107 citations as recorded by crossref.

1. Parameter transferability under changing climate: case study with a land surface model in the Durance watershed, France C. Magand et al. https://doi.org/10.1080/02626667.2014.993643
2. Dependence of model-based extreme flood estimation on the calibration period: case study of the Kamp River (Austria) P. Brigode et al. https://doi.org/10.1080/02626667.2015.1006632
3. Using altimetry observations combined with GRACE to select parameter sets of a hydrological model in a data-scarce region P. Hulsman et al. https://doi.org/10.5194/hess-24-3331-2020
4. Improving Parameter Transferability of GR4J Model under Changing Environments Considering Nonstationarity L. Zeng et al. https://doi.org/10.3390/w11102029
5. Debates: Does Information Theory Provide a New Paradigm for Earth Science? Sharper Predictions Using Occam's Digital Razor S. Weijs & B. Ruddell https://doi.org/10.1029/2019WR026471
6. Diagnostic Evaluation of Hydrologic Models Employing Flow Duration Curve V. Chilkoti et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001778
7. Contribution of the satellite-data driven snow routine to a karst hydrological model S. Çallı et al. https://doi.org/10.1016/j.jhydrol.2022.127511
8. Impacts of Uncontrolled Operator Splitting Methods on Parameter Identification, Prediction Uncertainty, and Subsurface Flux Representation in Conceptual Hydrological Models B. Woldegiorgis et al. https://doi.org/10.1029/2022WR033250
9. Hydrological Model Calibration in Data-Scarce Mediterranean Catchments: A Comparative Assessment of Three Strategies A. Jahanshahi et al. https://doi.org/10.3390/hydrology13020066
10. Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models K. Fowler et al. https://doi.org/10.1002/2015WR018068
11. The hazards of split-sample validation in hydrological model calibration R. Arsenault et al. https://doi.org/10.1016/j.jhydrol.2018.09.027
12. Operational Comparison of Rainfall-Runoff Models through Hypothesis Testing J. Fidal & T. Kjeldsen https://doi.org/10.1061/(ASCE)HE.1943-5584.0001892
13. hydroMOPSO: A flexible and model-independent multi-objective optimisation R package for environmental and hydrological models R. Marinao et al. https://doi.org/10.1016/j.envsoft.2025.106851
14. Using multiple objective calibrations to explore uncertainty in extreme event modeling A. Roche et al. https://doi.org/10.1139/cjce-2020-0275
15. Transit time distributions, legacy contamination and variability in biogeochemical 1/fαscaling: how are hydrological response dynamics linked to water quality at the catchment scale? M. Hrachowitz et al. https://doi.org/10.1002/hyp.10546
16. Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration S. Gharari et al. https://doi.org/10.5194/hess-18-4839-2014
17. The predictive performance of process‐explicit range change models remains largely untested D. Uribe‐Rivera et al. https://doi.org/10.1111/ecog.06048
18. Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al. https://doi.org/10.5194/hess-27-4385-2023
19. Neglecting hydrological errors can severely impact predictions of water resource system performance D. McInerney et al. https://doi.org/10.1016/j.jhydrol.2024.130853
20. Signatures of human intervention – or not? Downstream intensification of hydrological drought along a large Central Asian river: the individual roles of climate variability and land use change A. Roodari et al. https://doi.org/10.5194/hess-25-1943-2021
21. Enhanced SWAT calibration through intelligent range-based parameter optimization L. Zhao et al. https://doi.org/10.1016/j.jenvman.2024.121933
22. Assessing uncertainties in surface water security: An empirical multimodel approach D. Rodrigues et al. https://doi.org/10.1002/2014WR016691
23. Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change S. Wi et al. https://doi.org/10.5194/hess-19-857-2015
24. Determining probability distributions of parameter performances for time-series model calibration: A river system trial S. Kim et al. https://doi.org/10.1016/j.jhydrol.2015.09.073
25. Spatially-varying parametrization of the Total Runoff Integrating Pathways (TRIP) scheme for improved river routing at the global scale A. Tsilimigkras et al. https://doi.org/10.1016/j.jhydrol.2025.133477
26. Comparative assessment of predictions in ungauged basins – Part 3: Runoff signatures in Austria A. Viglione et al. https://doi.org/10.5194/hess-17-2263-2013
27. Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment C. Tunaley et al. https://doi.org/10.1002/hyp.11313
