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Flood-PREPARED: Predicting Rainfall Events by Physical Analytics of REaltime Data

洪水准备：通过实时数据的物理分析预测降雨事件

基本信息

批准号：
NE/P017134/1
负责人：
Stuart Barr
金额：
$ 194.13万
依托单位：
Newcastle University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FP017134%2F1
关键词：
Flood PREPARED Predicting Rainfall Events

项目摘要

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 package 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.

Flood-PREPARED将开发国际领先的城市实时地表水洪水风险和影响分析能力。我们的愿景是提供工具和方法，使城市能够主动而不是被动地管理地表水洪水。这将通过开发新的物理分析方法来实现，该方法将先进的城市洪水灾害模型与来自多个实时数据源的大数据统计分析相结合，这些数据源描述了城市在地表水洪水风险和影响方面的当前状态和状况。通过结合基于物理的建模和统计分析，将为决策者提供更好的地表水洪水实时预测，以帮助在一系列治理规模上减轻洪水;从单个站点到国家紧急情况和响应。这一愿景将通过五个相互关联的工作包来实现：工作包1将开发所需的数据管理平台，用于捕获、管理和提供将被利用的各种实时数据，包括实时天气雷达、环境气象站数据馈送、下水道遥测测量、闭路电视数据和交通拥堵数据。数据来自纽卡斯尔耗资150万英镑的城市观测站，其中包括数百个无处不在的环境传感器，目前每天记录约100万次观测。工作包2将在一个新的水动力地表水驱替模型中使用这些数据，该模型采用统计数据同化和建模，以改进地表水驱替的实时校准和参数化。地面水动力模型的产出将用于第三工作包，以参数化实时影响分析。将利用闭路电视、社交媒体、交通监测等实时数据，开发新的预测模型，预测城市内的影响如何演变和级联，以改进应对和缓解工作包4将开发工作包2和3的工具和方法所需的综合计算工作流程和时间安排软件，以便以可操作的方式使用。将在工作包5中实施该系统的操作“现场”演示。通过与关键战略项目合作伙伴合作，将通过一系列案例研究在单个站点，城市和国家范围内对演示器进行严格评估，以评估如何实时改善地表洪水风险缓解。