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Article

What is the Trade-Off between Snowpack Stratification and Simulated Snow Water Equivalent in a Physically-Based Snow Model?

1
Institut National de la Recherche Scientifique, Centre Eau Terre Environnement (INRS-ETE), 490, Rue de la Couronne, Québec, QC G1K 9A9, Canada
2
Climate Research Division, Science and Technology Branch, Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, ON M3H 5T4, Canada
3
Hydrology, Climate and Climate Change Laboratory, École de Technologie Supérieure, University of Quebec, 1100 Notre-Dame Street West, Montréal, QC H3C 1K3, Canada
*
Author to whom correspondence should be addressed.
Water 2020, 12(12), 3449; https://doi.org/10.3390/w12123449
Received: 12 October 2020 / Revised: 3 December 2020 / Accepted: 3 December 2020 / Published: 8 December 2020
(This article belongs to the Special Issue Whither Cold Regions Hydrology under Changing Climate Conditions)
In Nordic watersheds, estimation of the dynamics of snow water equivalent (SWE) represents a major step toward a satisfactory modeling of the annual hydrograph. For a multilayer, physically-based snow model like MASiN (Modèle Autonome de Simulation de la Neige), the number of modeled snow layers can affect the accuracy of the simulated SWE. The objective of this study was to identify the maximum number of snow layers (MNSL) that would define the trade-off between snowpack stratification and SWE modeling accuracy. Results indicated that decreasing the MNSL reduced the SWE modeling accuracy since the thermal energy balance and the mass balance were less accurately resolved by the model. Nevertheless, from a performance standpoint, SWE modeling can be accurate enough with a MNSL of two (2), with a substantial performance drop for a MNSL value of around nine (9). Additionally, the linear correlation between the values of the calibrated parameters and the MNSL indicated that reducing the latter in MASiN increased the fresh snow density and the settlement coefficient, while the maximum radiation coefficient decreased. In this case, MASiN favored the melting process, and thus the homogenization of snow layers occurred from the top layers of the snowpack in the modeling algorithm. View Full-Text
Keywords: snow modeling; multilayer snow model; MASiN snow modeling; multilayer snow model; MASiN
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MDPI and ACS Style

Augas, J.; Abbasnezhadi, K.; Rousseau, A.N.; Baraer, M. What is the Trade-Off between Snowpack Stratification and Simulated Snow Water Equivalent in a Physically-Based Snow Model? Water 2020, 12, 3449. https://doi.org/10.3390/w12123449

AMA Style

Augas J, Abbasnezhadi K, Rousseau AN, Baraer M. What is the Trade-Off between Snowpack Stratification and Simulated Snow Water Equivalent in a Physically-Based Snow Model? Water. 2020; 12(12):3449. https://doi.org/10.3390/w12123449

Chicago/Turabian Style

Augas, Julien; Abbasnezhadi, Kian; Rousseau, Alain N.; Baraer, Michel. 2020. "What is the Trade-Off between Snowpack Stratification and Simulated Snow Water Equivalent in a Physically-Based Snow Model?" Water 12, no. 12: 3449. https://doi.org/10.3390/w12123449

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