123 citations as recorded by crossref.

1. Revisiting the Basis of Sensitivity Analysis for Dynamical Earth System Models H. Gupta & S. Razavi 10.1029/2018WR022668
2. Controls and characteristics of variability in soil moisture and groundwater in a headwater catchment H. McMillan & M. Srinivasan 10.5194/hessd-11-9475-2014
3. Benchmarking and Process Diagnostics of Land Models G. Nearing et al. 10.1175/JHM-D-17-0209.1
4. Event‐based classification for global study of river flood generating processes L. Stein et al. 10.1002/hyp.13678
5. Typhoon Nina and the August 1975 Flood over Central China L. Yang et al. 10.1175/JHM-D-16-0152.1
6. Advancing catchment hydrology to deal with predictions under change U. Ehret et al. 10.5194/hess-18-649-2014
7. Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement K. Fowler et al. 10.1029/2018WR023989
8. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments S. Almeida et al. 10.5194/hessd-12-5389-2015
9. Robust changes and sources of uncertainty in the projected hydrological regimes of Swiss catchments N. Addor et al. 10.1002/2014WR015549
10. On the ability of large-scale hydrological models to simulate land use and land cover change impacts in Amazonian basins D. Rodriguez & J. Tomasella 10.1080/02626667.2015.1051979
11. CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain G. Coxon et al. 10.5194/essd-12-2459-2020
12. Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall-runoff models K. Fowler et al. 10.1002/2015WR018068
13. HESS Opinions: Advocating process modeling and de-emphasizing parameter estimation A. Bahremand 10.5194/hess-20-1433-2016
14. Challenges of Operational River Forecasting T. Pagano et al. 10.1175/JHM-D-13-0188.1
15. Using R in hydrology: a review of recent developments and future directions L. Slater et al. 10.5194/hess-23-2939-2019
16. Accounting for the influence of vegetation and landscape improves model transferability in a tropical savannah region H. Gao et al. 10.1002/2016WR019574
17. Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions G. Nearing et al. 10.1175/JHM-D-15-0063.1
18. Seasonal streamflow forecasting by conditioning climatology with precipitation indices L. Crochemore et al. 10.5194/hess-21-1573-2017
19. A crash-testing framework for predictive uncertainty assessment when forecasting high flows in an extrapolation context L. Berthet et al. 10.5194/hess-24-2017-2020
20. Quantifying Positive and Negative Human-Modified Droughts in the Anthropocene: Illustration with Two Iranian Catchments . Kakaei et al. 10.3390/w11050884
21. Towards seamless large-domain parameter estimation for hydrologic models N. Mizukami et al. 10.1002/2017WR020401
22. Spatial Combination Modeling Framework of Saturation-Excess and Infiltration-Excess Runoff for Semihumid Watersheds P. Huang et al. 10.1155/2016/5173984
23. Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case I. Pechlivanidis & B. Arheimer 10.5194/hess-19-4559-2015
24. Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling H. Beck et al. 10.5194/hess-21-6201-2017
25. Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance A. Newman et al. 10.5194/hess-19-209-2015
26. Diagnosis of insidious data disasters J. Lundquist et al. 10.1002/2014WR016585
27. Uncertainty in hydrological signatures for gauged and ungauged catchments I. Westerberg et al. 10.1002/2015WR017635
28. Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges N. Addor et al. 10.1080/02626667.2019.1683182
29. Seasonality of runoff and precipitation regimes along transects in Peru and Austria M. Gaudry et al. 10.1515/johh-2017-0018
30. On the need to test hydrological models under changing conditions G. Thirel et al. 10.1080/02626667.2015.1050027
31. CAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in Brazil V. Chagas et al. 10.5194/essd-12-2075-2020
32. Benchmarking hydrological models for low-flow simulation and forecasting on French catchments P. Nicolle et al. 10.5194/hess-18-2829-2014
33. Étude de la sensibilité des paramètres d'un modèle «rural» sur des bassins versants urbanisés M. Saadi et al. 10.1051/lhb/2019013
34. A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations G. Coxon et al. 10.1002/2014WR016532
