13 citations as recorded by crossref.

1. Modelling hydrological responses under climate change using machine learning algorithms – semi-arid river basin of peninsular India G. Sireesha Naidu et al. https://doi.org/10.2166/h2oj.2020.034
2. Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) L. Breuer & J. Huisman https://doi.org/10.1016/j.advwatres.2008.10.010
3. Grid based calibration of SWAT hydrological models D. Gorgan et al. https://doi.org/10.5194/nhess-12-2411-2012
4. A guideline for spatio‐temporal consistency in water quality modelling in rural areas N. Fohrer et al. https://doi.org/10.1002/hyp.14711
5. Coupled water-carbon cycling in karst regions: a review of processes and modeling M. Shao et al. https://doi.org/10.1016/j.jhydrol.2025.134374
6. 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
7. SWAT use of gridded observations for simulating runoff – a Vietnam river basin study M. Vu et al. https://doi.org/10.5194/hess-16-2801-2012
8. Water source characterization through spatiotemporal patterns of major, minor and trace element stream concentrations in a complex, mesoscale German catchment H. Fröhlich et al. https://doi.org/10.1002/hyp.6804
9. Current concepts in nitrogen dynamics for mesoscale catchments L. BREUER et al. https://doi.org/10.1623/hysj.53.5.1059
10. Understanding nitrogen transfer dynamics in a small agricultural catchment: Comparison of a distributed (TNT2) and a semi distributed (SWAT) modeling approaches S. Ferrant et al. https://doi.org/10.1016/j.jhydrol.2011.05.026
11. Exploring impacts of vegetated buffer strips on nitrogen cycling using a spatially explicit hydro-biogeochemical modeling approach S. Klatt et al. https://doi.org/10.1016/j.envsoft.2016.12.002
12. Climate change expected to amplify land-use change impacts on nitrogen export from a subtropical catchment in China S. Jiang et al. https://doi.org/10.1016/j.jhydrol.2025.134888
13. Hydrological Modeling of Tributaries of Cantareira System, Southeast Brazil, with the Swat Model L. Pontes et al. https://doi.org/10.1590/1809-4430-eng.agric.v36n6p1037-1049/2016