the moment, the discharge mainly depends on the natural processes of evaporation and rain, including the drainage of the entire river basin. However, this natural scheme is about to change in the near future. The management plan for Sambangalou reservoir is expected to change the flow regime downstream significantly, by reducing the peak flow during the wet season and augmenting the base flow in the dry season. This smoothed

Dispersion

Advection Evaporation Rain

x

Figure 1.2: Basic system of saline intrusion in Gambian estuary



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availability of water during the year could reduce saline intrusion and increase irrigation opportunities. These irrigation opportunities are most widespread in The Gambia (Section 2.3). Considering human interventions and the character of this study, Gambia River Basin can be divided into three successive catchments: i) upper catchment, upstream of Sambangalou dam; ii) intermediate catchment, between Sambangalou and Gouloumbo and; iii) lower catchment: being the entire Gambian estuary and its tributaries. (Figure 1.3)

Obviously, the upper and intermediate catchment will be divided by the Sambagalou dam. The intermediate catchment changes into the lower catchment at Gouloumbo. At Gouloumbo, the river is already at sea level and under the influence of tides. Downstream of Gouloumbo, the tributaries are short or poorly fed, and thus testify to the considerable size of the lateral flood zones along the river valley. Any discharge in the estuary is therefore mainly governed by Gouloumbo flow. Gouloumbo is not just merely the place where the continental river turns into estuary, it is also in close proximity of the Gambian border. This is convenient for the purpose of this study, as it is possible to use Gouloumbo discharge as upper boundary condition in the saline intrusion model.

1.3 Estuarine morphology From the extended advection-dispersion equation in section 1.1 can be read that the flux, rate of rainfall and dispersion depend on the river geometry. This geometry can be deduced from the morphology of the Gambian estuary, the part of the river that is subject to saline intrusion. At Gouloumbo (KP530), Gambia River is already at sea level and under the influence of tides. This results into an extremely long estuary, which therefore can be divided in four reaches with different morphological characteristics. Upper reach, KP300 – KP530: The low water bed reaches up to 400 m. There is very little width difference between high and low water flow channel. Depth is between 3 m and 7 m. Sand and pebbles form the river bed. Upper estuary, KP150 – KP300: The high water bed has an average width of 5.5 km. The low water bed is wider than in the upper reach and is composed of muddy sand. This reach has many meanders and is anastomosing. Islands occur at a number of locations. The deepest parts of the estuary are within this reach, that has average depths of 8 – 16 m. A very healthy mangrove swamp has developed over a width of 3 km. Behind these

Banjul – KP 0

Legend: E = Evaporation Gam = Gambia DRS = Dam Release I = Irrigation Sen = Senegal Scenario P = Precipitation Gui = Guinea

EGam IGam PGam

DRS PGui

IGui

ISen PSen

Elake

Figure 1.3: Schematization natural processes and human intervention concerning

surface water



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swamps, there are flood zones covering a width of 1 km. Tributaries of between 2 km and 15 km length converge and flow into the river. Lower Estuary, KP20 – KP150: This reach is very wide, shallow (6 – 11 m) and less braiding than the upper estuary. Tidal flats, covered with 0.5 m of water at low tide are found along the edges, extending several kilometres to the south and a couple of hundred meters to the north. The channel of the river, about 3 km wide and 10 m deep, flows between these tidal flats. On either side of the high waterbed, mangroves grow over a distance up to 10 km wide. These mangroves are highly productive; therefore, the most productive fishing industries can be found within this reach. Estuary mouth, KP0 – KP20: Two narrow points limit tidal in- and outflows by reducing the wet section of the river. One is at Dog Island, where an overlooking continental plateau juts into the river; the other one is at Banjul, where a north-south sandbar forces the channel against Barra point. The river’s course is only 5 km wide at this point. Downstream of Kuntaur (KP254): The line of contact between the river channel and the continental plateau is very irregular, highlighting the existence of small independent valleys linked to the river valley. In this part of the river, subject to saline intrusion, swamps covers 1100 km2, mangroves 660 km2 and water 820 km2. [1]

1.4 Description of 1-D model SALNST To determine saline intrusion, the numerical model SALNST is used. This model, developed by Savenije [3], is used by both the Master Plan as the Feasibility Study V8 (Appendix 2: SALNST usage history). SALNST is an unsteady saline intrusion model based on the one-dimensional advection-dispersion equation, as explicated in section 1.1. This model, which applies to well mixed alluvial estuaries, has the possibility to introduce the influence of local rainfall and evaporation into the saline intrusion process. In addition, this model takes the flow reduction as a result of upstream water extractions into account. These extractions are caused by tidal swamp irrigation or pumping, as a function of cropping patterns and irrigated areas. River geometry is accounted for by depth, width and cross-section variables, the last two exponentially decreasing from the river mouth. The model was tested and applied on the Gambian estuary by Euroconsult. For the Gambian estuary, the model uses Gouloumbo as its upper boundary, whereas the lower boundary is located approximately 13 km downstream of Banjul. River-aquifer interaction is not accounted for. The structure of SALNST is presented in Appendix 3: Structure SALNST. The sensitivity of the model to its parameters has been examined in Appendix 4: Sensitivity Analysis. From this appendix, it can be concluded that large extractions of fresh water increase saline intrusion. These extractions can only be compensated by the import of ocean water into the estuary. Advection thus becomes negative, and since advection is more effective than dispersion, saline intrusion increases rapidly.



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Chapter 2: Economic and environmental issues The Gambian estuary is moderately exploited by small-scale fishing industries and is not polluted by either agricultural, industrial or shipping activities. [4] In the Gambian estuary, hypersalinity in the river channel is not prevalent. Hypersalinity is the acute increase of salinity in the upstream direction from the estuary mouth. It is a threat to the habitat as prevalent in neighbouring estuaries, where evaporation is high, and the fresh water inflow is low [5]. This chapter describes the impact of saline intrusion on vegetation, fish and crops. In addition, the irrigation water demand and irrigation process is explained.

2.1 Mangroves A detailed description of the mangrove species in the Gambian estuary and the impact of regulated flow can be found in the Master Plan. The Feasibility Study V8 argues that a temporary displacement of the salt front towards downstream would mean a the loss of mangroves. [6] As this study does not set a goal for maximum saline intrusion lengths further downstream than the Master Plan, it is unnecessary to repeat the assessment. However, in order to put in perspective the negative impact of an increasing saline intrusion on agriculture, it is important to highlight the basic functioning of mangroves.

2.1.1 Natural function Mangroves are the source of the organic richness of the estuarine waters and the fertility of flood plains. Through its primary production, mangroves provide the basis of the aquatic food chain and, due to its morphological characteristics, it provides a habitat for shallow water fish. The physical mechanism whereby the mangrove enriches the water and the flood plains can be summarised as follows. Fragments of vegetation from the mangrove are collected and carried from the undergrowth to the bolons and the river through the constant submersion/emergence cycle. During the rising tide, these fragments are suspended in the water; during ebb tide they are transported via the steepest slopes into the channels. Once they are suspended and circulating in the estuary, they start to decompose and provide nourishment for those organisms that feet on detritus and which constitute the basic food for fish. The finest particles of organic detritus combine with clay particles in suspension to form the organic silt which will recharge the fertilising capacity of the tidal reservoir before it is deposited at high tide. The mangrove also provides a shelter and perfect environment for spawning, laying and development of eggs and larvae. [1]

2.1.2 Growth conditions The mangrove zonation is related to both the frequency of flooding and the degree of salinity. To preserve the species in the Gambian estuary, the estuary needs to be flooded on a daily basis. In addition, mangroves are also prevalent in the transition zone characterised by less frequent flooding, between daily and monthly submersion. The two main species, Avicennia and Rhizophora, are characterised by their ability to adapt, when adult, to inter-seasonal variations in salinity. Avicennia withstands seasonal variations of between 30 and 100 g/l and Rhizophora between 0 and 40 g/l. However, a permanent reduction in salinity is expected to jeopardize reproduction possibilities, even for Rhizophora.



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2.2 Fishing industries The fishing industry in the Gambian estuary is predominantly focused on shrimp catchment for exporting purposes. Other estuarine fish have a good market value on the local market. [5]

2.2.1 Fish population Fish species in estuaries are categorized by their origin: continental, estuarine and marine. As expected, estuarine species dominate the Gambian estuary’s fish population. Continental species rarely occur within the estuary. It is suggested by Vidy that river flooding reduces the estuary’s function as a nursery ground for sea spawning species that cannot cope with low salinities [7]. Taking into account sea level rise and decreasing fresh water flooding, spawning opportunities will increase for marine species. Estuarine species reproduce mainly during the wet season, whereas sea spawning species have a more extended, yet overlapping reproduction period from May until November. Under regulated flow conditions, seasonal differences will decrease. A quantitative analysis of the impact on reproduction possibilities resulting from regulated flow is not available and beyond the scope of this study. Therefore, the hydraulic results of this study are not reflected on its impact on the fishing industry.

2.2.2 Shrimp abundance Shrimp exploitation for the European and West-African market has become increasingly important to Gambian fishing industry, overtaking fishing for regular fish for the local market. [5] According to Laë, fish resources are underexploited. Taking into account this underexploitation, and assuming that the fish population will remain unchanged as discussed above, shrimp exploitation is the main issue considering future fishing industries. Juvenile and sub-adult shrimps live in the estuary where their length of stay is approximately three months. The length of stay is influenced on water current and salinity. Values of 30 g/l favour a long stay until an average length of 13 cm [5]. Due to absence of hypersalinity in the river, sea level rise and regulated discharge are therefore expected to be in favour of shrimp abundance.

2.3 Agriculture in The Gambia Agriculture in The Gambia centers around the cultivation of rice, vegetables, fruits and peanuts. Salt water (>1.0 g/l) is fatal for all these crops, as are salinisated soils. For future agriculture, irrigation is considered to be the most profitable adaptation strategy to cope with irregular precipitation. Through irrigation, yields are expected to increase and, moreover, year-to-year variations decrease substantially [8]. Despite its promising qualities, irrigated agriculture in Gambia River Basin is still underdeveloped compared with the Senegal River valley. In total, around 4,900 ha has been developed in the river basin, 85% of which are on Gambian territory. Unfortunately, a third of this land has been abandoned due to land salinisation, design faults, lack of technical assistance to the rural population and other problems [1]. Gambian irrigation using surface water resources, primarily from the Gambia River, is used only for rice production. Mixed crops (vegetables and fruits) are either rain fed or irrigated by using groundwater resources. At present, the rice production surface area is 1,500 ha. A total area of approximately 17,700 ha is highly suitable for irrigation [1]. Considering that these areas are upstream KP170, the Master Plan aims to push back the salt front downstream KP170.



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Figure 2.1 shows four rice irrigation schemes and an example of highly suitable land when the saline front is stopped further downstream. Two mechanisms of surface water supply are used in these rice irrigation sites: pump irrigation and tidal irrigation.

2.3.1 Pump and tidal irrigation Pump irrigation is more expensive than tidal irrigation due to high investment and operational costs. In addition, irrigation water requirements are larger than for tidal swamp irrigation. Due to the good operational qualities and yield potential of tidal irrigation, the large pump irrigation site of Jahally (see Figure 2.1) is being turned into a tidal irrigation site at the moment of writing. Upstream KP300, only pump irrigation is possible, as the river channel is more confined and the tidal range decreases. Tidal irrigation indicates a system in which river water flows to the farmland at high tide. When preferable, the farmland can be drained at low tide in order to allow the rice to ripen and the soil to be cultivated. Tidal irrigation sites require high tide water levels that are high enough to inundate the fields and low tide water levels low enough to drain the fields adequately. These conditions are present downstream of KP300. Between KP170 and KP300, about 5,000 ha highly suitable area for tidal rice irrigation is yet unused. For mixed crops, highly suitable land is not available. [9] Adding the already exploited area of 1,500 ha, a total of 6,500 ha highly suitable area is available for tidal rice irrigation.

Tidal swamps are areas that are currently submerged at high tide and drained at low tide. From a hydrological point of view, these tidal swamps are the most efficient areas to be developed for rice production. This results from the facts that i) water is stored

KP254

Highly suitable tidal irrigation area

1

2

3

4

Figure 2.1: Tidal rice irrigation schemes Gambia River 1) Sukuta; 2) Kayai; 3) Jahaly and 4) Pacharr

0 km 5 km 10 km

Kuntaur



15

already in and on the soils of these tidal swamps and; ii) water is already consumed for evapo-transpiration. Per square meter, water requirements from these tidal swamps even exceed open water evaporation. [10]

2.3.2 Surface water requirements The Master Plan uses three water requirement assumptions (Table 2.1) for the areas in The Gambia that are either currently irrigated or potentially irrigable from Gambia River: - Assumption 1: irrigation of currently operating irrigation areas (1,500 ha of rice) - Assumption 2: irrigation of all currently existing irrigation areas (3,000 ha of rice) - Assumption 3: irrigation of all irrigable areas identified as having high suitability

(14,000 ha of rice, 3,700 ha of mixed crops)

Table 2.1: Water requirements [m3/s] in The Gambia resulting from three irrigation area

assumptions by the Master Plan

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1 4.2 2.6 3.3 3.7 1.4 0.1 2.8 0 0 1.6 2.0 1.1 2 8.5 4.6 5.9 6.5 2.4 0.1 5.5 0 0 3.1 3.9 1.5 3 42.4 25.4 32.9 34.8 14.3 0.9 25.9 0.1 0.1 13.9 17.0 8.6 Considering the priority given to irrigation by Gomez et al. as an adaptation strategy for agriculture in The Gambia [8], assumption 3 is the most probable water demand for the year 2100. In The Gambia, mixed crops require approximately 34% of the amount of water per square meter that rice demands [1]. To obtain SALNST input, the mixed crops area is multiplied by 0.34 and added to the rice area. Converted to rice production only, the projected highly suitable irrigable area is 15,300 ha imaginarily. If currently not inundated areas are developed for tidal irrigation (for example by excavating), water requirements are considered similar to pump irrigation water requirements. The water requirements for tidal swamps shown in Table 2.2 are derived from Euroconsult [10]. Water requirements for newly inundated land are obtained by dividing the water requirements of assumption 3 (Table 2.1) by the imaginary area highly suitable for rice production of 15,300 ha. These water requirements are used as monthly input variables for SALNST. Table 2.2: Extra rice water requirements from Gambia River for newly developed

irrigation [m3/s/1000ha]

Jan Feb Mar Apr May Jun Not inundated 2.779 1.665 2.156 2.281 0.937 0.059 Tidal Swamp 0.471 0.563 0.629 0.405 -0.451 -0.540

Jul Aug Sep Oct Nov Dec

Not inundated 1.697 0.007 0.007 0.911 1.114 0.564 Tidal Swamp -0.031 0.062 -0.108 0.201 -0.077 -0.035 Note that changes in evapo-transpiration due to increasing temperatures or modified rice varieties have not been taken into account.

