459 citations as recorded by crossref.

1. Measuring discharge in a river with tidal bores by use of the coastal acoustic tomography system X. Zhu et al. https://doi.org/10.1016/j.ecss.2012.03.022
2. Temporal variability in stage–discharge relationships J. Guerrero et al. https://doi.org/10.1016/j.jhydrol.2012.04.031
3. Flood drivers and trends: a case study of the Geul River catchment (the Netherlands) over the past half century A. Tsiokanos et al. https://doi.org/10.5194/hess-28-3327-2024
4. Investigation of Data-Driven Rating Curve (DDRC) Approach B. Bhandari et al. https://doi.org/10.3390/w15030604
5. Data for dynamics analysis of riverine dissolved organic in watersheds F. Rizinjirabake et al. https://doi.org/10.1016/j.dib.2018.08.171
6. 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
7. Estimating velocity distribution and flood discharge at river bridges using entropy theory – insights from computational fluid dynamics flow fields F. Bahmanpouri et al. https://doi.org/10.5194/hess-28-3717-2024
8. A review of mass flux monitoring and estimation methods for biogeochemical interface processes in watersheds Y. Lu et al. https://doi.org/10.1007/s11442-020-1760-5
9. 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
10. Development and evaluation of a global dynamical wetlands extent scheme T. Stacke & S. Hagemann https://doi.org/10.5194/hess-16-2915-2012
11. How Reliable Are ANN, ANFIS, and SVM Techniques for Predicting Longitudinal Dispersion Coefficient in Natural Rivers? R. Noori et al. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001062
12. Dimensionless Stage-Discharge Relationship for a Non-Linear Water Reservoir: Theory and Experiments G. Baiamonte https://doi.org/10.3390/hydrology7020023
13. Integrating remotely sensed surface water extent into continental scale hydrology B. Revilla-Romero et al. https://doi.org/10.1016/j.jhydrol.2016.10.041
14. Assessment and attribution of predictive hydrologic uncertainty in operational short-to-medium range ensemble streamflow forecasting S. Kim & D. Seo https://doi.org/10.1016/j.jhydrol.2026.135893
15. Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors B. Renard et al. https://doi.org/10.1029/2009WR008328
16. Benchmarking quantitative precipitation estimation by conceptual rainfall‐runoff modeling M. Heistermann & D. Kneis https://doi.org/10.1029/2010WR009153
17. Effects of sediment transport on flood hazards: Lessons learned and remaining challenges D. Vázquez-Tarrío et al. https://doi.org/10.1016/j.geomorph.2023.108976
18. Development of probabilistic inundation mapping for dam failure induced floods C. Tsai et al. https://doi.org/10.1007/s00477-018-1636-8
19. Can satellite land surface temperature data be used similarly to river discharge measurements for distributed hydrological model calibration? C. Corbari et al. https://doi.org/10.1080/02626667.2013.866709
20. Uncertainty analysis of radar rainfall estimates over two different climates in Iran E. Ghaemi et al. https://doi.org/10.1080/01431161.2017.1335909
21. Automated Real-Time Streamflow Acquisition in a Mountainous River Using Acoustic Tomography K. Kawanisi et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001604
22. A flood inundation forecast of Hurricane Harvey using a continental-scale 2D hydrodynamic model O. Wing et al. https://doi.org/10.1016/j.hydroa.2019.100039
23. Assessing the quality of the streamflow record for a long-term reference hydrometric station: Bow River at Banff P. Whitfield & J. Pomeroy https://doi.org/10.1080/07011784.2017.1399086
24. Exploring the optimal experimental setup for surface flow velocity measurements using PTV S. Dal Sasso et al. https://doi.org/10.1007/s10661-018-6848-3
25. River Plume Liftoff Dynamics and Surface Expressions R. Branch et al. https://doi.org/10.1029/2019WR026475
26. Uncertainty quantification in watershed hydrology: Which method to use? A. Gupta & R. Govindaraju https://doi.org/10.1016/j.jhydrol.2022.128749
27. Assessing the value of high‐resolution isotope tracer data in the stepwise development of a lumped conceptual rainfall–runoff model C. Birkel et al. https://doi.org/10.1002/hyp.7763
28. Water balance of selected floodplain lake basins in the Middle Bug River valley J. Dawidek & B. Ferencz https://doi.org/10.5194/hess-18-1457-2014
29. Probabilistic flood hazard mapping: effects of uncertain boundary conditions A. Domeneghetti et al. https://doi.org/10.5194/hess-17-3127-2013
30. Implications of model selection: a comparison of publicly available, conterminous US-extent hydrologic component estimates S. Saxe et al. https://doi.org/10.5194/hess-25-1529-2021
31. Multi‐model and multi‐sensor estimations of evapotranspiration over the Volta Basin, West Africa S. Andam‐Akorful et al. https://doi.org/10.1002/joc.4198
32. Glacial and geomorphic effects of a supraglacial lake drainage and outburst event, Everest region, Nepal Himalaya E. Miles et al. https://doi.org/10.5194/tc-12-3891-2018
33. Flood modelling: parameterisation and inflow uncertainty M. Mukolwe et al. https://doi.org/10.1680/wama.12.00087
34. Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments N. Dogulu et al. https://doi.org/10.5194/hess-19-3181-2015
35. Dynamic rating curve assessment for hydrometric stations and computation of the associated uncertainties: Quality and station management indicators T. Morlot et al. https://doi.org/10.1016/j.jhydrol.2014.05.007
36. Decoding the Hysteretic Behaviour of Hydraulic Variables in Lowland Rivers Using Multivariate Monitoring Approaches M. Muste et al. https://doi.org/10.1002/hyp.70008
37. A dip-corrected discharge estimation method for a river system A. Handique et al. https://doi.org/10.1016/j.flowmeasinst.2022.102222
38. Time-Lapse Photography: Low-Cost, Low-Tech Alternative for Monitoring Flow Depth G. Schoener https://doi.org/10.1061/(ASCE)HE.1943-5584.0001616
39. Calibrating a hydrological model in stage space to account for rating curve uncertainties: general framework and key challenges A. Sikorska & B. Renard https://doi.org/10.1016/j.advwatres.2017.04.011
40. Stream discharge characteristics through urbanization gradient in Danshui River, Taiwan: perspectives from observation and simulation J. Huang et al. https://doi.org/10.1007/s10661-011-2374-2
41. Predicting fecal coliform using the interval-to-interval approach and SWAT in the Miyun watershed, China J. Bai et al. https://doi.org/10.1007/s11356-017-9101-7
42. Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study P. Bauer-Gottwein et al. https://doi.org/10.5194/hess-19-1469-2015
43. Enhanced flood mapping using synthetic aperture radar (SAR) images, hydraulic modelling, and social media: A case study of Hurricane Harvey (Houston, TX) V. Scotti et al. https://doi.org/10.1111/jfr3.12647
44. Assessment of a numerical model to reproduce event‐scale erosion and deposition distributions in a braided river R. Williams et al. https://doi.org/10.1002/2015WR018491
45. Quantifying the natural flood management potential of leaky dams in upland catchments, Part I: A data-based modelling approach Z. van Leeuwen et al. https://doi.org/10.1016/j.jhydrol.2023.130448
46. Design flood estimation using extreme Gradient Boosting-based on Bayesian optimization D. Jarajapu et al. https://doi.org/10.1016/j.jhydrol.2022.128341
47. 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
48. Improving Operational Short- to Medium-Range (SR2MR) Streamflow Forecasts in the Upper Zambezi Basin and Its Sub-Basins Using Variational Ensemble Forecasting R. Valdés-Pineda et al. https://doi.org/10.3390/hydrology8040188
49. Large-Scale Hydrological Modeling for Calculating Water Stress Indices: Implications of Improved Spatiotemporal Resolution, Surface-Groundwater Differentiation, and Uncertainty Characterization L. Scherer et al. https://doi.org/10.1021/acs.est.5b00429
50. Hydrological response to changing climate conditions: Spatial streamflow variability in the boreal region C. Teutschbein et al. https://doi.org/10.1002/2015WR017337
51. Effect of streamflow measurement error on flood frequency estimation N. Velásquez & W. Krajewski https://doi.org/10.1007/s00477-024-02707-1
52. Considering rating curve uncertainty in water level predictions A. Sikorska et al. https://doi.org/10.5194/hess-17-4415-2013
53. Hybrid Modeling of a Gauging Station Rating Curve Ø. Pedersen & N. Rüther https://doi.org/10.1016/j.proeng.2016.07.535
54. Revisiting hysteresis of flow variables in monitoring unsteady streamflows M. Muste et al. https://doi.org/10.1080/00221686.2020.1786742
55. Application Of Boundary Layer Theory In Open Channel Flume Design W. Wei https://doi.org/10.21307/ijssis-2017-860
56. The great 1983 floods in South American large rivers: a continental hydrological modelling approach A. Fleischmann et al. https://doi.org/10.1080/02626667.2020.1747622
57. Ecosystem services (ES) provided by ditches in a desert agricultural valley F. Cital et al. https://doi.org/10.1016/j.ecoleng.2021.106462
58. Rationale for Monitoring Discharge on the Ground B. Fekete et al. https://doi.org/10.1175/JHM-D-11-0126.1
59. Effect of input data in hydraulic modeling for flood warning systems N. Lamichhane & S. Sharma https://doi.org/10.1080/02626667.2018.1464166
