Spatial prediction of topsoil salinity in the Chelif Valley, Algeria, using local ordinary kriging with local variograms versus whole-area variogram

Abstract

A novel form of ordinary kriging, involving the local estimation and modelling of the variogram at each prediction site (OKLV), is tested at a regional scale on a large data set, in order to adapt to non-uniform spatial structures and improve the assessment of the salinity hazard in the lower Chelif Valley, Algeria. The spatial variability study was carried out on a 38000 ha area using 5141 topsoil electrical conductivity (EC) measurements systematically sampled on a 250 m by 250 m grid. Variography analysis confirmed the existence of large trends in the EC variability with differing spatial structures between sub-areas.

OKLV performed better than ordinary kriging with a whole-area variogram (OKWV) in predicting the proportion of high saline soils in large blocks, but the predictions appeared mostly similar. In contrast, the estimation variance maps revealing the uncertainties of the spatial predictions were markedly different between the 2 methods. OKLV integrates the local spatial structure in the uncertainty assessment, whereas kriging with a whole-area variogram only considers the sampling intensity. Comparison with prediction errors on a validation set confirmed the consistency of the OKLV prediction variance. This appears to be a major improvement for decision-making procedures such as delineating areas where remediation should take place.