Flood inundation modeling and hazard mapping under uncertainty in the Sungai Johor basin, Malaysia; Dissertation, UNESCO-IHE Institute for Water Education, Delft and TU Delft.

Flood is a natural disaster that occurs almost regularly in Malaysia particularly during the monsoon seasons. Hence, it is of no surprise that flood is considered one of the most significant natural hazards in the country in terms of number of affected population, fatalities and economic damage. One of the efforts to minimize flood losses is providing useful information through floodplain inundation maps, i.e. spatial distribution of flood hazard. Traditionally, many modellers have used deterministic approaches in flood inundation modelling. Deterministic approaches are based on a single simulation with the “best fit model” and do not explicitly consider uncertainties in model parameters, terrain data, and model structure. When model results are then used to generate a flood hazard map, neglecting uncertainties may lead to precise, but inaccurate maps and lead to wrong or misleading information to decision makers. Thus, the scientific literature has recently proposed a number of probabilistic methods to recognize, assess and account for uncertainties affecting flood inundation modelling. In this context, this research work aims to contribute to this research work by further exploring the impact of various sources of uncertainty on the results of hydraulic models. The case study of this research is the Sungai Johor river basin in Malaysia. Both 1‐D and 2‐D hydraulic models were utilized. In using 1‐D hydraulic models, the geometric description of rivers and floodplains is performed by using a number of cross‐sections, which play an important role in the accuracy of model results. In this work, criteria for cross‐section spacing were tested and verified via numerical experiments. Similarly, digital elevation models (DEMs) used as geometrical input significantly affect the results of flood inundation modelling exercises. DEM is essential input that provides topographical data in flood inundation modelling. However, it can be derived from several sources either through remote sensing techniques (space‐borne or air‐borne imagery) or from more traditional ground survey methods. These DEMs are characterized by different precision and accuracy. This study quantified the effect of using different DEM data source and resolution in a 1‐D hydraulic modelling of floods. This study also explored the differences arising from the use of deterministic and uncertainty approaches in deriving design flood profiles and flood inundation maps. To this end, the generalized likelihood uncertainty estimation (GLUE) technique was used and the uncertainty in model predictions was derived through Monte Carlo analysis. In particular, this work focused on impact of uncertain inflow data and roughness coefficients in the accuracy of flood inundation models. As part of this research, 2‐D hydraulic modelling software (LISFLOOD‐FP) was also used to assess the effect of spatial data re‐sampling (e.g. from high to low resolution) on model outcomes. This study evaluated two re‐sampling techniques with combination of three different aggregation functions, i.e. minimum, maximum and mean values. This research work has not only provided useful results, but has also suggested further research and improvement of flood risk and mapping practices. The knowledge generated by, as well as the findings of this thesis, will be transferred to other study areas in Malaysia