Download Hydrologic impacts of climate change on the Nile River Basin

Climatic Change (2010) 100:433–461
DOI 10.1007/s10584-009-9693-0
Hydrologic impacts of climate change on the Nile River
Basin: implications of the 2007 IPCC scenarios
Tazebe Beyene · Dennis P. Lettenmaier · Pavel Kabat
Received: 3 September 2007 / Accepted: 28 July 2009 / Published online: 13 October 2009
© Springer Science + Business Media B.V. 2009
Abstract We assess the potential impacts of climate change on the hydrology and
water resources of the Nile River basin using a macroscale hydrology model. Model
inputs are bias corrected and spatially downscaled 21st Century simulations from
11 General Circulation Models (GCMs) and two global emissions scenarios (A2
and B1) archived from the 2007 IPCC Fourth Assessment Report (AR4). While all
GCMs agree with respect to the direction of 21st Century temperature changes, there
is considerable variability in the magnitude, direction, and seasonality of projected
precipitation changes. Our simulations show that, averaged over all 11 GCMs, the
Nile River is expected to experience increase in streamflow early in the study period
(2010–2039), due to generally increased precipitation. Streamflow is expected to
decline during mid- (2040–2069) and late (2070–2099) century as a result of both
precipitation declines and increased evaporative demand. The predicted multimodel
average streamflow at High Aswan Dam (HAD) as a percentage of historical (1950–
1999) annual average are 111 (114), 92 (93) and 84 (87) for A2 (B1) global emissions
scenarios. Implications of these streamflow changes on the water resources of the
Nile River basin were analyzed by quantifying the annual hydropower production
and irrigation water release at HAD. The long-term HAD release for irrigation
increases early in the century to 106 (109)% of historical, and then decreases to 87
(89) and 86 (84)% of historical in Periods II and III, respectively, for the A2 (B1)
global emissions scenarios. Egypt’s hydropower production from HAD will be above
the mean annual average historical value of about 10,000 GWH for the early part
of 21st century, and thereafter will generally follow the streamflow trend, however
T. Beyene · D. P. Lettenmaier (B)
Department of Civil and Environmental Engineering, University of Washington,
Box 352700, Seattle, WA 98195, USA
e-mail: [email protected]
P. Kabat
ALTERRA Green World Research, Wageningen University and Research Centre,
P.O. Box 47, 6700 AA, Wageningen, The Netherlands
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with large variability among GCMs. Agricultural water supplies will be negatively
impacted, especially in the second half of the century.
1 Introduction
The climate of Africa is both varied and varying. Varied, because climate ranges from
humid equatorial to seasonally arid and sub-tropical Mediterranean, and varying
because African climate exhibits differing degrees of temporal and spatial variability
(Hulme et al. 2001). Africa is vulnerable to the effects of interannual climate
variations such as the El Nino-Southern Oscillation (ENSO) with respect to extreme
events (drought, floods, and changes in hydrologic patterns) (Conway et al. 2007;
Latif and Dommenget 1999; Hulme et al. 2001). The portion of sub-Saharan Africa
that depends entirely on the Nile River for its water supply is particularly susceptible
to hydrologic changes that might be associated with a warmer climate. Flooding and
droughts will be pose challenges in the face of increasing pressure on water supplies
due to rapid population growth and dwindling resources (IPCC 2007; El-Fadel et al.
2003).
The Nile River basin is home to almost 20% of Africa’s population. It has
experienced high population growth rates, with the basin’s population expected to
double by 2025 (Population Action International 2001). Virtually all projections are
for continuing population growth, which in turn will increase demand for natural
resources among the ten Nile River riparian countries. In recent years the potential
effects of climate change on the Nile River basin have been given much more
attention, in part as a result of studies (e.g. Yates and Strzepek 1998a, b; Conway
et al. 2007) showing that the water resources of the basin are critically sensitive to
climate change.
The IPCC Fourth Assessment Report (AR4) has resulted in a wealth of General
Circulation Model (GCM) simulations that have been archived in a consistent
manner at the Lawrence Livermore National Laboratory Program for Climate
Model Diagnosis and Intercomparison (PCMDI). These simulations provide the
basis for a much more coherent analysis of possible effects of climate change using
multimodel ensemble techniques (e.g., Krishnamurti et al. 2000) than has previously
been possible. For instance, Maurer (2007) evaluated implications of projected 21st
Century climate for California’s water resources using PCMDI-archived output from
11 IPCC/AR4 GCMs. Christensen and Lettenmaier (2007) evaluated implications of
IPCC AR4 climate projections for Colorado River water resources from the same 11
GCMs and two global emissions scenarios. We follow the lead of these recent studies
in using multimodel ensemble methods to evaluate the implications of 21st Century
climate change for the Nile River basin.
Future changes and uncertainties in the allocation of Nile River water resources
may have significant effects on local and regional economies, agricultural production, energy availability, and environmental quality (NBI 2001; Hulme et al. 2005;
Conway and Hulme 1993; Yates and Strzepek 1998a, b). Water resources planning
based on the concept of a stationary climate is increasingly considered inadequate
for sustainable water resources management (Mohamed et al. 2005; Milly et al.
2008). In addition to natural variability, which is incorporated in existing water
planning methods, design of new water projects will have to deal with uncertainty
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associated with population growth and a changing climate. Therefore, understanding
the uncertainty in projected climate change over the next century is essential to
understanding how the economy of the Nile basin will evolve, including social
and environmental impacts. This uncertainty is attributable both to uncertainty in
future global emissions (related to policy decisions and public response) and to
uncertainties in model projections (due to differing sensitivities of the GCMs to
perturbations in atmospheric composition).
Water resources planning studies, which typically are conducted for time horizons
of several decades, now require consideration of ongoing and future global climate
change. The near certainty of increased future water demand in the Nile basin
(notwithstanding uncertainty as to magnitude of the increases) contrasts with the
uncertainty of climatically-induced changes in Nile River flow (Conway and Hulme
1996; Yates and Strzepek 1998a; Strzepek et al. 1995, 2000), both as to magnitude
and direction.
Although this study represents the first attempt to apply multimodel ensemble
techniques to the Nile River basin using the IPCC AR4 global emission scenarios,
the Nile River has been the focus of several previous studies of climate change using
different climate models and techniques (e.g. Conway 2005; Conway and Hulme
1996; Conway et al. 2007; Hulme 1992; Hulme et al. 2005; Strzepek and Yates 1999;
Strzepek et al. 1995). Yates and Strzepek (1998a, b) found that several climate change
scenarios implied that agriculture would be negatively affected by climate change
despite increased water availability and only moderate yield declines, as a result of
impacts associated with changes in local and regional biophysical systems and shifts
in national agricultural economies. Conway and Hulme (1996) used CO2 doubling
climate scenarios which provided widely diverging pictures of possible future Nile
River flows, ranging from a 30% increase to a 77% decrease. Strzepek and Yates
(1999) used a dry and wet scenario analysis of possible future conditions and found
that under wet climate scenarios, annual surplus water beyond 75 BCM (75 × 109 m3 )
remained unused whereas for drier scenarios (below 75 BCM), water was a constraint
to agricultural production into the 21st century. As a result, resources were diverted
to less water demanding crops and to livestock and non-agricultural sectors. Tate
et al. (2004) analyzed the sensitivity of the water balance of Lake Victoria to climate
change using HadCM3 A2 and B2 emission scenarios, and found that changes in
annual rainfall and evaporation derived from HadCM3 implied that declines in water
levels would occur during the 2021–2050 time horizon. This contrasted with projected
increases in water levels later in the century (2070–2099). Since most of these studies
were based on a single GCM and/or emission scenario, the uncertainty in these
predictions was not evaluated. All of these studies were limited by the coarse spatial
resolution of the climate models and the small number of climate models that could
be evaluated.