28. Scenario-based analysis of upstream land use Land Cover Changes (LULC) in the Densu River Basin (DRB) on catchment hydrology including the Weija Reservoir, Ghana J. Acheampong et al. https://doi.org/10.1080/15715124.2025.2553805
29. Disaggregated monthly hydrological models can outperform daily models in providing daily flow statistics and extrapolate well to a drying climate A. John et al. https://doi.org/10.1016/j.jhydrol.2021.126471
30. A conceptual, distributed snow redistribution model S. Frey & H. Holzmann https://doi.org/10.5194/hess-19-4517-2015
31. Identifying advantages and drawbacks of two hydrological models based on a sensitivity analysis: a study in two Chilean watersheds V. Parra et al. https://doi.org/10.1080/02626667.2018.1538593
32. Seeking genericity in the selection of parameter sets: Impact on hydrological model efficiency V. Andréassian et al. https://doi.org/10.1002/2013WR014761
33. Assessing the Performance of Two Hydrologic Models for Forecasting Daily Streamflows in the Cazones River Basin (Mexico) F. González-Leiva et al. https://doi.org/10.4236/ojmh.2016.63014
34. Hydrological climate change impact assessment in high latitudes: are bucket-type models up to the task? A. Todorović et al. https://doi.org/10.1016/j.envsoft.2026.106964
35. An R package to partition observation data used for model development and evaluation to achieve model generalizability Y. Ji et al. https://doi.org/10.1016/j.envsoft.2024.106238
36. Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement K. Fowler et al. https://doi.org/10.1029/2018WR023989
37. Quantifying the Uncertainty Created by Non‐Transferable Model Calibrations Across Climate and Land Cover Scenarios: A Case Study With SWMM A. Sytsma et al. https://doi.org/10.1029/2021WR031603
38. Streamflow Simulation in Semiarid Data-Scarce Regions: A Comparative Study of Distributed and Lumped Models at Aguenza Watershed (Morocco) A. Bouadila et al. https://doi.org/10.3390/w15081602
39. A framework for seasonal variations of hydrological model parameters: impact on model results and response to dynamic catchment characteristics T. Lan et al. https://doi.org/10.5194/hess-24-5859-2020
40. HESS Opinions: The complementary merits of competing modelling philosophies in hydrology M. Hrachowitz & M. Clark https://doi.org/10.5194/hess-21-3953-2017
41. A Bayesian Hierarchical Framework for Postprocessing Daily Streamflow Simulations across a River Network Á. Ossandón et al. https://doi.org/10.1175/JHM-D-21-0167.1
42. A hydro-climatic approach for extreme flood estimation in mountainous catchments M. Bashirgonbad et al. https://doi.org/10.1007/s13201-024-02149-8
43. Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany S. Wang et al. https://doi.org/10.5194/hess-28-4011-2024
44. Assessing water system vulnerabilities under changing climate conditions using different representations of a hydrological system A. Sharifinejad et al. https://doi.org/10.1080/02626667.2021.2014057
45. Effect of data length, spin-up period and spatial model resolution on fully distributed hydrological model calibration in the Moselle basin Ö. Ekmekcioğlu et al. https://doi.org/10.1080/02626667.2022.2046754
46. Lead-time-dependent calibration of a flood forecasting model P. Astagneau et al. https://doi.org/10.1016/j.jhydrol.2024.132119
47. Choosing an arbitrary calibration period for hydrologic models: How much does it influence water balance simulations? D. Myers et al. https://doi.org/10.1002/hyp.14045
48. Process consistency in models: The importance of system signatures, expert knowledge, and process complexity M. Hrachowitz et al. https://doi.org/10.1002/2014WR015484
49. Predicting the ungauged basin: model validation and realism assessment T. van Emmerik et al. https://doi.org/10.3389/feart.2015.00062
50. From marginal to conditional probability functions of parameters in a conceptual rainfall–runoff model: an event-based approach S. Sandoval & J. Bertrand-Krajewski https://doi.org/10.1080/02626667.2019.1635696
51. Time-varying parameters of the hydrological simulation model under a changing environment R. Liu et al. https://doi.org/10.1016/j.jhydrol.2024.131943
52. Time-varying hydrological simulation based on a SWD-SSC method J. Wang et al. https://doi.org/10.1016/j.ejrh.2024.101808
53. Probabilistic Projections of Multidimensional Flood Risks at a Convection‐Permitting Scale B. Zhang et al. https://doi.org/10.1029/2020WR028582
54. 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
