130 citations as recorded by crossref.

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12. Enhancing the hydrologic system differential response method for flood forecasting correction X. Zhang et al. 10.1016/j.jhydrol.2020.125793
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16. Perceptual perplexity and parameter parsimony K. Beven & N. Chappell 10.1002/wat2.1530
17. Panta Rhei 2013–2015: global perspectives on hydrology, society and change H. McMillan et al. 10.1080/02626667.2016.1159308
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23. Assessment of bottom-up satellite rainfall products on estimating river discharge and hydrologic signatures in Brazilian catchments A. Almagro et al. 10.1016/j.jhydrol.2021.126897
24. Explanation and Probabilistic Prediction of Hydrological Signatures with Statistical Boosting Algorithms H. Tyralis et al. 10.3390/rs13030333
25. An Empirical Reevaluation of Streamflow Recession Analysis at the Continental Scale A. Tashie et al. 10.1029/2019WR025448
26. Impact of Dataset Size on the Signature-Based Calibration of a Hydrological Model S. Mohammed et al. 10.3390/w13070970
27. Using Machine Learning to Identify Hydrologic Signatures With an Encoder–Decoder Framework T. Botterill & H. McMillan 10.1029/2022WR033091
28. Uncertainty in hydrological signatures for gauged and ungauged catchments I. Westerberg et al. 10.1002/2015WR017635
29. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Empirical Analysis of Fundamental Properties F. Fenicia et al. 10.1002/2017WR021616
30. 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
31. Understanding the Information Content in the Hierarchy of Model Development Decisions: Learning From Data S. Gharari et al. 10.1029/2020WR027948
32. Tradeoff between economic and environmental costs and benefits of hydropower production at run-of-river-diversion schemes under different environmental flows scenarios M. Bejarano et al. 10.1016/j.jhydrol.2019.03.048
33. Informing hydrological models of poorly gauged river catchments – A parameter regionalization and calibration approach C. Kittel et al. 10.1016/j.jhydrol.2020.124999
34. Regional Modeling of Long-Term and Annual Flow Duration Curves: Reliability for Information Transfer with Evolutionary Polynomial Regression V. Costa & W. Fernandes 10.1061/(ASCE)HE.1943-5584.0002051
35. Advancing traditional strategies for testing hydrological model fitness in a changing climate A. Todorović et al. 10.1080/02626667.2022.2104646
36. Control of climate and physiography on runoff response behavior through use of catchment classification and machine learning S. Du et al. 10.1016/j.scitotenv.2023.166422
37. Using Functional Data Analysis to Calibrate and Evaluate Hydrological Model Performance S. Larabi et al. 10.1061/(ASCE)HE.1943-5584.0001669
38. Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review Y. Guo et al. 10.1002/wat2.1487
39. The Treatment of Uncertainty in Hydrometric Observations: A Probabilistic Description of Streamflow Records D. de Oliveira & J. Vrugt 10.1029/2022WR032263
40. Nonlinear control of climate, hydrology, and topography on streamflow response through the use of interpretable machine learning across the contiguous United States Y. Wu & N. Li 10.2166/wcc.2023.279
41. A hybrid time- and signature-domain Bayesian inference framework for calibration of hydrological models: a case study in the Ren River basin in China S. Liu et al. 10.1007/s00477-022-02282-3
42. Accelerating advances in continental domain hydrologic modeling S. Archfield et al. 10.1002/2015WR017498
43. Estimation of streamflow recession parameters: New insights from an analytic streamflow distribution model A. Santos et al. 10.1002/hyp.13425
44. Assessment of water availability vulnerability in the Cerrado D. Althoff et al. 10.1007/s13201-021-01521-2
45. How is Baseflow Index (BFI) impacted by water resource management practices? J. Bloomfield et al. 10.5194/hess-25-5355-2021
46. Uni- and multivariate bias adjustment of climate model simulations in Nordic catchments: Effects on hydrological signatures relevant for water resources management in a changing climate F. Tootoonchi et al. 10.1016/j.jhydrol.2023.129807
47. CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain G. Coxon et al. 10.5194/essd-12-2459-2020
48. Modeling and Forecasting Vibrio Parahaemolyticus Concentrations in Oysters P. Namadi & Z. Deng 10.1016/j.watres.2020.116638
49. A Simple Approach to Account for Stage–Discharge Uncertainty in Hydrological Modelling R. Vázquez & H. Hampel 10.3390/w14071045
