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Hydrologic Impacts of Climate Change on the Nile River Basin: Implications of the 2007 IPCC Climate Scenarios Tazebe Beyene1, Dennis P. Lettenmaier1 and Pavel Kabat2 Abstract The potential impacts of climate change on the hydrology and water resources of the Nile River basin are assessed using a macroscale hydrology model driven by 21st century simulations of temperature and precipitation downscaled from runs of 11 General Circulation Models (GCMs) and two global emissions scenarios (A2 and B1) archived for the 2007 IPCC report. The results show that, averaged across the multimodel ensembles, the entire Nile basin will experience increases in precipitation early in the century (period I, 2010-2039), followed by decreases later in the century (periods II, 2040-2069 and III, 2070-2099) with the exception of the eastern-most Ethiopian highlands which is expected to experience increases in summer precipitation by 2080-2100. Summarized as spatial averages over the entire Nile basin, multimodel-average Nile basin precipitation changes as percentages of the historical period 1950-99 are 115 (117), 98 (104) and 93 (96), and temperature changes (as differences in ºC from 1950-99) are 1.5 (1.3), 3.2 (2.8) and 4.4 (3.6) for the global A2 (B1) emissions scenario. These changes in precipitation and temperature resulted in streamflows at High Aswan Dam (HAD) that are 111 (114), 92 (93), and 84 (87) percent of historical simulated streamflow (1950-1999) for periods I to III, respectively, for the global A2 (B1) emissions scenario. Implications of climate change on the water resources of the Nile River basin were analyzed by quantifying the annual hydropower production and irrigation water releases at High Aswan Dam, which generally would follow changes in streamflow, increasing early in the century to 112 (118) percent, but then decreasing to 92 (97) and 87 (91) percent in Periods I and III, respectively, for the A2 (B1) emissions scenario. 1 Department of Civil and Environmental Engineering Box 352700, University of Washington, Seattle WA 98195 2 ALTERRA Green World Research, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands 1.0 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 all these climates exhibit differing degrees of temporal and spatial variability. At the sub-regional scale, Africa is vulnerable to ENSO and related extreme events (drought, floods, and changes in hydrologic patterns). That 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 increasingly difficult to cope with in the face of increasing pressures on water supplies due to rapid population growth and dwindling resources. The Nile River basin is home to 336 million of Africa’s 850 million people. It has experienced high population growth rates and the population of the basin is expected to double between 1995 and 2025. Virtually all population projections are for continuing growth, which in turn will increase demand for natural resources among the 10 Nile River riparian countries. The potential effects of climate change on the basin have been given less attention than population growth, notwithstanding several earlier studies (e.g. Yates et al., 1998) showing that the water resources of the basin are susceptible to climate change. The IPCC Fourth Assessment Report (AR4) has resulted in a wealth of General Circulation Model (GCM) runs that have been archived in a consistent manner at the Lawrence Livermore National Laboratory Program for Climate Model Diagnosis and Intercomparison (PCMDI). These model runs 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 et al (2006) evaluated implications of projected 21st century climate for California’s water resources using PCMDI-archived output from 9 IPCC/AR4 GCMs, and Christensen and Lettenmaier (2007) evaluated implications of IPCC/AR4 climate projections for Colorado River water resources from 11 GCMs and two global emissions scenarios archived at 2 PCMDI. 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 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 et al., 1993, Yates et al., 1998). Water resource planning based on the concept of a stationary climate is increasingly considered inadequate for sustainable water resources management (Mohamed et al., 2005). In addition to natural variability, which is incorporated in existing water planning methods, new water projects will have to deal with uncertainty associated with population growth and trends in climate change. Therefore, understanding the uncertainty in projected climate change over the next century, which is attributable both to uncertainty in the future emissions pathway (related to policy decisions and public response) and uncertainties in model projections (due to differing sensitivities of the GCMs to perturbations in atmospheric composition), is essential to understanding how the economy of the Nile basin will evolve, including social and environmental impacts. Water resources planning studies which typically are conducted for time horizons of several decades now require consideration of ongoing global climate change and uncertainties in the signature of future climate change. The near certainty of increased future water demand in the Nile basin (notwithstanding uncertainty as to magnitude of demand increases) contrasts with the uncertainty of climatically-induced changes in the water supply of the Nile River basin (Conway et al., 1996, Yates et al., 1998(a), Strzepek et al., 1995, Strzepek et al., 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 basin has been the focus of several previous studies of climate change using different climate models and techniques. Yates et al., (1998a; b) found that several climate change scenarios implied that 3 agriculture would be negatively affected by climate change despite increased water availability and only moderate yield declines, as a result of climate change 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 [2000] used a dry and wet scenario analysis of possible future conditions and found that under wet climate scenarios, surplus water beyond 75 BCM (109 cubic meter) remained unused whereas for drier scenarios (below 75 BCM), water was a constraint to agricultural production into the 21st century, the result of which was that resources were diverted to less water demanding crops and the livestock and non-agricultural sectors. Tate et al., (2004) analyzed the sensitivity of the water balance of Lake Victoria to climate change using HadCM3 A2a and B2 emission scenarios, and indicated 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 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 as follows. 