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

Many environmental and agricultural problems are not restricted to national boundaries and therefore require international cooperation if solutions ar e to be found. Often, these solutions require the ability to use soil data as input in simulation models, however, despite a number of recognised inte rnational standards, soil data are rarely compatible across national fronti ers. This problem was encountered when creating the HYdraulic PRoperties of European Soils (HYPRES) database. The data, which includes particle-size d istributions, were collected from 20 institutions in 12 countries. Only a f ew of these institutions adhered strictly to a recognised international sys tem. 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 procedure s were evaluated. The accuracy of the different procedures was found to var y with size intervals between measured points of the particle-size distribu tion. The loglinear interpolation of the cumulative particle-size distribut ion has previously been used in various studies but was found to give the l east accurate estimation of the four procedures. Fitting the Gompertz curve , which is a special asymmetric type of curve described by a closed-form eq uation, showed less sensitivity to size intervals between measured points. However, interpolation within some of the particle-size distributions was n ot sufficiently accurate and this procedure could not be applied to particl e-size distributions where the number of measured size fractions was less t han the number of model parameters. Fitting a nonparametric spline function to the particle-size distributions showed a considerable increase, in accu racy of the interpolation with decreasing size intervals between measured p oints. As a novel approach, the similarity procedure was introduced which d oes not use any mathematical interpolation functions. It uses an external s ource 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 interpola tions. Once an extensive external reference data set with well-quantified p article-size distributions is available, the similarity procedure becomes a very powerful tool for interpolations. Based on the number and distributio n 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 si milarity procedure to estimate missing values. Results of this study were u sed 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 . (C) 1999 Elsevier Science B.V. All rights reserved.