A MODEL FOR RESERVOIR YIELD UNDER CLIMATE CHANGE SCENARIOS FOR
THE WATER STRESSED CITY OF BULAWAYO, ZIMBABWE
Bekitemba Moyo1,2, Elisha Madamombe3 and David Love 4,5,6
1
Department of Civil Engineering, University of Zimbabwe, PO MP 167, Mount Pleasant,
Harare, Zimbabwe
2
3
Department of Engineering Services, Beitbridge RDC, PO 32, Beitbridge, Zimbabwe
Research and Data Department, Zimbabwe National Water Authority, Harare, Zimbabwe
4
5
6
WaterNet, PO Box MP600, Mount Pleasant, Harare, Zimbabwe
ICRISAT Bulawayo, Matopos Research Station, PO Box 776 Bulawayo, Zimbabwe
Department of Geology, University of Zimbabwe, PO Box MP 167, Mount Pleasant, Harare,
Zimbabwe
ABSTRACT
The City of Bulawayo, the second largest city in Zimbabwe (population 981,000), although
located in the Zambezi Basin, sources its water mainly from five reservoirs located in the Upper
Mzingwane Subcatchment, Limpopo Basin. The reservoirs have failed to store their expected 4 %
yields. The city has frequently implemented water rationing or lesser restrictions. The city is
currently under stringent water rationing since the total runoff into the water supply reservoir
was low. A study was undertaken to determine if reservoir yields were falling, and possible
causes thereof.
1
Examination of 30-year rainfall and runoff records showed declining precipitation and runoff on
the five year moving averages. Dam yields, determined by Yield 200 model, have been declining
over the same period, from 131.3 Mm3 in 1980 to 67.90 Mm3 in 2005. The phenomenon, which
might influence such a trend, is global climate change.
Future yields of the reservoirs were estimated by two methods. The yield was projected from the
30-year trend to year 2030 using the best-fit line. This formed one scenario, while two additional
projections were determined using two scenarios of runoff and precipitation decline, predicted
from IPCC SRES emissions scenarios. Both of these predicted less reduced yields by 2030 (45.04
Mm3 and 41.72 Mm3) than the yield projection from current data (67.90 Mm3), suggesting the
possibility that the impact of climate change in southern Zimbabwe may be higher than predicted
by global models.
Unrestricted water demand for the city is projected to 83.70 Mm3 of raw water by year 2030.
This is far above even the most optimistic yield projection. It can therefore be concluded that the
City should have determined additional sources of water already. The state-owned Mtshabezi
dam and the Nyamandlovu aquifer connection could provide an increased total water supply in
the short-term, but longer-term solutions, water demand management or additional sources, or
both are required.
Key words: Catchment management, climate change, emission scenarios, reservoir yields
2
INTRODUCTION
Climate change occurs at a time scale of over one hundred years. It may be artificial: due to
increasing concentrations of greenhouse gases in the atmosphere (IPCC, 2000) or natural: caused
by periodic changes in distribution of incoming solar radiation resulting from variations in the
earth’s orbital geometry that is the tilt, precision of equinoxes and eccentricity (Graciano et al.,
2004). Greenhouse gas emissions are starting to change our climate, and an increasing body of
evidence shows the climate is changing:

The global average surface temperature has increased over the 20th century by about 0.6°C

Temperatures have risen during the past four decades in the lowest 8 kilometres of the
atmosphere

Snow cover and ice extent have decreased

Global average sea level rose between 0.1 and 0.2 metres during the 20th century

The effect of anthropogenic greenhouse gases is detected, despite uncertainties in sulphate
aerosol forcing and response (Houghton et al., 2001).
Climate change is projected to substantially reduce available water (as reflected by projected
runoff) in many of the water-scarce areas of the world (Arnell, 2003). Future prediction shows
that Southern Africa will get drier and the region will find it difficult to cope with impacts given
the present level of preparedness. Any increase of 1.7oC in mean temperature, the region’s
precipitation is expected to decrease by 5-20% in all major river basins except for Congo basin
which is going to decrease by 10% (Table 1). Basing on individual countries, Zimbabwe will
3
have shortfall precipitation of 19%. The potential evaporation estimated for Zimbabwe ranges
between 7.5% and 132% representing the varied climate regimes across the country.
Table 1. Predicted changes in precipitation, potential evaporation and runoff in major river basins
in Southern Africa, expressed as a 30-year monthly mean for the baseline period (1961-1990)
compared to the period 2010-2039, after Chenje et al. (1996).
