171 citations as recorded by crossref.

1. Water allocation using game theory under climate change impact (case study: Zarinehrood) H. Hemati & A. Abrishamchi https://doi.org/10.2166/wcc.2020.153
2. Comparing statistical post-processing of regional and global climate scenarios for hydrological impacts assessment: A case study of two Canadian catchments M. Troin et al. https://doi.org/10.1016/j.jhydrol.2014.11.047
3. Direct and component-wise bias correction of multi-variate climate indices: the percentile adjustment function diagnostic tool A. Casanueva et al. https://doi.org/10.1007/s10584-018-2167-5
4. Uneven shifts in flood and drought flows in a Brazilian water supply catchment T. Mattos et al. https://doi.org/10.1016/j.ejrh.2025.102498
5. Modeling future changes in the North-Estonian hydropower production by using SWAT O. Tamm et al. https://doi.org/10.2166/nh.2015.018
6. Future Riverine Inorganic Nitrogen Load to the Baltic Sea From Sweden: An Ensemble Approach to Assessing Climate Change Effects C. Teutschbein et al. https://doi.org/10.1002/2016GB005598
7. Flood hazard assessment under climate change scenarios in the Yang River Basin, Thailand S. Shrestha & W. Lohpaisankrit https://doi.org/10.1016/j.ijsbe.2016.09.006
8. The Role of Reservoir Reoperation to Mitigate Climate Change Impacts on Hydropower and Environmental Water Demands A. Dalcin et al. https://doi.org/10.1061/JWRMD5.WRENG-5810
9. Analysis of Rainfall-Runoff Characteristics on Bias Correction Method of Climate Change Scenarios D. Kum et al. https://doi.org/10.15681/KSWE.2015.31.3.241
10. A simple method of bias correction for GCM derived streamflow at catchment scale S. Islam et al. https://doi.org/10.1080/02626667.2023.2218036
11. Global warming increases the frequency of river floods in Europe L. Alfieri et al. https://doi.org/10.5194/hess-19-2247-2015
12. Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario I. Shkolnik et al. https://doi.org/10.1007/s00382-017-3600-6
13. Modelling climate change impacts on nutrients and primary production in coastal waters M. Pesce et al. https://doi.org/10.1016/j.scitotenv.2018.02.131
14. Assessing the impacts of climate change on river flows in England using the UKCP09 climate change projections M. Charlton & N. Arnell https://doi.org/10.1016/j.jhydrol.2014.09.008
15. Evaluating the Time-Invariance Hypothesis of Climate Model Bias Correction: Implications for Hydrological Impact Studies J. Velázquez et al. https://doi.org/10.1175/JHM-D-14-0159.1
16. Using dry and wet year hydroclimatic extremes to guide future hydrologic projections S. Oni et al. https://doi.org/10.5194/hess-20-2811-2016
17. Asynchronous Hydroclimatic Modeling for the Construction of Physically Based Streamflow Projections in a Context of Observation Scarcity S. Ricard et al. https://doi.org/10.3389/feart.2020.556781
18. Evaluating Hydroclimatic Change Signals from Statistically and Dynamically Downscaled GCMs and Hydrologic Models R. Shrestha et al. https://doi.org/10.1175/JHM-D-13-030.1
19. Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions? C. Teutschbein & J. Seibert https://doi.org/10.5194/hess-17-5061-2013
20. Multi-criteria hybrid-based bias correction selection, and machine learning ensemble modeling to improve extreme climate event projections in the Tendaho Catchment, Ethiopia A. Guyasa et al. https://doi.org/10.1007/s00704-025-05908-y
21. Hydrology and hydrological extremes under climate change scenarios in the Bosque watershed, North-Central Texas, USA G. Tefera & R. Ray https://doi.org/10.1007/s11356-023-27477-1
22. Climate change impacts on seasonal runoff in the source region of the Yellow River: Insights from CORDEX experiments with uncertainty analysis Y. Gao et al. https://doi.org/10.1016/j.jhydrol.2024.132132
23. Simulated future changes of extreme nutrient loads in a mesoscale agricultural watershed in Bavaria / Simulierte zukünftige Änderungen der Extremwerte für Nährstofffrachten in einem mesoskaligen landwirtschaftlichen Einzugsgebiet in Bayern B. Mehdi et al. https://doi.org/10.1515/boku-2016-0008
24. Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes M. Switanek et al. https://doi.org/10.5194/hess-21-2649-2017
25. Global projections of river flood risk in a warmer world L. Alfieri et al. https://doi.org/10.1002/2016EF000485
26. Appraisal of Climate Change and Its Impact on Water Resources of Pakistan: A Case Study of Mangla Watershed H. Haider et al. https://doi.org/10.3390/atmos11101071
27. Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective K. Kim et al. https://doi.org/10.1016/j.jhydrol.2021.127261
28. Impact of Reference Dataset Selection on RCM Evaluation, Bias Correction, and Resulting Climate Change Signals of Precipitation D. Gampe et al. https://doi.org/10.1175/JHM-D-18-0108.1
29. Risk assessment in water resources planning under climate change at the Júcar River basin S. Suárez-Almiñana et al. https://doi.org/10.5194/hess-24-5297-2020
30. Climate Change Impact Studies: Should We Bias Correct Climate Model Outputs or Post‐Process Impact Model Outputs? J. Chen et al. https://doi.org/10.1029/2020WR028638
31. Added value of dynamical downscaling for hydrological projections in the Chungju Basin, Korea M. Lee et al. https://doi.org/10.1002/joc.5825
32. Demonstrating the bias-correction impact on regional climate model (RegCM) over the Democratic People’s Republic of Korea: Implication for temperature and precipitation K. Jo & K. Pak https://doi.org/10.1007/s12040-022-01836-x
33. Remaining error sources in bias-corrected climate model outputs J. Chen et al. https://doi.org/10.1007/s10584-020-02744-z
34. CHASE-PL Climate Projection dataset over Poland – bias adjustment of EURO-CORDEX simulations A. Mezghani et al. https://doi.org/10.5194/essd-9-905-2017
35. Using raw regional climate model outputs for quantifying climate change impacts on hydrology J. Chen et al. https://doi.org/10.1002/hyp.11368
36. Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? A. Cannon et al. https://doi.org/10.1175/JCLI-D-14-00754.1
37. Future Runoff Analysis in the Mekong River Basin under a Climate Change Scenario Using Deep Learning D. Lee et al. https://doi.org/10.3390/w12061556
38. Using reanalysis‐driven regional climate model outputs for hydrology modelling J. Chen et al. https://doi.org/10.1002/hyp.13251
39. Sensitivity of Glacier Runoff to Winter Snow Thickness Investigated for Vatnajökull Ice Cap, Iceland, Using Numerical Models and Observations L. Schmidt et al. https://doi.org/10.3390/atmos9110450
40. Groundwater Risk Assessment in Imo River Basin of Southeastern Nigeria Using GIS-Based DRASTIC and GOD T. Emberga et al. https://doi.org/10.1007/s41101-023-00210-2
41. Assessing climate change impact on flood discharge in South America and the influence of its main drivers J. Brêda et al. https://doi.org/10.1016/j.jhydrol.2023.129284
42. Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction M. Vrac https://doi.org/10.5194/hess-22-3175-2018
43. Assessing the Influence of a Bias Correction Method on Future Climate Scenarios Using SWAT as an Impact Model Indicator T. Brighenti et al. https://doi.org/10.3390/w15040750
44. Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model E. Gelati et al. https://doi.org/10.5194/hess-22-2091-2018
45. Risk Analysis Related to Impact of Climate Change on Water Resources and Hydropower Production in the Lusatian Neisse River Basin M. Adynkiewicz-Piragas & B. Miszuk https://doi.org/10.3390/su12125060
46. How do potential evapotranspiration formulas influence hydrological projections? G. Seiller & F. Anctil https://doi.org/10.1080/02626667.2015.1100302
47. Uncertainty of Rainfall Products: Impact on Modelling Household Nutrition from Rain-Fed Agriculture in Southern Africa R. Luetkemeier et al. https://doi.org/10.3390/w10040499
48. Correcting for systematic biases in GCM simulations in the frequency domain H. Nguyen et al. https://doi.org/10.1016/j.jhydrol.2016.04.018
49. Effects of climate change on shallow landslides in a small coastal catchment in southern Italy F. Ciervo et al. https://doi.org/10.1007/s10346-016-0743-1
50. A Signal Processing Approach to Correct Systematic Bias in Trend and Variability in Climate Model Simulations C. Kusumastuti et al. https://doi.org/10.1029/2021GL092953