2.3.3 Irrigation scenarios The authors emphasize that the total area highly suitable for tidal rice irrigation is not equivalent to the total area of tidal swamps. This is an important notion, as SALNST bases water requirements for tidal irrigation on the assumption that tidal irrigation replaces tidal swamps. A soil survey to determine the total area of tidal swamps, suitable for rice irrigation, has not been carried out. The intended area is at least 0 ha, and 6,500 ha at most. To deal with this uncertainty, two irrigation scenarios have been developed for both these extremes.



16

Scenario Irr1 assumes all tidal irrigation area are tidal swamp area. For this, a total area of (15,300-6,500) 8,800 ha is projected to be subject to pump irrigation. Scenario Irr2 assumes all tidal irrigation area are not inundated at the moment. As said, the actual areas of tidal and pump irrigation for assumption 3 are somewhere in between of scenarios Irr1 and Irr2. To show the impact of irrigation, the reference scenario Irr0 has been taken into account. Table 2.3 summarizes the irrigation scenarios. Table 2.3: Rice and mixed crops areas for tidal and pump irrigation

Rice [1000ha]

Mixed crops [1000ha]

SALNST [1000ha]

Tidal Pump Tidal Pump Tidal Pump At present 1.5 0.0 0.0 0.0 1.5 0.0 Scenario Irr0 0.0 0.0 0.0 0.0 0.0 0.0 Scenario Irr1 6.5 7.5 0.0 3.7 6.5 8.8 Scenario Irr2 6.5 7.5 0.0 3.7 0.0 15.3



17

Chapter 3: Climate Change Though the Master Plan has a focus on the future, it assumes absence of climate changes. This assumption however, is not justified by international scientific consensus. A rise in global temperature will change the climate in several ways. Firstly, it will lead to a rise in Mean Sea Level. This results from expansion of ocean water, and from the melting of ice around the poles. Secondly, it will change the hydrological process of evapo-transpiration and precipitation. Evapo-transpiration will increase, as it is correlated positively to the temperature. However, international scientific consensus has not yet been reached on the direction and magnitude of the change in precipitation. In addition, these changes will differ locally. Section 3.1 addresses the question of the impact of a sea level rise of 60 cm on saline intrusion in the Gambian estuary. The estuary will respond to sea level rise by changing water depths and changing river width. In order to take account of this response, river geometry scenarios are discussed as input for SALNST. Section 3.2 deals with changing precipitation and temperature and its consequences for evaporation.

3.1 Sea level rise According to the Intergovernmental Panel on Climate Change [11], sea level is projected to rise between 9 and 88 cm during the period 2000–2100. Unfortunately, the IPCC [11] does not provide a statistical probability distribution. The UK government advice for the next 50 years is a sea level rise of 6 mm/year [12]. Van Goor et al. however consider a rate of 56 cm/century most likely. [13] This study takes account for a sea level rise of 60 cm by the year 2100. For comparison: sea level rise at present is approximately 1.4 mm/year [12]. The question is how the Gambian estuary will adjust morphologically to a sea level rise of 60 cm. The influence of sea level rise of the estuarine morphology is twofold. Firstly, it influences the morphological process, which is governed by erosion, sediment transport and deposition. Secondly, it influences the equilibrium state of the estuary to the mean sea level. This follows from the assumption that any estuary can reach an equilibrium state to an invariable mean sea level. [12] [13] In addition, an estuary can maintain a dynamic equilibrium relative to a certain sea level rise, under conditions of sufficient sediment supply and internal transport capacity. [13] The estuary consists mainly of a river channel and tidal flats, which could both respond to sea level rise differently [13]. However, as this division of the Gambian estuary is not supported by SALNST, the Gambian estuary is considered as a whole. The projected response is based upon the present morphology discussed in section 3.1.1. The focus on the response is on the river geometry, is it is used as input for SALNST.

3.1.1 Morphological response of the Gambian estuary Sediment demand of the estuary results from a discrepancy between its actual and its equilibrium morphological volume. In the event of sea level rise, this demand may be positive. [13] If the estuary would be in a state of dynamic equilibrium at present and in future, sediment demand equals the volume increase as a result of sea level rise. Estimating surface area to be 921*106 m2 [3] and assuming a constant sea level rise of 6.0 mm/yr, volume change is estimated as:

6 2 3 6 3921*10 *6.0*10 / 5.5*10 /dV dh

O m m yr m yrdt dt

−= = =



18

Erosion Historically, Gambia River is the main supplier of sediment to the estuary, rather than the Atlantic. Marine sediment is hardly found beyond KP20, because most of marine sediment deposits at the sandbar at Banjul.1 As sediment from the upper catchment will be cut off by the Sambangalou dam, the question arises whether the amount of sediment from tributaries and river will be sufficient to satisfy sediment demand. This can be estimated only roughly, with high uncertainty, since sediment concentration measurements are available only for the year 2002. Measurements from July 1st to November 5th 2002 show an average sediment concentration of 23.3 mg/l at Kedougou (near Sambangalou) and 42.1 mg/l at Gouloumbo [1]. Cutting off the upper catchment and using average intermediate flow for the dry season from Appendix 9: Input SALNST yields:

3 3 3* 202.1 / *(42.1 23.3)*10 / 3.8 /dM

Q C m s kg m kg sdt

−= = − =

Assuming erosion only to take place from July-November (125 days), total yearly sediment volume is:

3 3 3 3

3

3.8 /1.4*10 / 15.5*10 /

2650 /sed

dV dM kg sm s m yr

dt dt kg mρ−= = = =

Albeit estimated roughly, it is clear sediment availability is unable to meet sediment demand. At the downstream boundary, sea level rise could introduce residual marine sediment into the estuary, especially in the event of reduced river water flushing. This could assist the lower estuary to keep pace with sea level rise to some small extent, but probably not the upper estuary (>KP150). In addition to sediment demand and availability, sediment transport can constrain the ability of an estuary to keep pace with sea level rise. Long-term tide induced net sediment exchange between the channel and tidal flats of the estuary takes the character of diffusion [13]. But as sediment supply is considered insufficient, complex sediment transport computations remain unnecessary at the moment. Redistribution As the external forcing factor of sea level rise and lack of sediment import is assumed, the idea of upriver movement of the estuary arises. The base for this idea is a fixed sediment budget and a redistribution of this sediment due to changing energy gradients. This requires an increase in waves propagating in from the ocean as a result of the deeper water. This could erode the tidal flat sediments. The eroded sediments could move up the estuary, where they would be redeposited. Increased sea level in a typical trapezoidical cross-section leads to increased tidal volumes and, thus, to increased bed shear stress. In response, the cross-section widens, reducing velocities and shear stress until the critical thresholds have been crossed. This process is repeated along the length of the estuary although as tidal volumes decrease upriver, the cross-sectional response decreases as well. An Eulerian interpretation of this process would indicate that all cross-sections have migrated upriver and the migration distance will be governed by the initial increase in tidal discharge. For the Humber Estuary it is demonstrated that the migration distance decreases upriver, indicating that the landward transgression is accompanied by a change in planimetrical shape. The estuary is becoming more expansive at the mouth and it is also migrating landward. [12]

1 Derived from M. Njie, Department of Water Resources, Banjul, personal communication, April 2005



19

This would seem the likely chain of events, yet a sandbar crossing north to south at Banjul prevents waves propagating in from the ocean. If the sandbar is able to keep pace with sea level rise, it is unlikely large amounts of lower estuary’s sediment will be eroded and transported upriver. The tidal prism will remain limited by the sandbar. In addition, mangroves are very stable and prevent the river banks from erosion. The large area of mangroves breaks the little waves that propagate in the Gambia Estuary. However, sea level rise is expected to drown some of the mangroves and shift the area of mangroves in the direction perpendicular to the river channel.

3.1.2 River geometry simplifications for modelling Savenije has simplified the river geometry for the model SALNST into depth, width and cross-section variables, the last two exponentially decreasing from the river mouth. Savenije’s simplifications do not address the more complex river geometry pointed out in section 1.3. An attempt to incorporate the four reaches described in section 1.3, taking the channel as the element determining saline intrusion, leads to results presented in Appendix 4: Sensitivity Analysis. The results show a dramatic increase of saline intrusion. As historic data do not support such large intrusion lengths, the authors stick with Savenije’s geometrical simplifications, as the fit of this model use is by far more clear (Appendix 2: SALNST usage history). Width is determined by the width at the river mouth, decreasing exponentially upstream with coefficient b:

0( ) bxB x B e=

The coefficient b can be determined from a map or aerial photographs. In addition, it can be determined mathematically, based on the continuity equation [3]:

0 0

fHb

E h= −

In which H represents the average tidal range, E0 the average tidal excursion and factor f results from the fact that high tide is not reached at the same time along the estuary. The value of f varies between 0.8 and 0.9. The approach using a map is preferred, but has failed. The best map available is a 1:272,000 scaled GIS-map from the National Environmental Agency, on which the contour intervals of 5 m do not provide a sufficient level of accuracy. The discontinuous pattern of the estuary makes it even more difficult to be accurate. The two different scenarios determined, are therefore based on the mathematical approach.

3.1.3 River geometry scenarios Considering the morphological response of the Gambian estuary, the most probable result of any sea level rise is an increase of water depth throughout the estuary. In defining saline intrusion, the most important question is how this will affect the cross-section of the perpetual fresh water section. This follows from the fact that the extra volume will have to be filled with fresh water, which therefore can not be used in withstanding saline intrusion. Considering the present morphology, width will not change much upstream KP300. However, as tides influence the water level up to Gouloumbo, it is very likely water levels throughout the estuary will increase proportionally with the sea level. Scenario Geo0 represents the reference scenario. This includes the river geometry at present, including present water depths. Note that this scenario is below the threshold value of 9 cm sea level rise, projected by the IPCC.



20

Scenario Geo1 considers B0 to grow at the same rate as h0, which gives a proportional increase of width and cross-section throughout the estuary. Scenario Geo2 considers the width and associated cross-section at the river mouth to widen to a larger extent. As river width is expected to remain the same upstream KP 300, b is increased by 10 %, which is the range for coefficient f. A0 is determined inversely, using b as ‘width expanding coefficient’ with its base at KP300. Table 3.1 shows geometrical characteristics for the different scenarios. Note that the tidal prism, calculated by SALNST, is expected to change significantly under both scenarios Geo1 and Geo2. Table 3.1: Geometrical characteristics for River geometry scenarios

Tidal Prism [106m3]

Width mouth [m]

Water depth [m]

Width reduction coeff. [10-5]

Geo

0-

174

174-

300

300-

340

0-

174

174-

300

300-

340

0 810 17000 9.0 6.0 6.0 1.922 0.5088 0.5088 1 864 18100 9.6 6.6 6.6 1.922 0.5088 0.5088 2 1090 25244 9.6 6.6 6.6 2.114 0.5597 0.5088

3.2 Precipitation and evaporation At the upstream boundary, the saline concentration is about 0.1 g/l and the river width is relatively small. Furthermore, the rate of rainfall directly to the river ‘ r ’ hardly affects the discharge, because of this small width. At the downstream boundary, the influence of r is hardly felt, as the ocean salinity dominates the salinities at the mouth. Consequently, r (positive in case of dominant rain, negative in case of evaporation) mainly plays a role in the middle of the Gambian estuary. [3] The effect on the 1.0 g/l salt front is less, being subordinate to the process of advection-dispersion. Since climate change is a global issue, a Global Circulation Model (GCM) is used to gain data on future temperature and precipitation. GCMs are generally based upon emission scenarios drawn by the IPCC [14]. Because of the high uncertainty of future climate data, a proper explanation of data acquisition is explained in Appendix 6: Precipitation in Gambian estuary. The rain and evaporation data used are argued in section 3.2.1 and 3.2.2.

3.2.1 Precipitation The effect of precipitation in the fully mixed Gambian estuary depends on rain which falls directly on the water and a certain amount of runoff from the tidal swamps. Conceptually, the rainfall coefficient CR caters for minor tributaries and groundwater recharge, and together with measured rainfall Rm it determines effective rainfall Re:

e R mR C R=

The CR parameter could be split into Cswamps, Ctributaries and Cgroundwater by using a water balance, but data necessary to carry out such disaggregation is not yet available. Rainfall data for the 2070-2099 period are derived directly from the DWR downscaled HadCM3 data (Figure 3.1).



21

3.2.2 Evaporation The level of evaporation depends on the size of the estuary and, in particular, on the size of the surface area. As temperature is the only input available for the period of 2070-2099, evaporation is determined by the formula of Thornthwaite [15] and of Linacre [16]. Two models are used to increase the outcome certainty. As solar energy, wind and relative humidity also influence the evaporation, the data obtained remain estimations. Wind speed is low in the middle estuary. Table 3.2 presents data obtained. The 2010-2039 calculation is used to check the differences between the models. Calculations are explained in Appendix 7: Evaporation.

Figure 3.1: Monthly rainfall in Yallal for the period 2070-2099. Figure shows downscaled data from the Global Circulation model HadCM3.