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, all of which included at least one 100-year ensemble member, and two SRES (Scientific Report on Emission Scenarios) emissions scenarios (A2, corresponding roughly to unconstrained growth in emissions, and B1, corresponding to elimination of global emissions 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 4 (most of which run at a spatial resolution of two to four degrees latitude-longitude) and the spatial scale of our hydrologic model (which was applied at a 0.5 x 0.5 degree 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). 2.0 Approach 2.1 Study Area The Nile is the longest international river system in the world. It flows some 6700 km through ten countries before reaching the Mediterranean Sea. Its headwaters are in Lake Victoria at about 4º S latitude, and it flows mostly northward to its mouth at 32º N latitude (see Figure 2(a)). It has a drainage area of about 3.35 million km2, which covers 10% of the African continent, roughly equivalent to half the area of the continental United States. Egypt and the Sudan are the two major users of this river, while Ethiopia is the primary contributor to the bulk of runoff. This imbalance in the primary producers and consumers of the basin’s water resources has lead Swain (1977) 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) account for 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 5 elevation. Precipitation is virtually zero in the Sahara desert, and increases southward to about 1200–1600 mm/yr 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 driven by monsoon precipitation. The Blue Nile contributes about sixty percent of the total flow of the Nile, whereas the Baro-Akobo (Sobat), and Tekezze (Atbara) contribute slightly less than fifteen percent 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 (with 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, the Rosetta branch to the west and the Darneita to the east. 2.2 General Circulation Models (GCMs) 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 emission scenarios ranked from warmest to coolest in terms of global average emissions at mid-century are A1FI, A2, A1B, B2, A1T and B1. Global emission scenarios A2 and B1 were chosen for this study because they are the most widely simulated global emission scenarios in all models. Emissions scenario A2,which is based on the assumption that future economic and population growth will not be constrained and that there will be no future limitations on global emissions. The A2 global emission scenario projects global average CO2 concentrations will reach 850 ppm by 2100. Scenario B1, on the other hand, assumes 6 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 mid-century and reach 550 ppm by 2100. 2.3 Bias Corrections and Spatial Downscaling (BCSD) Despite continuing improvement in their physical representations of the climate system, there remains a substantial scale mismatch between GCMs and most hydrologic models. Furthermore, while GCMs have a computation time scale that is typically less than one hour, the physical realism at such short time steps is questionable, and the data volumes (realizing that GCM output is archived globally) are considerable. As a practical matter, most studies like this one use monthly aggregates of the GCM predictions, and therefore a temporal disaggregation to the hydrologic model time step (daily in this study) is required. The problem goes beyond computation, however; issues of bias are critical for hydrologic applications, and even at the native spatial resolution of GCMs and monthly time intervals, climate models are inherently biased. A number of downscaling and bias correction strategies have been suggested to solve this problem (e.g., Wood et al., 2002, Wilby et al., 2000, Wetterhall et al., 2005a among others). As shown by Wood et al (2004), none of the current generations of GCMs are immune to the bias problem, nor are higher resolution regional climate models. For this study we used the bias correction and spatial downscaling (BCSD) method developed by Wood et al. (2002). The method was initially developed for streamflow forecasting and later was modified for climate change studies by Wood et al. (2004). It is a statistical approach which uses empirical percentile-percentile mapping as its main element; the reader is referred to Wood et al. (2002) and Wood et al. (2004) for further details. The method has previously been used in several climate change studies, including Payne et al. (2004), Christensen et al. (2004), Maurer et 7 al. (2007), Christensen and Lettenmaier (2007) and Hayhoe et al (2007). In brief, the method downscales monthly temperature and precipitation at the GCM spatial scale (we regridded the climate variables to a common 2 degrees latitude by longitude spatial resolution to the one-half degree spatial resolution at which the VIC hydrology model was applied through use of a probability mapping procedure which utilizes the climatology of both observations (gridded to a one-half degree spatial resolution) and the model(s). For bias removal, empirical transformations via percentile-percentile mapping were constructed from the GCM climatology to the observed monthly climatology for both Tavg (monthly average temperature) and Ptot (monthly total precipitation). For Tavg, the linear trend is removed prior to bias correction and is re-imposed afterward, so as to avoid distortion of the tails of the probability distribution of temperature as temperatures rise. The observed climatology for the historical run (1950-1999) was derived from the global gridded precipitation data set described by Adam and Lettenmaier (2003).Sub-grid spatial variability was represented by spatially disaggregating bias-corrected, GCM-scale forcings to the one-half degree spatial resolution, following which the monthly time series of the one-half degree bias-corrected scenarios were temporally disaggregated to daily through use of a resampling procedure. The bias corrected and spatially and temporally downscaled climate variables were then used to force our VIC (Variable Infiltration Capacity) land surface hydrologic model. 