On the use of kriging in the spatial analysis of acid precipitation data

Abstract This paper examines a technique known as simple Kriging that is becoming popular in the spatial analysis of data pertinent to acid rain. In the first part of the paper, we provide a detailed derivation of the relevant equations in order to clarify the assumptions that underlie the technique. A major assumption is that a given set of observations can be represented as the sum of a constant mean and a stochastic fluctuation, which is governed by an isotropic and homogeneous spatial autocorrelation function. Because this assumption cannot be justified in the context of precipitation chemistry data that reflect inhomogeneous processes, we suggest a technique that combines deterministic modeling with the attractive features of Kriging. We demonstrate this technique by applying it to a data set consisting of annual averages of wet deposition of S. We also show that this simple spatial analysis method is a substantial improvement on simple Kriging.