We invert daily GNSS vertical position time series for terrestrial water storage (TWS) changes and characterize their spatiotemporal patterns using various geodetic and hydrological data in Sichuan which features complex climatic and geographical conditions. Our inversion strategy depends on a variational Bayesian principal component analysis (VBPCA), which recovers the equivalent water height (EWH) changes using three principal components that explain 82% of the data variance. Various data sets from GNSS, GRACE, and GLDAS indicate an increasing seasonal water variability from northeast to southwest Sichuan. The GNSS modeling results reveal significant annual EWH amplitudes (up to 300 mm), which are largely underestimated in both GRACE‐EWH (∼120 mm) and GLDAS‐EWH (∼100 mm) products. The GNSS‐EWH also shows considerable seasonal changes in the high‐altitude plateau but subtle seasonal oscillations in the lowland basin, whereas this sharp contrast is invisible in GRACE‐ and GLDAS‐EWH primarily due to coarse spatial resolution. The GNSS inferred water products are used to determine the scaling factor for GRACE, with a value of 2.1 in Sichuan. The regional average precipitation peaks in July, about 1–2 months ahead of the maximum of monthly water heights. A bimodal feature in daily precipitation data is most notable in the low‐elevation Sichuan Basin and results in two peaks in daily GNSS‐EWH time series. Our results demonstrate that GNSS can serve as an independent tool for measuring water storage with high spatiotemporal resolution and provides additional constraints for understanding hydrological dynamics.

We introduce a new hydrological index that enables assessment of extreme events every few days from the GRACE Follow‐On (GRACE‐FO) satellite mission. The Mass Change Index (MCI) was developed by standardizing instantaneous satellite gravity anomalies computed directly from orbit perturbations. It is based on hydrology‐related gravity change, namely, total water storage change, and thus equally sensitive to wet and dry anomalies. The key innovation of MCI is its sensitivity to instantaneous mass changes as opposed to monthly mean changes. GRACE‐FO's ground track permits MCI retrievals every 5–6 days in most low and mid latitude regions. We demonstrate the application of MCI to investigate hydrological extremes in the middle‐lower Yangtze River Basin (MLYRB). MCI detects extreme wet conditions (standardized index of 2.0–3.0) along the Yangtze River mainstream related to the catastrophic flood in 2020, consistent with daily streamflow observations. In contrast, a typical GRACE‐FO based monthly drought index significantly underestimates the severity of the event and misidentifies timing of the onset. MCI also detects extreme dry conditions (−2.0 to −2.5) prevailing within MLYRB, related to the unprecedented heatwave and drought event during the summer of 2022. A streamflow index and the monthly drought index both underestimate the severity of the event. MCI retains information in intersatellite range measurements that may be lost when processing monthly gravity solutions. It can also be processed more rapidly, increasing its potential value for hydrological monitoring systems and other operational applications.