Snow Accumulation and Ablation Model - Snow-17

This model is the GoldSim implementation of the SNOW-17 conceptual model, originally developed by the National Weather Service River Forecast System (NWSRFS). The model is thoroughly documented in a paper by Eric Anderson, which is included in this model. It is highly recommended to read this document before using the model (Anderson, 2006).

The SNOW-17 model uses average daily temperature as the primary index to determine energy exchange within the snow-air interface of the watershed being modeled. The only other required input is precipitation, although several coefficients are used for calibration (see the Input_Parameters Container). Once properly calibrated, the model can be used to forecast snowmelt effectively.

Key processes simulated by this model include:

• Precipitation Division: Determines whether precipitation falls as rain or snow based on temperature thresholds.
• Snow Accumulation: Adjusts new snowfall amounts and computes the density and depth of the snowpack.
• Energy Exchange: Calculates net radiation, latent and sensible heat transfer, and heat from precipitation at the snow-air interface.
• Heat Deficit: Tracks the heat deficit within the snowpack, which affects the ripeness and melt potential of the snow.
• Ground Melt: Accounts for melt at the snow-soil interface based on a constant daily melt rate.
• Outflow Calculation: Computes the outflow from the snowpack into the catchment area, considering the snowpack's ripeness and liquid water content.

Please note that this model does not calculate the attenuation and routing of water flows from the area. It is designed to operate with daily time steps.

Running a Sensitivity Analysis using GoldSim on this model can reveal the impact of input parameters on the peak snow water equivalent (SWE). The tornado chart below illustrates the sensitivity analysis, providing a graphical representation of how sensitive the results are to the specified independent variables. This is particularly useful for calibration, as it helps identify the parameters that most significantly affect the results.

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