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This article in JEQ

  1. Vol. 25 No. 3, p. 519-526
     
    Received: May 4, 1995


    * Corresponding author(s): bouma@bodlan.beng.wau.nl
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doi:10.2134/jeq1996.00472425002500030017x

Use of Soil Survey Data for Modeling Solute Transport in the Vadose Zone

  1. J. Bouma *,
  2. H. W. G. Booltink and
  3. P. A. Finke
  1. Researcher at the Staring Centre for Integrated Land, Soil and Water Research, Wageningen, the Netherlands.

Abstract

Abstract

Soil surveys have now been completed in many countries and qualitative interpretations in terms of soil suitability for different forms of land use, which are part of most soil survey reports, are being used widely. These interpretations are, however, essentially based on expert judgement and they are inadequate to answer many modern questions about ecological and environmental aspects of alternative forms of land use. Simulation modeling of solute transport and plant growth has become an operational tool in land use studies and soil survey databases can be an important source of basic soil and landscape information to be used in modeling. Still, many data are not in a form that can be used directly and an effort has to be made to transform soil survey data into a usable format, by developing pedotransfer functions. In discussing soil survey data, a distinction can be made between point- and area data. Case studies for leaching of nitrates (NO3) and growth of potato (Solanum tuberosum L.) in a loamy and clayey soil, illustrate use of different types of class-pedotransfer functions for functional soil horizons. Monte Carlo techniques are used to illustrate the effect of variability of hydraulic basic data on results obtained. Soil surveys define soil data and interpretations for areas of land by considering “representative” soil profiles for delineated areas on the map. Internal variation is expressed only in qualitative terms. Geostatistical techniques can be used to interpolate point data to areas of land, allowing quantitative expressions including error statements. The effects of upscaling of point data to cells of different sizes on leaching of NO3 and growth of potato are illustrated for data derived from a Dutch field. All illustrations demonstrate the crucial role of Geographic Information Systems (GIS) in storing and manipulating basic soil and landscape data.

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