11 citations as recorded by crossref.

1. Testing sensitivity of BILAN and GR2M models to climate conditions in the Gambia River Basin D. Ba et al. 10.2478/johh-2023-0044
2. On the application of rainfall projections from a convection-permitting climate model to lumped catchment models M. Ascott et al. 10.1016/j.jhydrol.2023.129097
3. New hybrid GR6J-wavelet-based genetic algorithm-artificial neural network (GR6J-WGANN) conceptual-data-driven model approaches for daily rainfall–runoff modelling C. Sezen & T. Partal 10.1007/s00521-022-07372-5
4. Sensitivity of global hydrological models to potential evapotranspiration estimation methods in the Senegal River Basin (West Africa) P. Ndiaye et al. 10.1016/j.ejrh.2024.101823
5. Evaluation of potential evapotranspiration assessment methods for hydrological modelling with SWAT in the Densu river basin in Ghana F. Adjei et al. 10.1007/s13762-022-03945-y
6. Trees diversity explains variations in biodiversity-ecosystem function relationships across environmental gradients and conservation status in riparian corridors S. Kinnoumè et al. 10.3389/ffgc.2024.1291252
7. Improving the simulations of the hydrological model in the karst catchment by integrating the conceptual model with machine learning models C. Sezen & M. Šraj 10.1016/j.scitotenv.2024.171684
8. Hourly rainfall-runoff modelling by combining the conceptual model with machine learning models in mostly karst Ljubljanica River catchment in Slovenia C. Sezen & M. Šraj 10.1007/s00477-023-02607-w
9. Two integrated conceptual–wavelet-based data-driven model approaches for daily rainfall–runoff modelling C. Sezen & T. Partal 10.2166/hydro.2022.171
10. Comparison of Three Daily Rainfall-Runoff Hydrological Models Using Four Evapotranspiration Models in Four Small Forested Watersheds with Different Land Cover in South-Central Chile N. Flores et al. 10.3390/w13223191
11. Quantification of climate change sensitivity of shallow and deep groundwater in Denmark I. Seidenfaden et al. 10.1016/j.ejrh.2022.101100