Explaining and forecasting interannual variability in the flow of the Nile River
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Siam-2015-Explaining and forec.pdf
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Author(s)
Siam, Mohamed Salah
Eltahir, Elfatih A. B.
Date Issued
March 2015
Journal
Hydrology and Earth System Sciences
Publisher
Copernicus GmbH
Citation
Siam, M. S., and E. A. B. Eltahir. “Explaining and Forecasting Interannual Variability in the Flow of the Nile River.” Hydrol. Earth Syst. Sci. 19, no. 3 (2015): 1181–1192.
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Parsons Laboratory for Environmental Science and Engineering (Massachusetts Institute of Technology)
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.5194/hess-19-1181-2015
