Variations in China's terrestrial water storage over the past decade using GRACE data

• Main Authors: Qian Zhao, Weiwei Wu, Yunlong Wu
• Format: Article
• Language: English
• Published: KeAi Communications Co., Ltd. 2015-05-01
• Series: Geodesy and Geodynamics
• Subjects: EOF (Empirical orthogonal function); GRACE (Gravity Recovery and Climate Experiment); Gravity field; Terrestrial water storage; Groundwater storage; GLDAS (Global Land Data Assimilation System); Monthly gravity field model; Traditional polynomial fitting method
• Online Access: http://www.sciencedirect.com/science/article/pii/S1674984715000373

Variations in China's terrestrial water storage from March 2003 to February 2013 were determined using data from the Gravity Recovery and Climate Experiment (GRACE) monthly gravity field model provided by the Center for Space Research. The results were compared with the variations in surface water estimated using the Global Land Data Assimilation System (GLDAS) hydrological model. The results indicated a decline in terrestrial water storage in the Shanxi and Xinjiang Tianshan regions over the past decade with a downward trend that reached −7.76 ± 0.71 mm/a and −5.8 ± 0.67 mm/a, respectively. Anthropogenic activities were considered to be the major cause of this terrestrial water loss (especially groundwater) in these regions. In contrast, the intersection of the Xinjiang and Tibet Autonomous Regions and the Qinghai Province showed an upward trend in the terrestrial water storage at a rate of 9.06 ± 0.37 mm/a, which is closely related to the high-quality local ecological environment and lack of human activities. At the intersections between the Chongqing, Guizhou, and Hunan Provinces and between the Jiangxi, Zhejiang, and Fujian Provinces, the terrestrial water storage increased at rates of 7.86 ± 0.9 and 8.68 ± 0.8 mm/a, respectively. These two regions received abundant annual precipitation; moreover, there was no considerable variation in the amount of groundwater storage over the past decade. In addition, the empirical orthogonal function (EOF) method used in this study could eliminate correlated errors in the GRACE monthly gravity field model more effectively than the traditional polynomial fitting method, and it did not generate false signals.