📖 ABSTRACT/OVERVIEW
Coastal flood risk in Lagos arises not from a single hazard but from the simultaneous or cascading interaction of multiple physical drivers (storm surge, fluvial flooding, tidal elevation, groundwater rise, extreme rainfall) whose compound occurrence is inadequately captured by conventional univariate return period analysis, leading to systematic underestimation of actual risk. This dissertation develops a novel compound coastal flood risk framework for Lagos that explicitly models the nonlinear dependencies among flood drivers, characterises the full multivariate joint probability distribution of compound flood events, and propagates uncertainty through impact assessment to derive probabilistic risk metrics. Copula-based multivariate statistical models are fitted to 40-year records of daily rainfall, storm surge, river discharge (Ogun and Osun Rivers), and tidal level to characterise their dependence structure and simulate the joint probability of compound flood driver combinations. A physically consistent compound flood event simulator generates an ensemble of 10,000 synthetic compound events spanning the full range of driver combinations, which are then individually simulated using the validated Delft3D-FM Lagos coastal flood model to compute inundation extent and depth. Property exposure, vulnerability functions for different building types, and population distribution are integrated in a probabilistic impact model to estimate annual expected damages and fatalities under current conditions and projected 2050 and 2100 climate scenarios incorporating sea level rise and changes in rainfall extremes from CMIP6. Equity analysis disaggregates flood risk by income quartile and housing type to identify disproportionate impacts on low-income communities in informal settlements. The framework establishes a replicable methodology for compound flood risk assessment in West African coastal megacities. Keywords: compound flooding, nonlinear dynamics, coastal flood risk, Lagos, copula modelling
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