60. Analyse de l’opportunité d’application des méthodes d’estimation des débits des rivières par courbe de tarage et capteur doppler immergé fixe L. Mballa E. & S. Bennis https://doi.org/10.1139/cjce-2013-0509
61. Enhanced river regulation following dam reoperation: Impacts on flow regime, sediment transport, and planform adjustment in a plateau river basin in the lower Ganga plains A. Ghorai & K. Ghosh https://doi.org/10.1016/j.catena.2024.107834
62. Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches G. Di Baldassarre et al. https://doi.org/10.1080/02626661003683389
63. Calibration of hydrological models using flow-duration curves I. Westerberg et al. https://doi.org/10.5194/hess-15-2205-2011
64. Scaling, similarity, and the fourth paradigm for hydrology C. Peters-Lidard et al. https://doi.org/10.5194/hess-21-3701-2017
65. Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality H. McMillan et al. https://doi.org/10.1002/hyp.9384
66. Uncertainty in stage–discharge rating curves: application to Australian Hydrologic Reference Stations data T. McMahon & M. Peel https://doi.org/10.1080/02626667.2019.1577555
67. Effects of Green–Gray–Blue Infrastructure Adjustments on Urban Drainage Performance: Time Lag and H–Q Curve Regulation Y. Yu et al. https://doi.org/10.3390/land14020419
68. A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non‐Gaussian errors G. Schoups & J. Vrugt https://doi.org/10.1029/2009WR008933
69. From Surface Flow Velocity Measurements to Discharge Assessment by the Entropy Theory T. Moramarco et al. https://doi.org/10.3390/w9020120
70. Correction of River Bathymetry Parameters Using the Stage–Discharge Rating Curve X. Zhou et al. https://doi.org/10.1029/2021WR031226
71. Flood frequency analysis based on simulated peak discharges B. Saghafian et al. https://doi.org/10.1007/s11069-013-0925-2
72. On the calibration of hydrological models in ungauged basins: A framework for integrating hard and soft hydrological information H. Winsemius et al. https://doi.org/10.1029/2009WR007706
73. Flooding in the Mekong Delta: the impact of dyke systems on downstream hydrodynamics V. Thanh et al. https://doi.org/10.5194/hess-24-189-2020
74. Reliability of flood marks and practical relevance for flood hazard assessment in southwestern Germany A. Bösmeier et al. https://doi.org/10.5194/nhess-22-2963-2022
75. Statistical filtering of river survey and streamflow data for improving At-A-Station hydraulic geometry relations S. Afshari et al. https://doi.org/10.1016/j.jhydrol.2017.01.038
76. Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events E. Acuña Espinoza et al. https://doi.org/10.5194/hess-29-1277-2025
77. Uncertainty quantification of floodplain friction in hydrodynamic models G. Dalledonne et al. https://doi.org/10.5194/hess-23-3373-2019
78. Auto-calibration of HEC-HMS Model for Historic Flood Event under Rating Curve Uncertainty. Case Study: Allala Watershed, Algeria A. Kastali et al. https://doi.org/10.1007/s12205-021-1051-4
79. Recent trends and variability in river discharge across northern Canada S. Déry et al. https://doi.org/10.5194/hess-20-4801-2016
80. Hydrograph recession extraction algorithm (HYDRA): Minimizing influence of stage uncertainty in identification of recession events B. Thomas https://doi.org/10.1016/j.advwatres.2021.103937
81. Identifying Stagnation Zones and Reverse Flow Caused by River‐Aquifer Interaction: An Approach Based on Polynomial Chaos Expansions P. Merchán‐Rivera et al. https://doi.org/10.1029/2021WR029824
82. Integrating Water Observation from Space Product and Time-Series Flow Data for Modeling Spatio-Temporal Flood Inundation Dynamics C. Huang et al. https://doi.org/10.3390/rs11212535
83. Effect of observation errors on the uncertainty of design floods G. Di Baldassarre et al. https://doi.org/10.1016/j.pce.2011.05.001
84. Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors B. Revilla-Romero et al. https://doi.org/10.5194/hess-18-4467-2014
85. Evaluation of the storage and evapotranspiration terms of the water budget for an agricultural watershed using local and remote-sensing measurements L. Hoeltgebaum & N. Dias https://doi.org/10.1016/j.agrformet.2023.109615
86. Environmental flow assessment, evaluation, and suggestions for dying riverine ecosystem of the transboundary Amudarya River, Central Asia R. Mahmood et al. https://doi.org/10.1016/j.ecolind.2023.111419
87. Infilling Missing Data in Hydrology: Solutions Using Satellite Radar Altimetry and Multiple Imputation for Data-Sparse Regions I. Ekeu-wei et al. https://doi.org/10.3390/w10101483
88. River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling A. Tarpanelli et al. https://doi.org/10.3390/rs5094145
89. Sequential data assimilation for real-time probabilistic flood inundation mapping K. Jafarzadegan et al. https://doi.org/10.5194/hess-25-4995-2021
90. The influence of wind farm development on the hydrochemistry and ecology of an upland stream K. Millidine et al. https://doi.org/10.1007/s10661-015-4750-9
91. Large observational bias on discharge in the Indus River since 1970s J. Liu et al. https://doi.org/10.1038/s41598-018-35600-3
92. Simulating historical flood events at the continental scale: observational validation of a large-scale hydrodynamic model O. Wing et al. https://doi.org/10.5194/nhess-21-559-2021
93. Effects of uncertain asset stock data on the assessment of climate change risks: A case study of bridge scour in the UK H. Dikanski et al. https://doi.org/10.1016/j.strusafe.2017.10.008
94. Identifying robust large-scale flood risk mitigation strategies: A quasi-2D hydraulic model as a tool for the Po river A. Castellarin et al. https://doi.org/10.1016/j.pce.2011.02.008
95. Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework M. Raleigh et al. https://doi.org/10.5194/hess-19-3153-2015
96. Estimating mountain basin‐mean precipitation from streamflow using Bayesian inference B. Henn et al. https://doi.org/10.1002/2014WR016736
97. Multi‐Level Monte Carlo Models for Flood Inundation Uncertainty Quantification G. Aitken et al. https://doi.org/10.1029/2022WR032599
98. Automatic Model Structure Identification for Conceptual Hydrologic Models D. Spieler et al. https://doi.org/10.1029/2019WR027009
99. Comparison of artificial neural networks and reservoir models for simulating karst spring discharge on five test sites in the Alpine and Mediterranean regions G. Cinkus et al. https://doi.org/10.5194/hess-27-1961-2023
100. 2D Finite Element Inundation Modelling in Anabranching Channels with Sparse Data: Examination of Uncertainties J. Sanyal et al. https://doi.org/10.1007/s11269-014-0619-x
101. Assessment of water resources to support the development of irrigation in northwest Cambodia: a water budget approach R. Valois et al. https://doi.org/10.1080/02626667.2017.1351030
102. Modeling the impacts of land use and land cover changes on streamflow and sediment yield with the SWAT Model in Migori River Watershed, Lake Victoria Basin Region, Kenya S. Opiyo https://doi.org/10.1080/19376812.2024.2324279
103. Hydrological modelling in a changing world M. Peel & G. Blöschl https://doi.org/10.1177/0309133311402550
104. Testing the use of single- and multi-mission satellite altimetry for the calibration of hydraulic models A. Domeneghetti et al. https://doi.org/10.1016/j.advwatres.2021.103887
105. A LISFLOOD-FP hydraulic model of the middle reach of the Congo F. O'Loughlin et al. https://doi.org/10.1016/j.jhydrol.2019.124203
106. Stabilization of stage–discharge curves following the establishment of forest plantations: Implications for sediment production R. Pizarro et al. https://doi.org/10.1002/rra.3718
107. Disentangling timing and amplitude errors in streamflow simulations S. Seibert et al. https://doi.org/10.5194/hess-20-3745-2016
108. Climate change impacts—throwing the dice? G. Blöschl & A. Montanari https://doi.org/10.1002/hyp.7574
109. A review and uncertainty analysis of Lake Urmia's hypsometric relationships S. Sima et al. https://doi.org/10.1016/j.jglr.2023.09.010
110. Filling the gaps: Calibrating a rainfall-runoff model using satellite-derived surface water extent B. Revilla-Romero et al. https://doi.org/10.1016/j.rse.2015.10.022
111. A review of low‐cost space‐borne data for flood modelling: topography, flood extent and water level K. Yan et al. https://doi.org/10.1002/hyp.10449
112. A continuous modelling approach for design flood estimation on sub-daily time scale B. Winter et al. https://doi.org/10.1080/02626667.2019.1593419
113. Application of 2D numerical simulation for rating curve development and inundation area mapping: a case study of monsoon dominated Dwarkeswar river S. Malik & S. Pal https://doi.org/10.1080/15715124.2020.1738447
114. Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis M. Lang et al. https://doi.org/10.1080/02626667.2010.504186
115. Flood risk assessment for Indian sub-continental river basins U. Vegad et al. https://doi.org/10.5194/hess-28-1107-2024
116. Flood Risk Assessments for Small Catchments Under Climate Change—How Can Scotland Improve Its Policy for Enhanced Flood Resilience and Preparedness F. Fileni et al. https://doi.org/10.1111/jfr3.70035
117. Uncertainty analysis of estuarine hydrodynamic models: an evaluation of input data uncertainty in the weeks bay estuary, alabama R. Camacho et al. https://doi.org/10.1016/j.apor.2014.04.004
