Sensitivity analysis of indicator weights for the construction of flood vulnerability indexes: A participatory approach

Abstract

The assessment of flood vulnerability is a complex task that involves numerous uncertainties. Within this context, sensitivity analyses are crucial to better understand the variability of vulnerability index outcomes according to different input parameters. The present study sheds light on the importance of assessing the sensitivity of different criteria weights to construct flood vulnerability indexes using the Maquiné basin (Brazil) as a case study. Specifically, we compared vulnerability scores based on weights derived from a participatory survey with 44 stakeholders to those based on an equal weighting scheme. Results helped us identify areas with low and high uncertainty and the variables contributing to this. Overall, the preference for indicator weights did not vary significantly among stakeholders with distinct socioeconomic characteristics. Furthermore, the choice of weights only had an impact on the spatial distribution of flood vulnerability in certain regions. Compared to equal weights, the flood vulnerability outcomes obtained by averaging the stakeholder scenarios were similar, indicating that the results were robust and not highly sensitive to the choice of weights. By adopting a participatory approach, we were able to consider multiple stakeholders' views, which helped to provide a more comprehensive perspective of flood vulnerability and potentially increased the acceptance of the results. Based on our findings, end-users can better understand the relative importance of each indicator and how they contribute to vulnerability. Furthermore, our results can help identify points where stakeholders disagree, which can be used to facilitate dialogue and consensus building. The methodology applied is straightforward and could be easily adapted to other multi-criteria decision-making problems.

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“…In fact, data‐driven methods excel in harnessing empirical evidence and large data sets for robust analyses but may overlook the nuanced contextual understanding that knowledge‐driven methods offer. Conversely, knowledge‐driven methods promote richer insights through participatory engagement and expert judgment but often have limited transferability between different cultural contexts or locations (Fekete et al., 2021; Moreira et al., 2023). Although the examples of applications here focus on drought and flood hazards, these methods can be used for other hazard types (e.g., earthquakes, storms, heatwaves, and landslides).…”

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“…In fact, data-driven methods excel in harnessing empirical evidence and large data sets for robust analyses but may overlook the nuanced contextual understanding that knowledge-driven methods offer. Conversely, knowledge-driven methods promote richer insights through participatory engagement and expert judgment but often have limited transferability between different cultural contexts or locations (Fekete et al, 2021;Moreira et al, 2023). Although the examples of applications here focus on drought and flood hazards, these methods can be used for other hazard types (e.g., earthquakes, storms, heatwaves, and landslides).…”

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“…District Census Handbook [71,72] Health institution Access to functional healthcare infrastructure is essential for the overall health and well-being of any community.…”