19 citations as recorded by crossref.

1. Large‐scale hydrology: advances in understanding processes, dynamics and models from beyond river basin to global scale H. Cloke & D. Hannah https://doi.org/10.1002/hyp.8059
2. Macro-HyProS: A new macro-scale hydrologic processes simulator for depression-dominated cold climate regions M. Tahmasebi Nasab & X. Chu https://doi.org/10.1016/j.jhydrol.2019.124366
3. Global hydrological models: a review A. Sood & V. Smakhtin https://doi.org/10.1080/02626667.2014.950580
4. Extending the historical in situ gauge network over Indian river reaches utilizing the Surface Water and Ocean Topography (SWOT) mission M. Soman & J. Indu https://doi.org/10.1080/02626667.2024.2368755
5. Hydrologic impacts of climate change: Comparisons between hydrological parameter uncertainty and climate model uncertainty J. Joseph et al. https://doi.org/10.1016/j.jhydrol.2018.08.080
6. Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins D. Raje et al. https://doi.org/10.1002/hyp.9731
7. Flood frequency under changing climate in the upper Kafue River basin, southern Africa: a large scale hydrological model application C. Ngongondo et al. https://doi.org/10.1007/s00477-013-0724-z
8. Macro-scale grid-based and subbasin-based hydrologic modeling: joint simulation and cross-calibration X. Chu et al. https://doi.org/10.2166/hydro.2018.026
9. Decision support systems in water resources in the demarcated region of Douro – case study in Pinhão river basin, Portugal L. Fernandes et al. https://doi.org/10.1111/wej.12042
10. Selecting hydrological models for developing countries: Perspective of global, continental, and country scale models over catchment scale models P. Paul et al. https://doi.org/10.1016/j.jhydrol.2021.126561
11. Effects of land cover change on flood peak discharges and runoff volumes: model estimates for the Nyando River Basin, Kenya L. Olang & J. Fürst https://doi.org/10.1002/hyp.7821
12. Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins D. Vu et al. https://doi.org/10.5194/hess-27-3485-2023
13. Estimating irrigation water requirements in Europe G. Wriedt et al. https://doi.org/10.1016/j.jhydrol.2009.05.018
14. Empirical Modeling of Stream Nutrients for Countries without Robust Water Quality Monitoring Systems I. Díaz et al. https://doi.org/10.3390/environments8110129
15. Global patterns and key drivers of stream nitrogen concentration: A machine learning approach R. Sheikholeslami & J. Hall https://doi.org/10.1016/j.scitotenv.2023.161623
16. Improving runoff estimates from regional climate models: a performance analysis in Spain D. González-Zeas et al. https://doi.org/10.5194/hess-16-1709-2012
17. Assimilation of future SWOT-based river elevations, surface extent observations and discharge estimations into uncertain global hydrological models S. Wongchuig-Correa et al. https://doi.org/10.1016/j.jhydrol.2020.125473
18. Modelling water and nutrient fluxes in the Danube River Basin with SWAT A. Malagó et al. https://doi.org/10.1016/j.scitotenv.2017.05.242
19. Quantifying groundwater storage dynamics in the Chesapeake Bay watershed (USA) using a large-scale integrated hydrologic model with detailed three-dimensional subsurface representation A. Seck & C. Welty https://doi.org/10.1007/s10040-022-02563-9