The ARMOSA simulation crop model: Overall features, calibration and validation results

Alessia Perego, Andrea Giussani, Mattia Sanna, Mattia Fumagalli, Marco Carozzi, Lodovico Alfieri, Stefano Brenna, Marco Acutis

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

ARMOSA is a dynamic simulation model which was developed to simulate crop growth and development, water and nitrogen dynamics under different pedoclimatic conditions and cropping systems in the arable land. The model is meant to be a tool for the evaluation of the impact of different crop management practices on soil nitrogen and carbon cycles and groundwater nitrate pollution. A large data set collected over three to six years from six monitoring sites in Lombardia plain was used to calibrate and validate the model parameters. Measured meteorological data, soil chemical and physical characterizations, crop-related data of different cropping systems allowed for a proper parameterization. Fit indexes showed the reliability of the model in adequately predicting crop-related variables, such as above ground biomass (RRMSE=11.18, EF=0.94, r=0.97), Leaf Area Index maximum value (RRMSE=8.24, EF=0.37, r=0.72), harvest index (RRMSE=19.4, EF=0.32, r=0.74), and crop N uptake (RRMSE=20.25, EF=0.69, r=0.85). Using two different one-year data set from each monitoring site, the model was calibrated and validated, getting to encouraging results: RRMSE=6.28, EF=0.52, r=0.68 for soil water content at different depths, and RRMSE=34.89, EF=0.59, r=0.75 for soil NO3-N content along soil profile. The simulated N leaching was in full agreement with measured data (RRMSE=26.62, EF=0.88, r=0.98).

Original languageEnglish
Pages (from-to)23-38
Number of pages16
JournalItalian Journal of Agrometeorology
Issue number3
Publication statusPublished - Dec 1 2013
Externally publishedYes

Keywords

  • Crop growth
  • Nitrogen leaching
  • Performance assessment
  • Simulation model
  • Water dynamics

ASJC Scopus subject areas

  • Forestry
  • Agronomy and Crop Science
  • Atmospheric Science

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