| Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data | |
| Li, Haosi; Yi, Shuang; Luo ZR(罗子人); Xu P(徐鹏) | |
| Corresponding Author | Yi, Shuang([email protected]) |
| Source Publication | WATER RESOURCES RESEARCH
 |
| 2024-06-01 | |
| Volume | 60Issue:6Pages:22 |
| ISSN | 0043-1397 |
| Abstract | 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 |
| Keyword | GRACE Follow-On line-of-sight gravity difference inter-satellite ranging measurements flood monitoring water resource management |
| DOI | 10.1029/2023WR036332 |
| Indexed By | SCI ; EI |
| Language | 英语 |
| WOS ID | WOS:001246520400001 |
| WOS Keyword | DROUGHT |
| WOS Research Area | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
| WOS Subject | Environmental Sciences ; Limnology ; Water Resources |
| Funding Project | 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 |
| Funding Organization | 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 |
| Classification | 二类/Q1 |
| Ranking | 3 |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://dspace.imech.ac.cn/handle/311007/95658 |
| Collection | 微重力重点实验室 |
| Recommended Citation GB/T 7714 | Li, Haosi,Yi, Shuang,Luo ZR,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, Haosi,Yi, Shuang,罗子人,&徐鹏.(2024).Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data.WATER RESOURCES RESEARCH,60(6),22. |
| MLA | Li, Haosi,et al."Revealing High-Temporal-Resolution Flood Evolution With Low Latency Using GRACE Follow-On Ranging Data".WATER RESOURCES RESEARCH 60.6(2024):22. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment