506 citations as recorded by crossref.

1. Impact of climate change on rainfall over Mumbai using Distribution-based Scaling of Global Climate Model projections A. Rana et al. https://doi.org/10.1016/j.ejrh.2014.06.005
2. 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
3. Regional analysis of drought severity‐duration‐frequency and severity‐area‐frequency curves in the Godavari River Basin, India K. Satish Kumar et al. https://doi.org/10.1002/joc.7137
4. Improving wind power forecasting accuracy through bias correction of wind speed predictions E. Spiliotis & E. Theodorou https://doi.org/10.1016/j.seta.2025.104599
5. High-resolution bias-corrected precipitation data over South Siberia, Russia N. Voropay et al. https://doi.org/10.1016/j.atmosres.2021.105528
6. Ensemble hydrological predictions at an intraseasonal scale through a statistical–dynamical downscaling approach over southwestern Amazonia W. Gomes et al. https://doi.org/10.2166/wcc.2024.262
7. Climate Change Effects on Precipitation and Streamflow in the Mediterranean Region A. Baycan et al. https://doi.org/10.3390/w17172556
8. Assessment of climate change impacts on flood hazard potential in the Alpine Lech watershed C. Dobler et al. https://doi.org/10.1016/j.jhydrol.2012.06.027
9. 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
10. Toward the reliable use of reanalysis data as a reference for bias correction in climate models: A multivariate perspective V. de Padua & K. Ahn https://doi.org/10.1016/j.jhydrol.2024.132102
11. Synergistic impact of climate and land use land cover change dynamics on the hydrological regime of Loktak Lake catchment under CMIP6 scenarios V. Anand et al. https://doi.org/10.1016/j.ejrh.2024.101851
12. Climate Change Impacts on Catchment-Scale Extreme Rainfall Variability: Case Study of Rize Province, Turkey A. Danandeh Mehr & E. Kahya https://doi.org/10.1061/(ASCE)HE.1943-5584.0001477
13. Estimating the response of hydrological regimes to future projections of precipitation and temperature over the upper Yangtze River X. Yang et al. https://doi.org/10.1016/j.atmosres.2019.104627
14. Future challenges of terrestrial water storage over the arid regions of Central Asia Y. Peng et al. https://doi.org/10.1016/j.jag.2024.104026
15. Climate Change Impacts on Water Resources and Reservoir Management: Uncertainty and Adaptation for a Mountain Catchment in Northeast Portugal C. Carvalho-Santos et al. https://doi.org/10.1007/s11269-017-1672-z
16. High-Resolution Climate Projections for a Densely Populated Mediterranean Region M. Nashwan et al. https://doi.org/10.3390/su12093684
17. Simulating Future Flows and Salinity Intrusion Using Combined One- and Two-Dimensional Hydrodynamic Modelling—The Case of Hau River, Vietnamese Mekong Delta D. Tran Anh et al. https://doi.org/10.3390/w10070897
18. Spatiotemporal bias adjustment of IMERG satellite precipitation data across Canada S. Moazami et al. https://doi.org/10.1016/j.advwatres.2022.104300
19. Assessment of solar geoengineering impact on precipitation and temperature extremes in the Muda River Basin, Malaysia using CMIP6 SSP and GeoMIP6 G6 simulations M. Tan et al. https://doi.org/10.1016/j.scitotenv.2024.174817
20. Occurrence of venlafaxine, other antidepressants and selected metabolites in the Rhine catchment in the face of climate change M. Schlüsener et al. https://doi.org/10.1016/j.envpol.2014.09.019
21. Projected Climate-Driven Shifts in Maize Production in Bosnia and Herzegovina: Regional Analysis Using Agroclimatic Indicators and Modelling Tools D. Soares et al. https://doi.org/10.3390/agriculture16090934
22. Addressing the challenges of climate scenario-based impact studies in modelling groundwater recharge on small barrier islands at the German North Sea coast A. Ley et al. https://doi.org/10.1016/j.ejrh.2023.101578
23. Assessment of mudflow risk in Uzbekistan using CMIP5 models G. Mamadjanova & G. Leckebusch https://doi.org/10.1016/j.wace.2021.100403
24. Climate Change Risk Management in Transnational River Basins: The Rhine S. van Pelt & R. Swart https://doi.org/10.1007/s11269-011-9891-1
25. A Proposal to Evaluate Drought Characteristics Using Multiple Climate Models for Multiple Timescales N. Tien Thanh https://doi.org/10.3390/cli6040079
26. Potential occurrence of Puccinia sorghi in corn crops in Paraná, under scenarios of climate change N. Ferreira & J. Miranda https://doi.org/10.1007/s00484-020-01880-6
27. Assessment of climate change impacts on crop and irrigation water demand in the Awash River basin of Ethiopia using CMIP6 models E. Meskelu et al. https://doi.org/10.1007/s43832-025-00307-w
28. A robust alternative for correcting systematic biases in multi-variable climate model simulations R. Mehrotra & A. Sharma https://doi.org/10.1016/j.envsoft.2021.105019
29. Simulations for CMIP6 With the AWI Climate Model AWI‐CM‐1‐1 T. Semmler et al. https://doi.org/10.1029/2019MS002009
30. Comparison of Hydrological Simulations of Climate Change Using Perturbation of Observations and Distribution‐Based Scaling L. van Roosmalen et al. https://doi.org/10.2136/vzj2010.0112
31. Transient scenarios for robust climate change adaptation illustrated for water management in The Netherlands M. Haasnoot et al. https://doi.org/10.1088/1748-9326/10/10/105008
32. 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
33. Modelling the impact of past and future climate scenarios on streamflow in a highly mountainous watershed: A case study in the West Seti River Basin, Nepal B. Bhatta et al. https://doi.org/10.1016/j.scitotenv.2020.140156
34. IWRAM: A hybrid model for irrigation water demand forecasting to quantify the impacts of climate change C. Dang et al. https://doi.org/10.1016/j.agwat.2023.108643
35. Combining Bias Correction Methods for Simulated Temperature and Precipitation by CMIP6 Models in Hamedan-Bahar Plain F. Ershadfath et al. https://doi.org/10.61186/jwmr.14.27.75
36. Seasonal and Annual Rainfall Variability and Their Impact on Rural Water Supply Services in the Wami River Basin, Tanzania S. Twisa & M. Buchroithner https://doi.org/10.3390/w11102055
37. Intensification of Extreme Rainfall in Indian River Basin: Using Bias Corrected CMIP6 Climate Data P. Chaubey & R. Mall https://doi.org/10.1029/2023EF003556
38. 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
39. Revisiting the bias correction of climate models for impact studies T. Dinh & F. Aires https://doi.org/10.1007/s10584-023-03597-y
40. Future changes in precipitation and temperature using cmip6 model based on topsis method: focus on Songhua river basin S. Chu et al. https://doi.org/10.1007/s00704-026-06127-9
41. Bias correction techniques for uncertainty reduction of long-term metocean data for ocean renewable energy systems M. Penalba et al. https://doi.org/10.1016/j.renene.2023.119404
42. TIN‐Copula bias‐correction method for model‐derived maximum temperature in the MENA region G. Lazoglou et al. https://doi.org/10.1002/joc.7364
43. Evaluation and comparison of the performances of the CMIP5 and CMIP6 models in reproducing extreme rainfall in the Upper Blue Nile basin of Ethiopia H. Belay et al. https://doi.org/10.1007/s00704-024-05187-z
44. Near-real-time forecasting of reservoir inflows using explainable machine learning and short-term weather forecasts K. Sushanth et al. https://doi.org/10.1007/s00477-023-02489-y
45. Robust assessment of future changes in extreme precipitation over the Rhine basin using a GCM S. Kew et al. https://doi.org/10.5194/hess-15-1157-2011
46. Exploring the Effect of Occurrence-Bias-Adjustment Assumptions on Hydrological Impact Modeling J. Van de Velde et al. https://doi.org/10.3390/w13111573
47. 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
48. Precision of raw and bias-adjusted satellite precipitation estimations (TRMM, IMERG, CMORPH, and PERSIANN) over extreme flood events: case study in Langat river basin, Malaysia E. Soo et al. https://doi.org/10.2166/wcc.2020.180
49. Effect of climate change on water flow and sediment flow E. Alexandre Schatz Sá et al. https://doi.org/10.26848/rbgf.v18.1.p723-740
50. On interpreting hydrological change from regional climate models L. Graham et al. https://doi.org/10.1007/s10584-006-9217-0
51. Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections N. Potter et al. https://doi.org/10.5194/hess-24-2963-2020
52. Current state of Mediterranean water resources and future trends under climatic and anthropogenic changes M. Milano et al. https://doi.org/10.1080/02626667.2013.774458
53. Streamflow response to regional climate model output in the mountainous watershed: a case study from the Swiss Alps K. Rahman et al. https://doi.org/10.1007/s12665-014-3336-0
54. Impact of bias nonstationarity on the performance of uni- and multivariate bias-adjusting methods: a case study on data from Uccle, Belgium J. Van de Velde et al. https://doi.org/10.5194/hess-26-2319-2022
55. Efficient treatment of climate data uncertainty in ensemble Kalman filter (EnKF) based on an existing historical climate ensemble dataset H. Liu et al. https://doi.org/10.1016/j.jhydrol.2018.11.047
56. Quantifying different sources of uncertainty in hydrological projections in an Alpine watershed C. Dobler et al. https://doi.org/10.5194/hess-16-4343-2012
57. Bias correction of climate model outputs influences watershed model nutrient load predictions L. Miralha et al. https://doi.org/10.1016/j.scitotenv.2020.143039
58. Influence of Rainfall Patterns on Rainfall–Runoff Processes: Indices for the Quantification of Temporal Distribution of Rainfall B. Oh et al. https://doi.org/10.3390/w16202904
59. Hydrological modeling in a region with sparsely observed data in the eastern Central Andes of Peru, Amazon L. Baltazar et al. https://doi.org/10.1016/j.jsames.2022.104151
60. Quantifying changes and drivers of runoff in the Kaidu River Basin associated with plausible climate scenarios B. Zhao et al. https://doi.org/10.1016/j.ejrh.2021.100968
61. 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
62. Enhancement of Satellite Precipitation Estimations with Bias Correction and Data-Merging Schemes for Flood Forecasting E. Soo et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002190
63. Integrating seasonal forecasts into real-time drought management: Júcar River Basin case study S. Suárez-Almiñana et al. https://doi.org/10.1016/j.ijdrr.2021.102777
64. Imprints of large‐scale climate oscillations on river flow in selected Canadian river catchments A. Olusola et al. https://doi.org/10.1002/rvr2.89
65. A Cascaded Adaptive Network-Based Fuzzy Inference System for Hydropower Forecasting N. Rathnayake et al. https://doi.org/10.3390/s22082905
66. CMIP6 model-based projections in temperature and rainfall for Ludhiana district of Punjab, India J. Singh et al. https://doi.org/10.1007/s12517-025-12349-4