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.400

0.450

0.500

2070 2072 2074 2076 2078 2080 2082 2084 2086 2088 2090 2092 2094 2096 2098

Year

Rain [m/month]



22

Table 3.2: Future open water evaporation calculations

1979-2002 Difference 2010-39 Difference 2070-99 MeanTemperature [°C] 28.0 +0.6 28.6 +3.2 31.8 Thornthwaite [m] 2.08 +0.05 2.13 +0.27 2.40 Linacre [m] 2.27 +0.07 2.34 +0.35 2.69

As shown in Table 3.2 and Figure 3.2, Linacre’s formula gives higher estimates, although the difference between the two is rather small. Maximum temperatures, minimum temperatures and evaporation of 1979-2002 are used to validate the models. For lack of data, the years 1981, 1996, 2000 and 2001 are neglected. As these data come from up country, it is hardly influenced by wind. The data are obtained by PAN-evaporation measurement. These should be multiplied by 0.77 in order to obtain open water evaporation data. [17]

Table 3.3: Validation open water evaporation outcome Thornthwaite and Linacre with

measured data

1979-2002 Mean yearly [m] Difference [%] Deviation [m] Measured 2.00 - 0.55 Thornthwaite 2.08 4.0 0.07 Linacre 2.27 13.5 0.08 As shown in the Table 3.3, Thornthwaite evaporation prediction is more accurate, just like its deviation. For this, his formula appears to be better. However, as Linacre does not differ extremely and shows more extreme evaporation in 2100, its outcome is valuable as well. Both scenarios are used to determine the effect of changing evaporation: Evap1 uses Thornthwaite; Evap2 uses Linacre. As the Linacre outcome seems high already, additional deviation has not been introduced. Mean monthly evaporation for 2100 is given in Table A7.1 (Thornthwaite) and Table A7.2 (Linacre). In SALNST, evaporation for all thirty years is inserted.

Figure 3.2: Future open water evaporation

according to temperature-based formulas

0

0.5

1

1.5

2

2.5

3

1980 2000 2020 2040 2060 2080 2100

Year [-]

Evaporation [m]

Thornthwaite Linacre



23

Chapter 4: Catchment upstream Gouloumbo The Sambangalou dam gives opportunities to augment base flows to create irrigation opportunities and to control saline intrusion during dry season. Regulated flow will lead on average to a reduction in downstream flood discharges from August to October, and to augmented base flows from December to June. According to the Master Plan, a guaranteed permanent fresh water discharge has to maintain the 1.0 g/l salt front below KP170. The Master Plan concludes water requirements for irrigated agriculture are completely satisfied over the period 1971-1996. The discharge obtained at Gouloumbo is always equal to or higher than the target hydrograph, which is itself 50 m3/s higher than the estimated crop requirements. As the Master Plan misinterpreted the model outcome, even less water is needed to maintain the salt front at KP170 (Appendix 2: SALNST usage history). However, according to IRDs Feasibility Study V8, water management at the Sambangalou dam is only driven by hydroelectric power generation. Important issues like irrigation and saline intrusion control are generally neglected and do not influence dam management. This chapter describes the scenarios in the Feasibility Study V8 report and give accompanying Gouloumbo discharges. Gouloumbo discharge is used as upper boundary condition for the model SALNST and consists of dam release at the dam and the flow from the intermediate catchment. Irrigation, evaporation and precipitation in the upper catchment influence dam level while irrigation and precipitation in the intermediate catchment directly influence the Gouloumbo discharge. However, Guinean and Senegalese climate data could not be obtained. Guinean precipitation is considered to be accounted for in the dam management scenarios. For precipitation data in the intermediate catchment, assumptions have been made coherent with section 3.2.

4.1 Upper catchment: Sambangalou dam In this section, the fundamentals for producing hydro power are described. The amount of power generated depends on the water level. If the water level is between level S1 and S2, a constant power P is produced. Power P is lower than the maximum output. If the level is below S1, power is not generated. If the water level rises above S2, the maximum water quantity will be turbined. (Figure 4.1)

Figure 4.1: Rules for generating hydro-power

Future open water evaporation (section 4.1.1) and irrigation in Guinea (section 4.1.2) both affect the lake’s water level. Neglecting these processes could have consequences for future dam functioning. Feasibility Study V8 designed different scenarios with different size of power P and heights S1 and S2 (section 4.1.3).

S2

S1

Rule 2: water level between S1 and S2, constant power P is produced.

Rule 1: water level below S1, power can not be generated efficiently.

Rule 3: water level above S2, turbine maximum water quantity to reduce risk of overspill.



24

4.1.1 Open water evaporation artificial lake Open water evaporation in the artificial lake is a great loss of fresh water to the Gambia River Basin. However, the extent of evaporation is not easy to determine, since there is direct evaporation data is not available. Ideally, a lake water balance should be used:

( , , ) ( ) ( ) ( ) ( )in groundwater release

dVE z PET t P t Q t Q t Q t

dt= + + − −

However, the data available is not compatible: Qin is available for the period 1954-2001, but the matching Qrelease is only available graphically. In addition, one could imagine that the river-aquifer interaction will change due to the lake. The balance is bound with high uncertainties. Therefore, the authors adopt an evaporation at present of 10 m3/s from the Master Plan. Estimating an average lake surface area (A) of 152 km2 [6] this corresponds with 2.08 m/yr. This is quite similar to the open water evaporation in Gambian estuary, as calculated by Thornthwaite’s formula in section 3.2.2. Adopting 2070-2099 evaporation of 2.40 m/yr from this section means open water evaporation increases with 0.32 m/yr (E). When considering dam management scenario A, this means power cannot be produced for more than thirteen days. Under scenario B, this is almost eleven days:

Scenario A:

6* 0.32*(152*10 )( ) 13.3

* 44*(3600*24)

E AT days days

Q t= = =

Scenario B:

6* 0.32*(152*10 )( ) 10.8

* 54*(3600*24)

E AT days days

Q t= = =

4.1.2 Irrigation Guinea At the moment, only 30 out of 28,000 ha potentially irrigable land has been developed for irrigation. The largest limitation to Guinean irrigation development is extreme isolation. Any large-scale irrigation development program will require a great deal of preliminary work to open up the area, in terms of road infrastructure in particular. A medium-term objective of developing 2,000 ha of lowlands and 400 ha of pilot irrigation schemes would appear reasonable according to the Master Plan. In long-term the Master Plan predicts an increasing development could even be a lot more. During wet season, the rainfall is sufficient to meet the water needs of most crops. In the dry season (about eight months), 2,400 ha would require 25.6*106 m3/year (I). The Master Plan concludes this represents only 1% of the average annual inflow at the dam site (2,245*106m3) and will therefore have only a minor impact on the water level. However, the authors note that irrigation in Guinea will have considerable effect, which will be negative to power production throughout the whole period:

Scenario A:

625.6*10( ) 6.7

* 44*(3600*24)

IT days days

Q t= = =

Scenario B:

625.6*10( ) 5.5

* 54*(3600*24)

IT days days

Q t= = =

4.1.3 Dam release scenarios The quantity turbined per kilowatt is inversely proportional to the head, thus, a large amount of electricity is generated after the wet season. In this period, the lake is at its highest level. IRD designed two different scenarios, A and B, both with power generation



25

P, dam release Q, height S1 and height S2. When shortages occur and water level drops below S2, scenario B is complemented with: - Dam release scenario C1 (no power from 16 - 30 June); - Dam release scenario C2 (no power from 1 - 30 June); - Dam release scenario C3 (no power from 15 May – 30 June) and; - Dam release scenario C4 (no power from 1 May – 30 June). Scenarios C1 and C3 are interpolations of B, C2 and C4. Since time increments in the saline intrusion model SALNST are monthly, and the interpolated scenarios C1 and C3 add little insights, for the present study it is chosen just to compute scenarios A, B, C2 and C4. In the absence of the dam management simulation model SIMULGAM, values have been estimated visually from the f=0.5-curve in Figures 4.2 and 4.3. As f represents the exceedence frequency, it means that half of the time the curve will be above and the other half of the time below the 0.5-curve. Therefore, this is the best estimate of the mean release, currently available. Though this approach is not most accurate or flexible, two comments can be made in its favor:

1. The upper catchment is influenced by a climate different from that prevailing at Basse. This approach separates the consecutive catchments, therefore the influence of rain in the intermediate and lower catchment can be pointed out quite clear.

2. As our interest is in downstream hydraulics, scenarios C2 and C4 can be seen as scenario B with a lower exceedence frequency. This supports a ‘no regret’-principle, which prevails at DWR.

Scenario A: Simple power demand for an installed capacity of 77 MW and a permanent “high management” parameter. The lake’s level under scenario A and rule 2 is between 188 and 196m: turbine throughput corresponding to the flow required to produce power equal to predefined value Ptar. When the lake level exceeds 196 meter, turbines are used at full capacity. (Table 4.1) Table 4.1: Power generation information scenario A

Rule 1 Rule 2 Rule 3 h [m] <188 188-196 >196 P [MW] 0 27,6 77 time [%] 2.6 64.5 32.9 Q [m3/s] 0 44 126 According to the Feasibility Study V8 (Figure 4.2), the 126 m3/s dam release (P=77MW) can be maintained from September until January (f=0.5). As the water level drops below 196 m in January, dam release will drop to 44 m3/s (P=27.6MW).



26

Scenario B (and C): Simple power demand for an installed capacity of 128,3 MW and a permanent `high management´ parameter limited to the month of August (and suspending power generation at the end of minimum flow period). The Lake’s level under scenario B and C and rule 2 is between 188 and 196m; turbine throughput corresponds to the flow required to generate predefined power Ptar. When pond level exceeds 196 m, turbines are used at full capacity. (Table 4.2) Table 4.2: Power generation information Dam release scenarios B and C

Rule 1 Rule 2 Rule 3 h [m] <188 188-196 >196 P [MW] 0 34.3 128 time [%] 3.5 83.1 13.4 Q [m3/s] 0 54 212 According to the Feasibility Study V8 (Figure 4.3), the 212 m3/s dam release (P=128MW) can be maintained only in October one in two years (f=0.50). As the water level drops below 196 m already in November, the dam release will drop to 54 m3/s (P=34.3MW). Scenario C2 and C4 show the consequences of stopping power generation at the dry season’s end. Under these circumstances, water is not released from the dam’s reservoir.

Figure 4.3: Daily discharges under scenario B and C

Figure 4.2: Daily discharges under scenario A



27

4.2 Intermediate catchment In defining discharge in the intermediate catchment, a runoff model based on a catchment water model has been used:

max( ) ( ) ( , , )dz

Q t P t E z PET t Sdt

= − −

In which z(t) is relative moisture storage and maxS is the maximum storage holding

capacity of the catchment. Model parameters maxS , runoff production parameter ε , and

groundwater discharge rate of over spilling aquifer(s) α in Table 4.3 are derived from

Njie (2002), who used a combination of heuristic and automatic calibration procedures, with due care given to physical correlates of parameters. [18] As said, the authors assume especially parameter α to change as a consequence of the Sambangalou dam.

Table 4.3: Hydraulic characteristics of the upper and intermediate catchment

Upper (Sambangalou)

Upper & Intermediate (Gouloumbo)

ε 0.281 0.137

α [mm/d] 0.610 0.206

maxS [mm] 800 900

Area [km2] 7,080 42,000

Since climate data in the intermediate section was not available, downscaled HadCM3 data have been used for precipitation in the intermediate section. Due to its location, Basse is considered to be the best approximation. This is in line with Njie (2002), though Basse data are not used for precipitation in the upper catchment, which is subject to a climate that is more wet. As mentioned in section 3.2.1, the downscaled HadCM3 data are highly uncertain. However, as precipitation in the intermediate catchment only influences wet season’s Gouloumbo flow, this uncertainty does not have a major impact on maximum saline intrusion length.

4.2.1 Domestic water demand Very little surface water is consumed for domestic purposes. In the long term, this will not exceed 0.4 m3/s, i.e. less than 1% of the target hydrograph discharge. Therefore, this was not taken into account in defining dam release scenarios.

4.2.2 Irrigation Senegal Irrigated agriculture is still underdeveloped compared with the Senegal River valley. A total of 650 ha has been developed for irrigation (out of a potential 4,100 ha of highly suitable land), and more than half has been abandoned. As the Gambia River is extremely deeply embanked in Senegal, water has to be pumped up to significant heights (around 15 m during low flow periods) and the profitability of crops is impaired considerably. Large irrigation changes in Senegal are not expected, according to the Master Plan. For the near future, developing 2,000 ha of lowlands, or very localized small irrigation areas around villages using pumping seems to be a reasonable aim. For the far future, it is fair to assume all highly suitable land will be used for irrigation. For water requirements a month, see Table 4.4 [1]. Note that change in the future evaporation has not been taken into account for irrigation in Senegal. Table 4.4: Irrigation requirements Senegal for assumption 3 [m3/s]

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Q 6.4 5.0 6.4 5.5 2.6 0.3 1.9 0 0 1.3 2.2 2.1



28

4.3 Gouloumbo discharge Gouloumbo discharge can be obtained for every scenario during the year:

Gouloumbo scenarioSambangalou Intermediate IrrigationSenegalQ Q Q Q= + −

Previous studies do not account for the possibility of bringing power generation to stop due to irrigation and increasing open water evaporation in Guinea. Section 4.1.1 and 4.1.2 argued a structural stop in power production for 16 days under scenario B. SALNST uses a monthly time step. Saline intrusion is susceptible to absence of flow, rather than to low flow for a longer period. Therefore, a scenario D’ calculates with a structural decrease in power production of one month. To determine the impact of half a month, the intrusion lengths of C4 and D’ are averaged and represented by - scenario D (no power from 15 April – 30 June). Figure 4.4 shows the mean natural Gouloumbo Discharge (1954-2001) and the Gouloumbo discharge under scenario A and B (2070-2099). Note that the total yearly amount of water is expected to decrease as a result of increasing evaporation, irrigation development and decreasing rainfall. An overview of intermediate flow and dam release obtained is given in Appendix 9: Input SALNST.

