100 citations as recorded by crossref.

1. Lithologic Controls on Parameters of Conceptual Rainfall–Runoff Model and Runoff Characteristics: A Case Study of the Xinanjiang Model X. Meng et al. https://doi.org/10.1061/JHYEFF.HEENG-6027
2. Spatial variability of hydrological processes and model structure diagnostics in a 50 km2catchment H. McMillan et al. https://doi.org/10.1002/hyp.9988
3. Combining a rainfall–runoff model and a regionalization approach for flood and water resource assessment in the western Po Valley, Italy A. Cislaghi et al. https://doi.org/10.1080/02626667.2019.1690656
4. Towards seamless large‐domain parameter estimation for hydrologic models N. Mizukami et al. https://doi.org/10.1002/2017WR020401
5. Probabilistic Description of Streamflow and Active Length Regimes in Rivers N. Durighetto et al. https://doi.org/10.1029/2021WR031344
6. Analysis of the relationships between topographic factors and landslide occurrence and their application to landslide susceptibility mapping: a case study of Mingchukur, Uzbekistan A. Kadirhodjaev et al. https://doi.org/10.1007/s12303-018-0052-x
7. Unsupervised hydrologic classification of rivers: Watershed controls on natural and anthropogenic flow regimes, Alabama, USA S. Praskievicz & C. Luo https://doi.org/10.1002/hyp.13394
8. Watershed classification by remote sensing indices: A fuzzy c-means clustering approach B. Choubin et al. https://doi.org/10.1007/s11629-017-4357-4
9. Catchment similarity concepts for understanding dynamic biogeochemical behaviour of river basins S. Krause et al. https://doi.org/10.1002/hyp.10093
10. Advancing catchment hydrology to deal with predictions under change U. Ehret et al. https://doi.org/10.5194/hess-18-649-2014
11. Baseflow signature behaviour of mountainous catchments around the North China Plain S. Lyu et al. https://doi.org/10.1016/j.jhydrol.2022.127450
12. Solar-based irrigation systems as a game changer to improve agricultural practices in sub-Sahara Africa: A case study from Mali B. Birhanu et al. https://doi.org/10.3389/fsufs.2023.1085335
13. An All-Season Flash Flood Forecasting System for Real-Time Operations P. Broxton et al. https://doi.org/10.1175/BAMS-D-12-00212.1
14. Using flow signatures and catchment similarities to evaluate the E-HYPE multi-basin model across Europe C. Donnelly et al. https://doi.org/10.1080/02626667.2015.1027710
15. 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
16. River Classification as a Geographic Tool in the Age of Big Data and Global Change S. Praskievicz https://doi.org/10.1111/gere.12251
17. A proposed composite Boussinesq equation for estimating baseflow recessions and storage-outflow relationship M. Alattar & T. Troy https://doi.org/10.1016/j.jhydrol.2023.130321
18. Characterizing hydrologic change through catchment classification K. Sawicz et al. https://doi.org/10.5194/hess-18-273-2014
19. Hydrological Partitioning and Subsurface Water Storage in Puna Andean Grasslands Revealed by a Paired Catchment Approach J. Bardales‐Zegarra et al. https://doi.org/10.1002/hyp.70566
20. Analysing spatio-temporal process and parameter dynamics in models to characterise contrasting catchments B. Guse et al. https://doi.org/10.1016/j.jhydrol.2018.12.050
21. Geospatial-based soil variability and hydrological zones of Abha semi-arid mountainous watershed, Saudi Arabia J. Mallick https://doi.org/10.1007/s12517-015-2302-9
22. Large-sample hydrology: a need to balance depth with breadth H. Gupta et al. https://doi.org/10.5194/hess-18-463-2014
23. Groundwater shapes North American river floods W. Berghuijs & L. Slater https://doi.org/10.1088/1748-9326/acbecc
24. Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution P. Troch et al. https://doi.org/10.5194/hess-17-2209-2013
25. Spatial analysis of annual runoff ratios and their variability across the contiguous U.S. H. Chang et al. https://doi.org/10.1016/j.jhydrol.2014.01.066
