Development of an improved hourly ensemble streamflow forecasting system for flood forecasting on small watersheds

开发改进的每小时集合水流预报系统，用于小流域洪水预报

• 批准号: 560780-2020
• 负责人: Arsenault, Richard
• 金额: $ 2.8万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=721806
• 关键词: Development; improved; hourly; ensemble; streamflow

Canada is blessed with plentiful water resources which have contributed to making it a leader in water-related fields such as hydropower and flood management. Nonetheless, major floods have caused millions of dollars of damages in the recent years and multiple initiatives have been put forth to evaluate methods to better predict their timing and magnitude to help public safety officials plan emergency response interventions. For the last 25 years, the hydrometeorological consulting firm Hydro Météo has helped municipalities, public safety agencies and watershed management organizations to forecast floods, prevent ice jams and instrument rivers across the province of Québec. Their expertise in hydrological forecasting allows them to provide custom analyses for their clients, improving response times and preventing damages to infrastructures and risks to human life as much as possible.Currently, Hydro Météo uses a forecasting system based on a simple, yet skillful, hydrological model running on a daily time step, and they run their model using weather forecasts from different sources to transform precipitation and temperatures into river streamflow. Hydro Météo is currently transitioning to a multi-model approach using an hourly time step to improve forecast resolution and accuracy, especially on smaller (between 20 and 2000 square kilometers) watersheds. However, efficiently implementing a forecasting system using multiple hydrological models and multiple weather forecast products on hourly timescales remains a key issue which and is still debated in the scientific community. This proposed project will evaluate and develop methods to allow sub-daily hydrological forecasting based on model performance in different hydrological regimes. This will make it possible to improve short-term forecasting for flood risk management, but also for more precise estimates of inflows to hydropower reservoirs for hydropower operating utilities.

加拿大拥有丰富的水资源，这使其成为水电和洪水管理等与水有关的领域的领先者。尽管如此，近年来，大洪水已经造成了数百万美元的损失，人们提出了多项举措，以评估更好地预测洪水发生的时间和程度的方法，以帮助公共安全官员规划应急干预措施。在过去的25年里，水文气象咨询公司Hydro Météo帮助魁北克省的市政当局、公共安全机构和流域管理组织预测洪水、防止冰堵和测量河流。他们在水文预报方面的专业知识使他们能够为客户提供定制的分析，尽可能缩短响应时间并防止对基础设施的破坏和对人类生命的风险。目前，Hydro Météo使用一种基于简单但熟练的水文模型的预报系统，该模型运行时使用来自不同来源的天气预报，将降水和温度转换为河流径流。Hydro Météo目前正在过渡到使用每小时时间步长的多模型方法，以提高预测分辨率和精度，特别是在较小的(20至2000平方公里)流域。然而，在每小时时间尺度上使用多种水文模型和多种天气预报产品有效地实施预报系统仍然是一个关键问题，科学界仍在讨论这一问题。这一拟议的项目将评估和开发方法，以便能够根据不同水文状况下的模型性能进行次日水文预报。这将使改进洪水风险管理的短期预测成为可能，而且还可以更准确地估计水电运营设施流入水电站水库的流量。