Figure 4.4: Mean Gouloumbo discharge during the year

0

100

200

300

400

500

600

700

800

900

1 2 3 4 5 6 7 8 9 10 11 12

Month [-]

Discharge [m3/s]

Natural Flow

Scenario A

Scenario B



29

Chapter 5: Scenarios computed Saline intrusion is defined by the Department of Water Resources of The Government of The Gambia as the 1.0 g/l salt front. Salinity profiles are previously studied in preparation of saline intrusion modeling. [3] Therefore, the 1.0 g/l saline intrusion length in wet and dry years are shown, which could possibly occur between 2070 and 2099. These saline intrusion lengths are calculated by SALNST and presented as Kilometer Points. Section 5.1 describes which variables affecting saline intrusion are changed and what strategy is taken to evaluate their effect on saline intrusion. In addition, the SALNST input is summarized. Section 5.2 presents the results of the computed scenarios.

5.1 Calculation strategy and input SALNST To determine the impact of the multitude of variables, the variables are calculated separately. Dam release scenarios A, B and D are used. River geometry, depending on sea level rise, is calculated with and without changing width and width-reduction coefficient. Evaporation has been derived from the Thornthwaite and the Linacre formulae, both of them using temperature projections. Different Gouloumbo flow sequences are calculated, consisting of dam release scenarios and natural runoff from the intermediate catchment. Table 5.1 defines the scenarios for the different factors. Table 5.1: Scenarios used in saline intrusion modeling. Those scenarios typed in bold are

used for further analysis in sections 5.2.1, 5.2.2, 5.2.3 and 5.2.4.

Factor Section Scenario Explanation Irr0 Reference: no irrigation Irr1 Highly suitable fully developed: 14,000 ha rice and

3,700 ha mixed crops. 6,500 ha tidal irrigation Irrigation 2.3

Irr2 17,700 ha pumped Geo0 Reference: no geometrical change Geo1 River widens proportionally to sea level rise of 60

cm by 2100 River

geometry 3.1

Geo2 River widens disproportionally to sea level rise of 60 cm by 2100

Evap1 Evaporation determined by Thornthwaite formula Evaporation 3.2

Evap2 Evaporation determined by Linacre formula A 0.5 frequency-curve of IRDs Scenario A B 0.5 frequency-curve of IRDs Scenario B C2 Dam release B, no release from 1 – 30 June C4 Dam release B, no release from 1 May - 30 June

Dam release

4.3

D Dam release B, no release from 15 April – 30 June Table 5.9 and Figure 5.7 and Table 5.10 and Figure 5.8 show the scenarios that earn a closer view. These scenarios are likely to occur and are therefore the base for the next chapters. Considering evaporation, scenario Evap1 (Thornthwaite) is considered most likely. The actual irrigation development projection is between Irr1 and Irr2. As the estuary’s response to sea level rise remains uncertain, both scenarios Geo1 and Geo2 are calculated. Since dam release scenarios A, B and D are considered, this leads to a total of twelve combined scenarios. Note that these combined scenarios are not evenly likely, as D represents B, but for a frequency of 0.05 instead of a 0.5-frequency under scenario B. However, the combined scenarios give a good range for the saline intrusion lengths that are likely to occur in the period 2070 – 2100. Monthly input details are found in Appendix 9: Input SALNST.



30

5.2 Results This section first shows the separate effect of irrigation; river geometry; evaporation and dam release on saline intrusion. Combination of these factors give most likely future intrusion length in the Gambian estuary.

5.2.1 Irrigation Differences between irrigation scenarios do not vary significantly among the dam release scenarios, which is shown in Table 5.2 and Figure 5.1. The impact of uncertainty on the area of tidal swamps that can be developed for irrigation is represented by the difference between scenarios Irr1 and Irr2. Differences in maximum saline intrusion lengths are within the range of 19 – 25 km for wet years and of 24 – 30 km for dry years respectively. Compared to the reference scenario Irr0, maximum saline intrusion increases over a distance of 22 – 54 km for wet years and of 30 – 65 km for dry years.

Table 5.2: Impact irrigation on maximum 1.0 g/l salt front [km]

(Evap1 and Geo0)

Irr DamR SIL (wet) SIL (dry)

A 156 162

B 142 154 0

D 242

A 178 197

B 165 185 1

D 272

A 199 227

B 184 215 2

D 296

Figure 5.1: Impact irrigation on maximum 1g/l salt front in dry years

(Evap1 and Geo0)

0 25 50 75 100 125 150 175 200 225 250 275 300

A

B

D

Dam release scenario [-]

Maximum saline intrusion length [km]

Irrigation 0 Irrigation 1 Irrigation 2



31

5.2.2 River geometry Maximum saline intrusion is expected to increase under a projected sea level rise of 60 cm. Table 5.3 and Figure 5.2 show the saline intrusion lengths under the river geometry scenarios. Compared to the reference scenario Geo0, saline intrusion lengths shift over a distance between 8 and 19 km. River geometry can be considered to have a significant impact on the saline intrusion lengths.

Table 5.3: Impact river geometry on maximum 1.0 g/l saline front [km]

(Irr1 and Evap1)

Geo DamR SIL (wet) SIL (dry)

A 178 197

B 165 185 0

D 272

A 190 210

B 176 195 1

D 280

A 195 213

B 181 198 2

D 284

Figure 5.2: Impact river geometry on maximum 1g/l salt front in dry years

(Irr1 and Evap1)

0 25 50 75 100 125 150 175 200 225 250 275 300

A

B

D



Geometry 0 Geometry 1 Geometry 2



32

5.2.3 Evaporation Different evaporation scenarios show small differences in the maximum 1.0 g/l salt front. This is shown in Table 5.4 and Figure 5.3. The difference between the Thornthwaite and Linacre predictions is merely 3 or 4 km, well under the yearly variations. Table 5.4: Impact evaporation on maximum 1.0 g/l salt front [KP]

(Irr1 and Geo0)

Evap DamR SIL (wet) SIL (dry)

A 178 197

B 165 185 1

D 272

A 181 201

B 168 188 2

D 276

0 25 50 75 100 125 150 175 200 225 250 275 300

A

B

D



Evaporation 1 Evaporation 2

Figure 5.3: Impact evaporation on maximum 1.0 g/l salt front in dry years

(Irr1 and Geo0)



33

5.2.4 Dam release The reason dam release scenarios C2, C4 and D give such alarming maximum saline intrusion lengths as shown in Table 5.5 and Figure 5.4, is the integration of irrigation under these scenarios. Saline intrusion lengths increase exponentially when dam release is stopped. (C2 represents one month; C4 two and D two and a half month stop in dam release). This can be derived from the continuity equation and an exponentially decreasing cross-section in the upstream direction. Dam release scenario A results into a larger saline intrusion length than scenario B. However, only lower exceedence frequencies of scenario B have been taken into account (C2, C4 and D), since it is more likely that dam release is stopped under scenario B. Table 5.5: Impact different Gouloumbo flow on maximum 1.0 g/l salt front [KP]

(Irr1, Evap1 and Geo0)

DamR SIL (wet) SIL (dry)

A 178 197

B 165 185

C2 211

C4 255

D 272

Figure 5.4: Impact different Gouloumbo flow on maximum 1.0 g/l salt front in dry

years

(Irr1, Evap1 and Geo0)

0 25 50 75 100 125 150 175 200 225 250 275 300

A

B

C2

C4

D





34

5.2.5 Combined scenarios Even in a wet year, with all tidal irrigation being formerly tidal swamps (Irr1), with a small impact on river geometry by a rise in mean sea level (Geo1) and with the most positive dam release scenario (B), the salt front can not be kept downstream of KP170. Under scenario A, salt water will intrude Gambia River between KP190 and KP243 at maximum. Under scenario B, maximum saline intrusion will be encountered between KP176 and KP230; and when dam release is stopped at the end of the dry season, the saline intrusion could go up to KP309. The difference in maximum saline intrusion between the river geometrical scenarios is less than 6 km in a wet year, and even smaller in a dry year. Table 5.6, Figure 5.5, Table 5.7 and Figure 5.6 give the intrusion length for different irrigation, geometry and dam release scenarios. Table 5.6: 1.0 g/l salt front for combined scenarios for Geo1 [KP]

DamR Irr Evap Geo SIL (wet) SIL (dry)

A 1 1 1 190 210

B 1 1 1 176 195

D 1 1 1 280

A 2 1 1 210 241

B 2 1 1 196 228

D 2 1 1 306

0 25 50 75 100 125 150 175 200 225 250 275 300 325

Irr 1

Irr 2

Irrigation [-]


Dam release A Dam release B Dam release D

Figure 5.5: Maximum 1.0 g/l salt front for combined scenarios in dry years for Geo1



35

Table 5.7: 1.0 g/l salt front for combined scenarios for Geo2 [KP]

DamR Irr Evap Geo SIL (wet) SIL (dry)

A 1 1 2 195 213

B 1 1 2 181 198

D 1 1 2 284

A 2 1 2 215 243

B 2 1 2 200 230

D 2 1 2 309

Summary:

- Extraction of irrigation water attracts the salt front in a dry year between 30 and 65 km

and in a wet year between 22 and 54 km, depending on the tidal swamp area developed

for irrigation

- Changing geometry due to a sea level rise of 60 cm pushes the salt front upriver by 8 to

19 km

- The differences in the attracted salt front between the evaporation predictions are about

3 - 4 km

- Scenario B gives better results in comparison with scenario A. The probability of stopping

water release at the end of the dry season is higher under scenario B. The extra salt

front attraction could go up to 87 km

- Even in wet years, the salt front can not be kept at KP170

- Under scenario A, the probability of stopping water release at the end of the dry season

is smaller. The saline intrusion is between KP190 and KP243

- Under scenario B, saline intrusion is between KP176 and KP198

- When water release is stopped at the end of the dry season, the salt front can go up to KP309

Figure 5.6: 1.0 g/l saline front for combined scenarios in dry years for Geo2

0 25 50 75 100 125 150 175 200 225 250 275 300 325

Irr 1

Irr 2

Irrigation [-]


Dam release A Dam release B Dam release D



36

Chapter 6: Adaptation strategies Blocking saline intrusion at KP170 with the proposed dam release scenarios is not possible in combination with the development of irrigation sites with an area of 17,700 ha. The target of KP170 and development of 17,700 ha are both derived from the Master Plan. This chapter will give two possibilities to deal with this conflict. Persevering the targets requires a certain water supply and regime, which could be in defiance with hydro-electricity targets. After discussions with the Department of Agriculture, it emerged that irrigation development upstream of KP228 is the main target for The Gambia.2 Therefore, dam release necessary to withstand saline intrusion at KP228 is calculated as a possible adaptation strategy in section 6.1. In section 6.2, the irrigation area is decreased and the effect of developing tidal swamp areas is examined. Less fresh water is required for crops and therefore more fresh water remains available to withstand saline intrusion.

6.1 Target hydrograph for agriculture The Master Plan determined that a net base discharge of 50 m3/s would withstand saline intrusion at KP170. The Master Plan simply added water requirements resulting from irrigation assumptions to this base discharge of 50 m3/s. This exercise has been repeated for the purpose of this adaptation strategy. Table 6.1 shows the net base discharge needed to withstand saline intrusion at KP170 or KP228, under the river geometrical scenarios. The values have been calculated iteratively by using SALNST. Table 6.1: Gouloumbo flow needed to stop saline intrusion

(Irr0 and Evap1)

KP Geo Qnet [m3/s]

170 0 37 170 1 42 170 2 45 228 0 17 228 1 20 228 2 20

Water requirements resulting from irrigation are not included. Therefore, irrigation for both Senegal and The Gambia is re-introduced in Table 6.2.

Table 6.2: Gouloumbo flow needed to fulfil irrigation requirements [m3/s]

Irr Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

1 34 23 29 28 8 -3 17 0 -1 11 12 7

2 49 30 39 40 17 1 28 0 0 15 19 11

Combining the Gouloumbo flow needed to stop saline intrusion at KP170 or KP228 and the Gouloumbo flow needed to fulfil irrigation requirements, results into the target hydrograph. However, as river flushing in the wet season is neglected, these target hydrographs can be considered too high. The combination of Table 6.1 and Table 6.2 show that the salt front reaches KP170 or KP228 in a certain month, the accompanying discharge is needed immediately at that point to stop further intrusion.

2 Derived from B. Jallow, Department of Agriculture, Banjul, personal communication, April 2005



37

6.2 Reducing irrigation development A plea for tidal swamp irrigation has already been discussed in section 2.3. Saline intrusion can not be resisted at KP170, therefore an alternative strategy is focussing on the development of tidal swamp land. The irrigation scenarios Irr1 and Irr2 are reconsidered. Pump irrigation is turned off, in order to keep focus on the development of tidal swamps for irrigation. This leads to a tidal irrigation area of 6,500 ha under scenario Irr1, and 0 ha under scenario Irr2. Since a large part of highly suitable land is upstream KP228, 6,500 ha of highly suitable land is assumed to be possible under scenario D as well. The results are shown in Table 6.3. Table 6.3: 1.0 g/l salt front for adjusted irrigation scenarios:

development of tidal swamps only [KP] (Geo1 and Evap1)

DamR Tidal [1000ha] SIL (wet) SIL (dry) 6.5 163 173

A 0 163 169 6.5 154 164

B 0 151 161 6.5 255

D 0 255

The area used for tidal swamp irrigation does not influence the saline intrusion length as the swamps already inundate at high tide. Turning off pump irrigation pushes back the salt front approximately 26 km in wet years and 36 km in dry years. For comparison, check values under Geo 1 in Table 5.3. Under dam release scenario D, the salt front can not be maintained at KP228. The saline intrusion of KP255 equals present saline intrusion. Since it is more likely that dam release is stopped under scenario B, scenario A is used to calculate the maximum amount of pump irrigated area to keep the maximum saline intrusion length at KP228. By using an iterative process to keep maximum saline intrusion downstream of KP228, the maximum area subject to pump irrigation is 12,500 ha. The area suitable for tidal irrigation upstream KP228 is 4,300 ha. (Appendix 5: Cumulative irrigable areas) If half of this suitable land (2,100 ha) is currently tidal swamp area, the total area available for irrigation can be estimated on 14,600 ha. Note that this is under the condition that the dam release from the Sambangalou dam’s reservoir is not suspended.

