Nutrient Cycling in Agroecosystems

, Volume 57, Issue 2, pp 119–129

Using a boundary line approach to analyze N2O flux data from agricultural soils

  • Ulrich Schmidt
  • Hanspeter Thöni
  • Martin Kaupenjohann
Article

DOI: 10.1023/A:1009854220769

Cite this article as:
Schmidt, U., Thöni, H. & Kaupenjohann, M. Nutrient Cycling in Agroecosystems (2000) 57: 119. doi:10.1023/A:1009854220769

Abstract

Predicting the N2O flux from soils is difficult because of the complex interplay of the various processes involved. In this study a boundary line approach was used to apply results from mechanistic experiments to N2O flux data resulting from measurements on field scale in southern Germany. Boundary lines were fitted to the rim of the data points in scattergrams depicting readily obtainable soil variables against the measured N2O flux. The boundary line approach is based on the hypothesis that this line depicts the functional dependency between the two variables. For determining these boundary lines a novel method was applied. The function best representing the relationship between the N2O flux and soil temperature had a maximum above 23 °C and the one between the N2O flux and the water filled pore space (WFPS, to represent water content) had a maximum at 72% WFPS. In the range of 0–20 mg N kg-1 the relationship between N2O flux and nitrate in the soil was best described by a linear function, whereas in the range of 0–35 mg N kg-1 a Michaelis–Menten function was more appropriate. The boundary lines specified in this study are in agreement with existing theoretical concepts as well as experimental results obtained under controlled and field conditions as reported in the literature. Therefore, the boundary line approach can be used to improve empirical models for predicting the N2O flux in the field.

boundary line field measurement model N2O flux 

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Ulrich Schmidt
    • 1
  • Hanspeter Thöni
    • 2
  • Martin Kaupenjohann
    • 1
  1. 1.Department of Soil ScienceGermany
  2. 2.Department of Applied Mathematics and StatisticsUniversity of HohenheimStuttgartGermany

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