A flood forecasting system commonly consists of at least two essential components, that is, a numerical weather prediction (NWP) model to provide rainfall forecasts and a hydrological/hydraulic model to predict the hydrological response. While being widely used for flood forecasting, hydrological models only provide a simplified representation of the physical processes of flooding due to negligence of strict momentum conservation. They cannot reliably predict the highly transient flooding process from intense rainfall, in which case a fully 2‐D hydrodynamic model is required. Due to high computational demand, hydrodynamic models have not been exploited to support real‐time flood forecasting across a large catchment at sufficiently high resolution. To fill the current research and practical gaps, this work develops a new forecasting system by coupling a graphics processing unit (GPU) accelerated hydrodynamic model with NWP products to provide high‐resolution, catchment‐scale forecasting of rainfall‐runoff and flooding processes induced by intense rainfall. The performance of this new forecasting system is tested and confirmed by applying it to “forecast” an extreme flood event across a 2,500‐km² catchment at 10‐m resolution. Quantitative comparisons are made between the numerical predictions and field measurements in terms of water level and flood extent. To produce simulation results comparing well with the observations, the new flood forecasting system provides 34 hr of lead time when the weather forecasts are available 36 hr beforehand. Numerical experiments further confirm that uncertainties from the rainfall inputs are not amplified by the hydrodynamic model toward the final flood forecasting outputs in this case.

中文翻译：

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基于高性能二维水动力模型和数值天气预报的实时洪水预报

洪水预报系统通常至少包括两个基本组成部分，即提供降雨量预报的数值天气预报（NWP）模型和预报水文响应的水文/水力模型。水文模型虽然被广泛用于洪水预报，但由于严格的动量守恒的疏忽而只能提供洪水物理过程的简化表示。他们无法从强降雨中可靠地预测高瞬态洪水过程，在这种情况下，需要一个完整的二维流体力学模型。由于较高的计算需求，尚未开发出水动力模型来以足够高分辨率支持跨大流域的实时洪水预报。为了填补当前的研究和实践空白，这项工作通过将图形处理单元（GPU）加速的水动力模型与NWP产品结合使用，开发了一种新的预报系统，以提供高分辨率，集水规模的强降雨引起的降雨径流和洪水过程的预报。通过将该新预报系统应用于“预测” 2500 km范围内的极端洪水事件，可以对其性能进行测试和确认。10 m分辨率下有^2个流域。在水位和洪水范围方面，在数值预测和现场测量之间进行了定量比较。为了产生与观测结果良好的模拟结果，当天气预报提前36小时可用时，新的洪水预报系统可以提供34小时的提前期。数值实验进一步证实，在这种情况下，水动力模型不会将降雨输入的不确定性放大到最终的洪水预报输出。