152 citations as recorded by crossref.

1. Channel Water Storage Anomaly: A New Remotely Sensed Quantity for Global River Analysis S. Coss et al. 10.1029/2022GL100185
2. Reconstruction of continuous GRACE/GRACE-FO terrestrial water storage anomalies based on time series decomposition X. Yang et al. 10.1016/j.jhydrol.2021.127018
3. A compound event-oriented framework to tropical fire risk assessment in a changing climate A. Ribeiro et al. 10.1088/1748-9326/ac7342
4. Probabilistic reconstruction of sea-level changes and their causes since 1900 S. Dangendorf et al. 10.5194/essd-16-3471-2024
5. Human-Induced and Climate-Driven Contributions to Water Storage Variations in the Haihe River Basin, China Y. Zhong et al. 10.3390/rs11243050
6. Detection and Characterization of Active Slope Deformations with Sentinel-1 InSAR Analyses in the Southwest Area of Shanxi, China X. Shi et al. 10.3390/rs12030392
7. Evaluation of the Consistency of Three GRACE Gap-Filling Data A. Qian et al. 10.3390/rs14163916
8. A Comprehensive Evaluation of GRACE‐Like Terrestrial Water Storage (TWS) Reconstruction Products at an Interannual Scale During 1981–2019 S. Deng et al. 10.1029/2022WR034381
9. A dynamical downscaling method of groundwater storage changes using GRACE data J. Sun et al. 10.1016/j.ejrh.2023.101558
10. Causal inference reveals the dominant role of interannual variability of carbon sinks in complicated environmental-terrestrial ecosystems C. Dang et al. 10.1016/j.rse.2024.114300
11. GRACE-based groundwater drought in the Indochina Peninsula during 1979–2020: Changing properties and possible teleconnection mechanisms X. Song et al. 10.1016/j.scitotenv.2023.168423
12. Extending MESMER-X: a spatially resolved Earth system model emulator for fire weather and soil moisture Y. Quilcaille et al. 10.5194/esd-14-1333-2023
13. Annual runoff coefficient variation in a changing environment: a global perspective J. Xiong et al. 10.1088/1748-9326/ac62ad
14. A data-driven approach to generate past GRACE-like terrestrial water storage solution by calibrating the land surface model simulations W. Jing et al. 10.1016/j.advwatres.2020.103683
15. Water storage changes (2003–2020) in the Ordos Basin, China, explained by GRACE data and interpretable deep learning Z. Hu et al. 10.1007/s10040-023-02713-7
16. The great 1983 floods in South American large rivers: a continental hydrological modelling approach A. Fleischmann et al. 10.1080/02626667.2020.1747622
17. Global Projections of Storm Surges Using High‐Resolution CMIP6 Climate Models S. Muis et al. 10.1029/2023EF003479
18. Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land L. Beusch et al. 10.5194/esd-11-139-2020
19. Extending the Global Mass Change Data Record: GRACE Follow‐On Instrument and Science Data Performance F. Landerer et al. 10.1029/2020GL088306
20. Improved the Characterization of Flood Monitoring Based on Reconstructed Daily GRACE Solutions over the Haihe River Basin S. Nie et al. 10.3390/rs15061564
21. Can climate change signals be detected from the terrestrial water storage at daily timescale? F. Huo et al. 10.1038/s41612-024-00646-w
22. How realistic are multi-decadal reconstructions of GRACE-like total water storage anomalies? C. Hacker & J. Kusche 10.1016/j.jhydrol.2024.132180
23. Bidirectional drought‐related canopy dynamics across pantropical forests: a satellite‐based statistical analysis L. Liu et al. 10.1002/rse2.229
24. Contemporary sea-level changes from global to local scales: a review A. Cazenave & L. Moreira 10.1098/rspa.2022.0049
25. Trends and uncertainties of mass-driven sea-level change in the satellite altimetry era C. Camargo et al. 10.5194/esd-13-1351-2022
