Assessing the skill of seasonal forecasting of streamflow and drought in the Limpopo basin, Southern Africa

The semi-arid Limpopo Basin in Southern Africa experiences frequent droughts, leading to shortfall of water resources available to irrigation, drinking water supply and environmental flow requirements. In this paper we explore three approaches to seasonal forecasting streamflow and derived drought indices in the basin. The first applies the ECMWF seasonal forecast system (S4), an operational global atmospheric model that provides seasonal ensemble forecast with a lead time of six months. We apply a 30 year hindcast set available for S4 in forcing a 0.05^O distributed hydrological model for the basin. The second approach uses the Ensemble Streamflow Prediction (ESP) method. This develops a forecast ensemble of six months lead time based on resampling historic meteorological data over the basin, and we again use this ensemble to force the hydrological model. The third approach again applies the ESP method, but we now use the ENSO index to condition the sampling probabilities.

We focus on comparing forecast skill over the wet season which is the most relevant to water users in the basin. Comparison of the skill of the three forecasting approaches in forecasting drought indices and streamflow shows that S4 is moderately skilful at the lead times up to 3-5 months. The ESP forecasts are skilful when compared to climatology, but only for the short lead times, and the skill decays rapidly with lead time. Forecasts based on the conditional ESP ensemble have improved skill when compared to ESP, though S4 forecasts remain superior. Through exploring drought indices that are used by reservoir operators in determining curtailments to water users we show how the forecasts can be meaningful to reservoir operators and irrigators in the basin.