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NSERC Canadian Floodnet

NSERC Canadian Floodnet
NSERC 加拿大洪水网
批准号:
451456-2013
负责人:
Coulibaly, Paulin
金额:
$76.49万
依托单位:
依托单位国家:
加拿大
项目类别:
Strategic Network Grants Program
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31
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项目摘要

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中文摘要
翻译
在加拿大,洪水被认为是对生命、财产、经济、社区/工业供水系统和环境最常见、分布最广的自然灾害。拟议的NSERC加拿大洪水网的主要目标是创建一个工具,用于全国范围内的协调努力,以改善对洪水过程及其影响的了解,并提高加拿大的洪水预报和管理能力。这是一项特别具有挑战性的任务,因为加拿大的地理和水文气候条件千差万别,但通过创建一个结构化的研究网络是可行的,该网络将科学家/专家、用户/业务预报员和私营部门聚集在一起,以解决复杂的基本研究问题和需要解决的技术差距,以便显著改进加拿大的洪水预报和管理。NSERC战略网络促进大学、联邦/省级机构和私营部门之间的合作,是优化资源和解决加拿大日益严重的洪灾问题的最佳途径。一些主要研究任务包括:(I)分析和描述加拿大各地的极端事件(洪水和风暴);(Ii)量化和减少洪水的预测不确定性;(Iii)开发加拿大先进的洪水警报系统;(Iv)评估洪水的物理、社会经济和环境影响,以加强加拿大的洪水管理政策。目前,加拿大还没有类似于欧洲(欧洲洪水预警系统)或美国(高级水文预报系统)的先进洪水警报系统可供运营使用。FroudNet将通过汇集学术界和工业界的资源和最佳专业知识来开发加拿大先进的洪水警报系统,以填补这一空白。加强洪水预报和管理的直接好处是巨大的,包括降低损害成本、保护人畜、减少社会经济影响和人类痛苦,以及保护社区供水系统和环境。
英文摘要
In Canada, floods are recognized as the most common, largely distributed natural hazard to life, property,economy, community/industry water systems, and the environment. The main objective of the proposedNSERC Canadian FloodNet is to create a vehicle for a concerted nation-wide effort to improve knowledge onflood processes and their impacts, and enhance flood forecasting and management capacity in Canada. This is aparticularly challenging task because of the large diversity of geographical and hydro-climatic conditions inCanada, but feasible through the creation of a structured research network that brings togetherscientists/experts, users/operational forecasters, and the private sector to tackle the complex and fundamentalresearch questions and the technological gaps that need to be addressed in order to significantly enhance floodforecasting and management in Canada. NSERC Strategic Network facilitating collaborative work betweenuniversities, federal/provincial agencies and private sector, is the best approach to optimize resources andexpertise to address the growing issue of floods in Canada. Some of the key research tasks include (i)Analyzing and characterizing extreme events (floods and storms) across Canada; (ii) Quantifying and reducingpredictive uncertainty of floods; (iii) Developing an advanced flood alert system for Canada; (iv) Assessingphysical, socio-economic, and environmental impacts of floods to enhance flood management policies inCanada. Currently, no advanced flood alert system similar to the one in Europe (European Flood AwarenessSystem) or in the US (Advanced Hydrologic Prediction System) is available for operational use in Canada.FloodNet will fill this gap by pooling together resources and best expertise from academia and industry todevelop the Canadian advanced flood alert system. The direct benefits of enhanced flood forecasts andmanagement are tremendous and include the reduced cost of damages, the protection of people and livestock,the reduction of socio-economic impacts and human distress, and the protection of community water systems and the environment.
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Deep Learning for Enhanced Multisensor Quantitative Precipitation Estimation
  • 批准号:
    RGPIN-2018-05769
  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
Deep Learning for Enhanced Multisensor Quantitative Precipitation Estimation
  • 批准号:
    RGPIN-2018-05769
  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
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  • 批准号:
    RGPIN-2018-05769
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2020
  • 负责人:
    Coulibaly, Paulin
  • 依托单位:
Deep Learning for Enhanced Multisensor Quantitative Precipitation Estimation
  • 批准号:
    RGPIN-2018-05769
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
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  • 负责人:
    Coulibaly, Paulin
  • 依托单位:
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