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Evaluating Potential Impacts of Climate Change on Surface Water Resource Availability of Upper Awash Sub-basin, Ethiopia rift valley basin. By Mekonnen.

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Presentation on theme: "Evaluating Potential Impacts of Climate Change on Surface Water Resource Availability of Upper Awash Sub-basin, Ethiopia rift valley basin. By Mekonnen."— Presentation transcript:

1 Evaluating Potential Impacts of Climate Change on Surface Water Resource Availability of Upper Awash Sub-basin, Ethiopia rift valley basin. By Mekonnen Daba Paper presented at African Dissemination Workshop on Innovative Application of ICTs in Addressing Water - related Impacts of Climate Change, 12th December, 2014 at Makerere University, Kampala

2 Introduction Climate changes
In the surface temperature, Changes in precipitation evapotranspiration rate Changes in global climate will have significant impact on local and regional hydrological regimes, which will in turn affect ecological, social and economic systems The economy of Ethiopia mainly depends on agriculture, and this in turn largely depends on available water resources. will accelerate the global hydrological cycle(IPCC, 2007) (IPCC, 2007) findings suggests that developing countries like Ethiopia will be more vulnerable to climate change due to their economic, climatic and geographic settings. Climate changes alter regional hydrologic conditions and results in a variety of impacts on water resource systems. Such hydrologic changes will affect almost every aspect of human well-being. The economy of Ethiopia mainly depends on agriculture, and this in turn largely depends on available water resources.

3 Key Sub-basin Problems
Upper Awash sub-basin is normally endowed with land features that are characterized by: Downstream irrigation , several towns, including the capital city, Addis Ababa, and industrial enterprises in the study area has been expanding from time to time there is an increasing demand for water which leads to competition for water among different sectors . Because of fast growing population rates, increasing resources and industrial development, water is becoming a very scarce and valuable resource. Water stress is one of several current and future critical issues facing Africa. About 25% of the contemporary African population experience water stress, while 69% live under conditions of relative water abundance (Vörösmarty et al., 2005 cited in Yehun, 2009). Many studies have been undertaken to investigate climate change impacts on water resource in different basin of Ethiopia using different models and emission scenarios. (Kifle,etal,1999;Shimelis,2004,Mengistu,D. et al. 2008;A.Negash,S.etal,2010; D.T.Mengistu,2012;Mussa,2011;Girma,T. et al. 2012;H.Q.Bang,etal,2013;T.A.Demissie,etal,2013), which have a  great potential to  threat  the human  society and  the environment. To better plan water management adaptation strategies, more information is necessary on the potential changes in climate and drought conditions.

4 So What are the Innovations/Solutions?
Therefore assessing the impact of climate change on Surface water resource availability, Taking projections of climatic variables (e.g., precipitation and temperature at a global scale, Downscaling these global-scale climatic variables to local-scale hydrologic variables, and Computing hydrological components for water resources variability and to give a clue and increase awareness on the possible future risks of climate change in order to mitigate the impacts climate change on water resources system. The general objective of this study is to assess the impacts of climate change on Surface water resource availability of upper Awash River basin by using the Regional climate model and Soil and Water Assessment Tool (SWAT) hydrology model. So What are the Innovations/Solutions? All the SWAT model applications in Ethiopia concentrate on the Blue Nile River Basin and none has been applied on Awash basin, particularly Upper awash. Based on the previous experiences of SWAT model application and the acceptable results obtained in Ethiopia, the SWAT model is preferred for this study. Several mathematical models are available to evaluate potential future implications due to the factors driving the changes. Of these, the Soil and Water Assessment Tool (SWAT) model has been employed widely to evaluate the impact of climate change on soil erosion and sediment yields (Shrestha et al., 2012) cited by T.A.Demissie, et al It has also been used to evaluate the impact of climate change on streamflow. For instance, Fontaine et al. (2009), Githui et al.(2009), Ficklin et al.(2009), and Li et al. (2011) used SWAT model to evaluate the impact of climate change on stream flow. Several researchers have applied the SWAT model in Ethiopia. For instance, the SWAT model was applied by Setegn et al. (2010) for the simulation of sediment yield in the Anjeni gauged catchment within the Blue Nile River basin. Mengistu and Sorteberg (2012) used the SWAT model to investigate the sensitivity of SWAT simulated stream flow to climatic changes within the Eastern Nile River basin.

