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Discussion papers | Copyright
https://doi.org/10.5194/hess-2018-158
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 16 Apr 2018

Research article | 16 Apr 2018

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Hydrology and Earth System Sciences (HESS) and is expected to appear here in due course.

Parameter uncertainty analysis for an operational hydrological model using residual based and limits of acceptability approaches

Aynom T. Tweldebrahn1, John F. Burkhart1,2, and Thomas V. Schuler1 Aynom T. Tweldebrahn et al.
  • 1Department of Geosciences, University of Oslo, Oslo, Norway
  • 2Statkraft, Oslo, Norway

Abstract. Parameter uncertainty estimation is one of the major challenges in hydrological modelling. Here we present parameter uncertainty analysis of a recently released distributed conceptual hydrological model applied in the Nea catchment, Norway. Two variants of the generalized likelihood uncertainty estimation (GLUE) methodologies, one based on the residuals and the other on the limits of acceptability, were employed. Streamflow and remote sensing snow cover data were used in conditioning model parameters and in model validation. When using the GLUE limit of acceptability (GLUE LOA) approach, a streamflow observation error of 25% was assumed. Neither the original limits, nor relaxing the limits up to a physically meaningful value, yielded a behavioural model capable of predicting streamflow within the limits in 100% of the observations. As an alternative to relaxing the limits; the requirement for percentage of model predictions falling within the original limits was relaxed. An empirical approach was introduced to define the degree of relaxation. The result shows that snow and water balance related parameters induce relatively higher streamflow uncertainty than catchment response parameters. Comparable results were obtained from behavioural models selected using the two GLUE methodologies.

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Aynom T. Tweldebrahn et al.
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Aynom T. Tweldebrahn et al.
Aynom T. Tweldebrahn et al.
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