94 citations as recorded by crossref.

1. Impact of leaf area index assimilation and gauge-corrected precipitation on land surface variables in LDAS-Monde: a case study over China E. Liu et al. https://doi.org/10.1016/j.jhydrol.2025.133304
2. Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations P. López López et al. https://doi.org/10.5194/hess-20-3059-2016
3. Parameter identification in hydrological models using groundwater-level measurements and satellite-based soil moisture P. Kreye et al. https://doi.org/10.1080/02626667.2019.1599120
4. Soil Moisture Monitoring at Kilometer Scale: Assimilation of Sentinel-1 Products in ISBA O. Rojas-Munoz et al. https://doi.org/10.3390/rs15174329
5. Incorporating Advanced Scatterometer Surface and Root Zone Soil Moisture Products into the Calibration of a Conceptual Semi-Distributed Hydrological Model M. Kubáň et al. https://doi.org/10.3390/w13233366
6. Assimilation of Satellite Soil Moisture Products for River Flow Prediction: An Extensive Experiment in Over 700 Catchments Throughout Europe D. De Santis et al. https://doi.org/10.1029/2021WR029643
7. Assimilation of surface soil moisture into a multilayer soil model: design and evaluation at local scale M. Parrens et al. https://doi.org/10.5194/hess-18-673-2014
8. Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals S. Tian et al. https://doi.org/10.1002/2016WR019641
9. Exploiting the synergy between SMAP and SMOS to improve brightness temperature simulations and soil moisture retrievals in arid regions M. Ebrahimi et al. https://doi.org/10.1016/j.jhydrol.2017.12.051
10. Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC M. Ebrahimi-Khusfi et al. https://doi.org/10.1016/j.jag.2017.12.005
11. The Impact of Spatial Dynamic Error on the Assimilation of Soil Moisture Retrieval Products X. Bai et al. https://doi.org/10.3390/rs17020239
12. Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation B. Naz et al. https://doi.org/10.5194/hess-23-277-2019
13. Soil moisture deficit estimation using satellite multi-angle brightness temperature L. Zhuo et al. https://doi.org/10.1016/j.jhydrol.2016.05.052
14. Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review Y. Li et al. https://doi.org/10.3390/rs8060456
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21. Toward a Surface Soil Moisture Product at High Spatiotemporal Resolution: Temporally Interpolated, Spatially Disaggregated SMOS Data Y. Malbéteau et al. https://doi.org/10.1175/JHM-D-16-0280.1
22. On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation J. Loizu et al. https://doi.org/10.1016/j.advwatres.2017.10.034
23. Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model E. Gelati et al. https://doi.org/10.5194/hess-22-2091-2018
24. SMOS brightness temperature assimilation into the Community Land Model D. Rains et al. https://doi.org/10.5194/hess-21-5929-2017
25. Remotely Sensed Soil Moisture Assimilation in the Distributed Hydrological Model Based on the Error Subspace Transform Kalman Filter Y. Li et al. https://doi.org/10.3390/rs15071852
26. The value of remotely sensed surface soil moisture for model calibration using SWAT D. Kundu et al. https://doi.org/10.1002/hyp.11219
27. Assimilation of Cosmic‐Ray Neutron Counts for the Estimation of Soil Ice Content on the Eastern Tibetan Plateau S. Mwangi et al. https://doi.org/10.1029/2019JD031529
28. A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data P. Leng et al. https://doi.org/10.1016/j.jag.2016.07.004
29. Continental satellite soil moisture data assimilation improves root-zone moisture analysis for water resources assessment L. Renzullo et al. https://doi.org/10.1016/j.jhydrol.2014.08.008
30. Improvement of the Trapezoid Method Using Raw Landsat Image Digital Count Data for Soil Moisture Estimation in the Texas (USA) High Plains S. Shafian & S. Maas https://doi.org/10.3390/s150101925
31. Review of the Kalman-type hydrological data assimilation L. Sun et al. https://doi.org/10.1080/02626667.2015.1127376
32. Simultaneous assimilation of in situ soil moisture and streamflow in the SWAT model using the Extended Kalman Filter L. Sun et al. https://doi.org/10.1016/j.jhydrol.2016.10.040
33. Assimilation of Leaf Area Index and Soil Water Index from Satellite Observations in a Land Surface Model in Hungary H. Tóth & B. Szintai https://doi.org/10.3390/atmos12080944