67. Piecewise‐quantile mapping improves bias correction of global climate model daily precipitation towards preserving quantiles and extremes Q. Zhang et al. https://doi.org/10.1002/joc.7687
68. Using multiple climate projections for assessing hydrological response to climate change in the Thukela River Basin, South Africa L. Graham et al. https://doi.org/10.1016/j.pce.2011.07.084
69. Land use, climate, and water change in the Vietnamese Mekong Delta (VMD) using earth observation and hydrological modeling A. Mondal et al. https://doi.org/10.1016/j.ejrh.2022.101132
70. Projections of future soil temperature in northeast Iran A. Araghi et al. https://doi.org/10.1016/j.geoderma.2019.04.034
71. A satellite-based approach to estimating spatially distributed groundwater recharge rates in a tropical wet sedimentary region despite cloudy conditions L. Barbosa et al. https://doi.org/10.1016/j.jhydrol.2022.127503
72. Bias correction of modelled precipitation from CORDEX-CORE experiments over the Upper Teesta River Basin S. Guchhait et al. https://doi.org/10.1007/s00382-023-07043-8
73. Novel bias correction framework for CMIP6 climate projections over Sri Lanka and streamflow impacts in the Malwathu River Basin S. Vasanthakumar et al. https://doi.org/10.1007/s40808-026-02858-w
74. Modelling the climate change impacts on river discharge and inundation extent in the Magdalena River basin – Colombia A. Munar et al. https://doi.org/10.1080/02626667.2023.2215932
75. Predicting integrated effects of subsurface drainage and climate change on water balance and nitrate losses S. Ziaeifar et al. https://doi.org/10.1007/s13201-025-02561-8
76. Impact and uncertainties of climate change on the hydrology of the Mara River basin, Kenya/Tanzania S. Dessu & A. Melesse https://doi.org/10.1002/hyp.9434
77. Prediction of climate variables by comparing the knearest neighbor method and MIROC5 outputs in an arid environment H. Golkar Hamzee Yazd et al. https://doi.org/10.3354/cr01545
78. Evaluation of four bias correction methods and random forest model for climate change projection in the Mara River Basin, East Africa P. das et al. https://doi.org/10.2166/wcc.2022.299
79. Applicability of ERA5 Reanalysis Precipitation Data in Runoff Modeling in China’s Ili River Basin Z. Li et al. https://doi.org/10.1061/JHYEFF.HEENG-6161
80. Climate-adaptive urban drainage modeling: Assessing future flood hazards in Algiers, Algeria E. Lameche et al. https://doi.org/10.1016/j.uclim.2026.102843
81. The Impacts of Climate Change on Irrigated Agriculture in Southern Portugal J. Rolim et al. https://doi.org/10.1002/ird.1996
82. Climate change impact on flood hazard in Europe: An assessment based on high‐resolution climate simulations R. Dankers & L. Feyen https://doi.org/10.1029/2007JD009719
83. The impact of varying spatial resolution of climate models on future rainfall simulations in the Pra River Basin (Ghana) E. Bessah et al. https://doi.org/10.2166/wcc.2019.258
84. Assessing the hydrological response from an ensemble of CMIP5 climate projections in the transition zone of the Atlantic region (Bay of Biscay) M. Meaurio et al. https://doi.org/10.1016/j.jhydrol.2017.02.029
85. Impact of climate change on hydrological conditions of Rhine and Upper Danube rivers based on the results of regional climate and hydrological models G. Szépszó et al. https://doi.org/10.1007/s11069-013-0987-1
86. The impact of a bias-correction approach (delta change) applied directly to hydrological model output when modelling the severity of ice jam flooding under future climate scenarios A. Das et al. https://doi.org/10.1007/s10584-022-03364-5
87. Exploratory analyses for the assessment of climate change impacts on the energy production in an Amazon run-of-river hydropower plant G. Mohor et al. https://doi.org/10.1016/j.ejrh.2015.04.003
88. Evaluation of subseasonal precipitation forecasts in the Uruguay River basin J. Badagian et al. https://doi.org/10.1002/joc.8634
89. Nonparametric statistical temporal downscaling of daily precipitation to hourly precipitation and implications for climate change scenarios T. Lee & C. Jeong https://doi.org/10.1016/j.jhydrol.2013.12.027
90. Assessment of climate change impact in the hydrological regime of River Pinios Basin, central Greece A. Panagopoulos et al. https://doi.org/10.1080/19443994.2014.984926
91. Precipitation bias correction of very high resolution regional climate models D. Argüeso et al. https://doi.org/10.5194/hess-17-4379-2013
92. 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
93. Using models to inform water policy in a changing climate: comparing the Australian and Uruguayan experiences A. Silvarrey Barruffa et al. https://doi.org/10.1071/MF19266
94. Inter-comparison of statistical downscaling methods for projection of extreme flow indices across Europe Y. Hundecha et al. https://doi.org/10.1016/j.jhydrol.2016.08.033
95. Bias Correction and Trend Analysis of Temperature Data by a High-Resolution CMIP6 Model over a Tropical River Basin D. Jose & G. Dwarakish https://doi.org/10.1007/s13143-021-00240-7
96. Towards a new generation of high-resolution meteorological input data for small-scale hydrologic modeling S. Leimer et al. https://doi.org/10.1016/j.jhydrol.2011.03.026
97. Optimization and Variants of Quantile-Based Methods for Bias Corrections of Statistically Downscaled Precipitation Data A. Goly & R. Teegavarapu https://doi.org/10.1061/(ASCE)HE.1943-5584.0001926
98. Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums D. Maraun https://doi.org/10.1029/2012GL051210
99. 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
100. Projection and Analysis of Floods in the Upper Heihe River Basin under Climate Change Y. Ye et al. https://doi.org/10.3390/atmos14071083
101. Bias correction of daily precipitation simulated by a regional climate model: a comparison of methods T. Lafon et al. https://doi.org/10.1002/joc.3518
102. Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River basin W. Gumindoga et al. https://doi.org/10.5194/hess-23-2915-2019
103. Climate change impact assessment on hydropower generation using multi-model climate ensemble V. Chilkoti et al. https://doi.org/10.1016/j.renene.2017.02.041
104. On bias correction of summer monsoon precipitation over India from CORDEX‐SA simulations A. Choudhary & A. Dimri https://doi.org/10.1002/joc.5889
105. The Impacts of Climate Change on Maximum Daily Discharge in the Payab Jamash Watershed, Iran F. Parandin et al. https://doi.org/10.1515/geo-2019-0080
106. Impact Analysis of Univariate and Multivariate Bias Correction on Rice Irrigation Water Needs in Jiangxi Province, China W. Hanggoro et al. https://doi.org/10.3390/w12020381
107. ASSESSING FUTURE SCENARIOS OF WATER AVAILABILITY USING CMPI5 HIGH RESOLUTION CLIMATE MODELS – CASE STUDY OF THE ALTO TIETÊ BASIN G. Calado & M. Valverde https://doi.org/10.5327/Z2176-947820200658
108. Hydrologic applicability of satellite-based precipitation estimates for irrigation water management in the data-scarce region S. Bista et al. https://doi.org/10.1016/j.jhydrol.2024.131310
109. Unpacking dasymetric modelling to correct spatial bias in environmental model outputs M. Kallio et al. https://doi.org/10.1016/j.envsoft.2022.105511
110. Assessing adaptation measures on agricultural water productivity under climate change: A case study of Huai River Basin, China C. Dai et al. https://doi.org/10.1016/j.scitotenv.2020.137777
111. Hydrological Climate-Impact Projections for the Rhine River: GCM–RCM Uncertainty and Separate Temperature and Precipitation Effects* T. Bosshard et al. https://doi.org/10.1175/JHM-D-12-098.1
112. Uncertainty in high‐resolution hydrological projections: Partitioning the influence of climate models and natural climate variability J. Moraga et al. https://doi.org/10.1002/hyp.14695
113. Hybrid approach in statistical bias correction of projected precipitation for the frequency analysis of extreme events M. Um et al. https://doi.org/10.1016/j.advwatres.2016.05.021
114. AGCM3.2S RUNOFF DATA BIAS CORRECTION OVER UPPER CHAO PHRAYA RIVER BASIN BASED ON LAND COVER GROUPING T. RAM-INDRA et al. https://doi.org/10.2208/jscejhe.76.2_I_91
115. Interpolated daily temperature and precipitation data for Level II ICP Forests plots in Germany S. Rukh et al. https://doi.org/10.1186/s13595-022-01167-3
116. Potential drought stress in a Swiss mountain catchment—Ensemble forecasting of high mountain soil moisture reveals a drastic decrease, despite major uncertainties O. Rössler et al. https://doi.org/10.1029/2011WR011188
117. Assessment of Climate Change Impacts on River High Flows through Comparative Use of GR4J, HBV and Xinanjiang Models Y. Tian et al. https://doi.org/10.1007/s11269-013-0321-4
118. A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield J. Ringard et al. https://doi.org/10.3390/s17061413
119. Extreme climate projections under representative concentration pathways in the Lower Songkhram River Basin, Thailand S. Shrestha & R. Roachanakanan https://doi.org/10.1016/j.heliyon.2021.e06146
120. Evaluating statistical downscaling methods for future temperature and precipitation projections in the Qilian mountains G. Liu et al. https://doi.org/10.3389/frsen.2026.1890112
121. Modelling the impact of climate change on the productivity and water-use efficiency of a central European beech forest T. Rötzer et al. https://doi.org/10.3354/cr01179
122. Economic vulnerability assessment in the water sector with a focus on electricity production in hydropower plants: Case of Montenegro J. Ćetković et al. https://doi.org/10.1051/e3sconf/202345204001
123. Climate change impact assessment on water resources under RCP scenarios: A case study in Mundaú River Basin, Northeastern Brazil C. Andrade et al. https://doi.org/10.1002/joc.6751
124. Bias Correction of RCM Precipitation by TIN-Copula Method: A Case Study for Historical and Future Simulations in Cyprus G. Lazoglou et al. https://doi.org/10.3390/cli8070085
125. Improving satellite and reanalysis precipitation estimates in a Himalayan River Basin: a comparative study of bias correction methods with focus on extremes and ensemble method performance H. Tiwari & R. Garg https://doi.org/10.1007/s12665-025-12626-1
126. Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods C. Teutschbein & J. Seibert https://doi.org/10.1016/j.jhydrol.2012.05.052
127. Modelling seasonal flows alteration in the Vietnamese Mekong Delta under upstream discharge changes, rainfall changes and sea level rise D. Anh et al. https://doi.org/10.1080/15715124.2018.1505735
128. Two novel error-updating model frameworks for short-to-medium range streamflow forecasting using bias-corrected rainfall inputs: Development and comparative assessment A. Khatun et al. https://doi.org/10.1016/j.jhydrol.2023.129199
