Characterizing the spatial variability of groundwater quality using the entropy theory: I. Synthetic data

Abstract

This paper, the first in a series of two, applies the entropy (or information) theory to describe the spatial variability of synthetic data that can represent spatially correlated groundwater quality data. The application involves calculating information measures such as transinformation, the information transfer index and the correlation coefficient. These measures are calculated using discrete and analytical approaches. The discrete approach uses the contingency table and the analytical approach uses the normal probability density function. The discrete and analytical approaches are found to be in reasonable agreement. The analysis shows that transinformation is useful and comparable with correlation to characterize the spatial variability of the synthetic data set, which is correlated with distance. Copyright © 2004 John Wiley & Sons, Ltd.