Crisis Probability Curves (CPCs): A Model for Assessing Vulnerability Thresholds Across Space and Over Time

被引:0
作者
Acosta, Lilibeth A. [1 ,2 ,3 ]
Galli, Fausto
机构
[1] Potsdam Inst Climate Impact Res PIK, D-14473 Potsdam, Germany
[2] UPLB, Sch Environm Sci & Management, Los Banos, Laguna, Philippines
[3] Univ Salerno DISES, Dept Econ & Stat, Salerno, Italy
来源
JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT | 2013年 / 16卷 / 01期
关键词
Vulnerability; Adaptive Capacity; Drought; Climate Change; Susceptibility; Binary choice model; CLIMATE-CHANGE; SUSCEPTIBILITY;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The paper discusses the concept, methods and application of the Crisis Probability Curves (CPCs) to assess vulnerability to droughts in selected regions in India, Portugal, and Russia using published data on susceptibility and water stress indices. The CPCs, which are estimated from regression models and represented in a diagram as contour plots, are a spatiotemporal vulnerability yardstick that estimates vulnerability levels and thresholds to the combined impacts of environmental stress and human susceptibility (or lack of adaptive capacity). As compared to the CPCs for Russia, those for India and Portugal tilt more towards the water stress axis. This implies that the level of vulnerability in the latter countries tends to be more sensitive to the changes in water stress level than socio-economic susceptibility. For a particular water stress level, however, the probability of crisis occurring in India is higher than in Portugal. India has thus the lowest vulnerability threshold. Using pooled and panel regression, the information for three case study regions was combined to develop a common measure of vulnerability thresholds. Building common or generic thresholds will allow comparison of vulnerability, across regions, which can be useful for policy in terms of developing priority list for providing adaptation support in vulnerable regions. However, the results revealed that there is a risk of under- or overestimating vulnerability thresholds when comparing regions not only. with different level, but also varying sources of vulnerability Thus, more crucial than developing generic vulnerability thresholds is highlighting differential vulnerability through selection of appropriate susceptibility indicators.
引用
收藏
页码:36 / 49
页数:14
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