Difference between revisions of "Continuous:Snowfall Accumulation and Melting"

Revision as of 14:10, 28 November 2012

When GSSHA is run in the LONG_TERM simulation mode, snowfall accumulation and melting is simulated to increase its utility in regions with significant snowfall. More accurate snow accumulation and melt algorithms as well as more accurate melt transport algorithms within GSSHA are active research and model development areas at ERDC. Snowfall has a large impact on hydrologic fluxes because snowfall is normally stored for a significant period of time in the snowpack and is later released as melt water. In many parts of the world melt of the snow cover is the single most important event of the water year (Gray and Prowse, 1993). Because snowfall accumulation and subsequent melting can have such a large influence in hydrologic response of a watershed, it is important to simulate these processes. The purpose of the snowfall accumulation and melting routine is to allow an accounting of these processes with the intent to differentiate between precipitation that is rainfall that will immediately infiltrate, pond and runoff or evaporate, and snow and ice that accumulates and significantly alters the timing of hydrologic fluxes.

All three methods used within GSSHA to simulate snow accumulation and melt assume that the snow pack consists of a single layer. Certain advantages - such as time variations of liquid water content (Bloschl & Kirnbauer 1991), interflow within the snow pack layers due to ice sheets, and avalanche modeling (Colbeck 1991) - do exist when applying multi-layer snow models, but the required data to accomplish such models on a watershed level is currently unrealistic in most basins. Multi-layer snow models are typically deployed at the site-scale where spatially-close data is available.

In nature snow is a distributed process. Because of the distributed structure of the GSSHA model the snow is modeled as a distributed process. Utilizing a distributed domain gives more potential of addressing a variety of real world problems than a semi-distributed or lumped-parameter model (kirnbauer, Bloeschl et al. 1994). Because of the distributed domain, the model can also account for Orographic Effects.

GSSHA Melt Algorithms
GSSHA currently employs three snow melt models:

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