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, RichardRF
• 金额: $ 2.84万
• 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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753876
• 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，这使其在水电和洪水管理等与水有关的领域处于领先地位。尽管如此，近年来，大洪水造成了数百万美元的损失，人们提出了多项举措来评估更好地预测洪水时间和规模的方法，以帮助公共安全官员计划应急干预措施。在过去的25年里，水文气象咨询公司Hydro msamtsamo帮助市政府、公共安全机构和流域管理组织预测洪水、防止冰塞和测量整个qusamebec省的河流。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分析，缩短响应时间，并尽可能地防止对基础设施的破坏和对人类生命的风险。目前，Hydro msamo使用的是一种基于简单但技术娴熟的每日时间步的水文模型的预测系统，他们使用来自不同来源的天气预报来运行他们的模型，将降水和温度转化为河流流量。Hydro msamtsamo目前正在过渡到使用每小时时间步长的多模式方法，以提高预报的分辨率和准确性，特别是在较小的（20至2000平方公里）流域。然而，如何在每小时的时间尺度上有效地实施一个使用多种水文模型和多种天气预报产品的预报系统，仍然是科学界争论的一个关键问题。这个拟议的项目将评估和开发方法，以允许基于不同水文制度的模型性能进行次日水文预报。这将有可能改进洪水风险管理的短期预报，也有可能更精确地估计水电运营公用事业的水电站水库的流入。