An indicative index of physical susceptibility of small islands to coastal erosion induced by climate change: an application to the Pacific islands

被引:15
|
作者
Kumar, Lalit [1 ]
Eliot, Ian [2 ,3 ]
Nunn, Patrick D. [4 ]
Stul, Tanya [2 ]
McLean, Roger [5 ]
机构
[1] Univ New England, Sch Environm & Rural Sci, Armidale, NSW, Australia
[2] Damara WA Pty Ltd, Innaloo, WA, Australia
[3] Univ Western Australia, Sch Earth & Environm, Perth, WA, Australia
[4] Univ Sunshine Coast, Sustainabil Res Ctr, Maroochydore, Qld, Australia
[5] Univ New South Wales, Australian Def Force Acad, Sch Phys Environm & Math Sci, Canberra, ACT, Australia
关键词
Climate change; Pacific; susceptibility; indicative susceptibility; islands; risks; ATOLL; ADAPTATION; MANAGEMENT;
D O I
10.1080/19475705.2018.1455749
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
An objective method is proposed to evaluate the susceptibility of islands to climate change. As used here, susceptibility is an estimate of the potential for physical change of an island coast in response to likely changes in climate-ocean boundary conditions. The evaluation is based on an assumption that the intensity of impact due to climate and ocean processes can be typically related to four physical and quantifiable variables: island rock-type (lithology), island shape (circularity), maximum elevation and area. These four physical variables were used to determine a dimensionless index for each of 1779 islands across 26 countries and 8 island types in the Pacific Ocean. Most islands fell in the high (29%), moderate (23%) and low (23%) susceptibility classes, whilst the remainder were split between the extremes of very high (12%) and very low (13%). Eleven countries had islands with all five levels, while eight had islands with mostly high and very high ratings.The index may be used as a tool for rapid appraisal by international and regional agencies as well as national governments for prioritization of adaptation measures to a changing climate, particularly when combined with climatic and oceanic process variables, together with knowledge of population and infrastructure.
引用
收藏
页码:691 / 702
页数:12
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