184 citations as recorded by crossref.

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14. Multi-model analysis of historical runoff changes in the Lancang-Mekong River Basin – Characteristics and uncertainties Y. Li et al. https://doi.org/10.1016/j.jhydrol.2023.129297
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24. Assessment of global reanalysis precipitation for hydrological modelling in data-scarce regions: A case study of Kenya M. Wanzala et al. https://doi.org/10.1016/j.ejrh.2022.101105
25. Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS H. Beck et al. https://doi.org/10.5194/hess-23-207-2019
26. Spatially Referenced Global River Flow Data for Aquatic Safety Assessment Exposure Models Developed from Publicly Available Global Data Sets R. Vamshi et al. https://doi.org/10.1021/acsestwater.4c00637
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45. A global analysis of diurnal variability in dust and dust mixture using CATS observations Y. Yu et al. https://doi.org/10.5194/acp-21-1427-2021
46. Ensemble Skill Gains Obtained From the Multi‐Physics Versus Multi‐Model Approaches for Continental‐Scale Hydrological Simulations W. Fei et al. https://doi.org/10.1029/2020WR028846
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48. Process diagnostics of snowmelt runoff in global hydrological and land surface models – Part 1: A systematic evaluation across basins of increasing complexity X. Lei et al. https://doi.org/10.5194/hess-30-5343-2026
49. Hydrological evaluation of satellite and reanalysis-based rainfall estimates over the Upper Tekeze Basin, Ethiopia K. Reda et al. https://doi.org/10.2166/nh.2022.131
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55. Associated impact mechanism of heavy rain and floods in the middle and lower reaches of the Yangtze river basin based on ocean-atmosphere anomaly patterns S. Wang et al. https://doi.org/10.1016/j.scitotenv.2024.174067
56. Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America M. Troin et al. https://doi.org/10.3390/w13213112
57. Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation S. Camici et al. https://doi.org/10.5194/gmd-15-6935-2022
58. Spatial and temporal drought patterns in Ethiopia: integrating ground and remote sensing data for comprehensive assessment M. GebreMariam et al. https://doi.org/10.2166/nh.2025.032
59. A dynamic-gated Mixture-of-Experts framework improves and interprets daily streamflow simulation W. Yuan et al. https://doi.org/10.1038/s43247-026-03799-z
60. Evaluation of Precipitation Products by Using Multiple Hydrological Models over the Upper Yellow River Basin, China X. Guan et al. https://doi.org/10.3390/rs12244023
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65. HESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologists R. Rigon et al. https://doi.org/10.5194/hess-26-4773-2022
66. Long‐Term Experimental Evaluation of a High‐Resolution Atmospheric General Circulation Model From a Hydrological Perspective Y. Miura & T. Nakaegawa https://doi.org/10.1029/2023JD038786
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72. Combined Use of Local and Global Hydro Meteorological Data with Hydrological Models for Water Resources Management in the Magdalena - Cauca Macro Basin – Colombia E. Rodríguez et al. https://doi.org/10.1007/s11269-019-02236-5
73. The effect of climate type on timescales of drought propagation in an ensemble of global hydrological models A. Gevaert et al. https://doi.org/10.5194/hess-22-4649-2018
74. Postprocessing continental-scale, medium-range ensemble streamflow forecasts in South America using Ensemble Model Output Statistics and Ensemble Copula Coupling V. Siqueira et al. https://doi.org/10.1016/j.jhydrol.2021.126520
75. Unveiling the impact of potential evapotranspiration method selection on trends in hydrological cycle components across Europe V. Thakur et al. https://doi.org/10.5194/hess-29-4395-2025
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79. Bias Correction of Global High-Resolution Precipitation Climatologies Using Streamflow Observations from 9372 Catchments H. Beck et al. https://doi.org/10.1175/JCLI-D-19-0332.1
80. Reconstruction of droughts in India using multiple land-surface models (1951–2015) V. Mishra et al. https://doi.org/10.5194/hess-22-2269-2018
81. Climate change dominates recent increase in streamflow in the Yellow River Basin Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2025.133737
82. Comparison of Extreme Rainfall Characteristics Between CHIRPS and Observational Data in North Sumatra in Relation to IOD and ENSO Events M. Nur et al. https://doi.org/10.1088/1755-1315/1551/1/012044
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