51. Modelling hydrological processes under climate change scenarios in the Jemma sub-basin of upper Blue Nile Basin, Ethiopia G. Worku et al. https://doi.org/10.1016/j.crm.2021.100272
52. A Decade of Climate Scenarios: The Ouranos Consortium Modus Operandi D. Huard et al. https://doi.org/10.1175/BAMS-D-12-00163.1
53. Impact of downscaled rainfall biases on projected runoff changes S. Charles et al. https://doi.org/10.5194/hess-24-2981-2020
54. Climate Change Impact on the Magnitude and Timing of Hydrological Extremes Across Great Britain R. Lane & A. Kay https://doi.org/10.3389/frwa.2021.684982
55. A comprehensive comparison of bias correction methods in climate model simulations: Application on ERA5-Land across different temporal resolutions P. Dhawan et al. https://doi.org/10.1016/j.heliyon.2024.e40352
56. The ClimEx Project: A 50-Member Ensemble of Climate Change Projections at 12-km Resolution over Europe and Northeastern North America with the Canadian Regional Climate Model (CRCM5) M. Leduc et al. https://doi.org/10.1175/JAMC-D-18-0021.1
57. The evaluation of the potential of global data products for snow hydrological modelling in ungauged high-alpine catchments M. Weber et al. https://doi.org/10.5194/hess-25-2869-2021
58. Comparison of potential future impacts of climate change on Streamflows in tropical and subtropical watersheds I. Chathuranika & D. Ismael https://doi.org/10.1016/j.ecohyd.2025.100699
59. Climate change impact on water resources availability: case study of the Llobregat River basin (Spain) P. Versini et al. https://doi.org/10.1080/02626667.2016.1154556
60. Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm L. Gao et al. https://doi.org/10.1155/2014/472741
61. Assessing silvicultural treatment effects on catchment hydrology under current and future climate scenarios J. García-Hernández et al. https://doi.org/10.1016/j.agrformet.2026.111523
62. Evaluating the impacts of climate change and crop land use change on streamflow, nitrates and phosphorus: A modeling study in Bavaria B. Mehdi et al. https://doi.org/10.1016/j.ejrh.2015.04.009
63. Can direct CMIP6 model simulations reproduce mean annual historical streamflow change? Q. Huang et al. https://doi.org/10.1016/j.catena.2023.107650
64. Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts L. Crochemore et al. https://doi.org/10.5194/hess-20-3601-2016
65. The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models R. Nijzink et al. https://doi.org/10.5194/hess-20-1151-2016
66. Impact of climate change on the flow of the Doce River basin F. Costa et al. https://doi.org/10.1590/2318-0331.272220220069
67. Hydrologic Model Evaluation and Assessment of Projected Climate Change Impacts Using Bias-Corrected Stream Flows J. Daraio https://doi.org/10.3390/w12082312
68. SABER: A Model-Agnostic Postprocessor for Bias Correcting Discharge from Large Hydrologic Models R. Hales et al. https://doi.org/10.3390/hydrology9070113
69. Modeling the Impact of Climate and Land Use/Land Cover Change on Water Availability in an Inland Valley Catchment in Burkina Faso M. Idrissou et al. https://doi.org/10.3390/hydrology9010012
70. Impacts of climate change on the seasonality of low flows in 134 catchments in the River Rhine basin using an ensemble of bias-corrected regional climate simulations M. Demirel et al. https://doi.org/10.5194/hess-17-4241-2013
71. Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed B. Mehdi et al. https://doi.org/10.1007/s11269-017-1830-3
72. Producing reliable hydrologic scenarios from raw climate model outputs without resorting to meteorological observations S. Ricard et al. https://doi.org/10.5194/hess-27-2375-2023
73. A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 °C, 2 °C and 3 °C S. Gosling et al. https://doi.org/10.1007/s10584-016-1773-3
74. Hydrological impacts of climate change on small ungauged catchments – results from a global climate model–regional climate model–hydrologic model chain A. Tsegaw et al. https://doi.org/10.5194/nhess-20-2133-2020
