42 citations as recorded by crossref.

1. A comprehensive calibration and validation of SWAT-T using local datasets, evapotranspiration and streamflow in a tropical montane cloud forest area with permeable substrate in central Veracruz, Mexico S. López-Ramírez et al. 10.1016/j.jhydrol.2021.126781
2. Analysing spatio-temporal process and parameter dynamics in models to characterise contrasting catchments B. Guse et al. 10.1016/j.jhydrol.2018.12.050
3. Omnipresent distribution of herbicides and their transformation products in all water body types of an agricultural landscape in the North German Lowland U. Ulrich et al. 10.1007/s11356-021-13626-x
4. An enhanced SWAT wetland module to quantify hydraulic interactions between riparian depressional wetlands, rivers and aquifers M. Rahman et al. 10.1016/j.envsoft.2016.07.003
5. Ten strategies towards successful calibration of environmental models J. Mai 10.1016/j.jhydrol.2023.129414
6. Identifying the connective strength between model parameters and performance criteria B. Guse et al. 10.5194/hess-21-5663-2017
7. Assessing parameter identifiability for multiple performance criteria to constrain model parameters B. Guse et al. 10.1080/02626667.2020.1734204
8. A joined multi-metric calibration of river discharge and nitrate loads with different performance measures M. Haas et al. 10.1016/j.jhydrol.2016.03.001
9. Climate change impacts model parameter sensitivity – implications for calibration strategy and model diagnostic evaluation L. Melsen & B. Guse 10.5194/hess-25-1307-2021
10. Technical Report—Methods: A Diagnostic Approach to Analyze the Direction of Change in Model Outputs Based on Global Variations in the Model Inputs A. Wang et al. 10.1029/2020WR027153
11. Evaluation of parameter sensitivity of a rainfall-runoff model over a global catchment set L. Santos et al. 10.1080/02626667.2022.2035388
12. Reactive ditches: A simple approach to implement denitrifying wood chip bioreactors to reduce nitrate exports into aquatic ecosystems? M. Pfannerstill et al. 10.1007/s12665-016-5856-2
13. Inter-comparison of experimental catchment data and hydrological modelling S. Singh et al. 10.1016/j.jhydrol.2017.04.049
14. Quantifying Spatial Changes in the Structure of Water Quality Constituents in a Large Prairie River within Two Frameworks of a Water Quality Model N. Hosseini et al. 10.3390/w8040158
15. Temporal Scale‐Dependent Sensitivity Analysis for Hydrological Model Parameters Using the Discrete Wavelet Transform and Active Subspaces D. Bittner et al. 10.1029/2020WR028511
16. Hydrological tracers, the herbicide metazachlor and its transformation products in a retention pond during transient flow conditions U. Ulrich et al. 10.1007/s11356-019-05815-6
17. Parameter Estimation and Uncertainty Analysis: A Comparison between Continuous and Event-Based Modeling of Streamflow Based on the Hydrological Simulation Program–Fortran (HSPF) Model H. Xie et al. 10.3390/w11010171
18. Regional analysis of parameter sensitivity for simulation of streamflow and hydrological fingerprints S. Höllering et al. 10.5194/hess-22-203-2018
19. Improving hydrological model optimization for riverine species J. Kiesel et al. 10.1016/j.ecolind.2017.04.032
20. Confluence simulations based on dynamic channel parameters in the grasslands lacking historical measurements M. Li et al. 10.1016/j.jhydrol.2023.130425
21. Combining global sensitivity analysis and multiobjective optimisation to estimate soil hydraulic properties and representations of various sole and mixed crops for the agro-hydrological SWAP model P. Stahn et al. 10.1007/s12665-017-6701-y
22. Simultaneously determining global sensitivities of model parameters and model structure J. Mai et al. 10.5194/hess-24-5835-2020
23. Variability in flow and tracer-based performance metric sensitivities reveal regional differences in dominant hydrological processes across the Athabasca River basin T. Holmes et al. 10.1016/j.ejrh.2022.101088
24. How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components M. Pfannerstill et al. 10.1111/1752-1688.12524
25. Projected changes in climate and hydrological regimes of the Western Siberian lowlands R. Sada et al. 10.1007/s12665-019-8047-0
26. Verification of PCSWMM's LID processes and their scalability over time and space Z. Zhang & C. Valeo 10.3389/frwa.2022.1058883
27. Advancing isotope‐enabled hydrological modelling for ungauged calibration of data‐scarce humid tropical catchments A. Watson et al. 10.1002/hyp.15065
28. Towards simplification of hydrologic modeling: identification of dominant processes S. Markstrom et al. 10.5194/hess-20-4655-2016
29. Revealing the positive influence of young water fractions derived from stable isotopes on the robustness of karst water resources predictions K. Çallı et al. 10.1016/j.jhydrol.2023.129549
30. PondR: a process-oriented model to simulate the hydrology of drainage ponds S. Willkommen et al. 10.2166/hydro.2017.038
31. The 3DNet-Catch hydrologic model: Development and evaluation A. Todorović et al. 10.1016/j.jhydrol.2018.10.040
32. Identifying Dominant Processes in Time and Space: Time‐Varying Spatial Sensitivity Analysis for a Grid‐Based Nitrate Model S. Wu et al. 10.1029/2021WR031149
33. Assessing the impacts of Best Management Practices on nitrate pollution in an agricultural dominated lowland catchment considering environmental protection versus economic development M. Haas et al. 10.1016/j.jenvman.2017.02.060
34. What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling T. Wagener & F. Pianosi 10.1016/j.earscirev.2019.04.006
35. On characterizing the temporal dominance patterns of model parameters and processes B. Guse et al. 10.1002/hyp.10764
36. How weather conditions and physico-chemical properties control the leaching of flufenacet, diflufenican, and pendimethalin in a tile-drained landscape S. Willkommen et al. 10.1016/j.agee.2019.03.017
37. Demasking the integrated information of discharge: Advancing sensitivity analysis to consider different hydrological components and their rates of change B. Guse et al. 10.1002/2016WR018894
38. Assessment of deterministic PMF modelling approaches G. Felder & R. Weingartner 10.1080/02626667.2017.1319065
39. Increasing parameter identifiability through clustered time-varying sensitivity analysis L. Wang et al. 10.1016/j.envsoft.2024.106189
40. Dynamics of hydrological-model parameters: mechanisms, problems and solutions T. Lan et al. 10.5194/hess-24-1347-2020
41. Simulation of Daily Flow Pathways, Tile‐Drain Nitrate Concentrations, and Soil‐Nitrogen Dynamics Using SWAT C. Ikenberry et al. 10.1111/1752-1688.12569
42. Quantifying dynamic sensitivity of optimization algorithm parameters to improve hydrological model calibration W. Qi et al. 10.1016/j.jhydrol.2015.11.052