2.4 VIC land surface hydrologic model The VIC land surface hydrologic model of Liang et al. (1994; 1996) was implemented at ½ degree (~48km) spatial resolution and 3-hourly temporal resolution in energy balance mode , in which the model runs at 3hourly time step and iterates for surface temperature rather than setting surface temperature equal to air temperature. VIC is a semi-distributed grid-based land surface 8 hydrologic model which parameterizes the dominant hydrometeorological processes taking place at the land surface-atmosphere interface. 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 basin outlet (tributary or main stem) channels (see Figure 2(b) for channel routing network and gauging stations). A mosaic representation of land cover, and sub-grid parameterizations for infiltration and the spatial variability of precipitation and temperature, account for sub-grid scale 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 gauging locations, the Blue Nile at Eldiem, the main stem at Dongola, and the main stem at HAD. A calibration procedure similar to that described in Nijssen et al. (1997) was followed to assure a match between model-simulated and observed flows for the period in which historic streamflow observations were available. A validation result of Nile river flow for two gauging stations is shown in Figure 1. 3.0 Results and discussions In the following section we summarize our analysis of the results from downscaled and bias corrected GCM climate models and the selected global emission scenarios. The bias corrected and spatially-downscaled hydrologic drivers (temperature and precipitation) of future climate (20002100) are compared to 1950–1999 gridded historical observations. We further analyzed and compared derived hydrologic variables (runoff, SWE, evaporation) simulated by VIC for the GCM scenarios to VIC simulations driven by the 1950–1999 climate observations. These climate change results derived from both global emission scenarios are segregated into three time horizons, period I (2010–2039), period II (2040–2069), and period III (2070–2099). Hydrologic response of the 9 basin to the changing climate is analyzed by quantifying future streamflow changes at selected gauging stations and implication of these streamflow changes are further evaluated using reservoir operation model targeting future hydropower production and irrigation water release for agriculture at HAD (High Aswan Dam). 3.1 Temperature and precipitation changes Figures3 (a–c)show the downscaled and bias-corrected long-term multimodel average precipitation, temperature and simulated hydrologic parameters (evapotranspiration, runoff, and soil moisture). The downscaled and bias-corrected temperature and precipitation (and other derived model forcings, following methods outlined in Maurer [2007]) time series from each ensemble climate model were used to force the VIC model for both A2 and B1 emission scenarios. The 1950 – 1999 historical data were used as a baseline reference for evaluating predicted changes. Because the sub-basins of the Nile have different physical and hydroclimatological characteristics, we evaluated results 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. The results presented in Figures 3(a-c) include long-term changes in simulated runoff, evapotranspiration, and soil moisture Projected temperature changes across climate models early in the century (period I) are somewhat consistent and mostly are in the range of 1 to 1.5 ºC warmer than the historical (19501999) average. The temperature results tend to diverge through the century from period II to period III, with an increasing trend in all models. As expected, Scenario A2 is generally warmer than Scenario B1.For the entire Nile basin multimodel average temperature increased by 1.5 (1.3), 3.2 (2.8) and 4.4 (3.6) ºC relative to the historical (1950-1999) mean for the A2 (B1) global emission scenarios (Table 4). The ensemble spread as measured by the inner quartile distance tend to diverge from period I to period III with inner-quartile ranges (1st, 3rd) of (1.4, 1.7), (3.4, 3.8) and (4.4, 4.9) 10 for Scenario A2 and (1.1, 1.3), (2.6, 3.0) and (3.5, 3.9) for scenario B1 for periods I to III respectively (Figure 4(a-c)). Signatures of temperature projections within the Blue Nile and Lake Victoria regions are different, but both have consistent positive trends. Projected multimodel temperature increases in the Lake Victoria region are 1.1 (1.0), 2.5 (1.9) and 3.4 (2.9) ºC relative to the 1950-1999 historical average with inner-quartile ranges of (1, 1.2), (2.2, 2.8) and (3.4, 4.0) for emissions scenario A2 and (0.9, 1.1), (1.7, 2.0) and (2.7, 3.2) for scenario B1 for the three periods respectively. The corresponding predictions of mean temperature changes for the Blue Nile subbasin are 1.2 (1.2), 3.1 (2.6), and 4.1 (3.4) ºC for A2 (B1) emission scenarios. The pattern of ensemble spread is similar to that for the Lake Victoria region (Figure 4). In general, the downstream part of the Nile basin is expected to experience more warming than the headwater subbasins. Changes in precipitation are generally reflected in the annual runoff volumes more than in the seasonal shape of the hydrographs (Lettenmaier et al., 1999) and there is much less consistency between climate model projections of precipitation changes than for temperature. In the multimodel ensemble average, precipitation increases over the entire basin for the period 2010-2039, however, by 2070-2099, precipitation decreases substantially. The IPCC 3rd assessment report (IPCC 2001) concluded that Nile basin will experience decreases in precipitation ranging between zero and forty percent by the end of the 21st century, a result which was based on nine GCMs. Similar conclusions are also inferred from the IPCC 4th Assessment Report on African climate change (IPCC 2007) which found that temperatures will increase by up to 5.8 ºC by the end of the century in arid or semi-arid areas that are prevalent in Africa. The report also added that sometime between 2080 and the end of the century, average annual precipitation is very likely to decrease along Africa’s Mediterranean coast by a fifth with declines also expected in the northern Sahara and the northern west African coast. Declines are also predicted for much of southern Africa with the extreme west of the region likely to experience