INCORPORATING CLIMATE-CHANGE INTO RISK ASSESSMENT USING GREY MATHEMATICAL-PROGRAMMING

Climate change presents problems for risk assessment procedures due to the difficulty of assigning a measure of probability to any future sc enario. Grey systems theory provides an alternative means of quantifyi ng uncertainty based on interval numbers. Within a mathematical progra mming model, grey systems theory provides a means for working with unc ertainties that are not amenable to stochastic or fuzzy quantification . An example of forestry and agricultural expansion in the Mackenzie R iver Basin is used to illustrate grey mathematical programming in a ho p, skip and jump formulation. In this example, climatic constraints ar e implicitly contained in other parameters which did not incorporate t he different components of uncertainty associated with meteorological observations. These components can be combined into a numerical interv al that can be used in determining a grey number. However, most of the se uncertainties are negligible in climatic data sets due to the numbe r of observations. Nevertheless, these uncertainties point to some of the problems in assessing the risks of climate change, and a grey math ematical programming algorithm is useful for assessing the sensitivity of a decision to climatically sensitive parameters. (C) 1997 Academic Press Limited