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Monitoring the changes of water storage over the Huang-huai-hai plain based on the GRACE satellite
Author(s): Zenghui Kan; Chaoshun Liu; Fengxue Qiao; Wei Gao; Maosi Chen
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Paper Abstract

This study calculated the land water storage using the time-varying monthly gravity data from the GRACE (Gravity Recovery and Climate Experience) gravity satellite combined with Gaussian smoothing filter. The characteristics of spatiotemporal variations of long-term regional land water storage derived from the linear fitting method were then examined from January 2003 to December 2013. The results showed that the water storage over the huang-huai-hai plain showed an overall declining trend from 2003 to 2013 and the average declining rate is about 2.86 mm/a. The comparison between the GEACE calculation results with the soil moisture content products from the global land data assimilation system (GLDAS) showed that they are very highly consistent. The variations of regional mean soil moisture over the huang-huai-hai plain also exhibited a downward trend from 2003 to 2013 with an average declining rate about 0.74 mm/a. Based on water balance equation, we obtained the change of average groundwater storage and it showed a decreasing variability with a general declining trend with an average rate about 2.22 mm/a. In addition, the retrieved groundwater data was proven to be accurate compared to observations from groundwater wells measurement with high consistency and correlations. . Further investigations focused on analyzing the impacts of precipitation factors on groundwater variations, implying that the human influences are the main reasons for the decline in groundwater.

Paper Details

Date Published: 19 September 2016
PDF: 9 pages
Proc. SPIE 9975, Remote Sensing and Modeling of Ecosystems for Sustainability XIII, 99750G (19 September 2016); doi: 10.1117/12.2237333
Show Author Affiliations
Zenghui Kan, East China Normal Univ. (China)
Chaoshun Liu, East China Normal Univ. (China)
Fengxue Qiao, East China Normal Univ. (China)
Wei Gao, East China Normal Univ. (China)
Colorado State Univ. (United States)
Maosi Chen, Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9975:
Remote Sensing and Modeling of Ecosystems for Sustainability XIII
Wei Gao; Ni-Bin Chang, Editor(s)

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