| 项目编号: | NE/J017302/1
|
| 项目名称: | The Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE) |
| 作者: | Jim William Hall
|
| 承担单位: | University of Oxford
|
| 批准年: | 2011
|
| 开始日期: | 2012-01-10
|
| 结束日期: | 2016-30-04
|
| 资助金额: | GBP322445
|
| 资助来源: | UK-NERC
|
| 项目类别: | Research Grant
|
| 国家: | UK
|
| 语种: | 英语
|
| 特色学科分类: | Civil eng. & built environment 
; (20%)
; Climate & Climate Change 
; (10%)
; Complexity Science 
; (10%)
; Environmental planning 
; (20%)
; Geosciences 
; (40%)
|
| 英文摘要: | 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. |
| 资源类型: | 项目
|
| 标识符: | http://119.78.100.158/handle/2HF3EXSE/103028
|
| Appears in Collections: | 科学计划与规划
气候变化与战略
|
|
There are no files associated with this item.
|
|
作者单位: | University of Oxford
|
| Recommended Citation: | |
Jim William Hall. The Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE). 2011-01-01.
|
|
|