86 citations as recorded by crossref.

1. 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
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6. Toward improved deep learning-based regionalized streamflow modeling : Exploiting the power of basin similarity Y. Xu et al. https://doi.org/10.1016/j.envsoft.2025.106374
7. Evaluation of streamflow estimates for the Rovuma River M. Minihane https://doi.org/10.1016/j.pce.2012.09.003
8. High-resolution hydrometeorological data from a network of headwater catchments in the tropical Andes B. Ochoa-Tocachi et al. https://doi.org/10.1038/sdata.2018.80
9. A mechanistic hydro-epidemiological model of liver fluke risk L. Beltrame et al. https://doi.org/10.1098/rsif.2018.0072
10. Hydrological design in the HELPING decade – inspiring the community to innovate the hydrological design concept S. Fischer et al. https://doi.org/10.1080/02626667.2024.2436634
11. Conceptual Models and Calibration Performance—Investigating Catchment Bias A. Buzacott et al. https://doi.org/10.3390/w11112424
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16. Hydro Genome Mapping: An Approach for the Diagnosis, Evaluation and Improving Prediction Capability of Hydro-Meteorological Models G. Dumedah https://doi.org/10.1007/s11269-019-02336-2
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21. Large-basin hydrological response to climate model outputs: uncertainty caused by internal atmospheric variability A. Gelfan et al. https://doi.org/10.5194/hess-19-2737-2015
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23. Robustness of Process-Based versus Data-Driven Modeling in Changing Climatic Conditions S. O et al. https://doi.org/10.1175/JHM-D-20-0072.1
24. The Data Synergy Effects of Time‐Series Deep Learning Models in Hydrology K. Fang et al. https://doi.org/10.1029/2021WR029583
25. Advancing catchment hydrology to deal with predictions under change U. Ehret et al. https://doi.org/10.5194/hess-18-649-2014
26. Improved Rainfall‐Runoff Calibration for Drying Climate: Choice of Objective Function K. Fowler et al. https://doi.org/10.1029/2017WR022466
27. Quantifying Long‐Term and Event‐Scale Baseflow Effects across the Flood Frequency Curve P. Spellman & V. Webster https://doi.org/10.1111/1752-1688.12852
28. 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
29. 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
30. A bootstrap-based differential split-sample test to assess the transferability of conceptual rainfall-runoff models under past and future climate variability H. Dakhlaoui et al. https://doi.org/10.1016/j.jhydrol.2019.05.056
31. Improving process representation in conceptual hydrological model calibration using climate simulations M. Minville et al. https://doi.org/10.1002/2013WR013857
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33. A global assessment of the timing of extreme rainfall from TRMM and GPM for improving hydrologic design A. Libertino et al. https://doi.org/10.1088/1748-9326/11/5/054003
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36. Many Commonly Used Rainfall‐Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections K. Fowler et al. https://doi.org/10.1029/2019WR025286
37. A framework for testing the ability of models to project climate change and its impacts J. Refsgaard et al. https://doi.org/10.1007/s10584-013-0990-2
38. Grappling with uncertainties in physical climate impact projections of water resources R. Dankers & Z. Kundzewicz https://doi.org/10.1007/s10584-020-02858-4
39. Pitfalls of space-time trading when parametrizing a land use dependent hydrological model L. Oudin & M. Lalonde https://doi.org/10.5802/crgeos.146
40. Physio‐climatic controls on vulnerability of watersheds to climate and land use change across the U. S. A. Deshmukh & R. Singh https://doi.org/10.1002/2016WR019189
41. Improved monthly streamflow prediction using integrated multivariate adaptive regression spline with K-means clustering: implementation of reanalyzed remote sensing data O. Kisi et al. https://doi.org/10.1007/s00477-024-02692-5
42. Comparing flow duration curve and rainfall–runoff modelling for predicting daily runoff in ungauged catchments Y. Zhang et al. https://doi.org/10.1016/j.jhydrol.2015.03.043
43. Hydrological impacts of climate change in gauged and ungauged watersheds of the Olifants basin: a trading-space-for-time approach R. Singh et al. https://doi.org/10.1080/02626667.2013.819431
44. Documentation and validation of climate change perception of an ethnic community of the western Himalaya A. Sharma et al. https://doi.org/10.1007/s10661-020-08512-x
45. The compensating effect of glaciers: Characterizing the relation between interannual streamflow variability and glacier cover M. van Tiel et al. https://doi.org/10.1002/hyp.13603
46. Dependence of rainfall–runoff model performance on calibration conditions under changing climatic conditions A. Jahanshahi et al. https://doi.org/10.1080/02626667.2024.2441325
47. Eco-hydrologic model cascades: Simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates B. Guse et al. https://doi.org/10.1016/j.scitotenv.2015.05.078
48. Regionalization of land‐use impacts on streamflow using a network of paired catchments B. Ochoa‐Tocachi et al. https://doi.org/10.1002/2016WR018596
49. Exploring the Influence of Smallholders' Perceptions Regarding Water Availability on Crop Choice and Water Allocation Through Socio‐Hydrological Modeling L. Kuil et al. https://doi.org/10.1002/2017WR021420
50. Assessing Potential Effects of Climate Change on Highway-Runoff Flows and Loads in Southern New England by Using Planning-Level Space-for-Time Analyses L. Jeznach et al. https://doi.org/10.1177/03611981231155183
