104 citations as recorded by crossref.

1. Rationale and Efficacy of Assimilating Remotely Sensed Potential Evapotranspiration for Reduced Uncertainty of Hydrologic Models A. Rajib et al. https://doi.org/10.1029/2017WR021147
2. Conditioning a Hydrologic Model Using Patterns of Remotely Sensed Land Surface Temperature M. Zink et al. https://doi.org/10.1002/2017WR021346
3. Remotely sensed ET for streamflow modelling in catchments with contrasting flow characteristics: an attempt to improve efficiency A. Kunnath-Poovakka et al. https://doi.org/10.1007/s00477-018-1528-y
4. 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
5. Regional-scale InSAR investigation and landslide early warning thresholds in Umbria, Italy F. Ponziani et al. https://doi.org/10.1016/j.enggeo.2023.107352
6. Using nowcasting technique and data assimilation in a meteorological model to improve very short range hydrological forecasts M. Poletti et al. https://doi.org/10.5194/hess-23-3823-2019
7. Synergistic Calibration of a Hydrological Model Using Discharge and Remotely Sensed Soil Moisture in the Paraná River Basin A. Fleischmann et al. https://doi.org/10.3390/rs13163256
8. A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks J. Liu et al. https://doi.org/10.5194/hess-28-2871-2024
9. The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review D. Jiang & K. Wang https://doi.org/10.3390/w11081615
10. A Hybrid Approach Combining Conceptual Hydrological Models, Support Vector Machines and Remote Sensing Data for Rainfall-Runoff Modeling M. Kwon et al. https://doi.org/10.3390/rs12111801
11. Water Balance in Alpine Catchments by Sentinel Data R. Perico et al. https://doi.org/10.1029/2021WR031355
12. Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review Y. Guo et al. https://doi.org/10.1002/wat2.1487
13. Divergent sensitivity of surface water and energy variables to precipitation product uncertainty in the Tibetan Plateau W. Qi et al. https://doi.org/10.1016/j.jhydrol.2019.124338
14. Modeling Hydrological Response to Climate Change in a Data-Scarce Glacierized High Mountain Astore Basin Using a Fully Distributed TOPKAPI Model I. Atif et al. https://doi.org/10.3390/cli7110127
15. Flow Prediction Using Remotely Sensed Soil Moisture in Irish Catchments C. Yang & F. O’Loughlin https://doi.org/10.3390/w12082202
16. Improving process-consistency of an ecohydrological model through inclusion of spatial patterns of satellite-derived land surface temperature D. Duethmann et al. https://doi.org/10.1016/j.jhydrol.2023.130433
17. Improved Understanding of the Link Between Catchment‐Scale Vegetation Accessible Storage and Satellite‐Derived Soil Water Index L. Bouaziz et al. https://doi.org/10.1029/2019WR026365
18. Identification and parameter estimation algorithm of radar signal subtle features D. Li et al. https://doi.org/10.1016/j.phycom.2020.101140
19. Information content of spatially distributed ground-based measurements for hydrologic-parameter calibration in mixed rain-snow mountain headwaters F. Avanzi et al. https://doi.org/10.1016/j.jhydrol.2019.124478
20. On the distribution and productivity of mountain grasslands in the Gran Paradiso National Park, NW Italy: A remote sensing approach G. Filippa et al. https://doi.org/10.1016/j.jag.2022.102718
21. Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis E. Moges et al. https://doi.org/10.3390/w13010028
22. The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites R. Tong et al. https://doi.org/10.5194/hess-26-1779-2022
23. Impact of Rainfall Assimilation on High-Resolution Hydrometeorological Forecasts over Liguria, Italy S. Davolio et al. https://doi.org/10.1175/JHM-D-17-0073.1
24. Multivariate calibration of the agricultural policy/environmental eXtender model for field scale simulation of hydrologic and agronomic outcomes Q. Pallardy et al. https://doi.org/10.1016/j.scitotenv.2026.181480
25. Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review Y. Li et al. https://doi.org/10.3390/rs8060456
26. On the importance of soil moisture in calibration of rainfall–runoff models: two case studies M. Shahrban et al. https://doi.org/10.1080/02626667.2018.1487560
27. The Curve Number Concept as a Driver for Delineating Hydrological Response Units E. Savvidou et al. https://doi.org/10.3390/w10020194
