Articles | Volume 21, issue 3
Research article
17 Mar 2017
Research article |  | 17 Mar 2017

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Mathias Seibert, Bruno Merz, and Heiko Apel

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Cited articles

Belayneh, A., Adamowski, J., Khalil, B., and Ozga-Zielinski, B.: Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models, J. Hydrol., 508, 418–429,, 2014.
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Chen, J., Li, M., and Wang, W.: Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast, Math. Probl. Eng., 2012, 915053,, 2012.
Diro, G. T., Black, E., and Grimes, D. I. F.: Seasonal forecasting of Ethiopian spring rains, Meteorol. Appl., 83, 73–83,, 2008.
Short summary
Seasonal early warning is vital for drought management in arid regions like the Limpopo Basin in southern Africa. This study shows that skilled seasonal forecasts can be achieved with statistical methods built upon driving factors for drought occurrence. These are the hydrological factors for current streamflow and meteorological drivers represented by anomalies in sea surface temperatures of the surrounding oceans, which combine to form unique combinations in the drought forecast models.