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  • Teleconnection, Modeling, Climate Anomalies Impact and Forecasting of Rainfall and Streamflow of the Upper Blue Nile River Basin
  • Elsanabary, Mohamed Helmy Mahmoud Moustafa
  • English
  • Egypt
    Nile River
    Upper Blue Nile River Basin
    Wavelet Empirical Orthogonal Function
    Hydrologic modeling
    Sacramento Model
    Interaction Soil Biosphere Atmosphere model
    Climate Anomalies
    Global Oceanic Sea Surface Temperature
    Artificial Neural Network- Genetic Algorithms
    Indian Ocean Dipole
    Water Resources Management
    Irrigation Improvement Project
    Seasonal Precipitation
    Rainfall Variability
    Climate Variability
  • Jul 10, 2012 3:45 PM
  • Thesis
  • English
  • HTML
  • 30157172 bytes
  • The Nile River, the primary water resource and the life artery for the downstream countries, Egypt and Sudan, exhibits strong seasonal fluctuations. The Upper Blue Nile basin (UBNB), the most significant tributary of the Nile, contributes more than half of the Nile’s streamflow. Prompted by the lack of knowledge on the nonstationarity of hydro-climatic processes in the Ethiopian Highlands (EH), and the Oceanic Sea Surface Temperature (SST), this thesis employed the nonstationary techniques of Wavelet principal component analysis (WPCA) and coherence analysis to identify the spatial, temporal and frequency variability regimes of these hydro-climatic processes. A fully distributed, physically-based model, which is a modified version of the Interactions Soil-Biosphere-Atmosphere (MISBA), and a lumped- conceptual SAC-SMA model, was used to model the UBNB streamflow. To study the potential effect of climate anomalies on the UBNB, years of rainfall/temperature data, when climate anomalies are active, were re-sampled and used to drive MISBA and SAC-SMA. An artificial neural network calibrated by a genetic algorithm (ANN-GA) model, is developed to forecast the seasonal rainfall of UBNB through teleconnection with selected sectors of SST. Results show that seasonal rainfall predicted by ANN-GA agrees well with the observed rainfall data of UBNB. The Valencia and Schaake model was used to disaggregate the forecasted seasonal rainfall to weekly rainfall, which was found to reasonably capture the UBNB observed weekly rainfall characteristics. ANN-GA was developed to directly forecast the UBNB seasonal streamflow from seasonal oceanic SST and then disaggregated to weekly streamflow. To improve the streamflow forecast, we combined the forecasted seasonal rainfall, in addition to the SST predictors. Results indicate that forecasts based on climate indices alone possess considerable skill (correlation of 0.66) with up to four months lead time, while combining the rainfall and SST as predictors provides better results (correlation of 0.83). The analysis of nonstationary energy helped to determine the effects of global oceanic anomalies on the rainfall/streamflow of the UBNB. Knowledge on these effects on UBNB will be useful to the planning and water resources management of the Nile River, especially under the impact of both climate variability and impending droughts.
  • Elsanabary, M. H. and Gan, T. Y. (2012). "Investigation of Seasonal Rainfall Variability Over the Ethiopian Highlands: Teleconnection Between the Upper Blue Nile Basin Rainfall and the Oceanic Anomalies", Proc. Conf. 2012 CSCE Annual General Conference, June 6-9, 2012, Edmonton, AB, CA.
  • Doctoral
  • Doctor of Philosophy
  • Department of Civil and Environmental Engineering
  • Water Resources Engineering
  • Thian Yew Gan (Departement of Civil and Environmental Engineering)
    Mohamed Al-Hussein (Civil and Environmental Engineering)
    Paul Myers (Earth and Atmospheric Sciences)
  • Thian Yew Gan (Departement of Civil and Environmental Engineering)
    Evan Davies (Civil and Environmental Engineering)
    Paul Myers (Earth and Atmospheric Sciences)
    Yang Liu (Civil and Environmental Engineering)
    Marwan El-Rich (Civil and Environmental Engineering)
    D. J. (Dave) Sauchyn (Senior Research Scientist (PARC) and Professor of Geography (University of Regina)

Apr 24, 2014 4:44 PM


Jul 10, 2012 3:45 PM


Deanna Baron