129. Comparative assessment of climate change and its impacts on three coastal aquifers in the Mediterranean T. Stigter et al. https://doi.org/10.1007/s10113-012-0377-3
130. A climate-adapted GIS-based simulation-optimization method for optimal basin-scale wetland placement to mitigate nonpoint source pollution under shared socioeconomic pathways C. Dai et al. https://doi.org/10.1016/j.jhydrol.2026.135109
131. Development and evaluation of a hydrologic data-assimilation scheme for short-range flow and inflow forecasts in a data-sparse high-latitude region using a distributed model and ensemble Kalman filtering J. Samuel et al. https://doi.org/10.1016/j.advwatres.2019.06.004
132. Sensitivity study of RegCM4.7 model to land surface schemes (BATS and CLM4.5) forced by MPI-ESM1.2-HR in simulating temperature and precipitation over Iran L. Kosari Moghadam et al. https://doi.org/10.1007/s00704-024-05135-x
133. Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China G. Fang et al. https://doi.org/10.5194/hess-19-2547-2015
134. National scale assessment of climate change impacts on flooding in Finland N. Veijalainen et al. https://doi.org/10.1016/j.jhydrol.2010.07.035
135. Bias Correction of Historical and Future Simulations of Precipitation and Temperature for China from CMIP5 Models X. Yang et al. https://doi.org/10.1175/JHM-D-17-0180.1
136. 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
137. Assessment of the effects of climate change on water balance components in the upper Erer subbasin, Ethiopia B. Mummed & Y. Seleshi https://doi.org/10.1016/j.heliyon.2024.e30297
138. Variance analysis of forecasted streamflow maxima in a wet temperate climate N. Al Aamery et al. https://doi.org/10.1016/j.jhydrol.2018.03.038
139. Assessment of Climate Change Impacts on Reservoir Storage Reliability, Resilience, and Vulnerability Using a Multivariate Frequency Bias Correction Approach H. Nguyen et al. https://doi.org/10.1029/2019WR026022
140. Assessment of the Expected Runoff Change in Spain Using Climate Simulations L. Barranco et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000920
141. Strategic prioritization of sewersheds to mitigate combined sewer overflows under climate change J. Petrucci et al. https://doi.org/10.1016/j.envc.2025.101088
142. 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
143. Precipitation-based climate change hotspots across India through a Multi-model assessment from CMIP6 S. Sarkar et al. https://doi.org/10.1016/j.jhydrol.2023.129805
144. Improving Hydro-Climatic Projections with Bias-Correction in Sahelian Niger Basin, West Africa G. Oyerinde et al. https://doi.org/10.3390/cli5010008
145. Multi-model ensemble CMIP6 for prediction of climate changes: evidence from Asia O. Mousavikhaledi et al. https://doi.org/10.1007/s10668-025-06371-5
146. On the Use of Modis Snow Cover Product for Assessing Snow Extension and Duration Over the Po River Basin P. Da Ronco & C. De Michele https://doi.org/10.2139/ssrn.2490937
147. Projection of Extreme Temperature Events over the Mediterranean and Sahara Using Bias-Corrected CMIP6 Models H. Babaousmail et al. https://doi.org/10.3390/atmos13050741
148. Evaluation of bias correction methods for multi-satellite rainfall estimation products R. Andari et al. https://doi.org/10.1088/1755-1315/1317/1/012008
149. Evaluating Bias-Correction Methods for Seasonal Dynamical Precipitation Forecasts S. Golian & C. Murphy https://doi.org/10.1175/JHM-D-22-0049.1
150. Exploring the potential of deep learning for streamflow forecasting: A comparative study with hydrological models for seasonal and perennial rivers A. Izadi et al. https://doi.org/10.1016/j.eswa.2024.124139
151. Future extreme precipitation intensities based on a historic event I. Manola et al. https://doi.org/10.5194/hess-22-3777-2018
152. Projections of climate change impacts on floods and droughts in Germany using an ensemble of climate change scenarios S. Huang et al. https://doi.org/10.1007/s10113-014-0606-z
153. Comparison of empirical statistical methods for downscaling daily climate projections from CMIP5 GCMs: a case study of the Huai River Basin, China L. Wang et al. https://doi.org/10.1002/joc.4334
154. Comparing grounded theory and phenomenology as methods to understand lived experience of engineering educators implementing problem-based learning S. Chance et al. https://doi.org/10.1080/03043797.2019.1607826
155. Joint bias correction and seasonal multi-model ensemble strategies for improving daily runoff simulation: A comprehensive evaluation based regional climate model LMDZ outputs A. El Bilali et al. https://doi.org/10.1016/j.ejrh.2026.103596
156. Spatio-temporal variation of precipitation projection based on bias-adjusted CORDEX-SA regional climate model simulations for arid and semi-arid region A. Ghaemi et al. https://doi.org/10.3354/cr01722
157. Global hotspots for the occurrence of compound events N. Ridder et al. https://doi.org/10.1038/s41467-020-19639-3
158. Climate change impacts on floodway and floodway fringe: a case study in Shahrchay River Basin, Iran A. Rahmani-Rezaeieh et al. https://doi.org/10.1007/s12517-020-05444-1
159. Exploring variability in climate change projections on the Nemunas River and Curonian Lagoon: coupled SWAT and SHYFEM modeling approach N. Čerkasova et al. https://doi.org/10.5194/os-20-1123-2024
160. 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
161. Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections L. Seaby et al. https://doi.org/10.1016/j.jhydrol.2013.02.015
162. Comparison and Bias Correction of TMPA Precipitation Products over the Lower Part of Red–Thai Binh River Basin of Vietnam H. Le et al. https://doi.org/10.3390/rs10101582
163. On the Observations and Environmental Modeling in Xingó Hydropower Plant - Northeast Brazil: Present and Future Hydroclimatic Features W. Luiz-Silva et al. https://doi.org/10.1007/s10666-021-09810-5
164. Assessment of Climate Change Impacts on Extreme High and Low Flows: An Improved Bottom-Up Approach A. Alodah & O. Seidou https://doi.org/10.3390/w11061236
165. Assessment of future water availability scenarios for São Lourenço supply system watershed in São Paulo, Brazil G. Calado & M. Valverde https://doi.org/10.1007/s40899-025-01257-w
166. Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography J. Crossman et al. https://doi.org/10.5194/hess-18-5125-2014
167. ERA5-land–based drought assessment using SPI and SPEI to support smart agriculture in Prince Edward Island, Canada R. Malekian et al. https://doi.org/10.1016/j.atech.2026.102077
168. Spectral representation of the annual cycle in the climate change signal T. Bosshard et al. https://doi.org/10.5194/hess-15-2777-2011
169. Intraseasonal scale ensemble forecasts of precipitation and evapotranspiration for the Madeira River basin using different physical parameterizations W. Gomes et al. https://doi.org/10.1016/j.atmosres.2022.106086
170. Simulating low‐probability peak discharges for the Rhine basin using resampled climate modeling data A. te Linde et al. https://doi.org/10.1029/2009WR007707
171. Modeling the effects of climate change on hydrology and sediment load in a headwater basin in the Brazilian Cerrado biome V. de Oliveira et al. https://doi.org/10.1016/j.ecoleng.2019.04.021
172. Assessment of Satellite-Based Precipitation Estimates over Egypt T. Gado et al. https://doi.org/10.1061/JHYEFF.HEENG-6051
173. Downscaling, bias correction, and spatial adjustment of extreme tropical cyclone rainfall in ERA5 using deep learning G. Ascenso et al. https://doi.org/10.1016/j.wace.2024.100724
174. Assessing Climate Change Impacts on Irrigation Water Requirements under Mediterranean Conditions—A Review of the Methodological Approaches Focusing on Maize Crop D. Soares et al. https://doi.org/10.3390/agronomy13010117
175. Review of global climate models used for drought assessment and forecasting S. Tayyaba et al. https://doi.org/10.1007/s43832-026-00352-z
176. Variations in Projections of Precipitations of CMIP6 Global Climate Models under SSP 2–45 and SSP 5–85 M. Shiru et al. https://doi.org/10.1007/s12205-022-0149-7
177. Past and projected rainfall and temperature trends in a sub-humid Montane Forest in Northern Kenya based on the CMIP5 model ensemble G. Muhati et al. https://doi.org/10.1016/j.gecco.2018.e00469
178. Response of the river discharge in the Tocantins River Basin, Brazil, to environmental changes and the associated effects on the energy potential R. Von Randow et al. https://doi.org/10.1007/s10113-018-1396-5
179. Assessment of Future Climate Change Impact on an Agricultural Reservoir in South Korea J. Lee & H. Shin https://doi.org/10.3390/w13152125
180. Frequency analysis based on Peaks-Over-Threshold approach for GPM IMERG precipitation product H. Aksu et al. https://doi.org/10.1007/s00704-023-04555-5
181. Inter-Comparison of Gauge-Corrected Global Satellite Rainfall Estimates and Their Applicability for Effective Water Resource Management in a Transboundary River Basin: The Case of the Meghna River Basin I. Khairul et al. https://doi.org/10.3390/rs10060828
182. Space-Time Variability of Maximum Daily Rainfall in Piura River Basin in Peru Related to El Niño Occurrence M. Farias de Reyes et al. https://doi.org/10.3390/w16233452
183. Empirical-statistical downscaling and error correction of regional climate models and its impact on the climate change signal M. Themeßl et al. https://doi.org/10.1007/s10584-011-0224-4
184. The hydrological response of the Ourthe catchment to climate change as modelled by the HBV model T. Driessen et al. https://doi.org/10.5194/hess-14-651-2010
185. The Elbe river flooding 2002 as seen by an extended regional climate model S. Kotlarski et al. https://doi.org/10.1016/j.jhydrol.2012.09.020
186. Comparison of monthly rainfall generated from dynamical and statistical downscaling methods: a case study of the Heihe River Basin in China H. Su et al. https://doi.org/10.1007/s00704-016-1771-4
187. Effects of the El Niño-Southern Oscillation (ENSO) on rainfall anomalies in Central Java, Indonesia A. Firmansyah et al. https://doi.org/10.1007/s12517-022-11016-2
188. Response of hypoxia to future climate change is sensitive to methodological assumptions K. Hinson et al. https://doi.org/10.1038/s41598-024-68329-3
189. Quantifying the Impacts of Climate Change on Streamflow Dynamics of Two Major Rivers of the Northern Lake Erie Basin in Canada B. Zhang et al. https://doi.org/10.3390/su10082897
190. Doğu Karadeniz Havzası Lokal Meteorolojik Değişkenleri İçin Bir Ölçek İndirgeme Uygulaması ve Senaryo Esaslı Öngörüler S. NACAR et al. https://doi.org/10.18400/tekderg.895112
