37 citations as recorded by crossref.

1. Climate change impact on extreme precipitation and peak flood magnitude and frequency: observations from CMIP6 and hydrological models H. Meresa et al. https://doi.org/10.1007/s11069-021-05152-3
2. Integral recovery of an urban watershed through the implementation of nature-based solutions R. Bonilla Brenes et al. https://doi.org/10.3389/frsus.2024.1425732
3. 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
4. Hydrological climate change impact assessment in high latitudes: are bucket-type models up to the task? A. Todorović et al. https://doi.org/10.1016/j.envsoft.2026.106964
5. Advanced artificial intelligence and remote sensing for earth observation–based tree crop monitoring: A global review with african perspectives A. Moussaid et al. https://doi.org/10.1016/j.neucom.2026.134165
6. Projected Changes in Spatiotemporal Propagation of Droughts Over the Loess Plateau: Roles of Climate and Vegetation Change F. Ma et al. https://doi.org/10.1002/hyp.70246
7. Performance assessment of six bias correction methods using observed and RCM data at upper Awash basin, Oromia, Ethiopia B. Tumsa https://doi.org/10.2166/wcc.2021.181
8. Precipitation Concentration Impact on Flood frequency, Periodicities and Return Periods in Kaduna River E. Okonofua et al. https://doi.org/10.37933/nipes/7.3.2025.1464
9. Leveraging River Network Topology and Regionalization to Expand SWOT-Derived River Discharge Time Series in the Mississippi River Basin C. Nickles & E. Beighley https://doi.org/10.3390/rs13081590
10. Improving explainable AI in attributing hydrological responses to climate variabilities in snow-dominated watersheds J. Hui et al. https://doi.org/10.1016/j.asoc.2025.113682
11. Aridity shifts in the MENA region under the Paris Agreement climate change scenarios M. Hamed et al. https://doi.org/10.1016/j.gloplacha.2024.104483
12. Relative impacts of climate change and land cover change on streamflow using SWAT in the Clackamas River Watershed, USA J. Chen & H. Chang https://doi.org/10.2166/wcc.2020.123
13. Assessing the Runoff Response to Vegetation Cover and Climate Change in a Typical Forested Headwater Watershed G. Zhang et al. https://doi.org/10.1007/s11269-025-04155-0
14. Recent changes to Arctic river discharge D. Feng et al. https://doi.org/10.1038/s41467-021-27228-1
15. Uncertainty in estimating the relative change of design floods under climate change: a stylized experiment with process-based, deep learning, and hybrid models S. Poudel et al. https://doi.org/10.1016/j.jhydrol.2025.134427
16. GHydroMod-SIM-DAI v1.0: A new distributed hydrological model capable of dynamically recognizing runoff generation mechanisms and accounting for aboveground and underground anthropogenic impacts Y. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.134184
17. Quantifying the impacts of land cover change on hydrological responses in the Mahanadi river basin in India S. Naha et al. https://doi.org/10.5194/hess-25-6339-2021
18. Advancing traditional strategies for testing hydrological model fitness in a changing climate A. Todorović et al. https://doi.org/10.1080/02626667.2022.2104646
19. 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
20. Future climate impacts on the hydrology of headwater streams in the Amazon River Basin: Implications for migratory goliath catfishes D. Feng et al. https://doi.org/10.1002/hyp.13952
21. Exploring the Potential of Multi-Hydrological Model Weighting Schemes to Reduce Uncertainty in Runoff Projections Z. Ersoy et al. https://doi.org/10.3390/w17202919
22. Runoff simulation of the Kaidu River Basin based on the GR4J-6 and GR4J-6-LSTM models J. Yang et al. https://doi.org/10.1016/j.ejrh.2024.102034
23. Soft Data in Hydrologic Modeling: Prediction of Ecologically Relevant Flows with Alternate Land Use/Land Cover Data H. Haas et al. https://doi.org/10.3390/w13212947
24. 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
25. The Applicability of SWOT’s Non-Uniform Space–Time Sampling in Hydrologic Model Calibration C. Nickles et al. https://doi.org/10.3390/rs12193241
26. Integrating hydrologic response into climate change model evaluation and machine learning-based multi-model ensemble approach for extreme climate indices and spatio-temporal projections M. Pujari & R. Swain https://doi.org/10.1007/s12040-026-02958-2
27. Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city: the case of Shanghai H. Xu et al. https://doi.org/10.5194/nhess-22-2347-2022
28. Importance of Parameter and Climate Data Uncertainty for Future Changes in Boreal Hydrology A. Marshall et al. https://doi.org/10.1029/2021WR029911
29. Multi-Model Assessment of Streamflow Simulations under Climate and Anthropogenic Changes Exemplified in Two Indian River Basins A. Somisetty et al. https://doi.org/10.3390/w14020194
30. Quantifying the contribution of SWAT modeling and CMIP6 inputting to streamflow prediction uncertainty under climate change C. Chen et al. https://doi.org/10.1016/j.jclepro.2022.132675
31. Revolutionizing the future of hydrological science: Impact of machine learning and deep learning amidst emerging explainable AI and transfer learning R. Maity et al. https://doi.org/10.1016/j.acags.2024.100206
32. Adapting cities to the surge: A comprehensive review of climate-induced urban flooding G. Dharmarathne et al. https://doi.org/10.1016/j.rineng.2024.102123
33. Impacts of Climate Change on the Hydrology of a Highly Disturbed Tropical River Basin C. Alvarenga et al. https://doi.org/10.3390/earth7020052
34. Assessment of Basin‐Scale Concurrent Dry and Wet Extreme Dynamics Under Multimodel CORDEX Climate Scenarios S. Swain et al. https://doi.org/10.1002/joc.8677
35. Application of a Fractional Instantaneous Unit Hydrograph in the TOPMODEL: A Case Study in Chengcun Basin, China X. Xiang et al. https://doi.org/10.3390/app13042245
36. Assessment of hydrological parameter uncertainty versus climate projection spread on urban streamflow and floods Z. Ul Hassan et al. https://doi.org/10.1016/j.jhydrol.2024.131546
37. Long-term effects of forest growth dynamics and climate change on groundwater recharge and evapotranspiration in a steep catchment of western Japan R. Guyo et al. https://doi.org/10.1016/j.ecolind.2025.113652