An Integrated Risk Assessment Framework for Compound Flooding in Canadian Urban Environments

加拿大城市环境复合洪水综合风险评估框架

基本信息

  • 批准号:
    556285-2020
  • 负责人:
  • 金额:
    $ 4.08万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Alliance Grants
  • 财政年份:
    2020
  • 资助国家:
    加拿大
  • 起止时间:
    2020-01-01 至 2021-12-31
  • 项目状态:
    已结题

项目摘要

Canadian urban environments are prone to compound flood events that result from the interactions between multiple contributing factors including rainfall, runoff, groundwater, sewer backup, and seawater levels in coastal zones. Analysis of different flood generating mechanisms in isolation without proper characterization of their interrelationships can lead to significant underestimations of flood risks. This can severely undermine resilience measures for communities and infrastructure leading to the misallocation of investment in flood protection measures. In this project, we will develop an integrated statistical and physically-based framework to simulate and predict compound flood risks under climate change in urban domains to develop effective mitigation plans. The proposed framework will characterize the dependencies between multiple flood generating mechanisms based on a multivariate statistical approach and will identify rare compound events. We will develop sampling methods to generate boundary conditions from the resulting joint distribution to drive physically based hydrodynamic models. This project will evaluate the added value of coupled hydrodynamic models to represent the combined effects of overland flooding with groundwater infiltration and sewer backup compared to models that do not represent the dynamics between the surface and sub-surface flows. We will drive the hydrodynamic models with an ensemble of boundary conditions generated through the historical and future joint distributions to assess projected changes in compound flood events. The resulting framework will be used to characterize the contribution of each factor to the impacted areas and develop preventive measures for future scenarios considering the effects of more intense hydroclimatic events and sea-level rise due to climate change. In collaboration with the Institute for Catastrophic Loss Reduction (ICLR), we will disseminate the results from the proposed project directly to insurance industry executives and key officials involved in the management of urban flood risks. This project will provide river forecast centres, conservation authorities, insurance industries, municipalities, among other stakeholders with data, rigorous methodology, and personnel to analyze and predict compound flooding and develop robust mitigation plans that will benefit all Canadians.
加拿大城市环境容易发生复合洪水事件,这些事件是多种因素相互作用的结果,这些因素包括降雨、径流、地下水、下水道备份和沿海地区的海平面。孤立地分析不同的洪水产生机制,而没有适当地描述它们之间的相互关系,可能会导致对洪水风险的严重低估。这可能严重破坏社区和基础设施的复原力措施,导致防洪措施投资分配不当。在这个项目中,我们将开发一个综合的统计和物理基础框架,以模拟和预测城市领域气候变化下的复合洪水风险,以制定有效的缓解计划。该框架将基于多变量统计方法表征多种洪水发生机制之间的相关性,并将识别罕见的复合事件。我们将开发采样方法,从产生的联合分布中生成边界条件,以驱动基于物理的流体动力学模型。该项目将评估耦合水动力模型的附加值,以与不代表地表和地下水流之间动态的模型相比,反映地面洪水与地下水渗透和下水道备份的综合影响。我们将用通过历史和未来联合分布产生的一系列边界条件来驱动水动力学模型,以评估复合洪水事件的预测变化。所产生的框架将用来确定每个因素对受影响地区的贡献,并考虑到气候变化引起的更强烈的水文气候事件和海平面上升的影响,为未来的情况制定预防措施。我们将与减少灾难性损失研究所(ICLR)合作,将拟议项目的结果直接传播给保险业高管和参与城市洪水风险管理的主要官员。该项目将为河流预报中心、保护当局、保险业、市政当局和其他利益攸关方提供数据、严格的方法和人员,以分析和预测复合洪水,并制定强有力的缓解计划,使所有加拿大人受益。

项目成果

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Najafi, MohammadReza其他文献

Najafi, MohammadReza的其他文献

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{{ truncateString('Najafi, MohammadReza', 18)}}的其他基金

Improved Characterization of Hydroclimatic Extremes through the Development of a Comprehensive Nonstationary Modelling Framework
通过开发综合非平稳建模框架改进极端水文气候特征
  • 批准号:
    RGPIN-2017-05558
  • 财政年份:
    2022
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Discovery Grants Program - Individual
Improved Characterization of Hydroclimatic Extremes through the Development of a Comprehensive Nonstationary Modelling Framework
通过开发综合非平稳建模框架改进极端水文气候特征
  • 批准号:
    RGPIN-2017-05558
  • 财政年份:
    2021
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Discovery Grants Program - Individual
An Integrated Risk Assessment Framework for Compound Flooding in Canadian Urban Environments
加拿大城市环境复合洪水综合风险评估框架
  • 批准号:
    556285-2020
  • 财政年份:
    2021
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Alliance Grants
Improved Characterization of Hydroclimatic Extremes through the Development of a Comprehensive Nonstationary Modelling Framework
通过开发综合非平稳建模框架改进极端水文气候特征
  • 批准号:
    RGPIN-2017-05558
  • 财政年份:
    2020
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Discovery Grants Program - Individual
An integrated top-down and bottom-up approach to assess and mitigate river flood risks under climate and land-use change
采用自上而下和自下而上的综合方法来评估和减轻气候和土地利用变化下的河流洪水风险
  • 批准号:
    523924-2018
  • 财政年份:
    2019
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Collaborative Research and Development Grants
Improved Characterization of Hydroclimatic Extremes through the Development of a Comprehensive Nonstationary Modelling Framework
通过开发综合非平稳建模框架改进极端水文气候特征
  • 批准号:
    RGPIN-2017-05558
  • 财政年份:
    2019
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Discovery Grants Program - Individual
Probabilistic bias adjustment of remotely sensed quantitative precipitation estimations to improve urban flood risk assessments in southern Canada
遥感定量降水估计的概率偏差调整以改进加拿大南部城市洪水风险评估
  • 批准号:
    538219-2019
  • 财政年份:
    2019
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Engage Grants Program
An integrated top-down and bottom-up approach to assess and mitigate river flood risks under climate and land-use change
采用自上而下和自下而上的综合方法来评估和减轻气候和土地利用变化下的河流洪水风险
  • 批准号:
    523924-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Collaborative Research and Development Grants
Improved Characterization of Hydroclimatic Extremes through the Development of a Comprehensive Nonstationary Modelling Framework
通过开发综合非平稳建模框架改进极端水文气候特征
  • 批准号:
    RGPIN-2017-05558
  • 财政年份:
    2018
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Discovery Grants Program - Individual
Improved Characterization of Hydroclimatic Extremes through the Development of a Comprehensive Nonstationary Modelling Framework
通过开发综合非平稳建模框架改进极端水文气候特征
  • 批准号:
    RGPIN-2017-05558
  • 财政年份:
    2017
  • 资助金额:
    $ 4.08万
  • 项目类别:
    Discovery Grants Program - Individual

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