Likely Effects Of Climate Change on Runoff from Limpopo Basin -

Botswana

By

Prof. B. P. ParidaDept. of Environmental Science

University of Botswana

Background

Much of Southern Africa below Latitude 20o S is basically Semi-Arid

This includes BOTSWANA whereAnnual Rainfall ~ 250 – 500 mmEvaporation ~ 2000 mmTopography ~ Flat and Deep Sandy Soil

(These together limit the effectiveness of Rainfall)

Sources of Water

Rivers and Streams : Average runoff is very low~0.6 mm for the whole country> All endogenous rivers originating in Botswana are ephemeral with an average of 10–70 days of flow in a year.

Other Sources: Desalination, Water carriers to tap international rivers – Very Expensive

Groundwater :

Location of Boreholes in Botswana

Sources..(Groundwater..contd)

Wellfield Extraction Rate

in M m3

Recharge Rate

in M m3

Jwaneng N. 10 2

Orapa 5 0.2

Palla

(Source: BNWMP, 1991)

12 2.4

Water Supply..

Clearly Botswana is one amongst the water stressed countries of the world(where water use is more than 20% of their renewable water supply)

Botswana is highly dependent on its natural resource base : mining, livestock, wild-life based tourism, textiles, soda ash and agriculture

In Summary:

Water is the single most important constraint to the development of Botswana

The Limpopo Basin

The major source of water in the eastern Botswana and it is important because of its strategic value to Botswana, South Africa Zimbabwe and Mozambique.

Drains from a catchment area of about 80 000 km2 (~1/8 area of Botswana)

Approximately carry about 10 mm of surface water annually.

The Limpopo Basin

The catchment serves as the main source for Gaborone & rapid and ongoing expansion of southeastern Botswana.

In Botswana alone.. 4 dams viz: Gaborone, Bokaa, Letsibogo and Shashe have been built with a total capacity of 350 M m3 (against projected demand of about 325 M m3 by 2020)

Indicative Studies Reveal that:

A rise of 0.02 to 0.05oC per decade in Africa in the present century (IPCC)

(greatest over the interior of semi-arid margins of Sahara and Central Southern Africa.)

Limpopo basin is likely to experience between 5 to 15% decrease in rainfall, 5 to 20% increase in Evaporation, and 25 to 35 % decrease in streamflow. (Desanker and Magadza, 2001).

Main objective

To quantify the effect of climate change on the flow regime of Limpopo basin – hence develop flow scenarios.

to find by what percentage the runoff will either increase or decrease in the coming years?

what will be the trend in flow over the coming decades in this century?

Philosophy:

Rainfall ~ Runoff is a complex paradigm as it represents the catchment’s response which is a function of land use

So, any adaptation strategy that needs to be developed to overcome the effects of climate change, would primarily centre around a well structured catchment management strategy along with strategies for water use management.

PROPOSED METHODOLOGY

Use past climatic and flow information (monthly rainfall, PE, and flow data over the past 20-30 years including data on landuse) to carry out water balance, hence compute the annual yield.

Use the past data as above to develop an ANN model which can be used for flow predictions.

Use the generated climatic scenario to develop flow scenario for the Limpopo.

CONCEPT OF MULTI-CELL WATER BALANCE :P = AET + OF + ΔSM + ΔGWS +GWR + Interception

stream

Impervious

OF

P

I

AET

Infiltration

SM

GWS

Percolation to G/water

GWR

Data Collection:

Rainfall Data: Monthly data at 37 stations (1971 – 1998)

Evaporation Data: Monthly data at 4 stations (1971 – 1998)

Flow Data : Monthly data at 1 station (1978 – 1998)

Soil Data : Field Capacity of major soil types in the basin as per the soil atlas.

Procedure for Multi-cell Water Balance: Long term average rainfall values and

evaporation values are superimposed on the soil map and the catchment is then divided into 75 cells – each cell basically representing uniform rainfall, evaporation and soil type.

For each cell and for a given year runoff is computed. (Thornthwaite and Mather, 1957)

For each year total runoff from the catchment is computed at the outlet by adding up flows from the 75 cells.

Total runoff / Total rainfall = Runoff coeff.

A TYPICAL WATER BALANCE COMPUTATION TABLE ( Field Capacity = 125 mm )

JAN FEB MAR

APR MAY

JUN JUL AUG

SEP OCT NOV

DEC

TOTAL

P 103 33 21 12 32 0 0 12 12 68 122 69 484PE 139 80 86 92 68 52 62 79 118 141 120 135 1172

P-PE -36 -47 -65 -80 -36 -52 -62 -67 -106

-73 2 -66

APWL -102

-149

-214

-294

-330

-382

-444

-511

-617

-690

0 -66

SM 55 37 22 12 9 6 3 2 1 0 125 73

ΔSM -18 -18 -15 -10 -3 -3 -3 -1 -1 -1 125 -52

AET 121 51 36 22 35 3 3 13 13 69 120 121

DEFICIT 18 29 50 70 33 49 59 66 105 72 0 14 565

SURPLUS

0 0 0 0 0 0 0 0 0 0 123 62

TARO 31 16 8 4 2 1 0 0 0 0 123 62

RO 15 8 4 2 1 1 0 0 0 0 61 31 123DET 16 8 4 2 1 0 0 0 0 0 62 31

Average Rainfall in Limpopo Catchment system between 1971 and 1998

y = -3.108x + 6556.2

0.00

200.00

400.00

600.00

800.00

1970 1975 1980 1985 1990 1995 2000

Years

Ave

arg

e R

ain

fall

(m

m)

Runoff Coefficient for Limpopo Catchment system between 1971 and 1998

y = 0.0049x - 9.255

00.10.20.30.40.50.60.7

1970 1975 1980 1985 1990 1995 2000

Years

Ru

no

ff C

oef

fici

ents

CUSUM Analysis of Rainfall Values in the Limpopo Catchment

-400.00

-200.00

0.00

200.00

400.00

600.00

800.00

1970 1975 1980 1985 1990 1995 2000

Years

CU

SU

M R

ain

fall

Val

ues

Runoff Coefficient in % and Rainfall for the Limpopo Catchment between 1981 and 1998

0100200300

400500600700

1980 1985 1990 1995 2000

Years

Ru

no

ff C

oef

fici

ents

(%

)R

ain

fall

(m

m)

CONCEPTUALISATION OF ARTIFICIAL NEURAL NETWORK BASED ON A

BIOLOGICAL NEURON

Cell body

Nucleus Axons

Dendrites Sunapses

Nucleus

Axon

Dendrides

Components of a neuron

HOW DOES THE ANN WORK ??

Processing element

Weights Wn Inputs Xn

Output path

Transfer Sum

Xo

X1

X2

X3

Xn

Wo

W1

W2

W3

W4 . . .

The basic structural functioning of a neuron

A MULTI-LAYERED FEED FORWARD NEURAL NETWORK WITH ONE HIDDEN LAYER

input layer

Hidden layer

Output layer

Output array

A multi-layer feedfoward neural network with one hidden layer

Conclusion

Using scenario of monthly rainfall and evaporation values from the GCM / RCM models (AF 07), scenarios on likely runoff from the Limpopo basin by the above two techniques will be created.

Co-operation needed:

Monthly rainfall and evaporation data scenarios for the Limpopo basin in the next 30 – 50 years will be necessary (GCM /RCM / Empirical / Other climate Model).

Formulation of appropriate catchment management strategies as possible adaptation strategy.