26. Functional approach to exploring climatic and landscape controls of runoff generation: 1. Behavioral constraints on runoff volume H. Li et al. https://doi.org/10.1002/2014WR016307
27. Quantifying Climate and Catchment Control on Hydrological Drought in the Continental United States G. Konapala & A. Mishra https://doi.org/10.1029/2018WR024620
28. Flood-type trend analysis for alpine catchments A. Sikorska-Senoner & J. Seibert https://doi.org/10.1080/02626667.2020.1749761
29. Effects of different regional climate model resolution and forcing scales on projected hydrologic changes P. Mendoza et al. https://doi.org/10.1016/j.jhydrol.2016.08.010
30. Hydrological regime shifts driven by climate and anthropogenic interference in the Upper Paraná River Basin, Brazil H. Yan https://doi.org/10.1016/j.jsames.2025.105834
31. Hydrological Interpretation of a Statistical Measure of Basin Complexity S. Pande & M. Moayeri https://doi.org/10.1029/2018WR022675
32. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene S. Thompson et al. https://doi.org/10.5194/hess-17-5013-2013
33. Catchment hydrological response and transport are affected differently by precipitation intensity and antecedent wetness J. Knapp et al. https://doi.org/10.5194/hess-29-3673-2025
34. Smart low flow signature metrics for an improved overall performance evaluation of hydrological models M. Pfannerstill et al. https://doi.org/10.1016/j.jhydrol.2013.12.044
35. Evaluating post-processing approaches for monthly and seasonal streamflow forecasts F. Woldemeskel et al. https://doi.org/10.5194/hess-22-6257-2018
36. Impact of vegetation cover on hydro-sedimentary fluxes in the marly badlands of the Southern Alps (Draix-Bléone Critical Zone Observatory, SE France) R. Bunel et al. https://doi.org/10.1016/j.geomorph.2025.109726
37. Monthly Runoff Regime Regionalization Through Dissimilarity-Based Methods M. Qamar et al. https://doi.org/10.1007/s11269-015-1087-7
38. How do hydrologic modeling decisions affect the portrayal of climate change impacts? P. Mendoza et al. https://doi.org/10.1002/hyp.10684
39. Improving the representation of hydrologic processes in Earth System Models M. Clark et al. https://doi.org/10.1002/2015WR017096
40. Affinity propagation approach for catchment classification applied to arid catchments A. Hidayatulloh et al. https://doi.org/10.1016/j.jafrearsci.2021.104374
41. A Nonlinear Local Approximation Approach for Catchment Classification S. Khan & B. Sivakumar https://doi.org/10.3390/e26030218
42. Identifying Hydrologic Regimes and Drivers in Nova Scotia, Canada: Catchment Classification Efforts for a Data-Limited Region L. Johnston et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002200
43. Heterogeneity in Spatiotemporal Variability of High Mountain Asia's Runoff and Its Underlying Mechanisms Y. Zhu et al. https://doi.org/10.1029/2022WR032721
44. On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes F. Maina et al. https://doi.org/10.5194/hess-26-3805-2022
45. What makes Darwinian hydrology "Darwinian"? Asking a different kind of question about landscapes C. Harman & P. Troch https://doi.org/10.5194/hess-18-417-2014
46. Automatic Model Structure Identification for Conceptual Hydrologic Models D. Spieler et al. https://doi.org/10.1029/2019WR027009
47. Ensemble hydrological forecasts for reservoir management of the Shipshaw River catchment using limited data E. Reig et al. https://doi.org/10.1080/07011784.2020.1834880
48. The importance of hydraulic groundwater theory in catchment hydrology: The legacy of Wilfried Brutsaert and Jean-Yves Parlange P. Troch et al. https://doi.org/10.1002/wrcr.20407
49. HESS Opinions: The complementary merits of competing modelling philosophies in hydrology M. Hrachowitz & M. Clark https://doi.org/10.5194/hess-21-3953-2017
50. Effect of climate change and mining on hydrological connectivity of surficial layers in the Athabasca Oil Sands Region M. Kompanizare et al. https://doi.org/10.1002/hyp.13292
51. Understanding Catchments’ Hydrologic Response Similarity of Upper Blue Nile (Abay) basin through catchment classification Z. Tegegn et al. https://doi.org/10.1007/s40808-021-01298-y
