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Modeling Climate Change Impact on the Hydrology of Keleta Watershed in the Awash River Basin, Ethiopia

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Abstract

Regional and local hydrological regimes are significantly vulnerable to global climate change which threaten water resources and food security of nations. This study investigates the likely impact of climate change on hydrological processes of the Keleta watershed in the Awash River Basin, Ethiopia. Delta statistical downscaling methods were used to downscale 20 global circulation models (GCMs) and 2 representative concentration pathways (RCPs) (RCP 4.5 and RCP 8.5) over the study periods of 2050s and 2080s. The Soil and Water Assessment Tool (SWAT) model was used to simulate hydrological processes. The model was calibrated and validated using monthly observed streamflow data for the baseline year (1985). It performed well with a Nash-Sutcliffe efficiency (NSE) ≥ 0.74, ratio of the root mean square error to the standard deviation of measured data (RSR) ≤ 0.51, and percent bias (PBIAS) ≤ 15.3. The results show that RCP 4.5 predicts an average precipitation increase of 15.2 and 17.2% for mid- and end-of-century data, respectively. Similarly, RCP 8.5 predicts an average precipitation increase of 19.9 and 34.4% for mid- and end-of-century data, respectively. Mid-century minimum and maximum temperature increases range from 1.8 to 1.6 °C (RCP 4.5) to 2.6 to 2.1 °C (RCP 8.5), respectively, while end-of-century increases vary from 2.4 to 2.0 °C (RCP 4.5) and 4.6 to 3.7 °C (RCP 8.5), respectively. This leads to an average increase in runoff by 70%. The increased rainfall, warmer temperature, and significant increment in the hydrologic components, and particularly the excess runoff and associated extreme peak flow over the coming decades, are likely to put a tremendous pressure on the hydrological system of the watershed. This calls for sustainable and effective adaptive measures for future water resource management.

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References

  1. Dibike, Y. B., & Coulibaly, P. (2005). Hydrologic impact of climate change in the Saguenay watershed: comparison of downscaling methods and hydrologic models. Journal of Hydrology, 307, 145–163.

    Article  Google Scholar 

  2. Feng, S., Hu, Q., Huang, W., Ho, C. H., Li, R., & Tang, Z. (2014). Projected climate regime shift under future global warming from multi-model, multi-scenario CMIP5 simulations. Global and Planetary Change, 112, 41–52.

    Article  Google Scholar 

  3. Kim, B., Kim, B., & Kwon, H. (2011). Assessment of the impact of climate change on the flow regime of the Han River Basin using indicators of hydrologic alteration. Hydrological Processes, 25, 691–704.

    Article  Google Scholar 

  4. Li, M.-H., Tien, W., & Tung, C.-P. (2009). Assessing the impact of climate change on the land hydrology in Taiwan. Paddy and Water Environment, 7, 283–292.

    Article  Google Scholar 

  5. Bharati, L., Gurung, P., Jayakody, P., Smakhtin, V., & Bhattarai, U. (2014). The projected impact of climate change on water availability and development in the Koshi. Mountain Research and Development, 34, 118–130.

    Article  Google Scholar 

  6. Cousino, L. K., Becker, R. H., & Zmijewski, K. A. (2015). Modeling the effects of climate change on water, sediment, and nutrient yields from the Maumee River watershed. Journal of Hydrology: Regional Studies, 4, 762–775.

    Google Scholar 

  7. Fiseha, B. M., Setegn, S. G., Melesse, A. M., Volpi, E., & Fiori, A. (2014). Impact of climate change on the hydrology of Upper Tiber River Basin using bias corrected regional climate model. Water Resources Management, 28, 1327–1343.

    Article  Google Scholar 

  8. Wu, C. H., Huang, G. R., & Yu, H. J. (2015). Prediction of extreme floods based on CMIP5 climate models: a case study in the Beijing River Basin, South China. Hydrology and Earth System Sciences, 19, 1385–1399.

