Long-term Terrestrial Water Storage Anomalies (TWSA) can be used to quantitatively characterize hydrological drought features. TWSA data in the Dongting Lake Basin (DTLB) were retrieved from multiple datasets, including satellite gravimetry (Gravity Recovery and Climate Experiment satellites and the succeeding Follow-On mission), global hydrology models (WaterGAP Global Hydrology Model, v2.2e), and a reanalysis model (Modern-Era Retrospective Analysis for Research and Applications, version 2). These TWSA datasets, along with observed temperature and precipitation data, were utilized to compare the suitability of two methods—the General Regression Neural Network and Long Short-Term Memory Neural Network—for reconstructing long-term TWSA in the DTLB. Quantitative analyses of hydrological drought characteristics were conducted using the long-term TWSA. The results indicate that in the DTLB, the reconstructed TWSA using General Regression Neural Network is superior to that obtained using Long Short-Term Memory Neural Network, and reconstructions using Modern-Era Retrospective Analysis for Research and Applications-2 as input data outperform those using WaterGAP Global Hydrology Model. Since 1980, terrestrial water storage in the DTLB has shown an increasing trend, partly influenced by the rising water storage capacity of reservoirs. The water storage deficit index, estimated by removing the increasing trend in reservoir storage, provided a more accurate representation of historical hydrological drought characteristics. From July to December 2022, the DTLB experienced an extreme drought, with a total terrestrial water storage deficit intensity reaching -790 mm, of which -140 mm was attributed to the water storage deficit after adjusting for the increasing trend in reservoir storage. This study ① emphasized the significant influence of reservoir water storage trend on accurate assessment of hydrological drought; ② provided a theoretical and methodological guidance on dynamic monitoring of water resources, drought and flood monitoring and assessment for the Dongting Lake Basin and other basins or regions globally;③ provided references for scientific and rational management of basin-scale water resources.