River Basin
% Change in
% change in potential
% change in
precipitation
evaporation
runoff
Congo
+10
+10 to +18
+10 to +15
Zambezi
- 10 to –20
+10 to +25
-26 to –40
Rovuma
-10 to +5
+25
-30 to –40
Limpopo
-5 to –15
+5 to+ 20
-25 to –35
Orange
-5 to +5
+4 to +10
-10 to +10
Runoff is harvested, for use, through damming the rivers or pumping straight from the perennial
rivers. Construction of large reservoirs with large storage ratio (full supply capacity/mean annual
runoff) aims at carrying over the runoff in high rainfall years for use in below average years in
order to assure the supply water for urban, industrial, mining and agricultural purposes (Mitchell,
1987). The function of a storage reservoir is to balance out the variation in both supply and
demand and thus to provide the consumer with an assured quantity of water for use as and when
required. The variations must be balanced not only within each year, but also over sequences of
many years, so that water from year of good rainfall is conserved for use during years of drought
(Kabell, 1974)
4
Zimbabwe is in a semi arid region of the world, where water is a vital and scarce commodity.
Large dams have been planned on major rivers and tributaries. These storage works have been
designed to have carry over capacity to balance out the long sequences of years of varying runoff
(Kabell, 1984). Management of such works poses some challenges to the water resources
managers. Challenges such as excessive evaporation and siltation are major ones, which affect
the reservoir capacity. Such storage works have not been designed to generate the minimum cost
of water, but were designed to generate the maximum practical yield from the catchment.
According to the IPCC (1990), vulnerabilities in present water uses (i.e where demand exceeds
firm yield) and conflicts among current uses are likely to be exacerbated by global warming in
most arid and semi-arid regions. Adaptation is an adjustment in natural or human systems in
response to actual or expected climatic stimuli or their effects (Kabat et al., 2003). A variety of
adaptations can be considered (Table 2).
Table 2. Recommendations for municipal water supplies (modified from table 4:13, IPCC, 2001)
Supply-side options
Demand-side options
Option
Comments
Option
Comments
Increase reservoir
Expensive; potential
Incentives to use less
Possibly limited
capacity
environmental
(e.g. through pricing)
opportunity; needs
impacts
institutional framework
Extra supply: more
Potential limited
Legally enforceable
Potential political impact:
from rivers and
impacts
water use standards
usually cost-inefficient
5
groundwater
(e.g for appliances)
Inter-basin
Expensive; potential
Increase use of grey
transfers
environmental
water
Potentially expensive
impacts
Desalination
Expensive (high
Reduce leakage
energy use)
Potentially expensive to
reduce to very low levels
esp. in old systems
Development of
Possibly too technically
ecological sanitation.
advanced for wide
application in large urban
systems
The City of Bulawayo, the second largest city in Zimbabwe, lies at an altitude of approximately
1350 m above the sea level. Its water supply is mainly based on surface water accumulated in
five reservoirs located in Upper Mzingwane catchment. The five reservoirs have failed to store
their expected 4% yields that they were designed for. It has been noticed that there is some
precipitation pattern, which is influencing the yield of the reservoirs. The city is famous for its
water rationing and restrictions. For the past eighty years the following were the years when
restrictions were imposed: 1938-1943, 1947, 1951, 1953, 1968, 1971-1973, 1983 and 1990 while
the rationing were imposed in the following years 1949,1984,1987 and 1991 while it stringent
water rationing has been imposed this year as the dams’ inflows were poor again.
6
It is imperative that the nature of the rainfall pattern and its variability with time be looked at
closely so that the runoff to and storage in the dams is appreciated. There is some realization that
climate is changing in the city’s reservoir catchments. There are times of inadequate rainfall and
times of plenty but it seems the rainfall pattern and magnitude is changing. There is a bigger
variation between dry and wet years with poor years having a bigger effect than years of plenty.
This study has three objectives: the first is to establish whether there is any significant changes in
temperature and precipitation in the city council’s reservoirs’ catchment areas, the second being
determining quantitatively the expected changes in inflows and yields into the city’s water supply
reservoirs due to expected climate variability and finally, to develop adaptation strategies that
will help mitigate the adverse impacts due to climate variability on the water supply reservoirs.
Two greenhouse emission scenarios will be analysed, one with high emissions and another with
low emission, using IPCC SRES emissions scenarios (IPCC, 2000). Their predicted effects will
be superimposed on the city’s projected future water demand and the deficit will be determined.