191. Assessment of climate change impact on rainfall for studying water availability in upper Mahanadi catchment, India R. Jaiswal et al. https://doi.org/10.2166/wcc.2017.097
192. Assessing the Impact of Land Cover, Soil, and Climate on the Storage Potential of Dryland Sand Dams J. Eisma et al. https://doi.org/10.3389/frwa.2021.671455
193. Future Changes in the Free Tropospheric Freezing Level and Rain–Snow Limit: The Case of Central Chile P. Mardones & R. Garreaud https://doi.org/10.3390/atmos11111259
194. Future projections of water level and thermal regime changes of a multipurpose subtropical reservoir (Sao Paulo, Brazil) C. Barbosa et al. https://doi.org/10.1016/j.scitotenv.2020.144741
195. The value of large-scale climate variables in climate change assessment: The case of Botswana’s rainfall P. Kenabatho et al. https://doi.org/10.1016/j.pce.2012.08.006
196. Impacts of climate change on temperature and evaporation from a large reservoir in Australia F. Helfer et al. https://doi.org/10.1016/j.jhydrol.2012.10.008
197. Assessing the relative effectiveness of statistical downscaling and distribution mapping in reproducing rainfall statistics based on climate model results A. Langousis et al. https://doi.org/10.1002/2015WR017556
198. Alpine snow cover in a changing climate: a regional climate model perspective C. Steger et al. https://doi.org/10.1007/s00382-012-1545-3
199. Bias correction of precipitation through Singularity Stochastic Removal: Because occurrences matter M. Vrac et al. https://doi.org/10.1002/2015JD024511
200. Observed and simulated climate variability and trends in a semi- arid region S. Jayanthi & V. Keesara https://doi.org/10.1007/s41324-019-00278-w
201. CHIRPWeb, an Online Tool for Providing a Bias Corrected CHIRP Grid Dataset Using Field Measurements J. Pérez-Sánchez et al. https://doi.org/10.1007/s00024-026-03966-5
202. Evaluating statistical and machine learning bias-correction methods for CMIP6 rainfall projections in a tropical megacity N. Miniandi et al. https://doi.org/10.1007/s00704-026-06223-w
203. Multivariate Modeling of Projected Drought Frequency and Hazard over India V. Gupta et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001893
204. Climate projections of precipitation and temperature in cities from ABC Paulista, in the Metropolitan Region of São Paulo—Brazil M. Valverde et al. https://doi.org/10.3389/fclim.2023.1127026
205. Multivariate copula quantile mapping for bias correction of reanalysis air temperature data F. Alidoost et al. https://doi.org/10.1080/14498596.2019.1601138
206. Study on the Spatial and Temporal Characteristics of Mesoscale Drought in China under Future Climate Change Scenarios X. Gong et al. https://doi.org/10.3390/w13192761
207. Variation of hydro-climatic extremes in headwater regions of Hei River basin under climate change L. Wang et al. https://doi.org/10.1016/j.ejrh.2023.101561
208. High-Resolution Temperature Datasets in Portugal from a Geostatistical Approach: Variability and Extremes A. Fonseca & J. Santos https://doi.org/10.1175/JAMC-D-17-0215.1
209. Intra- and interannual streamflow variations of Wardha watershed under changing climate N. Sowjanya. P et al. https://doi.org/10.1080/09715010.2018.1473057
210. Evaluating Water Supply Capacity of Embankment Raised Reservoir on Climate Change J. Lee & J. Noh https://doi.org/10.5389/KSAE.2015.57.4.073
211. Comparative analysis of bias correction techniques for future climate assessment using CMIP6 hydrological variables for the Indian subcontinent M. Shah et al. https://doi.org/10.1007/s11600-024-01378-4
212. Evaluation de deux méthodes de correction de biais des sorties de modèles climatiques régionaux Cordex-Africa pour la prévision des pluies  : cas du bassin côtier oranais S. Taïbi et al. https://doi.org/10.5194/piahs-384-213-2021
213. Impacts of land-use and climate changes on surface runoff in a tropical forest watershed (Brazil) M. Lucas-Borja et al. https://doi.org/10.1080/02626667.2020.1787417
214. Indirect downscaling of hourly precipitation based on atmospheric circulation and temperature F. Beck & A. Bárdossy https://doi.org/10.5194/hess-17-4851-2013
215. Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe D. Meißner et al. https://doi.org/10.5194/hess-21-6401-2017
216. Reliability of the global climate models during 1961–1999 in arid and semiarid regions of China Y. Yang et al. https://doi.org/10.1016/j.scitotenv.2019.02.188
217. Enhancing uncertainty of regional climate models for climate change projection at Western Nile Delta R. Farag et al. https://doi.org/10.1080/23570008.2024.2335582
218. CHESS-SCAPE: high-resolution future projections of multiple climate scenarios for the United Kingdom derived from downscaled United Kingdom Climate Projections 2018 regional climate model output E. Robinson et al. https://doi.org/10.5194/essd-15-5371-2023
219. Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin P. Parasar & A. Krishna https://doi.org/10.1038/s41598-025-13221-x
220. Projecting Relative Sea Level Rise under Climate Change at the Phrachula Chomklao Fort Tide Gauge in the Upper Gulf of Thailand C. Jaroenongard et al. https://doi.org/10.3390/w13121702
221. Projection of Streamflow Change Using a Time‐Varying Budyko Framework in the Contiguous United States Z. Li & S. Quiring https://doi.org/10.1029/2022WR033016
222. Impact of climate change on water resources of upper Kharun catchment in Chhattisgarh, India N. Kumar et al. https://doi.org/10.1016/j.ejrh.2017.07.008
223. Predicting impacts of climate change on evapotranspiration and soil moisture for a site with subhumid climate A. Herceg et al. https://doi.org/10.2478/johh-2019-0017
224. Machine learning to optimize climate projection over China with multi-model ensemble simulations T. Li et al. https://doi.org/10.1088/1748-9326/ac1d0c
225. Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods Z. Iqbal et al. https://doi.org/10.3390/su14116620
226. Soil moisture estimation using Sentinel-1 SAR and field observation in the Eastern Ghats region of India U. Mandal et al. https://doi.org/10.1007/s10661-026-15459-y
227. Climate projections of chill hours and implications for olive cultivation in Minas Gerais, Brazil F. Martins et al. https://doi.org/10.1590/s1678-3921.pab2020.v55.01852
228. Stochastic approach to analyzing the uncertainties and possible changes in the availability of water in the future based on scenarios of climate change G. Oliveira et al. https://doi.org/10.5194/hess-19-3585-2015
229. Assessment of CMIP6 models’ performances and projection of precipitation based on SSP scenarios over the MENAP region E. Mesgari et al. https://doi.org/10.2166/wcc.2022.195
230. Effects of climate and land cover changes on water availability in a Brazilian Cerrado basin P. Siqueira et al. https://doi.org/10.1016/j.ejrh.2021.100931
231. Assessment of the Sources of Variation in Changes of Precipitation Characteristics over the Rhine Basin Using a Linear Mixed-Effects Model M. Hanel & T. Buishand https://doi.org/10.1175/JCLI-D-14-00775.1
232. A multi-model approach for improved simulations of future water availability at a large Eastern Mediterranean karst spring A. Hartmann et al. https://doi.org/10.1016/j.jhydrol.2012.08.024
233. Integrating machine learning and zoning-based techniques for bias correction in gridded precipitation data to improve hydrological estimation in the data-scarce region T. Meema et al. https://doi.org/10.1016/j.jhydrol.2024.132356
234. Evaluating Droughts and Trends in Data-Scarce Regions: A Case Study of Palestine Using ERA5, Standardized Precipitation Index, Bias Correction, Classical and Innovative Trend Approaches A. Abu Arra & E. Şişman https://doi.org/10.3390/w17182780
235. Bias adjustment of satellite-based precipitation estimation using artificial neural networks-cloud classification system over Saudi Arabia R. Alharbi et al. https://doi.org/10.1007/s12517-018-3860-4
236. Projected climate change impacts on soil erosion over Iran S. Doulabian et al. https://doi.org/10.1016/j.jhydrol.2021.126432
237. Impact of diverse configuration in multivariate bias correction methods on large-scale hydrological modelling under climate change K. Ahn et al. https://doi.org/10.1016/j.jhydrol.2023.130406
238. The impact of climate change on groundwater recharge and runoff in a humid, equatorial catchment: sensitivity of projections to rainfall intensity L. MILEHAM et al. https://doi.org/10.1623/hysj.54.4.727
239. 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
240. Projected Changes in the Tibetan Plateau Snowpack Resulting From Rising Global Temperatures A. Nury et al. https://doi.org/10.1029/2021JD036201
241. Compound and successive events of extreme precipitation and extreme runoff under heatwaves based on CMIP6 models P. Sun et al. https://doi.org/10.1016/j.scitotenv.2023.162980
242. Multiscale assessments of hydroclimatic modelling uncertainties under a changing climate G. Oyerinde et al. https://doi.org/10.2166/wcc.2022.266
243. Regionalization of Climate Change Simulations for the Assessment of Impacts on Precipitation, Flow Rate and Electricity Generation in the Xingu River Basin in the Brazilian Amazon E. Lucas et al. https://doi.org/10.3390/en15207698
244. Implications of climate change in the twenty‐first century for simulated magnitude and frequency of bed‐material transport in tributaries of the Saint‐Lawrence River P. Verhaar et al. https://doi.org/10.1002/hyp.7918
245. Improving seasonal forecasts of air temperature using a genetic algorithm J. Ratnam et al. https://doi.org/10.1038/s41598-019-49281-z
246. Evaluation of two precipitation data sets for the Rhine River using streamflow simulations C. Photiadou et al. https://doi.org/10.5194/hess-15-3355-2011
247. Comparative analysis of bias correction methods for IMERG V06 precipitation products: case study in Guangxi, China M. Yang et al. https://doi.org/10.1080/2150704X.2024.2307321
248. Climate Simulation Using RCM Data for Jamnagar District H. Bhatu & H. Rank https://doi.org/10.12944/CWE.12.2.25
249. Evaluation of bias-adjusted satellite precipitation estimations for extreme flood events in Langat river basin, Malaysia E. Soo et al. https://doi.org/10.2166/nh.2019.071
250. Assessing future changes in flood frequencies under CMIP6 climate projections using SWAT modeling: a case study of Bitlis Creek, Turkey E. Yalcin https://doi.org/10.2166/wcc.2024.646
251. Virtual water content of temperate cereals and maize: Present and potential future patterns M. Fader et al. https://doi.org/10.1016/j.jhydrol.2009.12.011
252. Downscaling projections of climate change in Sao Tome and Principe Islands, Africa S. Chou et al. https://doi.org/10.1007/s00382-020-05212-7
253. Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments X. Gong et al. https://doi.org/10.1016/j.ecolind.2021.108198
