Open-source GIS-Based Multi-Criteria Flood Risk Model for data-constrained environments

Shamsudeen Abubakar, Samuel Oyatoye, Oreoluwa Adebayo, Chidumebi Ezenwoko, Ayomide Owoyemi, Ben Seun Oyajumo, Joshua Owoyemi, Favour Chiemerie Madubuko, Kelvin Akyea, Afeez Mohammed, Godwin Musa, Chisom Rutherford, Emmanuella Nkanang, Kabir Mumuni

Flooding poses a major hazard across diverse environments and can be particularly difficult to estimate in urban/urbanizing cities without detailed hydrodynamic data/models. This paper presents a GIS-based, multi-criteria model that integrates openly available hydrological, soil, land cover, and drainage network data to produce a relative Flood Risk Index (FRI) at high spatial resolution. A modular Python-based workflow is developed to fetch these data, pre-process spatial layers, normalize heterogeneous indicators, and combine them into a single 0–1 flood risk score. The model emphasizes transparency, reproducibility, and adaptability for risk screening and decision-support in flood-prone, data-scarce regions, and is demonstrated through application on several major Sub-Saharan cities. The overall product is an adaptable, extensible product to provide flood risk guidance to individuals and city planners.