Articles | Volume 19, issue 3
Hydrol. Earth Syst. Sci., 19, 1181–1192, 2015
https://doi.org/10.5194/hess-19-1181-2015
Hydrol. Earth Syst. Sci., 19, 1181–1192, 2015
https://doi.org/10.5194/hess-19-1181-2015

Research article 03 Mar 2015

Research article | 03 Mar 2015

Explaining and forecasting interannual variability in the flow of the Nile River

M. S. Siam and E. A. B. Eltahir M. S. Siam and E. A. B. Eltahir
  • Ralph M. Parsons Laboratory, Massachusetts Institute of Technology, 15 Vassar St., Cambridge, MA 02139, USA

Abstract. This study analyzes extensive data sets collected during the twentieth century and defines four modes of natural variability in the flow of the Nile River, identifying a new significant potential for improving predictability of floods and droughts. Previous studies have identified a significant teleconnection between the Nile flow and the eastern Pacific Ocean. El Niño–Southern Oscillation (ENSO) explains about 25% of the interannual variability in the Nile flow. Here, this study identifies a region in the southern Indian Ocean, with a similarly strong teleconnection to the Nile flow. Sea surface temperature (SST) in the region (50–80° E and 25–35° S) explains 28% of the interannual variability in the flow of the Nile River and, when combined with the ENSO index, the explained variability of the flow of the Nile River increases to 44%. In addition, during those years with anomalous SST conditions in both oceans, this study estimates that indices of the SSTs in the Pacific and Indian oceans can collectively explain up to 84% of the interannual variability in the flow of the Nile. Building on these findings, this study uses the classical Bayesian theorem to develop a new hybrid forecasting algorithm that predicts the Nile flow based on global model predictions of indices of the SST in the eastern Pacific and southern Indian oceans.

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Short summary
This paper explains the different natural modes of interannual variability in the flow of the Nile River and also presents a new index based on the sea surface temperature (SST) over the southern Indian Ocean to forecast the flow of the Nile River. It also presents a new hybrid forecasting algorithm that can be used to predict the Nile flow based on indices of the SST in the eastern Pacific and southern Indian oceans.