Glacio-hydrological melt and run-off modelling: application of a limits of acceptability framework for model comparison and selection
2018
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 Virkisa 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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