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Future Water Supply Projections in Ethiopia Under Climate Change Using NASA NEX-GDDP and LDAS Simulations
  • Jose M. Molina,
  • Benjamin F. Zaitchik,
  • Zablon A. Adane
Jose M. Molina

Corresponding Author:[email protected]

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Benjamin F. Zaitchik
Johns Hopkins University
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Zablon A. Adane
World Resources Institute
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Ethiopia’s socioeconomic development is strongly dependent on both its natural resources and hydroclimatic dynamics. Current and projected effects of climate change and variability in the Horn of Africa pose an enormous challenge to the country’s water resources management. We modeled multi-basin runoff scenarios in the country by calibrating statistical models first followed by extrapolation of the regressed functions into a future data domain under assumptions of stationarity. Precipitation and average near-surface air temperature predictors were used to calibrate Generalized Linear Models (GLM) to project 2011-2070 monthly runoff in a high-emission scenario (RCP 8.5) for selected General Circulation Models (GCM). Gridded fields of downscaled and bias-corrected precipitation, Tmax and Tmin for 10 CMIP5 GCMs were obtained from the NASA NEX-GDDP database. Hydrologic simulations from the NASA Land Data Assimilation System (LDAS) were used as proxies of observational basin response. Noah-MP’s climate forcings (CHIRPS precipitation and MERRA temperatures) were used to perform additional bias-correction over basin-averaged predictors extracted from the NEX-GDDP ensemble models. Monthly mean estimates for precipitation/temperature projections showed wetter/warmer conditions than the baseline for almost all regions. 2011-2040 July temperature climatology in most GCMs exhibited the strongest warming (> 1.5C o) in Central Ethiopia and it gradually decreased northwards and southwards. Correlation analysis showed that precipitation variations explain most of runoff variability during the rainy seasons. Future GLM runoff estimates suggest a generalized national increase of mean annual water supply when compared with historical LDAS, although spatio-temporal differences were observed across the country. The mentioned hydrological gains are driven by spatially distributed changes in precipitation with the biggest positive trends in the southeastern region followed by moderate precipitation increases in the Central Highlands and neutral changes in the Northwest. Few GCMs (e.g., GFDL-CM3) project drier conditions in the rainy seasons and a slight decrease in the mean annual runoff for most basins. The wettest model in the Abay basin, IPSL-CM5A-LR, predicts 15% increase in annual runoff when compared to historical averages.