Developing a Spatially Explicit Humanitarian Flood Vulnerability Index for Refugee Settlements using Fuzzy Multi-Criteria Decision Analysis

The increasing number of refugees and the impacts of climate change necessitate improved flood vulnerability assessments for refugee settlements. Refugee settlements, often located in hazardous areas with limited infrastructure, tend to face high vulnerability. However, approaches to spatially assess flood vulnerability within these settlements are limited. This paper presents the development of a Humanitarian Flood Vulnerability Index (HFVI) tailored to refugee settlements, incorporating expert knowledge through the application of the Fuzzy Analytical Hierarchical Process (FAHP). The methodology takes into account the inclusion of expert judgment in weighting the indicators and integrates uncertainty analysis. A novel approach combines fuzzy logic with the Oneat- a-Time (OAT) sensitivity method, providing a spatially explicit representation of weight uncertainties, to enable more informed decision-making and better-targeted interventions to ultimately improve the protection of refugees from flooding. The HFVI incorporates multiple vulnerability indicators, including physical and social dimensions, to create a composite raster-based index quantifying flood vulnerability in refugee settlements. A case study was performed in the UNHCR refugee settlement Mahama in Rwanda to illustrate the application of the HFVI using global and local data sets. The results demonstrate the effectiveness of the HFVI in identifying vulnerability hotspots. Limitations are discussed concerning the reproducibility and validity of the results, highlighting areas for improvement, ultimately aiming to enhance targeted flood risk mitigation strategies and resilience of refugee settlements to increasing flood risks.