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# From China’s Heavy Precipitation in 2020 to a “Glocal” Hydrometeorological Solution for Flood Risk Prediction

Fund Project:

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

• The prolonged mei-yu/baiu system with anomalous precipitation in the year 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 the Yangtze River basin. Significant precipitation and flooding anomalies have already been seen in magnitude and extension so far this year, which have been exerting much higher pressure on emergency responses in flood control and mitigation than in other years, even though a rainy season with multiple ongoing serious flood events in different provinces is not that uncommon in China. Instead of delving into the causes of the uniqueness of this year’s extreme precipitation-flooding situation, which certainly warrants in-depth exploration, in this article we 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 different types of significant precipitation-caused flooding, which happen extensively almost every year in many countries such as China, India and the United States. Such a GHS-F model is necessary from both scientific and operational perspectives, with the strength in providing spatially consistent flood definitions and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain. Priorities in the development of such a GHS-F are suggested, emphasizing the user’s requirements and needs according to practical experiences with various flood response agencies.
摘要: 2020年，梅雨系统给中国南方带来了长时间的异常强降水，导致南方大部分地区的江河湖泊水位暴涨，持续引发了山洪、城市内涝、山体滑坡等自然灾害，其中以长江流域洪涝灾害最严重。总的来说，今年我国强降水和洪涝灾害的发生规模和范围均出现了明显的异常增多现象，这使得相关部门对于防汛减灾应急响应的压力也较往年增大。尽管今年我国洪灾频发，但雨季多个省份发生多起严重洪涝灾害的现象在我国并不罕见。本文没有深入探讨今年极端降水引发的洪涝灾害形成的独特性原因，而是对这一全国性灾害问题提出了具有普适性的水文气象解决方案。近年来，由极端降水引发的洪涝灾害事件几乎每年都在中国、印度和美国等许多国家发生。”从全球到区域（Glocal, Global to local）”的水文气象解决方案（GHS-F, A “glocal” hydrometeorological solution for floods）被认为是更好地监测不同类型降水引起的洪涝灾害、减轻洪涝灾害风险损失至关重要的解决方案。GHS-F考虑了全球区域的脆弱性和恢复机制的异质性，能提出统一的空间洪水定义和洪水风险分类标准；从科学性和可操作性的角度来看，GHS-F模型都是十分必要的。本文还提出了发展全球统一框架的GHS-F模型需优先级解决的事项，并需根据各抗洪减灾机构的实际经验，优先考虑用户的实际需要。
• Figure 1.  (a) Distribution map of flood events from late May to mid-July 2020. Red arrows indicate the timeline of flood-event occurrences and red dots indicate the most severely affected cities. (b) Number of people affected by each major event, according to social media sources.

Figure 2.  Daily zonal mean precipitation over part of mainland China (20°–44.5°N). Eleven extreme precipitation events (dates in bold black font) in central to eastern China since the onset of the monsoon up to 28 July 2020. The number of days (in red) are the lead days when corresponding events were skillfully predicted with good quality using medium- and extended-range quantitative precipitation forecasting by the National Meteorological Center.

Figure 3.  Schematic illustration of a GHS-F: DRIVE model, including an urban flood module in addition to pluvial (flash) flooding and fluvial flood modeling.

Figure 4.  An example of GFMS output from global to local scale flooding. (a) Global streamflow distribution map with resolution of 12 km. (b) China's flood detection/intensity distribution map with resolution of 10 km. (c) Distribution map of surface storage of local watershed with resolution of 1 km (d) Local streamflow distribution map resolution of 1 km. (e) Urban waterlogging map with 5 km resolution

Figure 5.  (a) Flood detection and intensity by GFMS with the China Meteorological Administration’s real-time quantitative precipitation estimation. (b) Risk estimation of flash flooding. (c) Sentinel-1-based flood inundation mapping for Dongting Lake, with the inset showing the temporal variations of lake areas, estimated by NOAA NPP satellite optical band data, together with the water level measured on the ground at the lake outlet. (d) Fluvial flooding in small- to mid-sized rivers.

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## Manuscript History

Manuscript revised: 09 September 2020
Manuscript accepted: 10 September 2020
###### 通讯作者: 陈斌, bchen63@163.com
• 1.

沈阳化工大学材料科学与工程学院 沈阳 110142

## From China’s Heavy Precipitation in 2020 to a “Glocal” Hydrometeorological Solution for Flood Risk Prediction

###### Corresponding author: Huan WU, wuhuan3@mail.sysu.edu.cna;
• 1. Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, and School of Atmospheric Sciences, Sun Yat-sen University, Guangdong 510000, China
• 2. Southern Marine Science and Engineering Laboratory, Guangdong 519000, China
• 3. Earth System Science Interdisciplinary Center, University of Maryland, Maryland 20742, USA
• 4. School of Geographical Sciences, University of Bristol, Bristol BS8 1TH, UK
• 5. DFO Global Flood Observatory, University of Colorado Boulder, Boulder 80309, USA
• 6. CIMA Research Foundation, Savona 17100, Italy
• 7. National Meteorological Center, Beijing 100081, China
• 8. Guangdong Meteorological Center, Guangzhou, Guangdong 510000, China
• 9. GuangXi Climate Center, Nanning, Guangxi 530000, China
• 10. Guangdong Climate Center, Guangzhou, Guangdong 510000, China
• 11. China Three Gorges Corporation, Beijing 100081, China

Abstract: The prolonged mei-yu/baiu system with anomalous precipitation in the year 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 the Yangtze River basin. Significant precipitation and flooding anomalies have already been seen in magnitude and extension so far this year, which have been exerting much higher pressure on emergency responses in flood control and mitigation than in other years, even though a rainy season with multiple ongoing serious flood events in different provinces is not that uncommon in China. Instead of delving into the causes of the uniqueness of this year’s extreme precipitation-flooding situation, which certainly warrants in-depth exploration, in this article we 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 different types of significant precipitation-caused flooding, which happen extensively almost every year in many countries such as China, India and the United States. Such a GHS-F model is necessary from both scientific and operational perspectives, with the strength in providing spatially consistent flood definitions and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain. Priorities in the development of such a GHS-F are suggested, emphasizing the user’s requirements and needs according to practical experiences with various flood response agencies.

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