31 citations as recorded by crossref.

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2. 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
3. Vulnerability of groundwater quantity for an arid coastal aquifer under the climate change and extensive exploitation K. Soliman & D. Amin https://doi.org/10.1007/s13201-025-02404-6
4. Impact of climate change on the vulnerability of drinking water intakes in a northern region B. Leveque et al. https://doi.org/10.1016/j.scs.2020.102656
5. Global Projections of Storm Surges Using High‐Resolution CMIP6 Climate Models S. Muis et al. https://doi.org/10.1029/2023EF003479
6. On projected hydrological scenarios under the influence of bias-corrected climatic variables and LULC S. Sahoo et al. https://doi.org/10.1016/j.ecolind.2019.105440
7. Fidelity of reanalysis datasets in floodplain mapping: Investigating performance at inundation level over large regions M. Mohanty & S. Simonovic https://doi.org/10.1016/j.jhydrol.2020.125757
8. Future water availability in the largest freshwater Mediterranean lake is at great risk as evidenced from simulations with the SWAT model T. Bucak et al. https://doi.org/10.1016/j.scitotenv.2016.12.149
9. The Effect of Climate Change on Forest Fire Danger and Severity in the Canadian Boreal Forests for the Period 1976–2100 Y. Wang https://doi.org/10.1029/2023JD039118
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11. Catchment response to climate change under CMIP6 scenarios: a case study of the Krishna River Basin S. Anil et al. https://doi.org/10.2166/wcc.2024.442
12. Remaining error sources in bias-corrected climate model outputs J. Chen et al. https://doi.org/10.1007/s10584-020-02744-z
13. Consortium of Management Practices in Long-Run Improves Soil Fertility and Carbon Sequestration in Drylands of Semi-Arid Tropics G. Chander et al. https://doi.org/10.1007/s42106-023-00249-0
14. Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions I. Pechlivanidis et al. https://doi.org/10.1007/s10584-016-1723-0
15. Evaluation of a New Statistical Method—TIN-Copula–for the Bias Correction of Climate Models’ Extreme Parameters G. Lazoglou et al. https://doi.org/10.3390/atmos11030243
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17. Towards Reducing Climate Change Impact Assessment Process Uncertainty A. Gaur & S. Simonovic https://doi.org/10.1007/s40710-015-0070-x
18. Review of bias correction methods for climate model outputs in hydrology A. Menapace et al. https://doi.org/10.1016/j.jhydrol.2025.133213
19. Bias correction of surface air temperature and precipitation in CORDEX East Asia simulation: What should we do when applying bias correction? J. Chen et al. https://doi.org/10.1016/j.atmosres.2022.106439
20. An exhaustive investigation of changes in projected extreme precipitation indices and streamflow using CMIP6 climate models: A case study S. Anil & P. Raj https://doi.org/10.1007/s12040-024-02267-6
21. Climate change impact on river flow extremes in the Upper Blue Nile River basin H. Meresa & M. Gatachew https://doi.org/10.2166/wcc.2018.154
22. Bias correction of CMIP6 GCMs for historical and future air temperatures across China S. Wei et al. https://doi.org/10.1016/j.atmosres.2025.108193
23. Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6 V. Mishra et al. https://doi.org/10.1038/s41597-020-00681-1
24. Impacts of Climate Change on the Precipitation and Streamflow Regimes in Equatorial Regions: Guayas River Basin M. Ilbay-Yupa et al. https://doi.org/10.3390/w13213138
25. Global Climate Model Selection for Analysis of Uncertainty in Climate Change Impact Assessments of Hydro-Climatic Extremes P. Breach et al. https://doi.org/10.4236/ajcc.2016.54036
26. 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
27. Projection of Future Extreme Precipitation and Flood Changes of the Jinsha River Basin in China Based on CMIP5 Climate Models Z. Yuan et al. https://doi.org/10.3390/ijerph15112491
28. Modeling Hydrological and Environmental Consequences of Climate Change and Urbanization in the Boise River Watershed, Idaho J. Kim & J. Ryu https://doi.org/10.1111/1752-1688.12712
29. Using Natural Variability as a Baseline to Evaluate the Performance of Bias Correction Methods in Hydrological Climate Change Impact Studies J. Chen et al. https://doi.org/10.1175/JHM-D-15-0099.1
30. 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
31. 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