50. Large Scale Evaluation of Relationships Between Hydrologic Signatures and Processes H. McMillan et al. 10.1029/2021WR031751
51. 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
52. Linking hydrologic signatures to hydrologic processes: A review H. McMillan 10.1002/hyp.13632
53. Catchment Functioning Under Prolonged Drought Stress: Tracer‐Aided Ecohydrological Modeling in an Intensively Managed Agricultural Catchment X. Yang et al. 10.1029/2020WR029094
54. Equifinality and Flux Mapping: A New Approach to Model Evaluation and Process Representation Under Uncertainty S. Khatami et al. 10.1029/2018WR023750
55. CABra: a novel large-sample dataset for Brazilian catchments A. Almagro et al. 10.5194/hess-25-3105-2021
56. Probabilistic Predictions of Ecologically Relevant Hydrologic Indices Using a Hydrological Model J. Hernandez‐Suarez & A. Nejadhashemi 10.1029/2021WR031104
57. Enhancing urban runoff modelling using water stable isotopes and ages in complex catchments A. Smith et al. 10.1002/hyp.14814
58. High-resolution hydrometeorological data from a network of headwater catchments in the tropical Andes B. Ochoa-Tocachi et al. 10.1038/sdata.2018.80
59. The 3DNet-Catch hydrologic model: Development and evaluation A. Todorović et al. 10.1016/j.jhydrol.2018.10.040
60. Trade-offs between parameter constraints and model realism: a case study F. Jehn et al. 10.1038/s41598-019-46963-6
61. Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica S. Arciniega-Esparza et al. 10.5194/hess-26-975-2022
62. How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications H. McMillan et al. 10.1002/2016WR020328
63. On the choice of calibration metrics for “high-flow” estimation using hydrologic models N. Mizukami et al. 10.5194/hess-23-2601-2019
64. Global evaluation of runoff from 10 state-of-the-art hydrological models H. Beck et al. 10.5194/hess-21-2881-2017
65. CAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in Brazil V. Chagas et al. 10.5194/essd-12-2075-2020
66. A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin, East China S. Pan et al. 10.1080/02626667.2017.1388917
67. Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity G. Papacharalampous et al. 10.1016/j.scitotenv.2020.144612
68. Streamflow uncertainty due to the limited sensitivity of controls at hydrometric stations I. Horner et al. 10.1002/hyp.14497
69. An improved method to estimate the rate of change of streamflow recession and basin synthetic recession parameters from hydrographs M. Gao et al. 10.1016/j.jhydrol.2021.127254
70. Evaluation of Satellite Precipitation Products for Estimation of Floods in Data-Scarce Environment M. Masood et al. 10.1155/2023/1685720
71. What control the spatial patterns and predictions of runoff response over the contiguous USA? S. Jiang et al. 10.1007/s11442-024-2249-4
72. Model averaging versus model selection: estimating design floods with uncertain river flow data K. Okoli et al. 10.1080/02626667.2018.1546389
73. Coupling SWAT and LSTM for Improving Daily Streamflow Simulation in a Humid and Semi-humid River Basin Z. Mei et al. 10.1007/s11269-024-03975-w
74. A new fractal-theory-based criterion for hydrological model calibration Z. Bai et al. 10.5194/hess-25-3675-2021
75. Evaluation of Satellite Precipitation Products in Simulating Streamflow in a Humid Tropical Catchment of India Using a Semi-Distributed Hydrological Model T. Sharannya et al. 10.3390/w12092400
76. What Are the Key Drivers Controlling the Quality of Seasonal Streamflow Forecasts? I. Pechlivanidis et al. 10.1029/2019WR026987
77. Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network M. Gauch et al. 10.5194/hess-25-2045-2021
78. The Impact of the Uncertain Input Data of Multi-Purpose Reservoir Volumes under Hydrological Extremes S. Paseka & D. Marton 10.3390/w13101389
79. A Ranking of Hydrological Signatures Based on Their Predictability in Space N. Addor et al. 10.1029/2018WR022606
80. Characterizing Watersheds to Support Land-use Planning in Indonesia: A Case Study of Brantas Tropical Watershed B. Wiwoho et al. 10.1016/j.ecohyd.2023.06.001
81. A comprehensive intercomparison study between a lumped and a fully distributed hydrological model across a set of 50 catchments in the United Kingdom S. Sinha et al. 10.1002/hyp.14544
82. LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe C. Klingler et al. 10.5194/essd-13-4529-2021
83. Event‐Based Recession Analysis for Estimation of Basin‐Wide Characteristic Drainage Timescale and Groundwater Storage Trends M. Hameed et al. 10.1029/2023WR035829
84. Evaluation of hydrological models at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures A. Gupta et al. 10.1016/j.jhydrol.2024.131774