52. A multiple hydrograph separation technique for identifying hydrological model structures and an interpretation of dominant process controls on flow duration curves C. Leong & Y. Yokoo https://doi.org/10.1002/hyp.14569
53. A bibliometric analysis and overview of the effectiveness of Nature-based Solutions in catchment scale flood mitigation P. Herath et al. https://doi.org/10.1016/j.nbsj.2025.100235
54. A step toward global-scale applicability and transferability of flow duration curve studies: A flow duration curve review (2000–2020) C. Leong & Y. Yokoo https://doi.org/10.1016/j.jhydrol.2021.126984
55. Scaling, similarity, and the fourth paradigm for hydrology C. Peters-Lidard et al. https://doi.org/10.5194/hess-21-3701-2017
56. A decade of Predictions in Ungauged Basins (PUB)—a review M. Hrachowitz et al. https://doi.org/10.1080/02626667.2013.803183
57. Hunting for Information in Streamflow Signatures to Improve Modelled Drainage R. Schneider et al. https://doi.org/10.3390/w14010110
58. Simulating flash flood hydrographs and behavior metrics across China: Implications for flash flood management X. Zhai et al. https://doi.org/10.1016/j.scitotenv.2020.142977
59. Use of an Efficient Proxy Solution for the Hillslope‐Storage Boussinesq Problem in Upscaling of Subsurface Stormflow M. Ranjram & J. Craig https://doi.org/10.1029/2020WR029105
60. Flood‐type classification in mountainous catchments using crisp and fuzzy decision trees A. Sikorska et al. https://doi.org/10.1002/2015WR017326
61. A soil column model for predicting the interaction between water table and evapotranspiration M. Maquin et al. https://doi.org/10.1002/2016WR020183
62. Machine learning based identification of dominant controls on runoff dynamics H. Oppel & A. Schumann https://doi.org/10.1002/hyp.13740
63. Rapid mapping of global flood precursors and impacts using novel five-day GRACE solutions A. Rateb et al. https://doi.org/10.1038/s41598-024-64491-w
64. Flood predictions from metrics to classes by multiple machine learning algorithms coupling with clustering-deduced membership degree X. Zhai et al. https://doi.org/10.1007/s11442-026-2442-8
65. An argument-driven classification and comparison of reservoir operation optimization methods B. Dobson et al. https://doi.org/10.1016/j.advwatres.2019.04.012
66. On the selection of precipitation products for the regionalisation of hydrological model parameters O. Baez-Villanueva et al. https://doi.org/10.5194/hess-25-5805-2021
67. Coevolution of volcanic catchments in Japan T. Yoshida & P. Troch https://doi.org/10.5194/hess-20-1133-2016
68. On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe A. Tuel et al. https://doi.org/10.5194/hess-26-2649-2022
69. Upscaling hydrological processes and land management change impacts using a metamodeling procedure C. Fraser et al. https://doi.org/10.1002/wrcr.20432
70. A Hydrologic Functional Approach for Improving Large‐Sample Hydrology Performance in Poorly Gauged Regions J. Janssen & A. Ameli https://doi.org/10.1029/2021WR030263
71. A methodology to estimate flow duration curves at partially ungauged basins E. Ridolfi et al. https://doi.org/10.5194/hess-24-2043-2020
72. Insights on expected streamflow response to land-cover restoration P. James Dennedy-Frank & S. Gorelick https://doi.org/10.1016/j.jhydrol.2020.125121
73. Exploring the physical controls of regional patterns of flow duration curves – Part 3: A catchment classification system based on regime curve indicators E. Coopersmith et al. https://doi.org/10.5194/hess-16-4467-2012
74. Typecasting catchments: Classification, directionality, and the pursuit of universality T. Smith et al. https://doi.org/10.1016/j.advwatres.2017.12.020
75. Parameter regionalization of large-scale distributed rainfall–runoff models using a conditional probability method T. Sayama et al. https://doi.org/10.1186/s40645-025-00691-w