34. A simplified Extended Kalman Filter for the global operational soil moisture analysis at ECMWF P. de Rosnay et al. https://doi.org/10.1002/qj.2023
35. Assimilating ASCAT normalized backscatter and slope into the land surface model ISBA-A-gs using a Deep Neural Network as the observation operator: Case studies at ISMN stations in western Europe X. Shan et al. https://doi.org/10.1016/j.rse.2024.114167
36. Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation C. Albergel et al. https://doi.org/10.3390/rs11050520
37. A Review of Satellite-Derived Soil Moisture and Its Usage for Flood Estimation S. Kim et al. https://doi.org/10.1007/s41976-019-00025-7
38. Soil moisture mapping in a semiarid region, based on ASAR/Wide Swath satellite data M. Zribi et al. https://doi.org/10.1002/2012WR013405
39. Reducing multiplicative bias of satellite soil moisture retrievals K. Kornelsen & P. Coulibaly https://doi.org/10.1016/j.rse.2015.04.031
40. Deriving pedotransfer functions for soil quartz fraction in southern France from reverse modeling J. Calvet et al. https://doi.org/10.5194/soil-2-615-2016
41. The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes V. Masson et al. https://doi.org/10.5194/gmd-6-929-2013
42. Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications K. Kornelsen & P. Coulibaly https://doi.org/10.1016/j.jhydrol.2012.10.044
43. LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the Contiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables C. Albergel et al. https://doi.org/10.3390/rs10101627
44. Data assimilation for continuous global assessment of severe conditions over terrestrial surfaces C. Albergel et al. https://doi.org/10.5194/hess-24-4291-2020
45. Inter-comparison of energy balance and hydrological models for land surface energy flux estimation over a whole river catchment R. Guzinski et al. https://doi.org/10.5194/hess-19-2017-2015
46. A quality assessment of the soil water index by the propagation of ASCAT soil moisture error estimates through an exponential filter D. De Santis & D. Biondi https://doi.org/10.1080/01431161.2017.1382745
47. Absolute versus temporal anomaly and percent of saturation soil moisture spatial variability for six networks worldwide L. Brocca et al. https://doi.org/10.1002/2014WR015684
48. Comparison of SWAT and MODIS Evapotranspiration Data for Multiple Timescales P. Parajuli et al. https://doi.org/10.3390/hydrology9060103
49. The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France D. Fairbairn et al. https://doi.org/10.5194/hess-21-2015-2017
50. ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better? C. Albergel et al. https://doi.org/10.5194/hess-22-3515-2018
51. Translating aboveground cosmic-ray neutron intensity to high-frequency soil moisture profiles at sub-kilometer scale R. Rosolem et al. https://doi.org/10.5194/hess-18-4363-2014
52. A Generic First-Order Radiative Transfer Modelling Approach for the Inversion of Soil and Vegetation Parameters from Scatterometer Observations R. Quast et al. https://doi.org/10.3390/rs11030285
53. Spatial Evaluation and Assimilation of SMAP, SMOS, and ASCAT Satellite Soil Moisture Products Over Africa Using Statistical Techniques B. Mousa & H. Shu https://doi.org/10.1029/2019EA000841
54. Hydrologic model calibration using remotely sensed soil moisture and discharge measurements: The impact on predictions at gauged and ungauged locations Y. Li et al. https://doi.org/10.1016/j.jhydrol.2018.01.013
55. Joint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimation A. Gevaert et al. https://doi.org/10.5194/hess-22-4605-2018
56. Comparative Analysis of Landsat-8, Sentinel-2, and GF-1 Data for Retrieving Soil Moisture over Wheat Farmlands Q. Wang et al. https://doi.org/10.3390/rs12172708
57. SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia H. Lievens et al. https://doi.org/10.1016/j.rse.2015.06.025
58. A Novel Scheme for Merging Active and Passive Satellite Soil Moisture Retrievals Based on Maximizing the Signal to Noise Ratio B. Mousa et al. https://doi.org/10.3390/rs12223804
59. Triple Collocation Analysis of Soil Moisture From Metop-A ASCAT and SMOS Against JRA-55 and ERA-Interim K. Miyaoka et al. https://doi.org/10.1109/JSTARS.2016.2632306
60. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model P. Laiolo et al. https://doi.org/10.1016/j.jag.2015.06.002
