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Groundwater Depletion Estimated from GRACE: A Challenge of Sustainable Development in an Arid Region of Central Asia

Journal article
Authors Z. Y. Hu
Q. M. Zhou
X. Chen
Deliang Chen
J. F. Li
M. Y. Guo
G. Yin
Z. Duan
Published in Remote Sensing
Volume 11
Issue 16
Publication year 2019
Published at Department of Earth Sciences
Language en
Links dx.doi.org/10.3390/rs11161908
Keywords groundwater variation, terrestrial water storage, GRACE, GLDAS, arid region, sustainable, climate-change, data sets, evapotranspiration, precipitation, variability, irrigation, regression, xinjiang, river
Subject categories Earth and Related Environmental Sciences

Abstract

Under climate change and increasing water demands, groundwater depletion has become regional and global threats for water security, which is an indispensable target to achieving sustainable developments of human society and ecosystems, especially in arid and semiarid regions where groundwater is a major water source. In this study, groundwater depletion of 2003-2016 over Xinjiang in China, a typical arid region of Central Asia, is assessed using the gravity recovery and climate experiment (GRACE) satellite and the global land data assimilation system (GLDAS) datasets. In the transition of a warm-dry to a warm-wet climate in Xinjiang, increases in precipitation, soil moisture and snow water equivalent are detected, while GRACE-based groundwater storage anomalies (GWSA) exhibit significant decreasing trends with rates between-3.61 +/- 0.85 mm/a of CSR-GWSA and -3.10 +/- 0.91 mm/a of JPL-GWSA. Groundwater depletion is more severe in autumn and winter. The decreases in GRACE-based GWSA are in a good agreement with the groundwater statistics collected from local authorities. However, at the same time, groundwater abstraction in Xinjiang doubled, and the water supplies get more dependent on groundwater. The magnitude of groundwater depletion is about that of annual groundwater abstraction, suggesting that scientific exploitation of groundwater is the key to ensure the sustainability of freshwater withdrawals and supplies. Furthermore, GWSA changes can be well estimated by the partial least square regression (PLSR) method based on inputs of climate data. Therefore, GRACE observations provide a feasible approach for local policy makers to monitor and forecast groundwater changes to control groundwater depletion.

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