26. Filling GRACE data gap using an innovative transformer-based deep learning approach L. Wang & Y. Zhang 10.1016/j.rse.2024.114465
27. Reconstructed centennial precipitation-driven water storage anomalies in the Nile River Basin using RecNet and their suitability for studying ENSO and IOD impacts J. Wang et al. 10.1016/j.jhydrol.2024.132272
28. High-resolution temporal gravity field data products: Monthly mass grids and spherical harmonics from 1994 to 2021 M. Uz et al. 10.1038/s41597-023-02887-5
29. Origin of interannual variability in global mean sea level B. Hamlington et al. 10.1073/pnas.1922190117
30. Predictive Skill Assessment for Land Water Storage in CMIP5 Decadal Hindcasts by a Global Reconstruction of GRACE Satellite Data L. Jensen et al. 10.1175/JCLI-D-20-0042.1
31. Changes of terrestrial water storage during 1981–2020 over China based on dynamic-machine learning model E. Zhu et al. 10.1016/j.jhydrol.2023.129576
32. Climate Change and Hydrological Extremes J. Xiong & Y. Yang 10.1007/s40641-024-00198-4
33. Showcasing MESMER‐X: Spatially Resolved Emulation of Annual Maximum Temperatures of Earth System Models Y. Quilcaille et al. 10.1029/2022GL099012
34. Reconstructing GRACE-like time series of high mountain glacier mass anomalies B. Liu et al. 10.1016/j.rse.2022.113177
35. Soil Moisture Assimilation Improves Terrestrial Biosphere Model GPP Responses to Sub-Annual Drought at Continental Scale X. Xing et al. 10.3390/rs15030676
36. Providing Enhanced Insights into Groundwater Exchange Patterns through Downscaled GRACE Data J. Sun et al. 10.3390/rs16050812
37. Improved Drought Characteristics in the Pearl River Basin Based on Reconstructed GRACE Solution with Enhanced Temporal Resolution L. Wang et al. 10.3390/rs15194849
38. The Novel Microwave Temperature Vegetation Drought Index (MTVDI) Captures Canopy Seasonality across Amazonian Tropical Evergreen Forests L. Liu et al. 10.3390/rs13030339
39. Monitoring Droughts From GRACE B. Vishwakarma 10.3389/fenvs.2020.584690
40. Influence of Terrestrial Water Storage on Flood Potential Index in the Yangtze River Basin, China P. Yang et al. 10.3390/rs14133082
41. Future socio-ecosystem productivity threatened by compound drought–heatwave events J. Yin et al. 10.1038/s41893-022-01024-1
42. A Shift From Temperature to Water as the Primary Driver for Interannual Variability of the Tropical Carbon Cycle B. He et al. 10.1029/2023GL102812
43. Assessing the interannual and subseasonal variabilities in water storage using multi-source soil moisture products and GRACE/GRACE-FO satellites and its applications Q. Li et al. 10.1016/j.jhydrol.2023.130439
44. Bridging the Temporal Gaps in GRACE/GRACE–FO Terrestrial Water Storage Anomalies over the Major Indian River Basins Using Deep Learning P. Moudgil et al. 10.1007/s11053-024-10312-w
45. Random Forest-Based Reconstruction and Application of the GRACE Terrestrial Water Storage Estimates for the Lancang-Mekong River Basin S. Tang et al. 10.3390/rs13234831
46. Bridging the gap between GRACE and GRACE-FO using a hydrological model X. Zhang et al. 10.1016/j.scitotenv.2022.153659
47. Seesaw Terrestrial Wetting and Drying Between Eastern and Western Australia A. Chen et al. 10.1029/2020EF001893
48. Reinterpreting Global GRACE Trends Based on Century‐Long GRACE‐REC Data Y. Zhong et al. 10.1029/2023WR035817
49. Minimizing uncertainties in climate projections and water budget reveals the vulnerability of freshwater to climate change O. Adeyeri et al. 10.1016/j.oneear.2023.12.013
50. GTWS-MLrec: global terrestrial water storage reconstruction by machine learning from 1940 to present J. Yin et al. 10.5194/essd-15-5597-2023
51. Leaf shedding of Pan-Asian tropical evergreen forests depends on the synchrony of seasonal variations of rainfall and incoming solar radiation J. Wu et al. 10.1016/j.agrformet.2021.108691