35. On the choice of calibration metrics for “high-flow” estimation using hydrologic models N. Mizukami et al. 10.5194/hess-23-2601-2019
36. The CR of Evaporation: A Calibration‐Free Diagnostic and Benchmarking Tool for Large‐Scale Terrestrial Evapotranspiration Modeling N. Ma & J. Szilagyi 10.1029/2019WR024867
37. Moving sociohydrology forward: a synthesis across studies T. Troy et al. 10.5194/hessd-12-3319-2015
38. Global karst springs hydrograph dataset for research and management of the world’s fastest-flowing groundwater T. Olarinoye et al. 10.1038/s41597-019-0346-5
39. Historical and future changes in global flood magnitude – evidence from a model–observation investigation H. Do et al. 10.5194/hess-24-1543-2020
40. Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets F. Kratzert et al. 10.5194/hess-23-5089-2019
41. Using Natural Experiments and Counterfactuals for Causal Assessment: River Salinity and the Ganges Water Agreement G. Penny et al. 10.1029/2019WR026166
42. Toward a theoretical framework for integrated modeling of hydrological change S. Ceola et al. 10.1002/wat2.1038
43. Crossing the rural–urban boundary in hydrological modelling: How do conceptual rainfall–runoff models handle the specificities of urbanized catchments? M. Saadi et al. 10.1002/hyp.13808
44. Is Catchment Classification Possible by Means of Multiple Model Structures? A Case Study Based on 99 Catchments in Germany R. Ley et al. 10.3390/hydrology3020022
45. Using flow signatures and catchment similarities to evaluate the E-HYPE multi-basin model across Europe C. Donnelly et al. 10.1080/02626667.2015.1027710
46. Flood triggering in Switzerland: the role of daily to monthly preceding precipitation P. Froidevaux et al. 10.5194/hess-19-3903-2015
47. Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach F. Garavaglia et al. 10.5194/hess-21-3937-2017
48. A review of freely accessible global datasets for the study of floods, droughts and their interactions with human societies S. Lindersson et al. 10.1002/wat2.1424
49. Panta Rhei 2013–2015: global perspectives on hydrology, society and change H. McMillan et al. 10.1080/02626667.2016.1159308
50. Toward seamless hydrologic predictions across spatial scales L. Samaniego et al. 10.5194/hess-21-4323-2017
51. Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case I. Pechlivanidis & B. Arheimer 10.5194/hessd-12-2885-2015
52. Crash tests for forward-looking flood control in the city of Zürich (Switzerland) M. Zappa et al. 10.5194/piahs-370-235-2015
53. Identification of factors influencing hydrologic model performance using a top‐down approach in a large number of U.S. catchments C. Massmann 10.1002/hyp.13566
54. The hazards of split-sample validation in hydrological model calibration R. Arsenault et al. 10.1016/j.jhydrol.2018.09.027
55. Replication of ecologically relevant hydrological indicators following a modified covariance approach to hydrological model parameterization A. Visser-Quinn et al. 10.5194/hess-23-3279-2019
56. Improvement and evaluation of the Iowa Flood Center Hillslope Link Model (HLM) by calibration-free approach F. Quintero et al. 10.1016/j.jhydrol.2020.124686
57. Diagnostic Evaluation of Large‐Domain Hydrologic Models Calibrated Across the Contiguous United States O. Rakovec et al. 10.1029/2019JD030767
58. Multi-Basin Modelling of Future Hydrological Fluxes in the Indian Subcontinent I. Pechlivanidis et al. 10.3390/w8050177
59. Process consistency in models: The importance of system signatures, expert knowledge, and process complexity M. Hrachowitz et al. 10.1002/2014WR015484
60. Are modern metaheuristics successful in calibrating simple conceptual rainfall–runoff models? A. Piotrowski et al. 10.1080/02626667.2016.1234712
61. Using hydrological and climatic catchment clusters to explore drivers of catchment behavior F. Jehn et al. 10.5194/hess-24-1081-2020
62. A comprehensive, multisource database for hydrometeorological modeling of 14,425 North American watersheds R. Arsenault et al. 10.1038/s41597-020-00583-2
63. A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States N. Ma et al. 10.1002/2017JD027597