118. New method for estimation of stage-discharge curves in natural rivers M. Maghrebi et al. https://doi.org/10.1016/j.flowmeasinst.2016.09.008
119. Discharge estimation in a backwater affected meandering river H. Hidayat et al. https://doi.org/10.5194/hess-15-2717-2011
120. Soil hydrology: Recent methodological advances, challenges, and perspectives H. Vereecken et al. https://doi.org/10.1002/2014WR016852
121. Probabilistic Flood Maps to support decision‐making: Mapping the Value of Information L. Alfonso et al. https://doi.org/10.1002/2015WR017378
122. Improving flood inundation forecasts through the assimilation of in situ floodplain water level measurements based on alternative observation network configurations A. Van Wesemael et al. https://doi.org/10.1016/j.advwatres.2019.05.025
123. Water Balance Dynamics during Ten Years of Ecological Development at Chicken Creek Catchment W. Schaaf et al. https://doi.org/10.2136/vzj2017.04.0074
124. Uncertainty in streamflow rating curves: methods, controls and consequences K. Tomkins https://doi.org/10.1002/hyp.9567
125. Use of the data depth function to differentiate between case of interpolation and extrapolation in hydrological model prediction S. Singh et al. https://doi.org/10.1016/j.jhydrol.2012.11.034
126. Estimation of the terrestrial water budget over northern China by merging multiple datasets Y. Yao et al. https://doi.org/10.1016/j.jhydrol.2014.06.046
127. Falsification‐Oriented Signature‐Based Evaluation for Guiding the Development of Land Surface Models and the Enhancement of Observations H. Zheng et al. https://doi.org/10.1029/2020MS002132
128. Data errors and hydrological modelling: The role of model structure to propagate observation uncertainty A. Montanari & G. Di Baldassarre https://doi.org/10.1016/j.advwatres.2012.09.007
129. On a discrete version of the CIR process M. Kounta & M. Lefebvre https://doi.org/10.1080/10236198.2012.739618
130. Flow simulation based on MISO and LSTM models in the Yangtze River-Dongting Lake System C. Li et al. https://doi.org/10.1016/j.ejrh.2025.102469
131. Analysis of rapidly decreasing discharge in the transboundary Amudarya River, Central Asia: considering climate change and human impacts R. Mahmood et al. https://doi.org/10.1016/j.iswcr.2026.100682
132. Uncertainty quantification in reconstruction of sparse water quality time series: Implications for watershed health and risk-based TMDL assessment G. Mallya et al. https://doi.org/10.1016/j.envsoft.2020.104735
133. Technical Note: Monitoring of unsteady open channel flows using the continuous slope-area method K. Lee et al. https://doi.org/10.5194/hess-21-1863-2017
134. Estimation of uncertainty sources in the projections of Lithuanian river runoff J. Kriauciuniene et al. https://doi.org/10.1007/s00477-012-0608-7
135. Global Fully Distributed Parameter Regionalization Based on Observed Streamflow From 4,229 Headwater Catchments H. Beck et al. https://doi.org/10.1029/2019JD031485
136. A Review of Coupled Hydrologic-Hydraulic Models for Floodplain Assessments in Africa: Opportunities and Challenges for Floodplain Wetland Management I. Chomba et al. https://doi.org/10.3390/hydrology8010044
137. Investigation of stage‐discharge model performance for streamflow estimating: A case study of the Gono River, Japan M. Maghrebi et al. https://doi.org/10.1002/rra.4106
138. Application of advection-diffusion routing model to flood wave propagation: A case study on Big Piney River, Missouri USA Y. Yang et al. https://doi.org/10.1007/s12583-016-0626-3
139. Combining hydraulic knowledge and uncertain gaugings in the estimation of hydrometric rating curves: A Bayesian approach J. Le Coz et al. https://doi.org/10.1016/j.jhydrol.2013.11.016
140. Contribution of channel geometry adjustments to stage variance based on rating-curves in the main stream of the Lancang–Mekong river L. He et al. https://doi.org/10.1038/s41598-025-19822-w
141. Photogrammetric discharge monitoring of small tropical mountain rivers: A case study at Rivière des Pluies, Réunion Island A. Stumpf et al. https://doi.org/10.1002/2015WR018292
142. Discharge estimation combining flow routing and occasional measurements of velocity G. Corato et al. https://doi.org/10.5194/hess-15-2979-2011
143. River velocity measurements using optical flow algorithm and unoccupied aerial vehicles: A case study J. Jyoti et al. https://doi.org/10.1016/j.flowmeasinst.2023.102341
144. When does spatial resolution become spurious in probabilistic flood inundation predictions? J. Savage et al. https://doi.org/10.1002/hyp.10749
145. Uncertainty in radar‐rainfall composite and its impact on hydrologic prediction for the eastern Iowa flood of 2008 B. Seo et al. https://doi.org/10.1002/wrcr.20244
146. The suitability of remotely sensed soil moisture for improving operational flood forecasting N. Wanders et al. https://doi.org/10.5194/hess-18-2343-2014
147. Canada’s Contributions to the SWOT Mission – Terrestrial Hydrology(SWOT-C TH) A. Pietroniro et al. https://doi.org/10.1080/07038992.2019.1581056
148. Improvement of model evaluation by incorporating prediction and measurement uncertainty L. Chen et al. https://doi.org/10.5194/hess-22-4145-2018
149. Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation B. Renard et al. https://doi.org/10.1029/2011WR010643
150. Effective precipitation duration for runoff peaks based on catchment modelling A. Sikorska et al. https://doi.org/10.1016/j.jhydrol.2017.11.028
151. From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution M. Herrnegger et al. https://doi.org/10.5194/hess-19-4619-2015
152. Evaluation of Land Surface Subprocesses and Their Impacts on Model Performance With Global Flux Data J. Li et al. https://doi.org/10.1029/2018MS001606
153. Worth of hydraulic and water chemistry observation data in terms of the reliability of surface water-groundwater exchange flux predictions under varied flow conditions D. Partington et al. https://doi.org/10.1016/j.jhydrol.2020.125441
154. Framework for UAV-based river flow velocity determination employing optical recognition A. Kriščiūnas et al. https://doi.org/10.1016/j.jag.2024.104154
155. Contrasting rainfall-runoff characteristics of floods in desert and Mediterranean basins D. Zoccatelli et al. https://doi.org/10.5194/hess-23-2665-2019
156. On the Impacts of Observation Location, Timing, and Frequency on Flood Extent Assimilation Performance A. Dasgupta et al. https://doi.org/10.1029/2020WR028238
157. A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth S. Catsamas et al. https://doi.org/10.3390/s23146314
158. A Modified Laboratory Approach to Determine Reaeration Rate for River Water M. Nuruzzaman et al. https://doi.org/10.1007/s13369-017-2897-0
159. Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models L. Devitt et al. https://doi.org/10.1088/1748-9326/abfac4
160. Stage‐discharge uncertainty derived with a non‐stationary rating curve in the Choluteca River, Honduras I. Westerberg et al. https://doi.org/10.1002/hyp.7848
161. Is the current flood of data enough? A treatise on research needs for the improvement of flood modelling G. Di Baldassarre & S. Uhlenbrook https://doi.org/10.1002/hyp.8226
162. Can bed-load help to validate hydrology studies in mountainous catchment? The case study of the Roize (Voreppe, France) G. Piton et al. https://doi.org/10.1051/e3sconf/20160704020
163. Uncertainty in streamflow measurements significantly impacts estimates of downstream nitrate export S. Speir et al. https://doi.org/10.1088/1748-9326/ad0ad2
164. Multiscale Analysis of Sediment Dynamics Associated With Reservoir Flushing Operations T. Soto Parra et al. https://doi.org/10.1002/hyp.70159
165. Assessment of global reanalysis precipitation for hydrological modelling in data-scarce regions: A case study of Kenya M. Wanzala et al. https://doi.org/10.1016/j.ejrh.2022.101105
166. Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium) O. Leta et al. https://doi.org/10.1016/j.envsoft.2015.02.010
167. CFD modeling as part of a hybrid modeling case study for a gauging station with challenging hydraulics Ø. Pedersen & N. Rüther https://doi.org/10.1080/19942060.2019.1581661
168. An interactive Web-GIS fluvial flood forecast and alert system in operation in Portugal S. Mourato et al. https://doi.org/10.1016/j.ijdrr.2021.102201
169. Discharge estimation from H‐ADCP measurements in a tidal river subject to sidewall effects and a mobile bed M. Sassi et al. https://doi.org/10.1029/2010WR009972
170. Using width-based rating curves from spatially discontinuous satellite imagery to monitor river discharge T. Pavelsky https://doi.org/10.1002/hyp.10157
171. A new fuzzy linear regression approach for dissolved oxygen prediction U. Khan & C. Valeo https://doi.org/10.1080/02626667.2014.900558
172. Hydrological conditions control in situ DOM retention and release along a Mediterranean river A. Butturini et al. https://doi.org/10.1016/j.watres.2016.04.036
173. Simple vs complex rating curves: accounting for measurement uncertainty, slope ratio and sample size M. Sörengård & G. Di Baldassarre https://doi.org/10.1080/02626667.2017.1367397
