Improved Tidal and Non-Tidal Representation of Numerical Models through Data Model Integration

Abstract

The strategic importance of Singapore regional waters (SRW) has led to numerous studies to understand the physical processes that drive, and are driven, by the hydrodynamics in the SRW. However, due to geo-political realities and its highly complex tidal and non-tidal variation, relatively few studies encompass the region as a whole. The main objective of the research presented in this thesis is to understand, examine and develop effective and efficient methods to improve tidal and non-tidal representation in SRW through data model integration (DMI) approach. In conclusion, several techniques of DMI have been successfully developed and implemented to improve hydrodynamic numerical model performance and to better understand (i) the behaviour of the tide in the region and its sensitivities to changes in tidal boundary forcing and to local depth and friction variation in the narrow regions of the Malacca Strait (ii) the physics of the non-tidal barotropic water levels, currents and their forcing mechanisms for the highly complex Singapore regional waters and (iii) the feasibility of applying mutual information theory and genetic programming as an offline data driven modelling tool to capture the non-tidal barotropic dynamics and then using them for updating the numerical model prediction in real time applications.