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The Nile River, the primary water resource and the life artery for 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. This book employed the nonstationary techniques of Wavelet principal component analysis (WPCA) and coherence analysis to identify the spatio-temporal and frequency variability regimes of these hydro-climatic processes. A fully distributed, a modified version of the Interactions Soil-Biosphere-Atmosphere model of Météo-France , and a lumped, SAC-SMA, was used to study the potential hydrologic effect of climate anomalies on the UBNB were re-sampled and used to drive MISBA and SAC-SMA. An artificial neural network calibrated by a genetic algorithm (ANN-GA) model, was developed to forecast the seasonal rainfall of UBNB through teleconnection with selected oceanic sectors of SST. ANN-GA was also forced with seasonal oceanic SST to directly forecast seasonal streamflow which was then disaggregated to weekly streamflow. Knowledge gained on such teleconnection will be useful for the planning and management of its water resources.
About the author
Mohamed Elsanabary, PhD, P.Eng., completed his Bachelor's and Master¿s degrees in Civil Engineering in Civil Engineering from Suez Canal University, Egypt. He earned his PhD in Water Resources Engineering in 2012 from The University of Alberta. Currently, he is an Assistant Professor at Civil Engineering Department, Port Said University.