174. High‐frequency streamflow acquisition and bed level/flow angle estimates in a mountainous river using shallow‐water acoustic tomography K. Kawanisi et al. https://doi.org/10.1002/hyp.10796
175. Hydraulic–hydrologic model for water resources management of the Zambezi basin T. Cohen Liechti et al. https://doi.org/10.1080/23249676.2014.958581
176. Analysis of extreme flow uncertainty impact on size of flood hazard zones for the Wronki gauge station in the Warta river T. Dysarz et al. https://doi.org/10.1007/s11600-019-00264-8
177. Global evapotranspiration models and their performance at different spatial scales: Contrasting a latitudinal gradient against global catchments I. Fuentes et al. https://doi.org/10.1016/j.jhydrol.2023.130477
178. Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range B. Henn et al. https://doi.org/10.1016/j.jhydrol.2016.08.009
179. Continuous measurements of flow rate in a shallow gravel‐bed river by a new acoustic system K. Kawanisi et al. https://doi.org/10.1029/2012WR012064
180. Buffering municipal wastewater pollution using urban wetlands in sub-Saharan Africa: a case of Masaka municipality, Uganda N. Bateganya et al. https://doi.org/10.1080/09593330.2015.1023363
181. Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture G. Tayfur & L. Brocca https://doi.org/10.1007/s11269-015-1012-0
182. On the Use of Original and Bias-Corrected Climate Simulations in Regional-Scale Hydrological Scenarios in the Mediterranean Basin L. Sangelantoni et al. https://doi.org/10.3390/atmos10120799
183. Mapping Flood Risk Uncertainty Zones in Support of Urban Resilience Planning S. Brandt et al. https://doi.org/10.17645/up.v6i3.4073
184. Expanding towards contraction: the alternation of floods and droughts as a fundamental component in river ecology S. Bernal et al. https://doi.org/10.1007/s10533-024-01197-1
185. Hydraulic scale modelling of the rating curve for a gauging station with challenging geometry Ø. Pedersen et al. https://doi.org/10.2166/nh.2019.044
186. A decade of Predictions in Ungauged Basins (PUB)—a review M. Hrachowitz et al. https://doi.org/10.1080/02626667.2013.803183
187. Quality assessment of hydrometeorological observational data and their influence on hydrological model results in Alpine catchments F. Hofmeister et al. https://doi.org/10.1080/02626667.2023.2172335
188. Bias Correction of Global High-Resolution Precipitation Climatologies Using Streamflow Observations from 9372 Catchments H. Beck et al. https://doi.org/10.1175/JCLI-D-19-0332.1
189. Towards adaptive stage-flow rating curve for large lowland river streams on the lower Tisza River with backwater impacts using deep learning and copula approach M. Stojković et al. https://doi.org/10.1016/j.ejrh.2026.103407
190. A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement S. Catsamas et al. https://doi.org/10.3390/s22197451
191. Linear Optimal Runoff Aggregate (LORA): a global gridded synthesis runoff product S. Hobeichi et al. https://doi.org/10.5194/hess-23-851-2019
192. On the theoretical velocity distribution and flow resistance in natural channels T. Moramarco & S. Dingman https://doi.org/10.1016/j.jhydrol.2017.10.068
193. Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach E. Demaria et al. https://doi.org/10.1029/2010JD015157
194. Uncertainty Assessment of Synthetic Design Hydrographs for Gauged and Ungauged Catchments M. Brunner et al. https://doi.org/10.1002/2017WR021129
195. Uncertainty in Rating-Curves Due to Manning Roughness Coefficient S. Vatanchi & M. Maghrebi https://doi.org/10.1007/s11269-019-02421-6
196. Understanding the Interannual Variation in the River Stage–Discharge Relationship and Its Impact on Flood Discharge Estimation S. Kona & R. Das Bhowmik https://doi.org/10.1061/JHYEFF.HEENG-6484
197. The benefits and trade-offs of multi-variable calibration of the WaterGAP global hydrological model (WGHM) in the Ganges and Brahmaputra basins H. Hasan et al. https://doi.org/10.5194/hess-29-567-2025
198. Heteroscedastic and symmetric efficiency for hydrological model evaluation criteria C. Zhan et al. https://doi.org/10.2166/nh.2019.121
199. Hydrological Model Calibration with Streamflow and Remote Sensing Based Evapotranspiration Data in a Data Poor Basin T. Sirisena et al. https://doi.org/10.3390/rs12223768
200. Can a Calibration-Free Dynamic Rainfall‒Runoff Model Predict FDCs in Data-Scarce Regions? Comparing the IDW Model with the Dynamic Budyko Model in South India A. Nag & B. Biswal https://doi.org/10.3390/hydrology6020032
201. Hydro‐meteorological approach for the estimation of hurricane‐induced floods D. Fernández‐Rivera et al. https://doi.org/10.1111/jfr3.12454
202. Impact of suspicious streamflow data on the efficiency and parameter estimates of rainfall–runoff models C. Thébault et al. https://doi.org/10.1080/02626667.2023.2234893
203. No support for using brown trout as an indicator species for ecological impacts of low flow in Swedish rivers M. Elenius et al. https://doi.org/10.1016/j.indic.2024.100414
204. Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America M. Tarek et al. https://doi.org/10.5194/hess-24-2527-2020
205. Hydroclimatic sustainability assessment of changing climate on cholera in the Ganges-Brahmaputra basin F. Nasr-Azadani et al. https://doi.org/10.1016/j.advwatres.2016.11.018
206. Investigating hysteresis in floodplain dynamics of lakes in the middle St. Johns River using Sentinel-1 SAR imagery K. Hubbard et al. https://doi.org/10.1016/j.ejrh.2026.103542
207. Observing Global Surface Water Flood Dynamics P. Bates et al. https://doi.org/10.1007/s10712-013-9269-4
208. Development of discharge-stage curves affected by hysteresis using time varying models, model trees and neural networks V. Wolfs & P. Willems https://doi.org/10.1016/j.envsoft.2014.01.021
209. Unsupervised image velocimetry for automated computation of river flow velocities M. Perks et al. https://doi.org/10.5194/hess-29-3727-2025
210. Cloudburst floods in mountains: State of knowledge, occurrence, factors of formation L. Kuksina et al. https://doi.org/10.1134/S1875372817010036
211. Changes in monthly flows in the Yangtze River, China – With special reference to the Three Gorges Dam J. Chen et al. https://doi.org/10.1016/j.jhydrol.2016.03.008
212. Analysis of trends of hydrologic and climatic variables E. Forootan https://doi.org/10.17221/154/2018-SWR
213. Uncertainties in measuring and estimating water‐budget components: Current state of the science S. Levin et al. https://doi.org/10.1002/wat2.1646
214. Hydrology of inland tropical lowlands: the Kapuas and Mahakam wetlands H. Hidayat et al. https://doi.org/10.5194/hess-21-2579-2017
215. Simulating the daily discharge of the Mandovi River, west coast of India K. Suprit et al. https://doi.org/10.1080/02626667.2012.674641
216. On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy A. Lombardi et al. https://doi.org/10.5194/hess-28-3777-2024
217. Time stability of catchment model parameters: Implications for climate impact analyses R. Merz et al. https://doi.org/10.1029/2010WR009505
218. Design flood estimation for global river networks based on machine learning models G. Zhao et al. https://doi.org/10.5194/hess-25-5981-2021
219. Disentangling precipitation forcing and parameter uncertainty in a multi-objective surface–subsurface hydrologic modeling framework S. Abbas et al. https://doi.org/10.1016/j.jhydrol.2026.136136
220. Prerequisites for Accurate Monitoring of River Discharge Based on Fixed‐Location Velocity Measurements K. Kästner et al. https://doi.org/10.1002/2017WR020990
221. Uncertainty Analysis of a 1D River Hydraulic Model with Adaptive Calibration M. Bessar et al. https://doi.org/10.3390/w12020561
222. Pursuing the method of multiple working hypotheses for hydrological modeling M. Clark et al. https://doi.org/10.1029/2010WR009827
223. Conceptual Models and Calibration Performance—Investigating Catchment Bias A. Buzacott et al. https://doi.org/10.3390/w11112424
224. Quality and reactivity of dissolved organic matter in a Mediterranean river across hydrological and spatial gradients E. Ejarque et al. https://doi.org/10.1016/j.scitotenv.2017.05.113
225. Use of Lower-Order and Higher–Order Streams in Modelling the Rating Curve A. Ibeje https://doi.org/10.1007/s11269-018-2145-8
226. Application of Sentinel-1A Synthetic Aperture Radar Datasets for the Estimation of Stream Flow in Various Sections of the Sone River H. Kumar & T. Roshni https://doi.org/10.1007/s40030-022-00669-7
227. Long‐Term Water Imbalances of Watersheds Resulting From Biases in Hydroclimatic Data Sets for Water Budget Analyses X. Tan et al. https://doi.org/10.1029/2021WR031209
228. A Comprehensive Review of Machine Learning and Deep Learning Methods for Flood Inundation Mapping A. Silwal et al. https://doi.org/10.3390/earth7020044
229. Contribution of hydrological modeling to the water resources assessment using soil-moisture accounting model: the case of the wadi Taria (Macta basin, NW Algeria) Y. Anouar et al. https://doi.org/10.5004/dwt.2017.21631
230. Flood map boundary sensitivity due to combined effects of DEM resolution and roughness in relation to model performance N. Lim & S. Brandt https://doi.org/10.1080/19475705.2019.1604573