falls by as much as forty percent through June and August. In 11 contrast, tropical and eastern Africa may experience increased rainfall of seven percent (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 (IPCC 2001). In the remainder of this paper, we more formally analyze these results from multiple models through computation of multimodel ensemble averages. Despite the variations in individual climate model predictions, over the entire Nile basin 8 (9) and 3 (6) of the 11 GCMs for the A2 (B1) global emission scenario predicted increases in precipitation for 2010-2039 and 2070-2099, respectively (Tables 2 and 3). Multimodel average annual Nile basin precipitation changes in percentages of historical (1950-1999) precipitation are 115 (117), 98 (104) and 93 (96) for the A2 (B1) emissions scenario with observed spread among ensemble member prediction expressed as inner-quartile range (1st,3rd) for A2 emission scenario of (-2, 26),(-12, 12) and (-20, 3. The inner-quartile ranges for scenario B1 are (5, 30),(-5, 15) and (-10, 6). The multimodel ensemble average annual precipitation changes for the Blue Nile sub-basin expressed as a percentage of 1950-99 precipitation are 115 (117), 98 (104) and 106 (96) for the A2 (B1) global emission scenario and periods I to III, respectively. The changes for the Lake Victoria sub-basin are 117 (123), 98 (105) and 90 (97) relative to the historical average (1950-1999). Spatial variations in these changes over the Blue Nile sub-basin are noticeable, with most of the increases occurring in the Atbara and Upper Blue Nile (Figure 5 (a-c)). A relatively similar spread pattern is depicted within the sub-basins as for the entire Nile basin; the inner-quartile ranges are shown in Figure 4 (d–f) for precipitation changes. Tables 2 (a-c) and 3 (a-c) summarize the annual average changes in precipitation and temperature for the entire Nile basin and the two sub-basins. We evaluate the end points in precipitation projections among the 11 GCMs used in this study. The GISS (Goddard Institute for Space Studies) and GFDL (Geophysical Fluid Dynamics Laboratory) climate models represent the end points of the range of precipitation predictions. GISS is the wettest (precipitation increases 12 ranging between 40-58%) whereas the GFDL is the driest with predicted decreases in precipitation of up to 34% for the period 2070-2100. The corresponding projected 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. We also analyzed seasonal precipitation changes for the wet (JJA) and dry (DJF) seasons. As shown in Figures 5 (a-d) and summarized in Table 5, strong increases in both winter and summer precipitation are predicted in the ensemble mean across the Nile basin particularly for period I, although the magnitude and spatial patterns vary by sub-basin mainly due to the spatial heterogeneity and hydroclimatic variations associated with general circulation and teleconnections. Dominant JJA precipitation increases are predicted for the Blue Nile basin, mainly the Upper Blue Nile. This might be associated with increased monsoon intensity in the Ethiopian highlands, which is particularly important for runoff generation given that under current climate the Nile River at El Diem receives more than 70% of its annual flow during the summer season from the Ethiopian highlands (Mishrah et al., 2005). This implies in turn that increases in summer precipitation in this part of the basin will result in substantial increases in the Nile River flow at HAD. 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 2 shows the projected changes in Nile River flow at the main stem Nile gauging station at HAD and the Blue Nile flow at El diem (located upstream from the Roseires Reservoir in Sudan; see Figures 1a and b) predicted using the methods summarized in Section 2. 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 of the changes differ substantially from GCM to GCM. 13 Figures 6(a-b) and 6 (c-d) show changes in predicted long-term mean monthly Nile flow at HAD and Blue Nile flow at El diem, respectively, for periods I and III for global emissions scenario A2. Using the multimodel approach, the ensemble mean predicted annual streamflow for Periods I-III for the main stem Nile at HAD are 111 (114), 92 (93) and 84 (87) as percentages of historical (1950-1999) streamflow with corresponding multimodel spread expressed as innerquartile (1st, 3rd) ranges of (-2, 23),(-16, 5) and (-28, -5) for the three periods, respectively. The same numbers for Blue Nile at El diem are 118 (120), 97 (99) and 93 (101) (see also Tables 6 and 7) with associated spread of (6, 31), (-14, 6) and (-21, 0) for the A2 global emissions scenario and Periods I-III, respectively. Similar to temperature and precipitation, we evaluated the end points. GISS predictions for Blue Nile mean annual flow at El diem for the A2 (B1) global emission scenarios are 148 (154), 133 (134), and 126 (125); whereas the GFDL predictions are 83 (86), 77 (75) and 71 (70). Similarly, Nile streamflow at HAD is predicted to change to 134 (136), 126 (127) and 112 (115) percent of the 1950-99 mean for GISS, and 77 (92), 71 (85) and 62 (75) percent by GFDL for the A2 (B1) global emission scenarios and periods I-III, respectively. These scenarios suggest major changes in the current hydrologic characteristics of the Nile basin. Early in the century, multimodel average annual flows exceed the historical (1950-1999) long-term average of 88 BCM at HAD; with 7 (7) GCMs in period I exceeding the 1950-99 average, whereas only 3 (4) of the models suggest increases in period III for the A2(B1) global emissions scenario. Similarly, 9 (8) models predict increases in Blue Nile flow at El diem early in the century (period I ), and 6 (5) for the A2 (B1) global emissions scenario in period III. The inter model variation substantially differs as we go from period I to III for both emissions scenarios with consistent negative trends in the longterm average streamflow. tThese spreads are presented in Figure 4 (g-h). 