Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR024618 |
Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges | |
Li, Bailing1,2; Rodell, Matthew2; Kumar, Sujay2; Beaudoing, Hiroko Kato1,2; Getirana, Augusto1,2; Zaitchik, Benjamin F.3; de Goncalves, Luis Gustavo4; Cossetin, Camila5; Bhanja, Soumendra6; Mukherjee, Abhijit7; Tian, Siyuan8,9; Tangdamrongsub, Natthachet1,2; Long, Di10; Nanteza, Jamiat11; Lee, Jejung12; Policelli, Frederick2; Goni, Ibrahim B.13; Daira, Djoret14; Bila, Mohammed14; de Lannoy, Gabrielle15; Mocko, David16; Steele-Dunne, Susan C.17; Save, Himanshu18; Bettadpur, Srinivas18 | |
2019-09-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:9页码:7564-7586 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Brazil; Canada; India; Australia; Peoples R China; Uganda; Nigeria; Chad; Belgium; Netherlands |
英文摘要 | The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state-of-the-art terrestrial water storage product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low-flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM-simulated groundwater correlates strongly with 12-month precipitation anomalies in low-latitude and midlatitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional-scale drought indicators, with discrepancies mainly in their estimated drought severity. |
英文关键词 | global GRACE data assimilation groundwater storage estimates global groundwater drought monitoring groundwater temporal variability groundwater drought |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000492139200006 |
WOS关键词 | WATER-TABLE DYNAMICS ; LAND-SURFACE SCHEME ; HIGH-PLAINS AQUIFER ; FORECASTING SYSTEM ; GRAVITY RECOVERY ; CLIMATE-CHANGE ; STORAGE ; DEPLETION ; MODEL ; REPRESENTATION |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/186910 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Maryland, ESSIC, College Pk, MD 20742 USA; 2.NASA, Goddard Space Flight Ctr, Hydrol Sci Lab, Greenbelt, MD 20771 USA; 3.Johns Hopkins Univ, Depart Earth & Planetary Sci, Baltimore, MD USA; 4.Natl Inst Space Res, Ctr Weather Forecast & Climate Studies, Sao Paulo, Brazil; 5.Climatempo, Sao Jose Dos Campos, SP, Brazil; 6.Athabasca Univ, Fac Sci & Technol, Athabasca, AB, Canada; 7.Indian Inst Technol Kharagpur, Dept Geol & Geophys, Kharagpur, W Bengal, India; 8.Australian Natl Univ, Res Sch Earth Sci, Canberra, ACT, Australia; 9.Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT, Australia; 10.Tsinghua Univ, Dept Hydraul Engn, Beijing, Peoples R China; 11.Makerere Univ, Dept Geog Geoinformat & Climat Sci, Kampala, Uganda; 12.Univ Missouri, Dept Geosci, Kansas City, MO 64110 USA; 13.Univ Maiduguri, Dept Geol, Maiduguri, Borno State, Nigeria; 14.Lake Chad Basin Commiss, Ndjamena, Chad; 15.Katholieke Univ Leuven, Dept Earth & Environm Sci, Leuven, Belgium; 16.Sci Applicat Int Corp, Reston, VA USA; 17.Delft Univ Technol, Dept Water Management Civil Engn & Geosci, Delft, Netherlands; 18.Univ Texas Austin, Ctr Space Res, Austin, TX USA |
推荐引用方式 GB/T 7714 | Li, Bailing,Rodell, Matthew,Kumar, Sujay,et al. Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges[J]. WATER RESOURCES RESEARCH,2019,55(9):7564-7586. |
APA | Li, Bailing.,Rodell, Matthew.,Kumar, Sujay.,Beaudoing, Hiroko Kato.,Getirana, Augusto.,...&Bettadpur, Srinivas.(2019).Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges.WATER RESOURCES RESEARCH,55(9),7564-7586. |
MLA | Li, Bailing,et al."Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges".WATER RESOURCES RESEARCH 55.9(2019):7564-7586. |
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