75. A Bayesian framework for uncertainty quantification of rainfall Intensity–Duration–Frequency (IDF) curves B. Takhellambam et al. https://doi.org/10.1016/j.atmosres.2026.109165
76. Bias correction of global and regional simulated daily precipitation and surface mean temperature over Southeast Asia using quantile mapping method S. Ngai et al. https://doi.org/10.1016/j.gloplacha.2016.12.009
77. Assessing atmospheric bias correction for dynamical consistency using potential vorticity E. Rocheta et al. https://doi.org/10.1088/1748-9326/9/12/124010
78. Bias adjustment for threshold-based climate indicators P. Hoffmann et al. https://doi.org/10.5194/asr-15-107-2018
79. Bias correction methods for regional climate model simulations considering the distributional parametric uncertainty underlying the observations K. Kim et al. https://doi.org/10.1016/j.jhydrol.2015.10.015
80. Establishing a Range of Extreme Precipitation Estimates in California for Planning in the Face of Climate Change D. Feldman et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001410
81. Regional climate models' performance in representing precipitation and temperature over selected Mediterranean areas R. Deidda et al. https://doi.org/10.5194/hess-17-5041-2013
82. Long-term flood risk assessment of watersheds under climate change based on the game cross-efficiency DEA Q. Su https://doi.org/10.1007/s11069-020-04269-1
83. The influence of natural variability and interpolation errors on bias characterization in RCM simulations N. Addor & E. Fischer https://doi.org/10.1002/2014JD022824
84. Assessing uncertainty of hydrological and ecological parameters originating from the application of an ensemble of ten global-regional climate model projections in a coastal ecosystem of the lagoon of Venice, Italy M. Pesce et al. https://doi.org/10.1016/j.ecoleng.2019.04.011
85. 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. https://doi.org/10.1016/j.jhydrol.2023.129807
86. An Integrated Statistical Method to Generate Potential Future Climate Scenarios to Analyse Droughts A. Collados-Lara et al. https://doi.org/10.3390/w10091224
87. Forcing the Penman-Montheith Formulation with Humidity, Radiation, and Wind Speed Taken from Reanalyses, for Hydrologic Modeling S. Ricard & F. Anctil https://doi.org/10.3390/w11061214
88. Future water resources and droughts in the Atlas Mountains of Morocco under a high-emission climate scenario O. Lahnik et al. https://doi.org/10.1016/j.ejrh.2025.102371
89. A comparison of methods for estimating climate change impact on design rainfall using a high-resolution RCM J. Li et al. https://doi.org/10.1016/j.jhydrol.2017.02.019
90. Assessment of Climate Change Impact on Water Requirement and Rice Productivity K. N’guessan et al. https://doi.org/10.1016/j.rsci.2023.03.010
91. Improving Future Estimation of Cheliff-Mactaa-Tafna Streamflow via an Ensemble of Bias Correction Approaches M. Renima et al. https://doi.org/10.3390/cli10080123
92. Sensitivity of future continental United States water deficit projections to general circulation models, the evapotranspiration estimation method, and the greenhouse gas emission scenario S. Chang et al. https://doi.org/10.5194/hess-20-3245-2016
93. Impact of bias adjustment strategy on ensemble projections of hydrological extremes P. Astagneau et al. https://doi.org/10.5194/hess-29-5695-2025
94. Simulating streamflow in ungauged basins under a changing climate: The importance of landscape characteristics C. Teutschbein et al. https://doi.org/10.1016/j.jhydrol.2018.03.060
95. Assessing future changes in hydroclimatic processes in the Metropolitan Region of Belo Horizonte, Brazil, with the expanded Bluecat framework L. Santos et al. https://doi.org/10.3389/frwa.2025.1541052
96. Developing tailored climate change scenarios for hydrological impact assessments V. Ntegeka et al. https://doi.org/10.1016/j.jhydrol.2013.11.001
97. Advancing global hydrologic modeling with the GEOGloWS ECMWF streamflow service R. Hales et al. https://doi.org/10.1111/jfr3.12859
98. Climate change impacts on ecologically relevant hydrological indicators in three catchments in three European ecoregions J. Kiesel et al. https://doi.org/10.1016/j.ecoleng.2018.12.019
99. Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods D. Kum et al. https://doi.org/10.1155/2014/704151
100. Quantifying the influence of climate change on streamflow of Rietspruit sub-basin, South Africa V. Banda et al. https://doi.org/10.2166/wcc.2024.690
101. Variable resolution modeling of near future mean temperature changes in the dry sub-humid region of Ghana E. Bessah et al. https://doi.org/10.1007/s40808-018-0479-0
102. Multivariate—Intervariable, Spatial, and Temporal—Bias Correction* M. Vrac & P. Friederichs https://doi.org/10.1175/JCLI-D-14-00059.1
103. Bias-adjusted projections of snow cover over eastern Canada using an ensemble of regional climate models É. Bresson et al. https://doi.org/10.5194/tc-20-333-2026
104. Climate change impacts on South American water balance from a continental-scale hydrological model driven by CMIP5 projections J. Brêda et al. https://doi.org/10.1007/s10584-020-02667-9
105. Incorporating hydrology into climate suitability models changes projections of malaria transmission in Africa M. Smith et al. https://doi.org/10.1038/s41467-020-18239-5
106. A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions C. Schürz et al. https://doi.org/10.5194/hess-23-1211-2019
107. Impact of Climate Change on the Hydrological Regimes in Bavaria B. Poschlod et al. https://doi.org/10.3390/w12061599
108. Balancing trade-offs between ecosystem services in Germany’s forests under climate change M. Gutsch et al. https://doi.org/10.1088/1748-9326/aab4e5
109. Future Climate and Land Use Change Impacts on River Flows in the Tapajós Basin in the Brazilian Amazon F. Farinosi et al. https://doi.org/10.1029/2019EF001198
110. Physically-based distributed modelling of the hydrology and soil erosion under changes in landuse and climate of a humid tropical river basin S. Sreedevi et al. https://doi.org/10.1016/j.catena.2022.106427
111. Projected Changes in the Water Budget for Eastern Colombia Due to Climate Change O. Molina et al. https://doi.org/10.3390/w12010065
112. Hydrological response to changing climate conditions: Spatial streamflow variability in the boreal region C. Teutschbein et al. https://doi.org/10.1002/2015WR017337
113. Climate projections of a multivariate heat stress index: the role of downscaling and bias correction A. Casanueva et al. https://doi.org/10.5194/gmd-12-3419-2019
114. Development of daily downscaled, bias-corrected CMIP6 climate datasets for estimating reference evapotranspiration (ETo) in South Asia A. Saha et al. https://doi.org/10.1038/s41597-025-06149-4
115. Climate change and its effects on the streamflow of an Andean river basin with volcanic activity H. Salas et al. https://doi.org/10.2166/wcc.2023.340
116. Trends in projections of standardized precipitation indices in a future climate in Poland M. Osuch et al. https://doi.org/10.5194/hess-20-1947-2016
117. Trends and climate change analysis for common climate variables in Gelgel Belese Watershed, Upper Blue Nile Basin, Ethiopia K. Shitu et al. https://doi.org/10.1007/s00704-023-04568-0
118. Projected frequency of low to high-intensity rainfall events over India using bias-corrected CORDEX models A. Boyaj et al. https://doi.org/10.1016/j.atmosres.2024.107760
119. Multisite bias correction of precipitation data from regional climate models J. Hnilica et al. https://doi.org/10.1002/joc.4890
120. Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (upper Clutha River, New Zealand) A. Jobst et al. https://doi.org/10.5194/hess-22-3125-2018
121. Assessing the limits of bias‐correcting climate model outputs for climate change impact studies J. Chen et al. https://doi.org/10.1002/2014JD022635
122. Downscaling and correction of regional climate models outputs with a hybrid geostatistical approach L. Poggio & A. Gimona https://doi.org/10.1016/j.spasta.2015.04.006
123. The Influence of Climate Model Biases on Projections of Aridity and Drought D. Ficklin et al. https://doi.org/10.1175/JCLI-D-15-0439.1
124. Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models O. Kisi et al. https://doi.org/10.1080/02626667.2019.1632460