    Article  Google Scholar 

  9. Yip, Q. K. Y. K. Y., Burn, D. H. H., Seglenieks, F., Pietroniro, A., Eric, D. D., Yip, Q. K. Y., Burn, D. H., Seglenieks, F., Pietroniro, A., & Soulis, E. D. (2012). Climate impacts on hydrological variables in the Mackenzie River Basin. Canadian Water Resources Journal, 37, 37–41.

    Article  Google Scholar 

  10. Boko, M., Niang, I., Nyong, A., Vogel, C., Githeko, A., Medany, M., Osman-Elasha, B., Tabo, R., & Yanda, P. (2007). Africa. Climate change 2007: impacts, adaptation and vulnerability. Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change (pp. 433–467). Cambridge: Cambridge University Press.

    Google Scholar 

  11. Dessu, S. B., & Melesse, A. M. (2013). Impact and uncertainties of climate change on the hydrology of the Mara River Basin, Kenya/Tanzania. Hydrological Processes, 27, 2973–2986.

    Google Scholar 

  12. Dile, Y. T., Berndtsson, R., & Setegn, S. G. (2013). Hydrological response to climate change for Gilgel Abay River, in the Lake Tana Basin—Upper Blue Nile Basin of Ethiopia. PLoS One, 8, 12–17.

    Article  Google Scholar 

  13. Basheer, A. K., Lu, H., Omer, A., Ali, A. B., & Abdelgader, A. M. S. (2015). Impacts of climate change under CMIP5 RCP scenarios on the streamflow in the Dinder River and ecosystem habitats in Dinder National Park, Sudan. Hydrology and Earth System Sciences, 12, 10157–10195.

    Article  Google Scholar 

  14. Beyene, T., Lettenmaier, D. P., & Kabat, P. (2010). Hydrologic impacts of climate change on the Nile River Basin: implications of the 2007 IPCC scenarios. Climate Change, 100, 433–461.

    Article  Google Scholar 

  15. Ebrahim, G. Y., Jonoski, A., Van Griensven, A., & Di Baldassarre, G. (2013). Downscaling technique uncertainty in assessing hydrological impact of climate change in the Upper Beles River Basin, Ethiopia. Hydrology Research, 44, 377–398.

    Article  Google Scholar 

  16. Huntington, T. G. (2006). Evidence for intensification of the global water cycle: review and synthesis. Journal of Hydrology, 319, 83–95.

    Article  Google Scholar 

  17. Yan, R., Gao, J., & Li, L. (2016). Modeling the hydrological effects of climate and land use/cover changes in Chinese lowland polder using an improved WALRUS model. Hydrology Research. https://doi.org/10.2166/hydro.2016.204.

  18. Kundzewicz, Z. W., Mata, L. J., Arnell, N. W., Döll, P., Kabat, P., Jiménez, B., Miller, K. A., Oki, T., Sen, Z., & Shiklomanov, I. A. (2007). Freshwater resources and their management. Climate change 2007: impacts, adaptation and vulnerability. Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press.

    Google Scholar 

  19. Dahal, V., Shakya, N. M., & Bhattarai, R. (2016). Estimating the impact of climate change on water availability in Bagmati Basin, Nepal. Environmental Processes, 3, 1–17.

    Article  Google Scholar 

  20. Turral, H., Burke, J., & Faurès, J.-M. (2011). Climate change, water and food security, FAO water reports. Rome: FAO.

    Google Scholar 

  21. Li, Y. L., Tao, H., Yao, J., & Zhang, Q. (2015). Application of a distributed catchment model to investigate hydrological impacts of climate change within Poyang Lake catchment (China). Hydrology Research. https://doi.org/10.2166/hydro.2015.092.

  22. Milly, P. C. D., Betancourt, J., Falkenmark, M., Hirsch, R. M., Kundzewicz, Z. W., Lettenmaier, D. P., & Stouffer, R. J. (2008). Stationarity is dead: whither water management? Science, 319, 573–574.

