Evaluation of different procedures to interpolate particle-size distributions to achieve compatibility within soil databases

Abstract

Many environmental and agricultural problems are not restricted to national boundaries and therefore require international cooperation if solutions are to be found. Often, these solutions require the ability to use soil data as input in simulation models, however, despite a number of recognised international standards, soil data are rarely compatible across national frontiers. This problem was encountered when creating the HY draulic PR operties of E uropean S oils (HYPRES) database. The data, which includes particle-size distributions, were collected from 20 institutions in 12 countries. Only a few of these institutions adhered strictly to a recognised international system. Therefore, interpolation of the cumulative particle-size distribution was required to achieve compatibility of particle-size distributions within the HYPRES database. In this study, four different interpolation procedures were evaluated. The accuracy of the different procedures was found to vary with size intervals between measured points of the particle-size distribution. The loglinear interpolation of the cumulative particle-size distribution has previously been used in various studies but was found to give the least accurate estimation of the four procedures. Fitting the Gompertz curve, which is a special asymmetric type of curve described by a closed-form equation, showed less sensitivity to size intervals between measured points. However, interpolation within some of the particle-size distributions was not sufficiently accurate and this procedure could not be applied to particle-size distributions where the number of measured size fractions was less than the number of model parameters. Fitting a nonparametric spline function to the particle-size distributions showed a considerable increase in accuracy of the interpolation with decreasing size intervals between measured points. As a novel approach, the similarity procedure was introduced which does not use any mathematical interpolation functions. It uses an external source of soil information from which soils are selected with particle-size distributions that match the distribution of the soil under investigation. This similarity procedure was capable of giving the most accurate interpolations. Once an extensive external reference data set with well-quantified particle-size distributions is available, the similarity procedure becomes a very powerful tool for interpolations. Based on the number and distribution of measured points on the particle-size distributions, a general rule was formulated to decide whether to fit a spline function or use the novel similarity procedure to estimate missing values. Results of this study were used to classify all soils in the HYPRES database into the same soil texture classes used in the 1:1.000.000 scale Soil Geographical Database of Europe.