254. Impacts of climate change on water resources in the Mediterranean Basin: a case study in Catalonia, Spain D. Pascual et al. https://doi.org/10.1080/02626667.2014.947290
255. Inflow Forecast of Iranamadu Reservoir, Sri Lanka, under Projected Climate Scenarios Using Artificial Neural Networks C. Karunanayake et al. https://doi.org/10.1155/2020/8821627
256. Investigating seasonal drought severity-area-frequency (SAF) curve over Indian region: incorporating GCM and scenario uncertainties S. Das et al. https://doi.org/10.1007/s00477-021-02073-2
257. Evaluation of drought events using multiple drought indices under climate change in the Upper Indus Basin T. Shamim et al. https://doi.org/10.1007/s10661-024-13366-8
258. Future fluvial erosion and sedimentation potential of cohesive sediments in a coastal river reach of SW Finland E. Lotsari et al. https://doi.org/10.1002/hyp.10080
259. Precipitation projections using a spatiotemporally distributed method: a case study in the Poyang Lake watershed based on the MRI-CGCM3 L. Zhang et al. https://doi.org/10.5194/hess-23-1649-2019
260. A Bayesian Kriging model applied for spatial downscaling of daily rainfall from GCMs C. Lima et al. https://doi.org/10.1016/j.jhydrol.2021.126095
261. Macro-scale evolution and uncertainty of rainfall erosivity in the Dawen river basin under future climate scenarios R. Zhao et al. https://doi.org/10.1088/1742-6596/3205/1/012010
262. The impact of bias correcting regional climate model results on hydrological indicators for Bavarian catchments F. Willkofer et al. https://doi.org/10.1016/j.ejrh.2018.06.010
263. Assessment of climate change impacts on water resources of the Purus Basin in the southwestern Amazon R. DALAGNOL et al. https://doi.org/10.1590/1809-4392201601993
264. Increasing climatic and anthropogenic pressure on the Matopiba agricultural frontier and its impacts on water resources: a case study of the Corrente River Basin L. Ferraz et al. https://doi.org/10.1007/s00704-026-06226-7
265. Nonstationary probabilistic downscaling of extreme precipitation M. Kallache et al. https://doi.org/10.1029/2010JD014892
266. Modelling the impact of climate and land cover change on hydrology and water quality in a forest watershed in the Basque Country (Northern Spain) M. Peraza-Castro et al. https://doi.org/10.1016/j.ecoleng.2018.07.016
267. Future short-term estimation of flowrate of the Euphrates river catchment located in Al-Najaf Governorate, Iraq through using weather data and statistical downscaling model H. Kareem & A. Alkatib https://doi.org/10.1515/eng-2022-0027
268. Climate change assessment for a small island: a Tahiti downscaling experiment M. Hopuare et al. https://doi.org/10.3354/cr01298
269. Calibrating regionally downscaled precipitation over Norway through quantile-based approaches D. Bolin et al. https://doi.org/10.5194/ascmo-2-39-2016
270. Projection of Future Hydropower Generation in Samanalawewa Power Plant, Sri Lanka B. Khaniya et al. https://doi.org/10.1155/2020/8862067
271. WRF‐based dynamical downscaling of ERA5 reanalysis data for High Mountain Asia: Towards a new version of the High Asia Refined analysis X. Wang et al. https://doi.org/10.1002/joc.6686
272. Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin R. Junqueira et al. https://doi.org/10.3390/w14142178
273. Predicting changes in monthly streamflow to Karaj dam reservoir, Iran, in climate change condition and assessing its uncertainty V. Keteklahijani et al. https://doi.org/10.1016/j.asej.2018.11.004
274. Tropical hydro-climatic responses to global warming and solar radiation modification in the Kelantan River Basin, Malaysia H. Du et al. https://doi.org/10.2166/wcc.2025.587
275. Temperature and precipitation changes under CMIP6 projections in the Mujib Basin, Jordan S. Alsalal et al. https://doi.org/10.1007/s00704-024-05087-2
276. Seasonal Forecasting of Onset of Summer Rains over South Africa J. Ratnam et al. https://doi.org/10.1175/JAMC-D-18-0067.1
277. Climate Change Impacts on Irrigation Requirements of Preserved Forage for Horses under Mediterranean Conditions D. Soares et al. https://doi.org/10.3390/agronomy10111758
278. TeaNet: An Enhanced Attention Network for Climate-Resilient River Discharge Forecasting Under CMIP6 SSP585 Projections P. Parasar et al. https://doi.org/10.3390/su17094230
279. Exploring high-end scenarios for local sea level rise to develop flood protection strategies for a low-lying delta—the Netherlands as an example C. Katsman et al. https://doi.org/10.1007/s10584-011-0037-5
280. Evaluation of climate modeling factors impacting the variance of streamflow N. Al Aamery et al. https://doi.org/10.1016/j.jhydrol.2016.08.054
281. Statistical Bias Correction of RegCM4 Output Data (Study Area: Indramayu Regency) . Anria et al. https://doi.org/10.1088/1755-1315/363/1/012024
282. Bias correction of regional climate model simulations for the impact assessment of the climate change in Egypt T. Gado et al. https://doi.org/10.1007/s11356-021-17189-9
283. Shifted dominant flood drivers of an alpine glacierized catchment in the Tianshan region revealed through interpretable deep learning W. Liang et al. https://doi.org/10.1038/s41612-025-00918-z
284. Comparison of GCM‐ and RCM‐simulated precipitation following stochastic postprocessing J. Eden et al. https://doi.org/10.1002/2014JD021732
285. Sensitivity of potential evaporation estimates to 100 years of climate variability R. Bartholomeus et al. https://doi.org/10.5194/hess-19-997-2015
286. Evaluation and application of a SWAT model to assess the climate change impact on the hydrology of the Himalayan River Basin B. Bhatta et al. https://doi.org/10.1016/j.catena.2019.104082
287. Streamflow simulations using error correction ensembles of satellite rainfall products over the Huaihe river basin F. Chen et al. https://doi.org/10.1016/j.jhydrol.2020.125179
288. Assessment of the Probability of Autochthonous Transmission of Chikungunya Virus in Canada under Recent and Projected Climate Change V. Ng et al. https://doi.org/10.1289/EHP669
289. A novel probabilistic and metaheuristic approach for evaluation of CMIP6 models and bias corrected multimodel ensemble for future projection of temperature characteristics R. Khalil & Z. Ali https://doi.org/10.1007/s00477-025-03014-z
290. Evaluation of Simple Statistical Downscaling Methods for Monthly Regional Climate Model Simulations with Respect to the Estimated Changes in Runoff in the Czech Republic M. Hanel et al. https://doi.org/10.1007/s11269-013-0466-1
291. Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations S. van Pelt et al. https://doi.org/10.5194/hess-16-4517-2012
292. Evaluation of temporal drought variation and projection in a tropical river basin of Kerala M. Jincy Rose & N. Chithra https://doi.org/10.2166/wcc.2020.240
293. Spatio-Temporal Analysis of Historical and Future Climate Data in the Texas High Plains Y. Chen et al. https://doi.org/10.3390/su12156036
294. Numerical modelling of land subsidence related to groundwater withdrawal in the Firenze-Prato-Pistoia basin (central Italy) M. Ceccatelli et al. https://doi.org/10.1007/s10040-020-02255-2
295. Water temperature increases in the river Rhine in response to climate change P. Hardenbicker et al. https://doi.org/10.1007/s10113-016-1006-3
296. Evaluation of Bias Correction Methods for Regional Climate Models: Downscaled Rainfall Analysis Over Diverse Agroclimatic Zones of India R. Jaiswal et al. https://doi.org/10.1029/2021EA001981
297. Optimal dike investments under uncertainty and learning about increasing water levels T. van der Pol et al. https://doi.org/10.1111/jfr3.12063
298. Simulating hydrological responses to climate change using dynamic and statistical downscaling methods: a case study in the Kaidu River Basin, Xinjiang, China W. Ba et al. https://doi.org/10.1007/s40333-018-0068-0
299. Stochastic bias correction of dynamically downscaled precipitation fields for Germany through Copula-based integration of gridded observation data G. Mao et al. https://doi.org/10.5194/hess-19-1787-2015
300. Large decrease in streamflow and sediment load of Qinghai–Tibetan Plateau driven by future climate change: A case study in Lhasa River Basin P. Tian et al. https://doi.org/10.1016/j.catena.2019.104340
301. TSWS: An observation-based streamflow dataset of Tianshan Mountains watersheds (1901–2019) S. Li et al. https://doi.org/10.1038/s41597-025-05046-0
302. Use of SWAT to determine the effects of climate and land use changes on streamflow and sediment concentration in the Purna River basin, India A. Nilawar & M. Waikar https://doi.org/10.1007/s12665-018-7975-4
303. Performance evaluation of satellite-based rainfall estimation across climatic zones in Burkina Faso J. Garba et al. https://doi.org/10.1007/s00704-023-04593-z
304. Bias correction of high resolution regional climate model data P. Berg et al. https://doi.org/10.1016/j.jhydrol.2012.04.026
305. 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
306. Impact of Climate Change on the Hydrology of Upper Tiber River Basin Using Bias Corrected Regional Climate Model B. Fiseha et al. https://doi.org/10.1007/s11269-014-0546-x
307. The role of compound climate and weather extreme events in creating socio-economic impacts in South Florida J. Ali et al. https://doi.org/10.1016/j.wace.2023.100625
308. Estimating the Risk of River Flow under Climate Change in the Tsengwen River Basin H. Wei et al. https://doi.org/10.3390/w8030081
309. A comprehensive evaluation of the accuracy of satellite-based precipitation estimates over Thailand C. Kaprom et al. https://doi.org/10.1016/j.ejrh.2025.102380
310. Quantification of Expected Changes in Peak Flow Quantiles in Climate Change by Combining Continuous Hydrological Modelling with the Modified Curve Number Method E. Soriano et al. https://doi.org/10.1007/s11269-020-02670-w
311. Multi-Basin Modelling of Future Hydrological Fluxes in the Indian Subcontinent I. Pechlivanidis et al. https://doi.org/10.3390/w8050177
312. 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
313. Performance evaluation of hydrological models using ensemble of General Circulation Models in the northeastern China M. Faiz et al. https://doi.org/10.1016/j.jhydrol.2018.08.057
314. Greater Sustainability in the Future of Hanjiang River Under Climate Change: The Case of Nitrogen Y. Zhang et al. https://doi.org/10.3390/su17041523
315. Climate and Land Use Effects on Hydrologic Processes in a Primarily Rain‐Fed, Agricultural Watershed Q. Phung et al. https://doi.org/10.1111/1752-1688.12764
316. ENSEMBLES-based assessment of regional climate effects in Luxembourg and their impact on vegetation K. Goergen et al. https://doi.org/10.1007/s10584-013-0756-x