In this paper, we assess the hydrologic implications of climate change on the
water resources of the Nile River basin through a four-step process. The first step
is extraction of the key hydrologic drivers (precipitation and temperature) from the
PCMDI archives. In our case, we extracted output from 11 GCMs to be consistent
with Christensen and Lettenmaier (2007) and Maurer (2007). All the selected GCMs
included at least one 100-year run, and two SRES (Scientific Report on Emission
Scenarios) global emissions scenarios (A2, corresponding roughly to unconstrained
growth in emissions, and B1, corresponding to elimination of global emissions
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increases by 2100) from PCMDI. The second step is removal of the inherent bias
in the climate model predictions and resolution of the scale mismatch between the
GCMs (most of which run at a spatial resolution of 2◦ to 5◦ latitude–longitude) and
the spatial scale of our hydrologic model (which was applied at a 1/2 × 1/2◦ latitude–
longitude spatial resolution). The third step is forcing the hydrologic model using the
downscaled and bias corrected climate model output. The final step is driving a Lake
Nasser reservoir operations model using the simulated streamflows associated with
the 11 GCMs and two global emissions scenarios to assess the impact of the changing
climate on hydropower production and irrigation water supply extracted from the
Nile River at High Aswan Dam (HAD).
2 Approach
Our overall approach is to start with multiple model ensembles of projected future
(21st century) climate scenarios from the 2007 IPCC Fourth Assessment Report
(AR4), which we then spatially downscale and bias correct to a spatial scale appropriate to a regional hydrology model. Each of 22 100-year ensembles (11 GCMs each
using two emissions scenarios) is used to force the Variable Infiltration Capacity
(VIC) hydrology model, which produces corresponding ensembles of projected
streamflow at inflow points to major dams and reservoirs in the Nile River basin.
Implications of the changes in streamflow for water management are analyzed by
using the hydrology model sequences as input to a model of the Lake Nasser
reservoir, formed by High Aswan Dam (HAD). We detail the specifics of each step
in this section.
2.1 Study area
The Nile River flows some 6700 km through ten countries before reaching the
Mediterranean Sea, making it the longest international river system in the world. Its
headwaters are in Lake Victoria at about 4◦ S latitude, from which it flows mostly
northward to its mouth at 32◦ N latitude (see Fig. 1a). It has a drainage area of
about 3.35 million km2 , which is equivalent to about 10% of the African continent or
roughly 1/2 the area of the continental United States. Egypt and the Sudan are the
two major users of this river, while Ethiopia is the primary source. This imbalance
in the primary producers and consumers of the basin’s water resources lead Swain
(1997) to conclude that the Nile is the international river system which currently has
the greatest potential to precipitate major armed conflict.
The major lakes in the basin (Lakes Victoria, Nasser and Tana) have a total
surface area of about 81,500 km2 and the area covered by swamps is an additional
69,700 km2 (Biswas 1994). Precipitation is to a large extent governed by the movement of the Inter-Tropical Convergence Zone (ITCZ) and its interaction with topography. In general, precipitation increases from north to south, and with elevation.
Precipitation is virtually zero in the Sahara Desert, and increases southward to about
1,200–1,600 mm/year on the Ethiopian and Equatorial Lakes Plateaus (Mohamed
et al. 2005).
The Nile is formed by three tributaries, the Blue Nile, the White Nile, and the
Atbara. The flow of the Blue Nile is strongly seasonal because its runoff is primarily
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Fig. 1 Head waters and sub-basins of the main stem Nile (a) and locations of the two gauging stations
and flow routing network derived from 1/2◦ (latitude–longitude) DEM (b)
driven by monsoon precipitation. The Blue Nile contributes about 60% of the total
flow of the Nile, whereas the Baro-Akobo (Sobat), and Tekezze (Atbara) contribute
slightly less than 15% each. The headwaters of all the tributaries of the Blue Nile are
in the highlands of Ethiopia, and the bulk of their runoff (70% on average) occurs
between July and September. Among the tributaries of the Blue Nile, the Upper Blue
Nile (drainage area 175,000 km2 ), which contributes about 50% of the Nile’s flow at
High Aswan Dam (HAD), is the most important. The White Nile and the Blue Nile
join north of Khartoum, where they are joined by the Atbara. The river then flows
north through Lake Nasser, the second largest man-made lake in the world, before
splitting into two major distributaries just north of Cairo.
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2.2 General Circulation Models (GCMs)
General Circulation Models (GCMs) are mathematical representations of atmospheric, oceanic, and continental processes and interactions. These models are
limited by complexity and uncertainty as well as non-linear interactions among atmospheric and oceanic processes (Hillel and Rosenzweig 1989). Table 1 summarizes
the 11 GCMs for which model output was used to construct forcing data for the
hydrologic model. For IPCC/AR4, six global greenhouse gas emissions scenarios
were used following the IPCC 2001 scenarios. The global emissions scenarios ranked
from highest to lowest in terms of global average emissions at mid-century are A1FI,
A2, A1B, B2, A1T and B1. The A1 world describes a future of rapid economic
growth, low population growth, and rapid introduction of new and more efficient
technology. World population approaches 8.25 billion by 2080 and economic growth
averages 3.3%. The A1F1 and A1B subgroups differ only in their descriptions of
the world’s energy sources; both assume continued reliance on fossil fuels. The
A2 world is one of high population growth (14 billion by 2080) and less rapid
economic development (2.3%). B1 describes a future of rapid change in economic
structures and the introduction of clean technologies, where population growth is
low (8.25 billion by 2080) but economic growth is relatively rapid (2.9%). In the B2
world, both population growth and economic growth are moderate (10.1 billion by
2080 coupled with 2.7% economic growth).
Global emission scenarios A2 and B1 were chosen for this study because they are
the most widely simulated global emission scenarios in all models. The A2 global
emission scenario projects global average CO2 concentrations will reach 850 ppm by
Table 1 Description of GCMs (General Circulation Models)
GCM
Modeling group, country
IPCC model ID
Reference
CNRM
Centre National de Recherches
Météoroliques, France
CSIRO Atmospheric Research,
Australia
Geophysical Fluid Dynamics
Laboratory, USA
Goddard Institute for
Space Studies, USA
Hadley Center for Climate and
Prediction and Research, UK
Institute for Numerical
Mathematics, Russia
Institut Pierre Simon
Laplace, France
Center for Climate Systems
Research, Japan
Max Planck Institute for
Meteorology, Germany
Meteorological Research
Institute, Japan
National Center for Atmospheric
Research, USA
CNRM-CM3
Salas-Mélia et al. 2005
CSIRO-Mk3.0
Gordon et al. 2002
GFDL-CM2.0
Delworth et al. 2006
GISS-ER
Russell et al. 1995, 2000
UKMO-HadCM3
Gordon et al. 2002
INM-CM3.0
Diansky and Volodin 2002
IPSL-CM4
IPSL 2005
MIROC3.2
K-1 model developers 2004
ECHAM5/MPI-OM
Jungclaus et al. 2006
MRI-CGCM2.3.2
Yukimoto et al. 2001
PCM
Washington et al. 2000
CSIRO
GFDL
GISS
HADCM3
INMCM
IPSL
MIROC
MPI
MRI
PCM
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2100. Scenario B1, on the other hand, assumes an increasing dependence on clean
and resource-efficient technologies. CO2 concentrations under this scenario initially
increase at nearly the same rate as in the A2 scenario, but then level off around midcentury and reach 550 ppm by 2100.
