Real‐Time Flood Forecasting Based on a High‐Performance 2‐D Hydrodynamic Model and Numerical Weather Predictions

Xiaodong Ming,Xilin Xia,Dingmin Li,Qiuhua Liang,Hayley J Fowler

doi:10.1029/2019wr025583

Xiaodong Ming, Xilin Xia + Show 3 more

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https://doi.org/10.1029/2019wr025583

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Abstract

AbstractA 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.

Highlights

Flooding is one of the most frequent and widely distributed natural hazards, causing significant losses to human lives and properties every year across the world (Balica et al, 2013)
The proposed flood forecasting system set up for the Eden Catchment is tested by reforecasting a severe flood event that occurred on 6 December 2015
To validate the current flood forecasting system, numerical rainfall predictions produced by the U.K. Variable (UKV) model are first compared with radar and gauge observations, and the model outputs from HiPIMS driven by radar rainfall inputs are evaluated against the observed flood extent and measured water levels

Summary

Introduction

Flooding is one of the most frequent and widely distributed natural hazards, causing significant losses to human lives and properties every year across the world (Balica et al, 2013). Regardless of the type of floods being considered, a complete flood forecasting system normally includes at least two components, that is, a model to predict the sources/drivers of flooding, such as precipitation, river flow, and storm surge, and a hydrological or hydraulic model to efficiently simulate the catchment response and flooding processes along the river networks and in the floodplains. An accurate numerical weather prediction (NWP) model is an essential component of a flood forecasting system to provide reliable prediction of rainfall. In the last few decades, following the improved scientific understanding of weather processes and significant technical breakthroughs in computing technologies, it has become a common practice to run large‐scale NWP models on government‐funded supercomputers at ~10‐km horizontal resolution.

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