317. Prospective analysis of soybean distribution in the Tocantins state considering climate change scenarios A. Andrade & E. Collicchio https://doi.org/10.1590/1983-40632022v5272969
318. Performance assessment of bias correction methods using observed and regional climate model data in different watersheds, Ethiopia H. Daniel https://doi.org/10.2166/wcc.2023.115
319. Post‐Processed CMIP6 Climate Projections for Hydro‐Environmental Risk Assessment in the Middle East and Central Asia P. Reggiani et al. https://doi.org/10.1002/joc.70261
320. Investigation of multi-model spatiotemporal mesoscale drought projections over India under climate change scenario V. Gupta & M. Jain https://doi.org/10.1016/j.jhydrol.2018.10.012
321. A perfect model study on the reliability of the added small-scale information in regional climate change projections G. Lenderink et al. https://doi.org/10.1007/s00382-022-06451-6
322. Exploring pathways for sustainable water management in river deltas in a changing environment M. Haasnoot et al. https://doi.org/10.1007/s10584-012-0444-2
323. Projections of climate change impacts on river flood conditions in Germany by combining three different RCMs with a regional eco-hydrological model S. Huang et al. https://doi.org/10.1007/s10584-012-0586-2
324. Projection of future streamflow changes of the Pearl River basin in China using two delta-change methods F. Yuan et al. https://doi.org/10.2166/nh.2015.159
325. Statistical bias correction of regional climate model simulations for climate change projection in the Jemma sub-basin, upper Blue Nile Basin of Ethiopia G. Worku et al. https://doi.org/10.1007/s00704-019-03053-x
326. 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
327. Performance Evaluation of Bias Correction Methods for Climate Change Monthly Precipitation Projections over Costa Rica M. Mendez et al. https://doi.org/10.3390/w12020482
328. Improving future temperature projections with bias correction methods in Lake of Guiers/Senegal B. Alioune https://doi.org/10.5897/AJEST2021.3031
329. Evaluating a hierarchy of bias correction methods for ERA5-Land SWE across Canada N. Kanda & C. Fletcher https://doi.org/10.1088/2515-7620/aded5a
330. Projected river water temperatures in Poland under climate change scenarios W. Dong et al. https://doi.org/10.1016/j.ejrh.2025.102368
331. Evaluation and Bias Correction of ECMWF Extended-Range Precipitation Forecasts over the Confluence of Asian Monsoons and Westerlies Using the Linear Scaling Method M. Tudaji et al. https://doi.org/10.3390/hydrology12080218
332. Climate variability impacts on runoff projection under quantile mapping bias correction in the support CMIP6: An investigation in Lushi basin of China P. Xue et al. https://doi.org/10.1016/j.jhydrol.2022.128550
333. Projecting rice water footprint for different shared socioeconomic pathways under arid climate conditions E. Elsadek et al. https://doi.org/10.1007/s00271-025-01019-8
334. Projected Hydrological Regime Shifts in Kazakh Rivers Under CMIP6 Climate Scenarios: Integrated Modeling and Seasonal Flow Analysis A. Nurbatsina et al. https://doi.org/10.3390/atmos16091020
335. Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations R. Rojas et al. https://doi.org/10.5194/hess-15-2599-2011
336. Assessing Long-Term Hydrological Impact of Climate Change Using an Ensemble Approach and Comparison with Global Gridded Model-A Case Study on Goodwater Creek Experimental Watershed S. Gautam et al. https://doi.org/10.3390/w10050564
337. Assessment of future water availability and seasonal patterns of dry seasons under climate change in Cidanau Watershed Banten Province, Indonesia S. Saputra et al. https://doi.org/10.1016/j.ejrh.2025.102344
338. Evaluation of Hybrid Downscaling Method Combined Regional Climate Model with Step-Wise Scaling Method M. Lee & D. Bae https://doi.org/10.3741/JKWRA.2013.46.6.585
339. The ability of societies to adapt to twenty-first-century sea-level rise J. Hinkel et al. https://doi.org/10.1038/s41558-018-0176-z
340. Downscaling of GCM-Simulated Precipitation Using Model Output Statistics J. Eden & M. Widmann https://doi.org/10.1175/JCLI-D-13-00063.1
341. Impact modelling of water resources development and climate scenarios on Zambezi River discharge H. Kling et al. https://doi.org/10.1016/j.ejrh.2014.05.002
342. Evaluating the Applicability of a Quantile–Quantile Adjustment Approach for Downscaling Monthly GCM Projections to Site Scale over the Qinghai-Tibet Plateau Z. Yin et al. https://doi.org/10.3390/atmos12091170
343. Future projections of crop water and irrigation water requirements using a bias-corrected regional climate model coupled with CROPWAT A. Agrawal et al. https://doi.org/10.2166/wcc.2023.349
344. An improved bias correction scheme based on comparative precipitation characteristics K. Kim et al. https://doi.org/10.1002/hyp.10366
345. Impacts of climatic changes on the vegetative development of olive cultivars G. Florêncio et al. https://doi.org/10.1590/1807-1929/agriambi.v23n9p641-647
346. Enhancement of RegCM4.7‐CLM precipitation and temperature by improved bias correction methods over Central Africa A. Mbienda et al. https://doi.org/10.1002/met.2116
347. Assessment of Near-Term Runoff Response at a River Basin Scale in Central Vietnam Using Direct CMIP5 High-Resolution Model Outputs D. Nam et al. https://doi.org/10.3390/w10040477
348. Climate change impact analysis on watershed using QSWAT N. Reddy et al. https://doi.org/10.1007/s41324-017-0159-6
349. Simulating maize responses to climate change using a set of agroclimatic indicators in a maize-producing region of Portugal D. Soares et al. https://doi.org/10.1016/j.agwat.2026.110435
350. Estimation of Soil Moisture Applying Modified Dubois Model to Sentinel-1; A Regional Study from Central India A. Singh et al. https://doi.org/10.3390/rs12142266
351. Projected changes in the near‐future mean climate and extreme climate events in northeast Thailand D. Khadka et al. https://doi.org/10.1002/joc.7377
352. Using climate change scenarios to evaluate future effectiveness of potential wetlands in mitigating high flows in a Midwestern U.S. watershed K. Walters & M. Babbar-Sebens https://doi.org/10.1016/j.ecoleng.2016.01.014
353. Modeling the impact of climate change on streamflow and major hydrological components of an Iranian Wadi system N. Mahmoodi et al. https://doi.org/10.2166/wcc.2020.098
354. 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
355. Evaluation of a bias correction method applied to downscaled precipitation and temperature reanalysis data for the Rhine basin W. Terink et al. https://doi.org/10.5194/hess-14-687-2010
356. Climate change projections of rainfall and its impact on the cropland suitability for rice and wheat crops in the Sone river command, Bihar S. Kumar et al. https://doi.org/10.1007/s00704-020-03319-9
357. Coupled hydrological and hydrodynamic modelling application for climate change impact assessment in the Nemunas river watershed–Curonian Lagoon–southeastern Baltic Sea continuum R. Idzelytė et al. https://doi.org/10.5194/os-19-1047-2023
358. Assessment of flash floods taking into account climate change scenarios in the Llobregat River basin M. Velasco et al. https://doi.org/10.5194/nhess-13-3145-2013
359. 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
360. Hydrological Impacts of Climate Change in a Well-preserved Upland Watershed C. de Moura et al. https://doi.org/10.1007/s11269-019-02450-1
361. An analysis of the performance of RCMs in simulating current climate over western Canada E. Barrow & D. Sauchyn https://doi.org/10.1002/joc.5028
362. 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
363. Bias Correction in CMIP6 Models Simulations and Projections for Brazil’s Climate Assessment L. Brumatti et al. https://doi.org/10.1007/s41748-023-00368-8
364. Comparison of precipitation projections of CMIP5 and CMIP6 global climate models over Yulin, China M. Shiru et al. https://doi.org/10.1007/s00704-021-03823-6
365. A novel procedure for monitoring temperature characteristics using multiple climate projections R. Khalil & Z. Ali https://doi.org/10.1007/s00477-025-03031-y
366. Attribution of Hydrologic Changes in a Tropical River Basin to Rainfall Variability and Land-Use Change: Case Study from India S. Setti et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001937
367. Impact of GCM structure uncertainty on hydrological processes in an arid area of China G. Fang et al. https://doi.org/10.2166/nh.2017.227
368. Impact of climate change on the flow of the Doce River basin F. Costa et al. https://doi.org/10.1590/2318-0331.272220220069
369. Spatiotemporal characteristics and hydrological implications of downscaled hourly precipitation climate scenarios for South Korea T. Lee et al. https://doi.org/10.1002/joc.7300
370. Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield T. Hu et al. https://doi.org/10.1016/j.agrformet.2023.109458
371. Simulating maize response to historical climate variability in a main maize-producing region of Portugal D. Soares et al. https://doi.org/10.1016/j.agwat.2026.110611
372. Future high- and low-flow estimations for Central Vietnam: a hydro-meteorological modelling chain approach Q. Dang et al. https://doi.org/10.1080/02626667.2017.1353696
373. Assessing the effects of land cover and future climate conditions on the provision of hydrological services in a medium-sized watershed of Portugal C. Carvalho-Santos et al. https://doi.org/10.1002/hyp.10621
374. Bias Correction of Mixed Distributions of Temperature with Strong Diurnal Signal M. Haider et al. https://doi.org/10.1175/WAF-D-21-0108.1
375. Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin R. Haren et al. https://doi.org/10.1088/1748-9326/8/1/014053
376. A multimodel assessment of drought characteristics and risks over the Huang-Huai-Hai River basin, China, under climate change C. Dai et al. https://doi.org/10.1007/s00704-020-03236-x
377. Assessment of climate change impact on water resources in the Pungwe river basin L. Andersson et al. https://doi.org/10.1111/j.1600-0870.2010.00480.x
378. Assessment of Climate Change Impact on Future Streamflow of Periyar River Basin, India, Using SWAT Model L. Barman et al. https://doi.org/10.1007/s41976-025-00255-y
379. Continental-scale bias correction and random forest downscaling of CMIP6 precipitation across Europe S. Doshi et al. https://doi.org/10.1080/10106049.2026.2657618
380. Evaluation of future flow variability in ungauged basins: Validation of combined methods J. Samuel et al. https://doi.org/10.1016/j.advwatres.2011.09.015
381. Evaluating Future Stream Flow by Operation of Agricultural Reservoir Group considering the RCP 8.5 Climate Change Scenario J. Lee & J. Noh https://doi.org/10.5389/KSAE.2015.57.5.113