Summary:

- To maintain the salt front at KP170, 42 m3/s is needed, not taking into account irrigation

- To maintain the salt front at KP228, 20 m3/s is needed, not taking into account irrigation

- Add irrigation water requirement from Table 6.2, and the minimum Gouloumbo flow needed

to maintain the salt front at KP170 or KP228 can be calculated

- If only developing tidal swamp area, the saline intrusion is reduced with 25 km in wet years

and 35 km in dry years

- Even without irrigation, the salt front goes up to KP255 under scenario D

- Tidal swamp irrigation hardly influences saline intrusion - Under scenario A, the total irrigation potential is about 14,600 ha



38

Chapter 7: Conclusions and recommendations The results are based on the 1-D numerical model SALNST. The very complex system of advection and dispersion largely depends on water movements and river geometry. The numerical model simplifies both water movements as well as river geometry. In addition, as the focus of this study is in future, assumptions were made to estimate future natural water supply. The authors stress that saline intrusion lengths are the results of simplified calculations based on estimated data. Therefore, these results can not be considered as exact predictions of saline intrusion lengths. However, validation of the simplified 1-D model shows quite a good fit with historic data of maximum saline intrusion lengths. In addition, the assumptions made are well considered and underpinned. Parts of the uncertainties are accounted for by several scenarios. For these reasons, the results of this study can be considered as a good indication of saline intrusion under the conditions set. Structural monitoring activities as well as updating assessments are vital elements to put this study in perspective.

7.1 Conclusions The Gambia River Basin Hydraulic Master Plan by the OMVG concludes that the minimum flow necessary to stop saline intrusion at KP170 is 50m3/s, leaving irrigation requirements out of consideration. However, the numerical saline intrusion model used in the Master Plan takes its origin 13 km downstream of Banjul, while the Master Plan assumes this origin to be at Banjul. This study argues that the minimum flow necessary is only 42m3/s. In the Feasibility Study Report: Study of Electric power generation and transmission in OMVG member countries, adjustments made to the numerical saline intrusion model are not justified. Since power production is the only management parameter, irrigation in the entire Gambia River Basin is generally neglected and saline intrusion is only examined as a side effect from dam management. Increasing evaporation as a consequence of a global rise in temperature has not been taken into account. Periods of stopping dam release can occur at the end of the dry season, when irrigation requirements are high. Irrigating 14,000 ha of rice and 3,700 ha of mixed crops attracts the salt front by 32 – 60 km in dry years and 25 – 47 km in wet years, depending on the surface area of tidal swamp that is cultivated. Assuming that this surface area is 2,100 ha (equivalent to half the area highly suitable for tidal irrigation upstream from KP228), irrigation shifts saline intrusion in the upstream direction by 49 km in dry years and 34 km in wet years. Changed river geometry due to a sea level rise of 60 cm pushes the salt front 10 – 20 km further upstream, depending on the morphological response of the estuary. Significant difference in saline intrusion cannot be observed between the two projections of open water evaporation from the estuary. Dam release influences the salt front substantially. Compared to dam release scenario B, scenario A allows the salt front to intrude the river for an additional 13 km. Stopping dam release for one month attracts the salt front by 24 km; two months leads to an attraction of 70 km; and two and a half month even attracts the salt front by 87 km. These dramatic shifts of the salt front result from the continuity equation: when water extraction exceeds Gouloumbo flow, ocean water is attracted into the estuary. This advective transport of salt water in the upstream direction will accelerate saline intrusion quickly, as advection is a more effective transport mechanism than dispersion.



39

Combining these scenarios and accounting for future precipitation and evaporation shows the salt front can not be kept downstream of KP170. Under scenario A, the maximum salt front will be between KP190 and KP243; and under scenario B between KP176 and KP230, depending on rainfall and the total area of tidal swamp cultivated. Stopping dam release from the dam’s reservoir for 2.5 months at the end of the dry season could attract the salt front up to KP309, upstream of the tidal irrigation areas. When the Sambangalou dam is operating, there is not a hydraulic constraint to keep saline intrusion downstream of KP228. When ensuring a discharge of 20 m3/s enlarged with the water requirements to fulfil irrigation requirements, the salt front is kept at KP228 and 14,000 ha of rice and 3,700 ha of mixed crops can be irrigated. However, as water demand remains a political issue, this requires some organizational conditions. Setting the target of maximum saline intrusion at KP228, a dry area of 12,500 ha can be irrigated under dam release scenario A, apart from the cultivation of tidal swamps. Estimating 2,100 ha of tidal swamp area suitable for tidal irrigation, the maximum irrigation area under scenario A is 14,600 ha. Note that the area of potentially irrigable land decreases after adapting the target of KP228. Stopping dam release for 2.5 months without extracting irrigation water requirements still gives an intrusion length up to KP255, equal to the present maximum saline intrusion length. Under scenario D, the Sambangalou dam does not have a positive effect on Gambian agricultural development.

Summary:

- Previous studies on future saline intrusion either base on incorrect model assumptions

or neglect irrigation or climate change

- Net flow necessary to keep salt front at KP170 is 42m3/s instead of 50m3/s

- Dam release could be stopped for 0 - 2.5 months

- Irrigation water needs attract the salt front 32 - 60 km in dry years and 25 – 47 km in

wet years, depending on the swamp irrigation area

- Sea level rise pushes the salt front 8 - 19 km further upstream, depending on the

morphological response of the estuary

- Advective salt transport pulls the salt water for an additional 24 km when dam release

is stopped for 1 month; 70 km for 2 months and 87 km for 2.5 months

- Two different open water evaporation scenarios show no significant difference

- Under scenario A, salt front will be between KP190 and KP243; and under scenario B

between KP176 and KP230. This range covers for rainfall and the total surface area of

cultivated tidal swamp

- Stopping dam release at the end of the dry season could attract the salt front up to

KP309, upstream of the tidal irrigation areas

- When ensuring a discharge of 20 m3/s enlarged with the water requirements to fulfil

irrigation requirements, the salt front is kept at KP228 and the 17,700 ha can be

irrigated

- Setting the target of the maximum saline intrusion at KP228, a dry area of 12,500 ha

can be irrigated under dam release scenario A. This estimates does not include the

cultivation of tidal swamps

- Under scenario D, the Sambangalou dam does not have a positive effect on Gambian

agricultural development.



40

7.2 Recommendations The OMVG is entrusted with the task to plan the hydraulic development of the Gambia River Basin. As in-house capacity is insufficient, consultants are being hired for the technical advice needed. However, if knowledge or manpower is insufficient, a second opinion from within the OMVG is impossible. The knowledge of the lower level (national) institutes can be very valuable in obtaining such a second opinion, but can only be utilized when reports, methods and modeling instruments are fully transparent. This chapter gives three recommendations for further action. Section 7.2.1 recommends a survey on cultivable tidal swamp areas, section 7.2.2 proposes a yearly water budget and section 7.2.3 argues recalculation of dam release scenarios.

7.2.1 Survey on cultivable tidal swamp areas It is shown that cultivation of tidal swamps has not a negative impact on saline intrusion. On the other hand, the area of pump irrigation influences the salt front substantially. Therefore, cultivation of tidal swamps is preferable to cultivation of dry land. It is recommended to do a survey on the area of cultivable tidal swamps. From a hydrological point of view, it is important to determine the difference in water demand between tidal and pump irrigation. In addition, crop water requirements are likely to increase under a rise in global temperature. From an agricultural point of view, a soil survey is needed to verify the conditions for rice growth. Finally, this tidal swamp area has to be tested not only on physical conditions, but also on economic conditions like internal rate of return and the availability of labor and infrastructure. Because of the great relevance for irrigation development programs, it is recommended that this survey on cultivable tidal swamp area is carried out within the Department of Agriculture, assisted by the Department of Water Resources of The Gambia.

7.2.2 Yearly water budget agreement Water is essential for irrigation and for hydropower generation. Furthermore, irrigation and power have a daily influence on the lives of many people within the Gambia River Basin. Therefore, a high certainty of available surface water for power production and irrigation, improves the quality of life directly. This pleas for a year-to-year dam release scenario. This dam release scenario should be the optimal scenario for the year concerned, taking into account power production, saline intrusion and irrigation targets. Fortunately, the information needed for such a planning is available already to a large extent of certainty at the end of the wet season. By this time, the water budget for the whole year can be determined as the amount of rainfall, live storage and salinity profiles can be measured. The factors requiring a (potentially) large water demand from Gambia River can be monitored. This includes accounting for the monitored growth rates of the four water demanding factors: agriculture (irrigation and saline intrusion), power production, industry and households. Due to its international character, such a year-to-year water budget has to be agreed on within the context of the OMVG. The Permanent Water Committee of the OMVG appears to be the right panel for monitoring.



41

7.2.3 Recalculation of dam release scenarios The yearly water budget agreement has to be founded by simulations that show all water requirements are fulfiled. It is recommended to redo the calculations of the dam release scenarios. This study assists such recalculations. Irrigation using surface water resources from Gambia River has to be integrated under the new dam release scenarios. The aim to keep maximum saline intrusion downstream of KP170 can be reconsidered. Since it is the estimated target of the Department of Agriculture, KP228 is recommended as the new goal, at least for the near future. In reconsidering this goal, a decision has to be made on whether a minimum base flow for agricultural purposes (irrigation and saline intrusion), independent of power production, is preferable or not. Open water evaporation is bound to change due to a rise in temperature. In addition, river-aquifer interaction is bound to change due to the forming of an artificial lake. These changes can only be measured as the residual item on the water balance in Gambia River Basin. This residual item can be monitored in order to anticipate on these losses in defining the water budget. Proper modeling of estuarine morphology is expensive and therefore not recommended for the sole purpose of saline intrusion control. Since the OMVG is responsible for defining dam release scenarios, it is recommended that the OMVG takes responsibility the recalculation of dam release simulations.

Summary:

- Survey on cultivable tidal swamp areas by the Department of Agriculture

o Cultivation of tidal swamps does not have a negative impact on saline intrusion

o Difference in water demand between pump area on higher grounds and tidal area

o Crop water requirements under a rise in global temperature

o Economic conditions like internal rate of investment and availability of

infrastructure and labor

- Yearly water budget agreement within the OMVG

o Sustainable development of power production and irrigation

o Quantity of water is known at the end of the wet season and the various water

demands can be tuned and communicated

- Recalculation of dam release scenarios by the OMVG/IRD, accounting for:

o Decision on a minimum base flow for agricultural purposes, leaving power

production out of consideration

o The goal of KP170 for maximum saline intrusion. This depends on irrigation

development programs and the survey on cultivable tidal swamp areas

o Future open water evaporation from dam’s reservoir

o All water extractions, including future irrigation Guinea, Senegal and The Gambia

o Generic hydraulic data instead of historic data



42

Acknowledgements This study is conducted at the Department of Water Resources (DWR) in Banjul, The Gambia. The authors are highly appreciative to DWR for providing the resources necessary. Special thanks to B. Gomes and M.S. Jallow for providing the information needed, and to S. Sanyang for being a very knowledgeable guide on the field trip. Very special thanks to M. Njie, who proved to be a outstanding supervisor, having great knowledge of hydrology, modeling techniques and Gambia River. Crucial point in this report was the availability of software model SALNST. Disinterestedly H.H.G. Savenije let us use his software for which we give our gratitude. This study is part of the curriculum of Civil Engineering and Management at the University of Twente. The authors express thanks to J.G. de Kiewit and especially K.M. Wijnberg for their feedback and input.



43

References [1] Sogreah Ingenierie, Hydroconsult International and SCET-Tunisie (1999), Gambia

River Basin Hydraulic Master Plan. Consultancy report prepared for OMVG. Dakar. [2] Institut de Recherche pour le Développement (IRD) (2004). Feasibility Study

Report: Study of Electric power generation and transmission in OMVG member countries - Volume 8: Reports on Gambia River environmental hydrology and its hydraulic modelling. IRDs contribution to consultancy report by COTECO group prepared for OMVG, Dakar.

[3] Savenije, H.H.G. (1988). Influence of rain and evaporation on salt intrusion in estuaries. Journal of Hydraulic Engineering, volume 114, no 12.

[4] Albaret, J-J. et al. (2004). Fish diversity and distribution in the Gambia Estuary, West Africa, in relation to environmental variables. IRD, Dakar.

[5] Laë, R. et al. (2004). Effects of a targeted shrimp (Penaeus notialis) exploitation on fish catches in the Gambia Estuary. IRD, Dakar.

[6] Institut de Recherche pour le Développement (IRD) (2004). Feasibility Study Report: Study of Electric power generation and transmission in OMVG member countries - Volume 1: Executive Summary. IRDs contribution to consultancy report by COTECO group prepared for OMVG, Dakar.

[7] Vidy, G. et al. (2003). Juvenile fish assemblages in the creeks of the Gambia Estuary. IRD, Dakar.

[8] Gomez, B. et al., (2004). Adaptation to Climate Change for Agriculture in The Gambia: An explorative study on adaptation strategies for millet. Department of Water Resources, Banjul.

[9] AGRAR und HYDROTECHNIC GMBH, Howard Humphreys Limited (1986). Kekreti reservoir project.

[10] Euroconsult (1986). Assessment of possibilities for tidal irrigation along the Gambia River.

[11] Intergovernmental Panel on Climate Change, Third Assessment Report (2002). [12] Pethick, J. (2001). Coastal management and sea level rise. University of

Newcastle. [13] Van Goor, M.A. et al. (2003). Impact of sea level rise on the morphological

equilibrium state of tidal inlets. Delft Hydraulics and Delft University of Technology.

[14] Intergovernmental Panel on Climate Change (2000), Special Report on Emission Scenarios. Cambridge University Press, New York.