64. HESS Opinions: The complementary merits of competing modelling philosophies in hydrology M. Hrachowitz & M. Clark 10.5194/hess-21-3953-2017
65. Characteristics and controls of variability in soil moisture and groundwater in a headwater catchment H. McMillan & M. Srinivasan 10.5194/hess-19-1767-2015
66. Global Maps of Streamflow Characteristics Based on Observations from Several Thousand Catchments* H. Beck et al. 10.1175/JHM-D-14-0155.1
67. The CAMELS data set: catchment attributes and meteorology for large-sample studies N. Addor et al. 10.5194/hess-21-5293-2017
68. Global-scale regionalization of hydrologic model parameters H. Beck et al. 10.1002/2015WR018247
69. Diagnostic calibration and cross-catchment transferability of a simple process-consistent hydrologic model T. Smith et al. 10.1002/hyp.10955
70. Event-based prediction of stream turbidity using a combined cluster analysis and classification tree approach A. Mather & R. Johnson 10.1016/j.jhydrol.2015.10.032
71. Computational approaches for annual maximum river flow series H. Tiwari et al. 10.1016/j.asej.2015.07.016
72. Benchmarking of a Physically Based Hydrologic Model A. Newman et al. 10.1175/JHM-D-16-0284.1
73. A process‐based approach to attribution of historical streamflow decline in a data‐scarce and human‐dominated watershed G. Penny et al. 10.1002/hyp.13707
74. Hydrological modelling of the Vistula and Odra river basins using SWAT M. Piniewski et al. 10.1080/02626667.2017.1321842
75. Validation of a national hydrological model H. McMillan et al. 10.1016/j.jhydrol.2016.07.043
76. The Quantile Solidarity approach for the parsimonious regionalization of flow duration curves C. Poncelet et al. 10.1080/02626667.2017.1335399
77. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments S. Almeida et al. 10.5194/hess-20-887-2016
78. Are Model Transferability And Complexity Antithetical? Insights From Validation of a Variable-Complexity Empirical Snow Model in Space and Time A. Lute & C. Luce 10.1002/2017WR020752
79. What Are the Key Drivers Controlling the Quality of Seasonal Streamflow Forecasts? I. Pechlivanidis et al. 10.1029/2019WR026987
80. Multiscale and Multivariate Evaluation of Water Fluxes and States over European River Basins O. Rakovec et al. 10.1175/JHM-D-15-0054.1
81. Development of a large-sample watershed-scale hydrometeorological dataset for the contiguous USA: dataset characteristics and assessment of regional variability in hydrologic model performance A. Newman et al. 10.5194/hessd-11-5599-2014
82. Scaling, similarity, and the fourth paradigm for hydrology C. Peters-Lidard et al. 10.5194/hess-21-3701-2017
83. Global evaluation of runoff from 10 state-of-the-art hydrological models H. Beck et al. 10.5194/hess-21-2881-2017
84. Identifying the connective strength between model parameters and performance criteria B. Guse et al. 10.5194/hess-21-5663-2017
85. Parameter's Controls of Distributed Catchment Models—How Much Information is in Conventional Catchment Descriptors? R. Merz et al. 10.1029/2019WR026008
86. Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms G. Papacharalampous et al. 10.3390/w11102126
87. Heteroscedastic and symmetric efficiency for hydrological model evaluation criteria C. Zhan et al. 10.2166/nh.2019.121
88. Understanding the impacts of catchment characteristics on the shape of the storage capacity curve and its influence on flood flows H. Gao et al. 10.2166/nh.2017.245
89. Virtual laboratories: new opportunities for collaborative water science S. Ceola et al. 10.5194/hess-19-2101-2015
90. The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset C. Alvarez-Garreton et al. 10.5194/hess-22-5817-2018
91. Efficient estimation of flood forecast prediction intervals via single- and multi-objective versions of the LUBE method L. Ye et al. 10.1002/hyp.10799
92. On the Robustness of Conceptual Rainfall‐Runoff Models to Calibration and Evaluation Data Set Splits Selection: A Large Sample Investigation D. Guo et al. 10.1029/2019WR026752
93. Improving the realism of hydrologic model functioning through multivariate parameter estimation O. Rakovec et al. 10.1002/2016WR019430
94. Improving the theoretical underpinnings of process-based hydrologic models M. Clark et al. 10.1002/2015WR017910