125. Comparing Meteorological Data Sets in the Evaluation of Climate Change Impact on Hydrological Indicators: A Case Study on a Mexican Basin J. Velázquez-Zapata https://doi.org/10.3390/w11102110
126. Reduction of the uncertainties in the hydrological projections in Korean river basins using dynamically downscaled climate projections L. Qiu et al. https://doi.org/10.1007/s00382-022-06201-8
127. A Holistic Modelling Approach for the Estimation of Return Levels of Peak Flows in Bavaria F. Willkofer et al. https://doi.org/10.3390/w12092349
128. Regional hydrologic response to climate change in the conterminous United States using high-resolution hydroclimate simulations B. Naz et al. https://doi.org/10.1016/j.gloplacha.2016.06.003
129. Bias Correction and Evaluation of Precipitation Data from the CORDEX Regional Climate Model for Monitoring Climate Change in the Wadi Chemora Basin (Northeastern Algeria) S. Derdour et al. https://doi.org/10.3390/atmos13111876
130. An R package for assessment of statistical downscaling methods for hydrological climate change impact studies M. Hanel et al. https://doi.org/10.1016/j.envsoft.2017.03.036
131. Variabilidad del impacto del cambio climático en el régimen hidrológico de dos cuencas de la región Huasteca J. Velázquez Zapata et al. https://doi.org/10.22201/fi.25940732e.2020.21.3.021
132. Evaluating the uncertainty of climate model structure and bias correction on the hydrological impact of projected climate change in a Mediterranean catchment A. Senatore et al. https://doi.org/10.1016/j.ejrh.2022.101120
133. Assessment of Climate Change Impact on Water Resources in the Upper Senegal Basin (West Africa) M. Mbaye et al. https://doi.org/10.4236/ajcc.2015.41008
134. Improving the Reliability and Added Value of Dynamical Downscaling via Correction of Large‐Scale Errors: A Norwegian Perspective M. Pontoppidan et al. https://doi.org/10.1029/2018JD028372
135. An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment P. Smitha et al. https://doi.org/10.1016/j.jhydrol.2017.11.010
136. Long-term sustainability of large water resource systems under climate change: A cascade modeling approach D. Haro-Monteagudo et al. https://doi.org/10.1016/j.jhydrol.2020.124546
137. Rectifying low-frequency variability in future climate sea surface temperature simulations: are corrections for extreme change scenarios realistic? C. Kusumastuti et al. https://doi.org/10.1088/1748-9326/accdf1
138. Dynamical downscaling and data assimilation for a cold-air outbreak in the European Alps during the Year Without a Summer of 1816 P. Stucki et al. https://doi.org/10.5194/cp-20-2327-2024
139. Projected effects of climate change in precipitation and streamflows of the Upper Orinoco River Basin from global and regional climate models H. Salas et al. https://doi.org/10.2166/wcc.2024.659
140. Impacts of Climate Change on the Hydrological Regime of the Danube River and Its Tributaries Using an Ensemble of Climate Scenarios J. Stagl & F. Hattermann https://doi.org/10.3390/w7116139
141. Quantile Mapping Bias Correction on Rossby Centre Regional Climate Models for Precipitation Analysis over Kenya, East Africa B. Ayugi et al. https://doi.org/10.3390/w12030801
142. Climate projections in the Hornsund area, Southern Spitsbergen M. Osuch & T. Wawrzyniak https://doi.org/10.1515/popore-2016-0020
143. How does bias correction of regional climate model precipitation affect modelled runoff? J. Teng et al. https://doi.org/10.5194/hess-19-711-2015
144. Local‐ and landscape‐scale impacts of clear‐cuts and climate change on surface water dissolved organic carbon in boreal forests S. Oni et al. https://doi.org/10.1002/2015JG003190
145. Exploration of optimal time steps for daily precipitation bias correction: a case study using a single grid of RCM on the River Exe in southwest England K. Kim et al. https://doi.org/10.1080/02626667.2015.1027207
146. High-end climate change impact on European runoff and low flows – exploring the effects of forcing biases L. Papadimitriou et al. https://doi.org/10.5194/hess-20-1785-2016
