Generating High-Resolution DEMs from Two Different Resolution Data for 2D Flood Mapping

Flood hazard mapping is essential for reducing flood risks by identifying vulnerable areas and guiding response strategies. However, obtaining high-resolution topographic data over large areas can be costly, and reducing this expense while maintaining accuracy is crucial for effective 2D hydraulic mapping. The limited availability of topographic data in river areas makes it difficult to delineate flood inundation. This research aims to investigate the best model for extending high-resolution Digital Elevation Model (DEM) data as input for flood hazard mapping. To enhance DEM resolution, the best model was selected by comparing Root Mean Square Error (RMSE) values from various interpolation methods, namely nearest neighbour interpolation (NNI), bicubic, and bilinear in spatial analysis. The model was then validated using 40 data points. Subsequently, the best model was used to generate a DEM for a larger scale as input for 2D modeling with HEC-RAS. The flood inundation model was validated twice: first, based on water level measurements at the Automatic Water Level Recorder (AWLR) Rowotamtu, and second, based on field observations of extreme flood events. The model results show that the best interpolation method for obtaining a high-resolution DEM is bilinear. The first flood data validation produces an RMSE value of 0.113, while the second is slightly higher at 0.316. Both results indicate good model accuracy, and the flood inundation maps generated can be used to demonstrate flood hazards.