Two demand scenarios will be considered for the city; one when water demand management is
assumed to be fully implemented according to NORPLAN AS 2001 recommendations and one
when the year 2000 consumption levels remain unrestricted and the population increases
exponentially at a rate of 3% per annum. Thereafter, adaptation strategies will be proposed for the
City.
METHODS
7
The evaluation of the effect of climate change on the reservoir yields in Upper Mzingwane
catchment was carried out for all four reservoir catchments namely, Mzingwane, Ncema (Lower
and Upper), Inyankuni and Lower Insiza (Mayfair) dams. Information required for evaluation
was rainfall, temperature, demography, water use, evaporation, stream flow, and upstream and
downstream water rights for each reservoir. Temperature, rainfall, evaporation and stream flows
were considered for stations within the catchments and nearby catchments to assess consistency
and possible gap filling for missing data. The data collected covered thirty years from 1970 to
2000. This period was chosen since the city’s raw water supply has been operating continuously
without additional source since 1976 when the last dam was connected to the system. The upper
limit of year 2000 was chosen as most of processed and updated data available was done up to
year 2000.
Daily rainfall data for several locations within Upper Mzingwane catchment were obtained from
the Meteorological Department. The stations eventually utilized were to meet the following basic
criteria:
 location within the respective dam catchments
 containing sufficiently long observed records falling within the chosen period, and
 fair spread on the length of the catchment to give good coverage.
The stations selected were Esigodini, Mzinyathini, Mzingwane Dam, Mbalabala, Falcon College
and Filabusi Police station. Falcon College results were rejected as they only for 15 year period
(between 1975 &1990). The Esigodini data was used to represent the pattern for Ncema and
Inyankuni dams, Mzinyathini data was used for Mzingwane dam, and Filabusi data was used for
Lower Insiza Dam. Daily rainfall data for all the above stations (1930-2000) were converted into
8
annual data, arranged in such a way so as to coincide them to the Zimbabwean hydrological year,
which spans from 1 October to 30 September the following year. The 5-year moving average for
mean annual rainfall (M.A.R/F) and the coefficient of Variation (Cv) for each station were
computed.
A hydrological gauging station was identified for each dam so as to represent the inflows into the
dams (Table 3). The stations satisfied the following criteria:
 Long enough record of flows
 The station has reliable data
 The station is located just upstream of the dam and not affected by the dams’ through
back at highest dam level.
Table 3. Hydrological stations used for data collection
Station
Hydrological River
Name
Zone
B30
BUZ4
Mzingwane
Location
Mzingwane dam
Catchment
Year
Area (km2)
opened
448
1958
U/S
B11
BNC
Ncema
Ncema dam U/S
640
1943
B60&B61
BIK
Inyankuni
Inyankuni dam
365
1962
982
1973
U/S
B89 &
BIN2
Insiza
Insiza dam U/S
B88
9
Monthly runoff data was collected from Zimbabwe National Water Authority (ZINWA) data and
research branch. The annual mean runoff was plotted against the hydrological years for each
gauge station. Gaps (missing data) were filled by best fitting line from linear regression from
nearby stations. Student t-test was used for testing the trend on the data series. The five-year
moving average was calculated for Mean Annual Rainfall (M.A.R) and Coefficient of variation
(Cv) of runoff.
Both daily minimum and maximum temperatures were collected from the Meteorology
Department and converted into annual time steps, from 1 October to the following 30 September.
Pan evaporation data was obtained for each dam.
The summer and winter water commitments for all the dams were obtained from the water rights
data bank of Zimbabwe National Water Authority. The individual water rights were reviewed
noting the point of abstraction relative to the dam, the history, the quantity of the right and the
owner of the property served by the water right. Each right was split into the winter and summer
commitment. The rights were summed for each dam according to their location (upstream or
downstream). The fractional area covering the water-righted areas were also obtained by plan
metering the water right map. These parameters are the inputs into the yield model as well.
Data on raw water abstraction history, consumption pattern and dams operations was collected
from the City of Bulawayo. A site visit to all the dams was undertaken to gather information on
the operation, maintenance, conveyance capacities and their water level states during the study
10
period. This data mainly was used for demand versus availability comparison and future demand
forecasting.