55. Development of a copula‐based particle filter (CopPF) approach for hydrologic data assimilation under consideration of parameter interdependence Y. Fan et al. https://doi.org/10.1002/2016WR020144
56. The robustness of conceptual rainfall-runoff modelling under climate variability – A review H. Ji et al. https://doi.org/10.1016/j.jhydrol.2023.129666
57. Comparison between dynamic and static sensitivity analysis approaches for impact assessment of different potential evapotranspiration methods on hydrological models performance R. Nonki et al. https://doi.org/10.1175/JHM-D-20-0192.1
58. Research on green water components and potential evaluation framework based on MIKE SHE model – A case study in the Loess Plateau of China L. Wang et al. https://doi.org/10.1016/j.ecolind.2023.110613
59. A sequential experimental design for multivariate sensitivity analysis using polynomial chaos expansion X. Shang et al. https://doi.org/10.1080/0305215X.2019.1651309
60. Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach F. Garavaglia et al. https://doi.org/10.5194/hess-21-3937-2017
61. Identifying time-varying hydrological model parameters to improve simulation efficiency by the ensemble Kalman filter: A joint assimilation of streamflow and actual evapotranspiration M. Xiong et al. https://doi.org/10.1016/j.jhydrol.2018.11.038
62. A Framework for Dry Period Low Flow Forecasting in Mediterranean Streams K. Risva et al. https://doi.org/10.1007/s11269-018-2060-z
63. A time-varying parameter estimation approach using split-sample calibration based on dynamic programming X. Zhang & P. Liu https://doi.org/10.5194/hess-25-711-2021
64. A decade of Predictions in Ungauged Basins (PUB)—a review M. Hrachowitz et al. https://doi.org/10.1080/02626667.2013.803183
65. The Quest for Hydrological Signatures: Effects of Data Transformation on Bayesian Inference of Watershed Models M. Sadegh et al. https://doi.org/10.1007/s11269-018-1908-6
66. Quantification and allocation of uncertainties of climate change impacts on hydropower potential under 1.5 °C and 2.0 °C global warming levels in the headwaters of the Benue River Basin, Cameroon R. Nonki et al. https://doi.org/10.1016/j.renene.2023.118979
67. WITHDRAWN: Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective K. Kim et al. https://doi.org/10.1016/j.hydroa.2021.100109
68. Unwrapping the triptych of climatic, social and energy-market uncertainties in the operation of multipurpose hydropower reservoirs G. Sakki et al. https://doi.org/10.1016/j.jhydrol.2024.132416
69. Calibrating Environment Canada's MESH Modelling System over the Great Lakes Basin A. Haghnegahdar et al. https://doi.org/10.1080/07055900.2014.939131
70. Global Sensitivity Analysis of environmental models: Convergence and validation F. Sarrazin et al. https://doi.org/10.1016/j.envsoft.2016.02.005
71. The role of conceptual hydrologic model calibration in climate change impact on water resources assessment A. Todorovic & J. Plavsic https://doi.org/10.2166/wcc.2015.086
72. Comparison of Hydrological Platforms in Assessing Rainfall-Runoff Behavior in a Mediterranean Watershed of Northern Morocco M. Aqnouy et al. https://doi.org/10.3390/w15030447
73. A physics-driven hybrid transformer model for hydrologic simulation under nonstationary environmental conditions H. Zhang et al. https://doi.org/10.1016/j.jhydrol.2026.135133
74. A Clustering Preprocessing Framework for the Subannual Calibration of a Hydrological Model Considering Climate‐Land Surface Variations T. Lan et al. https://doi.org/10.1029/2018WR023160
75. Optimal Hydrological Model Calibration Strategy for Climate Change Impact Studies S. Bérubé et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002148
76. Improved Rainfall‐Runoff Calibration for Drying Climate: Choice of Objective Function K. Fowler et al. https://doi.org/10.1029/2017WR022466
77. An efficient framework for hydrologic model calibration on long data periods S. Razavi & B. Tolson https://doi.org/10.1002/2012WR013442
78. Improving Information Extraction From Simulated Discharge Using Sensitivity‐Weighted Performance Criteria B. Guse et al. https://doi.org/10.1029/2019WR025605
79. Sensitivity and identifiability analysis of a conceptual-lumped model in the headwaters of the Benue River Basin, Cameroon: implications for uncertainty quantification and parameter optimization R. Nonki et al. https://doi.org/10.2166/nh.2023.243
