Water storage changes (2003–2020) in the Ordos Basin, China, explained by GRACE data and interpretable deep learning.

Groundwater storage (GWS) decline, as well as total water storage (TWS) decline, in the (semi)arid Ordos Basin (China) poses great challenges to the water supply and ecological environment. In this study, the major factors causing the rapid loss of water storage during 2003–2020 are first investigated using correlation analysis, where the storage estimates are derived from the Gravity Recovery and Climate Experiment (GRACE) satellites. The major hydroclimatic drivers of monthly water storage changes are then explored among precipitation (P), evapotranspiration (ET), and runoff (RO) using an interpretable deep learning (IDL) method. The relative contribution of each driver is quantified by leveraging the interpretability nature of IDL. Results show that the GWS depletion (–0.82 cm/year) primarily accounts for the TWS loss (–0.73 cm/year) in the Ordos Basin under increased precipitation. The decreased TWS and GWS are both closely related to the increased vegetation density and coal production, indicating that they are the major drivers of the long-term water loss. At the monthly scale, the IDL method reveals that P and ET contribute over 75% to the changes of both TWS and GWS in most regions. The response lag of TWS to P and ET is generally 1–3 months. In contrast, GWS shows a more complicated response to P and ET with a longer lag range of 1–11 months in different regions due to the complicated Ordos Basin aquifer systems. These findings achieve a better understanding of hydrologic cycles and better guide sustainable water resources management in the Ordos Basin. [ABSTRACT FROM AUTHOR]