Developing enhanced impact models for integration with next generation NWP and climate outputs
Developing enhanced impact models for integration with next generation NWP and climate outputs
批准号:
NE/I005366/1
负责人:
Paul Bates
金额:
$69.1万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2010
资助国家:
英国
项目状态:
已结题
起止时间:
2010 至 --
中文摘要
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英文摘要
Current best estimates indicate that approximately 5M people living in 2M properties are at risk of flooding resulting from extreme storms in the UK. Of these approximately 200,000 homes are not protected against a 1 in 75 year recurrence interval event, the Government's minimum recommended level of protection. When major floods do occur then total damage costs are high (£3.5Bn for the summer 2007 floods) and the total annual spending on flood defence approaches £800M. Protecting this population and minimizing these costs into the future requires the development of robust hydrologic and hydraulic models to translate the outputs from Numerical Weather Prediction (NWP) and climate models into meaningful estimates of impact (with uncertainty). These predictions of impact can then be used to plan investment decisions, provide real-time warnings, design flood defence schemes and generally help better manage storm risks and mitigate the effects of dangerous climate change. Building on foundations developed by consortium members as part of the NERC Flood Risk from Extreme Events (FREE) and EPSRC/NERC Flood Risk Management Research Consortium (FRMRC) Programmes, we here propose an integrated programme of research that will lead to step change improvements in our ability to quantify storm impacts over both the short and long term. Based on the knowledge gained in the above programmes, we suggest that improvements in storm impact modelling can be achieved through four linked objectives which we are uniquely positioned to deliver. Specifically, these are: 1. Downscaling, uncertainty propagation and evaluation of hydrologic modelling structures. 2. The development of data assimilation and remote sensing approaches to enhance predictions from storm impact models. 3. Fully dynamically coupled extreme storm surge and fluvial modelling. 4. The development of a new class of hydraulic model that can be used to convert predictions of rainfall-runoff or coastal extreme water levels to estimates of flood extent and depth at the resolution of LiDAR data (~1 - 2m horizontal resolution) over whole city regions using a true momentum-conserving approach. In this proposal we evaluate the potential of the above four approaches to reduce the uncertainty in ensemble predictions of storm impact given typical errors in the NWP and climate model outputs which are used as boundary forcing for impact modelling chains. Our initial characterization of the errors in predicted storm features (spatial rainfall and wind speed fields) in current implementations of NWP and climate models will be based on existing studies conducted by the UK Met Office and the University of Reading. As the project proceeds we will use the advances in storm modelling being developed for Deliverables 1 and 2 of this call to enhance our error characterizations and ensure that the techniques we develop are appropriate for current and future meteorological modelling technologies. We will rigorously evaluate the success of our proposed methods through the use of unique benchmark data sets of storm impact being developed at the Universities of Bristol and Reading.
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DOI:
10.1002/hyp.8370
发表时间:
2012-12-30
期刊:
HYDROLOGICAL PROCESSES
影响因子:
3.2
作者:
[Aronica, G. T., Franza, F., Neal, J. C.]
通讯作者:
Neal, J. C.
Observing Global Surface Water Flood Dynamics
观察全球地表水洪水动态
DOI:
10.1007/s10712-013-9269-4
发表时间:
2013
期刊:
Surveys in Geophysics
影响因子:
4.6
作者:
[Bates P]
通讯作者:
Bates P
Technical Note: The Normal Quantile Transformation and its application in a flood forecasting system
技术说明:正态分位数变换及其在洪水预报系统中的应用
DOI:
10.5194/hessd-8-9275-2011
发表时间:
2011
期刊:
影响因子:
--
作者:
[Bogner K]
通讯作者:
Bogner K
DOI:
10.1002/hyp.7905
发表时间:
2011-04-30
期刊:
HYDROLOGICAL PROCESSES
影响因子:
3.2
作者:
[Bray, Michaela, Han, Dawei, Williams, Michael]
通讯作者:
Williams, Michael
DOI:
10.1002/hyp.9947
发表时间:
2014-06-30
期刊:
HYDROLOGICAL PROCESSES
影响因子:
3.2
作者:
[Alfieri, Lorenzo, Salamon, Peter, Feyen, Luc]
通讯作者:
Feyen, Luc
共 6 条
UQ4FM: Uncertainty quantification algorithms for flood modelling
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批准号:EP/X040941/1
-
项目类别:Research Grant
-
资助金额:$47.82万
-
财政年份:2024
-
负责人:Paul Bates
-
依托单位:
SWOT-UK: The UK contribution to validating SWOT in the Bristol Channel and River Severn, with application to coastal and river management.
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批准号:NE/V009125/1
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项目类别:Research Grant
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资助金额:$12.52万
-
财政年份:2021
-
负责人:Paul Bates
-
依托单位:
SRP-IF: Open access global flood hazard layers.
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批准号:NE/M007766/1
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项目类别:Research Grant
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资助金额:$18.2万
-
财政年份:2014
-
负责人:Paul Bates
-
依托单位:
Reducing uncertainty in flood prediction: the representation of vegetation in hydraulic models
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批准号:NE/K004816/1
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项目类别:Research Grant
-
资助金额:$2.46万
-
财政年份:2013
-
负责人:Paul Bates
-
依托单位:
INSURANCE and WATER: Estimating uncertainty in future flood risk analysis for insurance and re-insurance markets
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批准号:NE/H017836/1
-
项目类别:Training Grant
-
资助金额:$8.64万
-
财政年份:2010
-
负责人:Paul Bates
-
依托单位:
Doctoral Training Grant (DTG) to provide funding for 3 PhD studentships
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批准号:NE/H526994/1
-
项目类别:Training Grant
-
资助金额:$11.18万
-
财政年份:2009
-
负责人:Paul Bates
-
依托单位:
Doctoral Training Grant (DTG) to provide funding for 3 PhD Studentships
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批准号:NE/H525146/1
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项目类别:Training Grant
-
资助金额:$26.81万
-
财政年份:2009
-
负责人:Paul Bates
-
依托单位:
Modelling vegetation growth and its impact on slope hydrology and stability
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批准号:NE/F011113/1
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项目类别:Research Grant
-
资助金额:$4.03万
-
财政年份:2008
-
负责人:Paul Bates
-
依托单位:
PPD-DEI: Supporting Youth with Disabilities in Science, Technology, Engineering, and Mathematics: The SIU SY-STEM Project
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批准号:0228133
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项目类别:Standard Grant
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资助金额:$7.68万
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财政年份:2003
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负责人:Paul Bates
-
依托单位:
国内基金
海外基金
噬菌体靶向肠道粪肠球菌提高帕金森病左旋多巴疗效的机制研究
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批准号:82371251
-
项目类别:面上项目
-
资助金额:49.00万元
-
批准年份:2023
-
负责人:肖勤
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依托单位: