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From Recent Heavy Precipitation in China to a Glocal Hydrometeorological Solution for Flood Risk Prediction

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This study was supported by National Key R&D Program of China (grant no.2017YFA0604300),the National Natural Science Foundation of China (Grants 41861144014,41775106, and U1811464) and, and also partially by the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (No.2017ZT07X355) and the project of Chinese Ministry of Emergency Management on “Catastrophe Evaluation Modeling Study”.

  • The prolonged Meiyu-Baiu system with anomalous precipitation in the year of 2020 has swollen many rivers and lakes, caused flash flooding, urban flooding and landslides, and consistently wreaked havoc across large swathes of China, particularly in Yangtze river basin. Significant precipitation and flooding anomalies have already been seen in magnitude and extension by now for this year, which have been exerting much higher pressure to emergency response in flood control and mitigation than in other years, even though a rainy season with multiple on-going serious flood events in different provinces is not very uncommon in China. Instead of digging into the causations of the uniqueness of this year’s extreme precipitation-flooding situation, which certainly warrants exploration in-depth, we here provide a short view toward a more general hydrometeorological solution to this “annual” nationwide problem. A Glocal (global to local) Hydrometeorological Solution for Floods (GHS-F) is considered to be critical for better preparedness, mitigation, and management of significant precipitation-caused different types of flooding which happen extensively almost every year in many countries such as China, India and USA for examples. Such GHS-F model is necessary from both scientific and operational perspectives with the strength in providing spatially consistent flood definition and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain. Priorities in the development of such GHS-F are suggested emphasizing the user’s requirements and needs according to the practical experiences with various flood response agencies.
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Manuscript History

Manuscript received: 03 August 2020
Manuscript revised: 09 September 2020
Manuscript accepted: 10 September 2020
通讯作者: 陈斌, bchen63@163.com
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From Recent Heavy Precipitation in China to a Glocal Hydrometeorological Solution for Flood Risk Prediction

Abstract: The prolonged Meiyu-Baiu system with anomalous precipitation in the year of 2020 has swollen many rivers and lakes, caused flash flooding, urban flooding and landslides, and consistently wreaked havoc across large swathes of China, particularly in Yangtze river basin. Significant precipitation and flooding anomalies have already been seen in magnitude and extension by now for this year, which have been exerting much higher pressure to emergency response in flood control and mitigation than in other years, even though a rainy season with multiple on-going serious flood events in different provinces is not very uncommon in China. Instead of digging into the causations of the uniqueness of this year’s extreme precipitation-flooding situation, which certainly warrants exploration in-depth, we here provide a short view toward a more general hydrometeorological solution to this “annual” nationwide problem. A Glocal (global to local) Hydrometeorological Solution for Floods (GHS-F) is considered to be critical for better preparedness, mitigation, and management of significant precipitation-caused different types of flooding which happen extensively almost every year in many countries such as China, India and USA for examples. Such GHS-F model is necessary from both scientific and operational perspectives with the strength in providing spatially consistent flood definition and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain. Priorities in the development of such GHS-F are suggested emphasizing the user’s requirements and needs according to the practical experiences with various flood response agencies.

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