93 citations as recorded by crossref.

1. Precipitation extremes on multiple timescales – Bartlett–Lewis rectangular pulse model and intensity–duration–frequency curves C. Ritschel et al. https://doi.org/10.5194/hess-21-6501-2017
2. Assessment of integrated watershed health based on the natural environment, hydrology, water quality, and aquatic ecology S. Ahn & S. Kim https://doi.org/10.5194/hess-21-5583-2017
3. Comparing Performance of ANN and SVM Methods for Regional Flood Frequency Analysis in South-East Australia A. Zalnezhad et al. https://doi.org/10.3390/w14203323
4. The sensitivity of fluvial flood risk in Irish catchments to the range of IPCC AR4 climate change scenarios S. Bastola et al. https://doi.org/10.1016/j.scitotenv.2011.08.042
5. Comparing ensemble projections of flooding against flood estimation by continuous simulation A. Smith et al. https://doi.org/10.1016/j.jhydrol.2014.01.045
6. An automatic parameter calibration method for the SWAT model in runoff simulation Y. Wang et al. https://doi.org/10.1002/rra.3655
7. A method for incorporating climate variability in climate change impact assessments: Sensitivity of river flows in the Eden catchment to precipitation scenarios R. Ledbetter et al. https://doi.org/10.1007/s10584-011-0386-0
8. Fully Stochastic Distributed Methodology for Multivariate Flood Frequency Analysis I. Flores-Montoya et al. https://doi.org/10.3390/w8060225
9. The integrated effects of climate and hydrologic uncertainty on future flood risk assessments S. Steinschneider et al. https://doi.org/10.1002/hyp.10409
10. A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales J. Park et al. https://doi.org/10.5194/hess-23-989-2019
11. Uncertainty in hydrologic modelling for estimating hydrologic response due to climate change (Santiam River, Oregon) C. Surfleet & D. Tullos https://doi.org/10.1002/hyp.9485
12. A simple scheme to adjust Poisson cluster rectangular pulse rainfall models for improved performance at sub-hourly timescales J. Park et al. https://doi.org/10.1016/j.jhydrol.2021.126296
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14. Parameter conditioning and prediction uncertainties of the LISFLOOD-WB distributed hydrological model X. MO et al. https://doi.org/10.1623/hysj.51.1.45
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21. Uncertainty in the impacts of projected climate change on the hydrology of a subarctic environment: Liard River Basin R. Thorne https://doi.org/10.5194/hess-15-1483-2011
22. Toward a statistical framework to quantify the uncertainties of hydrologic response under climate change S. Steinschneider et al. https://doi.org/10.1029/2011WR011318
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25. Inferring the flood frequency distribution for an ungauged basin using a spatially distributed rainfall-runoff model G. Moretti & A. Montanari https://doi.org/10.5194/hess-12-1141-2008
26. Quantitative evaluation of decadal scale climatic variability in the Chambal River Basin; focus on the Banas Badlands M. Gupta & M. Resmi https://doi.org/10.1007/s00382-025-07756-y
27. Predicting river flows for future climates using an autoregressive multinomial logit model N. Augustin et al. https://doi.org/10.1029/2006WR005127
28. Assessing the results of scenarios of climate and land use changes on the hydrology of an Italian catchment: modelling study D. D'Agostino et al. https://doi.org/10.1002/hyp.7765
29. Impact of climate change on flood characteristics in Brahmaputra basin using a macro-scale distributed hydrological model S. GHOSH & S. DUTTA https://doi.org/10.1007/s12040-012-0181-y
30. Towards a coherent philosophy for modelling the environment K. Beven https://doi.org/10.1098/rspa.2002.0986
31. IMPACT OF CLIMATE AND LAND USE CHANGES ON THE FLOOD CHARACTERISTICS OF THE BRAHMAPUTRA BASIN S. Ghosh & S. Dutta https://doi.org/10.1080/09715010.2011.10515058
32. Why continuous simulation? The role of antecedent moisture in design flood estimation S. Pathiraja et al. https://doi.org/10.1029/2011WR010997
33. Assessment on Flood Characteristics Changes Using Multi-GCMs Climate Scenario K. Son et al. https://doi.org/10.3741/JKWRA.2010.43.9.789
34. An event simulation approach to the assessment of flood level frequencies: risk maps for the Warsaw reach of the River Vistula R. Romanowicz & A. Kiczko https://doi.org/10.1002/hyp.10857
35. Spectral representation of the annual cycle in the climate change signal T. Bosshard et al. https://doi.org/10.5194/hess-15-2777-2011
