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

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.