2.3 VIC land surface hydrologic model
The Variable Infiltration Capacity (VIC) model of Liang et al. (1994, 1996) is a
semi-distributed grid-based land surface hydrological model which parameterizes
the dominant hydrometeorological processes taking place at the land surface–
atmosphere interface. The VIC model forcings were daily precipitation, maximum
and minimum temperature, and daily average wind speed, for each 1/2◦ model grid
cell (other forcing variables—specifically downward solar and longwave radiation,
and dew point were derived from daily temperature and temperature range using
methods described by Maurer et al. (2002). The model was implemented at 1/2◦
(∼48 km) spatial resolution for the entire Nile basin. The model consists of two
major components: vertical and horizontal. The vertical component calculates the
water and energy balance components for each individual grid cell. The horizontal
component is a convolution integral, which routes the runoff generated at each
grid cell to specific locations. A mosaic representation of land cover, and sub-grid
parameterizations for infiltration and the spatial variability of precipitation and
temperature, account for spatial heterogeneities in key hydrological processes. The
model uses three soil layers and one vegetation layer with energy and moisture fluxes
exchanged between the layers.
The model was calibrated for the entire Nile basin at three stream gauge locations,
the Blue Nile at Eldiem, the main stem at Dongola, and the main stem at HAD.
Calibration for the Lake Victoria basin could not be performed due to lack of reliable
observed streamflow records. A calibration procedure similar to that described in
Nijssen et al. (1997) and Payne et al. (2004) was followed to assure a match between
model-simulated and observed flows for the period in which historic streamflow
observations were available. Validation results for two gauging stations are shown
in Fig. 2a–b. The simulations generally reproduce the observed long term monthly
mean hydrograph and also capture interannual flow variations. Since VIC was run at
a finer spatial resolution than the General Circulation Models, a bias correction and
spatial downscaling step (method described in the Section 2.5) was used to bridge the
resolution gap between climate model and VIC for the future climate simulations.
2.4 Uncertainties in GCMs prediction of climate change variables
Despite advances in GCMs and computational resources, which have resulted in
increased spatial resolution, climate model outputs nonetheless have considerable
biases and uncertainties in the simulation of both temperature and precipitation
under current climate conditions. These biases are usually large enough that direct
use of these variables as input to hydrological models is infeasible (see e.g. IPCC
AR4 WG1 report, Tebaldi et al. 2004, Greene et al. 2006 and Wilby et al. 2000),
and therefore a bias removal and spatial downscaling step is essential. Although
spatial resolution can be improved through use of regional climate models, and biases
reduced somewhat, Wood et al. (2004) show that even when regional climate models
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Fig. 2 Naturalized and observed Nile River flow at selected gauging stations and some measures of
agreement between naturalized and observed flow. R correlation coefficient, E Nash–Sutcliffe model
efficiency coefficient, BIAS bias for the period 1966–1999. Main Nile River flow at DONGOLA (a)
and Upper Blue Nile at Rosiers Upstream of El diem (b), Sudan for the period 1970–1999. Validation
period shown excludes the period 1950–1965 used for model calibration
are used, a bias removal step is essential where the climate model output is used to
force a hydrological model. We summarize in this section the approach that we have
used, which is a variation of the bias correction and spatial downscaling (BCSD)
approach described in more detail by Wood et al. (2002, 2004), and used in a number
of previous studies (e.g. Christensen et al. 2004; Christensen and Lettenmaier 2007;
Hayhoe et al. 2007; Maurer 2007).
2.5 Bias Correction and Spatial Downscaling (BCSD)
The BCSD approach we use in this study is described by Wood et al. (2002, 2004). It
takes monthly values of precipitation (Ptot) and average temperature (Tavg) from
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the GCM output. These values are disaggregated in space (to the 1/2◦ latitude–
longitude resolution) and in time (from monthly to daily) to provide forcings to our
land surface hydrologic model. Although GCMs produce output at much shorter
time steps than monthly, the archived output at PCMDI is monthly for most of the
11 models we used.
The BCSD method uses empirical quantile–quantile mapping as its main element.
In brief, the method downscales monthly simulated and observed temperature and
precipitation at the GCM spatial scale (regridded to common 2 × 2◦ latitude by
longitude spatial resolution) to 1/2◦ resolution at which the VIC hydrology model
was applied. The quantile–quantile mapping procedure is “trained” to monthly empirical probability distributions of the climate model output for current climate and
observed gridded climate data at the same (2◦ ) spatial resolution. The climate model
output was temporally and spatially disaggregated using the resampling approach
of Wood et al. (2002, 2004) to create a daily time series for the hydrology model
at the 1/2◦ spatial resolution. The resampling was performed on a monthly basis by
sampling with replacement from the historical observation record in such a way that
the statistics of the monthly 1/2◦ values were preserved, while the sequencing of daily
values was provided by the subsampling. In application of the method, the linear
trend in Tavg (daily average temperature) is removed prior to bias correction and is
re-imposed afterward, to avoid distortion of the tails of the probability distribution
of temperature as temperatures rises. The climatology for the historical run (1950–
1999) was the global gridded precipitation data set developed and described in Adam
and Lettenmaier (2003), and Adam et al. (2006).
3 Results and discussions
In this section we summarize our analysis of the results from bias corrected and
spatially downscaled GCM climate models and two SRES global emission scenarios A2 and B1. The bias corrected and spatially-downscaled hydrologic drivers
(temperature and precipitation) for future climate (2000–2100) are compared to the
1950–1999 gridded historical global data set of Adam and Lettenmaier (2003). We
further analyzed and compared derived hydrologic variables (runoff, evapotranspiration and soil moisture) simulated by VIC forced by GCM scenarios to historical
simulations (1950–1999). The climate change simulations derived from both global
emissions scenarios are segregated into three time horizons, period I (2010–2039),
period II (2040–2069), and period III (2070–2099). Hydrologic response of the
basin to changing climate is analyzed by quantifying future streamflow changes at
selected gauging stations and further evaluating the implications of these streamflows
for water management using a reservoir operation model that represents annual
hydropower production and irrigation water releases at High Aswan Dam.
3.1 Temperature and precipitation changes
Although GCM model output is archived at a monthly time step and is downscaled
to a daily time step to force the VIC model, we focus here on precipitation and
temperature changes in northern hemisphere winter (DJF) and summer (JJA), as
these are the main rainy season of the Nile basin (DJF for Equatorial Africa and JJA
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for Eastern Africa), as well as annually. We summarize model results both as the
multimodel mean, and a measure of Inter-Model-Spread, range of prediction, which
gives an indication of the uncertainty in the future projections. The bias-corrected
and downscaled temperature and precipitation time series from each climate model
Fig. 3 a Downscaled and bias-corrected long-term (30 year) mean monthly temperature, precipitation, simulated runoff, evapotranspiration, and soil moisture for the entire Nile basin. b Downscaled
and bias-corrected long-term (30 year) mean monthly temperature, precipitation, simulated runoff,
evapotranspiration, and soil moisture for Blue Nile basin region. c Downscaled and bias-corrected
long-term (30 year) mean monthly temperature, precipitation, simulated runoff, evapotranspiration,
and soil moisture for the Lake Victoria region
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(ensemble member) was used to force the VIC model for both A2 and B1 global
emissions scenarios. Figure 3a–c show the bias-corrected and downscaled long-term
multimodel average precipitation, temperature and simulated hydrologic parameters
(evaporation, runoff, and soil moisture). The 1950–1999 (Adam and Lettenmaier
2003; Adam et al. 2006) historical precipitation and temperature data were used as
a baseline reference for the purpose of model calibration, validation and evaluation
of predicted changes from climate models. Because the sub-basins of the Nile basin
have different physical and hydroclimatological characteristics, we evaluated results
Fig. 3 (continued)
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over the main stem Nile (Main Nile) and the two most important sub-basins, the Blue
Nile sub-basin and the Lake Victoria region (Equatorial region) separately.
