Articles | Volume 21, issue 7
Hydrol. Earth Syst. Sci., 21, 3325–3352, 2017
https://doi.org/10.5194/hess-21-3325-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 3325–3352, 2017
https://doi.org/10.5194/hess-21-3325-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
05 Jul 2017
Research article
| 05 Jul 2017
Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding
Christa Kelleher et al.
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- Data-driven modelling and spatial complexity supports heterogeneity-based integrative management for eliminating Simulium neavei-transmitted river blindness E. Michael et al. 10.1038/s41598-020-61194-w
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- A Regularization Approach to Improve the Sequential Calibration of a Semidistributed Hydrological Model A. Lavenne et al. 10.1029/2018WR024266
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- Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in situ data for calibrating a global hydrological model S. Hosseini-Moghari et al. 10.5194/hess-24-1939-2020
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Latest update: 04 Feb 2023
Short summary
Models are tools for understanding how watersheds function and may respond to land cover and climate change. Before we can use models towards these purposes, we need to ensure that a model adequately represents watershed-wide observations. In this paper, we propose a new way to evaluate whether model simulations match observations, using a variety of information sources. We show how this information can reduce uncertainty in inputs to models, reducing uncertainty in hydrologic predictions.
Models are tools for understanding how watersheds function and may respond to land cover and...