61. Evaluating Multi-Source Soil Moisture Products for Root-Zone Soil Moisture Representation in Yunnan, China R. Wang et al. https://doi.org/10.3390/rs18101669
62. Multi-objective calibration of a hydrologic model using spatially distributed remotely sensed/in-situ soil moisture M. Rajib et al. https://doi.org/10.1016/j.jhydrol.2016.02.037
63. Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area C. Albergel et al. https://doi.org/10.5194/gmd-10-3889-2017
64. Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France A. Barbu et al. https://doi.org/10.5194/hess-18-173-2014
65. Quick estimation of parameters for the land surface data assimilation system and its influence based on the extended Kalman filter and automatic differentiation J. Tian et al. https://doi.org/10.1007/s11430-022-1180-8
66. Comparing soil moisture retrievals from SMOS and ASCAT over France M. Parrens et al. https://doi.org/10.5194/hess-16-423-2012
67. Remote sensing data assimilation A. Nair et al. https://doi.org/10.1080/02626667.2020.1761021
68. Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates A. Al-Yaari et al. https://doi.org/10.1016/j.rse.2014.04.006
69. Exploiting Satellite-Based Surface Soil Moisture for Flood Forecasting in the Mediterranean Area: State Update Versus Rainfall Correction C. Massari et al. https://doi.org/10.3390/rs10020292
70. Comparing Assimilation of Synthetic Soil Moisture Versus C‐Band Backscatter for Hyper‐Resolution Land Surface Modeling L. Sun et al. https://doi.org/10.1029/2020WR028921
71. The Assimilation of Remote Sensing-Derived Soil Moisture Data into a Hydrological Model for the Mahanadi Basin, India S. Behera et al. https://doi.org/10.1007/s12524-019-00954-2
72. A 3 km spatially and temporally consistent European daily soil moisture reanalysis from 2000 to 2015 B. Naz et al. https://doi.org/10.1038/s41597-020-0450-6
73. The soil moisture data bank: The ground-based, model-based, and satellite-based soil moisture data A. Tavakol et al. https://doi.org/10.1016/j.rsase.2021.100649
74. Evaluation of satellite soil moisture products over Norway using ground-based observations A. Griesfeller et al. https://doi.org/10.1016/j.jag.2015.04.016
75. Combined Assimilation of Satellite Precipitation and Soil Moisture: A Case Study Using TRMM and SMOS Data L. Lin et al. https://doi.org/10.1175/MWR-D-17-0125.1
76. Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations M. Pablos et al. https://doi.org/10.3390/rs10070981
77. Bare soil hydrological balance model “MHYSAN”: Calibration and validation using SAR moisture products and continuous thetaprobe network measurements over bare agricultural soils (Tunisia) A. Gorrab et al. https://doi.org/10.1016/j.jaridenv.2016.12.005
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79. Assimilation of Sentinel 1 and SMAP – based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins S. Azimi et al. https://doi.org/10.1016/j.jhydrol.2019.124367
80. Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations S. Wang et al. https://doi.org/10.3390/rs70505734
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82. The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation J. Shuttleworth et al. https://doi.org/10.5194/hess-17-3205-2013
83. Assimilation of Soil Moisture and Ocean Salinity (SMOS) brightness temperature into a large-scale distributed conceptual hydrological model to improve soil moisture predictions: the Murray–Darling basin in Australia as a test case R. Hostache et al. https://doi.org/10.5194/hess-24-4793-2020
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85. Assimilation of ASCAT Radar Backscatter Coefficients over Southwestern France T. Corchia et al. https://doi.org/10.3390/rs15174258
86. Towards a Long-Term Reanalysis of Land Surface Variables over Western Africa: LDAS-Monde Applied over Burkina Faso from 2001 to 2018 M. Tall et al. https://doi.org/10.3390/rs11060735
87. Testing conceptual and physically based soil hydrology schemes against observations for the Amazon Basin M. Guimberteau et al. https://doi.org/10.5194/gmd-7-1115-2014
88. Assessing Hydrological Modelling Driven by Different Precipitation Datasets via the SMAP Soil Moisture Product and Gauged Streamflow Data L. Yi et al. https://doi.org/10.3390/rs10121872
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