51. Streamflow prediction in ungauged catchments through use of catchment classification and deep learning M. He et al. https://doi.org/10.1016/j.jhydrol.2024.131638
52. Spatiotemporal patterns of baseflow metrics for basins draining the Oak Ridges Moraine, southern Ontario, Canada J. Buttle et al. https://doi.org/10.1080/07011784.2014.985511
53. Regional-scale analysis of extreme precipitation from short and fragmented records A. Libertino et al. https://doi.org/10.1016/j.advwatres.2017.12.015
54. Citizen science in hydrology and water resources: opportunities for knowledge generation, ecosystem service management, and sustainable development W. Buytaert et al. https://doi.org/10.3389/feart.2014.00026
55. Panel regressions to estimate low‐flow response to rainfall variability in ungaged basins M. Bassiouni et al. https://doi.org/10.1002/2016WR018718
56. 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
57. 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
58. How Robust Is a Multi-Model Ensemble Mean of Conceptual Hydrological Models to Climate Change? T. Kimizuka & Y. Sawada https://doi.org/10.3390/w14182852
59. Regional Analysis of the Dependence of Peak-Flow Quantiles on Climate with Application to Adjustment to Climate Trends T. Over et al. https://doi.org/10.3390/hydrology12050119
60. A framework estimating cumulative impact of damming on downstream water availability Y. Zhang et al. https://doi.org/10.1016/j.jhydrol.2019.05.061
61. Performance of the LandSoil expert‐based model to map erosion and sedimentation: application to a cultivated catchment in central Belgium V. Cantreul et al. https://doi.org/10.1002/esp.4808
62. Regionalisation of hydrological responses under land-use change and variable data quality S. Visessri & N. McIntyre https://doi.org/10.1080/02626667.2015.1006226
63. The transferability of hydrological models under nonstationary climatic conditions C. Li et al. https://doi.org/10.5194/hess-16-1239-2012
64. Can Remotely Sensed Actual Evapotranspiration Facilitate Hydrological Prediction in Ungauged Regions Without Runoff Calibration? Y. Zhang et al. https://doi.org/10.1029/2019WR026236
65. Hydrologic Modeling, Uncertainty, and Sensitivity in the Okavango Basin: Insights for Scenario Assessment A. Linhoss et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000755
66. The influence of parametric uncertainty on the relationships between HBV model parameters and climatic characteristics M. Osuch et al. https://doi.org/10.1080/02626667.2014.967694
67. How pixel size affects a sediment connectivity index in central Belgium V. Cantreul et al. https://doi.org/10.1002/esp.4295
68. 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
69. Uncertainty in Flow Time-Series Predictions in a Tropical Monsoon-Dominated Catchment in Northern Thailand S. Visessri & N. McIntyre https://doi.org/10.1061/(ASCE)HE.1943-5584.0001407
70. Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review Y. Guo et al. https://doi.org/10.1002/wat2.1487
71. Spatial Persistence of Water Chemistry Patterns Across Flow Conditions in a Mesoscale Agricultural Catchment S. Gu et al. https://doi.org/10.1029/2020WR029053
72. Changes in streamflow statistical structure across the United States due to recent climate change A. Gupta et al. https://doi.org/10.1016/j.jhydrol.2023.129474
73. Towards hydrological model calibration using river level measurements J. Jian et al. https://doi.org/10.1016/j.ejrh.2016.12.085
74. Streamflow elasticity as a function of aridity V. Andréassian et al. https://doi.org/10.5194/hess-30-1865-2026
75. Smiling in the rain: Seven reasons to be positive about uncertainty in hydrological modelling J. Juston et al. https://doi.org/10.1002/hyp.9625
76. Uncertainty quantification in watershed hydrology: Which method to use? A. Gupta & R. Govindaraju https://doi.org/10.1016/j.jhydrol.2022.128749
77. Storage‐discharge characteristics of an active rock glacier catchment in the Innere Ölgrube, Austrian Alps T. Wagner et al. https://doi.org/10.1002/hyp.14210
78. The effect of year-to-year variability of leaf area index on Variable Infiltration Capacity model performance and simulation of runoff Z. Tesemma et al. https://doi.org/10.1016/j.advwatres.2015.07.002
79. Incorporating uncertainty in hydrological predictions for gauged and ungauged basins in southern Africa E. Kapangaziwiri et al. https://doi.org/10.1080/02626667.2012.690881
80. Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement K. Fowler et al. https://doi.org/10.1029/2018WR023989
81. A Whittaker Biome‐Based Framework to Account for the Impact of Climate Change on Catchment Behavior A. Deshmukh & R. Singh https://doi.org/10.1029/2018WR023113
82. Deep learning, explained: Fundamentals, explainability, and bridgeability to process-based modelling S. Razavi https://doi.org/10.1016/j.envsoft.2021.105159
83. Catchment-based water resources modelling and planning of the transboundary Inkisi River in the Congo Basin L. Nkaba et al. https://doi.org/10.1080/02626667.2025.2511806
84. Probabilistic Projections of Anthropogenic Climate Change Impacts on Precipitation for the Mid-Atlantic Region of the United States* L. Ning et al. https://doi.org/10.1175/JCLI-D-11-00565.1
85. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments S. Almeida et al. https://doi.org/10.5194/hess-20-887-2016
86. The sensitivity of water availability to changes in the aridity index and other factors—A probabilistic analysis in the Budyko space L. Gudmundsson et al. https://doi.org/10.1002/2016GL069763