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Landslides

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Social multi-criteria evaluation to identify appropriate disaster risk reduction measures: application to landslides in the Rwenzori Mountains, Uganda

  • Jan MaesEmail author
  • Kewan Mertens
  • Liesbet Jacobs
  • Bosco Bwambale
  • Liesbet Vranken
  • Olivier Dewitte
  • Jean Poesen
  • Matthieu Kervyn
Thematic Issue
  • 131 Downloads

Abstract

Over the past decades, the global exposure of persons and assets to natural hazards, like landslides, has increased faster than that their vulnerability has decreased. Therefore, the Sendai Framework for Disaster Risk Reduction (DRR) made a call in 2015 for more investment in DRR. Recent studies exposed the lack of scientific evaluation data for selecting DRR measures. The objective of this research is to develop a participatory methodology for identifying appropriate DRR measures based on stakeholder groups’ perceptions. More specifically, we propose a social multi-criteria evaluation which combines a two-phased participatory multi-criteria analysis with an institutional analysis for its design and a discourse analysis for interpreting its outcomes. This method is then tested for a case study focusing on landslides in the Rwenzori Mountains region (Uganda) to illustrate both its relevance and practical challenges. The results from the case study highlight the perceived importance of the acceptability of measures above cost, feasibility and effectiveness criteria, by district and village stakeholder groups. Frequently recommended DRR actions, such as disaster risk zonation or relocation, are shown to be perceived negatively by local stakeholders despite being put forward in national policies. This study contributes to the DRR literature as it proposes a new method to support DRR-related decision-making. It also contributes to the understanding of landslide risk reduction in the Rwenzori Mountains region as it presents the first attempt to identify appropriate landslide risk reduction measures for the region.

Keywords

Decision support system Multi-criteria analysis Delphi Discourse 

Supplementary material

10346_2018_1030_MOESM1_ESM.docx (24 kb)
ESM 1 (DOCX 23 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Earth and Environmental SciencesKU LeuvenLeuvenBelgium
  2. 2.Department of GeographyVrije Universiteit BrusselBrusselsBelgium
  3. 3.School of Agricultural & Environmental SciencesMountains of the Moon UniversityFort PortalUganda
  4. 4.Department of Earth SciencesRoyal Museum for Central AfricaTervurenBelgium

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