Time-Series Modelling of Avalanche Activity from Meteorological Data

Avalanche-hazard evaluation by field analysts is largely achieved along causal intuitive lines, depending for its success upon the experience of the analyst in his particular area. Several attempts have been made in the past to quantify such procedures by means of statistical models based upon meteorological measurements. Modified forms of a multivariate technique known as linear discriminant analysis have been tried with only partial success. Intercorrelated variables and autocorrelated data, omission of time-lagged terms, insufficient variation in the dependent variable, and sampling difficulties may have combined to weaken the discriminant approach. These problems and the nature of the phenomenon suggest that a stochastic transfer-function time-series approach may be a useful alternative method.A numerical weighting scheme has been devised for the representation of avalanche activity for the Rogers Pass area of British Columbia in terms of terminus, size, and moisture-content codes for each event. From various types of correlation analysis performed on data for the period 1965–73, models were developed using the “best” weighting scheme for avalanche activity representation and the most promising meteorological variables, as indicated by the results of the correlation analysis.These relatively simple models demonstrate a good fit to the actual data, in both a descriptive and a simulated-forecasting situation.