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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- Comparison of hydrological models for the assessment of water resources in a data-scarce region, the Upper Blue Nile River Basin G. Tegegne et al. 10.1016/j.ejrh.2017.10.002
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- Modeling arid/semi-arid irrigated agricultural watersheds with SWAT: Applications, challenges, and solution strategies M. Samimi et al. 10.1016/j.jhydrol.2020.125418
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- The Effects of Model Complexity on Model Output Uncertainty in Co‐Evolved Coupled Natural‐Human Systems C. Lin & Y. Yang 10.1029/2021EF002403
- 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
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- 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
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- Event-based nonpoint source pollution prediction in a scarce data catchment L. Chen et al. 10.1016/j.jhydrol.2017.06.034
13 citations as recorded by crossref.
- 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
- Comparison of hydrological models for the assessment of water resources in a data-scarce region, the Upper Blue Nile River Basin G. Tegegne et al. 10.1016/j.ejrh.2017.10.002
- Designing river water quality policy interventions with scarce data: the case of the Middle Tagus Basin, Spain A. Bolinches et al. 10.1080/02626667.2019.1708915
- Revisiting the application of the SWAT model in arid and semi-arid regions: a selection from 2009 to 2022 A. Rocha et al. 10.1007/s00704-023-04546-6
- Modeling arid/semi-arid irrigated agricultural watersheds with SWAT: Applications, challenges, and solution strategies M. Samimi et al. 10.1016/j.jhydrol.2020.125418
- 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
- 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: 20 Nov 2024
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...