85. Assessing Hydrograph Similarity and Rare Runoff Dynamics by Cross Recurrence Plots D. Wendi et al. 10.1029/2018WR024111
86. Hourly rainfall-runoff modelling by combining the conceptual model with machine learning models in mostly karst Ljubljanica River catchment in Slovenia C. Sezen & M. Šraj 10.1007/s00477-023-02607-w
87. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Theory and Comparison to Existing Applications D. Kavetski et al. 10.1002/2017WR020528
88. Including Regional Knowledge Improves Baseflow Signature Predictions in Large Sample Hydrology S. Gnann et al. 10.1029/2020WR028354
89. A note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall–runoff modeling F. Kratzert et al. 10.5194/hess-25-2685-2021
90. Uncertainty Impact on Water Management Analysis of Open Water Reservoir D. Marton & S. Paseka 10.3390/environments4010010
91. Revisit hydrological modeling in ungauged catchments comparing regionalization, satellite observations, and machine learning approaches R. Dasgupta et al. 10.1016/j.hydres.2023.11.001
92. 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
93. Shyft v4.8: a framework for uncertainty assessment and distributed hydrologic modeling for operational hydrology J. Burkhart et al. 10.5194/gmd-14-821-2021
94. Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models K. Fowler et al. 10.1002/2015WR018068
95. HESS Opinions: The complementary merits of competing modelling philosophies in hydrology M. Hrachowitz & M. Clark 10.5194/hess-21-3953-2017
96. Models of everywhere revisited: A technological perspective G. Blair et al. 10.1016/j.envsoft.2019.104521
97. Propagation of rating curve uncertainty in design flood estimation G. Steinbakk et al. 10.1002/2015WR018516
98. Estimating the Optimal Velocity Measurement Time in Rivers’ Flow Measurements: An Uncertainty Approach R. Clasing & E. Muñoz 10.3390/w10081010
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100. A review of hydrologic signatures and their applications H. McMillan 10.1002/wat2.1499
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102. Embracing equifinality with efficiency: Limits of Acceptability sampling using the DREAM(LOA) algorithm J. Vrugt & K. Beven 10.1016/j.jhydrol.2018.02.026
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106. Snow hydrology signatures for model identification within a limits‐of‐acceptability approach B. Schaefli 10.1002/hyp.10972
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108. Simulation of the cumulative hydrological response to green infrastructure P. Avellaneda et al. 10.1002/2016WR019836
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111. Shift Happens! Adjusting Stage‐Discharge Rating Curves to Morphological Changes at Known Times V. Mansanarez et al. 10.1029/2018WR023389
112. Unpacking some of the linkages between uncertainties in observational data and the simulation of different hydrological processes using the Pitman model in the data scarce Zambezi River basin D. Hughes & F. Farinosi 10.1002/hyp.14141
113. Global Runoff Signatures Changes and Their Response to Atmospheric Environment, GRACE Water Storage, and Dams S. Yan et al. 10.3390/rs13204084
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119. The application of CHIRPS-based Pitman modelling in South Africa J. Kibii & J. Du Plessis 10.1016/j.pce.2023.103475
120. Using hydrological and climatic catchment clusters to explore drivers of catchment behavior F. Jehn et al. 10.5194/hess-24-1081-2020
121. Flow Prediction in Ungauged Catchments Using Probabilistic Random Forests Regionalization and New Statistical Adequacy Tests C. Prieto et al. 10.1029/2018WR023254
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123. Improving performance of bucket-type hydrological models in high latitudes with multi-model combination methods: Can we wring water from a stone? A. Todorović et al. 10.1016/j.jhydrol.2024.130829
124. Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships M. Eddy et al. 10.1002/eco.2387
125. The role of previously glaciated landscapes in spatiotemporal variability of streamflow in snow-dominated watersheds: British Columbia, Canada X. Chen et al. 10.1016/j.ejrh.2023.101478
126. Multi-Criteria Process-Based Calibration Using Functional Data Analysis to Improve Hydrological Model Realism S. Larabi et al. 10.1007/s11269-017-1803-6
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129. Deriving hydrological signatures from soil moisture data F. Branger & H. McMillan 10.1002/hyp.13645
130. Impact of Stage Measurement Errors on Streamflow Uncertainty I. Horner et al. 10.1002/2017WR022039