Evaluating the Performance of Ordinary Kriging in Mapping Soil Salinity

Abstract

AbstractThe performance of ordinary kriging (OK) is impacted by different factors that characterize the data sets being interpolated. The following factors were investigated as part of this study to evaluate the performance of OK in mapping soil salinity: (1) sampling density (field scale, subbasin scale, and subbasin scale merged with field scale); (2) spatial point patterns (random, aggregated, and regular); (3) spatial and no spatial autocorrelations; (4) normal and skewed distributions; and (5) homogeneity and heterogeneity. The objective of this study is to evaluate the performance of the OK model against each of the aforementioned factors. To achieve this objective, 36 different data sets were selected from data collected from 1999 to 2008 in a study area in the Lower Arkansas River Valley in Colorado. These data sets were selected to represent the different factors used to evaluate the performance of OK, in which each factor is represented by three different data sets. Assessments of the OK model r...