Long-Range Forecasting of the Nile River Flows Using Climatic Forcing
Open Access
- 1 July 2003
- journal article
- Published by American Meteorological Society in Journal of Applied Meteorology and Climatology
- Vol. 42 (7), 890-904
- https://doi.org/10.1175/1520-0450(2003)042<0890:lfotnr>2.0.co;2
Abstract
Correlation analysis is used to determine the linear relationship between the Nile River flows and leading climatic indicators, such as SST and precipitation, in an effort to establish a basis for quantitative long-term streamflow prediction. The analysis of the lead–lag correlations between the Blue Nile River flows during the “flood season” [July–August–September–October (JASO)] and SSTs led to the identification of a number of regions in the oceans that are significantly correlated and suggests that the SSTs may be useful for predicting the Blue Nile flows. The significant correlation regions between SST in the Pacific and Blue Nile JASO flows evolve through time in a manner that is consistent with the ENSO development; that is, the evolution of the ENSO signal in the Pacific Ocean is reflected in the evolution of the referred cross-correlation field. In addition, the Blue Nile River JASO flow is significantly correlated with the previous year August–November Guinea precipitation, which suggests that the Guinea precipitation is another potential predictor of the Blue Nile River flows with 11 months of lead time. Furthermore, models based on multiple linear regression (MLR) and principal component analysis (PCA) are used to forecast the Blue Nile flows based on SST in the three oceans and the previous year of Guinea precipitation. The models based on PCA showed significant improvement in forecast accuracy over MLR models that were developed in terms of the original variables. The predictability is shown to be the highest for forecasts made in the preceding season and decreases as the lead time increases. The coefficients of multiple determination R2 for validation based on PCA models vary in the range 84%–59% for forecast lead times of 4–16 months. Further analysis using only SST predictors for the period 1913–89 indicates that the predictability of the Blue Nile River JASO flows is more affected by the variability of SSTs in the Pacific Ocean than by those of the other oceans. The conclusion is that long-range forecasting of the Blue Nile River flows with lead times over 1 yr is possible with a high degree of explained variance by using SST in a few regions in the Pacific Ocean and the previous year of Guinea precipitation.Keywords
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