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PYRAMID: Platform for dYnamic, hyper-resolution, near-real time flood Risk AssessMent Integrating repurposed and novel Data sources

PYRAMID: Platform for dYnamic, hyper-resolution, near-real time flood Risk AssessMent Integrating repurposed and novel Data sources
PYRAMID:动态、超分辨率、近实时洪水风险评估平台,集成重新利用和新颖的数据源
批准号:
NE/V00378X/1
负责人:
Hayley Jane Fowler
金额:
$100.94万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

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项目成果

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中文摘要
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英文摘要
Flooding has been identified by the government as the number one priority and risk to the UK. Flooding already causes millions of pounds worth of damage to people's homes, infrastructure and the economy every year, and is projected to become even more severe under climate change. Being able to plan for, respond to and manage flooding effectively is therefore essential.We are lucky to have a tradition of flood management in the UK led by the Environment Agency. Operational flood models use meteorological data combined with elevation data to show us where flooding will occur. These models produce flood risk maps for planning and forecasting purposes and have helped us design flood defences for many areas.However, flooding is not only dependent on the topography of an area. There are many other factors at play that evolve over time: culverts can get blocked, flood gates are left open and flood walls can fall into disrepair. This can dramatically alter the extent and depth of a flood. Not only that, but our exposure to flood risk changes too. Far less disruption occurs from a flood overnight than during rush hour traffic. A prime example of this is the flooding of Boscastle in 2004. During the event, 116 cars parked in a carpark were washed downstream, blocking a bridge, causing water to back up and flood unexpected areas. If the rain had fallen in the evening, the cars would not have been in the carpark and the impact of the flood would have been smaller. Could we have predicted this? Can we reduce the impact of flooding for similar future events? We think that with the right data and tools, we can.We will build a tool that will change how we respond to flood risks as they evolve. The tool will allow flood risk managers to deploy just-in-time maintenance and alleviation measures, such as clearing critical blocked culverts or setting up mobile flood defences. To achieve this, the tool will incorporate brand new types of data and cutting edge flood models into an easy-to-use online platform that allows users to visualise evolving flood risks. The platform (called PYRAMID) will be developed in conjunction with the Environment Agency, local authorities and community groups to ensure that it delivers relevant information for critical decision-making in near-real time. The platform will have toolkits to make it easy for communities to incorporate their data, providing essential local information.The new data driving this modelling will be key. The data that we need are available but sit fragmented across a range of organisations in difficult-to-use formats. We will use artificial intelligence to extract this useful information from hidden datasets, such as old reports, flood asset registers and various types of satellite imagery. In addition, we want to incorporate brand new information from novel sensors that are being deployed as part of Newcastle University's Urban Observatory. These sensors monitor things like soil moisture and rainfall at very high resolutions, as well as other factors like traffic and congestion. We can also monitor the condition of specific factors affecting flood risk, such as whether particular culverts are blocked or whether certain flood walls are in poor condition. These factors can be monitored by looking at a combination of satellite remote sensing and sensors deployed on lorries and other vehicles. We will also harness data collected communities and citizens.All of this information will be put into our flood models. We have a hyper-resolution hydrodynamic flood model that can accurately simulate the movement of debris in flood flows at a centimetre scale. This model will work in conjunction with a broader catchment model, which will provide information on the hydrological conditions in the wider area. The platform will be trialled in Newcastle to take advantage of existing government investments in the Urban Observatory and a legacy of flood research conducted here.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Rapidly intensifying extreme weather events in a warming world: how important are large-scale dynamics in generating extreme floods?
在变暖的世界中迅速加剧的极端天气事件:大规模动态对于产生极端洪水有多重要?
DOI: 10.5194/egusphere-egu24-22472
发表时间: 2024
期刊:
影响因子: --
作者: [Fowler H]
通讯作者: Fowler H
DOI: 10.1016/j.isprsjprs.2022.05.007
发表时间: 2022-07
期刊: ISPRS Journal of Photogrammetry and Remote Sensing
影响因子: 12.7
作者: [Shidong Wang;M. Peppa;W. Xiao;S. B. Maharjan;S. Joshi;J. Mills]
通讯作者: Shidong Wang;M. Peppa;W. Xiao;S. B. Maharjan;S. Joshi;J. Mills
DOI: 10.1016/j.envsoft.2021.105169
发表时间: 2021-08-27
期刊: ENVIRONMENTAL MODELLING & SOFTWARE
影响因子: 4.9
作者: [Lewis, Elizabeth, Pritchard, David, Fowler, Hayley J.]
通讯作者: Fowler, Hayley J.
World Weather Attribution: Rapid attribution of heavy rainfall events leading to the severe flooding in Western Europe during July 2021.
世界天气归因:对导致 2021 年 7 月西欧严重洪水的强降雨事件的快速归因。
DOI: --
发表时间: 2021
期刊:
影响因子: --
作者: [Kreienkamp F]
通讯作者: Kreienkamp F
6
    Assessment of connections between atmospheric planetary waves and extreme rainfall events
    • 批准号:
      NE/V020595/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $1.38万
    • 财政年份:
      2021
    • 负责人:
      Hayley Jane Fowler
    • 依托单位:
    Facilitating Stochastic Simulation for UK Climate Resilience
    • 批准号:
      NE/W007037/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $8.99万
    • 财政年份:
      2021
    • 负责人:
      Hayley Jane Fowler
    • 依托单位:
    STORMY-WEATHER: Plausible storm hazards in a future climate
    • 批准号:
      NE/V004166/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $45.1万
    • 财政年份:
      2020
    • 负责人:
      Hayley Jane Fowler
    • 依托单位:
    FUTURE-DRAINAGE: Ensemble climate change rainfall estimates for sustainable drainage
    • 批准号:
      NE/S017348/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $18.24万
    • 财政年份:
      2019
    • 负责人:
      Hayley Jane Fowler
    • 依托单位:
    国内基金
    海外基金
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information