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Updated: Jun 7, 2026

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
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Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

Published on: September 1, 2020

Soil-test N recommendations augmented with PEST-optimized RZWQM simulations.

R W Malone1, D B Jaynes, L Ma

  • 1USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA, USA. rob.malone@ars.usda.gov

Journal of Environmental Quality
|November 4, 2010
PubMed
Summary
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Understanding year-to-year soil nitrate test (LSNT) variability is key for producer adoption. This study shows LSNT reduces nitrate loss in tile drainage, with early-season weather driving N rate variations.

Area of Science:

  • Agricultural Science
  • Environmental Science
  • Soil Science

Background:

  • Late-spring soil nitrate tests (LSNT) offer potential for optimizing nitrogen (N) fertilizer management.
  • Variability in LSNT results can impact producer confidence and adoption rates.
  • Understanding watershed-scale N dynamics is crucial for water quality management.

Purpose of the Study:

  • To evaluate the Root Zone Water Quality Model (RZWQM) for simulating watershed-scale LSNT variability.
  • To analyze long-term N dynamics under LSNT and conventional N application strategies.
  • To identify key environmental factors influencing interannual LSNT-based N rate variations.

Main Methods:

  • Utilized autoregressive techniques and the PEST calibration program to optimize RZWQM.

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Last Updated: Jun 7, 2026

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  • Simulated watershed-scale LSNT effects in the tile-drained Walnut Creek, Iowa watershed.
  • Developed a statistical model using RZWQM simulations (1970-2005) to assess weather impacts on N rates.

    • Main Results:

    • RZWQM accurately simulated lower nitrate concentrations in discharge from LSNT treatments compared to fall N applications.
    • Early-season precipitation and temperature explained 90% of interannual variation in LSNT-based N rates.
    • Long-term simulations indicated lower average N loss in tile flow for LSNT (20.4 kg N ha⁻¹) versus spring (22.2 kg N ha⁻¹) and fall (27.3 kg N ha⁻¹) applications.

    Conclusions:

    • RZWQM is a valuable tool for assessing the water quality impacts of LSNT.
    • LSNT enhances N retention in the root zone for crop uptake, reducing N loss.
    • Interannual LSNT N rate adjustments are primarily driven by early-season weather patterns.