This paper presents an analysis of regional terrestrial water storage (TWS) changes and drought characteristics in Southwest China, encompassing Sichuan Province, Chongqing Municipality, Yunnan Province, and Guizhou Province. Existing geodetic datasets, such as those from the Gravity Recovery and Climate Experiment (GRACE) and its successor satellites (GRACE Follow-On), as well as Global Navigation Satellite System (GNSS) data, face significant challenges related to limited spatial resolution and insufficient station distribution. To address these issues, we propose a novel inversion method that integrates GNSS and GRACE/GFO data by establishing virtual stations for GRACE/GFO data and determining the weight values between GNSS and GRACE/GFO using the Akaike Bayesian Information Criterion (ABIC). This method allows for estimating the TWS changes from December 2010 to June 2023 and monitoring drought conditions in conjunction with hydrometeorological data (precipitation, evapotranspiration, and runoff). The results show strong correlations between TWS changes from the joint inversion and GNSS (0.98) and GRACE/GFO (0.69). The Joint Drought Severity Index (Joint-DSI) indicates five major drought events, with the most severe occurring from July 2022 to June 2023, with an average deficit of 86.133 km³. Extreme drought primarily impacts Sichuan and Yunnan, driven by abnormal precipitation deficits. The joint inversion methodology presented in this study provides a practical approach for monitoring TWS changes and assessing drought characteristics in Southwest China. This paper leverages the complementary strengths of GNSS and GRACE/GFO data and offers new insights into regional water resource management and drought detection.

Geodetic data, especially from the Global Navigation Satellite System (GNSS) and Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GFO), are extensively employed in hydrological drought monitoring across various spatial scales due to their unique spatial resolution. In recent years, Brazil has experienced some of the most severe drought events in decades. This study focuses on Brazil and its northeastern Amazon Plain, investigates the spatiotemporal characteristics of terrestrial water storage (TWS) changes, and calculates the hydrological drought severity index (DSI) and meteorological drought index for comprehensive analysis of drought conditions. The results indicate that the time series of TWS changes derived from different data sources are highly correlated, with correlation coefficients exceeding 0.85, and are consistent with the trend of precipitation variation, reflecting notable seasonal fluctuations, i.e., an increase in precipitation during the spring and summer seasons leads to a rise in TWS, while a decrease in precipitation during the autumn and winter seasons triggers a reduction in TWS. In terms of spatial distribution, the annual amplitude of TWS variation is most pronounced in the northeastern Amazon Plain. The highest amplitude, approximately 800 mm, is observed near the Amazon River Basin, and this amplitude gradually weakens from northeast to southwest. GNSS and GRACE/GFO data reveal four hydrological drought events in Brazil from 2013 to 2024, with two of these events detected using GRACE/GFO data. The most severe droughts occurred between 2023 and 2024, primarily driven by prolonged precipitation deficits and the El Niño phenomenon, lasting up to nine months. Additionally, three distinct drought events were identified in the Amazon Plain, suggesting that its hydrological dynamics significantly influenced Brazil’s drought conditions. These results demonstrate the capability of geodetic data to effectively monitor water deficit and drought duration on both small spatial scales and short timeframes, thereby providing crucial support for timely responses to and the management of hydrological drought events.