Temporal changes in the spatial patterns of weak layer shear strength and stability on uniform slopes
Logan, Spencer Carl
MetadataShow full item record
Avalanche forecasting involves the prediction of spatial and temporal variability of the stability of the snowpack. Greater spatial variability increases the uncertainty of forecasts and reduces the ability of a forecaster to extrapolate snowpack stability reliably. A greater understanding of the spatial patterns of stability, and how they change through time, could improve avalanche forecasting. I examined temporal changes in shear strength and stability of three persistent weak layers at three different sites. Sites were located on uniform slopes to minimize factors that introduce variability or large-scale trends in the snowpack. At each site, shear strength and stability of the same persistent layer were measured in adjacent plots, sampled at intervals of one to eight days apart. Experimental variograms and pit-to-plot ratios provided measures of the spatial variability. Because adjacent plots began with similar conditions, differences between the plots were attributed to temporal change. Shear strength of two buried surface hoar layers increased through time and became more variable. As the layers aged, the rate of strengthening decreased. Stability indices initially increased, then decreased as snowfall increased the slab stress. Changes in the spatial structure were most apparent when the layers were younger and gaining strength most rapidly. As the layers aged, the spatial measures provided less information. Strength of depth hoar increased initially, then decreased as the depth hoar grew and bonds weakened. Spatial correlation increased over time between the first three plots. A strong wind event and warm weather led to considerable change to the snowpack between the third and fourth samples, complicating comparisons. On these three weak layers, shear strength could be reliably extrapolated over a distance of at least 17 m on 86% of the days sampled, provided a sufficient number of tests were conducted to characterize the statistical distribution. The optimal spacing of tests changes as the autocorrelation length of shear strength changes. The number of tests required increases as the overall variability of shear strength increases. This suggests that test spacing is less important on older layers because the autocorrelation length is short, but more tests are required to characterize the slope statistically.