[15] Wilson, E.M. (1983). Engineering Hydrology, page 47-49. University of Salford. [16] Linacre, E.T. (1994). Estimating U.S. Class-A pan evaporation from few climate

data. [17] Linsley, R.K. Jr. et al. (1982). Hydrology for Engineers, Singapore. [18] Njie, M. (2002). Second Assessment of Climate Change induced Vulnerabliity in

the Gambian Water Resources Sector and Adaptation Strategies. Department of Water Resources, Banjul.



44

List of Figures and Tables

Figures Figure 1.1: Gambia River Basin Area Figure 1.2: Basic system of saline intrusion in Gambian estuary Figure 1.3: Schematization natural processes and human intervention concerning surface water Figure 2.1: Tidal rice irrigation schemes Gambia River Figure 3.1: Monthly rainfall in Yallal for the period 2070-2099. Figure shows downscaled data from the Global Circulation model HadCM3. Figure 3.2: Future open water evaporation according to temperature-based formulas Figure 4.1: Rules for generating hydro-power Figure 4.2: Daily discharges for scenario A Figure 4.3: Daily discharges for scenario B and C Figure 4.4: Mean Gouloumbo discharge during the year Figure 5.1: Impact irrigation on maximum 1.0 g/l salt front in dry years (Evap1 and Geo0) Figure 5.2: Impact river geometry on maximum 1.0 g/l salt front in dry years (Irr1 and Evap1) Figure 5.3: Impact evaporation on maximum 1.0 g/l salt front in dry years (Irr1 and Geo0) Figure 5.4: Impact different Gouloumbo flow on maximum 1.0 g/l salt front in dry years (Irr1, Evap1 and Geo0) Figure 5.5: Maximum 1.0 g/l salt front for combined scenarios in dry years for Geo1 Figure 5.6: 1.0 g/l saline front for combined scenarios in dry years for Geo2 Figure A3.1: Water depth in dry season of 1977-1978, using the comprehensive method (measured depth at one point in a river section) Figure A3.2: Water depth in December 2004, using the more sophisticated echo sounder method (average of depths measured with an 0.5m-interval over the whole river section) Figure A3.3: Calculation difference between DWR model use and OMVG model use Figure A3.4: Validation of the DWR model use for 1.0 g/l salt front



45

Tables Table 2.1: Water requirements [m3/s] in The Gambia resulting from three irrigation area assumptions by the Master Plan Table 2.2: Extra rice water requirements from Gambia River for newly developed irrigation [m3/s/1000ha] Table 2.3: Rice and mixed crop area for tidal and pump irrigation Table 3.1: Geometrical characteristics for River geometry scenarios Table 3.2: Future open water evaporation calculations Table 3.3: Validation open water evaporation outcome Thornthwaite and Linacre with measured data Table 4.1: Power generation information scenario A Table 4.2: Power generation information scenarios B and C Table 4.3: Hydraulic characteristics of the upper and intermediate catchment Table 4.4: Irrigation requirements Senegal for scenario 3 [m3/s] Table 5.1: Scenarios used in saline intrusion modeling. Those scenarios typed in bold are used for further analysis in sections 5.2.1, 5.2.2, 5.2.3 and 5.2.4 Table 5.2: Impact irrigation on maximum 1.0 g/l salt front [km] (Evap1 and Geo0) Table 5.3: Impact river geometry on maximum 1.0 g/l saline front [km] (Irr1 and Evap1) Table 5.4: Impact evaporation on maximum 1.0 g/l salt front [KP] (Irr1 and Geo0) Table 5.5: Impact different Gouloumbo flow on maximum 1.0 g/l salt front [KP] (Irr1, Evap1 and Geo0) Table 5.6: 1.0 g/l salt front for combined scenarios for Geo1 [KP] Table 5.7: 1.0 g/l salt front for combined scenarios for Geo2 [KP] Table 6.1: Gouloumbo flow needed to stop saline intrusion (Irr0 and Evap1) Table 6.2: Gouloumbo flow needed to fulfil irrigation requirements [m3/s] Table 6.3: 1.0 g/l salt front for adjusted irrigation scenarios: development of tidal swamps only [KP] (Geo1 and Evap1) Table A1.1: Notations Table A4.1: Sensitivity analysis input parameters SALNST Table A5.1: Cumulative net surface [Ha] of irrigable areas in the Gambia Table A7.1: Mean open water evaporation according to Thornthwaite’s formula [m/mth] Table A7.2: Mean open water evaporation according to Linacre’s formula [m/mth] Table A7.3: Validation Linacre and Thornthwaite Table A9.1: Precipitation Yallal [m] Table A9.2: Evaporation input SALNST according to Thornthwaite formula [m] Table A9.3: Evaporation input SALNST according to Linacre formula [m] Table A9.4: Sambangalou dam release for different scenarios [m3/s] Table A9.5: Irrigation Senegal Table A9.6: Natural flow intermediate between Sambangalou and Gouloumbo



46

Appendices Appendix 1: Notations Appendix 2: SALNST usage history Appendix 3: Structure SALNST Appendix 4: Sensitivity analysis Appendix 5: Cumulative irrigable areas Appendix 6: Precipitation in Gambian estuary Appendix 7: Evaporation in Gambian estuary Appendix 8: SALNST code Appendix 9: Input SALNST



47

Appendix 1: Notations In this study the symbols in Table A1.1 are used: Table A1.1: Notations

A time-average cross-sectional area [m2]

0A cross-sectional area at estuary mouth [m2]

a convection coefficient [m/s]

B width of estuary [m]

0B width at estuary mouth [m]

b estuary shape coefficient [1/m]

c salt content [g/l]

Ec evaporation coefficient [-]

Rc rainfall coefficient [-]

0c salt content at estuary mouth [kg/m3]

D effective time-average dispersion [m2/s]

0D dispersion at estuary mouth [m2/s]

E tidal excursion [m]

eE open water evaporation [m]

pE potential evapotranspiration [m]

0E constant tidal excursion [m]

f factor [-]

g acceleration of gravity [m/s2]

0h constant estuary depth [m]

H tidal amplitude [m]

K Van der Burgh coefficient [-]

L saline intrusion length [m]

P tidal prism [m3]

Q discharge [m3/s]

fQ fresh upstream discharge [m3/s]

r rainfall rate [m/s]

eR effective rainfall [m]

mR measured rainfall [m]

t time [s]

T tidal period [s]

x distance from estuary mouth [m]



48

Appendix 2: SALNST usage history Since 1995 the OMVG uses the numerical model SALNST to compute saline intrusion in Gambia River. For the Department of Water Resources, the present report is the first to make use of the model. Since the model was obtained directly from its creator H.H.G. Savenije, the authors compared the original data with the modifications made by the OMVG. SALNST is used in two OMVG reports:

1. Gambia River Basin Hydraulic Master Plan, Summary Report, February 1999 (in short: Master Plan);

2. Feasibility Study Report – Study of Electric Power Generation and Transmission in OMVG Member Countries, Volume 8: Reports on Gambia River environmental hydrology and its hydraulic modeling, March 2004 (in short: Feasibility Study V8)

Both reports support a multi-purpose dam at Sambangalou. SALNST was used to define the 1.0 g/l salt front as a result of different dam release scenarios. However, a simple mistake has been made as the model uses a different origin for presenting river km. Though Banjul is commonly defined as the estuary mouth, SALNST defines the estuary mouth approximately 13 km downstream of Banjul, in order to achieve a fixed boundary condition for ocean salinity (35 g/l). As a consequence, the Master Plan structurally overestimated saline intrusion approximately by 13 km. The Feasibility Study V8 spotted the poor fit of the modelled data compared to the measured data. After changing the height parameter to 6.0 m for the whole estuary, the approximation of the 1.0 g/l salt front improved. However, these changes were not founded and not coherent with height measurements (Figure A2.1 and A2.2). Furthermore, the Feasibility Study V8 decreased the evaporation coefficient, but this is not consistent with an expected rise in temperature. Moreover, it is not consistent with a decreasing water depth. After inquiring H.H.G. Savenije, he confirmed the possibility of a shifted x-axis by the model. After undoing the modifications made in the Feasibility Study V8, and comparing the computations of the unchanged model with the Feasibility Study V8 computations, it comes clear that any comparison is pointless (Figure A2.3). The outcomes of the Master Plan are still valid, when reduced by 13 km. A validation of the unchanged model is shown by Figure A2.4.



49

Figure A2.2: Water depth in December 2004, using the more sophisticated echo

sounder method (average of depths measured with an 0.5m-interval over the whole river section)

-25

-20

-15

-10

-5

0

0 50 100 150 200 250 300 350

River kilometres - KP

Water depth [m]

Figure A2.1: Water depth in dry season of 1977-1978, using the comprehensive

method (measured depth at one point in a river section)

-25.0

-20.0

-15.0

-10.0

-5.0

0.0

0 50 100 150 200 250

River kilometres - KP

Water depth [m]

Nov-77

Dec-77

Jan-78

Feb-78

Apr-78

May-78

Jun-78

Mar-78



50

Figure A2.3: Calculation difference between DWR model use and OMVG model use

1/10/1970

2/9/1970

3/11/1970

4/10/1970

5/10/1970

6/9/1970

7/9/1970

8/8/1970

9/7/1970

10/7/1970

11/6/1970

12/6/1970

-13

53

123

193

263

0

2

4

6

8

10

12

14

16

18

Salt concentration [g/l]

Date [-]

PK from Banjul [km]

Regulated flow 1970: outcome Savenije minus outcome OMVG

Figure A2.4: Validation of the DWR model use for 1.0 g/l salt front

y = 1.0136x

R2 = 0.934

0

50

100

150

200

250

300

0 50 100 150 200 250 300

Measured 1g/l front

Modelled 1 g/l front



51

Appendix 3: Structure SALNST SALNST is basically built up as follows:

a. Script: <filename>.for b. Input: the model has two input files: one for model variables and one for monthly

hydrologic data: <filename>.dat and <filename>.hdr. c. Output: Two output files are generated by the program: <filename>.geo and

<filename>.out. The first output file gives geometrical information on the estuary, the latter gives the calculated salinities as a function of time and place. The latter file is of such a size, that it can be imported in an Excel Spreadsheet for plotting and analysis.

The main input parameters and data for the model are [2]:

1. Monthly time increment records: irrigated agriculture water requirements [m3/s/1000ha], estuary evaporation losses [m/month], estuary rainfall [m/month] and upstream (in this case: Gouloumbo) flow input [m3/s] ;

2. Ocean salinity and upstream river salinity [g/l]; 3. Initial Gouloumbo flow [m3/s] to quantify an initial salinity profile under

permanent conditions; 4. Average length of a tidal period [s], average tide amplitude [m] and tide

attenuation coefficient [-]; 5. Multiplying factors to take account of estuary rainfall and evaporation; 6. Surface area of irrigated crops for which water is taken from estuary [1000ha]; 7. Flow section [m2] and depth [m] at river mouth; 8. River geometry parameters for different reaches. The estuary is represented in

the form of two successive reaches. Each reach is characterized by a fixed water depth and a width, exponentially decreasing in the upstream direction by coefficient b [m-1];

9. Calculation time increment [1, 2, 3, 5, 6, 10, 15 or 30 days].



52

Appendix 4: Sensitivity Analysis This appendix gives an overview of the sensitivity of all the parameters used by the model SALNST, except for the parameters of ocean salinity, tidal period and time increment. Table A4.1 shows the outcomes of the maximum saline intrusion lengths for wet and dry years respectively for the 2070-2100 period, for the minimum and maximum values of the parameter concerned. The table shows the model is especially sensitive to changes in water depth, the area of pumped irrigation and the (initial) flow. Table A4.1: Sensitivity analysis input parameters SALNST Unit Minimum Maximum Default

Value Wet Dry Value Wet Dry Value

1 Estuary evaporation m/month 0.100 151 154 0.300 157 164 Thornthwaite

2 Estuary rainfall m/month 0 153 161 max 150 158 HadCM3

3 Initial flow m3/s 4 287 142.5 114 Scen B

4 River salinity g/l 0.01 150 160 0.1 150 161 0.1

5 Tidal range m 1 151 161 1.2 151 160 1.1

6 Attenuation coeff - 0.8 150 160 0.9 150 160 0.8

7 Coefficient Rain - 2 151 161 4 150 161 3

8 Coefficient Evap - 0.5 151 152 1 150 160 0.7

9 Area pump 1000 ha 0 150 160 30 182 214 0

10 Area tidal 1000 ha 0 150 160 6.5 149 161 0

11 A0 m2 153000 150 160 180000 158 167 153000

12 B E-05/m 1.922 150 160 2.1 141 149 1.922

A0 & b 150 160 150 160 -

13 ∆h m 0 150 160 0.8 154 162 0

14 3rd Reach (h=12) km - - - - 258 283 -

15 4rd reach km - - - - 201 252 -

16 Water requirements m3/s/ha Savenije 156 166 Evap + 160 173 Savenije

Notes concerning input in Table A4.1:

2. The measured values of the wettest year of the period 1961-1990 (i.e. 1988) are used for maximum rainfall

3. The average flow of Scenario B is being used as maximum Initial flow below 4 m3/s gives a long-term salt front beyond KP340 Initial flow of 12 m3/s gives a long-term salt front at KP170

12. Only the first reach (0-174 km) is examined 14&15. The adjusted river geometry is based on section 1.3 Estuarine

morphology 16. Maximum crop water requirements are based on increased evapo-transpiration

as a result of climate change. Area Pump is set at 9000 ha.

14 Reach b x A h 0 0 0 153000 9.0 1 -7.51E-06 163000 45345 9.0 2 -1.70E-05 313000 4721 12.0 3 -5.09E-06 340000 1706 5.0 15 0 0 0 108000 9.0 1 -4.38E-05 20000 45003 9.0 2 -3.93E-06 150000 30004 10.0 3 -1.34E-05 300000 4803 12.0 4 -5.09E-06 340000 1632 5.0



53

Appendix 5: Cumulative irrigable areas

Table A5.1: Cumulative net surface [Ha] of irrigable areas in the Gambia Net surface = 0.8*gross surface



54

Appendix 6: Precipitation in Gambian estuary This appendix gives background information on i) Data acquisition ii) IPCC SRES Scenarios and iii) GCM downscaling process.

