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Statistical estimation and prediction of avalanche activity from meteorological data for the Rogers Pass area of British Columbia Salway, Anthony Austen

Abstract

The prediction of avalanche activity, by observers in the field, is largely achieved along causal-intuitive lines, depending for its success upon the experience of the observer in his own particular area. Various attempts have been made in the past to quantify such procedures using predictive models based upon meteorological measurements. Modified forms' of a multivariate statistical technique known as linear discriminant analysis, have been tried (Judson and Erickson (1973). Bois et al. (1974) and Bovis (1974) with only partial success. The non-inclusion of time lag decay terms, autocorrelations in the data, insufficient variation in the dependent variable and sampling difficulties, combine to weaken the discriminant approach. These problems and the nature of the phenomenon suggest that a time series approach is required. A completely flexible system of data storage, retrieval and computer analysis has been designed to facilitate the development of time series models for predicting avalanche activity from meteorological observations for the Rogers Pass area of British Columbia. These methods involve autoregressive integrated moving average (ARIMA) stochastic process description techniques, as well as transfer function and stochastic noise identification and estimation procedures. Such methods not only optimize the selection of the most appropriate intercorrelated independent variables for model development, but actually exploit these intercorrelations to considerable advantage; A numerical weighting scheme was devised for the representation of avalanche activity in terms of terminus, size and moisture content codes for each event. Various types of correlation analysis were performed on the data for the period, 1965-73, in which the relationship between avalanche activity and a comprehensive set of simple and complex meteorological variables was examined. Models were then developed for individual years and the entire period, using the three best weighting schemes for avalanche activity representation, and the most promising meteorological variables, as indicated by the results of the correlation analyses. Multiple correlation coefficients as high as 0.87, using a simple two-term model, based on a composite series, involving snowpack depth, water equivalent of new snow and humidity, have been obtained for individual years, and as high as 0.81, using a single six-term model consisting of only two composite meteorological series, for the entire period. Prediction profiles, plotted from these models, indicate that a high level of forecasting accuracy could be possible if such models are fitted to future years. A simulated forecast was performed on data for the period, 1969-73, using a model developed for the period, 1965-69, with a multiple correlation coefficient of 0.83. A value of 0.76 was realized for the simulated forecast indicating a high degree of precision. During this study, great emphasis was placed on keeping the procedures general, rather than specific, so that, besides producing an accurate evaluation of the avalanche hazard at Rogers Pass, it would also be possible to successfully apply such methods to other areas which have an avalanche problem.

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