5 Study Area map . .

6 The Methodology used To evaluate climate change impacts on the water availability of the following steps: Precipitation, and temperature, is extracted From GCM. A Dynamic downscale GCM output to RCM Bias corrected RCM with historical met data. Meteorological data + observed stream flows + (SWAT) Sensitivity analysis calibrated and validated Simulation model at 2020s, 2050s and 2080s periods to assess the climate scenarios and their impact on water resources system. Finally, To give a clue and increase awareness on the possible future risks of climate change in order to mitigate the impacts climate change on water resources system.

7

8 Key Finding's Scenarios Developed for the Future time series (2011-2100)
The general trend exhibits rising for temperature and decreasing for total annual precipitation.

9 Changes in rainfall and temperature at upper awash basin level
Changes in Average annual minimum temperature Changes in Average annual maximum temperature 2020: C 2050:+0.820C 2080:+2.140C 2020: C 2050: C 2080: C Also the estimate range is same with results of Girma.M (2012) and IPCC‟s average mean annual temperature across Ethiopia will increase by between 0.9 and 1.1°C by the year 2030 and from 1.7 to 2.1°C by the year 2050. Basin-average annual rainfall based on the ECHAM5 downscaling by using the same model by (Girma.M 2012) point out that the CCLM downscaling resulted in the upper Blue Nile were 1.8, -6.6 and -6.4% in , and respectively. The result of this analysis confirmed also with the IPCC‟s , precipitation show a change of between 0.6 and 4.9% and 1.1 to 18.2% for 2030 and 2050, respectively (NM,A, 2006). 2020: +2.4% 2050:-2.14% 2080: %

10 SWAT Hydrological Model Results Flow Calibration
Manual calibration (manually and automatically) using observed flow gauged at the outlet of the watershed flow calibration at the outlet of Hombole and Melka kunture guaging stations Hombole total flow(m3/s) Average flow(m3/s) R2 ENS Bias RMSE RVE Period gauged simulated 39.95 48.34 0.83 0.80 8.38 16.78 0.320 Melka kunture 28.05 33.26 0.90 0.91 9.6 13.4 0.186

11 Projected changes in the mean annual and seasonal stream flow
Generally our results also suggest that the relationship of annual stream flow to annual precipitation may change in a future climate in that a unit decrease in precipitation will cause a larger decrease in stream flow for the year 2050 and 2080. 2020: +4.9% 2050:-2.46% 2080:-18.14% 2020: +2.04% 2050:-9.90% 2080:-19.73%

12 Monthly and annual impacts on future Surface runoff
The future scenario generated runoff shows a decreasing in the future time series for the two periods from 2050 and 2080 comparing with the base period , but for the future time series 2020 has an increasing in runoff comparing with the base period. 2020: +8% 2050:-1.5% 2080:-3.52% 2020: +7.49% 2050:-0.99% 2080:+7.14%

13 Adaptation Strategies
Based on result of study stream flow and runoff decrease for the future 2050 and 2080 periods, below are some possible adaptation options to be implemented to overcome the reduction stream flow and surface runoff in the watershed :- Watershed based integrated water resource management approach. Constructing water storage structures to store excess water flowing during rainy season so as to use it for dry season. Consideration of climate change and its impact at all levels of water resource development projects from the planning up to the execution and management phases.

14 Conclusions From the scenario results indicate that an increase in precipitation resulted in an increase in annual runoff and stream flow. In contrast, a temperature increase caused a decrease in annual runoff. The runoff has a negative correlation with temperature change but a positive correlation with precipitation change. Generally the analyses carried out in this study revealed that climate change would have a significant impact on the Surface runoff and stream flow, and other hydrological parameter causing a possible reduction on the total water availability in the upper awash sub-basin.

15 Recommendations In addition to fluctuations on temperature and precipitation, deforestation and population growth due to industrial expansion in the area are among current trends over the sub- basin. Hence, it is important to examine the impacts of climate and land use changes over the study area. It is believed that the results of this study give a clue and increase awareness on the possible future risks of climate change. This in combination of the future climate change impact on reduction of the available water in the watershed causes a water stress within and around the Sub-basin. Hence, it is strictly recommended that the adaptation measures proposed in the above section need to be effectively implemented in any existing and development of a new project in the study area. . Uncertainties in the study The levels of uncertainty of the SWAT stream flow simulations were calculated by comparing the SWAT simulated stream flow from observed ( ) and Bias corrected RCM ( ). The highest percentage of biases is found for Bias corrected RCM ( ) (19.31%) and observed ( ) (12.32%) . The largest contribution to the total error or bias was attributable to Bias Corrected RCM downscaling error (19.31%).

16 THANK YOU!!!


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