231. Uncertainty in the estimation of backwater effects at bridge crossings L. Brandimarte & M. Woldeyes https://doi.org/10.1002/hyp.9350
232. Quantifying the relative impact of hydrological and hydraulic modelling parameterizations on uncertainty of inundation maps A. Annis et al. https://doi.org/10.1080/02626667.2019.1709640
233. A probabilistic framework for floodplain mapping using hydrological modeling and unsteady hydraulic modeling E. Ahmadisharaf et al. https://doi.org/10.1080/02626667.2018.1525615
234. Improving flood forecasting using conditional bias-penalized ensemble Kalman filter H. Lee et al. https://doi.org/10.1016/j.jhydrol.2019.05.072
235. Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale G. Papacharalampous et al. https://doi.org/10.1016/j.advwatres.2019.103470
236. Recent developments in predictive uncertainty assessment based on the model conditional processor approach G. Coccia & E. Todini https://doi.org/10.5194/hess-15-3253-2011
237. The Impact of the Uncertain Input Data of Multi-Purpose Reservoir Volumes under Hydrological Extremes S. Paseka & D. Marton https://doi.org/10.3390/w13101389
238. Effect of dam discharges and tides to transport of Yangtze River using coastal acoustic tomography systems C. Xiao et al. https://doi.org/10.3389/fmars.2022.1066693
239. Integrating remote sensing data with flood inundation models: how far have we got? P. Bates https://doi.org/10.1002/hyp.9374
240. Sources of uncertainty in estimating stream solute export from headwater catchments at three sites R. Yanai et al. https://doi.org/10.1002/hyp.10265
241. SHORT TERM PREDICTION OF WATER LEVEL AND DISCHARGE USING A 2D DYNAMIC WAVE MODEL WITH PARTICLE FILTERS Y. KIM et al. https://doi.org/10.2208/jscejhe.68.I_25
242. Novel high-frequency acoustic monitoring of streamflow-turbidity dynamics in a gravel-bed river during artificial dam flush M. Al Sawaf & K. Kawanisi https://doi.org/10.1016/j.catena.2018.09.033
243. Assessment of the Value of Remotely Sensed Surface Water Extent Data for the Calibration of a Lumped Hydrological Model A. Meyer Oliveira et al. https://doi.org/10.1029/2023WR034875
244. Quantification of uncertainty in estimated nitrate-N loads in agricultural watersheds Y. Jiang et al. https://doi.org/10.1016/j.jhydrol.2014.06.027
245. Statistical Uncertainty in Hydrometeorological Trend Analyses C. Onyutha https://doi.org/10.1155/2016/8701617
246. Machine learning model for stage-discharge curve calculation J. Langhammer et al. https://doi.org/10.14712/23361980.2025.25
247. Tidal reversal and flow velocities using temperature and specific conductance in a small wetland creek T. Eaton https://doi.org/10.1016/j.jhydrol.2016.09.030
248. Observation impact, domain length and parameter estimation in data assimilation for flood forecasting E. Cooper et al. https://doi.org/10.1016/j.envsoft.2018.03.013
249. Simultaneous assimilation of water levels from river gauges and satellite flood maps for near-real-time flood mapping A. Annis et al. https://doi.org/10.5194/hess-26-1019-2022
250. On constructing limits-of-acceptability in watershed hydrology using decision trees A. Gupta et al. https://doi.org/10.1016/j.advwatres.2023.104486
251. Integrating unmanned aerial systems and LSPIV for rapid, cost-effective stream gauging Q. Lewis et al. https://doi.org/10.1016/j.jhydrol.2018.03.008
252. Quantification and attribution of errors in the simulated annual gross primary production and latent heat fluxes by two global land surface models J. Li et al. https://doi.org/10.1002/2015MS000583
253. Effects of tributary inflows on unsteady flow hysteresis and hydrodynamics in the mainstream H. Tang et al. https://doi.org/10.2166/nh.2024.018
254. Leveraging multi-variable observations to reduce and quantify the output uncertainty of a global hydrological model: evaluation of three ensemble-based approaches for the Mississippi River basin P. Döll et al. https://doi.org/10.5194/hess-28-2259-2024
255. Large Addition of Freshwater to the Tidal Reaches of the Yangtze (Changjiang) River X. Mei et al. https://doi.org/10.1007/s12237-019-00518-0
256. Connecting a lake and its upstream watersheds: a joint water balance approach M. Sugita et al. https://doi.org/10.1080/02626667.2025.2481166
257. The use of crowdsourced social media data to improve flood forecasting C. Songchon et al. https://doi.org/10.1016/j.jhydrol.2023.129703
258. Magnitude and variability of land evaporation and its components at the global scale D. Miralles et al. https://doi.org/10.5194/hess-15-967-2011
259. Improvement of Flood Extent Representation With Remote Sensing Data and Data Assimilation T. Nguyen et al. https://doi.org/10.1109/TGRS.2022.3147429
260. Uncertainty quantification of multi-source hydrological data products for the improvement of water budget estimations in small-scale Sakarya basin, Turkey G. Kayan et al. https://doi.org/10.1080/02626667.2022.2093642
261. Toward a satellite-based observation of atmospheric heat source over land K. Yang et al. https://doi.org/10.1002/2013JD021091
262. Flash floods: formation, study and distribution L. Kuksina et al. https://doi.org/10.1051/e3sconf/202016302005
263. Modeling discharge rating curves with Bayesian B-splines B. Hrafnkelsson et al. https://doi.org/10.1007/s00477-011-0526-0
264. Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models J. Neal et al. https://doi.org/10.1016/j.jhydrol.2015.07.026
265. Tracking the weight of Hurricane Harvey’s stormwater using GPS data C. Milliner et al. https://doi.org/10.1126/sciadv.aau2477
266. Assessment of the combined effects of Manning roughness and DEM resolution for the water surface elevation prediction using the HEC-RAS model: a case study of Moudjar River in the Northeast of Algeria S. Kechida et al. https://doi.org/10.1007/s40808-023-01821-3
267. Hydrometeorological Characterization of a Flash Flood Associated with Major Geomorphic Effects: Assessment of Peak Discharge Uncertainties and Analysis of the Runoff Response W. Amponsah et al. https://doi.org/10.1175/JHM-D-16-0081.1
268. Challenges in Applying Machine Learning Models for Hydrological Inference: A Case Study for Flooding Events Across Germany L. Schmidt et al. https://doi.org/10.1029/2019WR025924
269. A method for extending stage-discharge relationships using a hydrodynamic model and quantifying the associated uncertainty Q. Shao et al. https://doi.org/10.1016/j.jhydrol.2017.11.012
270. A blueprint for process‐based modeling of uncertain hydrological systems A. Montanari & D. Koutsoyiannis https://doi.org/10.1029/2011WR011412
271. A flood-crest forecast prototype for river floods using only in-stream measurements M. Muste et al. https://doi.org/10.1038/s43247-022-00402-z
272. Optimization of rain gauge sampling density for river discharge prediction using Bayesian calibration A. Wadoux et al. https://doi.org/10.7717/peerj.9558
273. Modelling shallow and narrow urban salt-wedge estuaries: Evaluation of model performance and sensitivity to optimise input data collection D. Jovanovic et al. https://doi.org/10.1016/j.ecss.2018.10.022
274. Mathematical description of water flow quantity for microhydroelectric station D. Kodirov et al. https://doi.org/10.1088/1755-1315/614/1/012032
275. Short-term optimal operation of water systems using ensemble forecasts L. Raso et al. https://doi.org/10.1016/j.advwatres.2014.06.009
276. Estimating the Uncertainty of Hydrological Predictions through Data-Driven Resampling Techniques A. Sikorska et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000926
277. Optical Tracking Velocimetry (OTV): Leveraging Optical Flow and Trajectory-Based Filtering for Surface Streamflow Observations F. Tauro et al. https://doi.org/10.3390/rs10122010
278. Systematic interrogation area optimization in large-scale particle image velocimetry using information entropy H. Ho et al. https://doi.org/10.1016/j.jher.2025.100665
279. Extent of gross underestimation of precipitation in India G. Goteti & J. Famiglietti https://doi.org/10.5194/hess-28-3435-2024
280. Abordagem fuzzy para caracterização de incertezas estruturais e quantificação de riscos hidrológicos: estudo de caso do reservatório Orós no semiárido brasileiro J. Batista de Sousa Raulino et al. https://doi.org/10.36659/dae.2022.013
281. Flood frequency under changing climate in the upper Kafue River basin, southern Africa: a large scale hydrological model application C. Ngongondo et al. https://doi.org/10.1007/s00477-013-0724-z
282. Insights into Flood Wave Propagation in Natural Streams as Captured with Acoustic Profilers at an Index-Velocity Gaging Station M. Muste et al. https://doi.org/10.3390/w14091380
283. A review and synthesis of hysteresis in hydrology and hydrological modeling: Memory, path-dependency, or missing physics? S. Gharari & S. Razavi https://doi.org/10.1016/j.jhydrol.2018.06.037
284. Reconstruction of Tidal Discharges in the St. Lawrence Fluvial Estuary: The Method of Cubature Revisited P. Matte et al. https://doi.org/10.1029/2018JC013834
285. Application of hydro energy in small power supply systems D. Kodirov et al. https://doi.org/10.1088/1755-1315/614/1/012037
286. A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations G. Coxon et al. https://doi.org/10.1002/2014WR016532