28. Hydrologic model predictability improves with spatially explicit calibration using remotely sensed evapotranspiration and biophysical parameters A. Rajib et al. https://doi.org/10.1016/j.jhydrol.2018.10.024
29. Climatic Drivers of Greening Trends in the Alps G. Filippa et al. https://doi.org/10.3390/rs11212527
30. Performing Hydrological Monitoring at a National Scale by Exploiting Rain-Gauge and Radar Networks: The Italian Case G. Bruno et al. https://doi.org/10.3390/atmos12060771
31. A regional early warning system for debris flows M. Ponziani et al. https://doi.org/10.1051/e3sconf/202341507012
32. Evaluating satellite-derived soil moisture data for improving the internal consistency of process-based ecohydrological modelling D. Duethmann et al. https://doi.org/10.1016/j.jhydrol.2022.128462
33. A parallel computing-based and spatially stepwise strategy for constraining a semi-distributed hydrological model with streamflow observations and satellite-based evapotranspiration L. Zhang et al. https://doi.org/10.1016/j.jhydrol.2021.126359
34. Coastal Risk Assessment Framework: Comparison of modelled fluvial and marine inundation impacts, Bocca di Magra, Ligurian coast, Italy S. De Angeli et al. https://doi.org/10.1016/j.coastaleng.2017.09.011
35. Analysis of the streamflow extremes and long-term water balance in the Liguria region of Italy using a cloud-permitting grid spacing reanalysis dataset F. Silvestro et al. https://doi.org/10.5194/hess-22-5403-2018
36. Stepwise prediction of runoff using proxy data in a small agricultural catchment B. Széles et al. https://doi.org/10.2478/johh-2020-0029
37. Impact-based flash-flood forecasting system: Sensitivity to high resolution numerical weather prediction systems and soil moisture F. Silvestro et al. https://doi.org/10.1016/j.jhydrol.2019.02.055
38. Parameter Optimization for Uncertainty Reduction and Simulation Improvement of Hydrological Modeling J. Hui et al. https://doi.org/10.3390/rs12244069
39. Hydrological model skills change with drought severity; insights from multi-variable evaluation G. Bruno et al. https://doi.org/10.1016/j.jhydrol.2024.131023
40. Improving the hydrological consistency of a process-based solute-transport model by simultaneous calibration of streamflow and stream concentrations J. Salmon-Monviola et al. https://doi.org/10.5194/hess-29-127-2025
41. Cosmic‐ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads M. Schrön et al. https://doi.org/10.1029/2017WR021719
42. The Added Value of Different Data Types for Calibrating and Testing a Hydrologic Model in a Small Catchment B. Széles et al. https://doi.org/10.1029/2019WR026153
43. Utilizing Satellite Surface Soil Moisture Data in Calibrating a Distributed Hydrological Model Applied in Humid Regions Through a Multi-Objective Bayesian Hierarchical Framework H. Yang et al. https://doi.org/10.3390/rs11111335
44. Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding C. Kelleher et al. https://doi.org/10.5194/hess-21-3325-2017
45. Evaluation of Sentinel-1, SMAP and SMOS surface soil moisture products for distributed eco-hydrological modelling in Mediterranean forest basins J. Gomis-Cebolla et al. https://doi.org/10.1016/j.jhydrol.2022.127569
46. Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface H. McMillan et al. https://doi.org/10.1002/hyp.14481
47. Stepwise calibration of a lumped hydrological model for Xun River basin, China, considering the heterogeneity of soil moisture B. Yi et al. https://doi.org/10.1016/j.ejrh.2025.102293
48. Enhancing simulation accuracy of a semi-distributed conceptual hydrological model using satellite soil moisture products H. Cai et al. https://doi.org/10.1016/j.jhydrol.2026.135751
49. Soil Moisture for Hydrological Applications: Open Questions and New Opportunities L. Brocca et al. https://doi.org/10.3390/w9020140
50. Broaden your horizon: The use of remotely sensed data for modeling populations of forest species at landscape scales P. Jensen et al. https://doi.org/10.1016/j.foreco.2021.119640
51. Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales G. Baroni et al. https://doi.org/10.5194/hess-21-2301-2017
