Using ENSO Indices to Enhance Long-Range Ensemble Streamflow Forecasts in The Blue Nile River

River forecasting centers around the globe have been using hydrologic ensemble forecast systems operationally. Better-enhanced forecasting systems are the ultimate need of the decision maker. This study proposes an enhancement technique for Long-Range Ensemble Streamflow Forecasts in The Blue Nile River. Many studies showed the link between summer rainfall and the large scale climate oscillations. Strong correlation is found between the El-Nino Southern Oscillations (ENSO) and annual flows in the Nile River at Diem on the Sudanese-Ethiopian boarders. Long-range streamflow forecasts produced by The Nile Forecast System at Ministry of Public Works and Irrigation in Egypt are used. Traditionally, baseline forecast weights each trace of the ensemble equally. In this study, we add an enhancement process to the forecasts by changing their weights depending on the correlation between the Streamflow and the ENSO indices (e.g. SST3.4, SOI). Weighting techniques using different distributions of the ENSO indices (e.g. Kernel, Gaussian) are examined. Diagnostic verification measures are used to evaluate this enhancement process.