Integrating Earth Observation with Hydrodynamic Modelling for National-Scale Fluvial Flood Risk Assessment in Nigeria

National-scale fluvial flood risk assessment in Nigeria is constrained by sparse river discharge gauging networks, the absence of large-scale high-resolution terrain data, and the computational demands of physically-based hydrodynamic modelling across a country with seventeen major river basins, creating significant evidence gaps for national flood risk governance. This dissertation integrates Earth Observation with hydrodynamic modelling to produce the first physically-based national-scale fluvial flood risk assessment for Nigeria, making original methodological and empirical contributions. Virtual gauging stations derived from ICESat-2 laser altimetry observations are developed to supplement sparse conventional gauging, providing river water surface elevation calibration data across thirty-eight reaches. A multi-scale hydrodynamic modelling cascade from global LISFLOOD-FP simulations to reach-scale HEC-RAS 2D simulations is developed and implemented, using a novel computational domain decomposition strategy that manages national coverage within feasible run-time constraints. COP-DEM at 30-metre resolution constitutes the baseline terrain input, corrected for vegetation and building artefacts using a bias correction model calibrated against airborne LiDAR strips. National-scale flood inundation maps are produced for ten, fifty, and one hundred year return periods, and probabilistic risk surface integration with building footprint, population, and GDP exposure data generates a national flood risk atlas. Validation against Sentinel-1 SAR-derived flood extents for the 2020 and 2022 catastrophic events demonstrates satisfactory spatial performance. The dissertation provides NEMA and the Federal Ministry of Finance with a peer-reviewed national flood risk evidence base for infrastructure investment prioritisation. Keywords: fluvial flood risk, hydrodynamic modelling, Earth observation, national scale, Nigeria.