Participatory appraisal workshops were held in the dam catchments. The objective of the
workshops was to obtain oral appraisal of the participants’ perception about the climate change
and variability from the 1920s to present. Each workshop consisted of seven old citizens of the
area including the local leadership. Overall, the age range for the participants was fifty-eight
years and eighty-three years. The parameters which were discussed were variability in rainfall,
temperature, stream flows, reduction in volume of wetlands, land use changes, situations before
and after dam constructions, extreme events like flooding, cold winters, drought and hot summers
as well as the general water availability for domestic and livestock in their areas.
The reservoir yield calculations were carried out using Yield 200 model developed by Mitchell
(1989). The model uses an empirically fitted Weibull distribution to establish the probabilities of
annual inflows corresponding to the annual yield or draw off from a reservoir. The model was
written in QWBASIC form computer programme.(Mitchell, 1989) The monthly inflows are
obtained from the gauge station upstream of the dam. This model gives a correct answer within
the accuracy of the data supplied, and treats the runoff as a stochastic variable. It is applicable to
larger dams (storage ratio equal to 0.5 M.A.R and above) where there is carry over of stored
water from year to year. Inputs into the model were: dam catchment (km2), dam upstream mean
annual runoff (mm)
11
According to Arnell (2003), the predicted changes in runoff by year 2050 compared to 1990
greenhouse emission levels in Zimbabwe under model Had CM3 scenario A1 are 30% reduction
for high greenhouse gas emission and a reduction of 20% for low emission scenario using Other
model under scenario A2 .The model predicts that precipitation will fall by 30% under high
emission scenario while it will fall by 15 % under low emission scenario. These predictions were
done using Had CM3 and CSIRO under scenarios A2 and MKII respectively (Arnell, 2003).
These two predictions up to 2030 formed the data for the calculation of predicted mean annual
runoff and rainfall, coefficients of variation of both runoff and rainfall. These were then input
into the yield model with other input variables assumed constant. These two sets of yield results
formed two scenario results while the third scenario was the projection of the current trend.
The water demand projection was determined using two scenarios as well. One scenario was
unrestricted water demand. In this scenario it is assumed the city supplies the water at a level of
demand such the water is supplied as the residents wish, with same levels of losses and without
any restrictions. The consumption growth rate has been assumed to be directly proportional
growth rate of 3% (from City Council master plan) for this scenario. The other scenario is when
the city fully implements the water demand management strategy with losses, estimated to be
reduced to 10 000m3 per day.
RESULTS AND DISCUSSION
Temperature
12
The maximum temperature trend (Fig. 1) shows a warming trend at a rate of 0.410C per decade
while minimum shows a warming trend of 0.340C. This implies that winter seasons are becoming
warmer and the rate of increase is higher than that of maximum temperatures.
30.0
25.0
y = 0.0412x - 55.405
Temperature (oC)
20.0
Mean Max. Bulawayo
Mean Min. Bulawayo
Linear (Mean Max. Bulawayo)
Linear (Mean Min. Bulawayo)
15.0
y = 0.0342x - 54.975
10.0
5.0
0.0
1970
1975
1980
1985
1990
1995
2000
Fig. 1. Mean Minimum and maximum temperature variation for Bulawayo (1970-2000).
Rainfall
The rainfall trends (Fig. 2) show a decrease in precipitation for all stations. Compared to their
respective averages, Esigodini precipitation decreases at a rate of 2.8% per decade while Filabusi
decreases at a rate of 2.5% per decade
Stream flow (runoff)
13
There is some noticeable decrease in the amplitude of the runoff peaks into the dams oveer the 30
year period (Fig. 3). After the 1979/80 hydrological year, there was a jump in the pattern and the
number of no flow recorded also increased. After that year there was an increase in the duration
of number of drought years. As the inflows into a reservoir directly affect its yield, there should
be a corresponding jump in decrease of the reservoir yields. The sub catchment also experienced
some increase in no flows in its streams. A peak in temperatures coincides with peaks in
precipitation. For drought years, there is maximum peak and vice versa during years of plenty
precipitation. This is illustrated by taking drought years of 91/92 and 82/83 where both minimum
and maximum temperatures had peaks while year 2000 had a drop in both trends. This means that
there is a direct relationship between the precipitation pattern and the temperature pattern. The
ambient temperature are affected by the ambient humidity, therefore the higher the humidity the
cooler it becomes. The runoff peaks also correspond to the precipitation peaks. Generally on all
graphs low rainfall in year 91/92 coincides with low flows in the streams. Year 1978/79 was a
year of plenty rainfall in all dam catchments, and also there were high recordings of the runoff.
This shows that there is a relationship between rainfall and stream flows.
