Abstract

Abstract: Groundwater depletion is a serious threat to agriculture and economic development, with an adverse impact on the ecological environment in Beijing. With the successful implementation of the South-to-North Water Diversion Project (SNWDP), groundwater (GW) depletion is expected to be alleviated. Here, we bridged the gap of the monthly terrestrial storage anomaly (TWSA) observations of the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-On (GRACE-FO) missions, then downscaled the spatial resolution of GW storage anomaly (GWSA) from 0.5°×0.5° to 0.25°×0.25° in Beijing using deep learning (DL) method, and precisely quantified the characteristics and causes of GWSA before and after the SNWDP, including that 1)  reconstructed 0.5°×0.5° TWSA in Beijing during 2004 to 2021 using three DL architectures (Long Short-Term Memory (LSTM), Gate Recurrent Unit (GRU), Multilayer Perceptron (MLP)); 2) selected the optimal performance of DL for downscaling GWSA from 0.5°×0.5° to 0.25°×0.25°; 3) quantitatively analyzed of GWSA characteristics before and after the SNWDP basing on Random Forest (RF). The results indicated that the trend of downscaled GWSA was consistent with in-situ grounder water level measurements, while the seasonal amplitude differed. Before the SNWDP (2004-2014), the GW in Beijing showed a declining trend with a rate of -20.8 mm/yr, of which human factors contributed 75.7% (21.9% and 21.1% for domestic water and agricultural water, respectively), and climatic factors accounted for 24.1%. After the SNWDP (2015-2021), GW gradually increased by 39.3 mm/yr, and GW was significantly restored, of which the human factors accounted for 59.2% (30.7% and 14.2% for domestic water and water diverted to Beijing by the SNWDP, respectively). Our research could provide a new reliable theoretical support and technical reference for GRACE/GRACE-FO dynamic monitoring of groundwater.Keywords: Beijing GW storage; spatial resolution downscaling; DL; GRACE/GRACE-FO; SNWDP

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