Data acquisition Past climate change studies in The Gambia that have used Global Circulation Model (GCM) results to predict future climate change demonstrated a considerable variance and inconsistency in their projections, depending on the GCM. Thus, selection of the GCM defines the character of the data considerably. In their study Adaptation to climate change for agriculture in The Gambia, Gomez et al. [8] faced the same problem. In the end they chose to work with The Hadley Centre’s HADCM3, representing the most extreme reduction in precipitation and a rather extreme rise in temperature in relation to four other GCMs (NCAR, CCCMA, ECHAM, and CSIRO). This choice was partially based on the results of previous climate change studies of The Gambia (US Country Studies and National Communication to UNFCCC), and partially on information from current GCM indications of the Gambia. On the other hand, they chose the HadCM3, because this model fits with DWR’s “no-regret” principle. Since their arguments are viable for the present study, a second assessment of GCMs has not been carried out. The downscaled HadCM3 data, provided by DWR, are being used. These data are based on the IPCC Special Report on Emission Scenarios (SRES) A2 scenario. In SRES, IPCC defined four scenarios [14]. Because all four IPCC SRES scenarios are evenly likely, the A2 scenario has been adopted without further inquiry. Background information on the IPCC SRES scenarios as well as on the downscaling process of the HadCM3 data is illustrated in the next sections. HadCM3 represents a possible future, using the A2 IPCC SRES scenario. However, some limitations to this approach are essential: - HadCM3 represents the worst case scenario. - Though Yallal is the most representative station for the purpose of the present study,

considerable local variations occur within small stretches [8]. - Since the entire country of The Gambia falls into one GCM grid, the actual

precipitation amount will differ between the Gambian meteorological stations due to the downscaling procedure, but the relative changes will remain constant.

- By using the dataset of just one GCM, only one statistical time series is obtained, which allows the authors to keep the focus on sea level rise and changing discharges as a result of the Sambangalou dam and future irrigation.

Though these limitations are making the future precipitation data highly uncertain, the downscaled HadCM3 data are the best estimate to suit the purposes of this study. Three HadCM3 climate variables have been statistically downscaled by DWR: precipitation, maximum temperature and minimum temperature. The latter two are being used to calculate open water evaporation in the Gambia estuary. Just 4 out of 23 stations in The Gambia have the required record length to downscale the HadCM3 data properly: Yundum, Yallal, Georgetown and Basse. [8] Since its location is at the middle of the estuary (Figure 1.1), Yallal is chosen as the station for meteorological data.



55

IPCC SRES Scenarios The IPCC prepared a total of 40 emission scenarios (IPCC Special Report on Emission Scenarios – SRES). The scenarios were based on the emission driving forces of demographic, economic and technological evolutions that produce greenhouse gas (mainly carbon dioxide) and sulphur emissions. Four scenario ‘storylines’ were developed, each of which will have its own influence on climate change (the list below has been adapted from Special Report on Emission Scenarios, p. 4-5): Storyline A1: The A1 scenario describes a future world of very rapid economic growth, global population that peaks in the mid 21st century and declines thereafter, and the rapid introduction of new and more efficient technologies. Major underlying themes are convergence among regions, capacity building and increased cultural and social interactions, with a substantial reduction in regional differences in per capita income. Storyline A2: The A2 scenario describes a very heterogeneous world. The underlying theme is self reliance and preservation of local identities. Fertility patterns across regions converge very slowly, which results in continuously increasing population. Economic development is primarily regionally oriented and per capita economic growth and technological changes are more fragmented than in other storylines. Storyline B1: The B1 scenario describes a convergent world with the same global population as the A1 scenario (population that peaks in mid-century and declines thereafter), but with rapid change in economic structures towards a service and information oriented economy, with reductions in material intensity and the introduction of clean and resource efficient technologies. The emphasis is on global solutions to economic, social and environmental sustainability, including improved equity, but without additional climate initiatives. Storyline B2: The B2 scenario describes a world in which the emphasis is on local solutions to economic, social and environmental sustainability. It is a world with a continuously increasing global population, at a rate lower than that in the A2 scenario, with intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 storylines. While the B2 scenario is also oriented towards environmental protection and social equity, it focuses on local and regional levels.



56

Downscaling HadCM3 data to The Gambia (This text has been adapted from Gomez et al., 2004, p. 19)

Three climate variables were downscaled: precipitation, and minimum and maximum temperature. The downscaling procedure was done at a monthly time period for three time periods: the reference period 1961 – 1990, the near future period 2010 – 2039, and the distant future period 2070 - 2099. The downscaling procedure can be described in four steps: STEP 1. Preparing the observed reference period data. The reference time period is set for all variables at 1961 – 1990 for the HADCM3 model. The station data is daily, and will need to be converted to monthly values (monthly precipitation is the sum of the daily precipitation for the corresponding month, monthly minimum and maximum temperature is equal to the average of the minimum and maximum temperatures for the corresponding months). STEP 2. Computing the adjusted reference period GCM time series. The objective is to downscale the unadjusted reference period GCM data to fit the statistical characteristics of variability and mean of the corresponding reference period observed historical station data. First equation was used to attain the corrected, or adjusted, climate parameter, thus creating the ‘adjusted reference period GCM time series’:

MobsMobs

Mgcm

MgcmMgcm

Mgcm aaa

a ,,

,

,,

,' +⋅

−= σ

σ

where: a’gcm is the corrected climate parameter (total precipitation or average temperature) agcm the simulated climate parameter

gcma the average simulated climate parameter

σgcm the standard deviation of the simulated climate parameter σobs the standard deviation of the observed climate parameter

obsa the average observed climate parameter, and

M the subscript indicating that analyses were done for each month separately. STEP 2a. From this equation two adjustment factors, for each month considered, can be derived using the same time span for observations as well as GCM “projections” (e.g. 1961-1990):

Mgcm

Mobs

Madja

aa

,

,

, =

Mgcm

Mobs

Madj

,

,

,σ

σσ =

STEP 4. Derive the adjusted GCM values for future projections (e.g. 2010-2039, 2070-2099). These above two adjustment factors are used to derive the adjusted GCM values for future projections (e.g. 2010-2039, 2070-2099):

( ) )(' ,,,,,, MadjMgcmMadjMgcmMgcmMgcm aaaaa ⋅+⋅−= σ



57

Appendix 7: Evaporation in Gambian estuary

Thornthwaite Thornthwaite has devised a method to calculate estimates of the potential evapo-transpiration from short, close-set vegetation with an adequate water supply, in the latitudes of the USA. Open water evaporation is larger than short close-set vegetation. This is caused by both the greater reflectivity of vegetation compared to open water and the transpiration of plants virtually ceases at night. Penman concluded that the evaporation rate from a freshly wetted bare soil was about 90 per cent of that from an open water surface exposed tot the same weather. Assumption 1: As short, close-set vegetation evaporates less than bare soil, all calculation outcomes are divided by 85% to get the open water evaporation. Assumption 2: The formula is also valid for the latitude of The Gambia as the differing latitude is compensated. If tn = average monthly temperature of the consecutive months of the year in °C (where n = 1, 2, 3, …, 12) and j = monthly ‘heat index’, then

1.514

5

ntj

=

and the yearly ‘heat index’, J, is given by 12

1J j= Σ (for the 12 months)

The potential evapo-transpiration for any month with average temperature t (°C) is then given, as PEx, by

1016

a

x

tPE

J

=

mm per month

where a = (675*10-9)J3-(771*10-7)J2+(179*10-4)J+0.492

However PEx is a theoretical standard monthly value based on 30 days and 12 hours of sunshine per day. The actual PE for the particular month with average temperature t (°C) is given by

360x

DTPE PE=

where D = number of days in the month T = average number of hours between sunrise and sunset in the month.3 First, all evaporations are calculated for 360 successive months. The averaged data for each month are divided by 0.85. Table A7.1 shows calculation for open water evaporation using Thornthwaite formula.

3 Adventist. Visited on March 15th 2005. www.adventist.org/sun/index.cgi?cntr=Gambia&city=Banjul&x=108&y=9



58

Table A7.1: Mean open water evaporation according to Thornthwaite’s formula [m/mth]

OWE OWE OWE 1979-2002 2010-2039 2070-2099 January 0.15 0.15 0.18

February 0.17 0.17 0.19

March 0.18 0.18 0.20

April 0.19 0.19 0.21

May 0.19 0.20 0.21

June 0.19 0.19 0.21

July 0.18 0.19 0.21

August 0.17 0.18 0.20

September 0.17 0.17 0.20

October 0.18 0.18 0.21

November 0.17 0.18 0.20

December 0.15 0.15 0.18

Total 2.08 2.13 2.40

Linacre The method of Linacre is based on open water evaporation.

1000*(0,75 )*15*( )

100

80

md

r TT T

AETPT

− + − −=

−

ETP = Potential Evapo-transpiration (mm/day) A = Latitude r = Albedo T = Mean Temperature (°C) Td = Morning Temperature (°C) Tm = Mean Temperature reduced to sea level Mean temperature T is obtained by dividing Tmax+Tmin by two. Td, the morning temperature is Tmin. Since the whole estuary is very close to sea level, reducing temperature to sea level is not necessary. (normally, Tm=T+0.006h) r is for water 7%, so 0.07 [16] and A is 13.3, the latitude of Banjul. Table A7.2 shows calculated open water evaporations, using Linacre formula. Table A7.2: Mean open water evaporation according to Linacre’s formula [m/month]

OWE OWE OWE 1979-2002 2010-2039 2070-2099 January 0.183 0.185 0.207

February 0.185 0.180 0.197

March 0.216 0.218 0.233

April 0.218 0.216 0.232

May 0.216 0.231 0.254

June 0.188 0.205 0.232

July 0.173 0.187 0.222

August 0.164 0.177 0.214

September 0.164 0.169 0.214

October 0.183 0.193 0.245

November 0.191 0.194 0.224

December 0.185 0.179 0.205

Total 2.265 2.335 2.679



59

Validating formulas Thornthwaite and Linacre To check both formulas, the deviation is calculated (Table A7.3). As 20 years of data are available, 240 measurement point are used. To calculate the deviation, the mean evaporation over the 20 years is calculated.

2( )x

n

deviation

x evaporation

mean monthly evaporation

n total measurements

µσ

σ

µ

Σ −=

=

=

=

=

Table A7.3: Validation Linacre and Thornthwaite

1979-2002 Mean yearly [m] Difference [%] Deviation [m] Measured 2.00 - - Thornthwaite 2.08 4.0 0.07 Linacre 2.27 13.5 0.08 As the Thornthwaite outcome is very close to the measured data, the assumption that short close-set vegetation evaporation is 85% of open water evaporation seems correct.



60

Appendix 8: SALNST code Parameters used in de SALNST model (.dat-file)

OBS TITLE FOR $$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$ THE GAMBIA ESTUARY SALINITY INTRUSION MODEL OBS OCEAN SALINITY, RIVER SALINITY, INITIAL DISCHARGE (m3/s) FOR ##.## ##.## ######.## 35.0 00.1 63. OBS TIDAL PERIOD (s), TIDAL RANGE (m), DAMPING FOR #####.# ##.## #.## 44400. 1.0 0.8 OBS RATIO EVAP, RATIO RAIN, AREA PUMP (1000 ha), AREA TIDAL (1000 ha) FOR #.## #.## #####.# #####.# 0.7 3.0 0. 0. OBS NUMBER OF REACHES, CROSS-AREA MOUTH, DEPTH MOUTH FOR ## ######.# ##.## 2 153000. 9. OBS START YEAR, NUMBER OF YEARS FOR #### ## 1970 1 OBS DISTANCE (m), WIDTH REDUCT. COEFF., DEPTH (m) OBS as many as number of reaches FOR ######.# -.########## ##.## 174000. -1.922E-05 9.0 340000. -5.088E-06 6.0 OBS CALCULATION STEP (m), TIME STEP (days) [1,2,3,5,6,10,15 or 30] FOR #####. ##. 2000. 5. OBS OUTPUT X-STEP, OUTPUT TIME STEP FOR #####. ##. 10000. 10.



