Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data

doi:10.1029/2023WR036332

	Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data
	Li, Hao-si 4; Yi, Shuang 4; Luo, Zi-ren 2,3; Xu, Peng 1,2,3
刊名	WATER RESOURCES RESEARCH
	2024-06-01
卷号	60 期号:6 页码:22
关键词	GRACE Follow-On line-of-sight gravity difference inter-satellite ranging measurements flood monitoring water resource management
ISSN号	0043-1397
DOI	10.1029/2023WR036332
通讯作者	Yi, Shuang(s.yi@ucas.ac.cn)
英文摘要	An emerging approach is utilizing the line-of-sight gravity difference (LGD) between the twin Gravity Recovery and Climate Experiment Follow-On (GFO) satellites to refine the temporal resolution of water storage estimates from 1 month to days, thus making the data applicable to transient extreme climate events like floods. However, applying the approach to medium-scale climate events (with mass changes of several tens of gigatons) is challenging due to surrounding signal contamination and low signal-to-noise ratios. To address this problem, this study develops an improved algorithm accounting for peripheral signal sources and temporal correlations in mass variation. Two floods in July 2021 in Western Europe and Central China (CC) are chosen as case studies to demonstrate our approach's applicability to moderate floods in complex hydrological settings. The results present the temporal progression of the floods up to a maximum of similar to 40 Gt with a scale of 3-5 days. However, the GFO-derived water gain in CC is much lower than expected values from land surface models, indicating a mass deficit during the flood. We find that the potent manipulation of water resources by human activities might impact the predictive capabilities of these models, thereby misrepresenting the hydrological evolution during the flood event. This study refines the viability of applying GFO data to restore transient dynamics characterizing extreme climate events of similar to 20 Gt magnitude. We also provide insights on the use of LGD data for high-temporal-resolution estimation of water storage changes and underscore the non-negligible influence of human interventions on short-term hydrological dynamics. Flood monitoring based on the Gravity Recovery and Climate Experiment (GRACE) Follow-On laser and microwave ranging observations with 3-5 days resolution Two 2021 summer floods of about 40 gigatons in Western Europe and Central China are compared GRACE Follow-On's flood detectability has been enhanced to detect floods as small as 16 gigatons
资助项目	the National Natural Science Foundation of China[E214040201] ; the National Natural Science Foundation of China[E421040401] ; National Natural Science Foundation of China, China[110400M003] ; University of Chinese Academy of Sciences Research[E2ET0411X2] ; University of Chinese Academy of Sciences Research[E3ER0402A2] ; Fundamental Research Funds for the Central Universities ; NASA Goddard Space Flight Center, and Technology University of Graz Institute of Geodesy
WOS关键词	DROUGHT
WOS研究方向	Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
语种	英语
WOS记录号	WOS:001246520400001
资助机构	the National Natural Science Foundation of China ; National Natural Science Foundation of China, China ; University of Chinese Academy of Sciences Research ; Fundamental Research Funds for the Central Universities ; NASA Goddard Space Flight Center, and Technology University of Graz Institute of Geodesy
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/95657]
专题	力学研究所_国家微重力实验室
通讯作者	Yi, Shuang
作者单位	1.Lanzhou Univ, Lanzhou Ctr Theoret Phys, Lanzhou, Peoples R China 2.UCAS, Hangzhou Inst Adv Study, Hangzhou, Peoples R China 3.Chinese Acad Sci, Inst Mech, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Key Lab Computat Geodynam, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Li, Hao-si,Yi, Shuang,Luo, Zi-ren,et al. Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data[J]. WATER RESOURCES RESEARCH,2024,60(6):22.
APA	Li, Hao-si,Yi, Shuang,Luo, Zi-ren,&Xu, Peng.(2024).Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data.WATER RESOURCES RESEARCH,60(6),22.
MLA	Li, Hao-si,et al."Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data".WATER RESOURCES RESEARCH 60.6(2024):22.