14 Previous studies of the impact of climate change on Nile River flow have been confounded by inconsistencies in emissions scenarios and other aspects of the model simulations and partially for that reason have produced widely divergent results. Although there is considerable divergence among ensembles (as well as models) in our results, there is nonetheless some general consistency. Furthermore, even though other recent studies differ in the emissions scenarios used and other aspects of the model simulations, there is some qualitative agreement between the results of these studies and ours. For instance, Arnell's (1999) study suggested that precipitation in the Nile basin would increase by about 10% by 2050, but he suggested 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 obtained a range of –9% to +12% in changes in mean annual Nile flows at HAD for 2025. Strzepek et al. (1995) assessed the impact of climate change using three GCMs (UKMO, GFDL and GISS) with doubled global atmospheric concentrations (2xCO2) to predict Nile flow changes at HAD for 2060. In their results, GISS was the wettest model and had a 30% increase in annual streamflow; whereas for UKMO, there was a 12% decrease; and for the driest model GFDL, there was a 78% decrease. Yates et al. (1998a) found declines up to -9% in the annual flow at HAD by 2060 for doubled CO2, but they found increases for the GISSA and UKMO models for the same period which produced about 40% increase in annual flow at HAD. Yates et al. (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 for CO2 doubling) with increases as much as 137% for GISS. Only one GCM (GFDL) showed a decline in annual flow at Aswan (-15%) relative to the long-term average Nile flow. 15 In summary, the multimodel approach we used showed general agreement with the previous studies in that temperatures will rise throughout the Nile basin, but there is considerable uncertainty and disparity in spatial and temporal predictions of changes in precipitation as to both magnitude and direction. This makes the analysis of implications of these changes for streamflow more complicated and uncertain. To provide a sense of the characteristics of the multimodel ensemble streamflow predictions, we summarize our streamflow prediction results in Tables 7 and 8. Theses results show that for a change in precipitation of +15 (+17)% associated with warming of +1.5 (+1.3) ºC for the period 2010-2039 for the A2 (B1) global emissions scenario, annual Nile flow at HAD will change by +11 (14)%. However, for a precipitation change of -7 (-4)% and warming of +4.4 (+3.6) ºC for the period 2070-2099, mean annual Nile flow will experience changes on the order of -16 (-13)% for the A2 (B1) global emissions scenario. Clearly the underlying assumptions of the global emissions scenarios are manifested in the hydrologic response of the river system; the global emissions scenario A2 seems to be the most realistic given the fact that the Nile river basin economic development and population growth will change greatly over the next century. 3.3 Implications of climate change to water resource management of the Nile River Since water resources are inextricably linked with climate, the prospect of global climate change raises serious concerns as to implications for water resources and regional development (Riebsame et al., 1995). Efforts to provide adequate water resources in the Nile rive basin will confront several challenges over the next century, including population pressure and resulting land use changes, with potential hydroecological consequences. Climate change and climate variability (which results in droughts and flooding) will make addressing the pressing issue of water resources management in the Nile basin more complex. According to the IPCC (1998), the Nile River experienced reductions in runoff of 20% between 1972 and 1987, which leads to significant 16 interruptions in hydropower generation. A 1995 study by Reibsame 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 the 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 High Aswan Dam (HAD). We term this model the Lake Nasser Reservoir Model (LNRM). LNRM is a simulation model which includes and represents the major physical water management structures, reservoir operation rule curves and water use policies of the HAD system. In constructing LNRM, we made two assumptions. First we based operation of the HAD system 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 10 BCM which is estimated to be the annual evaporation loss from the Sudd Swamps and reservoirs within the system. 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). 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 scenario), thus we have not included future upstream development in our modelling approach. Georgakakos’ analysis was based on the assumption of climate stationarity. LNRM includes data for: (1) Lake Nasser reservoir and HAD characteristics, (2) simulated river flows (reservoir inflows), (3) existing 17 installed hydropower facility, (4) water use policies, and (5) reservoir operation rules. All the sequences of data flow are 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 our VIC land surface 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 loss from the lake surface based on reservoir surface area which is derived as a nonlinear function of head and reservoir storage, and models hydropower production and irrigation water release 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, in which the initial storage in Lake Nasser was set to its actual 1999 value of 162.5 BCM (reservoir elevation 182.1 m). The reservoir storage is linked to numerous converters used to describe the relationships resulting from the particular state of the storage. They produce reservoir elevation, power generation, spill, and evaporation losses. 