382. Impact of Climate Change on Drought in the Upstream Yangtze River Region G. Lu et al. https://doi.org/10.3390/w8120576
383. Elevation dependency of snowfall changes under climate change over the Tibetan Plateau: Evidence from CMIP6 GCMs Y. Gao et al. https://doi.org/10.1016/j.atmosres.2024.107832
384. Accuracy assessment and bias correction of remote sensing–based rainfall products over semiarid watersheds H. Ouatiki et al. https://doi.org/10.1007/s00704-023-04586-y
385. Novel application of a process convolution approach for calibrating output from numerical models M. Holthuijzen et al. https://doi.org/10.1002/env.2822
386. Daily gridded temperature and precipitation datasets over the Black Sea catchment: 1961–1990 and climate change scenarios for 2071–2100 A. Gago-Silva et al. https://doi.org/10.1007/s00704-020-03147-x
387. Finding appropriate bias correction methods in downscaling precipitation for hydrologic impact studies over North America J. Chen et al. https://doi.org/10.1002/wrcr.20331
388. Characterisation of the Sensitivity of Water Resources Systems to Climate Change A. Chavez-Jimenez et al. https://doi.org/10.1007/s11269-013-0404-2
389. 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
390. Evaluation of corrected APHRODITE estimates for hydrological simulation in the Yarlung Tsangpo–Brahmaputra River Basin X. Luo et al. https://doi.org/10.1002/joc.6449
391. Continental-scale bias-corrected climate and hydrological projections for Australia J. Peter et al. https://doi.org/10.5194/gmd-17-2755-2024
392. Climate Change and Reservoir Impacts on 21st-Century Streamflow and Fluvial Sediment Loads in the Irrawaddy River, Myanmar T. Sirisena et al. https://doi.org/10.3389/feart.2021.644527
393. Projection of future non-stationary intensity-duration-frequency curves using the pooled CMIP6 climate models A. Mianabadi et al. https://doi.org/10.1007/s11069-024-06779-8
394. SSAS: Spatiotemporal Scale Adaptive Selection for Improving Bias Correction on Precipitation Y. Liu et al. https://doi.org/10.1109/TCYB.2021.3072483
395. Lapse rate-adjusted bias correction for CMIP6 GCM precipitation data: An application to the Monsoon Asia Region M. Shanmugam et al. https://doi.org/10.1007/s10661-023-12187-5
396. 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
397. Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments A. Sharma et al. https://doi.org/10.2166/wcc.2023.230
398. Improving CMIP6 projections of daily precipitation using a mean-adjusted time variability correction technique Y. Shao & C. Bishop https://doi.org/10.1007/s00382-025-07731-7
399. Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction Z. Deng et al. https://doi.org/10.1007/s00382-017-3931-3
400. Impacts of climate change on temperature, precipitation and hydrology in Finland – studies using bias corrected Regional Climate Model data T. Olsson et al. https://doi.org/10.5194/hess-19-3217-2015
401. Climate Change Adaptation Measures in the Irrigation of a Super-Intensive Olive Orchard in the South of Portugal S. Branquinho et al. https://doi.org/10.3390/agronomy11081658
402. Investigating the Performance of CMIP6 Seasonal Precipitation Predictions and a Grid Based Model Heterogeneity Oriented Deep Learning Bias Correction Framework B. Huang et al. https://doi.org/10.1029/2023JD039046
403. Simulating future trends in hydrological regimes in Western Switzerland M. Milano et al. https://doi.org/10.1016/j.ejrh.2015.10.010
404. Time Scale Decomposition of Climate and Correction of Variability Using Synthetic Samples of Stable Distributions M. Gomez‐Garcia et al. https://doi.org/10.1029/2018WR023053
405. Hydrologic Impacts of Surface Elevation and Spatial Resolution in Statistical Correction Approaches: Case Study of Flumendosa Basin, Italy E. Perra et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001969
406. Assessing Climate Change Impacts on Precipitation and Temperature in a Mediterranean Basin under CMIP6 Scenarios E. Yalcin & K. Koparal Bozkurt https://doi.org/10.34248/bsengineering.1746627
407. Responses of Hydrological Processes under Different Shared Socioeconomic Pathway Scenarios in the Huaihe River Basin, China Y. Yao et al. https://doi.org/10.3390/w13081053
408. Peak Water Levels Rise Less Than Mean Sea Level in Tidal Channels Subject to Depth Convergence by Deepening J. Leuven et al. https://doi.org/10.1029/2022JC019578
409. Detecting Rising Wildfire Risks for South East England V. Thompson et al. https://doi.org/10.1002/cli2.70002
410. Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling R. Kim et al. https://doi.org/10.5194/tc-15-771-2021
411. Trend analysis for integrated regional climate change impact assessments in the Lusatian river catchments (north-eastern Germany) A. Gädeke et al. https://doi.org/10.1007/s10113-017-1138-0
412. Assessment of water resources and crop yield under future climate scenarios: A case study in a Warangal district of Telangana, India T. Chanapathi et al. https://doi.org/10.1007/s12040-019-1294-3
413. Forecasting the groundwater levels in the Baltic through standardized index analysis A. Babre et al. https://doi.org/10.1016/j.wace.2024.100728
414. Development of framework for assessment of impact of climate change in a command of water resource project R. Jaiswal et al. https://doi.org/10.1007/s12040-019-1328-x
415. Analysis of the spatiotemporal changes in global tropospheric ozone concentrations from 1980 to 2020 B. Liang et al. https://doi.org/10.1016/j.scitotenv.2024.175817
416. Conditioning model output statistics of regional climate model precipitation on circulation patterns F. Wetterhall et al. https://doi.org/10.5194/npg-19-623-2012
417. Potential future impact of climate change on recharge in the Sierra de las Nieves (southern Spain) high-relief karst aquifer using regional climate models and statistical corrections E. Pardo-Igúzquiza et al. https://doi.org/10.1007/s12665-019-8594-4
418. 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
419. The Polar WRF Downscaled Historical and Projected Twenty-First Century Climate for the Coast and Foothills of Arctic Alaska L. Cai et al. https://doi.org/10.3389/feart.2017.00111
420. Does bias correction increase reliability of flood projections under climate change? A case study of large rivers in Germany S. Huang et al. https://doi.org/10.1002/joc.3945
421. Evaluation and selection of CORDEX-SA datasets and bias correction methods for a hydrological impact study in a humid tropical river basin, Kerala M. Saranya & V. Nair Vinish https://doi.org/10.2166/wcc.2021.139
422. Testing the Hydrological Coherence of High‐Resolution Gridded Precipitation and Temperature Data Sets L. Laiti et al. https://doi.org/10.1002/2017WR021633
423. An assessment of gridded precipitation products over High Mountain Asia I. Dollan et al. https://doi.org/10.1016/j.ejrh.2024.101675
424. Present and future climate conditions for winegrowing in Spain M. Lorenzo et al. https://doi.org/10.1007/s10113-015-0883-1
425. Response of runoff and sediment transport process to climate change in the headwater regions of Yangtze River L. Wang et al. https://doi.org/10.1016/j.jhydrol.2026.135079
426. Modeling suspended sediment transport and assessing the impacts of climate change in a karstic Mediterranean watershed S. Nerantzaki et al. https://doi.org/10.1016/j.scitotenv.2015.07.092
427. Farklı yanlılık düzeltme yöntemlerinin istatistiksel ölçeğe indirgenmiş yağış projeksiyonlarına uygulanması U. KIRDEMİR & U. OKKAN https://doi.org/10.25092/baunfbed.654535
428. Impacts of climate change on rice yields in the Nile River Delta of Egypt: A large-scale projection analysis based on CMIP6 E. Elsadek et al. https://doi.org/10.1016/j.agwat.2024.108673
429. Assessing Future Impacts of Climate Change on Water Supply System Performance: Application to the Pozzillo Reservoir in Sicily, Italy D. Peres et al. https://doi.org/10.3390/w11122531
430. Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment) S. Marahatta et al. https://doi.org/10.3390/w13111548
431. Integrating Climate Modelling, Downscaling, and Bias Correction for Drought Studies: Current Approaches and Future Directions C. Naresh & A. Mathew https://doi.org/10.1007/s11269-026-04843-5
432. A multimodel assessment of climate change impacts on extreme hydrological drought under CMIP6-SSP scenarios in the Hanjiang River Basin, China H. Zhu et al. https://doi.org/10.1007/s10113-025-02485-8
433. Impacts of climate change on streamflow and sediment concentration under RCP 4.5 and 8.5: A case study in Purna river basin, India A. Nilawar & M. Waikar https://doi.org/10.1016/j.scitotenv.2018.09.334
434. Daily climate data for the Amhara region in Northwestern Ethiopia K. Sisay et al. https://doi.org/10.1002/joc.4880
435. 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
436. Climate change impact to Mackenzie river Basin projected by a regional climate model C. Kuo et al. https://doi.org/10.1007/s00382-020-05177-7
437. Selection of general circulation models for the projections of spatio-temporal changes in temperature of Borneo Island based on CMIP5 Z. Sa’adi et al. https://doi.org/10.1007/s00704-019-02948-z
438. Simulation of structural and non-structural measures for climate change adaptation in water resources systems in the Capibaribe and Ipojuca River basins, Pernambuco state, Brazil L. Costa Ferreira Nunes & A. Ribeiro Neto https://doi.org/10.2166/wcc.2025.502
439. Estimated changes in flood quantiles of the river Meuse from resampling of regional climate model output R. Leander et al. https://doi.org/10.1016/j.jhydrol.2007.12.020
440. Snow depth reconstruction over last century: Trend and distribution in the Tianshan Mountains, China Q. Li et al. https://doi.org/10.1016/j.gloplacha.2018.12.008
441. On the Benefits of Bias Correction Techniques for Streamflow Simulation in Complex Terrain Catchments: A Case-Study for the Chitral River Basin in Pakistan M. Usman et al. https://doi.org/10.3390/hydrology9110188
442. Evaluating the Impact of Statistical Bias Correction on Climate Change Signal and Extreme Indices in the Jemma Sub-Basin of Blue Nile Basin G. Tefera et al. https://doi.org/10.3390/su151310513
443. Climate change impact assessment on a German lowland river using long short-term memory and conceptual hydrological models A. Ley et al. https://doi.org/10.1016/j.ejrh.2025.102426
444. Assessment of PERSIANN Satellite Products over the Tulijá River Basin, Mexico L. Ceferino-Hernández et al. https://doi.org/10.3390/rs16142596
445. Evaluating watershed hydrological responses to climate changes at Hangar Watershed, Ethiopia A. Galata et al. https://doi.org/10.2166/wcc.2021.229
