(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) in PP declines faster (À46.5 ± 6.8 mm/yr) than the deep GWS in ECP (À16.9 ± 1.9 mm/yr). However, the shallow GWS in PP recovered more quickly especially during the 2008-2011 drought period. Despite its lower magnitude, the GRACE-derived GWS depletion in ECP reveals the overexploitation of deep GWS. This study demonstrated that the heterogeneous GWS variations can potentially be detected by GRACE at the subregional scale smaller than the typical GRACE footprint (200,000 km 2 ).

No abstract

Groundwater (GW) overexploitation is a critical issue in North China with large GW level declines resulting in urban water scarcity, unsustainable agricultural production, and adverse ecological impacts. One approach to addressing GW depletion was to transport water from the humid south. However, impacts of water diversion on GW remained largely unknown. Here, we show impacts of the central South-to-North Water Diversion on GW storage recovery in Beijing within the context of climate variability and other policies. Water diverted to Beijing reduces cumulative GW depletion by~3.6 km 3 , accounting for 40% of total GW storage recovery during 2006-2018. Increased precipitation contributes similar volumes to GW storage recovery of~2.7 km 3 (30%) along with policies on reduced irrigation (~2.8 km 3 , 30%). This recovery is projected to continue in the coming decade. Engineering approaches, such as water diversions, will increasingly be required to move towards sustainable water management.

Regional evapotranspiration (ET) can be enhanced by human activities such as irrigation or reservoir impoundment. Here the potential of using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data in water budget calculations to detect human‐induced ET change is investigated over the Haihe River basin of China. Comparison between GRACE‐based monthly ET estimate (2005–2012) and Global Land Data Assimilation System (GLDAS)‐modeled ET indicates that human‐induced ET due to intensive groundwater irrigation from March to May can only be detected by GRACE. GRACE‐based ET (521.7 ± 21.1 mm/yr), considerably higher than GLDAS ET (461.7 ± 29.8 mm/yr), agrees well with existing estimates found in the literature and indicates that human activities contribute to a 12% increase in ET. The double‐peak seasonal pattern of ET (in May and August) as reported in published studies is well reproduced by GRACE‐based ET estimate. This study highlights the unique capability of GRACE in detecting anthropogenic signals over regions with large groundwater consumption.

Groundwater plays a critical role in the global water cycle and is the drinking source for almost half of the world's population. However, exact quantification of its storage change remains elusive due primarily to limited ground observations in space and time. The Gravity Recovery and Climate Experiment (GRACE) twin-satellite data have provided global observations of water storage variations at monthly sampling for over a decade and a half, and is enable to estimate changes in groundwater storage (GWS) after removing other water storage components using auxiliary datasets and models. In this paper, we present an overview of GWS changes in three main aquifers within China using GRACE data, and conduct a comprehensive accuracy assessment using in situ ground well observations and hydrological models. GRACE detects a significant GWS depletion rate of 7.2 ± 1.1 km 3 /yr in the North China Plain (NCP) during 2002-2014, consistent with ground well observations and model predictions. The Liaohe River Basin (LRB) experienced a pronounced GWS decline during 2005-2009, at a depletion rate of 5.0 ± 1.2 km 3 /yr. Since 2010, GRACE-based GWS reveal a slow recovery in the LRB, with excellent agreement with ground well observations. For the whole study period 2002-2014, no significant long-term GWS depletion is found in the LRB nor in the Tarim Basin. A case study in the Inner Tibetan Plateau highlights there still exist large uncertainties in GRACE-based GWS change estimates.