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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 21, issue 12
Hydrol. Earth Syst. Sci., 21, 6345–6362, 2017
https://doi.org/10.5194/hess-21-6345-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 6345–6362, 2017
https://doi.org/10.5194/hess-21-6345-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 14 Dec 2017

Research article | 14 Dec 2017

Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

José-Luis Guerrero1,2, Patricia Pernica1, Howard Wheater1, Murray Mackay3, and Chris Spence4 José-Luis Guerrero et al.
  • 1Global Institute for Water Security, National Hydrology Research Centre, 11 Innovation Boulevard, Saskatoon, SK, Canada
  • 2Norwegian Institute for Water Research, Gaustadalléen 21, 0349 Oslo, Norway
  • 3Science and Technology Branch, Environment and Climate Change Canada, 4905 Dufferin Str., Toronto, ON, M3H5T4, Canada
  • 4Science and Technology Branch, Environment and Climate Change Canada, 11 Innovation Boulevard, Saskatoon, SK, Canada

Abstract. Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere – heat-exchange fluxes – is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue – different parameter-value combinations yielding equivalent results – the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.

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Short summary
Lakes are sentinels of climate change, and an adequate characterization of their feedbacks to the atmosphere could improve climate modeling. These feedbacks, as heat fluxes, can be simulated but are seldom measured, casting doubt on modeling results. Measurements from a small lake in Canada established that the model parameter modulating how much light penetrates the lake dominates model response. This parameter is measurable: improved monitoring could lead to more robust modeling.
Lakes are sentinels of climate change, and an adequate characterization of their feedbacks to...
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