    Article  CAS  Google Scholar 

  23. Mohamed, Y. A., Van den Hurk, B. J. J. M., Savenije, H. H. G., & Bastiaanssen, W. G. M. (2005). Hydroclimatology of the Nile: results from a regional climate model. Hydrology and Earth System Sciences Discussions, 9, 263–278.

    Article  Google Scholar 

  24. Mejia, J.F., Niswonger, R.G. and Huntington, J. 2014. Uncertainty transfer in modeling layers: from GCM to downscaling to hydrologic surface-groundwater modeling. In: 7th Intl. Congress on Env. Modelling and Software. International Environmental Modelling and Software Society, San Diego, USA.

  25. Mango, L. M., Melesse, A. M., McClain, M. E., Gann, D., & Setegn, S. G. (2011). Land use and climate change impacts on the hydrology of the upper Mara River Basin, Kenya: results of a modeling study to support better resource management. Hydrology and Earth System Sciences, 15, 2245–2258.

    Article  Google Scholar 

  26. Prudhomme, C., Reynard, N., & Crooks, S. (2002). Downscaling of global climate models for flood frequency analysis: where are we now? Hydrological Processes, 16, 1137–1150.

    Article  Google Scholar 

  27. Mengistu, D. T., & Sorteberg, A. (2012). Sensitivity of SWAT simulated streamflow to climatic changes within the Eastern Nile River Basin. Hydrology and Earth System Sciences, 16, 391–407.

    Article  Google Scholar 

  28. Edossa, D. C., Babel, M. S., & Das Gupta, A. (2010). Drought analysis in the Awash River Basin, Ethiopia. Water Resources Management, 24, 1441–1460.

    Article  Google Scholar 

  29. Kinfe, H. (1999). Impact of climate change on the water resources of Awash River Basin, Ethiopia. Climate Research, 12, 91–96.

    Article  Google Scholar 

  30. Tiruneh, Y., Berhanu, B., Ayalew, S., Tamrat, I., & Tesfaye, Y. (2013). Coping with water scarcity, the role of agriculture. Developing a water audit for Awash River Basin. Addis Ababa: FAO.

    Google Scholar 

  31. Bekele, D., Alamirew, T., Kebede, A., Zeleke, G., & Melesse, A. M. (2016). Analysis of rainfall trend and variability for agricultural water management in Awash River Basin, Ethiopia. Journal of Water and Climate Change, 8, 127–141. https://doi.org/10.2166/wcc.2016.044.

    Article  Google Scholar 

  32. FAO/UNESCO. (1995). The digital soil map of the world. Rome: Food and Agriculture Organization of the United Nations.

    Google Scholar 

  33. Tibebe, D., & Bewket, W. (2011). Surface runoff and soil erosion estimation using the SWAT model in the Keleta watershed, Ethiopia. Land Degradation & Development, 22, 551–564.

    Article  Google Scholar 

  34. IPCC. (2013). The physical science basis, contribution of working group I to the fifth assessment report. Cambridge: Cambridge University Press.

    Google Scholar 

  35. Diaz-Nieto, J., & Wilby, R. L. (2005). A comparison of statistical downscaling and climate change factor methods: Impacts on low flows in the river Thames, United Kingdom. Climate Change, 69, 245–268.

    Article  Google Scholar 

  36. Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large area hydrologic modeling and assessment, part I: model development. Journal of the American Water Resources Association, 34, 73–89.

    Article  CAS  Google Scholar 

  37. Neitsch, S.L., Arnold, J.G., Kiniry, J.R. & Williams, J.R. 2009. Soil & water assessment tool theoretical documentation version 2009. Texas, USA.

  38. Winchell, M., Srinivasan, R., Di Luzio, M. & Arnold, J. 2010. ArcSWAT interface for SWAT 2009: user’s guide. Texas, USA.