36. Geospatial mapping of flood susceptibility and hydro-geomorphic response to the floods in Ulhas basin, India S. Das https://doi.org/10.1016/j.rsase.2019.02.006
37. Flood Risk Assessment, Future Trend Modeling, and Risk Communication: A Review of Ongoing Research A. Salman & Y. Li https://doi.org/10.1061/(ASCE)NH.1527-6996.0000294
38. Current concepts in nitrogen dynamics for mesoscale catchments L. BREUER et al. https://doi.org/10.1623/hysj.53.5.1059
39. Global evidence that deforestation amplifies flood risk and severity in the developing world C. BRADSHAW et al. https://doi.org/10.1111/j.1365-2486.2007.01446.x
40. Generating Continuous Rainfall Time Series with High Temporal Resolution by Using a Stochastic Rainfall Generator with a Copula and Modified Huff Rainfall Curves D. Nguyen & S. Chen https://doi.org/10.3390/w14132123
41. Assessment of Flood Frequency Alteration by Dam Construction via SWAT Simulation J. Lee et al. https://doi.org/10.3390/w9040264
42. Probabilistic Design Storm Method for Improved Flood Estimation in Ungauged Catchments M. Berk et al. https://doi.org/10.1002/2017WR020947
43. An Overview of Flood Risk Analysis Methods D. Diaconu et al. https://doi.org/10.3390/w13040474
44. Climate change and probabilistic scenario of streamflow extremes in an alpine region T. Yang et al. https://doi.org/10.1002/2014JD021824
45. Regional assessment of forest effect on watershed hydrology: Slovakia as a case study T. Hlásny et al. https://doi.org/10.17221/55/2013-JFS
46. Future variability in groundwater-surface water interactions: Implications for streamflow and its components using SWAT-MODFLOW 6 and CMIP 6 projections S. Lee et al. https://doi.org/10.1016/j.jhydrol.2025.134511
47. A manifesto for the equifinality thesis K. Beven https://doi.org/10.1016/j.jhydrol.2005.07.007
48. Modelling storage‐driven connectivity between landscapes and riverscapes: towards a simple framework for long‐term ecohydrological assessment C. Soulsby et al. https://doi.org/10.1002/hyp.10862
49. Assessing the impact of flood inundation dynamics on an urban environment P. Gao et al. https://doi.org/10.1007/s11069-021-04868-6
50. Nonstationarity in Flood Time Series G. Gül et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000923
51. Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China J. Yang et al. https://doi.org/10.1016/j.jhydrol.2008.05.012
52. Dynamic TOPMODEL: A new implementation in R and its sensitivity to time and space steps P. Metcalfe et al. https://doi.org/10.1016/j.envsoft.2015.06.010
53. Climate change and fluvial flood risk in the UK: more of the same? R. Wilby et al. https://doi.org/10.1002/hyp.6847
54. Quantifying Uncertainties in Extreme Flood Predictions under Climate Change for a Medium-Sized Basin in Northeastern China W. Qi et al. https://doi.org/10.1175/JHM-D-15-0212.1
55. 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
56. Comparison of uncertainty sources for climate change impacts: flood frequency in England A. Kay et al. https://doi.org/10.1007/s10584-008-9471-4
57. Uncertainty Estimation Using the Glue and Bayesian Approaches in Flood Estimation: A case Study—Ba River, Vietnam P. Cu Thi et al. https://doi.org/10.3390/w10111641
58. Incorporating climate change in flood estimation guidance C. Wasko et al. https://doi.org/10.1098/rsta.2019.0548
59. Monte Carlo Assessment of Sampling Uncertainty of Climate Change Impacts on Water Resources Yield in Yorkshire, England N. Nawaz & A. Adeloye https://doi.org/10.1007/s10584-005-9043-9
60. Water Resource Vulnerability Characteristics by District’s Population Size in a Changing Climate Using Subjective and Objective Weights E. Chung et al. https://doi.org/10.3390/su6096141
61. A framework for assessing flood frequency based on climate projection information D. Raff et al. https://doi.org/10.5194/hess-13-2119-2009
62. Large sample behaviors of the generalized likelihood uncertainty estimation (GLUE) in assessing the uncertainty of rainfall‐runoff simulations A. Montanari https://doi.org/10.1029/2004WR003826
63. A limits of acceptability approach to model evaluation and uncertainty estimation in flood frequency estimation by continuous simulation: Skalka catchment, Czech Republic S. Blazkova & K. Beven https://doi.org/10.1029/2007WR006726
64. Role of Watershed Geomorphic Characteristics on Flooding in Indiana, United States K. Ahn & V. Merwade https://doi.org/10.1061/(ASCE)HE.1943-5584.0001289
