Evaluation of a methodology to translate rainfall forecasts into runoff forecasts for South Africa.
South Africa experiences some of the lowest water resource system yields in the world as a result of the high regional variability of rainfall and runoff. Population growth and economic development are placing increasing demands on the nation's scarce water resources. These factors, combined with some of the objectives of the new National Water Act (1998), are highlighting the need for efficient management of South Africa's water resources. In South Africa's National Water Act (1998) it is stated that its purpose is to ensure that the nation's water resources are protected, used, conserved, managed and controlled in a way, which takes into account, inter alia, i. promoting the efficient, sustainable and beneficial use of water in the public interest, and ii. managing floods and droughts. Efficient and sustainable water resource and risk management can be aided by the application of runoff forecasting. Forecasting thus fits into the ambit of the National Water Act and, therefore, there is a need for its operational application to be investigated. In this document an attempt is made to test the following hypotheses: Hypothesis 1: Reliable and skilful hydrological forecasts have the ability to prevent loss of life, spare considerable hardship and save affected industries and commerce millions of Rands annually if applied operationally within the context of water resources and risk management. Hypothesis 2: Long to medium term rainfall forecasts can be made with a degree of confidence, and these rainfall forecasts can be converted into runoff forecasts which, when applied within the framework of water resources and risk management, are more useful to water resource managers and users than rainfall forecasts by themselves. The validity of Hypothesis 1 is investigated by means of a literature review. South Africa's high climate variability and associated high levels of uncertainty as well as its current and future water resources situation are reviewed in order to highlight the importance of runoff forecasting in South Africa. Hypothesis 1 is further examined by reviewing the concepts of hazards and risk with a focus on the role of effective risk management in preventing human, financial and infrastructural losses. A runoff forecasting technique using an indirect methodology, whereby rainfall forecasts are translated into runoff forecasts, was developed in order to test Hypothesis 2. The techniques developed are applied using probabilistic regional rainfall forecasts supplied by the South African Weather Service for 30 day periods and categorical regional forecasts for one, three and four month periods for I regions making up the study area of South Africa, Lesotho and Swaziland. These forecasts where downscaled spatially for application to the 1946 Quaternary Catchments making up the study area and temporally to give daily rainfall forecast values. Different runoff forecasting time spans produced varying levels of forecast accuracy and skill, with the three month forecasts producing the worst results, followed by the four month forecasts. The 30 day and one month forecasts for the most part produced better results than the more extended forecast periods. In the study it was found that hydrological forecast accuracy results seem to be inversely correlated to the amount of rainfall received in a region, i.e. the wetter the region the less accurate the runoff forecasts. This trend is reflected in both temporal and spatial patterns where it would seem that variations in the antecedent moisture conditions in wetter areas and wetter periods contribute to the overall variability, rendering forecasts less accurate. In general, the runoff forecasts improve with corresponding improvements in the rainfall forecast accuracy. There are, however, runoff forecast periods and certain regions that produce poor runoff forecast results even with improved rainfall forecasts. This would suggest that even perfect rainfall forecasts still cannot capture all the local scale variability of persistence of wet and dry days as well as magnitudes of rainfall on individual days and the effect of catchment antecedent moisture conditions. More local scale rainfall forecasts are thus still needed in the South African region. In this particular study the methods used did not produce convincing results in terms of runoff forecast accuracy and skill scores. The poor performance can probably be attributed to the relatively unsophisticated nature of the downscaling and interpolative techniques used to produce daily rainfall forecasts at a Quaternary Catchment scale. It is the author's opinion that in the near future, with newly focussed research efforts, and building on what has been learned in this study, more reliable agrohydrological forecasts can be used within the framework of water resources and risk management, preventing loss of life, saving considerable hardship and saving affected industry and commerce millions of rands annually.