105 citations as recorded by crossref.

1. Behind every robust result is a robust method: Perspectives from a case study and publication process in hydrological modelling F. Fenicia & D. Kavetski https://doi.org/10.1002/hyp.14266
2. Climate change impacts on surface water resources in the Rheraya catchment (High Atlas, Morocco) A. Marchane et al. https://doi.org/10.1080/02626667.2017.1283042
3. Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective P. Astagneau et al. https://doi.org/10.5194/hess-25-3937-2021
4. Climate non-stationarity – Validity of calibrated rainfall–runoff models for use in climate change studies J. Vaze et al. https://doi.org/10.1016/j.jhydrol.2010.09.018
5. The impact of calibration conditions on the transferability of conceptual hydrological models under stationary and nonstationary climatic conditions W. Yang et al. https://doi.org/10.1016/j.jhydrol.2022.128310
6. Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data M. Peel et al. https://doi.org/10.5194/hess-19-1615-2015
7. Exploration of sub-annual calibration schemes of hydrological models K. Kim & D. Han https://doi.org/10.2166/nh.2016.296
8. Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development F. Fenicia et al. https://doi.org/10.1029/2010WR010174
9. Characterising performance of environmental models N. Bennett et al. https://doi.org/10.1016/j.envsoft.2012.09.011
10. A crash-testing framework for predictive uncertainty assessment when forecasting high flows in an extrapolation context L. Berthet et al. https://doi.org/10.5194/hess-24-2017-2020
11. Crash tests for forward-looking flood control in the city of Zürich (Switzerland) M. Zappa et al. https://doi.org/10.5194/piahs-370-235-2015
12. Holistic versus monomeric strategies for hydrological modelling of human-modified hydrosystems I. Nalbantis et al. https://doi.org/10.5194/hess-15-743-2011
13. Groundwater recharge dynamics to recent wetting in a cold region aquifer H. Mahmoud et al. https://doi.org/10.1016/j.ejrh.2025.102902
14. The influence of conceptual model structure on model performance: a comparative study for 237 French catchments W. van Esse et al. https://doi.org/10.5194/hess-17-4227-2013
15. An approach to the scaling problem in hydrological modelling: the deterministic modelling hydrological system Y. Vinogradov et al. https://doi.org/10.1002/hyp.7901
16. 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
17. Hydrological modelling at multiple sub-daily time steps: Model improvement via flux-matching A. Ficchì et al. https://doi.org/10.1016/j.jhydrol.2019.05.084
18. Synergies entre acteurs opérationnels et scientifiques au service de l'amélioration de la prévision des crues C. Furusho et al. https://doi.org/10.1051/lhb/2016033
19. Hydrological modelling in a changing world M. Peel & G. Blöschl https://doi.org/10.1177/0309133311402550
20. Impact of temporal resolution of inputs on hydrological model performance: An analysis based on 2400 flood events A. Ficchì et al. https://doi.org/10.1016/j.jhydrol.2016.04.016
21. Results of the DMIP 2 Oklahoma experiments M. Smith et al. https://doi.org/10.1016/j.jhydrol.2011.08.056
22. Hydrologically Aided Interpolation of Daily Precipitation and Temperature Fields in a Mesoscale Alpine Catchment N. Le Moine et al. https://doi.org/10.1175/JHM-D-14-0162.1
23. Improved method for identifying Manning’s roughness coefficients in plain looped river network area F. Yang et al. https://doi.org/10.1080/19942060.2020.1858967
24. Generalized Split-Sample Test Interpretation Using Rainfall Runoff Information Gain A. Ben Jaafar & Z. Bargaoui https://doi.org/10.1061/(ASCE)HE.1943-5584.0001868
25. Operational Comparison of Rainfall-Runoff Models through Hypothesis Testing J. Fidal & T. Kjeldsen https://doi.org/10.1061/(ASCE)HE.1943-5584.0001892
26. Validation of hydrological models: Conceptual basis, methodological approaches and a proposal for a code of practice D. Biondi et al. https://doi.org/10.1016/j.pce.2011.07.037
27. Diagnostic Evaluation of Hydrologic Models Employing Flow Duration Curve V. Chilkoti et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001778
28. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions F. Fenicia et al. https://doi.org/10.1002/2015WR017398
29. HESS Opinions: The complementary merits of competing modelling philosophies in hydrology M. Hrachowitz & M. Clark https://doi.org/10.5194/hess-21-3953-2017
30. A controlled model experiment for the global hydrological model WaterGAP3: Understanding recent and new advances in the model structure J. Kupzig & M. Flörke https://doi.org/10.1016/j.envsoft.2025.106703
31. Improving representation of hydrological process heterogeneity in grid-Xin’anjiang model through a stepwise approach Q. Zhang et al. https://doi.org/10.1016/j.jhydrol.2025.132897
32. Technical note: RAT – a robustness assessment test for calibrated and uncalibrated hydrological models P. Nicolle et al. https://doi.org/10.5194/hess-25-5013-2021
33. A channel transmission losses model for different dryland rivers A. Costa et al. https://doi.org/10.5194/hess-16-1111-2012
34. Diagnosis of Model Errors With a Sliding Time‐Window Bayesian Analysis H. Hsueh et al. https://doi.org/10.1029/2021WR030590
