Physically based modelling of alpine snow hydrology in the Canadian Rockies (Invited)
Abstract
Field, remote sensing and modelling studies at Marmot Creek Research Basin in the Canadian Rocky Mountain have been directed to advance the understanding of snow processes and to improve hydrological models of snow and streamflow. Physically based approaches are used due to the ungauged nature of most basins in the region. Physically based models can take advantage of remote sensing information for parameter selection, reducing the need for calibration of parameters from streamflow observations. Modelling studies of blowing snow over alpine terrain show that the spatial distributions of snow water equivalent in complex environments can be predicted with reasonable accuracy. An important new feature is the application of the model to aggregated landscape units (Hydrological Response Units or HRU) having common physiographic and aerodynamic characteristics; these landscape units require much less physiographic information than do fully spatially distributed blowing snow models and are suitable to application in remote alpine regions with sparse data. Alpine HRU can be easily distinguished using remote sensing information such as LiDAR estimated snow depths, or snow covered area during melt from visible spectrum high resolution imagery. Snow ablation studies have focussed on application of the energy balance to estimate snowmelt over landscape units with consideration of sub-unit depletion of snow covered area. In this case, HRU are segregated based on both snow accumulation characteristics and applied melt energy fluxes. Some indication of the spatial variability of snow accumulation is needed to estimate snow ablation and snow covered area depletion. Again, LiDAR estimated snow depths can be used to estimate the variability of snow accumulation and this parameter can then be used in calculating the shape of snowcovered area depletion curves. The calculated melt rates agree well with observations from snow surveys. Improved algorithms resulting from this application of field technology have been used to update a modular, object-oriented computer simulation of the cold regions hydrological cycle, the Cold Regions Hydrological Model, CRHM. CRHM can be easily and frequently updated as improved algorithms become available and used to predict both snow dynamics and streamflow from high mountain areas.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2010
- Bibcode:
- 2010AGUFM.C12A..06P
- Keywords:
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- 0736 CRYOSPHERE / Snow;
- 1855 HYDROLOGY / Remote sensing;
- 1863 HYDROLOGY / Snow and ice;
- 1894 HYDROLOGY / Instruments and techniques: modeling