138 citations as recorded by crossref.

1. Future projections of High Atlas snowpack and runoff under climate change A. Tuel et al. https://doi.org/10.5194/hess-26-571-2022
2. Geospatial dataset for hydrologic analyses in India (GHI): a quality-controlled dataset on river gauges, catchment boundaries and hydrometeorological time series G. Goteti https://doi.org/10.5194/essd-15-4389-2023
3. Global prevalence of non-perennial rivers and streams M. Messager et al. https://doi.org/10.1038/s41586-021-03565-5
4. Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti R. Bathelemy et al. https://doi.org/10.5194/essd-16-2073-2024
5. Functional relationships reveal differences in the water cycle representation of global water models S. Gnann et al. https://doi.org/10.1038/s44221-023-00160-y
6. A Global Assessment of Climate Change and Anthropogenic Effects on Changes in Streamflow R. Yang et al. https://doi.org/10.1007/s11269-025-04448-4
7. Technical note: Evaluation and bias correction of an observation-based global runoff dataset using streamflow observations from small tropical catchments in the Philippines D. Ibarra et al. https://doi.org/10.5194/hess-25-2805-2021
8. Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1 D. Xu et al. https://doi.org/10.5194/gmd-15-5021-2022
9. River effects on sea-level rise in the Río de la Plata estuary during the past century C. Piecuch https://doi.org/10.5194/os-19-57-2023
10. Climate drives observational changes in hydrological extremes across most global regions N. Wang et al. https://doi.org/10.1016/j.xinn.2025.101171
11. ADHI: the African Database of Hydrometric Indices (1950–2018) Y. Tramblay et al. https://doi.org/10.5194/essd-13-1547-2021
12. Key environmental factors determining life history strategies of river fishes and their historical changes in the Yangtze River L. Zhu et al. https://doi.org/10.1016/j.watbs.2025.100376
13. Estimation of Gridded Monthly Baseflow across Southern and Central India S. Gautam et al. https://doi.org/10.1016/j.pce.2026.104792
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20. Evaluating a reservoir parametrization in the vector-based global routing model mizuRoute (v2.0.1) for Earth system model coupling I. Vanderkelen et al. https://doi.org/10.5194/gmd-15-4163-2022
21. GRACE-REC: a reconstruction of climate-driven water storage changes over the last century V. Humphrey & L. Gudmundsson https://doi.org/10.5194/essd-11-1153-2019
22. Historical and future changes in global flood magnitude – evidence from a model–observation investigation H. Do et al. https://doi.org/10.5194/hess-24-1543-2020
23. Identification of uncertainty sources in quasi-global discharge and inundation simulations using satellite-based precipitation products Z. Wei et al. https://doi.org/10.1016/j.jhydrol.2020.125180
24. Global hydrological models continue to overestimate river discharge S. Heinicke et al. https://doi.org/10.1088/1748-9326/ad52b0
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26. Probabilistic predictions for meteorological droughts based on multi-initial conditions M. Torres-Vázquez et al. https://doi.org/10.1016/j.jhydrol.2024.131662
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29. Cyclones and Global Floods from an Observation-Simulation Evaluation: Contributions and Long-Term Changes L. Wang et al. https://doi.org/10.3390/w13212965
30. Accuracy Evaluation of Multiple Runoff Products: A Case Study of the Middle Reaches of the Yellow River H. Cui & C. Huang https://doi.org/10.3390/w17030461
31. Using century-long reanalysis and a rainfall-runoff model to explore multi-decadal variability in catchment hydrology at the European scale P. Brigode & L. Oudin https://doi.org/10.5194/hess-29-5535-2025
32. Latitudinal divergence in runoff responses to global forestation due to forest-atmosphere feedbacks F. Kan et al. https://doi.org/10.1038/s41467-026-68945-9
33. Four-decades assessment of hydrological drought using streamflow reconstruction in poorly-gauged basins in Vietnam B. Nguyen et al. https://doi.org/10.1016/j.asr.2025.12.030
34. Impact of land surface model schemes in snow-dominated arid and semiarid watersheds using the WRF-hydro modeling systems W. Hussainzada & H. Lee https://doi.org/10.3934/geosci.2024018
35. Shifts in global flood seasonality and their drivers S. Wang et al. https://doi.org/10.1080/02626667.2026.2661882
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37. A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies Z. Yin et al. https://doi.org/10.5194/essd-16-1559-2024
38. Use of streamflow indices to identify the catchment drivers of hydrographs J. Mathai & P. Mujumdar https://doi.org/10.5194/hess-26-2019-2022
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40. Investigating the response of hydrological processes to El Niño events using a 100-year dataset from the western Pacific Ocean N. Sekhon et al. https://doi.org/10.1016/j.ejrh.2022.101174