95. Estimating a-priori kinematic wave model parameters based on regionalization for flash flood forecasting in the Conterminous United States H. Vergara et al. 10.1016/j.jhydrol.2016.06.011
96. Virtual laboratories: new opportunities for collaborative water science S. Ceola et al. 10.5194/hessd-11-13443-2014
97. Land Use Change Increases Streamflow Across the Arc of Deforestation in Brazil M. Levy et al. 10.1002/2017GL076526
98. Analysing spatio-temporal process and parameter dynamics in models to characterise contrasting catchments B. Guse et al. 10.1016/j.jhydrol.2018.12.050
99. Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain R. Lane et al. 10.5194/hess-23-4011-2019
100. Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation B. Arheimer et al. 10.5194/hess-24-535-2020
101. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty E. Moges et al. 10.1002/2015WR018266
102. The Impacts of Native Forests and Forest Plantations on Water Supply in Chile C. Alvarez-Garreton et al. 10.3390/f10060473
103. How should a rainfall-runoff model be parameterized in an almost ungauged catchment? A methodology tested on 609 catchments C. Rojas-Serna et al. 10.1002/2015WR018549
104. What can we learn from the projections of changes of flow patterns? Results from Polish case studies M. Piniewski et al. 10.1007/s11600-017-0061-6
105. Advancing catchment hydrology to deal with predictions under change U. Ehret et al. 10.5194/hessd-10-8581-2013
106. Evaluating a finer resolution global hydrological model’s simulation of discharge in four West-African river basins T. Babalola et al. 10.1007/s40808-020-00948-x
107. Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations S. Yatheendradas et al. 10.1007/s10596-018-9804-y
108. Moving sociohydrology forward: a synthesis across studies T. Troy et al. 10.5194/hess-19-3667-2015
109. Estimating catchment scale groundwater dynamics from recession analysis – enhanced constraining of hydrological models T. Skaugen & Z. Mengistu 10.5194/hessd-12-11129-2015
110. Accelerating advances in continental domain hydrologic modeling S. Archfield et al. 10.1002/2015WR017498
111. Assessing the performance and robustness of two conceptual rainfall-runoff models on a worldwide sample of watersheds T. Mathevet et al. 10.1016/j.jhydrol.2020.124698
112. Looking beyond general metrics for model comparison – lessons from an international model intercomparison study T. de Boer-Euser et al. 10.5194/hess-21-423-2017
113. Full-flow-regime storage-streamflow correlation patterns provide insights into hydrologic functioning over the continental US K. Fang & C. Shen 10.1002/2016WR020283
114. Mapping (dis)agreement in hydrologic projections L. Melsen et al. 10.5194/hess-22-1775-2018
115. Using paired catchments to quantify the human influence on hydrological droughts A. Van Loon et al. 10.5194/hess-23-1725-2019
116. When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation on 3620 flood events F. Lobligeois et al. 10.5194/hessd-10-12485-2013
117. Advances in Quantifying Streamflow Variability Across Continental Scales: 1. Identifying Natural and Anthropogenic Controlling Factors in the USA Using a Spatially Explicit Modeling Method R. Alexander et al. 10.1029/2019WR025001
118. Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments P. Huang et al. 10.1016/j.jhydrol.2016.09.001
119. Performance and Reliability of Probabilistic Scenarios of Interpolated Rainfall Based on Geostatistics H. Razafimahefa & F. Anctil 10.1061/(ASCE)HE.1943-5584.0000913
120. The influence of conceptual model structure on model performance: a comparative study for 237 French catchments W. van Esse et al. 10.5194/hess-17-4227-2013
121. Benchmarking hydrological models for low-flow simulation and forecasting on French catchments P. Nicolle et al. 10.5194/hessd-10-13979-2013
122. When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation using 3620 flood events F. Lobligeois et al. 10.5194/hess-18-575-2014
123. On Lack of Robustness in Hydrological Model Development Due to Absence of Guidelines for Selecting Calibration and Evaluation Data: Demonstration for Data-Driven Models F. Zheng et al. 10.1002/2017WR021470