Annual average temperature changes across the Nile basin relative to the 1950–
1999 historical average range from 0.91 to 1.95◦ C for A2 and 0.94 to 1.54◦ C for
B1 global emissions scenario for period I (2010–2039). These values are equivalent
to about 0.3 to 0.6◦ C and 0.3 to 0.5◦ C warming per decade for A2 and B1 global
emissions scenarios, respectively. The model projections indicate that warming will
continue across the Nile region through the late 21st century to a level of (3.4, 5.9)◦ C
Fig. 3 (continued)
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and (3.0, 4.1)◦ C (Min, Max) for A2 and B1 global emissions scenarios by 2070–2099
relative to the 1950–1999 historical average.
For the purpose of assessment of the impact and implications of green house
gas-induced climate change scenarios of temperature and precipitation to the water
resources management of the Nile basin, we used the multimodel mean (average
of 11 GCMs) as well as range of prediction. As expected, Scenario A2 is generally
warmer than Scenario B1. For the entire Nile basin (Fig. 3a) multimodel annual
average temperature increased by 1.5 (1.3), 3.2 (2.8) and 4.4 (3.6)◦ C relative to
the historical (1950–1999) average for the A2 (B1) global emissions scenarios and
periods I to III respectively (Table 2).
Unlike future temperature predictions, the trends in which are unidirectional
across GCM models and throughout the Nile River basin, the directions of precipitation changes are mixed and highly variable both from sub-basin to sub-basin and
from season to season. Averaged across GCM models for SRES A2 and B1 global
emissions scenarios and for periods I to III, multimodel averages suggest that the
entire Nile basin, Blue Nile and Lake Victoria regions will experience increases in
DJF rainfall with the exception of the Lake Victoria region which is expected to
experience decreases in the late 21st Century (Fig. 5). JJA precipitation changes have
no clear signals in terms of magnitude and direction and vary substantially from subbasin to sub-basin (Fig. 4).
Individual GCM model predictions show wide range of prediction by region and
season for precipitation. For the entire Nile region for the A2 emissions scenario,
DJF precipitation changes range from −24 to 37% and −40 to 18% for period I
and III respectively. JJA precipitation for the entire Nile basin and A2 emissions
scenario ranges from −21 to 34 and −42 to 15% for periods I and III respectively,
showing relatively narrower range of prediction for JJA than DJF. The entire Nile
basin is projected to experience multimodel average DJF precipitation increases up
to 23 (12%) to 12 (3%) for A2 (B1) global emissions scenarios for periods I and III
respectively (Fig. 5). JJA precipitation changes will have early increases of up to 19
(15%) and then decreases in mid century of −3 (−1%) and then increases of 7 (4%)
in period III, mainly contributed by the late 2080–2090 JJA increases in the Blue Nile
sub-basin for A2 (B1) global emissions scenarios. Similarly, multimodel average DJF
and JJA precipitation changes for Blue Nile and Lake Victoria regions are shown in
Fig. 5.
Previous studies of seasonal precipitation changes over Africa are qualitatively
similar as to the direction and magnitude of seasonal precipitation changes. Hulme
et al. (2001) studied the impacts of African climate change by generating some
Table 2 Multimodel average
annual and seasonal (JJA and
DJF) temperature changes as
differences in degrees (◦ C) of
the historical (1950–1999) for
two sub-basins of the Nile
basin and entire Nile basin for
A2 (B1) global emission
scenarios and three periods
Scenario
Lake
Blue
Entire Nile basin
Victoria
Nile
Annual
DJF
JJA
Historical
19.8◦ C
21.25◦ C
23.45◦ C
22.11◦ C
25.24◦ C
A2 2010–39
A2 2040–69
A2 2070–99
B1 2010–39
B1 2040–69
B1 2070–99
1.06
2.51
3.45
1.0
1.9
2.91
1.25
3.1
4.18
1.22
2.55
3.37
1.48
3.22
4.36
1.31
2.76
3.65
1.38
2.89
3.90
1.02
2.78
3.54
1.16
2.45
3.60
1.15
2.50
3.58
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Fig. 4 Seasonal changes in precipitation and runoff for wet season (JJA). Panel (a) shows A2
emissions scenario JJA precipitation changes relative to mean historical (1950–1999), upper left panel
shows observed JJA 1950–99 precipitation, upper right panel shows changes in period 1, lower left
shows changes in period 2, and lower right shows changes in period 3. Panel (b): same as panel (a),
but for runoff
sensible guesses of climate change magnitudes. They sampled a plausible range of
scenarios at a global scale by making choices about future greenhouse gas forcings
and climate sensitivity following Hulme and Carter (1999b) and Carter et al. (1999).
Their analysis for the A2 emissions scenario combined with what they termed a high
sensitivity output showed that large areas of equatorial Africa will experience ‘significant’ increases in DJF rainfall of up to 50 or 100%, which is roughly comparable
to our 7 to 51% increases in the Blue Nile sub-basin. They also found for the same
scenario that precipitation would decrease ‘significantly’ in JJA over parts of the
Horn of Africa and northwest Africa. In contrast, the direction and magnitude of
Climatic Change (2010) 100:433–461
447
Fig. 5 Seasonal changes in precipitation and for wet season (JJA) and dry season (DJF). Upper
panel shows A2 and B1 emissions scenarios for DJF precipitation change and lower panel shows JJA
precipitation changes relative to mean historical (1950–1999) DJF and JJA precipitation
our JJA changes varies by time period, and do not show a clear signal, especially for
Blue Nile sub-basin.
In general, there is much less consistency among climate model projections of
precipitation than temperature (see Fig. 3a–c). In the multimodel ensemble, mean
annual precipitation increases over the entire basin for period I, however, by period
III, there are substantial basin-wide precipitation decreases. The IPCC TAR (IPCC
2001) concluded that the Nile basin will experience decreases in precipitation ranging
from zero and 40% by the end of the 21st century, a result which was based on
nine GCMs. Although less specific to the Nile basin, similar conclusions are also
inferred from the IPCC AR4. The report on African climate change (IPCC 2007)
found that sometime between 2080 and the end of the century, average annual
precipitation is very likely to decrease by a fifth along Africa’s Mediterranean coast,
with declines also expected in the northern Sahara and the northern West African
coast. Declines were also predicted for much of southern Africa with the extreme
west of the region likely to experience decreases of as much as 40% through June and
August. In contrast, tropical and eastern Africa may experience increased rainfall of
7% (IPCC 2007). As we will show below, the range of precipitation predictions by
the IPCC/AR4 climate models is generally consistent with this earlier expectation as
summarized in IPCC TAR.
448
Climatic Change (2010) 100:433–461
Despite the variations in individual climate model predictions, over the entire
Nile basin eight (nine) and three (six) of the 11 GCMs for the A2 (B1) global
emission scenario predicted increases in precipitation for period I and III, respectively (Tables 3, 4, 5, 6, 7 and 8). In the multimodel ensemble average, Nile basin
changes in precipitation, expressed as percentages of historical (1950–1999), are
115 (117), 98 (104) and 93 (96) for SRES A2 (B1) global emissions scenarios with
range of prediction for the A2 emission scenario of (−2, 26), (−12, 12) and (−20,
3), The range of prediction values for scenario B1 are (5, 30), (−5, 15) and (−10,
6). A range of prediction gives a rough indication of the ranges of uncertainty of
climate change predictions among GCMs; wider range indicates more uncertainty
and greater divergence among climate change predictions. The general trend is that
range of prediction becomes smaller towards the late 21st century, although the
reason is not clear.