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. The monthly streamflows associated with each GCM were translated first into a time series that accounts for upstream monthly withdrawals. The monthly withdrawal associated with each climate model’s streamflow sequence was subtracted as lumped single withdrawal prior to running LNRM. Such an approach was also used by Strzepek et al. (1996). LNRM system objectives 18 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 7 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 7. Much of the average mandated power requirement is satisfied in period I, however predicted hydropower generation fails to meet the annual average hydropower production targets for Periods II and III, mainly due to inflow reductions to HAD. This is a significant issue, since the historical annual average hydropower generated at HAD represents 1000 GWH, or 20% of total power generated within Egypt. The multimodel annual average power production at HAD generally follows changes in streamflow, increasing early in the century to 112 (118) percent of historical production for the period I A2 (B1) emissions scenario in the multimodel ensemble, but then decreasing to 92 (97) and 87 (91) percent of the historical mean for Periods II and III, respectively. In summary, the results indicate that Egypt would maintain its historical annual hydropower production through Period I, covering 23% (11500 GWH/yr) of its total energy production within the country, but will be limited to generating 18% (9000 GWH/yr) of its annual energy production by period III. The irrigation water release results (Table 9) indicate that, averaged annually, Egypt will satisfy its irrigation water requirement during Periods I with well above the historical irrigation water supply, and will be able to meet the 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. In general, the multimodel ensemble mean annual irrigation water release for the three periods and two global emission scenarios A2 (B1) are 59 (60), 48 (49) and 48 (47) BCM, compared to the historical release of 55.4 BCM (Table 9). 19 Irrigation water releases are not as affected by future climate in Periods II and III as compared with hydropower generation, but nonetheless in periods II and III Egypt will suffer from a reduction of 7 BCM (roughly equivalent to 457,000 ha of irrigable land). The nonlinearity in the irrigation water and hydropower production tradeoffs is mainly 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. 4.0 Conclusions Temperature predictions for all GCMs considered show increases throughout the 21st century, but the signature varies substantially from sub-basin to sub-basin and from GCM to GCM. In the multimodel average over the entire Nile basin, warming increases to more than 3.5 ºC relative to the historical (1950-1999) average by the end of Period III. Inner quartile ranges for the A2 emission scenario are (1.0, 1.2), (2.2, 2.8) and (3.4, 4.0) and for the B1 emission scenario are (0.9, 1.1), (1.7, 2.0) and (2.7, 3.2) for the three periods respectively. The multimodel average precipitation (as percentages of the 1950-1999 mean for the A2 (B1) emission scenario) are 115 (117), 98 (104) and 106 (96) with associated inner quartile ranges of (-2, 26), (-12, 12) and (-20, 3). For scenario B1 the inner-quartile ranges are (5, 30), (-5, 15) and (-10, 6). Similar analysis is made for the two main sub-basins and presented as boxplots in Figure 4. In general, the inner quartile ranges become narrower from period I through period III, however the spatial variations from subbasin to sub-basin persist. In general, winter (DJF) precipitation increases are predicted (in the multimodel mean) for equatorial Africa (Lake Victoria) early in the 21st century, and summer (JJA) precipitation increases are predicted for eastern Africa (Blue Nile region) throughout the 21st century. The timing and magnitude of changes in temperature and precipitation are critical to the hydrologic response of the Nile basin. The Nile River is expected to experience increases in 20 streamflow early in the century at both gauging stations studied, the Blue Nile at El diem and the main stem Nile at HAD, mostly due to increased precipitation. Subsequently, streamflow is expected to decline during periods II and III as a result of both precipitation declines and enhanced evapotranspiration due to increased temperature. The predicted multimodel mean streamflow at HAD (High Aswan Dam) are 111 (114), 92 (93) and 84 (87) as percentages of the historical (19501999) period for the A2 (B1) emissions scenario with corresponding inner-quartile ranges of (-2, 23), (-16, 5) and (-28, -5) for A2 emissions and (5, 26), (-13, 4) and (-28, -5) for B1 global emissions scenario and periods I-III, respectively. The corresponding numbers for the Blue Nile at El diem are 118 (120), 97 (99) and 93 (101) for the A2 (B1) global emission scenario with associated inner-quartile ranges of (6, 31),(-14, 6) and (-21, 0) for A2 and (9, 27), (-14, 6) and (-7, 8.5) for the B1 global emission scenario and periods I-III, respectively. The potential impacts of 21st century climate change on water resources of the Nile River were assessed using the simulated 21st century streamflows to drive a reservoir operations model for Lake Nasser. The simulations showed that in the multimodel average, Egypt’s annual energy production at HAD will remain relatively unaffected by climate change early in the 21st century (2010-2039). However, Egypt will suffer significant reductions in hydropower production by mid century despite projected increases in energy demand. The agricultural sector will experience shortfalls relative to historical average irrigation releases from Lake Nasser by mid century due increased evapotranspiration and hence reduced reservoir inflows, and increased evaporation from the Sudd swamps and Lake Nasser surface, as well as reductions in precipitation. Overall, our analysis suggests that well there will be some near-term benefits from climate change, primarily associated with increased precipitation, but by mid century, management of Nile water resources will become more challenging and complex. Furthermore, the uncertainty in climate change predictions (particularly rainfall patterns in the basin) and the complexity of water management 21 issues facing basin water users will place a premium on more integrative approaches to dealing with water supply and demand changes in the basin (Conway, 2005; Stern, 2007). 