A framework for understanding water-related multi-hazards in a sustainable development context. (April 2020)

• Record Type: Journal Article
• Authors: Docherty, Julia M; Mao, Feng; Buytaert, Wouter; Clark, Julian RA; Hannah, David M
• Is Part Of: Progress in physical geography. Volume 44:Number 2(2020)
• Page Start: 267
• Page End: 284
• Publication Date: 2020-04
• Subjects: Multi-hazards -- disaster risk reduction -- sustainable development -- bibliometric analysis; Physical geography -- Periodicals; 910.02
• DOI: 10.1177/0309133319900926
• Languages: English
• ISSNs: 0309-1333

Abstract

Hazards often do not occur in isolation and, for this reason, a multi-hazard approach is vital in realising their impact and providing solutions for disaster risk reduction and sustainable development. We present a novel framework that emerges from a bibliometric analysis of the multi-hazard literature and a critical appraisal of the existing approaches. It was found that multi-hazard research has expanded greatly over the last 20 years, furthering our understanding of the subject with important applications in risk assessment and management. These studies have contextualised multi-hazards, developed models and frameworks to analyse them, provided case studies to test multi-hazard-based approaches and produced reviews. It was found that landslides and floods are the most frequently co-occurring hazards within the bibliographic dataset, yet understanding of their interactions, hydrometeorological drivers and landscape controls remains poorly conceptualised. Therefore, we propose a new framework for investigating water-related multi-hazards that leverages and synthesises existing methods to address the challenges identified to date. We also find a geographical bias, with less multi-hazard research in lower- and middle-income countries and remote environments due to data scarcity and limited accessibility. Our framework therefore includes the ability to address geographically specific key considerations including available and accessible data, community variability and cross-sectoral collaborations. In doing so it offers guidance on structuring future analyses to improve our understanding of multi-hazards, reduce disaster risk, increase community resilience and make progress towards sustainable development.