The multimodel ensemble average annual precipitation changes for the Blue Nile
sub-basin expressed as a percentage of 1950–99 annual average precipitation are 115
(117), 98 (104) and 106 (96) for the A2 (B1) global emission scenario and periods I
to III, respectively. Changes for the Lake Victoria sub-basin are 117 (123), 98 (105)
and 90 (97) relative to the historical average (1950–1999). Tables 3, 4, 5, 6, 7, and 8
summarize the annual average changes in precipitation and temperature for the
entire Nile basin and the two sub-basins. We evaluated the end points in precipitation
projections, which correspond to the GISS (Goddard Institute for Space Studies)
and GFDL (Geophysical Fluid Dynamics Laboratory) climate models. Averaged
over the entire Nile basin and considering A2 global emissions scenario, GISS is
the wettest of the models, with precipitation increases of 40, 20, 16% relative to the
1950–1999 historical average for periods I to III, respectively. GFDL is the driest
model with corresponding predicted decreases in precipitation of 16, 38, and 36%
relative to historical for the three future periods. The corresponding projected annual
average temperature increases range from 1.0 to 6.0◦ C for GISS and 1.1 to 3.7◦ C for
GFDL for the entire Nile basin for periods I and III (Tables 9 and 10).
3.2 Streamflow changes
Conway and Hulme (1993) and Calder et al. (1995) found that the combined
effects of precipitation and temperature changes would have profound effects on
the streamflow regime of the Nile River. In this section, we analyze the inferred
changes in streamflow that would accompany the precipitation and temperature
changes summarized in Section 3.1. Table 11 shows the projected changes in Nile
River flow at HAD and the Blue Nile flow at Eldiem. Although there is a consistent
decline in streamflow in the ensemble mean and for most of the GCMs by the end
of the 21st century, the specific magnitudes and direction of changes in predictions
differ substantially across GCMs.
Changes in precipitation and temperature result in disproportional changes in
the hydrologic response of a river basin. For the A2 emission scenario, Fig. 6a–d
show simulated mean monthly hydrographs derived from all 11 GCMs at HAD, and
Blue Nile at ElDiem for period I and III. Under the A2 emission scenario, projected
changes in precipitation range between −16 to 40%, with a multimodel median of 7%
early in the century (2010–2039). These changes resulted in changes in the long-term
mean annual streamflow entering HAD ranging from −23 to 34%, with a multimodel
Lake Victoria
Blue Nile
Entire Nile
GFDL
1.11 (1.23)
1.42 (1.25)
1.55 (1.35)
CSIRO
0.87 (0.92)
1.57 (1.44)
1.77 (1.52)
CNRM
1.12 (1.09)
1.5 (1.1)
1.63 (1.23)
MPI
1.02 (0.96)
1.34 (1.3)
1.27 (1.17)
MRI
0.97 (0.89)
1.09 (0.78)
1.41 (0.94)
MIROC
1.33 (1.16)
1.76 (1.66)
1.95 (1.37)
IPSL
1.05 (1.03)
1.65 (1.49)
1.43 (1.23)
INMCM
1.22 (1.15)
1.13 (0.9)
1.38 (1.01)
HadCM3
1.28 (1.08)
1.35 (1.12)
1.35 (1.12)
PCM
0.72 (0.65)
0.96 (0.99)
0.91 (1.09)
Lake Victoria
Blue Nile
Entire Nile
GFDL
1.89 (1.44)
3.21 (2.87)
3.67 (2.73)
2.2 (1.62)
3.15 (2.62)
3.47 (2.84)
CSIRO
CNRM
2.57 (2.05)
3.13 (2.33)
3.77 (2.66)
MPI
2.45 (1.95)
2.71 (2.65)
3.59 (2.58)
MRI
2.67 (1.94)
3.56 (2.67)
3.78 (2.69)
MIROC
3.23 (2.46)
3.54 (2.79)
3.99 (3.43)
IPSL
2.75 (2.56)
3.05 (2.83)
3.31 (2.97)
INMCM
2.96 (1.78)
3.25 (2.76)
3.69 (3.09)
HadCM3
2.76 (1.68)
3.26 (2.83)
3.75 (3.22)
PCM
2.22 (1.95)
2.54 (1.99)
2.77 (2.25)
Lake Victoria
Blue Nile
Entire Nile
GFDL
3.44 (2.94)
3.21 (3.87)
3.67 (3.37)
CSIRO
3.23 (3.11)
3.89 (3.42)
4.53 (3.79)
CNRM
3.32 (2.81)
3.83 (3.21)
4.77 (3.64)
MPI
3.88 (3.17)
4.71 (3.38)
4.87 (3.81)
MRI
3.47 (3.05)
4.56 (3.41)
4.88 (3.59)
MIROC
3.93 (3.38)
5.54 (3.79)
5.86 (4.13)
IPSL
3.37 (2.66)
3.85 (3.13)
4.56 (3.45)
INMCM
3.91 (2.18)
4.23 (3.76)
4.49 (3.58)
HadCM3
4.01 (3.26)
4.66 (3.83)
4.21 (3.99)
PCM
2.39 (2.25)
2.84 (2.87)
3.38 (3.01)
GISS
141 (147)
153 (158)
140 (142)
Region
Lake Victoria
Blue Nile
Entire Nile
82 (92)
87 (96)
84 (90)
GFDL
135 (148)
118 (121)
131 (138)
CSIRO
128 (139)
109 (119)
107 (114)
CNRM
124 (129)
119 (114)
127 (133)
MPI
115 (110)
133 (139)
101 (110)
MRI
122 (132)
128 (135)
105 (109)
MIROC
131 (135)
107 (122)
125 (126)
IPSL
97 (101)
93 (90)
92 (97)
INMCM
96 (100)
102 (109)
95 (101)
HadCM3
124 (125)
123 (118)
120 (126)
PCM
Table 6 2010–2039 multimodel annual average change in precipitation (%) relative to 1950 1999 historical average for sub-basins of the Nile basin and the entire
basin for each GCM and the A2 (B1) global emissions scenario
GISS
3.95 (3.22)
4.72 (3.40)
5.04 (3.74)
Region
Table 5 2070–2099 multimodel annual average change in temperature (◦ C) relative to 1950–1999 historical average for sub-basins of the Nile basin and the entire
basin for each GCM and the A2 (B1) global emissions scenario
GISS
2.01 (1.55)
2.72 (1.55)
3.0 (1.97)
Region
Table 4 2040–2069 multimodel annual average change in temperature (◦ C) relative to 1950–1999 historical average for sub-basins of the Nile basin and the entire
basin for each GCM and the A2 (B1) global emissions scenario
GISS
0.99 (0.85)
1.51 (1.38)
1.64 (1.28)
Region
Table 3 2010–2039 multimodel annual average change in temperature (◦ C) relative to 1950–1999 historical average for sub-basins of the Nile basin and the entire
basin for each GCM and the A2 (B1) global emissions scenario
Climatic Change (2010) 100:433–461
449
131 (137)
124 (128)
120 (124)
Lake Victoria
Blue Nile
Entire Nile
68 (87)
66 (72)
62 (77)
GFDL
104 (112)
89 (101)
113 (114)
CSIRO
105 (109)
87 (111)
94 (103)
CNRM
103 (106)
105 (102)
109 (117)
MPI
98 (100)
100 (119)
89 (99)
MRI
107 (112)
103 (121)
93 (103)
MIROC
112 (105)
83 (107)
115 (112)
IPSL
81 (92)
79 (83)
81 (79)
INMCM
78 (81)
85 (93)
88 (91)
HadCM3
100 (111)
101 (103)
110 (115)
PCM
Lake Victoria
Blue Nile
Entire Nile
GFDL
56 (68)
73 (79)
64 (72)
98 (113)
99 (101)
103 (108)
CSIRO
CNRM
100 (104)
126 (113)
84 (93)
MPI
90 (94)
89 (94)
91 (100)
82 (101)
121 (123)
77 (96)
MRI
97 (96)
113 (111)
85 (88)
MIROC
107 (102)
93 (103)
102 (106)
IPSL
68 (77)
96 (91)
71 (72)
INMCM
73 (84)
97 (116)
93 (94)
HadCM3
101 (103)
114 (98)
104 (106)
PCM
Lake Victoria
116 mm
117% (136 mm)
98.81% (115 mm)