52. Reconstructing the data gap between GRACE and GRACE follow-on at the basin scale using artificial neural network Y. Lai et al. 10.1016/j.scitotenv.2022.153770
53. An Interannual Probabilistic Assessment of Subsurface Water Storage Over Europe Using a Fully Coupled Terrestrial Model C. Hartick et al. 10.1029/2020WR027828
54. Sea level rise along China coast from 1950 to 2020 D. Mu et al. 10.1007/s11430-023-1240-x
55. Century‐Scale Reconstruction of Water Storage Changes of the Largest Lake in the Inner Mongolia Plateau Using a Machine Learning Approach C. Fan et al. 10.1029/2020WR028831
56. Filling the gap between GRACE and GRACE-FO data using a model integrating variational mode decomposition and long short-term memory: a case study of Northwest China J. Chu et al. 10.1007/s12665-022-10716-y
57. Reconstructing GRACE-derived terrestrial water storage anomalies with in-situ groundwater level measurements and meteorological forcing data P. Li et al. 10.1016/j.ejrh.2023.101528
58. Observed changes in dry-season water availability attributed to human-induced climate change R. Padrón et al. 10.1038/s41561-020-0594-1
59. Anthropogenic and Climate-Driven Water Storage Variations on the Mongolian Plateau S. Zheng et al. 10.3390/rs15174184
60. Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability K. Wang et al. 10.1038/s41467-022-31175-w
61. Process-based estimate of global-mean sea-level changes in the Common Era N. Gangadharan et al. 10.5194/esd-13-1417-2022
62. Recent decrease of the impact of tropical temperature on the carbon cycle linked to increased precipitation W. Zhang et al. 10.1038/s41467-023-36727-2
63. Downscaling Simulation of Groundwater Storage in the Beijing, Tianjin, and Hebei Regions of China Based on GRACE Data J. Sun et al. 10.3390/rs15061490
64. Integrating ICESat-2 altimetry and machine learning to estimate the seasonal water level and storage variations of national-scale lakes in China L. Song et al. 10.1016/j.rse.2023.113657
65. Trade‐Offs Between Spatial and Temporal Accuracy of Complementary Relationship Models for Evaporation in an Ungauged Basin X. Zhang et al. 10.1029/2022WR034222
66. The causes of sea-level rise since 1900 T. Frederikse et al. 10.1038/s41586-020-2591-3
67. Benchmarking large-scale evapotranspiration estimates: A perspective from a calibration-free complementary relationship approach and FLUXCOM N. Ma et al. 10.1016/j.jhydrol.2020.125221
68. Bridging the gap between GRACE and GRACE-FO missions with deep learning aided water storage simulations M. Uz et al. 10.1016/j.scitotenv.2022.154701
69. Water-balance-based evapotranspiration for 56 large river basins: A benchmarking dataset for global terrestrial evapotranspiration modeling N. Ma et al. 10.1016/j.jhydrol.2024.130607
70. Separating the Precipitation‐ and Non‐Precipitation‐ Driven Water Storage Trends in China Y. Zhong et al. 10.1029/2022WR033261
71. Spatio-temporal dynamics of water storage across Northwest China over the past four decades W. Cheng et al. 10.1016/j.ejrh.2023.101488
72. G‐RUN ENSEMBLE: A Multi‐Forcing Observation‐Based Global Runoff Reanalysis G. Ghiggi et al. 10.1029/2020WR028787
73. Autoregressive Reconstruction of Total Water Storage within GRACE and GRACE Follow-On Gap Period A. Lenczuk et al. 10.3390/en15134827
74. Quantifying the Central European Droughts in 2018 and 2019 With GRACE Follow‐On E. Boergens et al. 10.1029/2020GL087285
75. Characterizing drought events occurred in the Yangtze River Basin from 1979 to 2017 by reconstructing water storage anomalies based on GRACE and meteorological data S. Zheng et al. 10.1016/j.scitotenv.2023.161755
