123 citations as recorded by crossref.

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2. Accounting for spatial correlation errors in the assimilation of GRACE into hydrological models through localization M. Khaki et al. 10.1016/j.advwatres.2017.07.024
3. A study of Bangladesh's sub-surface water storages using satellite products and data assimilation scheme M. Khaki et al. 10.1016/j.scitotenv.2017.12.289
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6. Progress in joint application of crop models and hydrological models Y. You et al. 10.1016/j.agwat.2024.108746
7. Comparison and Assessment of Three Advanced Land Surface Models in Simulating Terrestrial Water Storage Components over the United States Y. Xia et al. 10.1175/JHM-D-16-0112.1
8. Global-Scale Evaluation of XCO2 Products from GOSAT, OCO-2 and CarbonTracker Using Direct Comparison and Triple Collocation Method Y. Chen et al. 10.3390/rs14225635
9. Hydrological trends captured by assimilating GRACE total water storage data into the CLM5-BGC model H. Chi et al. 10.1016/j.jhydrol.2023.130527
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11. Exploring the Potential of Satellite Solar-Induced Fluorescence to Constrain Global Transpiration Estimates B. Pagán et al. 10.3390/rs11040413
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13. Triple collocation-based error estimation and data fusion of global gridded precipitation products over the Yangtze River basin C. Chen et al. 10.1016/j.jhydrol.2021.127307
14. Terrestrial Water Storage Change Retrieved by GRACE and Its Implication in the Tibetan Plateau: Estimating Areal Precipitation in Ungauged Region Y. Jia et al. 10.3390/rs12193129
15. Comparing global hydrological models and combining them with GRACE by dynamic model data averaging (DMDA) N. Mehrnegar et al. 10.1016/j.advwatres.2020.103528
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17. Terrestrial water storage changes in the Bug river transboundary catchment observed by GRACE and water balance analysis T. Solovey et al. 10.15407/Meteorology2024.06.004
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19. Modelling Freshwater Resources at the Global Scale: Challenges and Prospects P. Döll et al. 10.1007/s10712-015-9343-1
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21. Evaluation of Drydown Processes in Global Land Surface and Hydrological Models Using Flux Tower Evapotranspiration A. Martínez-de la Torre et al. 10.3390/w11020356
22. Climate Change and Hydrological Extremes J. Xiong & Y. Yang 10.1007/s40641-024-00198-4
23. Triple collocation-based multi-source evaporation and transpiration merging J. Park et al. 10.1016/j.agrformet.2023.109353
24. Rivers and Floodplains as Key Components of Global Terrestrial Water Storage Variability A. Getirana et al. 10.1002/2017GL074684
25. Estimating Terrestrial Snow Mass via Multi‐Sensor Assimilation of Synthetic AMSR‐E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals J. Wang et al. 10.1029/2021WR029880
26. Assessing daily GRACE Data Assimilation during flood events of the Brahmaputra River Basin L. Retegui-Schiettekatte et al. 10.1016/j.scitotenv.2025.179181
27. Assimilation of gridded terrestrial water storage observations from GRACE into a land surface model M. Girotto et al. 10.1002/2015WR018417
28. Combining Physically Based Modeling and Deep Learning for Fusing GRACE Satellite Data: Can We Learn From Mismatch? A. Sun et al. 10.1029/2018WR023333
29. Multi-mission satellite remote sensing data for improving land hydrological models via data assimilation M. Khaki et al. 10.1038/s41598-020-75710-5
30. The potential of global reanalysis datasets in identifying flood events in Southern Africa G. Gründemann et al. 10.5194/hess-22-4667-2018
31. The 2019–2020 Rise in Lake Victoria Monitored from Space: Exploiting the State-of-the-Art GRACE-FO and the Newly Released ERA-5 Reanalysis Products M. Khaki & J. Awange 10.3390/s21134304
32. Challenges of the Blue Economy: evidence and research trends R. Martínez-Vázquez et al. 10.1186/s12302-021-00502-1
33. Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models B. Li et al. 10.1038/s41598-019-47219-z
34. Surface Micro-Relief Evolution in Southeast Tibet Based on InSAR Technology . Gesangzhuoma et al. 10.3390/land14030503
35. Improving drought simulations within the Murray-Darling Basin by combined calibration/assimilation of GRACE data into the WaterGAP Global Hydrology Model M. Schumacher et al. 10.1016/j.rse.2017.10.029
36. Performance of Different Ensemble Kalman Filter Structures to Assimilate GRACE Terrestrial Water Storage Estimates Into a High‐Resolution Hydrological Model: A Synthetic Study A. Shokri et al. 10.1029/2018WR022785
37. The effect of surge on riverine flood hazard and impact in deltas globally D. Eilander et al. 10.1088/1748-9326/ab8ca6
38. Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model M. Khaki et al. 10.1016/j.advwatres.2017.07.001
39. Making the Best Use of GRACE, GRACE‐FO and SMAP Data Through a Constrained Bayesian Data‐Model Integration N. Mehrnegar et al. 10.1029/2023WR034544
40. Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate V. Levizzani & E. Cattani 10.3390/rs11192301
41. Global Estimation and Assessment of Monthly Lake/Reservoir Water Level Changes Using ICESat-2 ATL13 Products N. Xu et al. 10.3390/rs13142744
42. Benchmarking global hydrological and land surface models against GRACE in a medium-sized tropical basin S. Bolaños Chavarría et al. 10.5194/hess-26-4323-2022
43. Nonparametric Data Assimilation Scheme for Land Hydrological Applications M. Khaki et al. 10.1029/2018WR022854
44. Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response S. Tian et al. 10.5194/hess-23-1067-2019
45. Global Calibration and Error Estimation of Altimeter, Scatterometer, and Radiometer Wind Speed Using Triple Collocation A. Ribal & I. Young 10.3390/rs12121997
46. Assessing modern river sediment discharge to the ocean using satellite gravimetry M. Mouyen et al. 10.1038/s41467-018-05921-y
47. How long is the memory of forest growth to rainfall in asynchronous climates? R. Joshi et al. 10.1016/j.ecolind.2022.109057
48. Modeling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects Y. Wada 10.1007/s10712-015-9347-x
49. Unsupervised ensemble Kalman filtering with an uncertain constraint for land hydrological data assimilation M. Khaki et al. 10.1016/j.jhydrol.2018.06.080
50. GRACE-REC: a reconstruction of climate-driven water storage changes over the last century V. Humphrey & L. Gudmundsson 10.5194/essd-11-1153-2019
51. A global streamflow reanalysis for 1980–2018 L. Alfieri et al. 10.1016/j.hydroa.2019.100049
52. Impacts of climate change on the streamflow of a large river basin in the Australian tropics using optimally selected climate model outputs M. Usman et al. 10.1016/j.jclepro.2021.128091
53. Water cycle science enabled by the GRACE and GRACE-FO satellite missions M. Rodell & J. Reager 10.1038/s44221-022-00005-0
54. Recent Changes in Land Water Storage and its Contribution to Sea Level Variations Y. Wada et al. 10.1007/s10712-016-9399-6
55. Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges B. Li et al. 10.1029/2018WR024618
56. Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges D. Miralles et al. 10.1111/nyas.13912
57. Comparison of Data‐Driven Techniques to Reconstruct (1992–2002) and Predict (2017–2018) GRACE‐Like Gridded Total Water Storage Changes Using Climate Inputs F. Li et al. 10.1029/2019WR026551
58. Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations P. López López et al. 10.5194/hess-20-3059-2016
59. A two-update ensemble Kalman filter for land hydrological data assimilation with an uncertain constraint M. Khaki et al. 10.1016/j.jhydrol.2017.10.032
60. Deduction of reservoir operating rules for application in global hydrological models H. Coerver et al. 10.5194/hess-22-831-2018
61. Error covariance calculation for forecast bias estimation in hydrologic data assimilation V. Pauwels & G. De Lannoy 10.1016/j.advwatres.2015.05.013
62. 100 Years of Progress in Hydrology C. Peters-Lidard et al. 10.1175/AMSMONOGRAPHS-D-18-0019.1
63. The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models A. Gevaert et al. 10.5194/hess-22-4649-2018
64. Hydrological reanalysis across the 20th century: A case study of the Amazon Basin S. Wongchuig et al. 10.1016/j.jhydrol.2019.01.025
65. Triple Collocation-Based Uncertainty Analysis and Data Fusion of Multi-Source Evapotranspiration Data Across China D. Wang et al. 10.3390/atmos15121410
66. Understanding the intra-annual variability of streamflow by incorporating terrestrial water storage from GRACE into the Budyko framework in the Qinba Mountains P. Huang et al. 10.1016/j.jhydrol.2021.126988
67. Land Surface Model Calibration Using Satellite Remote Sensing Data M. Khaki 10.3390/s23041848
68. A Comparative Study of GRACE with Continental Evapotranspiration Estimates in Australian Semi-Arid and Arid Basins: Sensitivity to Climate Variability and Extremes H. Shen et al. 10.3390/w9090614
69. Global peak water limit of future groundwater withdrawals H. Niazi et al. 10.1038/s41893-024-01306-w
70. On the Use of Adaptive Ensemble Kalman Filtering to Mitigate Error Misspecifications in GRACE Data Assimilation A. Shokri et al. 10.1029/2018WR024670
71. A systematic impact assessment of GRACE error correlation on data assimilation in hydrological models M. Schumacher et al. 10.1007/s00190-016-0892-y
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73. Acceleration in the Global Mean Sea Level Rise: 2005–2015 S. Yi et al. 10.1002/2017GL076129
