Simulation of Moisture Deficits and Areal Interpolation by Universal Cokriging

Simulation models for calculating moisture deficits for areas of land require interpolation procedures to arrive from point observations to area‐covering statements. We use both (1) calculate first, interpolate later (CI) procedures, which interpolate calculated model results for test locations, and (2) procedures which interpolate basic soil data toward test locations, followed by model calculations, interpolate first, calculate later (IC) procedures. In this study several CI and IC procedures which simulate moisture deficits are compared by means of a test set of 100 observations, yielding the mean standard error (MSE). CI procedures consistently produced lower MSE values than IC procedures. Parameters of the pseudocovariance function (PCF), which models the spatial structure of bivariate increments in universal cokriging, were estimated by means of the restricted maximum likelihood procedure. Compared to universal kriging, universal cokriging yielded comparable MSE values, but a lower mean variance of the prediction error. Best results in this study were obtained by pointwise simulation model calculations, followed by statistical interpolations.