76. A Novel Standardized Drought and Flood Potential Index Based on Reconstructed Daily GRACE Data J. Xiong et al. 10.1175/JHM-D-22-0011.1
77. Anomalous Net Biome Exchange Over Amazonian Rainforests Induced by the 2015/16 El Niño: Soil Dryness‐Shaped Spatial Pattern but Temperature‐dominated Total Flux J. Wang et al. 10.1029/2023GL103379
78. Evaluation of evapotranspiration for exorheic basins in China using an improved estimate of terrestrial water storage change H. Bai et al. 10.1016/j.jhydrol.2022.127885
79. Models overestimate ecosystem water use efficiency for northern permafrost regions J. Wang & D. Liu 10.1016/j.agrformet.2023.109594
80. Reconstructing terrestrial water storage anomalies using convolution-based support vector machine I. Kalu et al. 10.1016/j.ejrh.2023.101326
81. A new precipitation emulator (PREMU v1.0) for lower-complexity models G. Liu et al. 10.5194/gmd-16-1277-2023
82. Spatial-temporal variations in evapotranspiration across the continental United States: An atmospheric water balance perspective S. Shang et al. 10.1016/j.jhydrol.2024.131699
83. Increasingly negative tropical water–interannual CO2 growth rate coupling L. Liu et al. 10.1038/s41586-023-06056-x
84. A Two‐Step Linear Model to Fill the Data Gap Between GRACE and GRACE‐FO Terrestrial Water Storage Anomalies X. Yang et al. 10.1029/2022WR034139
85. A hybrid approach for recovering high-resolution temporal gravity fields from satellite laser ranging A. Löcher & J. Kusche 10.1007/s00190-020-01460-x
86. Data‐Driven Gap Filling and Spatio‐Temporal Filtering of the GRACE and GRACE‐FO Records L. Gauer et al. 10.1029/2022JB025561
87. Hydrological Droughts of 2017–2018 Explained by the Bayesian Reconstruction of GRACE(‐FO) Fields S. Mo et al. 10.1029/2022WR031997
88. Long‐Term (1979‐Present) Total Water Storage Anomalies Over the Global Land Derived by Reconstructing GRACE Data F. Li et al. 10.1029/2021GL093492
89. GROOPS: A software toolkit for gravity field recovery and GNSS processing T. Mayer-Gürr et al. 10.1016/j.cageo.2021.104864
90. Estimating terrestrial water storage variations in Chile with the effects of earthquakes deducted P. Sun et al. 10.1080/02626667.2023.2230217
91. Global hydroclimatic drivers of terrestrial water storage changes in different climates X. Zhang et al. 10.1016/j.catena.2022.106598
92. Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data J. Xie et al. 10.5194/hess-26-5933-2022
93. Applying Reconstructed Daily Water Storage and Modified Wetness Index to Flood Monitoring: A Case Study in the Yangtze River Basin C. Xiao et al. 10.3390/rs15123192
94. Regional asymmetry in the response of global vegetation growth to springtime compound climate events J. Li et al. 10.1038/s43247-022-00455-0
95. Seasonal catchment memory of high mountain rivers in the Tibetan Plateau H. Gu et al. 10.1038/s41467-023-38966-9
96. Soil moisture seasonality alters vegetation response to drought in the Mongolian Plateau Z. Lu et al. 10.1088/1748-9326/abd1a2
97. Learning-based Reconstruction of GRACE Data Based on Changes in Total Water Storage and Its Accuracy Assessment Y. Su et al. 10.1007/s11770-024-1124-5
98. The efficacy of seasonal terrestrial water storage forecasts for predicting vegetation activity over Africa B. Cook et al. 10.1175/JHM-D-21-0046.1
99. Reconstruction of GRACE Mass Change Time Series Using a Bayesian Framework A. Rateb et al. 10.1029/2021EA002162
100. Hydrological variability in southern Siberia and the role of permafrost degradation L. Han & L. Menzel 10.1016/j.jhydrol.2021.127203
101. Rapid Mass Loss in West Antarctica Revealed by Swarm Gravimetry in the Absence of GRACE C. Zhang et al. 10.1029/2021GL095141
