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Building geochemically based quantitative analogies from soil classification systems using different compositional

Mark A Chappell1, Jennifer M Seiter1, Haley M West1

  • 1Environmental Laboratory, U.S. Army Engineer Research & Development Center, Vicksburg, Mississippi, United States of America.

Plos One
|February 20, 2019
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Summary
This summary is machine-generated.

Soil heterogeneity introduces uncertainty in biogeochemical models. This study developed quantitative analogies from soil properties, finding water-extracted (WE) compositions best classified soil types, improving model accuracy.

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Area of Science:

  • Soil Science
  • Environmental Science
  • Geochemistry

Background:

  • Soil heterogeneity significantly impacts near-surface biogeochemical modeling accuracy.
  • Existing soil classification systems rely on qualitative pedomorphological criteria, limiting quantitative applications.
  • Bridging qualitative soil taxonomy with quantitative physicochemical properties is crucial for improved modeling.

Purpose of the Study:

  • To develop a novel classification analogy concept for translating qualitative soil taxonomy into quantitative physicochemical descriptions.
  • To explore the potential of compositional data analysis (CoDA) for creating these quantitative analogies.
  • To assess the discriminatory power of different physicochemical compositions in classifying soil types.

Main Methods:

  • Collected soil horizons classified under the Alfisols taxonomic Order.
  • Quantified soil properties through physical and chemical characterizations.
  • Applied multivariate statistical modeling with CoDA, partitioning data into Water-extracted (WE), Mehlich-III extracted (ME), and particle-size distribution (PSD) compositions.

Main Results:

  • Quantitative analogies were developed using WE, ME, and PSD compositions.
  • The WE composition demonstrated superior ability to discriminate among soil samples compared to ME and PSD.
  • WE-based analogies were particularly effective at classifying soils at the Great Group and thermal regime levels.

Conclusions:

  • The developed classification analogy concept offers a quantitative approach to soil characterization.
  • Water-extracted (WE) soil composition provides a robust basis for discriminating between different soil types.
  • This methodology holds potential for enhancing the accuracy of biogeochemical models by reducing uncertainty associated with soil heterogeneity.