| 项目编号: | NE/P017134/1
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| 项目名称: | Flood-PREPARED: Predicting Rainfall Events by Physical Analytics of REaltime Data |
| 作者: | Stuart Barr
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| 承担单位: | Newcastle University
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| 批准年: | 2016
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| 开始日期: | 2017-01-05
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| 结束日期: | 2021-30-04
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| 资助金额: | GBP1523519
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| 资助来源: | UK-NERC
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| 项目类别: | Research Grant
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| 国家: | UK
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| 语种: | 英语
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| 特色学科分类: | Civil eng. & built environment 
; (10%)
; Environmental planning 
; (10%)
; Terrest. & freshwater environ. 
; (40%)
; Tools, technologies & methods 
; (40%)
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| 英文摘要: | Flood-PREPARED will develop an international leading capability for real-time surface water flood risk and impacts analysis for cities. Our vision is to provide the tools and methods that allow cities to become proactive, rather than be reactive, to managing surface water flooding
This will be achieved by developing new physical analytical methods that integrate advanced urban flood hazard models with statistical analytics of big data from multiple real-time data-feeds that describe the current state and condition of the city in terms of surface water flood risk and impacts. By coupling physically-based modelling and statistical analytics, decision makers will be provided with improved real-time predictions of surface water flooding to assist in flood mitigation at a range of governance scales; from the individual site through to national emergency and response. This vision will be delivered via five interrelated work packages:
Work package 1 will develop the data management platforms required for capturing, managing and making available the wide variety of real-time data that will be utilised, including real-time weather radar, environmental weather station data feeds, sewer telemetry gauging, CCTV data and traffic congestion data. Data comes from Newcastle's £1.5m Urban Observatory that includes hundreds of pervasive environmental sensors that currently record ~1million observations per day.
Work package 2 will employ this data within a new hydrodynamic surface water flood model that employs statistical data assimilation and modelling for improved real-time calibration and parameterisation for surface water flooding. The outputs of the hydrodynamic surface water flood model will be used in work package 3 to parameterise real-time impacts analysis. Using real-time data feeds such as CCTV, social media, traffic monitoring, new predictive models of how impacts evolve and cascade within cities will be developed for improved response and mitigation.
Work packge 4 will develop the integrated computational workflow and scheduling software required for the tools and methods of work package 2 and 3 to be employed in an operational manner. An operational 'live' demonstrator of the system will be implemented in work package 5.
Working with key strategic project partners the demonstrator will be rigorously evaluated through a series of case studies at the individual site, city and national scale to evaluate how improved surface flood risk mitigation in real-time can be undertaken. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/100214
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| Appears in Collections: | 科学计划与规划
气候变化与战略
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作者单位: | Newcastle University
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| Recommended Citation: | |
Stuart Barr. Flood-PREPARED: Predicting Rainfall Events by Physical Analytics of REaltime Data. 2016-01-01.
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