89.63% (104 mm)
123.45% (143 mm)
104.7% (121 mm)
96.63% (112 mm)
Scenario
Historical (1950–1999)
A2 2010–39
A2 2040–69
A2 2070–99
B1 2010–39
B1 2040–69
B1 2070–99
116% (113 mm)
91% (89 mm)
105% (103 mm)
120% (117 mm)
104% (102 mm)
106% (104 mm)
98 mm
Blue Nile
112% (78 mm)
98% (68 mm)
90% (63 mm)
117% (82 mm)
103% (72 mm)
95% (67 mm)
70 mm
Annual
Entire Nile basin
+12% (7 mm)
−7% (−4 mm)
−11% (−0.12 mm)
+8% (4.5 mm)
−3% (−1.65 mm)
−10% (5.5 mm)
+23% (3.5 mm)
+8% (1.2 mm)
+12% (1.8 mm)
+12% (1.8 mm)
+10% (1.5 mm)
+3% (0.15 mm)
JJA
55 mm
15 mm
DJF
Table 9 Multimodel average annual and seasonal (JJA and DJF) precipitation changes as percentages (mm) of the historical (1950–1999) long-term mean monthly
precipitation for two sub-basins of the Nile basin and entire Nile basin for the A2 (B1) global emissions scenario and three periods
GISS
114 (121)
137 (142)
116 (113)
Region
Table 8 2070–2099 multimodel annual average change in precipitation (%) relative to 1950–1999 historical average for sub-basins of the Nile basin and the entire
basin for each GCM and the A2 (B1) global emissions scenario
GISS
Region
Table 7 2040–2069 multimodel annual average change in precipitation (%) relative to 1950–1999 historical average for sub-basins of the Nile basin and the entire
basin for each GCM and the A2 (B1) global emissions scenario
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Climatic Change (2010) 100:433–461
Climatic Change (2010) 100:433–461
Table 10 Simulated
streamflow by each climate
model routed to the main stem
Nile gauging station at High
Aswan Dam (HAD) for
periods I to III and global
emission scenarios A2 (B1)
Numbers are expressed as
percentages of the mean
annual historical flow
(1950–1999)
451
GCM
Period 1
2010–2039
Period 2
2040–2069
Period 3
2070–2099
GFDL
GISS
CSIRO
INMCM
MPI
CNRM
IPSL
PCM
MIROC
HADCM3
MRI
77 (92)
134 (136)
108 (127)
95 (99)
130 (128)
112 (123)
101 (110)
110 (125)
119 (119)
89 (95)
126 (118)
71 (85)
126 (127)
102 (105)
82 (83)
112 (105)
96 (100)
87 (90)
94 (103)
102 (98)
77 (78)
108 (98)
62 (75)
112 (115)
107 (112)
70 (73)
97 (93)
83 (85)
75 (79)
81 (91)
85 (86)
67 (68)
93 (95)
median of 10%. By the late 21st century (2070–2099), projected changes in precipitation range from −24 to 26%, with multimodel median of −3% and resulting streamflow changes between −38 to 12%, with multimodel median of −17%.
Projections of streamflow for the B1 scenario are similar, but by 2070–2099 the
declines in streamflow are less severe than for the A2 emissions scenario. In general,
the above results indicate increasing precipitation during the early 21st century
in the multimodel average under both emissions scenarios which results in larger
basin streamflow increases due a multiplier effect (elasticity) on streamflow changes
relative to precipitation changes, and modest negative effects on streamflow resulting
from temperature increases. In contrast, the temperature effects tend to dominate
later in the 21st century, and are compounded by precipitation decreases.
To have a sense of the seasonal inter-model variability of predicted streamflow
changes, we analyzed ranges of precipitation changes and associated streamflow
changes for DJF and JJA for individual GCMs and the multimodel average. For the
downstream-most gauge (HAD), Fig. 7a–b show increases in DJF streamflow for the
three time periods (from early to late 21st century), with a declining trend towards
the end of 21st Century mainly due to reduced DJF precipitation in the Lake Victoria
region (about −10% as shown in Fig. 5). The JJA seasonal streamflow distribution
has a mixed signal as do the precipitation predictions, but the ranges of precipitation
changes are generally larger than the streamflow ranges.
Table 11 Simulated
streamflow for each climate
model routed to the Blue Nile
gauging station at Eldiem
(Sudan) for periods I to III
and the global emission
scenario A2 (B1)
Numbers in parenthesis are
percentages of the mean
annual historical flow
(1950–1999)
GCM
Period 1
2010–2039
Period 2
2040–2069
Period 3
2070–2099
GFDL
GISS
CSIRO
INMCM
MPI
CNRM
IPSL
PCM
MIROC
HADCM3
MRI
83 (87)
148 (154)
126 (125)
100 (106)
113 (112)
105 (106)
131 (130)
127 (125)
130 (129)
106 (115)
131 (120)
77 (78)
133 (136)
102 (102)
81 (87)
92 (85)
86 (91)
106 (113)
102 (101)
105 (105)
86 (92)
106 (99)
71 (72)
126 (125)
112 (117)
74 (81)
83 (91)
97 (105)
96 (105)
103 (112)
95 (104)
76 (95)
96 (101)
452
Climatic Change (2010) 100:433–461
Fig. 6 Simulated mean seasonal cycle of streamflow derived from all 11 GCMs for A2 global
emissions scenario at the main stem Nile gauging station, HAD (a, b) for the beginning (2010–2039)
and end of the 21st century (2070–2099) and at Blue Nile gauging station (El diem—Sudan) for the
same time period (c, d)
The Blue Nile basin, which receives more than 70% of its annual runoff during the
JJA season, experiences mixed signals among the models. JJA seasonal precipitation
predictions show increases on average, with predictions ranging from −26 to 53%,
and multimodel median of 18%; these changes in precipitation result in streamflow
increases ranging from −17 to 48%, with multimodel median of 26% for period I
Climatic Change (2010) 100:433–461
453
Fig. 7 Simulated seasonal streamflow changes derived from all 11 GCMs and multimodel average
for A2 global emissions scenario at the main stem Nile gauging station, HAD (a, b) and Blue Nile at
El Diem (c, d) for early (2010–2039), mid-(2040–2069) and late-(2070–2099) 21st century expressed
as percentage changes from mean seasonal Historical flow (1950–1999)
and A2 emissions scenario. The range of precipitation predictions becomes wider
through the late 21st century as compared to streamflow. By 2070–2099 precipitation
predictions for the Blue Nile basin range from (−36 to 24%, with multimodel median
24%, resulting in streamflow predictions ranging from −29 to 23% with a multimodel
median of −10%. There are disparities among models as to precipitation predictions
over both the Blue Nile and White Nile basins (Hulme et al. 2001). However,
increasing temperature will lead to greater evapotranspiration placing additional
stress on water resources regardless of changes in precipitation.
The seasonal precipitation and streamflow changes summarized above suggest
that the Blue Nile flow tends to be more sensitive to temperature than to precipitation, particularly late in the 21st century as annual average temperature is
expected to be warmer by 3◦ C or so in the multimodel average. Similarly, in the
Lake Victoria region, Conway and Hulme (1996) found that a 10% increase in Lake
Victoria rainfall caused a 31% increase in runoff, whereas and a 4% increase in lake
evaporation caused an 11% decrease in runoff.
Previous studies of the impact of climate change on Nile River flow have been
confounded by inconsistencies in global emissions scenarios and other aspects of
the model simulations and partially for that reason have produced widely divergent results. There are considerable inter-model differences in precipitation and
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Climatic Change (2010) 100:433–461
temperature, which result in relatively large ranges in predicted future Nile flow.
Nonetheless, there is some general consistency of our results with other recent studies. For instance, Arnell (1999) suggested that precipitation in the Nile basin would
increase by about 10% by 2050, but he inferred that this increased precipitation
would be offset by increased evapotranspiration, implying that the net effect on the
main stem flow might be insignificant. Conway and Hulme (1996) used hydrologic
models of the Blue Nile and Lake Victoria basins similar to the water balance model
of Piper et al. (1986). By combining changes in Lake Victoria outflows with changes
in runoff in the other Nile sub-basins, they estimated a range of −9% to +12%
changes in mean annual Nile flows at HAD for 2025.
Strzepek et al. (1995) assessed the impact of climate change using three GCMs
with doubled global atmospheric concentrations (2 × CO2 ) to predict Nile flow
changes at HAD for 2060. In their results, the wettest model resulted in a 30%
increase in annual streamflow; whereas for the intermediate model, there was a 12%
decrease; and for the driest model there was a 78% decrease. Yates and Strzepek
(1998a) found declines up to 9% in the annual flow at HAD by 2060 for doubled CO2
for one model, but increasing precipitation for two other models for the same period
that resulted in about 40% increase in annual flow at HAD. Yates and Strzepek
(1998b) reanalyzed the results of their CO2 doubling scenarios, and found that five
of six GCMs showed increased streamflows at HAD for the 2060s (roughly the time
of CO2 doubling) with increases as much as 137% for one model. Only one GCM
showed a decline in annual flow at Aswan (−15%).
In summary, the multimodel approach we used shows some agreement with
previous studies to the extent that temperatures rise throughout the Nile basin in
all studies, which has a negative effect on streamflow. However, considerable uncertainty and disparity in spatial and temporal predictions of changes in precipitation
complicates the overall analysis of streamflow changes. To provide a sense of the
characteristics of the multimodel ensemble streamflow predictions, we summarize
our streamflow prediction results in Tables 11 and 12. These results show that for a
change in precipitation of +15 (+17)% associated with warming of +1.5 (+1.3)◦ C for
the period 2010–2039 for the A2 (B1) global emissions scenario from the historical
simulation, annual Nile flow at HAD will increase by +11 (14)%. However, for a
precipitation change of −7 (−4)% and warming of +4.4 (+3.6)◦ C for the period
2070–2099, mean annual Nile flow will decrease by −16 (−13)% for the A2 (B1)
global emissions scenario. Although we did not undertake an analysis of elasticity of
Nile River flows (the fractional change in flow per fractional change in precipitation)
Table 12 Multimodel High Aswan Dam hydropower production metrics (×103 GWH/year)
Scenario
Minimum
1st
quartile
Historical 9.66 × 103 GWH/year
A2 2010–39 4.7
7.5
A2 2040–69 3.7
8.2
A2 2070–99 3.1
6.5
B1 2010–39 4.8
8.1
B1 2040–69 4.3
8.8
B1 2070–99 2.3
6.8
Mean
3rd
quartile
Max
Percentage change relative
to historical annual hydropower
production (×103 GWH/year)
10.7
9.9
9.0
11.4
10.5
8.8
13.2
11.0
10.4
13.2
11.7
10.1
20.5
17.3
17.5
21.6
18.8
16.6
110.3% (1)
102.6% (0.25)
93.4% (−0.65)
117.6% (1.7)
108.2% (0.8)
91.6% (−0.84)
Climatic Change (2010) 100:433–461
455
(see e.g., Dooge et al. 1999), it is clear that the effect of the temperature increases
is to decrease the effective elasticity with respect to increasing precipitation, and to
increase it with respect to decreasing precipitation.
3.3 Implications of climate change to water resource management
Because water resources management is inextricably linked with climate, the
prospect of global climate change raises serious concerns as to the sustainability of
water resources and regional development (Riebsame et al. 1995). Efforts to provide
adequate water resources in the Nile River basin will be challenged over the next
century by the pressures of increasing population and resulting land use change,
and with potential hydroecological consequences. Changes in climate and climate
variability (which results in droughts and flooding) will inevitably complicate water
resources management in the Nile basin. According to the IPCC (1998), the Nile
River experienced reductions in runoff of 20% between 1972 and 1987, which lead
to significant interruptions in hydropower generation. A 1995 study by Riebsame
et al. (1995) also concluded that among the several major rivers studied, the Nile
was the most susceptible to climate change in terms of its potential for hydropower
production.
To identify the nature of interactions between climate change and the managed
water resource system, we used a simple reservoir operations model which had
the objective of meeting target hydropower and irrigation releases at HAD. We
term this model the Lake Nasser Reservoir Model (LNRM). LNRM is a simulation
model which represents the major physical water management structures, reservoir
operation rule curves and water use policies of the Nile system. In constructing
LNRM, we made two assumptions. First, we based operation of HAD on the
provisions of the 1959 treaty between Sudan and Egypt, a treaty that was not
agreed to or recognized by other riparian countries (including Ethiopia, which is the
headwater source for more than 86% of the Nile’s water). The treaty awarded Sudan
25% (18.5 BCM) of the mean annual naturalized Nile flow at HAD of 84 BCM and
75% (55.5 BCM) to Egypt with any flow in excess of the mean annual flow of 84 BCM
to be shared equally between Egypt and Sudan (Said 1993; Johnson and Curtis 1994).
The calculation includes ten BCM which is estimated to be the annual evaporation
loss from Lake Nasser.
The second assumption is based on an assessment of flow and hydropower impacts
of two development scenarios in the Blue Nile Basin by the Nile Decision Support
System (DSS) of Georgakakos (2004) which was based on an assumption of climate
stationarity. The first scenario in the DSS was the current and existing conditions
of river flow and energy production whereas the second scenario was based on
development of four major hydropower plants (progressive hydropower development in Ethiopia). The study concluded that this development will not negatively
impact downstream hydropower production; therefore we have not included future
upstream development in the Blue Nile basin in LNRM. Furthermore, Sudan’s
abstractions are assumed to be similar to those required to meet historical demand
even though completion of Merowe Dam in Sudan will affect evaporation losses.
LNRM represents: (1) Lake Nasser reservoir and HAD characteristics, (2) simulated
river flows (reservoir inflows), (3) existing installed hydropower facilities, (4) water
use policies, and (5) reservoir operation rules. All the sequences of data flow are
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Climatic Change (2010) 100:433–461
linked using flow network nodes, and represent locations of local inflow and/or water
withdrawals and returns.
LNRM is driven by naturalized streamflow simulated using the VIC hydrologic
model. The system basically models Sudan’s complex water management system
upstream of Lake Nasser as a single, lumped withdrawal upstream of the inflow to
Lake Nasser. LNRM calculates evaporative losses from the lake surface based on
reservoir surface area which is derived as a nonlinear function of head and reservoir
storage. Hydropower production and irrigation water release are modelled as a
function of inflow, minimum and maximum release constraints, reservoir elevation,
tailwater elevation, turbine efficiency, and reservoir storage.