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44. Baltic hydro-climatic data: a regional data synthesis for the baltic sea drainage basin M. Zarei & G. Destouni https://doi.org/10.3389/feart.2025.1595943
45. The representation of rivers in operational ocean forecasting systems: a review P. Matte et al. https://doi.org/10.5194/sp-5-opsr-19-2025
46. Global‐Scale Prediction of Flood Timing Using Atmospheric Reanalysis H. Do et al. https://doi.org/10.1029/2019WR024945
47. Extending global river gauge records using satellite observations R. Riggs et al. https://doi.org/10.1088/1748-9326/acd407
48. Dynamic Sea Level Variability Due to Seasonal River Discharge: A Preliminary Global Ocean Model Study C. Piecuch & R. Wadehra https://doi.org/10.1029/2020GL086984
49. From empirical to physical constraints: Revisiting the structure of monthly water balance models with global evaluation Z. Ning et al. https://doi.org/10.1016/j.jhydrol.2026.134916
50. Global assessment of river flow regimes simulated by reach-level streamflow datasets Q. Luo et al. https://doi.org/10.1016/j.jhydrol.2026.136330
51. A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022) X. Chen et al. https://doi.org/10.5194/essd-15-4463-2023
52. Seasonal diversity of global flood changes and their drivers X. Gu et al. https://doi.org/10.1016/j.jhydrol.2025.133976
53. G‐RUN ENSEMBLE: A Multi‐Forcing Observation‐Based Global Runoff Reanalysis G. Ghiggi et al. https://doi.org/10.1029/2020WR028787
54. Design flood estimation for global river networks based on machine learning models G. Zhao et al. https://doi.org/10.5194/hess-25-5981-2021
55. CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain G. Coxon et al. https://doi.org/10.5194/essd-12-2459-2020
56. Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable M. Ibrahim et al. https://doi.org/10.5194/hess-29-1703-2025
57. Catchment precipitation partitioning in the Budyko framework is controlled by root zone storage capacity M. Ibrahim et al. https://doi.org/10.1088/1748-9326/ae612a
58. Global patterns in vegetation accessible subsurface water storage emerge from spatially varying importance of individual drivers F. van Oorschot et al. https://doi.org/10.1088/1748-9326/ad8805
59. Hydrometeorological Network of Namal Valley, Pakistan M. Sheraz et al. https://doi.org/10.1038/s41597-025-05310-3
60. Evaluating the impact of rainfall–runoff model structural uncertainty on the hydrological rating of regional climate model simulations H. Dakhlaoui & K. Djebbi https://doi.org/10.2166/wcc.2021.004
61. Floodwater utilization potential assessment of China based on improved conceptual model and multi-reservoir basin assessment method K. Wang et al. https://doi.org/10.1016/j.jhydrol.2023.129921
62. Impact of Continental Freshwater Runoff on Coastal Sea Level F. Durand et al. https://doi.org/10.1007/s10712-019-09536-w
63. Turning Lakes Into River Gauges Using the LakeFlow Algorithm R. Riggs et al. https://doi.org/10.1029/2023GL103924
64. Drought decreases annual streamflow response to precipitation, especially in arid regions A. Matanó et al. https://doi.org/10.5194/hess-29-2749-2025
65. CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland M. Höge et al. https://doi.org/10.5194/essd-15-5755-2023
66. Remotely sensed evapotranspiration-based ensemble streamflow modeling in an ungauged watershed under climate and land use/cover change, North Korea Y. Lee et al. https://doi.org/10.1016/j.jenvman.2026.129919
67. Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v1.2: an open-source, extendable framework providing implementations of 46 conceptual hydrologic models as continuous state-space formulations W. Knoben et al. https://doi.org/10.5194/gmd-12-2463-2019
68. Evaluation of river flood extent simulated with multiple global hydrological models and climate forcings B. Mester et al. https://doi.org/10.1088/1748-9326/ac188d
69. Climate and landscape jointly control European streamflow behaviour J. Rudlang et al. https://doi.org/10.5194/hess-30-4481-2026
70. An adaptive decomposition-denoising and temporal context fusion framework for multi-station water-level forecasting H. Lv et al. https://doi.org/10.1016/j.jhydrol.2026.135339
71. Attribution of streamflow changes across the globe based on the Budyko framework J. Liu et al. https://doi.org/10.1016/j.scitotenv.2021.148662
72. Drought in intermittent river and ephemeral stream networks R. Sarremejane et al. https://doi.org/10.1002/eco.2390
73. The Global Streamflow Indices and Metadata Archive (GSIM) – Part 1: The production of a daily streamflow archive and metadata H. Do et al. https://doi.org/10.5194/essd-10-765-2018
74. Improving satellite remote sensing estimates of the global terrestrial water cycle via neural network modeling M. Heberger et al. https://doi.org/10.1016/j.jhydrol.2025.133825