80. On the lack of robustness of hydrologic models regarding water balance simulation: a diagnostic approach applied to three models of increasing complexity on 20 mountainous catchments L. Coron et al. https://doi.org/10.5194/hess-18-727-2014
81. Assessing the role of uncertain precipitation estimates on the robustness of hydrological model parameters under highly variable climate conditions B. Bisselink et al. https://doi.org/10.1016/j.ejrh.2016.09.003
82. Dynamics of hydrological-model parameters: mechanisms, problems and solutions T. Lan et al. https://doi.org/10.5194/hess-24-1347-2020
83. Urban flood response and hydrological model performance in a tropical watershed of northeastern Brazil J. de Andrade et al. https://doi.org/10.1016/j.jsames.2026.106220
84. 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
85. Bayesian chemistry-assisted hydrograph separation (BACH) and nutrient load partitioning from monthly stream phosphorus and nitrogen concentrations S. Woodward & R. Stenger https://doi.org/10.1007/s00477-018-1612-3
86. Is ET often oversimplified in hydrologic models? Using long records to elucidate unaccounted for controls on ET C. Kelleher & S. Shaw https://doi.org/10.1016/j.jhydrol.2017.12.018
87. Towards more realistic runoff projections by removing limits on simulated soil moisture deficit K. Fowler et al. https://doi.org/10.1016/j.jhydrol.2021.126505
88. Influence of climate and land-use changes on the sensitivity of SWAT model parameters and water availability in a semi-arid river basin A. Sharma et al. https://doi.org/10.1016/j.catena.2022.106298
89. Comparison of ensemble data assimilation methods for the estimation of time-varying soil hydraulic parameters K. Liu et al. https://doi.org/10.1016/j.jhydrol.2020.125729
90. Hydrology under change: an evaluation protocol to investigate how hydrological models deal with changing catchments G. Thirel et al. https://doi.org/10.1080/02626667.2014.967248
91. Testing the realism of a topography-driven model (FLEX-Topo) in the nested catchments of the Upper Heihe, China H. Gao et al. https://doi.org/10.5194/hess-18-1895-2014
92. Conceptual modelling to assess the influence of hydro-climatic variability on runoff processes in data scarce semi-arid Andean catchments A. Nauditt et al. https://doi.org/10.1080/02626667.2016.1240870
93. A Streamlined Model-Based Strategy for Screening Wildfire Impact Scenarios Related to Peak Flood Flows: Hazard Prevention in Data-Limited Regions J. Romero-Cuellar et al. https://doi.org/10.1061/JHYEFF.HEENG-6318
94. A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox M. Sadegh et al. https://doi.org/10.1007/s11269-019-02283-y
95. Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model P. Kalura et al. https://doi.org/10.1002/hyp.15275
96. Modelling time-variant parameters of a two-parameter monthly water balance model C. Deng et al. https://doi.org/10.1016/j.jhydrol.2019.04.027
97. A three-source SVAT modeling of evaporation: Application to the seasonal dynamics of a grassed vineyard C. Montes et al. https://doi.org/10.1016/j.agrformet.2014.02.004
98. Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers L. Santos et al. https://doi.org/10.5194/hess-29-683-2025
99. Hydrologic modeling in dynamic catchments: A data assimilation approach S. Pathiraja et al. https://doi.org/10.1002/2015WR017192
100. Temporal variation and scaling of parameters for a monthly hydrologic model C. Deng et al. https://doi.org/10.1016/j.jhydrol.2018.01.049
101. Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective K. Kim et al. https://doi.org/10.1016/j.jhydrol.2021.127261
102. A Pareto‐Based Sensitivity Analysis and Multiobjective Calibration Approach for Integrating Streamflow and Evaporation Data P. Yeste et al. https://doi.org/10.1029/2022WR033235
103. Managing water resources in complex tropical basins: tailored SWAT ecohydrological modeling to the Rio das Velhas, Brazil A. Almeida et al. https://doi.org/10.1590/2318-0331.282320230034
104. Simulating Runoff and Actual Evapotranspiration via Time-Variant Parameter Method: The Effects of Hydrological Model Structures Z. Pan et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002220
105. A strategy for diagnosing and interpreting hydrological model nonstationarity S. Westra et al. https://doi.org/10.1002/2013WR014719
106. Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters L. Bouaziz et al. https://doi.org/10.5194/hess-26-1295-2022
107. Assessing the performance and robustness of two conceptual rainfall-runoff models on a worldwide sample of watersheds T. Mathevet et al. https://doi.org/10.1016/j.jhydrol.2020.124698