102. Divergent Causes of Terrestrial Water Storage Decline Between Drylands and Humid Regions Globally L. An et al. 10.1029/2021GL095035
103. Decline in terrestrial water recharge with increasing global temperatures C. Banerjee et al. 10.1016/j.scitotenv.2020.142913
104. Estimation of Terrestrial Water Storage Changes at Small Basin Scales Based on Multi-Source Data Q. Li et al. 10.3390/rs13163304
105. 1950~2020年中国沿海海平面上升 大. 穆 et al. 10.1360/N072023-0155
106. Filling the Data Gaps Within GRACE Missions Using Singular Spectrum Analysis S. Yi & N. Sneeuw 10.1029/2020JB021227
107. Using GRACE Data to Study the Impact of Snow and Rainfall on Terrestrial Water Storage in Northeast China A. Qian et al. 10.3390/rs12244166
108. Extending GRACE terrestrial water storage anomalies by combining the random forest regression and a spatially moving window structure W. Jing et al. 10.1016/j.jhydrol.2020.125239
109. Understanding the shift in drivers of terrestrial water storage decline in the central Inner Mongolian steppe over the past two decades X. Zhang et al. 10.1016/j.jhydrol.2024.131312
110. Evaluation of the Local Sea‐Level Budget at Tide Gauges Since 1958 J. Wang et al. 10.1029/2021GL094502
111. Reconstruction of GRACE Total Water Storage Through Automated Machine Learning A. Sun et al. 10.1029/2020WR028666
112. Reconstructing a long-term water storage-based drought index in the Yangtze River Basin Y. Zhong et al. 10.1016/j.scitotenv.2023.163403
113. Varying performance of eight evapotranspiration products with aridity and vegetation greenness across the globe H. Wang et al. 10.3389/fenvs.2023.1079520
114. Re-assessing global water storage trends from GRACE time series B. Vishwakarma et al. 10.1088/1748-9326/abd4a9
115. Calibration‐Free Complementary Relationship Estimates Terrestrial Evapotranspiration Globally N. Ma et al. 10.1029/2021WR029691
116. Identifying and separating climate- and human-driven water storage anomalies using GRACE satellite data B. Liu et al. 10.1016/j.rse.2021.112559
117. Using Satellite-Based Terrestrial Water Storage Data: A Review V. Humphrey et al. 10.1007/s10712-022-09754-9
118. Earth's Energy Imbalance From the Ocean Perspective (2005–2019) M. Hakuba et al. 10.1029/2021GL093624
119. Toward a Robust, Impact‐Based, Predictive Drought Metric S. Hobeichi et al. 10.1029/2021WR031829
120. A deep learning model for reconstructing centenary water storage changes in the Yangtze River Basin J. Wang et al. 10.1016/j.scitotenv.2023.167030
121. Terrestrial Evapotranspiration Over China From 1982 to 2020: Consistency of Multiple Data Sets and Impact of Input Data Y. Mao et al. 10.1029/2023JD039387
122. Reconstructing GRACE-like TWS anomalies for the Canadian landmass using deep learning and land surface model Q. Yu et al. 10.1016/j.jag.2021.102404
123. Reanalysis in Earth System Science: Toward Terrestrial Ecosystem Reanalysis R. Baatz et al. 10.1029/2020RG000715
124. Detecting and quantifying the impact of long-term terrestrial water storage changes on the runoff ratio in the head regions of the two largest rivers in China Z. Xu et al. 10.1016/j.jhydrol.2021.126668
125. Quantification and Assessment of Global Terrestrial Water Storage Deficit Caused by Drought Using GRACE Satellite Data J. Lu et al. 10.1109/JSTARS.2022.3180509
126. Solid Water Melt Dominates the Increase of Total Groundwater Storage in the Tibetan Plateau Y. Zou et al. 10.1029/2022GL100092
127. The Influence of ENSO on the Long‐Term Water Storage Anomalies in the Middle‐Lower Reaches of the Yangtze River Basin: Evaluation and Analysis X. Li et al. 10.1029/2023EA003007
128. A machine learning downscaling framework based on a physically constrained sliding window technique for improving resolution of global water storage anomaly G. Zhang et al. 10.1016/j.rse.2024.114359