287. Operational hydrological data assimilation with the recursive ensemble Kalman filter H. McMillan et al. https://doi.org/10.5194/hess-17-21-2013
288. Towards understanding the dynamic behaviour of floodplains as human-water systems G. Di Baldassarre et al. https://doi.org/10.5194/hess-17-3235-2013
289. A review of how uncertainties are assessed in water quality modeling: A paradigm shift towards more complete practices X. Sun et al. https://doi.org/10.1016/j.envsoft.2026.107068
290. Understanding Uncertainty in Probabilistic Floodplain Mapping in the Time of Climate Change Z. Zahmatkesh et al. https://doi.org/10.3390/w13091248
291. Global evaluation of terrestrial evaporation trend from diagnostic products F. Ruan et al. https://doi.org/10.1016/j.jhydrol.2025.132979
292. Making Different Decisions: Demonstrating the Influence of Climate Model Uncertainty on Adaptation Pathways J. Dimond et al. https://doi.org/10.3390/w17091366
293. Comparison of gridded datasets for the simulation of streamflow in Africa M. Tarek et al. https://doi.org/10.1088/1757-899X/974/1/012001
294. Uncertainty analysis of a 2D sediment transport model: an example of the Lower River Salzach F. Beckers et al. https://doi.org/10.1007/s11368-017-1816-z
295. The 3DNet-Catch hydrologic model: Development and evaluation A. Todorović et al. https://doi.org/10.1016/j.jhydrol.2018.10.040
296. Estimation of Amazon River discharge based on EOF analysis of GRACE gravity data J. Eom et al. https://doi.org/10.1016/j.rse.2017.01.011
297. Uncertainty propagation from gridded precipitation datasets to streamflow simulations: application to the Reno River basin (Italy) O. Cenobio-Cruz & G. Di Baldassarre https://doi.org/10.1080/02626667.2025.2590597
298. Tree structure generation from ensemble forecasts for real time control L. Raso et al. https://doi.org/10.1002/hyp.9473
299. Water, heat, and soil in a changing climate A. Souza et al. https://doi.org/10.1016/j.jsames.2025.105767
300. Determining the Optimal Spatial Distribution of Weather Station Networks for Hydrological Modeling Purposes Using RCM Datasets: An Experimental Approach R. Arsenault & F. Brissette https://doi.org/10.1175/JHM-D-13-088.1
301. Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al. https://doi.org/10.1029/2021WR031649
302. Flood risk mapping using uncertainty propagation analysis on a peak discharge: case study of the Mille Iles River in Quebec J. Zokagoa et al. https://doi.org/10.1007/s11069-021-04583-2
303. A new instream flow assessment method based on fuzzy habitat suitability and large scale river modelling S. Marsili-Libelli et al. https://doi.org/10.1016/j.envsoft.2012.10.005
304. Assessment of flood dynamics in a mountain stream using high‐resolution river flow records C. Xiao et al. https://doi.org/10.1002/hyp.14841
305. 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
306. Estimating water discharge from large radar altimetry datasets A. Getirana & C. Peters-Lidard https://doi.org/10.5194/hess-17-923-2013
307. Chromium fluxes and speciation in ultramafic catchments and global rivers C. McClain & K. Maher https://doi.org/10.1016/j.chemgeo.2016.01.021
308. Mapping of flood hazard induced by land subsidence in Semarang City, Indonesia, using hydraulic and spatial models B. Yuwono et al. https://doi.org/10.1007/s11069-023-06398-9
309. Uncertainty quantification for hydrological models based on neural networks: the dropout ensemble D. Althoff et al. https://doi.org/10.1007/s00477-021-01980-8
310. Estimating river discharge from water level observations using a differentiable hydraulic model with an embedded LSTM model to learn time-varying channel roughness P. Aarestrup et al. https://doi.org/10.1016/j.hydrch.2026.100013
311. The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets D. Miralles et al. https://doi.org/10.5194/hess-20-823-2016
312. Teaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exercise W. Knoben & D. Spieler https://doi.org/10.5194/hess-26-3299-2022
313. Building hazard maps with differentiated risk perception for flood impact assessment P. Bhola et al. https://doi.org/10.5194/nhess-20-2647-2020
314. Recent Changes of Floods and Related Impacts in Niger Based on the ANADIA Niger Flood Database E. Fiorillo et al. https://doi.org/10.3390/cli6030059
315. Estimation of River High Flow Discharges Using Friction-Slope Method and Hybrid Models F. Shirazi et al. https://doi.org/10.1007/s11269-023-03711-w
316. Integrated assessment for hydrometeorological drought based on Markov chain model J. Yang et al. https://doi.org/10.1007/s11069-016-2480-0
317. New methodology to develop high-resolution rainfall data using weather radar for watershed-scale water quality model D. Jeon et al. https://doi.org/10.5004/dwt.2019.23344
318. The influence of climate model uncertainty on fluvial flood hazard estimation L. Beevers et al. https://doi.org/10.1007/s11069-020-04282-4
319. Passive Microwave Radiometry at Different Frequency Bands for River Discharge Retrievals G. Brakenridge et al. https://doi.org/10.1029/2023EA002859
320. Beyond a fixed number: Investigating uncertainty in popular evaluation metrics of ensemble flood modeling using bootstrapping analysis T. Huang & V. Merwade https://doi.org/10.1111/jfr3.12982
321. Improvement of the Method using the Coefficient of Variation for Automatic Multi-segmentation Method of a Rating Curve Y. Kim et al. https://doi.org/10.3741/JKWRA.2015.48.10.807
322. Hydrological reanalysis across the 20th century: A case study of the Amazon Basin S. Wongchuig et al. https://doi.org/10.1016/j.jhydrol.2019.01.025
323. Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model J. Thomas Steven Savage et al. https://doi.org/10.1002/2015WR018198
324. Spatially distributed modelling of surface water-groundwater exchanges during overbank flood events – a case study at the Garonne River L. Bernard-Jannin et al. https://doi.org/10.1016/j.advwatres.2016.05.008
325. Increasing Alaskan river discharge during the cold season is driven by recent warming D. Blaskey et al. https://doi.org/10.1088/1748-9326/acb661
326. Distinguishing the effects of climate on discharge in a tropical river highly impacted by large dams F. Genz & L. Luz https://doi.org/10.1080/02626667.2012.690880
327. Uncertainty Assessment of Entropy-Based Circular Channel Shear Stress Prediction Models Using a Novel Method A. Kazemian-Kale-Kale et al. https://doi.org/10.3390/geosciences11080308
328. Going local: Evaluating and regionalizing a global hydrological model’s simulation of river flows in a medium-sized East African basin C. Siderius et al. https://doi.org/10.1016/j.ejrh.2018.10.007
329. RiverFlood-1D v 1.0: coupling parabolic and backwater (PAB) scheme and Muskingum-Cunge model for river flood routing, with application to the Po River (Italy) G. Ravazzani et al. https://doi.org/10.1016/j.envsoft.2026.107104
330. Assessing the Steady‐State Assumption in Water Balance Calculation Across Global Catchments J. Han et al. https://doi.org/10.1029/2020WR027392
331. Enhancing river model set-up for 2-D dynamic flood modelling P. Costabile & F. Macchione https://doi.org/10.1016/j.envsoft.2015.01.009
332. A physics-guided machine learning framework for accurate reconstruction of missing discharge records: case study of the Gandak River at Hajipur, India R. Prakash & J. Tripura https://doi.org/10.1007/s00477-026-03264-5
333. Out of tune: the dangers of aligning proxy archives M. Blaauw https://doi.org/10.1016/j.quascirev.2010.11.012
334. Water quality improvements from implementation of tailwater recovery systems A. Omer & B. Baker https://doi.org/10.1007/s40899-018-0249-1
335. A Simple Approach to Account for Stage–Discharge Uncertainty in Hydrological Modelling R. Vázquez & H. Hampel https://doi.org/10.3390/w14071045
336. Characteristics of gauged abrupt wave fronts (walls of water) in flash floods in Scotland D. Archer et al. https://doi.org/10.5194/hess-29-5777-2025
337. Reliability of Entropy-Based Telemetry Discharge Estimates in the Himalayan Rivers: A Comparative Study with ADCP and Current Meter A. Kumar & M. Jain https://doi.org/10.1080/02626667.2026.2710202
338. Flood Forecasting in Large River Basins Using FOSS Tool and HPC U. Dutta et al. https://doi.org/10.3390/w13243484
339. A Comparison of Methods for Streamflow Uncertainty Estimation J. Kiang et al. https://doi.org/10.1029/2018WR022708
340. Recent changes in extreme floods across multiple continents W. Berghuijs et al. https://doi.org/10.1088/1748-9326/aa8847
341. Non-linear fuzzy-set based uncertainty propagation for improved DO prediction using multiple-linear regression U. Khan et al. https://doi.org/10.1007/s00477-012-0626-5
342. Quantifying local rainfall dynamics and uncertain boundary conditions into a nested regional‐local flood modeling system M. Bermúdez et al. https://doi.org/10.1002/2016WR019903
343. Trends in Compound Flooding in Northwestern Europe During 1901–2014 P. Ganguli & B. Merz https://doi.org/10.1029/2019GL084220
344. Estimation of uncertainty in flood forecasts—A comparison of methods L. Boelee et al. https://doi.org/10.1111/jfr3.12516
345. Bayesian uncertainty assessment of flood predictions in ungauged urban basins for conceptual rainfall-runoff models A. Sikorska et al. https://doi.org/10.5194/hess-16-1221-2012
