Day-to-day water management is challenged by meteorological extremes, causing floods and droughts. Often operational water managers are informed too late about these upcoming events to be able to respond and mitigate their effects, such as by taking flood control measures or even requiring evacuation of local inhabitants. Therefore, the use of weather forecast information with hydrological models can be invaluable for the operational water manager to expand the forecast horizon and to have time to take appropriate action. This is called Anticipatory Water Management.
Anticipatory actions may have adverse effects, such as when flood control actions turn out to have been unnecessary, because the actual rainfall was less than predicted. Therefore the uncertainty of the forecasts and the associated risks of applying Anticipatory Water Management have to be assessed. To facilitate this assessment, meteorological institutes are providing ensemble predictions to estimate the dynamic uncertainty of weather forecasts. This dissertation presents ways of improving the end-use of ensemble predictions in Anticipatory Water Management.
1. Introduction;
2. Anticipatory Water Management;
3. Framework for Developing Anticipatory Water Management (AWM);
4. Case Study 1 - Rijnland Water System;
5. Case Study 2 - Upper Blue Nile;
6. Conclusions and Recommendations.
Schalk Jan van Andel (1978) graduated (with distinction) for his MSc degree in Integrated and quantitative water management from Wageningen University (2003). He specialised in the development and application of hydrological and hydrodynamic models. After graduating he worked as a specialist water management with HydroLogic, The Netherlands, and as a project officer with the Netherlands Water Partnership (NWP). In 2004 he joined UNESCO-IHE (Hydroinformatics and Knowledge Management department where he started the PhD research presented in this dissertation. At present Schalk Jan is a lecturer in Hydroinformatics at UNESCO-IHE, Delft, The Netherlands. His research interest concerns the application of meteorological data and forecasts in operational water management.
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