A comparison of spatial design methods for correlated observations

Random fields are frequently used to model spatial environmental processes. Optimum design theory for regression experiments is consequently employed to assess and construct monitoring networks for these processes. However, straightforward application of much of this theory is not possible, since the typical assumption of independent errors is violated. In the present article I intend to give an overview on design methods that attempt to cope with the problem, amongst them two recently developed approaches. For a comparison the techniques will be applied to the design of a water‐quality monitoring network in the Südliche Tullnerfeld in Lower Austria. Copyright © 2005 John Wiley & Sons, Ltd.