346. Multi-Satellite Data of Land Surface Temperature, Lakes Area, and Water Level for Hydrological Model Calibration and Validation in the Yangtze River Basin C. Corbari et al. https://doi.org/10.3390/w11122621
347. Catchment tomography - An approach for spatial parameter estimation D. Baatz et al. https://doi.org/10.1016/j.advwatres.2017.06.006
348. Hydrological change: Towards a consistent approach to assess changes on both floods and droughts B. Quesada-Montano et al. https://doi.org/10.1016/j.advwatres.2017.10.038
349. Observation operators for assimilation of satellite observations in fluvial inundation forecasting E. Cooper et al. https://doi.org/10.5194/hess-23-2541-2019
350. Examining the impact of lahars on buildings using numerical modelling S. Mead et al. https://doi.org/10.5194/nhess-17-703-2017
351. Transposing flood risk from extreme rainfall events: A case study of Hurricane Harvey E. Regier et al. https://doi.org/10.1111/jfr3.12778
352. Riverine dissolved organic carbon in Rukarara River Watershed, Rwanda F. Rizinjirabake et al. https://doi.org/10.1016/j.scitotenv.2018.06.194
353. Comparing Large-Scale Hydrological Model Simulations to Observed Runoff Percentiles in Europe L. Gudmundsson et al. https://doi.org/10.1175/JHM-D-11-083.1
354. Defining the hundred year flood: A Bayesian approach for using historic data to reduce uncertainty in flood frequency estimates B. Parkes & D. Demeritt https://doi.org/10.1016/j.jhydrol.2016.07.025
355. Diagnosing structural deficiencies of a hydrological model by time-varying parameters L. Zhou et al. https://doi.org/10.1016/j.jhydrol.2021.127305
356. Rating curve uncertainty and change detection in discharge time series: case study with 44‐year historic data from the Nyangores River, Kenya J. Juston et al. https://doi.org/10.1002/hyp.9786
357. Rainfall-runoff modelling using river-stage time series in the absence of reliable discharge information: a case study in the semi-arid Mara River basin P. Hulsman et al. https://doi.org/10.5194/hess-22-5081-2018
358. Testing new sources of topographic data for flood propagation modelling under structural, parameter and observation uncertainty M. Mukolwe et al. https://doi.org/10.1080/02626667.2015.1019507
359. Flood mapping under uncertainty: a case study in the Canadian prairies R. Bharath & A. Elshorbagy https://doi.org/10.1007/s11069-018-3401-1
360. Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison A. Fleischmann et al. https://doi.org/10.1016/j.hydroa.2019.100027
361. Identification of temporal consistency in rating curve data: Bidirectional Reach (BReach) K. Van Eerdenbrugh et al. https://doi.org/10.1002/2016WR018692
362. Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning A. Di Ciacca et al. https://doi.org/10.5194/hess-27-703-2023
363. Assimilation of Satellite Altimetry Data for Effective River Bathymetry J. Brêda et al. https://doi.org/10.1029/2018WR024010
364. Hydraulic Structures as Flow Measuring Devices E. Bilkova et al. https://doi.org/10.2478/rtuect-2023-0002
365. Propagation of structural uncertainty in watershed hydrologic models A. Gupta & R. Govindaraju https://doi.org/10.1016/j.jhydrol.2019.05.026
366. Flash floods: Observations and analysis of hydro-meteorological controls M. Borga et al. https://doi.org/10.1016/j.jhydrol.2010.07.048
367. Flood Hazard Scenarios of the Sirba River (Niger): Evaluation of the Hazard Thresholds and Flooding Areas G. Massazza et al. https://doi.org/10.3390/w11051018
368. Understanding and modelling the effects of wetland on the hydrology and water resources of large African river basins E. Makungu & D. Hughes https://doi.org/10.1016/j.jhydrol.2021.127039
369. A benchmarking framework to enhance cost-efficiency in water systems resilience planning under deep uncertainty L. Liu et al. https://doi.org/10.1016/j.jclepro.2026.147850
370. An Interval-Deviation Approach for hydrology and water quality model evaluation within an uncertainty framework L. Chen et al. https://doi.org/10.1016/j.jhydrol.2013.11.043
371. Accuracy assessment and error decomposition of internet of things sensor: Low-flow conditions in Dorimcheon stream A. Khatatbeh & Y. Kim https://doi.org/10.1016/j.jrras.2023.100595
372. Floodplain management in Africa: Large scale analysis of flood data P. Padi et al. https://doi.org/10.1016/j.pce.2011.02.002
373. Effect of Dam operation on monthly and annual trends of flow discharge in the Qom Rood Watershed, Iran H. Yaghmaei et al. https://doi.org/10.1016/j.jhydrol.2017.12.039
374. Comparison of stage/discharge rating curves derived from different recording systems: Consequences for streamflow data and water management in a Mediterranean island J. Fortesa et al. https://doi.org/10.1016/j.scitotenv.2019.02.158
375. Streamflow Observations From Cameras: Large‐Scale Particle Image Velocimetry or Particle Tracking Velocimetry? F. Tauro et al. https://doi.org/10.1002/2017WR020848
376. Flood Risk Assessment and Zoning for Niamey and Lokoja Metropolises in Niger and Nigeria Y. Nouhou et al. https://doi.org/10.3390/hydrology12010017
377. Analysis of Flow Estimation Methods for Small Hydropower Schemes in Bua River C. Kasamba et al. https://doi.org/10.4236/epe.2015.72005
378. Toward Global Stochastic River Flood Modeling O. Wing et al. https://doi.org/10.1029/2020WR027692
379. Discharge and nutrient uncertainty: implications for nutrient flux estimation in small streams C. Lloyd et al. https://doi.org/10.1002/hyp.10574
380. A review of methods for estimating the contribution of glacial meltwater to total watershed discharge J. Frenierre & B. Mark https://doi.org/10.1177/0309133313516161
381. Comment on “The Treatment of Uncertainty in Hydrometric Observations: A Probabilistic Description of Streamflow Records” by de Oliveira and Vrugt W. Knoben & M. Clark https://doi.org/10.1029/2022WR034294
382. A Multi‐Century Meteo‐Hydrological Analysis in the Italian Alps: Daily Streamflow (1862–2022) at Different Time Scales R. Ranzi et al. https://doi.org/10.1002/hyp.70305
383. Application of statistical techniques to proportional loss data: Evaluating the predictive accuracy of physical vulnerability to hazardous hydro-meteorological events C. Chow et al. https://doi.org/10.1016/j.jenvman.2019.05.084
384. Evaluation of the Impact of Multi-Source Uncertainties on Meteorological and Hydrological Ensemble Forecasting Z. Shu et al. https://doi.org/10.1016/j.eng.2022.06.007
385. Evaluation of hydrological models at gauged and ungauged basins using machine learning-based limits-of-acceptability and hydrological signatures A. Gupta et al. https://doi.org/10.1016/j.jhydrol.2024.131774
386. Lateral and subsurface flows impact arctic coastal plain lake water budgets J. Koch https://doi.org/10.1002/hyp.10917
387. Implementation of a Hydraulic Routing Model for Dendritic Networks with Offline Coupling to a Distributed Hydrological Model C. Choi et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001152
388. Simultaneous estimation of inflow and channel roughness using 2D hydraulic model and particle filters Y. Kim et al. https://doi.org/10.1111/j.1753-318X.2012.01164.x
389. Calibration and Validation of a Distributed Energy–Water Balance Model Using Satellite Data of Land Surface Temperature and Ground Discharge Measurements C. Corbari & M. Mancini https://doi.org/10.1175/JHM-D-12-0173.1
390. Adaptively monitoring streamflow using a stereo computer vision system N. Hutley et al. https://doi.org/10.5194/hess-27-2051-2023
391. Assessment of uncertainties in stage–discharge rating curves: a large-scale application to Quebec hydrometric network A. Mailhot et al. https://doi.org/10.5194/hess-29-3615-2025
392. Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions Z. Chen et al. https://doi.org/10.5194/hess-22-3807-2018
393. Artificial Neural Network Rainfall-Discharge Model Assessment Under Rating Curve Uncertainty and Monthly Discharge Volume Predictions A. Zeroual et al. https://doi.org/10.1007/s11269-016-1340-8
394. Atmospheric dynamics of extreme discharge events from 1979 to 2016 in the southern Central Andes F. Castino et al. https://doi.org/10.1007/s00382-020-05458-1
395. Can streamflow observations constrain snow mass reconstructions? Lessons from two synthetic numerical experiments P. Wiersma et al. https://doi.org/10.5194/hess-30-3331-2026
396. New estimates of silicate weathering rates and their uncertainties in global rivers S. Moon et al. https://doi.org/10.1016/j.gca.2014.02.033
397. Supraglacial Ponds Regulate Runoff From Himalayan Debris‐Covered Glaciers T. Irvine‐Fynn et al. https://doi.org/10.1002/2017GL075398
398. Multidecadal Analysis of an Engineered River System Reveals Challenges for Model-Based Design of Human Interventions K. Berends et al. https://doi.org/10.3390/civileng2030032
399. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting X. Zhang et al. https://doi.org/10.1016/j.jhydrol.2011.09.002
400. Potentialities of ensemble strategies for flood forecasting over the Milano urban area G. Ravazzani et al. https://doi.org/10.1016/j.jhydrol.2016.05.023
401. The Importance of Bank Storage in Supplying Baseflow to Rivers Flowing Through Compartmentalized, Alluvial Aquifers K. Rhodes et al. https://doi.org/10.1002/2017WR021619