  39. Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2004). Remote sensing and image interpretation (5th ed.). New York: Wiley.

    Google Scholar 

  40. Campbell, J. B., & Wynne, R. H. (2011). Introduction to remote sensing (5th ed.). New York: The Guilford Press.

    Google Scholar 

  41. Anderson, J.R., Hardy, E.E., Roach, J.T. and Witmer, R.E. 1976. A land use and land cover classification system for use with remote sensor data. USGS Professional Paper 964, Washington

  42. Thomlinson, J. R., Bolstad, P. V., & Cohen, W. B. (1999). Coordinating methodologies for scaling landcover classifications from site-specific to global: steps toward validating global map products. Remote Sensing of Environment, 70, 16–28.

    Article  Google Scholar 

  43. FAO, IIASA, ISRIC, ISS-CAS, & JRC. (2011). Harmonized world soil database. Rome: FAO.

    Google Scholar 

  44. Abayneh, E., Demeke, T., & Ashenafi, A. (2005). Soils of Melkassa Research Center and its testing sites. Addis Ababa: FAO.

    Google Scholar 

  45. Arnold, J. G., & Allen, M. P. (1999). Automated methods for estimating baseflow and ground water recharge from streamflow records. Journal of the American Water Resources Association, 35, 411–424.

    Article  Google Scholar 

  46. Abbaspour, K. C. (2012). SWAT-CUP: SWAT calibration and uncertainty programs—user manual. Dübendorf: Swiss Federal Institute of Aquatic Science and Technology.

    Google Scholar 

  47. Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. American Society of Agricultural and Biological Engineers, 50, 885–900.

    Google Scholar 

  48. Santhi, S., Arnold, J. G., Williams, J. R., Dugas, W. A., Srinivasan, R., & Hauck, L. M. (2001). Validation of the SWAT model on a large river basin with point and non point sources. Journal of the American Water Resources Association, 37, 1169–1188.

    Article  CAS  Google Scholar 

  49. Gupta, H. V., Sorooshian, S., & Yapo, P. O. (2005). Status of automatic calibration for hydrologic models: comparison with multilevel expert calibration. Journal of Hydrologic Engineering, 25, 1093–1120.

    Google Scholar 

  50. Christensen, J. H., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones, R., Kolli, R. K., Kwon, W. T., Laprise, R., Rueda, V. M., Mearns, L., Menéndez, C. G., Räisänen, J., Rinke, A., Sarr, A., & Whetton, P. (2007). Regional climate projections, climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.

    Google Scholar 

  51. Jha, M., Pan, Z., Takle, E. S., & Gu, R. (2004). Impacts of climate change on streamflow in the Upper Mississippi River Basin: a regional climate model perspective. Journal of Geophysical Research, 109, 1–12.

    Article  Google Scholar 

  52. Huang, M., & Zhang, L. (2004). Hydrological responses to conservation practices in a catchment of the Loess Plateau, China. Hydrological Processes, 18, 1885–1898.

    Article  Google Scholar 

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Acknowledgments

We would like to acknowledge the Ethiopian Institute of Agricultural Research (EIAR), Melkassa Agricultural Research Centre (MARC), Water and Land Resources Centre (WLRC) of Addis Ababa University, Ministry of Water, Irrigation and Electricity (MoWIE), Ethiopian Meteorological Agency (EMA), and Ethiopian Mapping Agency (EMA) for their data used in this study. We also acknowledge the critical review of the editor and the anonymous reviewers who contributed to clarifying the manuscript.

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Bekele, D., Alamirew, T., Kebede, A. et al. Modeling Climate Change Impact on the Hydrology of Keleta Watershed in the Awash River Basin, Ethiopia. Environ Model Assess 24, 95–107 (2019). https://doi.org/10.1007/s10666-018-9619-1

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  • DOI: https://doi.org/10.1007/s10666-018-9619-1

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