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Teleconnection, Modeling, Climate Anomalies Impact and Forecasting of Rainfall and Streamflow of the Upper Blue Nile River Basin

  • TELECONNECT BLUE NILE BASIN RAINFALL & RUNOFF

  • Author / Creator
    Elsanabary, Mohamed Helmy Mahmoud Moustafa
  • 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.

  • Subjects / Keywords
  • Graduation date
    2012-11
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3377641M
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Civil and Environmental Engineering
  • Specialization
    • Water Resources Engineering
  • Supervisor / co-supervisor and their department(s)
    • Paul Myers (Earth and Atmospheric Sciences)
    • Thian Yew Gan (Departement of Civil and Environmental Engineering)
    • Mohamed Al-Hussein (Civil and Environmental Engineering)
  • Examining committee members and their departments
    • Marwan El-Rich (Civil and Environmental Engineering)
    • Paul Myers (Earth and Atmospheric Sciences)
    • D. J. (Dave) Sauchyn (Senior Research Scientist (PARC) and Professor of Geography (University of Regina)
    • Thian Yew Gan (Departement of Civil and Environmental Engineering)
    • Evan Davies (Civil and Environmental Engineering)
    • Yang Liu (Civil and Environmental Engineering)