Study region Mainland China. Study focus Bridging the nearly one-year data gap between the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On mission (GRACE-FO) remains a key challenge in terrestrial water storage anomaly (TWSA) studies. However, the adequacy of trend separation in TWSA reconstruction has received limited attention. To address this, a nonlinear trend decomposition framework was developed to isolate continuous, low-frequency trends directly from TWSA time series. Using this framework, we reconstructed the TWSA driven by various hydro-climatic variables (including precipitation, temperature, evapotranspiration, runoff, and CLSMTWSA), and subsequently conducted comprehensive comparisons and applications. New hydrological insights for the region The nonlinear framework enhances reconstruction accuracy at both basin and grid scales. Across more than 15, 000 grid cells nationwide, it outperformed the piecewise linear method, increasing the Pearson correlation coefficient (CC), Nash-Sutcliffe efficiency (NSE), and Kling-Gupta efficiency (KGE) by 2. 1%, 4. 3%, and 28. 4%, respectively, while reducing the normalized root mean square error (NRMSE) by 40. 0%. Relative to linear decomposition, the CC, NSE, and KGE improvements reached 5. 4%, 10. 3%, and 59. 3%, respectively, with a 50. 0% reduction in NRMSE. Furthermore, the reconstructed TWSA successfully captures a major flood in May 2018 within the gap, and effectively quantifies the relative contributions of human activities and natural climate variability. These prominent advantages achieved in TWSA reconstruction firmly demonstrate the global generalizability and robust application potential of this nonlinear framework.
Nie et al. (Wed,) studied this question.