35. A Brief Analysis of Conceptual Model Structure Uncertainty Using 36 Models and 559 Catchments W. Knoben et al. https://doi.org/10.1029/2019WR025975
36. An approach to identify time consistent model parameters: sub-period calibration S. Gharari et al. https://doi.org/10.5194/hess-17-149-2013
37. Uncertainty estimation with deep learning for rainfall–runoff modeling D. Klotz et al. https://doi.org/10.5194/hess-26-1673-2022
38. Performance of the COSERO precipitation–runoff model under non-stationary conditions in basins with different climates H. Kling et al. https://doi.org/10.1080/02626667.2014.959956
39. 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
40. smash v1.0: a differentiable and regionalizable high-resolution hydrological modeling and data assimilation framework F. Colleoni et al. https://doi.org/10.5194/gmd-18-7003-2025
41. Techniques to evaluate the modifier process of National Weather Service flood forecasts Z. Zhu et al. https://doi.org/10.1016/j.hydroa.2020.100073
42. Hydrological simulation and evaluation of drought conditions in the ungauged watershed Parishan lake Iran, using the SWAT model S. Ansarifard et al. https://doi.org/10.2166/wcc.2024.268
43. Fit-for-purpose environmental modeling: Targeting the intersection of usability, reliability and feasibility S. Hamilton et al. https://doi.org/10.1016/j.envsoft.2021.105278
44. Does model performance improve with complexity? A case study with three hydrological models R. Orth et al. https://doi.org/10.1016/j.jhydrol.2015.01.044
45. Validation of a national hydrological model H. McMillan et al. https://doi.org/10.1016/j.jhydrol.2016.07.043
46. Understanding Heavy Tails of Flood Peak Distributions B. Merz et al. https://doi.org/10.1029/2021WR030506
47. When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation using 3620 flood events F. Lobligeois et al. https://doi.org/10.5194/hess-18-575-2014
48. HESS Opinions "Topography driven conceptual modelling (FLEX-Topo)" H. Savenije https://doi.org/10.5194/hess-14-2681-2010
49. Understanding dominant controls on streamflow spatial variability to set up a semi-distributed hydrological model: the case study of the Thur catchment M. Dal Molin et al. https://doi.org/10.5194/hess-24-1319-2020
50. Is the LSTM Model Better than RNN for Flood Forecasting Tasks? A Case Study of HuaYuankou Station and LouDe Station in the Lower Yellow River Basin Y. Wang et al. https://doi.org/10.3390/w15223928
51. The Court of Miracles of Hydrology: can failure stories contribute to hydrological science? V. Andréassian et al. https://doi.org/10.1080/02626667.2010.506050
52. 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
53. 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
54. 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
55. Assessment of a multimodel ensemble against an operational hydrological forecasting system A. Thiboult & F. Anctil https://doi.org/10.1080/07011784.2015.1026402
56. Discussion On “Incorporating Drought Management Planning into Determination of Yield” by B Berghout R. French & B. Berghout https://doi.org/10.7158/13241583.2012.11465398
57. A qualitative model structure sensitivity analysis method to support model selection S. Van Hoey et al. https://doi.org/10.1016/j.jhydrol.2014.09.052
58. Capacity of semi-parametric regression models to predict extreme-event water quality in the Northeastern US M. Hagemann & M. Park https://doi.org/10.1016/j.jhydrol.2017.02.017
59. 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
60. Physically consistent conceptual rainfall–runoff model for urbanized catchments M. Saadi et al. https://doi.org/10.1016/j.jhydrol.2021.126394
61. Testing sensitivity of BILAN and GR2M models to climate conditions in the Gambia River Basin D. Ba et al. https://doi.org/10.2478/johh-2023-0044
62. Distributed source pollutant transport module based on BTOPMC: a case study of the Laixi River basin in the Sichuan province of southwest China H. Zhang et al. https://doi.org/10.5194/piahs-379-323-2018
63. Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms G. Papacharalampous et al. https://doi.org/10.3390/w11102126
64. Using field data to inform and evaluate a new model of catchment hydrologic connectivity T. Smith et al. https://doi.org/10.1002/wrcr.20546
65. On evaluating the robustness of spatial-proximity-based regionalization methods L. Lebecherel et al. https://doi.org/10.1016/j.jhydrol.2016.05.031
66. Using models to inform water policy in a changing climate: comparing the Australian and Uruguayan experiences A. Silvarrey Barruffa et al. https://doi.org/10.1071/MF19266
67. Does a successful comprehensive evaluation increase confidence in a hydrological model intended for climate impact assessment? A. Gelfan et al. https://doi.org/10.1007/s10584-020-02930-z
68. A “monster” that made the SMAR conceptual model “right for the wrong reasons” M. Goswami & K. O'Connor https://doi.org/10.1080/02626667.2010.505170
69. Discussion on ‘Recommended practice for hydrologic investigations and reporting’ by RJ Nathan and TA McMahon R. French & M. Jones https://doi.org/10.1080/13241583.2018.1478243
