Computers are increasingly used in the simulation of natural phenomena such as floods. However, these simulations are based on numerical approximations of equations formalizing our conceptual understanding of flood flows. Thus, model results are intrinsically subject to uncertainty and the use of probabilistic approaches seems more appropriate. Uncertain, probabilistic floodplain maps are widely used in the scientific domain, but still not sufficiently exploited to support the development of flood mitigation strategies. This thesis analyses major sources of uncertainty in flood inundation models and shows methods to generate probabilistic floodplain maps. Then, the thesis shows how to use these maps to support decision making in terms of floodplain development under flood hazard threat.

1 Introduction
2 A review of flood inundation modelling
3 Case studies and data availability
4 Uncertainty in flood modelling
5 Flood hazard maps and damage
6 Usefulness of probabilistic flood hazard maps
7 Conclusions and recommendations

Micah M. Mukolwe is a trained civil engineer with interests in civil infrastructure design, implementation, project planning and management, and the effect (and mitigation) of natural hazards on floodplain receptors using hydroinformatics tools.