Abstract
Abstract. The hydrological model SWAT was run with daily station based precipitation and temperature data for the whole Eastern Nile basin including the three subbasins: the Abbay (Blue Nile), BaroAkobo and Tekeze. The daily and monthly streamflows were calibrated and validated at six outlets with station-based streamflow data in the three different subbasins. The model performed very well in simulating the monthly variability while the validation against daily data revealed a more diverse performance. The simulations indicated that around 60% of the average annual rainfalls of the subbasins were lost through evaporation while the estimated runoff coefficients were 0.24, 0.30 and 0.18 for Abbay, BaroAkobo and Tekeze subbasins, respectively. About half to two-thirds of the runoff could be attributed to surface runoff while the other contributions came from groundwater. Twenty hypothetical climate change scenarios (perturbed temperatures and precipitation) were conducted to test the sensitivity of SWAT simulated annual streamflow. The result revealed that the annual streamflow sensitivity to changes in precipitation and temperature differed among the basins and the dependence of the response on the strength of the changes was not linear. On average the annual streamflow responses to a change in precipitation with no temperature change were 19%, 17%, and 26% per 10% change in precipitation while the average annual streamflow responses to a change in temperature and no precipitation change were −4.4% K−1, −6.4% K−1, and −1.3% K−1 for Abbay, BaroAkobo and Tekeze river basins, respectively. 47 temperature and precipitation scenarios from 19 AOGCMs participating inCMIP3 were used to estimate future changes in streamflow due to climate changes. The climate models disagreed on both the strength and the direction of future precipitation changes. Thus, no clear conclusions could be made about future changes in the Eastern Nile streamflow. However, such types of assessment are important as they emphasise the need to use several an ensemble of AOGCMs as the results strongly dependent on the choice of climate models.
Highlights
Numerous studies have been conducted at different scales ranging from small watersheds to the entire globe to assess the impacts of climate change on hydrologic systems (Jha et al, 2006)
Taye et al (2011) simulated the climate change impact on hydrological extremes in two regions (Nyando basin found in white Nile and Lake Tana catchment located in upper Blue Nile subbasin) and noted that for Lake Tana catchment the GCM uncertainty was more important than the hydrological models uncertainty
The result part starts with a validation of the Soil and Water Assessment Tool (SWAT) model in the three different sub-basins, estimates of the individual sensitivity of the streamflow to temperature and precipitation in conducted before we investigate if the combined effect of temperature and precipitation changes may provide any non-linearities in the streamflow response
Summary
Numerous studies have been conducted at different scales ranging from small watersheds to the entire globe to assess the impacts of climate change on hydrologic systems (Jha et al, 2006). Sorteberg: Sensitivity of SWAT simulated streamflow to climatic changes the potential water resource management problems associated with water supply, power generation, and agricultural practices as well as for future water resource planning, reservoir design and management, and protection of the natural environment, it is necessary to provide quantitative estimates of the hydrological effects of climate change. In this regard as Taye et al (2011) stated several studies have been conducted on the sensitivity of streamflow to climate changes for many parts of the Nile. Taye et al (2011) simulated the climate change impact on hydrological extremes in two regions (Nyando basin found in white Nile and Lake Tana catchment located in upper Blue Nile subbasin) and noted that for Lake Tana catchment the GCM uncertainty was more important than the hydrological models uncertainty
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