14
1400
Bulawayo
1200
Esigodini
Annual Ranfall (mm)
1000
Filabusi
800
Linear
(Bulawayo)
600
Linear (Esigodini)
400
Linear (Filabusi)
200
20
00
19
97
19
94
19
91
19
88
19
85
19
82
19
79
19
76
19
73
19
70
19
67
19
64
19
61
19
58
19
55
19
52
19
49
19
46
19
43
19
40
19
37
19
34
19
31
0
Year Ending September
Fig. 2 Precipitation variation (1930 –2000) for Bulawayo, Esigodini and Filabusi
15
Fig. 3. Stream flow recorded (1970-200) for the rivers flowing into the dams
Reservoir yields and demand
Reservoir yield is declining, and predicted to decline further. The rate of decline predicted by the
IPCC SRES models is faster than the current trend (Fig. 4). Predicted future yields and the water
demands intersect from 2009 onwards. After these intersection points, the demand will be higher
than the combined yield and therefore a deficit will start (Table 4).
16
140.00
Current trend
Future high emissions
Future low emissions
120.00
3
Volume of yield or demand (Mm /year)
Unrestricted demand
WDM- demand
Power (Current trend)
100.00
80.00
60.00
40.00
20.00
0.00
2029/30
2024/25
2019/20
2014/15
2009/10
2004/5
1999/2000
1994/95
1989/90
1984/85
1979/80
Hydrological years
Fig. 4. Recorded dam yields and water demand (1979-2000), and predicted dam yields and
demand (2005-2030).
Table 4. Deficit levels by 2030
Climate
Unrestricted demand scenario
Water demand management scenario
Scenarios
Deficit year
Deficit year
Deficit by 2030
(Mm3/year)
Deficit by 2030
(Mm3/year)
High emissions
2009/10
41.98
17/18
27.78
Low emissions
2010/11
38.30
14/15
24.46
Current trend
2014/15
35.37
20/21
21.17
CONCLUSIONS AND RECOMMENDATIONS
From the results it can be observed that climate is changing in the study area. The river flows are
decreasing due to decrease in precipitation at a rate of 2.8% per decade for Esigodini and 2.5%
17
per decade for Filabusi compared to the long-term average of 70 years for Esigodini and 80 years
for Filabusi. Temperatures are warming up at a rate of 1.5% per decade and 2.2% per decade for
maximum and minimum temperatures respectively. This accelerates evaporation from the open
surface reservoirs. Rivers show a strong seasonal variability. Flows are often ephemeral and at
times limited to few weeks. There is some relationship between the precipitation variation and
runoff variation. In wet season of high rainfall there catchments experience some high inflows.
The demand is increasing yet the dam yields show a down ward trend. The city was
recommended to implement some water demand management, which was going to reduce the
consumption per capita from an average of 150 litres per capita per to 80 litres per capita per day.
Using a population growth rate of 3% per annum as stated in the city’s master plan the water
demand is also growing at this rate. Apparently the city council uses more water from Ncema
dams and Mzingwane because of the installed abstraction capacities in these dams. Inyankuni
follows the list then lastly Insiza. The city council needs to install pumps at Insiza to fully utilize
its allocated yield from the dam. Currently, it is using gravity to lower Ncema where it pumped to
the city.
In addition to water demand management, the city is recommended to implement some or all of
the following developments: increase the reservoir capacity by connecting Mtshabezi dam (yield
= 9.8 Mm3/year), extract more water from ground water from Nyamandlovu acquifer (yield = 4.4
Mm3/year), Umguza aquifer (7.3 Mm3/year), abstraction from Zambezi basin (161 Mm3/year)
and increased grey water recycling.
18
ACKNOWLEDGEMENTS
This paper contains research results from a M.Sc. project by B. Moyo at the University of
Zimbabwe, and is a contribution to WaterNet Challenge Program Project 17 “Integrated Water
Resource Management for Improved Rural Livelihoods: Managing risk, mitigating drought and
improving water productivity in the water scarce Limpopo Basin”, funded through the
Consultative Group on International Agricultural Research’s Challenge Program on Water and
Food. The research is also supported by a research grant from RELMA-in-ICRAF and a
scholarship awarded to B. Moyo by the WREM Trust. The opinions and results presented in this
paper are those of the authors and do not necessarily represent the donors or participating
institutions. The cooperation of the Bulawayo City Council and the Zimbabwe National Water
Authority (Research and Data Department and Catchment Manager: Mzingwane) has been
essential and is gratefully acknowledged.
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