DATA ASSIMILATION INTO A NUMERICAL SHALLOW-WATER FLOW MODEL - A STOCHASTIC OPTIMAL-CONTROL APPROACH

To assimilate water level data into numerical shallow water flow model s Kalman filtering and model fitting can be employed. An advantage of Kalman filtering is its stochastic nature. By introducing a system noi se process into the system equations it is possible to take into accou nt the inaccuracies of the underlying deterministic system. However, K alman filtering can only be employed for linear or weakly nonlinear pr oblems. Model fitting is more suitable for nonlinear problems but it i s a deterministic method. To combine the best of both approaches, a da ta assimilation procedure based on stochastic optimal control theory h as been developed. The new approach is applied to assimilate water lev el data into a storm surge prediction model.