Abstract
{ "background": "Urban drainage infrastructure in coastal West Africa faces increasing failure risks due to more intense precipitation events driven by climate change. Existing design standards often rely on historical rainfall data, which inadequately represent future climate uncertainty, leading to systems vulnerable to surcharge and flooding.", "purpose and objectives": "This study aimed to develop and demonstrate a probabilistic framework for designing climate-resilient urban drainage systems. The objective was to integrate future rainfall projections with one-dimensional hydraulic modelling to quantify and mitigate flood risks under changing climatic conditions.", "methodology": "A stochastic rainfall model was forced with downscaled regional climate model projections for a high-emission scenario. Intensity-duration-frequency curves were derived probabilistically. A coupled modelling approach was implemented, using the rainfall series as input to a hydraulic model of a representative drainage network in a coastal urban area. System performance was assessed using a logit model, $\\logit(p) = \\beta0 + \\beta1 \\cdot I{10} + \\epsilon$, where $p$ is the probability of system surcharge, and $I{10}$ is the 10-year return period intensity.", "findings": "The probabilistic analysis revealed a 95% credible interval for the 10-year design storm intensity increase of 18% to 32% by mid-century. The hydraulic modelling showed that conventional drainage designs would experience a 40% increase in the frequency of node flooding events under these projected rainfall conditions.", "conclusion": "Current drainage design practices in the region are insufficient to cope with projected climate change impacts, significantly elevating future flood risks. A shift towards probabilistic, climate-informed standards is essential.", "recommendations": "Adopt the developed probabilistic framework in national drainage design guidelines. Engineers should utilise climate projection ensembles to derive design storms, moving beyond deterministic historical data. Prioritise retrofitting existing systems in low-lying coastal zones.", "key words": "climate resilience, urban drainage, probabilistic design, hydraulic modelling, rainfall projections, West Africa", "cont