402. Bayesian Rating Curve Modeling: Alternative Error Model to Improve Low-Flow Uncertainty Estimation R. Garcia et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001903
403. Development of River Rating Curves for Simple to Complex Hydraulic Structure Based on Calibrated HEC-RAS Hydraulic Model, in Kwale, Coastal Kenya C. Wara et al. https://doi.org/10.4236/jwarp.2019.114028
404. User-oriented hydrological indices for early warning systems with validation using post-event surveys: flood case studies in the Central Apennine District A. Lombardi et al. https://doi.org/10.5194/hess-25-1969-2021
405. Applicability of recurrent neural networks to retrieve missing runoff records: challenges and opportunities in Turkey Y. Alsavaf & A. Teksoy https://doi.org/10.1007/s10661-021-09681-z
406. A framework for generating rating curves in Mahanadi River using hydrodynamic model and radar altimetry data P. Dhote et al. https://doi.org/10.1080/02626667.2024.2430387
407. Quantifying the Peak Flow Reduction Potential of Prairie Strips Using Integrated Surface‐Subsurface Modelling B. Eustace & A. Arenas https://doi.org/10.1002/sae2.70147
408. Quantifying Cr(VI) Production and Export from Serpentine Soil of the California Coast Range C. McClain et al. https://doi.org/10.1021/acs.est.6b03484
409. PeakTrace: Routing of hydropeaking waves using multiple hydrographs—A novel approach F. Greimel et al. https://doi.org/10.1002/rra.3978
410. 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
411. Perceptual perplexity and parameter parsimony K. Beven & N. Chappell https://doi.org/10.1002/wat2.1530
412. A Tool for Forecasting the Arrival Time of a Tracer or a Pollutant at a Karst Spring G. Preisig & L. Perrochet https://doi.org/10.1111/gwat.13218
413. Tall tales from the hydrological crypt: are models monsters? T. Mathevet & R. Garçon https://doi.org/10.1080/02626667.2010.503934
414. The Treatment of Uncertainty in Hydrometric Observations: A Probabilistic Description of Streamflow Records D. de Oliveira & J. Vrugt https://doi.org/10.1029/2022WR032263
415. Evaluation of an instantaneous dryness index-based calibration-free continuous hydrological model in India S. Patnaik et al. https://doi.org/10.2166/nh.2019.081
416. The 21st August 2020 Flood in Douala (Cameroon): A Major Urban Flood Investigated with 2D HEC-RAS Modeling J. Iroume et al. https://doi.org/10.3390/w14111768
417. Estimation of the uncertainty in water level forecasts at ungauged river locations using quantile regression K. Roscoe et al. https://doi.org/10.1080/15715124.2012.740483
418. Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin G. Simons et al. https://doi.org/10.3390/rs8040279
419. Impact of Precipitation Uncertainty on Flood Hazard Assessment in the Oueme River Basin D. Afféwé et al. https://doi.org/10.3390/hydrology12060138
420. Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling A. Gain et al. https://doi.org/10.5194/hess-15-1537-2011
421. Balancing Costs and Benefits in Selecting New Information: Efficient Monitoring Using Deterministic Hydro-economic Models L. Raso et al. https://doi.org/10.1007/s11269-017-1813-4
422. Reducing Inconsistencies in Point Observations of Maximum Flood Inundation Level B. Parkes et al. https://doi.org/10.1175/2012EI000475.1
423. Roughness and Discharge Uncertainty in 1D Water Level Calculations S. Bozzi et al. https://doi.org/10.1007/s10666-014-9430-6
424. Floodplain management strategies for flood attenuation in the river Po A. Castellarin et al. https://doi.org/10.1002/rra.1405
425. Mesh elevation modifications and upstream boundary adjustment as alternatives to roughness calibration in hydraulic modelling P. Khorsandi Kuhanestani et al. https://doi.org/10.1080/02626667.2026.2669185
426. Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis E. Moges et al. https://doi.org/10.3390/w13010028
427. Constraining coupled hydrological-hydraulic flood model by past storm events and post-event measurements in data-sparse regions R. Hdeib et al. https://doi.org/10.1016/j.jhydrol.2018.08.008
428. The use of SARAL/AltiKa altimeter measurements for multi-site hydrodynamic model validation and rating curves estimation: An application to Brahmaputra River P. Dhote et al. https://doi.org/10.1016/j.asr.2020.05.012
429. Benchmark dataset for hydraulic simulations of flash floods in the French Mediterranean region J. Godet et al. https://doi.org/10.5194/essd-17-2963-2025
430. On the contribution of remote sensing-based calibration to model hydrological and hydraulic processes in tropical regions A. Meyer Oliveira et al. https://doi.org/10.1016/j.jhydrol.2021.126184
431. A novel approach to flow estimation in tidal rivers H. Moftakhari et al. https://doi.org/10.1002/wrcr.20363
432. Modeling and mitigating natural hazards: Stationarity is immortal! A. Montanari & D. Koutsoyiannis https://doi.org/10.1002/2014WR016092
433. Distributed hydrological modeling of floods in the Cévennes-Vivarais region, France: Impact of uncertainties related to precipitation estimation and model parameterization R. Navas & G. Delrieu https://doi.org/10.1016/j.jhydrol.2018.08.032
434. Width‐Based Discharge Partitioning in Distributary Networks: How Right We Are J. Hariharan et al. https://doi.org/10.1029/2022GL097897
435. Future hydrology and climate in the River Nile basin: a review G. Di Baldassarre et al. https://doi.org/10.1080/02626667.2011.557378
436. Improving rating curve accuracy by incorporating water balance closure at river bifurcations M. Gensen et al. https://doi.org/10.1016/j.jhydrol.2022.127958
437. Remote Sensing-Derived Water Extent and Level to Constrain Hydraulic Flood Forecasting Models: Opportunities and Challenges S. Grimaldi et al. https://doi.org/10.1007/s10712-016-9378-y
438. Building vulnerability to hydro-geomorphic hazards: Estimating damage probability from qualitative vulnerability assessment using logistic regression S. Ettinger et al. https://doi.org/10.1016/j.jhydrol.2015.04.017
439. Testing an environmental flow-based decision support tool: Evaluating the fish model in the Murray Flow Assessment Tool R. Lester et al. https://doi.org/10.1016/j.envsoft.2018.09.012
440. 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
441. Towards a large-scale locally relevant flood inundation modeling framework using SWAT and LISFLOOD-FP A. Rajib et al. https://doi.org/10.1016/j.jhydrol.2019.124406
442. Hydrodynamic and Total Dissolved Solids Model of the Tigris River Using CE-QUAL-W2 M. Al-Murib & S. Wells https://doi.org/10.1007/s40710-019-00381-y
443. Is observation uncertainty masking the signal of land use change impacts on hydrology? S. Gebrehiwot et al. https://doi.org/10.1016/j.jhydrol.2018.12.058
444. Catchment Multisite Discharge Measurements for Hydrological Model Calibration L. Boscarello et al. https://doi.org/10.1016/j.proenv.2013.06.018
445. Suitability of a lumped rainfall–runoff model for flashy tropical watersheds in New Caledonia T. Desclaux et al. https://doi.org/10.1080/02626667.2018.1523613
446. A case study of flood frequency analysis by intercomparison of graphical linear log-regression method and Gumbel's analytical method in the Vaigai river basin of Tamil Nadu, India M. Ramasamy et al. https://doi.org/10.1016/j.chemosphere.2021.131571
447. An Integrated Modelling System to Predict Hydrological Processes under Climate and Land-Use/Cover Change Scenarios B. Farjad et al. https://doi.org/10.3390/w9100767
448. Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting P. Abbaszadeh et al. https://doi.org/10.5194/hess-29-2407-2025
449. Comprehensive post‐event survey of a flash flood in Western Slovenia: observation strategy and lessons learned L. Marchi et al. https://doi.org/10.1002/hyp.7542
450. Uncertainty analysis of flow velocity estimation by a simplified entropy model G. Corato et al. https://doi.org/10.1002/hyp.9590
451. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty E. Moges et al. https://doi.org/10.1002/2015WR018266
452. Assessing rating-curve uncertainty and its effects on hydraulic model calibration A. Domeneghetti et al. https://doi.org/10.5194/hess-16-1191-2012
453. Hydrological Parameters Estimation Using Remote Sensing and GIS for Indian Region: A Review P. Thakur et al. https://doi.org/10.1007/s40010-017-0440-z
454. Hydrological field data from a modeller's perspective: Part 2: process‐based evaluation of model hypotheses M. Clark et al. https://doi.org/10.1002/hyp.7902
455. An integrated Hydrological Model for Assessing Climate Change Impacts on Water Resources of the Upper Po River Basin G. Ravazzani et al. https://doi.org/10.1007/s11269-014-0868-8
456. Optical Methods for River Monitoring: A Simulation-Based Approach to Explore Optimal Experimental Setup for LSPIV D. Pumo et al. https://doi.org/10.3390/w13030247
457. Uncertainty of the peak flow reconstruction of the 1907 flood in the Ebro River in Xerta (NE Iberian Peninsula) J. Ruiz-Bellet et al. https://doi.org/10.1016/j.jhydrol.2016.12.041
458. Filling streamflow data gaps through the construction of rating curves in the Lake Tana sub-basin, Nile basin A. Haile et al. https://doi.org/10.2166/wcc.2023.372
459. On the derivation of flow rating curves in data-scarce environments S. Manfreda https://doi.org/10.1016/j.jhydrol.2018.04.058