DocumentCode :
2989327
Title :
Remotely sensed groundwater storage variations in Hai River basin, China
Author :
Xu, Haili ; Pan, Yun ; Gong, Huili ; Zhou, Demin
Author_Institution :
Base of the State Lab. of Urban Environ. Processes & Digital Modeling, Capital Normal Univ., Beijing, China
fYear :
2012
fDate :
15-17 June 2012
Firstpage :
1
Lastpage :
5
Abstract :
Groundwater is primary source of fresh water in many parts of the world, such as Hai River basin where groundwater accounts for 66% of local total water supply. This paper presented a remote sensing approach for monitoring groundwater storage changes with gravity satellite. It is achieved through water budget calculation with the input from GRACE (Gravity Recovery and Climate Experiment) and GLDAS (Global Land Data Assimilation System), which stands for terrestrial water storage and soil water storage, respectively. The results were validated by water table records in the unconfined aquifers of the basin. The GRACE-GLDAS estimates show a good correlation with the observed data except specific months. The R2 of 2005 (exclude May, June, and July), 2006 (exclude May to September), 2007 (exclude May and June), and 2008 (exclude September) are 0.554, 0.619, 0.516, and 0.627, respectively. It can be further inferred that intensive abstraction in summer may alters specific yield, which is a commonly used parameter for validating GRACE-derived groundwater storage.
Keywords :
groundwater; hydrological techniques; moisture; remote sensing; rivers; soil; water resources; AD 2005; AD 2006; AD 2007; AD 2008; China; GRACE-GLDAS estimates; Global Land Data Assimilation System; Hai River basin; gravity satellite; groundwater storage variation; remotely sensing; soil water storage; terrestrial water storage; unconfined aquifers; water budget calculation; water supply; Economics; GLDAS; GRACE; Groundwater monitoring; Hai River basin;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics (GEOINFORMATICS), 2012 20th International Conference on
Conference_Location :
Hong Kong
ISSN :
2161-024X
Print_ISBN :
978-1-4673-1103-8
Type :
conf
DOI :
10.1109/Geoinformatics.2012.6270267
Filename :
6270267
Link To Document :
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