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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Volume 12, issue 7 | Copyright
The Cryosphere, 12, 2175-2210, 2018
https://doi.org/10.5194/tc-12-2175-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 06 Jul 2018

Research article | 06 Jul 2018

Glacio-hydrological melt and run-off modelling: application of a limits of acceptability framework for model comparison and selection

Jonathan D. Mackay1,2, Nicholas E. Barrand1, David M. Hannah1, Stefan Krause1, Christopher R. Jackson2, Jez Everest3, and Guðfinna Aðalgeirsdóttir4 Jonathan D. Mackay et al.
  • 1School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
  • 2British Geological Survey, Environmental Science Centre, Keyworth, Nottingham, NG12 5GG, UK
  • 3British Geological Survey, Lyell Centre, Research Avenue South, Edinburgh, EH14 4AS, UK
  • 4Institute of Earth Sciences, University of Iceland, 101 Reykjavík, Iceland

Abstract. Glacio-hydrological models (GHMs) allow us to develop an understanding of how future climate change will affect river flow regimes in glaciated watersheds. A variety of simplified GHM structures and parameterisations exist, yet the performance of these are rarely quantified at the process level or with metrics beyond global summary statistics. A fuller understanding of the deficiencies in competing model structures and parameterisations and the ability of models to simulate physical processes require performance metrics utilising the full range of uncertainty information within input observations. Here, the glacio-hydrological characteristics of the Virkisá River basin in southern Iceland are characterised using 33 signatures derived from observations of ice melt, snow coverage and river discharge. The uncertainty of each set of observations is harnessed to define the limits of acceptability (LOA), a set of criteria used to objectively evaluate the acceptability of different GHM structures and parameterisations. This framework is used to compare and diagnose deficiencies in three melt and three run-off-routing model structures. Increased model complexity is shown to improve acceptability when evaluated against specific signatures but does not always result in better consistency across all signatures, emphasising the difficulty in appropriate model selection and the need for multi-model prediction approaches to account for model selection uncertainty. Melt and run-off-routing structures demonstrate a hierarchy of influence on river discharge signatures with melt model structure having the most influence on discharge hydrograph seasonality and run-off-routing structure on shorter-timescale discharge events. None of the tested GHM structural configurations returned acceptable simulations across the full population of signatures. The framework outlined here provides a comprehensive and rigorous assessment tool for evaluating the acceptability of different GHM process hypotheses. Future melt and run-off model forecasts should seek to diagnose structural model deficiencies and evaluate diagnostic signatures of system behaviour using a LOA framework.

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We apply a framework to compare and objectively accept or reject competing melt and run-off process models. We found no acceptable models. Furthermore, increasing model complexity does not guarantee better predictions. The results highlight model selection uncertainty and the need for rigorous frameworks to identify deficiencies in competing models. The application of this approach in the future will help to better quantify model prediction uncertainty and develop improved process models.
We apply a framework to compare and objectively accept or reject competing melt and run-off...
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