The hundred-year time series of monthly inflow records associated with each
GCM represents the dynamic supply to the reservoir, with the initial storage in
Lake Nasser was set to its 1999 value of 162.5 BCM (reservoir elevation 182.1 m).
The reservoir storage is linked to converters that describe the relationships resulting
from the particular state of the storage. They produce reservoir elevation, power
generation, and spill. Required release from the reservoir is linked to the set of
converters and together they describe the water release requirements from the
reservoir for irrigation water supply. To make the LNRM simulation realistic, the
irrigation water demand was assumed to be supply driven and dynamic in nature,
which allows future agricultural sector expansion, with mandated 5%, 10% and 15%
annual average increases in irrigation water demand for Periods I–III, respectively.
The model also allows for cutbacks in the demand by percentages which are designed
to overcome water shortages.
Monthly streamflows produced by forcing VIC with bias corrected and downscaled output from each GCM were translated first into time series that account
for upstream monthly withdrawals. The monthly withdrawal associated with each
climate model’s streamflow sequence was subtracted as a lumped single withdrawal
prior to running LNRM. This approach was also used by Strzepek et al. (1995).
LNRM system objectives include meeting water supply targets and avoiding water
shortages (for irrigation), avoiding excessive spills and generating as much firm and
average energy as possible.
Figure 8 shows a wide spread in the multimodel distribution of annual hydropower
production at HAD for the A2 and B1 global emission scenarios. The multimodel
average hydropower production is summarized in Table 11. Much of the average
mandated power requirement is satisfied in period I in the multimodel average, however predicted hydropower generation fails to meet the annual average hydropower
production targets for Periods II and III in the multimodel averages, mainly due
to inflow reductions to HAD. This is a significant issue, since the historical annual
average hydropower generated at HAD represents 10,000 GWH, or 20% of total
power generated within Egypt. The predicted multimodel annual average power
production at HAD generally follows changes in streamflow, increasing early in the
century to mid century with ensemble mean annual average percentage increases of
10 (18), and 3 (8) for periods I and II and percentage decreases of 7 (8) by period III
for A2 (B1) global emissions scenarios (Table 12). In summary, the results indicate
that in the multimodel average, Egypt will maintain its historical annual hydropower
production of 10,000 GWH from HAD hydropower through Periods I and II, but by
period III hydropower production will be reduced to 93 (92)% of its current climate
mean annual production for A2 (B1) emissions scenario.
Climatic Change (2010) 100:433–461
457
Fig. 8 Projected multi-model
ensemble average hydropower
production at HAD for the
base (historical) period and
three future periods, period I
(2010–2039), period II
(2040–2069) and period III
(2070–2099) for A2 and B1
global emission scenarios
The irrigation release results (Table 13) indicate that, averaged over the GCM
ensembles, Egypt will satisfy its current climate irrigation water requirement with
an additional 5% presumed irrigation water demand increase during Period I. In
addition to the increased additional irrigable land, spills account for 4 BCM/yr
through Toshika to the west, which might be a potential source of irrigation water
if properly utilized. The predicted multimodel mean annual irrigation water releases
for the three periods and two global emission scenarios A2 (B1) are 59 (60), 48
(49) and 48 (47) BCM, as compared with the historical mean annual release of
55.4 BCM (Table 13). These results suggest that irrigation water releases will be
much more affected by future climate in Periods II and III than is hydropower
generation. The results indicate that Egypt will experience a reduction of 7 BCM
(roughly equivalent to 457,000 ha of irrigable land) by the end of 21st century. The
nonlinearity in the irrigation water and hydropower production tradeoffs is mainly
Table 13 Multimodel long term average monthly irrigation releases from High Aswan Dam (BCM)
for historical 1950–1999 and three future periods
Month
Historical
A2_2010–
2039
A2_2040–
2069
A2_2070–
2099
B1_2010–
2039
B1_2040–
2069
B1_2070–
2099
Jan
Feb
Mar
Apr
May
June
July
Aug
Sep
Oct
Nov
Dec
Annual
3.50
4.00
4.20
4.00
5.30
6.50
7.00
6.30
4.30
3.70
3.60
3.00
55.40
3.71
4.24
4.45
4.24
5.62
6.89
7.42
6.68
4.56
3.92
3.82
3.18
58.72
3.06
3.49
3.67
3.49
4.63
5.67
6.11
5.50
3.75
3.23
3.14
2.62
48.36
3.01
3.44
3.61
3.44
4.56
5.59
6.02
5.42
3.70
3.18
3.10
2.58
47.64
3.82
4.36
4.58
4.36
5.78
7.09
7.63
6.87
4.69
4.03
3.92
3.27
60.39
3.12
3.56
3.74
3.56
4.72
5.79
6.23
5.61
3.83
3.29
3.20
2.67
49.31
2.94
3.36
3.53
3.36
4.45
5.46
5.88
5.29
3.61
3.11
3.02
2.52
46.54
458
Climatic Change (2010) 100:433–461
due to the fact that hydropower production and irrigation water releases are partially
competing at HAD, and lower inflows are magnified in hydropower production,
which is dependent on both water level and reservoir inflows. Given the potential
population growth of the region, the results suggest that reduced water supply will
pose a critical problem for Egypt by the late 21st century.
4 Conclusions
For the entire Nile basin and its two major sub-basins (Blue Nile and Lake Victoria
region), the simulated hydrologic impacts of future climate projected by 11 GCMs
forced under two SRES emissions scenarios were examined, as were their implications for Nile River water management. Based on A2 and B1 emissions scenarios and
from the 11 GCMs projections, temperature changes for the entire Nile and the two
major two sub-basins are expected to be warmer for the entire 21st century. Warming
is expected to be modest across the basin early in 21st century (2010–2039) with
average annual temperature projections by A2 and B1 emission scenarios similar.
By the mid and late 21st century, temperatures are warmer for A2 emission than for
B1 emissions scenario. Averaged over the entire Nile basin and all GCMs, average
annual temperature for the period 2070–2099 will increase by 4.4 ± 0.5◦ C for A2 and
3.6 ± 0.4◦ C for B1 global emissions scenario relative to the historical (1950–1999)
average annual temperature.
In general, in the multimodel averages, precipitation increases early in the century
and declines late in the 21st Century over most of the basin, however inter-model
variations are high. In the multimodel average, the models projects increases in
precipitation in the winter (DJF) season, whereas JJA precipitation changes are
mixed for the two source sub-basins.
There is much less agreement among the models as to the magnitude, and even
direction and seasonal changes in precipitation, and subsequently streamflow. In
the multimodel average, annual average Nile River inflow to HAD is projected
to increase by 11 (14)% in Period 1, but decrease by 8 (7) and 16 (13)% for A2
(B1) global emissions scenarios, relative to 1950–1999 annual average historical
flows. In the ensemble means, runoff declines for periods II and III for both global
emissions scenarios, with the greatest changes occurring in period III for the A2
global emissions scenario.
Reservoir simulations showed that annual average energy production will remain
relatively unaffected by climate change early in the 21st century (2010–2039). However, in the multimodel average, gradual reductions in hydropower production will
occur by mid and late 21st Century with annual hydropower production ranging from
−50 to 110% and −70 to 75% for the A2 emissions scenario, and −55 to 120%
and −60 to 80% for the B1 emissions scenario for periods I and III respectively,
relative to the historical simulation. The agricultural sector in general will experience
increasing shortfalls in releases from Lake Nasser by mid to late century.
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