Spatiotemporal Differences of Groundwater Recovery in North China Plain Using GRACE and Well Data.

Ground water Pub Date : 2025-06-11 DOI:10.1111/gwat.13497
Hao Zhang, Linsong Wang, Zhenran Peng, Linbing Hu
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Abstract

The long-term depletion of groundwater storage (GWS) in the North China Plain (NCP) has recovered recently, but the spatiotemporal characteristics of this recovery and its driving factors are still unclear. For this study, we estimated the GWS in the NCP using data from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On mission (GRACE-FO) and in situ well measurements. We quantified the spatiotemporal characteristics and the drivers for the transition from long-term GWS depletion to its rapid recovery in the NCP. To identify the turning point of the GWS recovery time, we used the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) method combined with the Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) algorithm. The result shows that the GWS recovery in the southern NCP (February 2020 to October 2020) occurred earlier than in the northern NCP (November 2020 to August 2021). The GWS recovery was detected 7 months earlier in in situ wells compared with satellite data. This discrepancy is attributable to the differences in the data resolution between the spatial and in situ well measurements, as well as the more drastic response of in situ wells to groundwater changes. Both precipitation and the South-to-North Water Diversion (SNWD) project affected GWS recovery, leading to the observed spatiotemporal differences. The contributions to annual GWS changes (i.e., annual ΔGWS) from climatic and human factors were further quantified. Our results indicate that climate was the dominant driver, accounting for 87.63% of the annual ΔGWS in the NCP, while human activities contributed 12.37%.

基于GRACE和井资料的华北平原地下水采收率时空差异研究
近年来,华北平原地下水库存量的长期枯竭有所恢复,但恢复的时空特征及其驱动因素尚不清楚。在这项研究中,我们使用重力恢复和气候实验(GRACE)及其后续任务(GRACE- fo)和现场井测量的数据估计了NCP中的GWS。我们量化了NCP地区GWS从长期耗竭到快速恢复的时空特征和驱动因素。为了识别GWS恢复时间的拐点,我们采用了改进的全集合经验模态分解与自适应噪声(ICEEMDAN)方法结合贝叶斯突变、季节性和趋势估计(BEAST)算法。结果表明,南区(2020年2月~ 2020年10月)GWS恢复早于北区(2020年11月~ 2021年8月)。与卫星数据相比,在原位井中检测到GWS采收率的时间提前了7个月。这种差异是由于空间和原位井测量数据分辨率的差异,以及原位井对地下水变化的响应更为剧烈。降水和南水北调工程都影响GWS恢复,导致观测到的时空差异。进一步量化了气候和人为因素对GWS年变化(即ΔGWS年)的贡献。结果表明,气候是主要驱动因子,占年ΔGWS的87.63%,而人类活动贡献12.37%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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