Title of article :
Improving Forecasts of Nile Flood Using SST Inputs in TFN Model
Author/Authors :
Rousselle، J. نويسنده , , Awadallah، A. G. نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2000
Pages :
-370
From page :
371
To page :
0
Abstract :
Egypt depends on the Nile River for all of its water resources. Using the streamflowsʹ history, the large fluctuations of the Nile flood cause the best predictions to be unsatisfactory. The purpose of this paper is to stochastically forecast the Nile summer runoff one-season-ahead using, as inputs, an El Nino-southern oscillation (ENSO) sea surface temperatures (SSTs) signal in the East Pacific and SSTs in the South Indian Ocean. Causality between inputs and outputs is established, and a multipleinput transfer function with noise (TFN) model is built for forecasting purposes. The model explains 63% of the variability of the Nile flood with relatively stable parameters. The mean of absolute percentage error of forecasts is 6% calculated on a data set that was not used in the parameter estimation. The model is parsimonious, and its behavior agrees with the most recent studies in climatology. The forecasting ability of the model is high for extreme floods and severe drought years, except when the South Atlantic Ocean displays a strong warm signal opposite to the El Nino-southern oscillation cold signal.
Keywords :
Capital Budgeting, Real Options , Management Information System , Computer Information Systems , Decisions Support Systems
Journal title :
JOURNAL OF HYDROLOGIC ENGINEERING
Serial Year :
2000
Journal title :
JOURNAL OF HYDROLOGIC ENGINEERING
Record number :
59466
Link To Document :
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