SihleNala-byte/lagos-durban-flood-esg-risk-finance

Comparative flood risk assessment of Lagos (Nigeria) and Durban (South Africa) using climate analysis, urbanisation metrics, spatial GIS modelling, regression analysis and scenario-based cost-benefit evaluation. # Urban Flood Risk & Climate Finance: A Comparative Analysis of Lagos, Nigeria and Durban, South Africa A end-to-end analytical pipeline integrating climate science, spatial analysis, statistical modelling, and financial scenario planning to assess urban flood risk and inform insurance, ESG finance, and adaptation investment decisions in two major African coastal cities. --- ## Overview Lagos and Durban are both densely populated, low-lying African coastal cities facing escalating flood risk but for very different structural reasons. This project builds a reproducible, data-driven pipeline to diagnose *why* flooding is happening, whether it's getting worse, how far the damage reaches, and what mitigation investment is economically justified, framed explicitly for insurance pricing, parametric trigger design, ESG green bond eligibility, and TCFD/ISSB physical risk disclosure use cases. ## Research Questions 1. **Why** is flooding happening in both cities? 2. **Has** flooding increased over time? 3. **How far** does flood damage reach, spatially and economically? 4. **What** mitigation solutions could reduce future flood risk? ## Key Findings - **The climate-flood paradox:** Both cities show *declining* annual rainfall totals alongside *increasing* flood frequency, explained by warming-driven storm intensification (Clausius-Clapeyron relation) rather than overall wetter conditions. - **Two distinct risk profiles:** Lagos faces density-driven flood risk on flat, low-lying coastal terrain; Durban faces topography-amplified runoff, with steep hills and narrow valleys funnelling water toward a vulnerable coastal strip. - **Structural vulnerability beyond climate:** OLS regression models show large gaps between predicted and observed damages (Lagos ~14×, Durban ~7× underestimates), pointing to structural urban vulnerability, not climate variables alone, as the primary driver of realised loss. - **Investment case:** A cost-benefit "invest vs. do nothing" scenari …