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UNESCO-IHE Institute for Water Education, Delft (2013)

Rainfall and streamflow forecasting for operational water management in the Incomati Basin, Southern Africa

Sunday, R.K.M. 

Titre : Rainfall and streamflow forecasting for operational water management in the Incomati Basin, Southern Africa

Auteur : Sunday, R.K.M. 

Université de soutenance : UNESCO-IHE Institute for Water Education, Delft

Grade : Master of Science (MS) 2013

Résumé partiel
When future water situation is unclear to water managers and dam operators, problems on water allocation among competing users may arise due to unforeseen water shortages. Thus, rainfall and streamflow forecasting may help to manage the uncertainty. Forecasting estimates how much water is likely to fall as rainfall and flow passing a specific river location during a particular time based on recent meteorological and catchment characteristics. Incomati River Basin in Southern African is almost in a closing status ; thus rainfall and streamflow forecasting are significant and relevant. The main objective of this research was to study the scope of rainfall and streamflow forecasting in the Incomati Basin by reviewing forecasting methods, by examining the needs and usefulness of forecasting, and by testing promising methods for rainfall and streamflow forecasting. The study used statistical methods of correlation and regression analyses. Also to explore the needs and uses, interviews and discussions with water managers, dam operators, water users and other stakeholders were carried out. Data used include Sea Surface Temperature (SST), El Niño Southern Oscillation (ENSO), air temperature, precipitation and streamflow. The study was inthree stages ; field survey and interviews, correlation and regression analyses, and rainfall and streamflow forecasting. The correlation analysis covered selected climatic and streamflow stations across whole Incomati Basin. However, models for rainfall and streamflow forecasting were tested for the Kaap sub-catchment located in the Crocodile catchment. Forecasting equations per method per time were generated. The forecasts are presented in terciles of aboveaverage, average and below average. The forecasts were verified using standard forecast verification scores such as probability of detection (POD), probability of false detection (POFD), false alarm rate (FAR) and accuracy. The survey results showed that about 97% of water stakeholders need and use rainfall forecasts. The major uses were personal plans like travelling (29%) and dressing (23%). The usefulness in water sector was reported for water allocation (23%), farming (11%) and flood monitoring (9%).On the other hand only 5% showed the need for streamflow forecasting. The rainfall forecastswere presented to have medium to high benefits. Generally, users affirmed the accuracy and benefits of weather forecasts and had no major concerns on the impacts of wrong forecasts. However, respondents indicated the need to improve the accuracy and accessibility of the forecast. Likewise, water managers expressed the need for both rainfall and flow forecasts but indicated that they face hindrances due to financial and human resource constraints.

Sujets  : river basins rainfall streamflow forecasting forecasting models Southern Africa

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