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Improving hydrological forecast skill on daily to seasonal time scales

Improving hydrological forecast skill on daily to seasonal time scales
提高每日到季节时间尺度的水文预报技能
批准号:
RGPIN-2022-05441
负责人:
Islam, Sirajul
金额:
$1.89万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
本研究计划的重点是为位于不列颠哥伦比亚省中北部内陆的奥米内卡地区设计一个改进的水文预测系统。目标是利用最先进的建模工具与先进的预测初始化方法相结合,开发一个有效的河流流量和水温综合水文预测系统。这将通过五个相互关联的项目来实现。第一个项目将侧重于水文模型的实施,以量化气候变化对奥米内卡地区主要流域水流时间和大小的影响。第二个项目将利用卫星和台站数据以及改进的数据同化方法,为这些流域生成可靠的土壤水分和雪水当量数据集。随后,土壤水分和雪水当量数据将用于项目三的初始水文预测,重点是开发一种熟练的日至季节时间尺度的流量预测系统。我们将使用传统的和基于物理的微扰方法构建不同的集合预报集。这些方法将用于为集合流预报选择优化的初始条件。我们将采用先进的统计方法,系统地评估我们的流量预报系统的性能。项目四将侧重于通过将河流水温方案与综合流量预测系统相结合来生成河流水温预报。第五个也是最后一个项目将利用土地利用变化对奥米内卡地区土地利用受到严重干扰的流域进行水文预测。这将使我们能够调查和预测这些流域在伐木、野火和树皮甲虫侵扰下的流量和水温变化。拟议的研究项目的结果将利用奥米内卡地区目前的洪水、林业和渔业管理实践。这个地区是许多居住在乔治王子、圣詹姆斯堡、麦肯齐和范德霍夫的社区的中心。所提出的建模框架将为该地区的公共安全、基础设施和水生栖息地至关重要的熟练水文预报提供新的信息。奥米内卡地区的许多流域经历了严重的土地利用干扰,主要是由于野火和甲虫侵扰。提出的研究方法将提高我们量化这些干扰对区域水资源影响的知识。此外,在研究计划下提出的建模框架和新方法将可转移到加拿大其他类似的流域。此外,该研究项目将培训下一代HQP,使其具备先进的计算和水文建模技能,以提高加拿大在可靠的流量预测和更好地管理其水资源方面的能力。
英文摘要
This research program focuses on designing an improved hydrological prediction system for the Omineca region located in the north-central interior section of British Columbia. The goal is to utilize state-of-the-art modeling tools combined with advanced forecast initialization methods to develop an efficient ensemble hydrological prediction system for the river streamflow and water temperature. This will be achieved by five interconnected projects. The first project will focus on hydrological model implementation to quantify climate change impacts on the streamflow timing and magnitude in key watersheds of the Omineca region. The second project will generate reliable soil moisture and snow water equivalent datasets for these watersheds using satellite and station-based data and improved data assimilation methods. The soil moisture and snow water equivalent data will be subsequently used to initialize hydrological predictions in project three, focusing on developing a skillful streamflow prediction system on days-to-seasonal time scales. We will construct different sets of ensemble forecasts by using traditional and physically-based perturbation methods. These methods will be used to select optimized initial conditions for ensemble streamflow forecasts. We will systematically evaluate the performance of our streamflow forecast system using advanced statistical measures. Project four will focus on generating river water temperature forecasts by coupling the river water temperature scheme with an ensemble streamflow prediction system. The fifth and final project will utilize land-use changes in hydrological predictions for watersheds with significant land-use disturbance in the Omineca region. This will allow us to investigate and predict changes in streamflow and water temperature under logging, wildfires, and bark beetle infestations in these watersheds. The results of proposed research program will leverage current flood, forestry, and fisheries management practices in the Omineca region. This region is central to many communities living in Prince George, Fort St. James, Mackenzie, and Vanderhoof. The proposed modeling framework will provide new information on skillful hydrological forecasts that are crucial for public safety, infrastructure, and aquatic habitats in this region. Many watersheds in the Omineca region have experienced significant land-use disturbances, primarily due to wildfires and beetle infestations. The proposed research approach will advance our knowledge to quantify the impacts of these disturbances on regional water resources. In addition, the modeling framework and new methodologies proposed under the research program will be transferable to other similar watersheds in Canada. Furthermore, this research program will train the next generation of HQP with advanced computational and hydrological modeling skills to increase Canada's capacity in reliable streamflow forecasts and better management of its water resources.
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Improving hydrological forecast skill on daily to seasonal time scales
  • 批准号:
    DGECR-2022-00163
  • 项目类别:
    Discovery Launch Supplement
  • 资助金额:
    $0.91万
  • 财政年份:
    2022
  • 负责人:
    Islam, Sirajul
  • 依托单位:
海外基金