446. Evaluating the impact of climate change on extreme temperature and precipitation events over the Kashmir Himalaya S. Ahsan et al. https://doi.org/10.1007/s00382-021-05984-6
447. Cloud obstruction and snow cover in Alpine areas from MODIS products P. Da Ronco & C. De Michele https://doi.org/10.5194/hess-18-4579-2014
448. Assessing potential flood vulnerability to climate change by CMIP3 and CMIP5 models: case study of the 2011 Thailand great flood S. Supharatid et al. https://doi.org/10.2166/wcc.2015.116
449. Time-Varying Evaluation of Compound Drought and Hot Extremes in Machine Learning–Predicted Ensemble CMIP5 Future Climate: A Multivariate Multi-Index Approach S. Swain et al. https://doi.org/10.1061/JHYEFF.HEENG-6026
450. Multisite bias correction of precipitation data from regional climate models J. Hnilica et al. https://doi.org/10.1002/joc.4890
451. The optimal bias correction for daily extreme precipitation indices over the Yangtze-Huaihe River Basin, insight from BCC-CSM1.1-m L. Zhu et al. https://doi.org/10.1016/j.atmosres.2022.106101
452. Identifying appropriate prediction models for estimating hourly temperature over diverse agro-ecological regions of India S. Bal et al. https://doi.org/10.1038/s41598-023-34194-9
453. Characteristics of extreme meteorological droughts over the Brazilian Pantanal throughout the 21st century V. Silva et al. https://doi.org/10.3389/frwa.2024.1385077
454. Water resources system vulnerability in high mountain areas under climate change L. Wang et al. https://doi.org/10.1016/j.jclepro.2023.136789
455. Recent snow cover changes over central European low mountain ranges C. Dong & L. Menzel https://doi.org/10.1002/hyp.13586
456. Assessing climate change impacts on hydrology from an ensemble of regional climate models, model scales and linking methods – a case study on the Lule River basin L. Graham et al. https://doi.org/10.1007/s10584-006-9215-2
457. Assessing the Impact of Climate Change on Sediment Loads in a Large Mediterranean Watershed S. Nerantzaki et al. https://doi.org/10.1097/SS.0000000000000164
458. Comparing Bias Correction Methods Used in Downscaling Precipitation and Temperature from Regional Climate Models: A Case Study from the Kaidu River Basin in Western China M. Luo et al. https://doi.org/10.3390/w10081046
459. Using a Hydrologic Model to Assess the Performance of Regional Climate Models in a Semi-Arid Watershed in Brazil C. Santos et al. https://doi.org/10.3390/w11010170
460. An Analysis of Non-stationary Drought Conditions in Parana State Based on Climate Change Scenarios R. Ploszai et al. https://doi.org/10.1007/s11269-022-03143-y
461. Assessment of Flood Risk Map under Climate Change RCP8.5 Scenarios in Taiwan Y. Chen et al. https://doi.org/10.3390/w14020207
462. Investigating the Outlook of Precipitation Changes in the Great Karun Using by CMIP5 series models z. mokhayeri et al. https://doi.org/10.61186/jgs.25.76.3
463. Review of bias correction methods for climate model outputs in hydrology A. Menapace et al. https://doi.org/10.1016/j.jhydrol.2025.133213
464. Assessment of rainfall bias correction techniques for improved hydrological simulation U. Ghimire et al. https://doi.org/10.1002/joc.5959
465. Statistical Bias Correction for Simulated Wind Speeds Over CORDEX‐East Asia D. Li et al. https://doi.org/10.1029/2018EA000493
466. Projection of low flow conditions in Germany under climate change by combining three RCMs and a regional hydrological model S. Huang et al. https://doi.org/10.2478/s11600-012-0065-1
467. Derivation of RCM-driven potential evapotranspiration for hydrological climate change impact analysis in Great Britain: a comparison of methods and associated uncertainty in future projections C. Prudhomme & J. Williamson https://doi.org/10.5194/hess-17-1365-2013
468. Skill of precipitation projectionin the Chao Phraya river Basinby multi-model ensemble CMIP3-CMIP5 S. Supharatid https://doi.org/10.1016/j.wace.2016.03.001
469. Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change T. van der Pol et al. https://doi.org/10.1016/j.jenvman.2015.02.016
470. Bias correction and characterization of climate forecast system re‐analysis daily precipitation in Ethiopia using fuzzy overlay B. Berhanu et al. https://doi.org/10.1002/met.1549
471. Bias correction of a gauge-based gridded product to improve extreme precipitation analysis in the Yarlung Tsangpo–Brahmaputra River basin X. Luo et al. https://doi.org/10.5194/nhess-20-2243-2020
472. Evaluation of Future Climate and Potential Impact on Streamflow in the Upper Nan River Basin of Northern Thailand M. Gunathilake et al. https://doi.org/10.1155/2020/8881118
473. Variation of Leaf Area Index (LAI) under Changing Climate: Kadolkele Mangrove Forest, Sri Lanka R. Makumbura et al. https://doi.org/10.1155/2022/9693303
474. Prediction of area burned under climatic change scenarios: A case study in the Great Xing’an Mountains boreal forest G. Yang et al. https://doi.org/10.1007/s11676-010-0035-x
475. AS INCERTEZAS ASSOCIADAS ÀS CONDIÇÕES CLIMÁTICAS OBTIDAS PELO MODELO ETA CPTEC/HADCM3: AVALIAÇÃO COMPARATIVA ENTRE OS DADOS SIMULADOS E OBSERVADOS DE PRECIPITAÇÃO, EVAPOTRANSPIRAÇÃO E VAZÃO NA BACIA HIDROGRÁFICA DO RIO IJUÍ, BRASIL. G. Oliveira et al. https://doi.org/10.1590/0102-778620140041
476. Assessment of climate change impacts on streamflow and hydropower potential in the headwater region of the Grande river basin, Southeastern Brazil V. de Oliveira et al. https://doi.org/10.1002/joc.5138
477. Projeção dos Eventos de Seca Meteorológica e Hidrológica na Bacia Hidrográfica do Rio Verde C. Oliveira et al. https://doi.org/10.1590/0102-7786390059
478. Projected Streamflow and Sediment Supply under Changing Climate to the Coast of the Kalu River Basin in Tropical Sri Lanka over the 21st Century T. Sirisena et al. https://doi.org/10.3390/w13213031
479. Comparing bias adjustment methods for CMIP6 extreme precipitation projections in the San-Pédro River Basin (Côte d’Ivoire, West Africa) F. Akaffou et al. https://doi.org/10.1007/s00704-026-06043-y
480. Nature rehabilitation by floodplain excavation: The hydraulic effect of 16 years of sedimentation and vegetation succession along the Waal River, NL G. Geerling et al. https://doi.org/10.1016/j.geomorph.2007.11.011
481. Water security implications of climate and socio-economic stressors for river basin management Q. Dau & A. Adeloye https://doi.org/10.1080/02626667.2021.1909032
482. Bias Correction of Zero-Inflated RCM Precipitation Fields: A Copula-Based Scheme for Both Mean and Extreme Conditions R. Maity et al. https://doi.org/10.1175/JHM-D-18-0126.1
483. Quantifying the contributions of multi-source uncertainty to multi-time scale indicators in hydrological modeling under climate change Y. Ye et al. https://doi.org/10.1016/j.ejrh.2024.101845
484. Projected Intensification and Persistence of Drought in Southeastern Anatolia, Turkey: A Multi-Index Analysis Based on CMIP6 Multi-Model Ensemble Projections E. Yalcin et al. https://doi.org/10.1007/s00024-026-04017-9
485. Multi-site multivariate downscaling of global climate model outputs: an integrated framework combining quantile mapping, stochastic weather generator and Empirical Copula approaches X. Li & V. Babovic https://doi.org/10.1007/s00382-018-4480-0
486. Adaptation by Himalayan Water Resource System under a Sustainable Socioeconomic Pathway in a High-Emission Context Q. Dau et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002064
487. Improving the Accuracy of Rainfall Prediction Using Bias-Corrected NMME Outputs: A Case Study of Surabaya City, Indonesia D. Faidah et al. https://doi.org/10.1155/2022/9779829
488. Assessment of trends in climatic extremes from observational data in the Kashmir basin, NW Himalaya S. Ahsan et al. https://doi.org/10.1007/s10661-021-09439-7
489. Integrated Climate, Pest, and Disease Risk Indicators for Pinus Plantations Under Current and Future Climates R. Xavier et al. https://doi.org/10.1007/s41748-026-01195-3
490. Prediction of Future Lake Water Availability Using SWAT and Support Vector Regression (SVR) S. Jayanthi et al. https://doi.org/10.3390/su14126974
491. Impacts of Bias‐Corrected ERA5 Initial Snow Depth on Dynamical Downscaling Simulations for the Tibetan Plateau Q. Lin et al. https://doi.org/10.1029/2021JD035625
492. Changes in Streamflow Dynamics in the Rhine Basin under Three High-Resolution Regional Climate Scenarios R. Hurkmans et al. https://doi.org/10.1175/2009JCLI3066.1
493. The drying up of Britain? A national estimate of changes in seasonal river flows from 11 Regional Climate Model simulations C. Prudhomme et al. https://doi.org/10.1002/hyp.8434
494. State‐of‐the‐art with regional climate models M. Rummukainen https://doi.org/10.1002/wcc.8
495. Performance Assessment of Bias Correction Methods for Precipitation and Temperature from CMIP5 Model Simulation D. Londhe et al. https://doi.org/10.3390/app13169142
496. Uncertainties in streamflow projections: a comprehensive examination of variabilities arising from climate and hydrological models in the Tahtali Dam Basin, Turkey U. Kirdemir et al. https://doi.org/10.1007/s00704-025-05416-z
497. Modelling the IDF curves using the temporal stochastic disaggregation BLRP model for precipitation data in Najaf City A. Hayder & M. Al-Mukhtar https://doi.org/10.1007/s12517-021-08314-6
498. Multi-model ensembles for regional and national wheat yield forecasts in Argentina M. Zachow et al. https://doi.org/10.1088/1748-9326/ad627c
499. Water Resources Impact Assessment Under Climate Change Scenarios in Mediterranean Watersheds S. Mourato et al. https://doi.org/10.1007/s11269-015-0947-5
500. Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user D. Maraun et al. https://doi.org/10.1029/2009RG000314
501. To bias correct or not to bias correct? An agricultural impact modelers’ perspective on regional climate model data P. Laux et al. https://doi.org/10.1016/j.agrformet.2021.108406
502. Climate risks and vulnerabilities of the Arabica coffee in Brazil under current and future climates considering new CMIP6 models C. Dias et al. https://doi.org/10.1016/j.scitotenv.2023.167753
503. Future variability of droughts in three Mediterranean catchments J. Lopez-Bustins et al. https://doi.org/10.1007/s11069-013-0754-3
504. Bias correction for near-real-time estimation of snow water equivalent using machine learning algorithms: A case study in the Tuolumne River basin, California K. Yang et al. https://doi.org/10.1016/j.rse.2025.114693
505. Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections J. Junk et al. https://doi.org/10.1007/s00484-015-0966-1
506. Precipitation ensembles conforming to natural variations derived from a regional climate model using a new bias correction scheme K. Kim et al. https://doi.org/10.5194/hess-20-2019-2016