15 Nov 2017
Research article | 15 Nov 2017
Identifying the connective strength between model parameters and performance criteria
Björn Guse et al.
Total article views: 2,372 (including HTML, PDF, and XML)Cumulative views and downloads (calculated since 01 Feb 2017)Views and downloads (calculated since 01 Feb 2017)
Viewed (geographical distribution)
Total article views: 2,348 (including HTML, PDF, and XML) Thereof 2,331 with geography defined and 17 with unknown origin.
Total article views: 1,491 (including HTML, PDF, and XML) Thereof 1,480 with geography defined and 11 with unknown origin.
Total article views: 857 (including HTML, PDF, and XML) Thereof 851 with geography defined and 6 with unknown origin.
18 citations as recorded by crossref.
- Variable Infiltration-Capacity Model Sensitivity, Parameter Uncertainty, and Data Augmentation for the Diyala River Basin in Iraq S. Waheed et al. 10.1061/(ASCE)HE.1943-5584.0001975
- Assessing the impact of a multimetric calibration procedure on modelling performance in a headwater catchment in Mau Forest, Kenya A. Kamamia et al. 10.1016/j.ejrh.2018.12.005
- Analysis of the Relative Importance of Model Parameters in Watersheds with Different Hydrological Regimes Y. Medina & E. Muñoz 10.3390/w12092376
- Assessing parameter identifiability for multiple performance criteria to constrain model parameters B. Guse et al. 10.1080/02626667.2020.1734204
- Responses of hydrological model equifinality, uncertainty, and performance to multi-objective parameter calibration Y. Her & C. Seong 10.2166/hydro.2018.108
- Modeling the impact of agricultural crops on the spatial and seasonal variability of water balance components in the Lake Tana basin, Ethiopia T. Tigabu et al. 10.2166/nh.2019.170
- Hydrological evaluation of global gridded precipitation datasets in a heterogeneous and data-scarce basin in Iran M. Khoshchehreh et al. 10.1007/s12040-020-01462-5
- Do model parameters change under changing climate and land use in the upstream of the Lancang River Basin, China? D. Ma et al. 10.1080/02626667.2020.1782915
- Improving Information Extraction From Simulated Discharge Using Sensitivity‐Weighted Performance Criteria B. Guse et al. 10.1029/2019WR025605
- Using numerical modeling error analysis methods to indicate changes in a watershed K. Mátyás & K. Bene 10.1556/606.2018.13.3.17
- Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin J. Towner et al. 10.5194/hess-23-3057-2019
- Flood hydrograph prediction in a semiarid mountain catchment: The role of catchment subdivision H. Rezaei‐Sadr 10.1111/jfr3.12568
- How to Tailor My Process‐Based Hydrological Model? Dynamic Identifiability Analysis of Flexible Model Structures T. Pilz et al. 10.1029/2020WR028042
- A review of alternative climate products for SWAT modelling: Sources, assessment and future directions M. Tan et al. 10.1016/j.scitotenv.2021.148915
- When is a hydrological model sufficiently calibrated to depict flow preferences of riverine species? J. Kiesel et al. 10.1002/eco.2193
- A review of hydrologic signatures and their applications H. McMillan 10.1002/wat2.1499
- Incorporating vegetation dynamics noticeably improved performance of hydrological model under vegetation greening P. Bai et al. 10.1016/j.scitotenv.2018.06.233
- Distinguishing the Relative Contribution of Environmental Factors to Runoff Change in the Headwaters of the Yangtze River M. Guo et al. 10.3390/w11071432
Latest update: 08 Aug 2022