75. Weakening flood, intensifying hydrological drought severity and decreasing drought probability in Northeast China W. Qi et al. https://doi.org/10.1016/j.ejrh.2021.100941
76. Variable contributions of vertical land motion to sea-level change inferred at tide gauges S. Dangendorf et al. https://doi.org/10.1038/s41561-026-02005-1
77. Hydrography90m: a new high-resolution global hydrographic dataset G. Amatulli et al. https://doi.org/10.5194/essd-14-4525-2022
78. Data quality assurance practices in research data repositories—A systematic literature review. An Annual Review of Information Science and Technology (ARIST) paper B. Stvilia et al. https://doi.org/10.1002/asi.24948
79. Trends in Global Flood and Streamflow Timing Based on Local Water Year C. Wasko et al. https://doi.org/10.1029/2020WR027233
80. Enhanced extremes without intensification of South America’s water cycle from 1980 to 2010 M. Zarei & G. Destouni https://doi.org/10.1038/s43247-026-03661-2
81. Influence of irrigation on root zone storage capacity estimation F. van Oorschot et al. https://doi.org/10.5194/hess-28-2313-2024
82. Sectoral water use responses to droughts and heatwaves: analyses from local to global scales for 1990–2019 G. Cárdenas Belleza et al. https://doi.org/10.1088/1748-9326/acf82e
83. EARLS: a runoff reconstruction dataset for Europe D. Klotz et al. https://doi.org/10.5194/essd-18-5485-2026
84. The Roles of Catchment Characteristics in Precipitation Partitioning Within the Budyko Framework J. Liu & Y. You https://doi.org/10.1029/2021JD035168
85. Timing of Landsat Overpasses Effectively Captures Flow Conditions of Large Rivers G. Allen et al. https://doi.org/10.3390/rs12091510
86. Observation‐Constrained Projection of Global Flood Magnitudes With Anthropogenic Warming W. Liu et al. https://doi.org/10.1029/2020WR028830
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88. LamaH | Large-Sample Data for Hydrology: Big data für die Hydrologie und Umweltwissenschaften C. Klingler et al. https://doi.org/10.1007/s00506-021-00769-x
89. Synchronization of global peak river discharge since the 1980s Y. Yang et al. https://doi.org/10.1038/s41558-025-02427-6
90. A global dataset of reservoir in-situ water levels for hydrological and remote sensing applications M. Zhang et al. https://doi.org/10.1038/s41597-026-07091-9
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93. Economic consequences of cascading drought-flood events: evidence from central Europe S. Deng et al. https://doi.org/10.1088/1748-9326/ae0f43
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99. GRUN: an observation-based global gridded runoff dataset from 1902 to 2014 G. Ghiggi et al. https://doi.org/10.5194/essd-11-1655-2019
100. The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features H. Müller Schmied et al. https://doi.org/10.5194/gmd-17-8817-2024
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110. Annual memory in the terrestrial water cycle W. Berghuijs et al. https://doi.org/10.5194/hess-29-1319-2025
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115. A hydrological knowledge-informed LSTM model for monthly streamflow reconstruction using distributed data: Application to typical rivers across the Tibetan plateau S. Hou et al. https://doi.org/10.1016/j.jhydrol.2024.132409
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118. A review of hydrologic signatures and their applications H. McMillan https://doi.org/10.1002/wat2.1499
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121. Quality assessment of hydrometeorological observational data and their influence on hydrological model results in Alpine catchments F. Hofmeister et al. https://doi.org/10.1080/02626667.2023.2172335
122. Inference of Parameters for a Global Hydrological Model: Identifiability and Predictive Uncertainties of Climate‐Based Parameters T. Yoshida et al. https://doi.org/10.1029/2021WR030660
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126. Priority Research Topics to Improve Streamflow Data Availability in Data-Scarce Countries: The Case for Ethiopia M. Taye et al. https://doi.org/10.3390/hydrology10120220
127. A data-driven persistence test for robust (probabilistic) quality control of measured environmental time series: constant value episodes N. Kaffashzadeh https://doi.org/10.5194/amt-16-3085-2023
128. An ensemble-based projection of future hydro-climatic extremes in Iran A. Jahanshahi et al. https://doi.org/10.1016/j.jhydrol.2024.131892
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132. GRDC-Caravan: extending Caravan with data from the Global Runoff Data Centre C. Färber et al. https://doi.org/10.5194/essd-17-4613-2025
133. Coherent Streamflow Variability in Monsoon Asia Over the Past Eight Centuries—Links to Oceanic Drivers H. Nguyen et al. https://doi.org/10.1029/2020WR027883
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