Between 100 and 150 years ago, the Italian government reclaimed land from the edge of the Venice lagoon for agricultural purposes. The reclaiming process mostly consists of constructing a barrier of earth and pumping water out of the area to maintain a dry zone on the surface. The cost of pumping directly affects the farmers’ bottom line. Over pumping is wasteful but under pumping causes poor crop production. Therefore, they need to understand, model, and predict the optimal amount of pumping. Several research labs at the Università degli Studi di Padova are constructing this model. In particular, my responsibility was to predict unsaturated hydraulic properties for a dense grid from measurements taken at 50 locations (multivariate geospatial statistics). I also developed a method to predict these values for other fields without measuring the properties directly (spatial upscaling and pedotransfer functions). This required an investigation into the underlying causal processes which develop the soil (factorial kriging analysis). One unique aspect of this site was the paleo-river channels which add extreme variability to the soil which was challenging from a geospatial statistical point of view. The novel part of this research is the application of geospatial statistics to the study of unsaturated hydraulic properties.
Bevington, J., F. Morari, D. Piragnolo, P. Teatini and G. Vellidis. 2016. Explanation of the Spatial Variation of Hydraulic Properties of Soils in the Venice Lagoon Margin (Italy) with Factorial Kriging Analysis. Geoderma. 262: 294-305.
Bevington, J., F. Morari, D. Piragnolo, P. Teatini and G. Vellidis. 2019. Spatial Prediction of Hydraulic Zones from Soil Properties and Secondary Data Using Factorial Kriging Analysis. Electronics in Agriculture. 156: 426-438.