课题基金 / 基金详情

Smart forecasting: joined-up flood forecasting (FF) infrastructure with uncertainties

Smart forecasting: joined-up flood forecasting (FF) infrastructure with uncertainties
智能预报:具有不确定性的联合洪水预报(FF)基础设施
批准号:
EP/R007349/1
负责人:
Georges Kesserwani
金额:
$139.11万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --

项目摘要

项目成果

Georges Kesserwani的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Reliable and comprehensive flood forecasting is crucial to ensure resilient cities and sustainable socio-economic development in a future faced with an unprecedented increase in atmospheric temperature and intensified precipitation. Floodwaters from the areas surrounding a city can heavily affect flood cycle behaviour across urban areas, introducing uncertainties into the forecast that are often non-negligible. However, currently the extent to which we can predict flood hazards is limited, and existing methods cannot for example deal with inter-regional dependencies (e.g. as was seen when floods affected nine different countries across Central and Eastern Europe). Presently in the UK approx. 25% of yearly flood insurance claims are from areas outside the zones forecast to be at flood risk, and annual flood damage costs are already high (approx. £1.5 billion). Also more than 20,000 houses per year continue to be built on floodplains.The need to transform flood forecasting for a range of applications and scales has already been recognised by various parties. The UK Climate Change Risk Assessment 2017 Evidence Report prioritises flooding as the greatest direct climate change related threat for UK cities now and in the future, and urges urgent action to be taken, including the development of new solutions over the next 5 years. The hydraulic software industry and consultancy firms have expressed a desire for more reliable and sophisticated flood forecasting approaches, which can also reduce the manual labour required. In addition, mathematics and engineering research communities are still searching for forecasting models that are joined-up, reliable and efficient, as well as versatile and adaptable. To address this need, 'Multi-Wavelets' technology will be employed in this fellowship with a view to transforming flood forecasting routines from a disparate set of activities into a unified automatic framework. The applicant's vision is to exploit the innate capability of Multi-Wavelets technology to reformulate flood forecasting methods by providing a smart modelling foundation for the delivery of timely and accurate flood maps, alongside statistically quantified uncertainties. This research presents a unique opportunity for the applicant, UK academia and UK industry, to establish a world leading capability in a nascent field while addressing Living With Environmental Change (LWEC) priorities for improved forecasting of environmental change. The fellowship research will stimulate the creation of new software infrastructure capable of significantly improving our flood forecasting ability across length scales and under multiple uncertainties, helping us to better design infrastructure against flood risk and to plan for the consequences.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Shallow-Flow Velocity Predictions Using Discontinuous Galerkin Solutions
使用不连续伽辽金解进行浅流速度预测
DOI: --
发表时间: 2023
期刊: Journal of Hydraulic Engineering
影响因子: 2.4
作者: [Georges Kesserwani]
通讯作者: Georges Kesserwani
DOI: 10.1016/j.advwatres.2020.103693
发表时间: 2020-07
期刊: Advances in Water Resources
影响因子: 4.7
作者: [G. Kesserwani;M. Sharifian]
通讯作者: G. Kesserwani;M. Sharifian
DOI: 10.1016/j.jhydrol.2020.125924
发表时间: 2020-10
期刊: Journal of Hydrology
影响因子: 6.4
作者: [Janice Lynn Ayog;G. Kesserwani;James Shaw;M. Sharifian;D. Baù]
通讯作者: Janice Lynn Ayog;G. Kesserwani;James Shaw;M. Sharifian;D. Baù
(Multi)wavelet-based Godunov-type simulators of flood inundation: Static versus dynamic adaptivity
基于(多)小波的 Godunov 型洪水淹没模拟器:静态自适应与动态自适应
DOI: 10.1016/j.advwatres.2022.104357
发表时间: 2023
期刊: Advances in Water Resources
影响因子: 4.7
作者: [Kesserwani G]
通讯作者: Kesserwani G
8
    Unified flood model with optimal zooming and linking at multiple scales
    • 批准号:
      EP/K031023/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $12.84万
    • 财政年份:
      2014
    • 负责人:
      Georges Kesserwani
    • 依托单位:
    海外基金