22 List of figures Figure 1: Simulated and observed Nile River flow at selected gauging stations for the period 19661999 a) Main Nile River flow at DONGOLA (a) and b) Upper Blue Nile at Rosiers Upstream of El diem, Sudan for the period 1970-1999. Validation period shown excludes the period 1950-1965 used for model calibration. ............................................................................................................30 Figure 2: Head waters and sub-basins of the main stem Nile (panel a) and locations of the two gauging stations and flow routing network derived from ½ degree (latitude-longitude) DEM (panel b). .................................................................................................................................................31 Figure 3: Downscaled and bias-corrected long-term (30yr) mean monthly temperature, precipitation, simulated runoff, evapotranspiration, and soil moisture for a) the entire Nile basin b) Blue Nile basin, and c) Lake Victoria region. The thick line (black) denotes the base historical (1950-1999) period. ......................................................................................................................32 Figure 4: Ranges of temperature change among ensemble members( panel a) for the period 20102039, panel b) the same except for the period 2040-2069 and similarly panel c) 2070-2099. Panels d), e) and f) show ranges of precipitation change as percentages for the three periods respectively. Letters V, B, and N in the panels represent Lake Victoria region, Blue Nile, and entire Nile basin respectively, where as letters A2 and B1 represent the two global emission scenarios A2 and B1. The lower two panels show ranges of streamflow change for main Nile flow at HAD and Blue Nile flow at El diem for three periods and two global emission scenarios .............................................33 Figure 5: Seasonal changes in precipitation and runoff for wet season (JJA) and dry season (DJF). Panel a) shows A2 emission scenario JJA precipitation changes relative to mean historical (19501999), 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; Panel c), same as panel a) except for DJF precipitation; Panel d), same as panel a ) except for DJF runoff....................................................................................34 23 Figure 6: Simulated mean seasonal cycle of streamflow derived from all 11 GCMs for A2 emissions scenario at the main Nile stem 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)..................................................................................................................35 Figure 7: Projected mult-imodel 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. .................................................36 24 References Adam, J.C. and D.P. 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Journal of Hydrologic Engineering 3(2):98-108. 29 Figure 1: Simulated and observed Nile River flow at selected gauging stations for the period 19661999 a) Main Nile River flow at DONGOLA (a) and b) Upper Blue Nile at Rosiers Upstream of El diem, Sudan for the period 1970-1999. Validation period shown excludes the period 1950-1965 used for model calibration. 30 Figure 2: Head waters and sub-basins of the main stem Nile (panel a) and locations of the two gauging stations and flow routing network derived from ½ degree (latitude-longitude) DEM (panel b). 31 Figure 3: Downscaled and bias-corrected long-term (30yr) mean monthly temperature, precipitation, simulated runoff, evapotranspiration, and soil moisture for a) the entire Nile basin b) Blue Nile basin, and c) Lake Victoria region. The thick line (black) denotes the base historical (1950-1999) period. 32 Figure 4: Ranges of temperature change among ensemble members( panel a) for the period 20102039, panel b) the same except for the period 2040-2069 and similarly panel c) 2070-2099. Panels d), e) and f) show ranges of precipitation change as percentages for the three periods respectively. Letters V, B, and N in the panels represent Lake Victoria region, Blue Nile, and entire Nile basin respectively, where as letters A2 and B1 represent the two global emission scenarios A2 and B1. The lower two panels show ranges of streamflow change for main Nile flow at HAD and Blue Nile flow at El diem for three periods and two global emission scenarios . 33 Figure 5: Seasonal changes in precipitation and runoff for wet season (JJA) and dry season (DJF). Panel a) shows A2 emission scenario JJA precipitation changes relative to mean historical (19501999), 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; Panel c), same as panel a) except for DJF precipitation; Panel d), same as panel a ) except for DJF runoff. 34 Figure 6: Simulated mean seasonal cycle of streamflow derived from all 11 GCMs for A2 emissions scenario at the main Nile stem 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). 35 Figure 7: Projected mult-imodel 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. 36 Table 1.Description of GCMs (General Circulation Models) GCM Modeling Group, Country IPCC Model I.D. Reference CNRM Centre National de CNRM-CM3 Salas-Mélia et Recherches Météoroliques, al.,2005 France CSIRO CSIRO Atmospheric CSIRO-Mk3.0 Research, Australia GFDL Geophysical Fluid Dynamics Gordon, H.B. et al., 2002 GFDL-CM2.0 Delworth et al., 2005 GISS-ER Russell et al., 1995, Laboratory, USA GISS Goddard Institute for Space Studies, USA HADCM3 Hadley Center for Climate 2000 UKMO-HadCM3 and Prediction and Research, Gordon, C. et al., 2002 UK INMCM Institute for Numerical INM-CM3.0 Mathematics, Russia IPSL Institut Pierre Simon Laplace, Diansky and Volodin, 2002 IPSL-CM4 IPSL, 2005 MIROC3.2 K-1 model France MIROC Center for Climate Systems Research, Japan MPI MRI developers, 2004 Max Planck Institute for ECHAM5 / MPI- Jungclaus et al., 2005 Meteorology, Germany OM Meteorological Research MRI-CGCM2.3.2 Yukimoto et al., 2001 PCM Washington et al., Institute, Japan PCM National Center for Atmospheric Research, USA 2000 37 Table 2(a): 2010-2039 multimodel annual average change in temperature (ºC) relative to 19501999 historical average for sub-basins of the Nile basin and the entire basin for each GCM and the A2 (B1) global emissions scenario. Region GISS GFDL CSIRO CNRM MPI MRI MIROC IPSL INMCM HadCM3 PCM Lake 0.99 1.11 0.97 1.33 1.05 1.22 0.87 1.12 1.02 (0.85) (1.23) (0.92) (1.09) (0.96) (0.89) (1.16) 1.51 1.57 1.5 1.34 1.09 (1.38) (1.25) (1.44) (1.1) (1.3) (0.78) (1.66) Entire 1.64 1.77 1.63 1.27 1.41 Nile (1.28) (1.35) (1.52) (1.23) (1.17) (0.94) (1.37) Victoria Blue Nile 1.42 1.55 1.76 1.95 1.28 0.72 (1.03) (1.15) (1.08) (0.65) 1.65 1.35 0.96 (1.49) (0.9) (1.12) (0.99) 1.43 1.35 0.91 (1.12) (1.09) 1.13 1.38 (1.23) (1.01) Table 2(b): 2040-2069 multimodel annual average change in temperature (ºC) relative to 19501999 historical average for sub-basins of the Nile basin and the entire basin for each GCM and the A2 (B1) global emissions scenario. Region GISS GFDL CSIRO CNRM MPI MRI MIROC IPSL INMCM HadCM3 PCM Lake 2.01 1.89 2.67 3.23 2.96 2.2 2.57 2.45 (1.55) (1.44) (1.62) (2.05) (1.95) (1.94) (2.46) 2.72 3.15 3.13 2.71 (1.55) (2.87) (2.62) (2.33) (2.65) (2.67) (2.79) Entire 3.0 3.47 3.77 3.59 Nile (1.97) (2.73) (2.84) (2.66) (2.58) (2.69) (3.43) Victoria