Modeling of Snowpack Accumulation and Losses in Mountainous Terrain for Both Snowpack Storage Mapping and Watershed Storage Estimates

TitleModeling of Snowpack Accumulation and Losses in Mountainous Terrain for Both Snowpack Storage Mapping and Watershed Storage Estimates
Publication TypeConference Proceedings
Year of Conference2013
AuthorsFroyland, Hugo, Stackhouse Josh, Schiefer Erik, and Decker Rand
Conference Name81st Annual Western Snow Conference
Series TitleProceedings of the Western Snow Conference
Date Published2013
Conference LocationJackson Hole, Wyoming
Keywordsablation, accumulation, modeling, Snow water equivalent, snowpack, SWE, watershed

A heuristic watershed-scale snowpack model that has been under development and verification at the University of Utah and now at Northern Arizona University since 1998 is now implemented on an articulate Geographic Information System (GIS) platform. Simple heuristic rules are established for the preferential accumulation and loss of snowpack in mountainous terrain. These rules include elevation and solar wattage, each at the pixel scale. The capacity for modern GIS to provide solar wattage explicitly from the root Digital Elevation Model (DEM), means that indexing this ablative potential with slope aspect and angle is no longer required. Each model run must be initialized with two snowpack Snow Water Equivalent (SWE) observations at different elevation within the watershed. One observation can be snowline. This means the model can be initialized for a water year start date, or an annual snowpack SWE maximum when it occurs, or forensic queries of historic events/years, and virtual events such as a “unit” storm or winter. Additionally, the efficiency with which a given watershed commutes water from snowpack storage to surface runoff is indexed with two different ratios; length of surface water channel in the watershed to area of the watershed, and length of watershed channel to watershed circumference. The test watersheds of Stackhouse (Rohde et al., 2012) are repeated with this model, and include four highland tributary watersheds in different physiographical provinces of the Rocky Mountains; Doyle Peak, San Francisco Peaks, Arizona; Kings Peak, Uintas, Utah; and Mt. Elbert and Jones Peak, Eastern San Juan Mountains, Colorado. These tributary sub-basins ranged in size from 88 to 210 million square meters. Snowpack accumulation and/or loss is modeled to the DEM pixel scale, in all of these cases, 30m by 30m. Snowpack SWE in storage, per pixel, is then integrated for an estimate of watershed aggregate snowpack SWE storage. As an aid in identifying watersheds that are particularly effective at snowpack SWE storage, this model allows for the comparison of SWE volumes in a given watershed to the area of the watershed; a measure of the watershed’s snow water volume to area efficiency. Another valuable data product of the model is a detailed mapping of snowpack SWE storage within the watershed at the pixel scale. This information can be used in a variety of ways. As examples of the decision support capabilities of the model, three water resource decision space challenges are investigated in an effort to demonstrate the utility of the model and include the following:

  • Watershed target identification and ground based cloud-seeding generator siting for snowpack augmentation, including estimates of snowpack storage volume increases to be realized.
  • Forest reclamation (thinning) target areas, at fine scales within a given watershed, that have the highest potential to increase net ground snow accumulation.
  • Point locations within a watershed where the accumulation of snowpack storage properties at the pixel scale are indicative of the watershed averages. i.e. for the purpose of establishing ground-based observation stations to extrapolate the basin’s aggregate snowpack SWE from one or only a few observation sites.