Can assimilating snow monitoring information offset the adverse effects of precipitation data scarcity in hydrological modelling applications? - Abbasnezhadi, Kian; Rousseau, Alain N. (2020)
The applicability of the Canadian Precipitation Analysis products known as the Regional Deterministic Precipitation Analysis (CaPA-RDPA) for hydrological modelling in boreal watersheds in Canada, which are constrained with shortage of precipitation information, has been the subject of a number of recent studies. The northern and mid-cordilleran alpine, sub-alpine, and boreal watersheds in Yukon, Canada, are prime examples of such Nordic regions where any hydrological modelling application is greatly scrambled due to lack of accurate precipitation information. In the course of the past few years, proper advancements were tailored to resolve these challenges and a forecasting system was designed at the operational level for short- to medium-range flow and inflow forecasting in major watersheds of interest to Yukon Energy. This forecasting system merges the precipitation products from the North American Ensemble forecasting System (NAEFS) and recorded flows or reconstructed reservoir inflows into the HYDROTEL distributed hydrological model, using the Ensemble Kalman Filtering (EnKF) data assimilation technique. In order to alleviate the adverse effects of scarce precipitation information, the forecasting system also enjoys a snow data assimilation routine in which simulated snowpack water content is updated through a distributed snow correction scheme. Together, both data assimilation schemes offer the system with a framework to accurately estimate flow magnitudes. This robust system not only mitigates the adverse effects of meteorological data constrains in Yukon, but also offers an opportunity to investigate the hydrological footprint of CaPA-RDPA products in Yukon, which is exactly the motivation behind this presentation. However, our overall goal is much more comprehensive as we are trying to elucidate whether assimilating snow monitoring information in a distributed hydrological model could meet the flow estimation accuracy in sparsely gauged basins to the same extent that would be achieved through either (i) the application of precipitation analysis products, or (ii) expanding the meteorological network. A proper answer to this question would provide us with valuable information with respect to the robustness of the snow data assimilation routine in HYDROTEL and the intrinsic added-value of using CaPA-RDPA products in sparsely gauged basins of Yukon.
Keywords: Rousseau_Alain

What is the Trade-Off between Snowpack Stratification and Simulated Snow Water Equivalent in a Physically-Based Snow Model? - Augas, Julien; Abbasnezhadi, Kian; Rousseau, Alain N.; Baraer, Michel (Water, 2020)
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.
Keywords: Baraer_Michel; Rousseau_Alain

Synchronized generation of high-resolution gridded precipitation and temperature fields - Abbasnezhadi, Kian; Rousseau, Alain N.; Wruth, Andrea M.; Zahmatkesh, Zahra (Journal of Hydrology, 2019)
Keywords: Rousseau_Alain