74. Exploring groundwater and soil water storage changes across the CONUS at 12.5 km resolution by a Bayesian integration of GRACE data into W3RA N. Mehrnegar et al. 10.1016/j.scitotenv.2020.143579
75. Reanalysis in Earth System Science: Toward Terrestrial Ecosystem Reanalysis R. Baatz et al. 10.1029/2020RG000715
76. Coupling a global glacier model to a global hydrological model prevents underestimation of glacier runoff P. Wiersma et al. 10.5194/hess-26-5971-2022
77. Evaluating Precipitation Datasets Using Surface Water and Energy Budget Closure S. Hobeichi et al. 10.1175/JHM-D-19-0255.1
78. Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins E. Nkiaka et al. 10.5194/hess-26-5899-2022
79. Changes of Hydrological Components in Arctic Rivers Based on Multi-Source Data during 2003–2016 H. Wu et al. 10.3390/w13243494
80. Towards hybrid modeling of the global hydrological cycle B. Kraft et al. 10.5194/hess-26-1579-2022
81. Groundwater Pumping Is a Significant Unrecognized Contributor to Global Anthropogenic Element Cycles M. Stahl 10.1111/gwat.12817
82. Evaluating dynamics of GRACE groundwater and its drought potential in Taihang Mountain Region, China M. Liu et al. 10.1016/j.jhydrol.2022.128156
83. Geodetic first order data assimilation using an extended Kalman filtering technique I. Kalu et al. 10.1007/s12145-022-00869-6
84. Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals S. Tian et al. 10.1002/2016WR019641
85. Determining water storage depletion within Iran by assimilating GRACE data into the W3RA hydrological model M. Khaki et al. 10.1016/j.advwatres.2018.02.008
86. Characterization of precipitation product errors across the United States using multiplicative triple collocation S. Alemohammad et al. 10.5194/hess-19-3489-2015
87. PyGLDA: a fine-scale python-based global land data assimilation system for integrating satellite gravity data into hydrological models F. Yang et al. 10.5194/gmd-18-6195-2025
88. An ensemble Kalman filter with rescaling disaggregation for assimilating terrestrial water storage into hydrological models L. Retegui-Schiettekatte et al. 10.1038/s41598-025-13602-2
89. River gauging at global scale using optical and passive microwave remote sensing A. Van Dijk et al. 10.1002/2015WR018545
90. Hydrological change from space geodetic data and correlation with climate indices in Sudan W. Godah et al. 10.1016/j.jafrearsci.2025.105608
91. Linear Optimal Runoff Aggregate (LORA): a global gridded synthesis runoff product S. Hobeichi et al. 10.5194/hess-23-851-2019
92. Direct Comparison and Triple Collocation: Which Is More Reliable in the Validation of Coarse‐Scale Satellite Surface Albedo Products X. Wu et al. 10.1029/2018JD029937
93. Improving the Accuracy of Groundwater Storage Estimates Based on Groundwater Weighted Fusion Model K. Su et al. 10.3390/rs14010202
94. Space-based natural and human-induced water storage change quantification M. Schumacher et al. 10.1038/s41598-025-01938-8
95. Benchmarking multimodel terrestrial water storage seasonal cycle against Gravity Recovery and Climate Experiment (GRACE) observations over major global river basins S. Bibi et al. 10.5194/hess-28-1725-2024
96. Understanding the global hydrological droughts of 2003–2016 and their relationships with teleconnections E. Forootan et al. 10.1016/j.scitotenv.2018.09.231
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98. Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed D. Casson et al. 10.5194/hess-22-4685-2018
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102. Optimizing Parameters in the Common Land Model by Using Gravity Recovery and Climate Experiment Satellite Observations Y. Su & S. Zhang 10.3390/land13040508
103. The potential and uncertainty of triple collocation in assessing satellite precipitation products in Central Asia X. Lu et al. 10.1016/j.atmosres.2021.105452
104. Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model E. Forootan et al. 10.1016/j.scitotenv.2023.169476
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113. The application of multi-mission satellite data assimilation for studying water storage changes over South America M. Khaki & J. Awange 10.1016/j.scitotenv.2018.08.079
114. Variations in the lake area, water level, and water volume of Hongjiannao Lake during 1986–2018 based on Landsat and ASTER GDEM data H. Yue & Y. Liu 10.1007/s10661-019-7715-6
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118. Calibrating land hydrological models and enhancing their forecasting skills using an ensemble Kalman filter with one-step-ahead smoothing M. Khaki et al. 10.1016/j.jhydrol.2020.124708
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122. Developing explainable AI models for predicting snowpack variability in Polar regions S. Sidra & S. Wagan 10.5817/CPR2025-1-8
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