Abstract
A majority of the annual precipitation in many mountains falls as snow, and obtaining accurate estimates of the amount of water stored within the snowpack is important for water supply forecasting. Mountain topography can produce complex patterns of snow distribution, accumulation, and ablation, yet the interaction of topography and meteorological patterns tends to generate similar inter-annual snow depth distribution patterns. Here, we question whether snow depth patterns at or near peak accumulation are repeatable for a 10-year time frame and whether years with limited snow depth measurement can still be used to accurately represent snow depth and mean snow depth. We used snow depth measurements from the West Glacier Lake watershed, Wyoming, USA, to investigate the distribution of snow depth. West Glacier Lake is a small (0.61 km2) windswept (mean of 8 m/s) watershed that ranges between 3277 m and 3493 m. Three interpolation methods were compared: (1) a binary regression tree, (2) multiple linear regression, and (3) generalized additive models. Generalized additive models using topographic parameters with measured snow depth presented the best estimates of the snow depth distribution and the basin mean amounts. The snow depth patterns near peak accumulation were found to be consistent inter-annually with an average annual correlation coefficient (r2) of 0.83, and scalable based on a winter season accumulation index (r2 = 0.75) based on the correlation between mean snow depth measurements to Brooklyn Lake snow telemetry (SNOTEL) snow depth data.
Highlights
IntroductionIt is important to understand the quantity and distribution of snow for purposes of streamflow forecasting [1]
In snow dominated areas, it is important to understand the quantity and distribution of snow for purposes of streamflow forecasting [1]
Snow accumulation and distribution patterns are often consistent over time [3,10,15,16,20,36,37,38]. This leads to the question: are spatial patterns sufficiently consistent across years with abundant measurements so that we can confidently use sparse measurements in other years to extrapolate the snowpack patterns? Here, we evaluate whether snow depth distribution patterns are consistent over a 10-year period within a sub-alpine basin, West Glacier Lake, in Wyoming, U.S.A., and whether spatial patterns are sufficiently consistent across years with abundant measurements so that we may confidently use sparse measurements in other years to extrapolate the snowpack patterns and estimate basin mean snow depth
Summary
It is important to understand the quantity and distribution of snow for purposes of streamflow forecasting [1]. The resultant distribution of snow often has a similar pattern from year to year [16,20] based on topography, canopy, if present, and wind characteristics, i.e., speed and direction [14,15]. These distribution patterns and the associated topography (and canopy) dictate further distribution and ablation processes [19] that dictate peak streamflows out of the basin [21], baseflow characteristics [22], and groundwater recharge [23]
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