Abstract
Abstract. Frozen ground can be important to flood production and is often heterogeneous within a watershed due to spatial variations in the available energy, insulation by snowpack and ground cover, and the thermal and moisture properties of the soil. The widely used continuous frozen ground index (CFGI) model is a degree-day approach and identifies frozen ground using a simple frost index, which varies mainly with elevation through an elevation–temperature relationship. Similarly, snow depth and its insulating effect are also estimated based on elevation. The objective of this paper is to develop a model for frozen ground that (1) captures the spatial variations of frozen ground within a watershed, (2) allows the frozen ground model to be incorporated into a variety of watershed models, and (3) allows application in data sparse environments. To do this, we modify the existing CFGI method within the gridded surface subsurface hydrologic analysis watershed model. Among the modifications, the snowpack and frost indices are simulated by replacing air temperature (a surrogate for the available energy) with a radiation-derived temperature that aims to better represent spatial variations in available energy. Ground cover is also included as an additional insulator of the soil. Furthermore, the modified Berggren equation, which accounts for soil thermal conductivity and soil moisture, is used to convert the frost index into frost depth. The modified CFGI model is tested by application at six test sites within the Sleepers River experimental watershed in Vermont. Compared to the CFGI model, the modified CFGI model more accurately captures the variations in frozen ground between the sites, inter-annual variations in frozen ground depths at a given site, and the occurrence of frozen ground.
Highlights
Frozen ground is important to predicting stormflows produced by certain watersheds (Shanley and Chalmers, 1999; McNamara et al, 1997; Prèvost et al, 1990; Woo, 1986)
The objective of this paper is to develop a model for frozen ground that (1) captures the spatial variations of frozen ground within a watershed, (2) allows the frozen ground model to be incorporated into a variety of watershed models, and (3) allows application in data sparse environments where limited forcing data may prohibit use of energy balance methods
No maps of observed snow depth are available for comparison, large-scale distributions of snowpack are known to be controlled by elevation, land cover, and slope/aspect (Fassnacht et al, 2017; Jost et al, 2007), which is more consistent with the radiation-derived temperature index (RTI) model
Summary
Frozen ground ( known as frozen soil or soil frost) is important to predicting stormflows produced by certain watersheds (Shanley and Chalmers, 1999; McNamara et al, 1997; Prèvost et al, 1990; Woo, 1986). Several plot-scale studies have shown that frozen ground can impede infiltration and enhance runoff (Bayard et al, 2005; Dunne and Black, 1971; Stähli et al, 1999). Several of these studies have shown that frozen ground is highly variable temporally and spatially (Campbell et al, 2010; Shanley and Chalmers, 1999; Stähli, 2017), which affects the amount and type of runoff (Wilcox et al, 1997). The presence and depth of frozen ground is affected by soil moisture (Fox, 1992; Willis et al, 1961) and the thermal conductivity of the soil (Farouki, 1981; Johansen, 1977)
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