Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Civil Engineering

The nile river provides Egypt with most of its water resources. Therefore, long and medium term forecasts of Nile {uFB02}ows at Aswan have been recognized as of significant importance to allow better management and operation of the water resource facilities. In this study, a wide range of climate indices and atmospheric fields were used as potential predictors for long range forecasting of Nile streamflow for one flood season ahead. Furthermore, the approach followed in this study will focus on searching for potential predictors, reducing the pool of potential predictors by using statistical analysis, applying principal component analysis (PCA), canonical correlation analysis (CCA), and multiple linear regression analysis for forecasting the Nile flow. Moreover, copula functions are used to construct a joint distribution of bivariate random variables and to describe the multivariate correlation structure between the Nile flow and different predictors, which can be very useful for improving long range Nile river flow forecasting

Issued also as CD