Decision making and uncertainty: Bayesian analysis of potential flood heights

This paper provides a case study of a method to estimate the value of additional information, before its acquisition, to aid decision making in the face of uncertainty. The approach employs conditional simulation in a Monte Carlo framework to conduct a Bayesian assessment of the value of information in an explicitly spatial setting. This paper demonstrates the procedure as applied by a hypothetical decision maker concerned with coastal flood control where flood damage is dependent on the spatial distribution of elevation. A set of known survey points provides the decision maker with limited knowledge of elevation. The method explored in the paper allows the decision maker to ascertain the potential value of additional survey information in terms of its ability to reduce uncertainty about flood damage.