65. A review of climate risk information for adaptation and development planning R. Wilby et al. https://doi.org/10.1002/joc.1839
66. Sensitivity of Catchment Transit Times to Rainfall Variability Under Present and Future Climates D. Wilusz et al. https://doi.org/10.1002/2017WR020894
67. Estimating the annual runoff frequency distribution based on climatic conditions and catchment characteristics: A case study across China Z. Liu et al. https://doi.org/10.1016/j.iswcr.2022.06.001
68. Assessment of antecedent moisture condition on flood frequency: An experimental study in Napa River Basin, CA J. Kim et al. https://doi.org/10.1016/j.ejrh.2019.100629
69. The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments S. Bastola et al. https://doi.org/10.1016/j.advwatres.2011.01.008
70. Have applications of continuous rainfall–runoff simulation realized the vision for process‐based flood frequency analysis? R. Lamb et al. https://doi.org/10.1002/hyp.10882
71. Process-based design flood estimation in ungauged basins by conditioning model parameters on regional hydrological signatures D. Biondi & D. De Luca https://doi.org/10.1007/s11069-015-1889-1
72. Spatial Mapping of Flood Susceptibility Using Decision Tree–Based Machine Learning Models for the Vembanad Lake System in Kerala, India P. Kulithalai Shiyam Sundar & S. Kundapura https://doi.org/10.1061/JWRMD5.WRENG-5858
73. The impact of future climate change on seasonal discharge, hydrological processes and extreme flows in the Upper Wye experimental catchment, Mid‐Wales C. Pilling & J. Jones https://doi.org/10.1002/hyp.1057
74. Ignorance is bliss: Or seven reasons not to use uncertainty analysis F. Pappenberger & K. Beven https://doi.org/10.1029/2005WR004820
75. A generalised likelihood uncertainty estimation mixed-integer programming model: Application to a water resource distribution network G. Chagwiza et al. https://doi.org/10.1080/23311835.2015.1048076
76. A process‐based insight into nonstationarity of the probability distribution of annual runoff C. Jiang et al. https://doi.org/10.1002/2016WR019863
77. How the performance of hydrological models relates to credibility of projections under climate change V. Krysanova et al. https://doi.org/10.1080/02626667.2018.1446214
78. Flood frequency estimation by continuous simulation of subcatchment rainfalls and discharges with the aim of improving dam safety assessment in a large basin in the Czech Republic S. Blazkova & K. Beven https://doi.org/10.1016/j.jhydrol.2003.12.025
79. Impact of Climate and Land Use Changes on the Flood Hazard of the Middle Brahmaputra Reach, India S. Dutta & S. Ghosh https://doi.org/10.20965/jdr.2012.p0573
80. Long Term Distributed Rainfall Runoff Analysis and Its Application to River Planning T. YAMAMOTO & M. LU https://doi.org/10.3178/jjshwr.22.198
81. On the Use of Satellite Rainfall Data to Design a Dam in an Ungauged Site C. Bertini et al. https://doi.org/10.3390/w12113028
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83. Use of daily precipitation uncertainties in streamflow simulation and forecast Y. Hwang et al. https://doi.org/10.1007/s00477-011-0460-1
84. Epistemic uncertainties and natural hazard risk assessment – Part 1: A review of different natural hazard areas K. Beven et al. https://doi.org/10.5194/nhess-18-2741-2018
85. Hydrological climate change impact assessment in high latitudes: are bucket-type models up to the task? A. Todorović et al. https://doi.org/10.1016/j.envsoft.2026.106964
86. Identification of rainfall–runoff models for operational applications / Identification de modèles pluie–débit pour des applications opérationnelles T. Wagener & N. McIntyre https://doi.org/10.1623/hysj.2005.50.5.735
87. Assessment of the climate change impacts on flood frequency (case study: Bazoft Basin, Iran) P. Almasi & S. Soltani https://doi.org/10.1007/s00477-016-1263-1
88. The effects of future nationwide forest transition to discharge in the 21st century with regard to general circulation model climate change scenarios G. Mouri et al. https://doi.org/10.1016/j.envres.2016.01.024
89. A stochastic approach for assessing the uncertainty of rainfall‐runoff simulations A. Montanari & A. Brath https://doi.org/10.1029/2003WR002540
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91. Assessment of Changes in Flood Frequency Due to the Effects of Climate Change: Implications for Engineering Design F. Quintero et al. https://doi.org/10.3390/hydrology5010019
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