Abstract
Applications of snowmelt models in Canada's north have been limited largely to energy balance models concentrating on micro scale studies or macroscale applications. The latter rely solely on basin-wide, optimized parameters for hydrological simulation and often neglect some of the major physical processes controlling melt production. Although physically realistic models can be implemented at the micrometeorological scale, the data requirements are often too numerous to make these types of models practical to apply at the meso- or macroscales. On the other hand, the standard lumped model approach often oversimplifies the physical processes and fails to reveal subtle differences between land cover types and their specific response to meteorological inputs. This paper focuses on the use of indexed snowmelt algorithms derived for individual land cover component characteristics of the wetland dominated region of the lower Liard River Valley. NWT, Canada. These algorithms use an hourly temperature index and a combination radiation-temperature index approach to estimate snowmelt within the different land cover types. The algorithms developed are incorporated into a fully distributed hydrological model (SPL7) that uses the grouped response unit (GRU) method for basin discretization. Snowmelt indices are estimated for both approaches using snow cover depletion data obtained during an extensive field campaign. The indices are then validated using historical data from complementary studies. Results show that the radiation-temperature algorithm provided slightly improved calibration results: however, both algorithms validated equally well.
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