TITLE:
A Qualitative Approach to Understanding the Role of DEM Error and Climate Change Impact on Long-Term Floodplain Inundation Mapping
AUTHORS:
Mohammad Hafizur Rahman, Seidou Ousmane, Sohel Rana
KEYWORDS:
DEM, Flood Simulations, Sensitivity Analysis, Surface Roughness, Flood Inundation Maps
JOURNAL NAME:
International Journal of Geosciences,
Vol.16 No.8,
August
15,
2025
ABSTRACT: Watershed management throughout the world has undergone revolutionary changes due to topographic data and the impact of climate change. Research in floodplain inundation mapping reflects these changes. As part of the current research, two aspects are examined: the impact of climate change and the influence of Digital Elevation Model (DEM) error on the Nith River floodplain inundation mapping. The study uses terrain data generated from SWOOP elevation points as well as climate change emissions scenarios regionally assessed by CRCM and MNR (SRES A2 and SR B1). Using Log Pearson Type III, a widely used frequency analysis, floods with a 100-year return period for different climate scenarios and historical storm events were calculated, and a steady-state 1D hydrodynamic HEC-RAS model was applied to simulate extreme event floods. The impacts of DEM errors and climate change on flood simulations were quantified by analyzing the results of the model. A sensitivity analysis of the hydraulic models was performed considering surface roughness and boundary conditions as potential uncertainties. As a result of the impact of climate change, the model indicated a significant increase in flood risk. It is not evident that DEM errors affect model performance, but they should be minimized to produce accurate flood maps. The sensitivity analyses demonstrated that surface roughness influences flood simulations. Geo-processing procedures, HEC-RAS and GeoRAS in ArcGIS, have been used to extract the 100-year flood inundation maps for the current and future conditions and compare them with those for the existing conditions. The 19.8% increase in inundation corresponds specifically to the SRES A2 scenario, representing a high-emission future. The SR B1 scenario (low-emission) was analyzed for comparison, but did not produce the maximum inundation values.