33 citations as recorded by crossref.

1. Multi-mission satellite remote sensing data for improving land hydrological models via data assimilation M. Khaki et al. https://doi.org/10.1038/s41598-020-75710-5
2. Terrestrial water storage changes over Xinjiang extracted by combining Gaussian filter and multichannel singular spectrum analysis from GRACE J. Guo et al. https://doi.org/10.1093/gji/ggy006
3. Multi-scale modeling of Earth's gravity field in space and time S. Wang et al. https://doi.org/10.1016/j.jog.2017.02.001
4. The spatio-temporal variability of groundwater storage in the Amazon River Basin F. Frappart et al. https://doi.org/10.1016/j.advwatres.2018.12.005
5. Analysis of the spatio-temporal variability of terrestrial water storage in the Great Artesian Basin, Australia J. Yan et al. https://doi.org/10.2166/ws.2016.136
6. Estimation of GRACE water storage components by temporal decomposition R. Andrew et al. https://doi.org/10.1016/j.jhydrol.2017.06.016
7. Response of terrestrial water storage and its change to climate change in the endorheic Tibetan Plateau L. Wang et al. https://doi.org/10.1016/j.jhydrol.2022.128231
8. Quantification of groundwater resource of Kandi subdivision of Murshidabad district, West Bengal M. Chowdhury & P. Paul https://doi.org/10.1007/s10668-019-00454-w
9. Estimation of quantitative measures of total water storage variation from GRACE and GLDAS-NOAH satellites using geospatial technology A. Singh et al. https://doi.org/10.1016/j.quaint.2017.04.014
10. Investigation of Short-Term Evolution of Soil Characteristics over the Lake Chad Basin Using GRACE Data T. Lopez et al. https://doi.org/10.3390/rs10060924
11. Satellite-derived GRACE groundwater storage variation in complex aquifer system in India L. Singh & S. Saravanan https://doi.org/10.1007/s40899-020-00399-3
12. Application of the Regional Water Mass Variations from GRACE Satellite Gravimetry to Large-Scale Water Management in Africa G. Ramillien et al. https://doi.org/10.3390/rs6087379
13. Efficient basin scale filtering of GRACE satellite products M. Khaki et al. https://doi.org/10.1016/j.rse.2017.10.040
14. Calibrating land hydrological models and enhancing their forecasting skills using an ensemble Kalman filter with one-step-ahead smoothing M. Khaki et al. https://doi.org/10.1016/j.jhydrol.2020.124708
15. Temporal/Spatial Variation of Terrestrial Water Storage and Groundwater Storage in Typical Inland River Basins of Central Asia Y. Lyu et al. https://doi.org/10.3390/w13233385
16. Basin-scale terrestrial water storage changes inferred from GRACE-based geopotential differences: a case study of the Yangtze River Basin, China B. Zhong et al. https://doi.org/10.1093/gji/ggac524
17. Assimilation of GRACE Follow‐On Inter‐Satellite Laser Ranging Measurements Into Land Surface Models M. Khaki et al. https://doi.org/10.1029/2022WR032432
18. Monitoring Groundwater Storage Changes Using the Gravity Recovery and Climate Experiment (GRACE) Satellite Mission: A Review F. Frappart & G. Ramillien https://doi.org/10.3390/rs10060829
19. Accounting for spatial correlation errors in the assimilation of GRACE into hydrological models through localization M. Khaki et al. https://doi.org/10.1016/j.advwatres.2017.07.024
20. Improved multichannel singular spectrum analysis for post-processing GRACE monthly gravity field models F. Wang et al. https://doi.org/10.1093/gji/ggaa339
21. Understanding the global hydrological droughts of 2003–2016 and their relationships with teleconnections E. Forootan et al. https://doi.org/10.1016/j.scitotenv.2018.09.231
22. A two-update ensemble Kalman filter for land hydrological data assimilation with an uncertain constraint M. Khaki et al. https://doi.org/10.1016/j.jhydrol.2017.10.032
23. Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors Q. Huang et al. https://doi.org/10.3390/su11236646
24. Nonparametric Data Assimilation Scheme for Land Hydrological Applications M. Khaki et al. https://doi.org/10.1029/2018WR022854
25. Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model M. Khaki et al. https://doi.org/10.1016/j.advwatres.2017.07.001
26. Data-adaptive spatio-temporal filtering of GRACE data P. Prevost et al. https://doi.org/10.1093/gji/ggz409
27. Changing characteristics of ecosystem and water storage under the background of warming and humidification in the Qilian Mountains, China B. Bai et al. https://doi.org/10.1016/j.scitotenv.2023.164959
28. Use of remote sensing and long-term in-situ time-series data in an integrated hydrological model of the Central Kalahari Basin, Southern Africa M. Lekula & M. Lubczynski https://doi.org/10.1007/s10040-019-01954-9
29. Quantifying the impacts of ENSO and IOD on rain gauge and remotely sensed precipitation products over Australia E. Forootan et al. https://doi.org/10.1016/j.rse.2015.10.027
30. Mapping probabilities of extreme continental water storage changes from space gravimetry J. Kusche et al. https://doi.org/10.1002/2016GL069538
31. Unsupervised ensemble Kalman filtering with an uncertain constraint for land hydrological data assimilation M. Khaki et al. https://doi.org/10.1016/j.jhydrol.2018.06.080
32. Sequential estimation of surface water mass changes from daily satellite gravimetry data G. Ramillien et al. https://doi.org/10.1007/s00190-014-0772-2
33. Assessing data assimilation frameworks for using multi-mission satellite products in a hydrological context M. Khaki et al. https://doi.org/10.1016/j.scitotenv.2018.08.032