147. Investigating the Role of Hydrological Model Parameter Uncertainties in Future Streamflow Projections V. Chilkoti et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001994
148. What is the importance of climate model bias when projecting the impacts of climate change on land surface processes? M. Liu et al. https://doi.org/10.5194/bg-11-2601-2014
149. Quantification of uncertainties in streamflow extremes in the Chaliyar river basin, India under climate change S. Ansa Thasneem et al. https://doi.org/10.1007/s00704-023-04410-7
150. Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble F. Willkofer et al. https://doi.org/10.5194/hess-28-2969-2024
151. Strong intensification of extreme fire weather in Europe under 3 °C compared to 2 °C global warming A. Bayar et al. https://doi.org/10.5194/esd-17-929-2026
152. Modeling climate and land use change impacts on the hydrology of the Tiélé catchment, Benin, West Africa Q. Togbévi et al. https://doi.org/10.1007/s40808-026-02744-5
153. Impacts of climate change on global total and urban runoff L. Gray et al. https://doi.org/10.1016/j.jhydrol.2023.129352
154. Ensemble flood risk assessment in Europe under high end climate scenarios L. Alfieri et al. https://doi.org/10.1016/j.gloenvcha.2015.09.004
155. Impact of climate change on hydrological conditions in a tropical West African catchment using an ensemble of climate simulations Y. Yira et al. https://doi.org/10.5194/hess-21-2143-2017
156. WITHDRAWN: Intercomparison of joint bias correction methods for precipitation and flow from a hydrological perspective K. Kim et al. https://doi.org/10.1016/j.hydroa.2021.100109
157. Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China L. Zhang et al. https://doi.org/10.1016/j.atmosres.2020.105331
158. Projection of runoff characteristics as a response to regional climate change in a Central/Eastern European catchment A. Kis et al. https://doi.org/10.1080/02626667.2020.1798008
159. Hydrological Modelling and Climate Adaptation under Changing Climate: A Review with a Focus in Sub-Saharan Africa V. Banda et al. https://doi.org/10.3390/w14244031
160. The Impact of Meteorological and Hydrological Memory on Compound Peak Flows in the Rhine River Basin S. Khanal et al. https://doi.org/10.3390/atmos10040171
161. Climate change impacts on future snow, ice and rain runoff in a Swiss mountain catchment using multi-dataset calibration S. Etter et al. https://doi.org/10.1016/j.ejrh.2017.08.005
162. Future drought propagation through the water-energy-food-ecosystem nexus – A Nordic perspective C. Teutschbein et al. https://doi.org/10.1016/j.jhydrol.2022.128963
163. Climate and hydrological models to assess the impact of climate change on hydrological regime: a review R. Kour et al. https://doi.org/10.1007/s12517-016-2561-0
164. Evaluation of impacts of future climate change and water use scenarios on regional hydrology S. Chang et al. https://doi.org/10.5194/hess-22-4793-2018
165. Review of bias correction methods for climate model outputs in hydrology A. Menapace et al. https://doi.org/10.1016/j.jhydrol.2025.133213
166. Adjusting spatial dependence of climate model outputs with cycle-consistent adversarial networks B. François et al. https://doi.org/10.1007/s00382-021-05869-8
167. Propagation of biases in climate models from the synoptic to the regional scale: Implications for bias adjustment N. Addor et al. https://doi.org/10.1002/2015JD024040
168. Modeling the impact of climate change on water resources and soil erosion in a tropical catchment in Burkina Faso, West Africa F. Op de Hipt et al. https://doi.org/10.1016/j.catena.2017.11.023
169. Impacts of climate change on the hydrological cycle over France and associated uncertainties G. Dayon et al. https://doi.org/10.1016/j.crte.2018.03.001
170. Assessing extreme precipitation from a regional climate model in different spatial–temporal scales: A hydrological perspective in South America J. Brêda et al. https://doi.org/10.1002/joc.7782
171. An evaluation framework for downscaling and bias correction in climate change impact studies E. Vogel et al. https://doi.org/10.1016/j.jhydrol.2023.129693