Blue Nile 3.21 3.67 3.56 3.78 3.54 3.99 2.75 2.76 2.22 (2.56) (1.78) (1.68) (1.95) 3.05 3.26 2.54 (2.83) (2.76) (2.83) (1.99) 3.31 3.75 2.77 (3.22) (2.25) 3.25 3.69 (2.97) (3.09) 38 Table 2(c): 2070-2099 multimodel annual average change in temperature (ºC) relative to 19501999 historical average for sub-basins of the Nile basin and the entire basin for each GCM and the A2 (B1) global emissions scenario. Region GISS GFDL CSIRO CNRM MPI MRI MIROC IPSL INMCM HadCM3 PCM Lake 3.95 3.47 3.93 3.44 Victoria (3.22) (2.94) 3.23 3.32 3.88 (3.11) (2.81) (3.17) (3.05) (3.38) 4.56 3.91 4.01 2.39 (2.66) (2.18) (3.26) (2.25) 3.85 4.66 2.84 Blue 4.72 3.21 3.89 3.83 4.71 Nile (3.40) (3.87) (3.42) (3.21) (3.38) (3.41) (3.79) (3.13) (3.76) (3.83) (2.87) Entire 5.04 3.67 4.53 4.77 4.87 4.56 4.21 3.38 Nile (3.74) (3.37) (3.79) (3.64) (3.81) (3.59) (4.13) (3.99) (3.01) 4.88 5.54 3.37 5.86 4.23 4.49 (3.45) (3.58) Table 3(a): 2010-2039 multimodel annual average change in precipitation (%) relative to 19501999 historical average for sub-basins of the Nile basin and the entire basin for each GCM and the A2 (B1) global emissions scenario. Region GISS GFDL CSIRO CNRM MPI MRI MIROC IPSL INMCM HadCM3 PCM Lake 141 82 135 128 124 115 122 131 97 96 124 Victoria (147) (92) (148) (139) (129) (110) (132) (135) (101) (100) (125) Blue 153 87 118 109 119 133 128 107 93 102 123 Nile (158) (96) (121) (119) (114) (139) (135) (122) (90) (109) (118) Entire 140 84 131 107 127 101 105 125 92 95 120 Nile (142) (90) (138) (114) (133) (110) (109) (126) (97) (101) (126) 39 Table 3(b): 2040-2069 multimodel annual average change in precipitation (%) relative to 19501999 historical average for sub-basins of the Nile basin and the entire basin for each GCM and the A2 (B1) global emissions scenario. Region GISS GFDL CSIRO CNRM MPI MRI MIROC IPSL INMCM HadCM3 PCM Lake 131 68 104 105 103 98 107 Victoria (137) (87) (112) (109) (106) (100) (112) Blue Nile 124 66 89 87 105 (128) (72) (101) (111) (102) (119) (121) Entire 120 62 113 94 109 Nile (124) (77) (114) (103) (117) (99) 100 89 78 100 (105) (92) (81) (111) 83 85 101 (107) (83) (93) (103) 93 115 88 110 (103) (112) (79) (91) (115) 103 112 81 79 81 Table 3(c): 2070-2099 multimodel annual average change in precipitation (%) relative to 19501999 historical average for sub-basins of the Nile basin and the entire basin for each GCM and the A2 (B1) global emissions scenario. Region GISS GFDL CSIRO CNRM MPI MRI MIROC IPSL INMCM HadCM3 PCM Lake 114 97 107 68 73 101 56 98 100 90 82 Victoria (121) (68) (113) (104) (94) (101) (96) (102) (77) (84) (103) Blue 137 73 99 126 89 121 93 96 97 114 Nile (142) (79) (101) (113) (94) (123) (111) (103) (91) (116) (98) Entire 116 64 103 84 91 77 85 102 71 93 104 Nile (113) (72) (108) (93) (100) (96) (88) (106) (72) (94) (106) 113 40 Table 4: Multimodel average annual and seasonal (JJA and DJF) temperature changes as differences in degrees (oC) 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 Historical Lake Blue Entire Nile basin Victoria Nile Annual DJF JJA 19.8 oC 21.25 23.45 oC 22.11 oC 25.24 oC o C A2 2010-39 1.06 1.25 1.48 1.38 1.16 A2 2040-69 2.51 3.1 3.22 2.89 2.45 A2 2070-99 3.45 4.18 4.36 3.90 3.60 B1 2010-39 1.0 1.22 1.31 1.02 1.15 B1 2040-69 1.9 2.55 2.76 2.78 2.50 B1 2070-99 2.91 3.37 3.65 3.54 3.58 41 Table 5: Multimodel average annual and seasonal (JJA and DJF) precipitation changes as percentages (mm) of the historical (1950-1999) for two sub-basins of the Nile basin and entire Nile basin for the A2 (B1) global emissions scenario and three periods. Scenario Historical Lake Victoria Blue Nile Entire Nile basin Annual DJF JJA 15mm 55mm 116mm 98mm 70mm A2 2010-39 117%(136mm) 116%(113mm) 112%(78mm) +25%(3.7mm) +18%(10mm) A2 2040-69 98.81%(115mm) 91%(89mm) 98%(68mm) -8.2%(-1.2mm) -5.4%(-3mm) A2 2070-99 89.63%(104mm) 105%(103mm) 90%(63mm) +4.7(0.69mm) -2.3%(-0.12mm) B1 2010-39 123.45%(143mm) 120%(117mm) 117%(82mm) +9.8%(1.44mm) +24%(13mm) B1 2040-69 104.7%(121mm) 104%(102mm) 103%(72mm) -6.7%(1mm) -2.6%(1.44mm) B1 2070-99 96.63%(112mm) 106%(104mm) 95%(67mm) +2.04 (1.14mm) (1950-1999) -1%(-0.15mm) 42 Table 6: Simulated streamflow by each climate model routed to the mainstem 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). GCM Period1 Period2 Period3 2010-2039 2040-2069 2070-2099 Gfdl 77(92) 71(85) 62(75) Giss 134(136) 126(127) 112(115) Csiro 108(127) 102(105) 107(112) Inmcm 95(99) 82(83) 70(73) Mpi 130(128) 112(105) 97(93) Cnrm 112(123) 96(100) 83(85) Ipsl 101(110) 87(90) 75(79) Pcm 110(125) 94(103) 81(91) Miroc 119(119) 102(98) 85(86) Hadcm3 89(95) 77(78) 67(68) Mri 126(118) 108(98) 93(95) 43 Table 7: Simulated streamflow for each climate model routed to the Blue Nile gauging station at El diem (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 Period1 Period2 Period3 2010-2039 2040-2069 2070-2099 Gfdl 83(87) 77(78) 71(72) Giss 148(154) 133(136) 126(125) Csiro 126(125) 102(102) 112(117) Inmcm 100(106) 81(87) 74(81) Mpi 113(112) 92(85) 83(91) Cnrm 105(106) 86(91) 97(105) Ipsl 131(130) 106(113) 96(105) Pcm 127(125) 102(101) 103(112) Miroc 130(129) 105(105) 95(104) Hadcm3 106(115) 86(92) 76(95) Mri 131(120) 106(99) 96(101) 44 Table 8: Multimodel High Aswan Dam hydropower production metrics Scenario Minimum 1st Mean Quartile Historical 3rd Max Quartile Percentage Change Relative to 9.66 x 103 historical annual GWH/yr Hydropower production (x103GWH/yr) A2 2010-39 4.7 7.5 10.7 13.2 20.5 110.3%(1) A2 2040-69 3.7 8.2 9.9 11.0 17.3 102.6%(0.25) A2 2070-99 3.1 6.5 9.0 10.4 17.5 93.4%(-0.65) B1 2010-39 4.8 8.1 11.4 13.2 21.6 117.6%(1.7) B1 2040-69 4.3 8.8 10.5 11.7 18.8 108.2%(0.8) B1 2070-99 2.3 6.8 88 10.1 16.6 91.6%(-0.84) 45 Table 9: Multimodel long term average monthly irrigation releases from High Aswan Dam (BCM) for historical 1950-1999 and three future periods A2_2010- A2_2040- A2_2070- B1_2010- B1_2040- B1_2070- 2069 2099 Month historical 2039 2069 2099 2039 Jan 3.50 3.71 3.06 3.01 3.82 3.12 2.94 Feb 4.00 4.24 3.49 3.44 4.36 3.56 3.36 Mar 4.20 4.45 3.67 3.61 4.58 3.74 3.53 Apr 4.00 4.24 3.49 3.44 4.36 3.56 3.36 May 5.30 5.62 4.63 4.56 5.78 4.72 4.45 June 6.50 6.89 5.67 5.59 7.09 5.79 5.46 July 7.00 7.42 6.11 6.02 7.63 6.23 5.88 Aug 6.30 6.68 5.50 5.42 6.87 5.61 5.29 Sep 4.30 4.56 3.75 3.70 4.69 3.83 3.61 Oct 3.70 3.92 3.23 3.18 4.03 3.29 3.11 Nov 3.60 3.82 3.14 3.10 3.92 3.20 3.02 Dec 3.00 3.18 2.62 2.58 3.27 2.67 2.52 Annual 55.40 58.72 48.36 47.64 60.39 49.31 46.54 46