52. Improving a distributed hydrological model using evapotranspiration‐related boundary conditions as additional constraints in a data‐scarce river basin F. Wambura et al. https://doi.org/10.1002/hyp.11453
53. Ecohydrologic model with satellite-based data for predicting streamflow in ungauged basins J. Choi et al. https://doi.org/10.1016/j.scitotenv.2023.166617
54. Hydrological modeling of the Silala River basin. 2. Validation of hydrological fluxes with contemporary data G. Yáñez‐Morroni et al. https://doi.org/10.1002/wat2.1696
55. Evaluating Consistency between the Remotely Sensed Soil Moisture and the Hydrological Model-Simulated Soil Moisture in the Qujiang Catchment of China L. Xiong et al. https://doi.org/10.3390/w10030291
56. SDANet: A Federated Efficient Remote Sensing Object Detection for Space-Air–Ground IoT Z. Wang et al. https://doi.org/10.1109/JIOT.2025.3579027
57. Nitrate Pathways, Processes, and Timing in an Agricultural Karst System: Development and Application of a Numerical Model A. Husic et al. https://doi.org/10.1029/2018WR023703
58. Testing Soil Moisture Performance Measures in the Conceptual‐Functional Equivalent to the WRF‐Hydro National Water Model R. Araki et al. https://doi.org/10.1111/1752-1688.70002
59. Intercomparison of Earth Observation products for hyper-resolution hydrological modelling over Europe A. García-García et al. https://doi.org/10.1016/j.rse.2025.115131
60. The use of machine learning techniques for a predictive model of debris flows triggered by short intense rainfall M. Ponziani et al. https://doi.org/10.1007/s11069-023-05853-x
61. Severe floods predictive ability: A proxy based probabilistic assessment of the Italian early warning system F. Silvestro et al. https://doi.org/10.1111/jfr3.12970
62. Comprehensive Analysis for Long-Term Hydrological Simulation by Deep Learning Techniques and Remote Sensing C. Xu et al. https://doi.org/10.3389/feart.2022.875145
63. Quantifying Flood Frequency Modification Caused by Multi-Reservoir Regulation Y. Tang et al. https://doi.org/10.1007/s11269-019-02374-w
64. Comparison of two early warning systems for regional flash flood hazard forecasting C. Corral et al. https://doi.org/10.1016/j.jhydrol.2019.03.026
65. The flash flood of the Bisagno Creek on 9th October 2014: An “unfortunate” combination of spatial and temporal scales F. Silvestro et al. https://doi.org/10.1016/j.jhydrol.2015.08.004
66. Propagating aleatory and epistemic uncertainty in land cover change prediction process A. Ferchichi et al. https://doi.org/10.1016/j.ecoinf.2016.11.006
67. Assessment of Suitable Gridded Climate Datasets for Large-Scale Hydrological Modelling over South Korea D. Lee & K. Ahn https://doi.org/10.3390/rs14153535
68. NRCS-CN Estimation from Onsite and Remote Sensing Data for Management of a Reservoir in the Eastern Pyrenees M. Sanz-Ramos et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001979
69. Improving real-time operational streamflow simulations using discharge data to update state variables of a distributed hydrological model F. Silvestro et al. https://doi.org/10.2166/nh.2021.162
70. What if the 25 October 2011 event that struck Cinque Terre (Liguria) had happened in Genoa, Italy? Flooding scenarios, hazard mapping and damage estimation F. Silvestro et al. https://doi.org/10.5194/nhess-16-1737-2016
71. Usefulness of Global Root Zone Soil Moisture Product for Streamflow Prediction of Ungauged Basins J. Choi et al. https://doi.org/10.3390/rs13040756
72. Remote Sensing of River Discharge: A Review and a Framing for the Discipline C. Gleason & M. Durand https://doi.org/10.3390/rs12071107
73. A Prior Estimation of the Spatial Distribution Parameter of Soil Moisture Storage Capacity Using Satellite-Based Root-Zone Soil Moisture Data Y. Tian et al. https://doi.org/10.3390/rs11212580
74. Satellite Imagery-Based SERVES Soil Moisture for the Analysis of Soil Moisture Initialization Input Scale Effects on Physics-Based Distributed Watershed Hydrologic Modelling N. Pradhan et al. https://doi.org/10.3390/rs12132108
75. Evaluating hydrological model performance using varying amounts of participatory monitoring water level data F. Mitze et al. https://doi.org/10.1371/journal.pwat.0000405
76. 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