61

Appendix 9: Input SALNST

Precipitation Table A9.1: Precipitation Yallal [m]

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2070 0.000 0.000 0.000 0.000 0.003 0.006 0.076 0.074 0.092 0.049 0.002 0.000

2071 0.000 0.001 0.000 0.002 0.005 0.015 0.043 0.343 0.043 0.000 0.000 0.000

2072 0.000 0.000 0.000 0.001 0.000 0.119 0.139 0.451 0.266 0.108 0.000 0.000

2073 0.000 0.000 0.000 0.001 0.000 0.016 0.354 0.205 0.231 0.010 0.001 0.000

2074 0.000 0.000 0.000 0.000 0.000 0.036 0.059 0.156 0.106 0.061 0.005 0.000

2075 0.000 0.000 0.001 0.000 0.000 0.019 0.063 0.072 0.135 0.016 0.000 0.000

2076 0.000 0.000 0.000 0.006 0.000 0.002 0.060 0.351 0.049 0.029 0.000 0.000

2077 0.000 0.000 0.000 0.000 0.001 0.056 0.247 0.167 0.291 0.009 0.000 0.000

2078 0.000 0.000 0.000 0.000 0.000 0.010 0.219 0.228 0.135 0.022 0.002 0.000

2079 0.000 0.000 0.000 0.000 0.000 0.038 0.133 0.249 0.074 0.001 0.000 0.000

2080 0.000 0.000 0.000 0.000 0.001 0.007 0.014 0.108 0.051 0.009 0.001 0.000

2081 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.036 0.012 0.032 0.000 0.000

2082 0.000 0.000 0.000 0.000 0.000 0.000 0.005 0.112 0.053 0.004 0.001 0.000

2083 0.000 0.000 0.000 0.004 0.000 0.019 0.025 0.007 0.080 0.006 0.000 0.000

2084 0.000 0.000 0.000 0.000 0.000 0.011 0.008 0.037 0.000 0.000 0.000 0.000

2085 0.000 0.000 0.001 0.000 0.000 0.032 0.141 0.133 0.159 0.127 0.001 0.000

2086 0.000 0.000 0.000 0.000 0.000 0.064 0.074 0.229 0.075 0.003 0.002 0.000

2087 0.000 0.000 0.000 0.000 0.000 0.013 0.031 0.185 0.028 0.001 0.002 0.000

2088 0.000 0.000 0.000 0.000 0.000 0.017 0.048 0.121 0.173 0.003 0.002 0.000

2089 0.000 0.000 0.000 0.001 0.000 0.025 0.062 0.159 0.127 0.020 0.001 0.000

2090 0.000 0.000 0.000 0.000 0.000 0.000 0.029 0.211 0.116 0.188 0.017 0.000

2091 0.000 0.000 0.000 0.000 0.000 0.057 0.078 0.107 0.063 0.071 0.000 0.000

2092 0.000 0.000 0.000 0.000 0.001 0.017 0.099 0.086 0.002 0.004 0.001 0.000

2093 0.000 0.000 0.000 0.000 0.000 0.031 0.120 0.126 0.279 0.006 0.005 0.000

2094 0.000 0.000 0.000 0.000 0.000 0.098 0.078 0.119 0.171 0.012 0.000 0.000

2095 0.000 0.000 0.000 0.002 0.000 0.001 0.054 0.107 0.094 0.007 0.000 0.000

2096 0.000 0.000 0.000 0.001 0.000 0.002 0.083 0.045 0.040 0.064 0.001 0.000

2097 0.000 0.000 0.000 0.001 0.000 0.004 0.165 0.083 0.079 0.007 0.000 0.003

2098 0.000 0.000 0.000 0.000 0.000 0.000 0.005 0.076 0.027 0.011 0.000 0.000

2099 0.000 0.000 0.000 0.000 0.000 0.058 0.314 0.271 0.050 0.021 0.000 0.000



62

Evaporation Table A9.2: Evaporation input SALNST according to Thornthwaite formula [m]


2070 0.167 0.189 0.199 0.205 0.210 0.215 0.210 0.205 0.202 0.207 0.205 0.167

2071 0.167 0.181 0.199 0.205 0.213 0.215 0.211 0.189 0.202 0.215 0.196 0.185

2072 0.181 0.189 0.196 0.207 0.215 0.213 0.199 0.189 0.189 0.189 0.189 0.167

2073 0.167 0.171 0.199 0.205 0.210 0.205 0.185 0.185 0.176 0.202 0.202 0.167

2074 0.167 0.181 0.185 0.199 0.205 0.207 0.202 0.199 0.199 0.205 0.199 0.167

2075 0.167 0.176 0.199 0.207 0.210 0.213 0.207 0.202 0.202 0.211 0.202 0.176

2076 0.167 0.189 0.193 0.202 0.210 0.213 0.211 0.196 0.199 0.205 0.202 0.193

2077 0.189 0.189 0.199 0.210 0.210 0.207 0.193 0.185 0.181 0.196 0.202 0.181

2078 0.181 0.193 0.193 0.202 0.211 0.210 0.196 0.189 0.196 0.207 0.202 0.181

2079 0.167 0.185 0.199 0.207 0.213 0.211 0.205 0.193 0.196 0.215 0.199 0.181

2080 0.167 0.181 0.193 0.202 0.207 0.207 0.210 0.211 0.211 0.211 0.210 0.196

2081 0.171 0.199 0.205 0.207 0.213 0.211 0.210 0.213 0.215 0.213 0.207 0.181

2082 0.196 0.189 0.205 0.205 0.211 0.211 0.211 0.210 0.205 0.213 0.207 0.176

2083 0.171 0.189 0.193 0.193 0.210 0.210 0.211 0.216 0.211 0.213 0.210 0.176

2084 0.171 0.185 0.199 0.210 0.211 0.211 0.215 0.216 0.216 0.215 0.207 0.196

2085 0.199 0.193 0.205 0.210 0.213 0.215 0.207 0.207 0.202 0.199 0.202 0.176

2086 0.181 0.189 0.196 0.207 0.210 0.211 0.207 0.199 0.205 0.213 0.196 0.181

2087 0.171 0.185 0.196 0.210 0.211 0.210 0.213 0.207 0.210 0.210 0.202 0.185

2088 0.171 0.185 0.205 0.210 0.210 0.210 0.205 0.202 0.196 0.213 0.202 0.181

2089 0.176 0.193 0.202 0.202 0.211 0.213 0.207 0.202 0.199 0.211 0.207 0.193

2090 0.176 0.189 0.205 0.205 0.215 0.213 0.210 0.202 0.199 0.185 0.193 0.171

2091 0.185 0.193 0.205 0.207 0.215 0.216 0.211 0.210 0.210 0.211 0.210 0.181

2092 0.176 0.193 0.199 0.205 0.215 0.213 0.210 0.207 0.213 0.215 0.210 0.196

2093 0.185 0.193 0.205 0.210 0.215 0.211 0.210 0.207 0.196 0.211 0.199 0.181

2094 0.171 0.181 0.199 0.207 0.213 0.213 0.210 0.205 0.199 0.213 0.207 0.185

2095 0.185 0.193 0.202 0.207 0.215 0.215 0.213 0.210 0.210 0.215 0.207 0.189

2096 0.176 0.185 0.205 0.210 0.216 0.211 0.205 0.211 0.210 0.210 0.207 0.193

2097 0.185 0.193 0.202 0.213 0.216 0.215 0.210 0.215 0.215 0.216 0.211 0.196

2098 0.193 0.202 0.210 0.210 0.216 0.216 0.216 0.213 0.213 0.216 0.211 0.185

2099 0.185 0.189 0.196 0.210 0.213 0.213 0.202 0.196 0.205 0.215 0.211 0.193



63

Table A9.3: Evaporation input SALNST according to Linacre formula [m]


2070 0.201 0.199 0.227 0.228 0.232 0.237 0.220 0.215 0.207 0.249 0.222 0.189

2071 0.201 0.187 0.230 0.226 0.246 0.238 0.233 0.177 0.215 0.270 0.231 0.196

2072 0.211 0.204 0.234 0.222 0.258 0.234 0.198 0.176 0.177 0.188 0.191 0.196

2073 0.192 0.196 0.234 0.226 0.243 0.216 0.173 0.175 0.161 0.217 0.218 0.182

2074 0.178 0.194 0.216 0.216 0.242 0.213 0.212 0.207 0.207 0.219 0.217 0.203

2075 0.206 0.190 0.241 0.241 0.248 0.234 0.220 0.211 0.213 0.250 0.227 0.198

2076 0.204 0.191 0.235 0.217 0.248 0.236 0.232 0.190 0.205 0.237 0.222 0.211

2077 0.195 0.195 0.226 0.233 0.245 0.208 0.188 0.172 0.163 0.207 0.217 0.200

2078 0.205 0.198 0.221 0.227 0.257 0.220 0.186 0.180 0.197 0.230 0.220 0.196

2079 0.202 0.181 0.221 0.230 0.251 0.226 0.214 0.185 0.200 0.268 0.224 0.200

2080 0.191 0.192 0.227 0.228 0.240 0.231 0.242 0.236 0.237 0.259 0.228 0.218

2081 0.201 0.194 0.237 0.241 0.272 0.243 0.247 0.254 0.252 0.259 0.233 0.209

2082 0.216 0.193 0.244 0.241 0.257 0.241 0.244 0.225 0.217 0.259 0.217 0.207

2083 0.200 0.195 0.228 0.202 0.250 0.230 0.234 0.260 0.236 0.264 0.227 0.213

2084 0.214 0.195 0.222 0.242 0.266 0.235 0.256 0.260 0.263 0.268 0.229 0.220

2085 0.209 0.197 0.232 0.235 0.261 0.242 0.217 0.226 0.203 0.200 0.212 0.209

2086 0.206 0.196 0.234 0.232 0.245 0.221 0.222 0.204 0.216 0.266 0.222 0.207

2087 0.213 0.199 0.237 0.236 0.251 0.224 0.238 0.219 0.234 0.248 0.223 0.207

2088 0.209 0.207 0.240 0.246 0.251 0.234 0.224 0.211 0.194 0.267 0.234 0.212

2089 0.217 0.204 0.237 0.234 0.252 0.228 0.220 0.208 0.202 0.247 0.227 0.213

2090 0.213 0.197 0.238 0.236 0.267 0.240 0.222 0.207 0.195 0.176 0.186 0.178

2091 0.205 0.194 0.239 0.238 0.269 0.237 0.230 0.231 0.225 0.243 0.236 0.212

2092 0.218 0.203 0.238 0.231 0.259 0.232 0.227 0.227 0.246 0.258 0.224 0.213

2093 0.214 0.205 0.235 0.237 0.252 0.230 0.222 0.219 0.187 0.264 0.214 0.196

2094 0.212 0.204 0.228 0.230 0.249 0.229 0.219 0.212 0.200 0.253 0.233 0.198

2095 0.214 0.205 0.242 0.233 0.265 0.240 0.237 0.231 0.227 0.256 0.231 0.216

2096 0.214 0.204 0.239 0.235 0.267 0.229 0.210 0.240 0.233 0.235 0.226 0.217

2097 0.219 0.198 0.237 0.243 0.262 0.240 0.219 0.245 0.247 0.265 0.242 0.202

2098 0.214 0.212 0.253 0.247 0.266 0.254 0.250 0.237 0.239 0.270 0.233 0.207

2099 0.211 0.195 0.233 0.230 0.253 0.229 0.197 0.186 0.211 0.267 0.240 0.217



64

Gouloumbo

Natural flow intermediate catchment To complement input SALNST, add Sambangalou dam release (Table A9.4) and subtract Irrigation Senegal (Table A9.5=Table 4.4) from Table A9.6

Table A9.4: Sambangalou dam release for different scenarios [m3/s]


A 126 44 44 44 44 44 44 44 126 126 126 126

B 54 54 54 54 54 54 54 54 54 212 54 54

C2 54 54 54 54 54 0 54 54 54 212 54 54

C4 54 54 54 54 0 0 54 54 54 212 54 54

D’ 54 54 54 0 0 0 54 54 54 212 54 54

Table A9.5: Irrigation Senegal Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

m3/s 6.4 5.0 6.4 5.5 2.6 0.3 1.9 0 0 1.3 2.2 2.1

Table A9.6: Natural flow intermediate between Sambangalou and Gouloumbo


2070 0 0.2 0.1 0 0 22.7 14.3 145.2 131.2 180.2 93.2 7.7

2071 0.8 0.3 1.9 0.1 0.7 36.8 35.5 84.5 589.7 123.5 7.8 2.8

2072 0.9 0.4 0.1 0.1 0.2 0 276.8 312.8 969.4 1067.3 501.7 31.8

2073 16.3 6.9 3 2.3 0.9 0.3 37.1 695.3 560.1 748.3 65.4 20.6

2074 7.1 3.1 1.4 0.6 0.3 3.1 85 118.1 278.5 230.1 129.5 18.5

2075 1.8 0.7 0.2 3 0.1 3.2 43.5 122.6 127.2 261.8 35 2

2076 0.7 0.3 0.1 0 1.9 3.6 4.5 115.9 612.5 143.5 72.8 5.1

2077 1.8 0.7 0.3 1.1 0.1 4.9 130.3 505.9 396 793.9 57.7 15.4

2078 6.6 2.6 1.1 0.5 0.3 0.1 24 423.5 490.4 377.4 69.4 14.4

2079 3.1 1.2 0.5 1.2 0.1 2.3 88.3 266.3 487.3 202.8 11.5 3.5

2080 1.3 0.5 0.2 0.1 0 4.9 16.9 27.5 177.9 99.3 16.5 4.3

2081 0.2 0.1 0 1 0 0 2.7 0.9 57.2 20.8 51 0.2

2082 0.1 0 0 0 0 0 0 9.5 180.2 100.7 7 3.5

2083 0.1 0 0 0 1.4 0.2 43.1 48.2 12.3 140 11.5 0.6

2084 0.1 0 0 0 0 0 25 15.3 59.6 1 0.1 0

2085 0 0 0 3.8 0 0 73.5 276.3 259.9 353.3 288.7 15.2

2086 4.5 2.2 0.6 0.3 0.2 0.1 149.9 153.1 425.6 188 13.7 8.7

2087 1 0.4 0.1 0.1 0 0 29.2 60.1 309.6 61.8 3.3 6.4

2088 0.3 0.1 0 0 0 0.7 40 93.1 207.6 348.8 14.3 7

2089 0.9 0.3 0.1 1 0.4 0.2 56.9 120.1 279.2 272.3 48.3 5.3

2090 1.2 0.4 0.2 0.1 0 1.1 0 54.5 349.8 252.5 394.7 72.2

2091 6.9 3.1 1.3 0.6 0.3 0.1 134.1 160.4 200.2 134 135.9 4

2092 1.1 0.4 0.1 0.1 0 5.6 38.9 192.4 158.6 6.7 7.9 3.1

2093 0.1 0.1 0 0 0 0 70.8 236.1 239.8 604 32.7 23.3

2094 2.9 1.2 0.4 0.2 0.1 1.6 228 170.1 232.4 375.2 36.4 5.3

2095 1.6 0.6 0.2 0.1 0.5 0 1.6 104.7 186.1 188.3 16 1.3

2096 0.5 0.2 0.1 0 0.2 0 4.1 156.9 80.2 75.9 111.1 3.7

2097 0.5 0.2 0.1 0 0.2 0 8.2 313 163.7 168.2 17.7 1.4

2098 11.3 0.2 0.1 0 0 0 0 9.5 122.2 50.3 18.1 0.2

2099 0.1 0 0 0 0 0 133 639.4 708.6 195.9 70.3 7.4

saline intrusion in gambia river after dam...

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