Consortium on Risk in the Environment: Diagnostic, Integration, Benchmarking, Learning and Elicitation (CREDIBLE)

环境风险联盟：诊断、整合、基准测试、学习和启发（CREDIBLE）

• 批准号: NE/J017043/1
• 负责人: David Stephenson
• 金额: $ 26.14万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FJ017043%2F1
• 关键词: Consortium; Risk; Environment; Diagnostic; Integration

Natural hazard events claim thousands of lives every year, and financial losses amount to billions of dollars. The risk of losing wealth through natural hazard events is now increasing at a rate that exceeds the rate of wealth creation. Therefore natural hazards risk managers have the potential, through well-informed actions, to significantly reduce social impacts and to conserve economic assets. By extension, environmental science, through informing the risk manager's actions, can leverage research investment in the low millions into recurring social and economic benefits measured in billions. However, to be truly effective in this role, environmental science must explicitly recognize the presence and implications of uncertainty in risk assessment.Uncertainty is ubiquitous in natural hazards, arising both from the inherent unpredictability of the hazard events themselves, and from the complex way in which these events interact with their environment, and with people. It is also very complicated, with structure in space and time (e.g. the clustering of storms), measurements that are sparse especially for large-magnitude events, and losses that are typically highly non-linear functions of hazard magnitude. The tendency among natural hazard scientists and risk managers (eg actuaries in insurance companies) is to assess the 'simple' uncertainty explicitly, and assign the rest to a large margin for error.The first objective of our project is to introduce statistical techniques that allow some of the uncertainty to be moved out of the margin for error and back into an explicit representation, which will substantially improve the transparency and defensibility of uncertainty and risk assessment. Obvious candidates for this are hazard models fitted on a catalogue of previous events (for which we can introduce uncertainty about model parameters, and about the model class), and limitations in the model of the 'footprint' of the hazard on the environment, and the losses that follow from a hazard event.The second objective is to develop methods that allow us to assess less quantifiable aspects of uncertainty, such as probabilities attached to future scenarios (eg greenhouse gas emissions scenarios, or population growth projections). The third objective is to improve the visualisation and communication of uncertainty and risk, in order to promote a shared ownership of choices between actions, and close the gap between the intention to act (eg, to build a levee, or relocate a group of people living in a high-risk zone) and the completion of the act. In natural hazards this gap can be large, because the cost of the act is high, many people may be affected, and the act may take several years to complete.Ultimately, everyone benefits from better risk management for natural hazards, although the nature of the benefits will depend on location. In the UK, for example, the primary hazard is flooding, and this is an area of particular uncertainty, as rainfall and coastal storm surges are likely to be affected by changes in the climate. A second hazard is drought, leading to heat stress and water shortages. Our project has explicit strands on inland flooding, wind-storms, and droughts. Other parts of the world are more affected by volcanoes or by earthquakes, and our project has strands on volcanic ash, debris flows as found in volcanic eruptions (ie lahars; avalanches are similar), and earthquakes. In the future, new hazards might emerge, such as the effect of space weather on communications. A key part of our project is to develop generic methods that work across hazards, both current and emerging.

自然灾害事件每年夺去数千人的生命，经济损失高达数十亿美元。现在，因自然灾害事件而损失财富的风险正在以超过财富创造速度的速度增加。因此，自然灾害风险管理者有可能通过明智的行动，显着减少社会影响并保护经济资产。推而广之，环境科学通过告知风险管理者的行动，可以将数百万美元的研究投资转化为数十亿美元的经常性社会和经济效益。然而，要真正有效地发挥这一作用，环境科学必须明确认识到风险评估中不确定性的存在和影响。不确定性在自然灾害中普遍存在，这既源于灾害事件本身固有的不可预测性，也源于这些事件与其环境和人类相互作用的复杂方式。它也非常复杂，具有空间和时间结构（例如风暴的聚集），测量结果稀疏，特别是对于大规模事件，损失通常是危险程度的高度非线性函数。自然灾害科学家和风险管理者（例如保险公司的精算师）的趋势是明确评估“简单”不确定性，并将其余的不确定性分配给较大的误差范围。我们项目的第一个目标是引入统计技术，允许将一些不确定性移出误差范围并返回到明确的表示中，这将大大提高不确定性和风险评估的透明度和可防御性。明显的候选者是安装在先前事件目录上的危害模型（为此我们可以引入模型参数和模型类别的不确定性），以及危害对环境的“足迹”模型的限制，以及危害事件带来的损失。第二个目标是开发方法，使我们能够评估不确定性的不太可量化的方面，例如与未来情景（例如温室气体）相关的概率。 气体排放情景或人口增长预测）。第三个目标是改善不确定性和风险的可视化和沟通，以促进行动之间选择的共同所有权，并缩小行动意图（例如，建造堤坝，或重新安置居住在高风险地区的一群人）与行动完成之间的差距。在自然灾害中，这种差距可能很大，因为该行动的成本很高，许多人可能受到影响，而且该行动可能需要几年时间才能完成。最终，每个人​​都会从更好的自然灾害风险管理中受益，尽管好处的性质将取决于地点。例如，在英国，主要灾害是洪水，这是一个特别不确定的领域，因为降雨和沿海风暴潮可能会受到气候变化的影响。第二个危险是干旱，导致热应激和缺水。我们的项目有明确的内陆洪水、风暴和干旱问题。世界其他地区更容易受到火山或地震的影响，我们的项目有火山灰、火山喷发中发现的泥石流（即火山泥流；雪崩类似）和地震。未来可能会出现新的危险，例如太空天气对通信的影响。我们项目的一个关键部分是开发适用于当前和新兴危害的通用方法。

项目成果

On the relevance of extremal dependence for spatial statistical modelling of natural hazards

自然灾害空间统计模型的极值依赖性的相关性

• DOI: 10.5194/nhess-2018-102
• 发表时间: 2018
• 作者: Dawkins L

The XWS open access catalogue of extreme European windstorms from 1979 to 2012

1979 年至 2012 年欧洲极端风暴的 XWS 开放获取目录

• DOI: 10.5194/nhess-14-2487-2014
• 发表时间: 2014
• 期刊: Natural Hazards and Earth System Sciences
• 影响因子: 4.6
• 作者: Roberts J

On the use of Bayesian decision theory for issuing natural hazard warnings.

• DOI: 10.1098/rspa.2016.0295
• 发表时间: 2016-10
• 期刊: Proceedings. Mathematical, physical, and engineering sciences
• 作者: Economou T;Stephenson DB;Rougier JC;Neal RA;Mylne KR
• 通讯作者: Mylne KR

Quantification of extremal dependence in spatial natural hazard footprints: independence of windstorm gust speeds and its impact on aggregate losses

空间自然灾害足迹的极值依赖性的量化：风暴阵风速度的独立性及其对总损失的影响

• DOI: 10.5194/nhess-18-2933-2018
• 发表时间: 2018
• 期刊: Natural Hazards and Earth System Sciences
• 影响因子: 4.6
• 作者: Dawkins L

The 21st century decline in damaging European windstorms

• DOI: 10.5194/nhess-16-1999-2016
• 发表时间: 2016-08-29
• 期刊: NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
• 影响因子: 4.6
• 作者: Dawkins, Laura C.;Stephenson, David B.;Maisey, Paul E.
• 通讯作者: Maisey, Paul E.