76. Recent decreasing precipitation and snowmelt reduce the floods around the Chinese Tianshan Mountains X. Li et al. https://doi.org/10.1016/j.scitotenv.2023.167324
77. On the structural limitations of recursive digital filters for base flow estimation C. Su et al. https://doi.org/10.1002/2015WR018067
78. A hybrid‐3D hillslope hydrological model for use in Earth system models P. Hazenberg et al. https://doi.org/10.1002/2014WR016842
79. A ranking system for comparing models' performance combining multiple statistical criteria and scenarios: The case of reference evapotranspiration models V. Aschonitis et al. https://doi.org/10.1016/j.envsoft.2019.01.005
80. Process-based karst modelling to relate hydrodynamic and hydrochemical characteristics to system properties A. Hartmann et al. https://doi.org/10.5194/hess-17-3305-2013
81. Exploring the physical controls of regional patterns of flow duration curves – Part 4: A synthesis of empirical analysis, process modeling and catchment classification M. Yaeger et al. https://doi.org/10.5194/hess-16-4483-2012
82. Karst water resources in a changing world: Review of hydrological modeling approaches A. Hartmann et al. https://doi.org/10.1002/2013RG000443
83. Isotopic response of run‐off to forest disturbance in small mountain catchments Y. Vystavna et al. https://doi.org/10.1002/hyp.13280
84. Catchment Classification Framework in Hydrology: Challenges and Directions B. Sivakumar et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000837
85. Climatic signatures in regulated flow regimes across the Central and Eastern United States M. Ferrazzi et al. https://doi.org/10.1016/j.ejrh.2021.100809
86. Climate and landscape jointly control European streamflow behaviour J. Rudlang et al. https://doi.org/10.5194/hess-30-4481-2026
87. Regional climate change projections of streamflow characteristics in the Northeast and Midwest U.S. E. Demaria et al. https://doi.org/10.1016/j.ejrh.2015.11.007
88. Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data C. O'Sullivan et al. https://doi.org/10.1016/j.scitotenv.2021.151139
89. Interpreting characteristic drainage timescale variability across Kilombero Valley, Tanzania S. Lyon et al. https://doi.org/10.1002/hyp.10304
90. GIS-based hydrological zones and soil geo-database of Ethiopia B. Berhanu et al. https://doi.org/10.1016/j.catena.2012.12.007
91. Optimizing hydrological consistency by incorporating hydrological signatures into model calibration objectives M. Shafii & B. Tolson https://doi.org/10.1002/2014WR016520
92. Predicting hydrologic response through a hierarchical catchment knowledgebase: A Bayes empirical Bayes approach T. Smith et al. https://doi.org/10.1002/2013WR015079
93. Algorithm for Delineating and Extracting Hillslopes and Hillslope Width Functions from Gridded Elevation Data P. Noël et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000783
94. Variations in Baseflow Recession Curves as a Function of Land-Use Change in the Keduang Watershed, Wonogiri Regency, Jawa Tengah Province, Indonesia B. Latuamury & M. Talaohu https://doi.org/10.21523/gcj5.19030202
95. Are streamflow recession characteristics really characteristic? M. Stoelzle et al. https://doi.org/10.5194/hess-17-817-2013
96. Drivers influencing streamflow changes in the Upper Turia basin, Spain G. Salmoral et al. https://doi.org/10.1016/j.scitotenv.2014.07.041
97. Incorporating student-centered approaches into catchment hydrology teaching: a review and synthesis S. Thompson et al. https://doi.org/10.5194/hess-16-3263-2012
98. Decoding parameter sensitivities across scales: a Wavelet–Sobol framework for hydrological modelling V. Sai Suswara et al. https://doi.org/10.1016/j.jhydrol.2026.135482
99. Hillslope-storage Boussinesq model for simulating subsurface water storage dynamics in scantily-gauged catchments S. Sahoo et al. https://doi.org/10.1016/j.advwatres.2018.08.016
100. Controls on spatial and temporal variability in streamflow and hydrochemistry in a glacierized catchment M. Engel et al. https://doi.org/10.5194/hess-23-2041-2019