70. 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
71. Large-sample hydrology: a need to balance depth with breadth H. Gupta et al. https://doi.org/10.5194/hess-18-463-2014
72. Comparing classical performance measures with signature indices derived from flow duration curves to assess model structures as tools for catchment classification R. Ley et al. https://doi.org/10.2166/nh.2015.221
73. Hydrological regime of remote catchments with extreme gradients under accelerated change: the Baker basin in Patagonia A. Dussaillant J. et al. https://doi.org/10.1080/02626667.2012.726993
74. Benchmarking hydrological models for low-flow simulation and forecasting on French catchments P. Nicolle et al. https://doi.org/10.5194/hess-18-2829-2014
75. The transferability of hydrological models under nonstationary climatic conditions C. Li et al. https://doi.org/10.5194/hess-16-1239-2012
76. Rainfall-Runoff Modeling of the Nested Non-Homogeneous Sava River Sub-Catchments in Slovenia K. Lavtar et al. https://doi.org/10.3390/w12010128
77. Improving the flood forecasting capability of the Xinanjiang model for small- and medium-sized ungauged catchments in South China J. Gong et al. https://doi.org/10.1007/s11069-021-04531-0
78. Process consistency in models: The importance of system signatures, expert knowledge, and process complexity M. Hrachowitz et al. https://doi.org/10.1002/2014WR015484
79. Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods C. Broderick et al. https://doi.org/10.1002/2016WR018850
80. Seasonal streamflow forecasting by conditioning climatology with precipitation indices L. Crochemore et al. https://doi.org/10.5194/hess-21-1573-2017
81. 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
82. Distributed rainfall‐runoff modelling for flood frequency estimation and flood forecasting L. Brocca et al. https://doi.org/10.1002/hyp.8042
83. Are Model Transferability And Complexity Antithetical? Insights From Validation of a Variable‐Complexity Empirical Snow Model in Space and Time A. Lute & C. Luce https://doi.org/10.1002/2017WR020752
84. Selecting hydrological models for developing countries: Perspective of global, continental, and country scale models over catchment scale models P. Paul et al. https://doi.org/10.1016/j.jhydrol.2021.126561
85. Challenges of Operational River Forecasting T. Pagano et al. https://doi.org/10.1175/JHM-D-13-0188.1
86. The distributed model intercomparison project – Phase 2: Experiment design and summary results of the western basin experiments M. Smith et al. https://doi.org/10.1016/j.jhydrol.2013.08.040
87. Accelerating advances in continental domain hydrologic modeling S. Archfield et al. https://doi.org/10.1002/2015WR017498
88. On the (im)possible validation of hydrogeological models V. Andréassian https://doi.org/10.5802/crgeos.142
89. 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
90. The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models R. Nijzink et al. https://doi.org/10.5194/hess-20-1151-2016
91. CAMELS-FR dataset: a large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking O. Delaigue et al. https://doi.org/10.5194/essd-17-1461-2025
92. A decade of Predictions in Ungauged Basins (PUB)—a review M. Hrachowitz et al. https://doi.org/10.1080/02626667.2013.803183
93. 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
94. Groundwater recharge predictions in contrasted climate: The effect of model complexity and calibration period on recharge rates C. Moeck et al. https://doi.org/10.1016/j.envsoft.2018.02.005
95. When does a parsimonious model fail to simulate floods? Learning from the seasonality of model bias P. Astagneau et al. https://doi.org/10.1080/02626667.2021.1923720
96. A framework to assess the realism of model structures using hydrological signatures T. Euser et al. https://doi.org/10.5194/hess-17-1893-2013
97. Multivariate calibration can increase simulated discharge uncertainty and model equifinality S. Pool et al. https://doi.org/10.5194/hess-30-2797-2026
98. Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions G. Seiller et al. https://doi.org/10.5194/hess-16-1171-2012
99. Assessing the Climatic and Temporal Transposability of the SWAT Model across a Large Contrasted Watershed Y. Grusson et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001491
100. 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
101. Elements of a flexible approach for conceptual hydrological modeling: 2. Application and experimental insights D. Kavetski & F. Fenicia https://doi.org/10.1029/2011WR010748
102. Exploration of warm-up period in conceptual hydrological modelling K. Kim et al. https://doi.org/10.1016/j.jhydrol.2017.11.015
103. Hydrological modelling of temporally-varying catchments: facets of change and the value of information A. Efstratiadis et al. https://doi.org/10.1080/02626667.2014.982123
104. Simultaneous Calibration of Hydrologic Model Structure and Parameters Using a Blended Model R. Chlumsky et al. https://doi.org/10.1029/2020WR029229
105. Do internal flow measurements improve the calibration of rainfall‐runoff models? J. Lerat et al. https://doi.org/10.1029/2010WR010179