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Sample text

Again, risk analysis may be employed to associate demand forecasts of a probabilistic nature with the probability distributions of the differently augmented supply system’s annual yields in any given future year, in order to generate the probability distribution of future deficits which accords with the set of future reliability standards, somehow chosen as most desirable. Different candidate investment projects can then be assessed to see which helps to meet the targetted reliability standards, with least overall cost.

THE WORKSHOP The Workshop from which this book stems was held at the University of Leicester in July 1985; it was intended to be of interest to members of the water industry, social scientists concerned with the interaction between economic and social factors and water demand, mathematicians and statisticians concerned with methodological aspects of demand forecasting, and engineers concerned with realisation of demand forecasting schemes. Financed by a grant from the ESRC Environmental Issues Programme, it was organised by Vince Gardiner and Paul Herrington of the University of Leicester, and Bryan Coulbeck of the Water Control Unit, Leicester Polytechnic.

1982). The accuracy of extrapolation (time series) methods: results of a forecasting competition. Journal of Forecasting, 1, 111–53. Million, G. (1980). D. ) Forecasting Public Utilities, 9–15. L. (1971). Forecasting electricity sales. The Statistician, 20, 15–22. J. et al. (1984). An examination of factors contributing to Delphic accuracy. Journal of Forecasting, 3, 173–82. C. (1980). S. ), Atlas of Drought in Britain 1975–6, Institute of British Geographers, London, 67–8. A. et al. (1981). Deterministic models for predicting residential water consumption.

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