The seasonal evolution of the ground thermal regime in cold regions influences hydrologic flow paths, soil biogeochemistry, and hillslope geomorphology. In mountain environments, steep topography produces strong gradients in solar insolation, vegetation, and snowpack dynamics that lead to large differences in soil temperature over short distances, suggesting a need for high‐resolution, process‐based models that quantify the influence of topography. We present soil temperature and snow depth results from a coupled thermo‐hydrologic model compared to field observations from Gordon Gulch, a seasonally snow‐covered montane catchment in the Colorado Front Range in the Boulder Creek Critical Zone Observatory. The field site features two instrumented hillslopes with opposing aspects: Despite the persistent snowpack on the north‐facing slope, seasonally frozen ground is more prevalent there than the south‐facing slope, which experiences significantly higher incoming radiation that prevents the persistence of frozen ground. A novel modeling framework is developed by coupling a surface energy balance model incorporating solar radiation and snowpack processes to an existing subsurface model (PFLOTRAN‐ICE). The coupled model is used to reproduce strong aspect‐controlled differences in soil temperature and snow depth evident from observations during water years 2013–2016, including a higher incidence of frozen ground under the north‐facing slope. Representation of the snowpack and its insulating effects significantly improves soil temperature estimates on the north‐facing slope, particularly the duration of soil freezing in the spring, which is underestimated by 1–2 months without including the snowpack.
Snow disappearance date (SDD) affects the ecohydrological dynamics of montane forests, by altering water availability, forest fire regime, and the land surface energy budget. The forest canopy modulates SDD through competing processes; dense canopy intercepts snowfall and enhances longwave radiation while shading snowpack from shortwave radiation and sheltering it from the wind. Limited ground‐based observations of snow presence and absence have restricted our ability to unravel the dominant processes affecting SDD in montane forests. We apply a lidar‐derived method to estimate fractional snow cover area (fSCA) at two relatively warm sites in the Sierra Nevada and two colder sites in the Rocky Mountains, which we link to SDD. With the exception of late season snowpack and low fSCA, snow retention is longer under low vegetation density than under high vegetation density in both warm and cold sites. Warm forests consistently have longer snow retention in open areas compared to dense under canopy areas, particularly on south‐facing slopes. Cold forests tend to have longer snow retention under lower density canopy compared to open areas, particularly on north‐facing slopes. We use this empirical analysis to make process inferences and develop an initial framework to predict SDD that incorporates the role of topography and vegetation structure. Building on our framework will be necessary to provide better forest management recommendations for snowpack retention across complex terrain and heterogenous canopy structure.
more » « less- Award ID(s):
- 2012310
- NSF-PAR ID:
- 10371021
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 57
- Issue:
- 12
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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