Assessing hazards and disaster risk on the coast for Pacific small island developing States: the need for a data-driven approach

IF 1.6 Q4 ENVIRONMENTAL SCIENCES
Sally Brown, Susan E. Hanson, David Sear, Christopher Hill, Craig W. Hutton
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Abstract

Small island developing States, such as those in the Pacific, are often prone to multiple hazards that have potential to result in disaster and / or restrict development. Hazard data can be limited in resolution or omitted in or near SIDS’ coasts, but a growing and improved range of datasets are becoming available. Through an analysis of approximately 100 policy documents on hazards and disaster risk management in Pacific island nations, we found: limited information on hazards and how they manifest to disasters at local levels, thus not fully connecting drivers and subsequent risk; at times a non-specific multi-hazard approach prompting the need to address more specific hazards; and restricted temporal and spatial scales of analysis that potentially limit continuity of actions where mitigation methods evolve. These limitations suggest that appropriate and timely high resolution hazard data is needed from the top-down to underpin the design and development of local disaster risk management plans, simultaneous to local, bottom-up knowledge and interpretation to bring the realities of such hazard data to life. Developing and ensuring openly available hazard data will enable island States to develop more robust, inclusive disaster risk management plans and mitigation policies, plus aid inter-island comparison for communal learning.

评估太平洋小岛屿发展中国家海岸的危险和灾害风险:需要采用数据驱动的方法
小岛屿发展中国家,例如太平洋地区的小岛屿发展中国家往往容易发生多种灾害,有可能导致灾难和(或)限制发展。在小岛屿发展中国家海岸或海岸附近,危险数据的分辨率可能有限,也可能被忽略,但越来越多的数据集正在变得可用。通过对太平洋岛国大约100份关于灾害和灾害风险管理的政策文件的分析,我们发现:关于灾害及其在地方一级对灾害的表现的信息有限,因此没有完全将驱动因素和后续风险联系起来;有时,非特定的多危险方法促使需要解决更具体的危险;以及分析的时间和空间尺度有限,这可能会限制缓解方法发展时行动的连续性。这些局限性表明,需要自上而下的适当和及时的高分辨率灾害数据,以支持当地灾害风险管理计划的设计和制定,同时需要当地自下而上的知识和解释,以使此类灾害数据的真实性栩栩如生。开发和确保公开可用的灾害数据将使岛屿国家能够制定更有力、更具包容性的灾害风险管理计划和缓解政策,并为社区学习提供岛屿间比较援助。
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CiteScore
3.80
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0.00%
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