29 citations as recorded by crossref.

1. Revealing the spatiotemporal evolution of the 2024 extreme flood in Guangdong Province: Insights from GRACE-FO and in situ measurements S. Liu et al.
2. A novel spatial downscaling algorithm based on deep learning considering geographical spatial heterogeneity and nonlinear changes: a case study of the Yangtze River Basin C. Luo et al.
3. Deep learning-aided temporal downscaling of GRACE-derived terrestrial water storage anomalies across the Contiguous United States M. Uz et al.
4. Multi-reservoirs joint flood control scheduling using a two-layer hedging robust optimization method under uncertain inflows X. Yu et al.
5. Decomposition-based reconstruction scheme for GRACE data with irregular temporal intervals Z. Yuan & X. Chen
6. A Framework for Characterization of Drought Events at the Basin Scale Based on High-Resolution Terrestrial Water Storage Reconstruction Z. Yuan et al.
7. Long short-term memory exploitation of satellite gravimetry to infer floods O. Sorkhabi & J. Awange
8. A semi-supervised LSTM framework for spatiotemporal downscaling of GRACE-derived terrestrial water storage anomalies to improve flood monitoring in the Yarlung Tsangpo River basin Y. Hu et al.
9. Evaluating Terrestrial Water Storage, Fluxes, and Drivers in the Pearl River Basin from Downscaled GRACE/GFO and Hydrometeorological Data Y. Xiong et al.
10. Significant variations in terrestrial water flux in mainland China during 2024 using GRACE-FO: impacts of extreme climate events Y. Zhong et al.
11. Applying Reconstructed Daily Water Storage and Modified Wetness Index to Flood Monitoring: A Case Study in the Yangtze River Basin C. Xiao et al.
12. Benchmarking multi-model evapotranspiration in the Yangtze River Basin using GNSS/GRACE fusion and anthropogenic disturbance quantification C. Chen et al.
13. Spatiotemporal evolution of 1998 extreme flood event in the Yangtze River basin from the perspective of the reconstructed GRACE/GRACE-FO data L. Cui et al.
14. Evaluating flood potential in the Mahanadi River Basin, India, using Gravity Recovery and Climate Experiment (GRACE) data and topographic flood susceptibility index under non-stationary framework S. Bhere & M. Reddy
15. Assessing and attributing flood potential in Brazil using GPS 3D deformation X. Yang et al.
16. Monitoring Significant Terrestrial Water Storage Increase From the “237” Extreme Flood Around the Haihe River Basin Using GRACE-FO and Precipitation Reconstruction J. Zhou et al.
17. Spatiotemporal Variability of Current and Future Sub‐Daily Rainfall in Japan Using State‐Of‐The‐Art High‐Quality Data Sets W. Zhao et al.
18. Spatial downscaling of GRACE terrestrial water storage anomalies for drought and flood potential assessment G. Yin et al.
19. Seasonal catchment memory of high mountain rivers in the Tibetan Plateau H. Gu et al.
20. Fusion and Analysis of Multi-Source Precipitation Data (2003–2021) in the Yangtze River Basin R. Sun et al.
21. A three-dimensional Copula-based standardized temperature precipitation evapotranspiration water storage index for comprehensive drought monitoring X. Huang et al.
22. Approaching the 1.5 °C warming threshold and escalating seasonal warm extremes in the Yangtze River Basin A. Dilawar et al.
23. Identification of Driving Factors of Long-Term Terrestrial Water Storage Anomaly Trend Changes in the Yangtze River Basin Based on Multisource Data and Geographical Detector Method Q. Li et al.
24. Exploring the utility of GRACE measurements for characterizing karst systems at a continental scale C. Orazulike et al.
25. Downscaling and Gap-Filling GRACE-Based Terrestrial Water Storage Anomalies in the Qinghai–Tibet Plateau Using Deep Learning and Multi-Source Data J. Chen et al.
26. The Flow of the Yangtze River Inverted From a Continuous Global Navigation Satellite System Station R. Zou et al.
27. Identification of drought-flood abrupt alternation thresholds triggering vegetation loss L. Wang et al.
28. High-resolution groundwater storage anomalies in the Middle and Lower Yangtze River Basin of China using machine learning fusion of in-situ wells, satellite gravity and hydrological model L. Hu et al.
29. Exploring potential drivers of terrestrial water storage anomaly trends in the Yangtze River Basin (2002–2019) J. Wang et al.