129. Future response of ecosystem water use efficiency to CO2 effects in the Yellow River Basin, China S. Chen et al. 10.5194/hess-28-4989-2024
130. Assessment of anthropogenic and climate-driven water storage variations over water-stressed river basins of Ethiopia A. Yoshe 10.2166/nh.2024.169
131. Global Terrestrial Water Storage Reconstruction Using Cyclostationary Empirical Orthogonal Functions (1979–2020) H. Chandanpurkar et al. 10.3390/rs14225677
132. Quantifying the long-term changes of terrestrial water storage and their driving factors X. Shi et al. 10.1016/j.jhydrol.2024.131096
133. Projected changes in terrestrial water storage and associated flood potential across the Yangtze River basin J. Xiong et al. 10.1016/j.scitotenv.2022.152998
134. Evaluating different predictive strategies for filling the global GRACE/-FO terrestrial water storage anomalies gap X. Wan et al. 10.1016/j.jhydrol.2023.130216
135. Impacts of Human Activities and Climate Change on Water Storage Changes in Shandong Province, China L. Deng et al. 10.1007/s11356-022-18759-1
136. Integrating GRACE/GRACE Follow-On and Wells Data to Detect Groundwater Storage Recovery at a Small-Scale in Beijing Using Deep Learning Y. Hu et al. 10.3390/rs15245692
137. The increasingly dominant role of climate change on length of day variations M. Shahvandi et al. 10.1073/pnas.2406930121
138. Improving the Reliability of the Prediction of Terrestrial Water Storage in Yunnan Using the Artificial Neural Network Selective Joint Prediction Model Z. Shi et al. 10.1109/ACCESS.2021.3051049
139. Machine Learning as a Strategic Tool for Helping Cocoa Farmers in Côte D’Ivoire S. Ferraris et al. 10.3390/s23177632
140. The global land water storage data set release 2 (GLWS2.0) derived via assimilating GRACE and GRACE-FO data into a global hydrological model H. Gerdener et al. 10.1007/s00190-023-01763-9
141. The Role of Space-Based Observations for Groundwater Resource Monitoring over Africa A. Springer et al. 10.1007/s10712-022-09759-4
142. Machine learning and copula-based analysis of past changes in global droughts and socioeconomic exposures L. Fang et al. 10.1016/j.jhydrol.2023.130536
143. Data-driven reconstruction reveals large-scale ocean circulation control on coastal sea level S. Dangendorf et al. 10.1038/s41558-021-01046-1
144. Monitoring the Catastrophic Flood With GRACE-FO and Near-Real-Time Precipitation Data in Northern Henan Province of China in July 2021 C. Xiao et al. 10.1109/JSTARS.2022.3223790
145. Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States C. Sohoulande et al. 10.1016/j.jhydrol.2020.125053
146. Bayesian convolutional neural networks for predicting the terrestrial water storage anomalies during GRACE and GRACE-FO gap S. Mo et al. 10.1016/j.jhydrol.2021.127244
147. Missing sea level rise in southeastern Greenland during and since the Little Ice Age S. Woodroffe et al. 10.5194/cp-19-1585-2023
148. Hydrological response to long-lasting dry spell at the southern edge of Siberian permafrost L. Han & L. Menzel 10.1016/j.scitotenv.2024.171330
149. Quantifying the 2022 extreme drought in the Yangtze River Basin using GRACE-FO A. Duan et al. 10.1016/j.jhydrol.2024.130680
150. Reconstructing GRACE-type time-variable gravity from the Swarm satellites H. Richter et al. 10.1038/s41598-020-80752-w
151. Future response of ecosystem water use efficiency to CO2 effects in the Yellow River Basin, China S. Chen et al. 10.5194/hess-28-4989-2024
152. Bridging the gap between GRACE and GRACE follow-on monthly gravity field solutions using improved multichannel singular spectrum analysis F. Wang et al. 10.1016/j.jhydrol.2021.125972