The role of flood forecasting is becoming increasingly important as the concept of risk-based approach is accepted in flood risk management. The risk-based approach not only requires efficient and abundant information for decision making in a risk framework. but needs the uncertainty appropriately accounted for and expressed. The rapid development in numerical weather prediction and weather radar technology make it feasible to provide precipitation pre- dictions and observations for flood warning and forecasting that benefit from the extended lead-time. Although the uncertainty issues related to standalone models have been addressed. little attention has been focused on the complex behaviour of coupled modelling systems when the uncertainty-bearing information propagates through the model cascade. The work presented in this thesis focuses on the issue of uncertainty propagation in this complex coupled modelling environment. A prototype system that integrates the high reso- lution numerical weather prediction. weather radar. and distributed hydrological models. was developed to facilitate the study. The uncertainty propagation and interactions were then analysed covering the uncertainty associated with the data. model structures, chaotic dynamics and coupling processes. The ensemble method was concluded to be the choice for the coupled system to produce forecasts able to account for the uncertainty cascaded from the precipitation prediction to the hydrological and hydraulic models. Finally. recommendations are made in relation to the exploration of complex coupled systems for uncertainty propagation in flood risk management, Keywords: Real-time flood forecasting, uncertainty propagation, NWP. weather radar. coupled models.
|Date of Award||2007|
|Supervisor||Ian Cluckie (Supervisor) & Dawei Han (Supervisor)|