Articles | Volume 20, issue 10
https://doi.org/10.5194/hess-20-4391-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-4391-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Oct 2016
Research article |
| 28 Oct 2016
A pre-calibration approach to select optimum inputs for hydrological models in data-scarce regions
Centre for Engineering Sustainability, School of Engineering, University of Liverpool, Liverpool, L69 3GH, UK
Jonathan Bridge
Centre for Engineering Sustainability, School of Engineering, University of Liverpool, Liverpool, L69 3GH, UK
Neil Macdonald
School of Environmental Sciences, University of Liverpool, Liverpool, L69 7ZT, UK
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- Surface Runoff and Drought Assessment Using Global Water Resources Datasets - from Oum Er Rbia Basin to the Moroccan Country Scale S. Strohmeier et al. 10.1007/s11269-019-02251-6
- Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions T. Mihret et al. 10.1016/j.ejrh.2024.102163
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- Integrating Satellite Rainfall Estimates with Hydrological Water Balance Model: Rainfall-Runoff Modeling in Awash River Basin, Ethiopia G. Adane et al. 10.3390/w13060800
- The Effects of Model Complexity on Model Output Uncertainty in Co‐Evolved Coupled Natural‐Human Systems C. Lin & Y. Yang 10.1029/2021EF002403
- Streamflow prediction based on the soil and water assessment tool in the Pajeú river basin, Brazilian semiarid T. Silva et al. 10.1016/j.jsames.2025.105420
- Assessing the performance of a physically based hydrological model using a proxy‐catchment approach in an agricultural environment V. Escobar‐Ruiz et al. 10.1002/hyp.13550
- Different calibration procedures for flows estimation using SWAT model L. Moreira et al. 10.1080/23249676.2020.1787246
- Impact of local versus global datasets on hydrological responses in Mahanadi River basin in India S. Naha et al. 10.1080/02626667.2023.2193700
- Neglecting Model Parametric Uncertainty Can Drastically Underestimate Flood Risks S. Sharma et al. 10.1029/2022EF003050
- Impact of Climate Change on Water Balance Components and Droughts in the Guajoyo River Basin (El Salvador) P. Blanco-Gómez et al. 10.3390/w11112360
- Investigating the impact of irrigation practices on hydrologic fluxes in a highly managed river basin M. Almahawis et al. 10.1016/j.agwat.2024.108954
1 citations as recorded by crossref.
Latest update: 18 May 2025
Short summary
The study presents a rapid, robust and reproducible approach to select optimum inputs for hydrological models. We show significant variation in pre-calibrated model performance due to the choice of different combinations of land-use, soil and weather datasets, particularly in data-scarce regions most in need of computationally-efficient approaches to optimise reliability of models and support decision-making. Our case study is directly relevant to planners and decision-makers in Wala, Jordan.
The study presents a rapid, robust and reproducible approach to select optimum inputs for...