77. Pasture areas in the Gran Paradiso National Park L. Stendardi et al. https://doi.org/10.1080/17445647.2022.2120835
78. Assessment of Nitrate Hazards in Umbria Region (Italy) Using Field Datasets: Good Agriculture Practices and Farms Sustainability O. Paladino et al. https://doi.org/10.3390/su12229497
79. 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
80. 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
81. REFLEX—A novel method for the rapid estimation of flood extent M. Arcorace et al. https://doi.org/10.1111/jfr3.13034
82. Evaluating data-driven and hybrid modeling of terrestrial actual evapotranspiration based on an automatic machine learning approach N. Guo et al. https://doi.org/10.1016/j.jhydrol.2023.130594
83. Runoff Prediction and Analysis Based on Improved CEEMDAN-OS-QR-ELM Y. Liu et al. https://doi.org/10.1109/ACCESS.2021.3072673
84. Research on Runoff Prediction Based on Time2Vec-TCN-Transformer Driven by Multi-Source Data Y. Liu et al. https://doi.org/10.3390/electronics13142681
85. Predictive Capability of a High-Resolution Hydrometeorological Forecasting Framework Coupling WRF Cycling 3DVAR and Continuum M. Lagasio et al. https://doi.org/10.1175/JHM-D-18-0219.1
86. The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction A. Kunnath-Poovakka et al. https://doi.org/10.1016/j.jhydrol.2016.02.018
87. Advancing hydrological modeling through multivariate calibration of multi-layer soil moisture dynamics Y. He et al. https://doi.org/10.1016/j.ejrh.2024.102125
88. Assimilation of H-SAF Soil Moisture Products for Flash Flood Early Warning Systems. Case Study: Mediterranean Catchments L. Cenci et al. https://doi.org/10.1109/JSTARS.2016.2598475
89. Constraining Remote River Discharge Estimation Using Reach‐Scale Geomorphology C. Brinkerhoff et al. https://doi.org/10.1029/2020WR027949
90. Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets M. Dembélé et al. https://doi.org/10.1029/2019WR026085
91. How much cryosphere model complexity is just right? Exploration using the conceptual cryosphere hydrology framework T. Mosier et al. https://doi.org/10.5194/tc-10-2147-2016
92. Modelling rainfall-induced landslides at a regional scale, a machine learning based approach S. Magrì et al. https://doi.org/10.1007/s10346-023-02173-w
93. Physically based distributed hydrological model calibration based on a short period of streamflow data: case studies in four Chinese basins W. Sun et al. https://doi.org/10.5194/hess-21-251-2017
94. Multi-criteria evaluation for parameter uncertainty assessment and ensemble runoff forecasting in a snow-dominated basin Y. Oğulcan Doğan et al. https://doi.org/10.2478/johh-2023-0003
95. Evaluating IMERG-F precipitation for SWAT hydrologic modeling in data-rich and sparse watersheds F. Jarrin-Perez et al. https://doi.org/10.1016/j.envsoft.2025.106574
96. Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring L. Cenci et al. https://doi.org/10.3390/rs10121950
97. Parameter Uncertainty of a Hydrologic Model Calibrated with Remotely Sensed Evapotranspiration and Soil Moisture A. Kunnath-Poovakka et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002055
98. Impacts of Introducing Remote Sensing Soil Moisture in Calibrating a Distributed Hydrological Model for Streamflow Simulation L. Xiong & L. Zeng https://doi.org/10.3390/w11040666
99. Enhancing Groundwater Recharge Through Nature-Based Solutions: Benefits and Barriers M. Kebede et al. https://doi.org/10.3390/hydrology11110195
100. On the contribution of remote sensing-based calibration to model hydrological and hydraulic processes in tropical regions A. Meyer Oliveira et al. https://doi.org/10.1016/j.jhydrol.2021.126184
101. A combined index to characterize agricultural drought in Italy at municipality scale L. Rossi et al. https://doi.org/10.1016/j.ejrh.2023.101404
102. Debris-flow Indicator for an early warning system in the Aosta valley region M. Ponziani et al. https://doi.org/10.1007/s11069-020-04249-5
103. Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica S. Arciniega-Esparza et al. https://doi.org/10.5194/hess-26-975-2022
104. A Complete Meteo/Hydro/Hydraulic Chain Application to Support Early Warning and Monitoring Systems: The Apollo Medicane Use Case M. Lagasio et al. https://doi.org/10.3390/rs14246348