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The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics

Author

Listed:
  • Nendel, C.
  • Berg, M.
  • Kersebaum, K.C.
  • Mirschel, W.
  • Specka, X.
  • Wegehenkel, M.
  • Wenkel, K.O.
  • Wieland, R.

Abstract

A fundamentally revised version of the HERMES agro-ecosystem model, released under the name of MONICA, was calibrated and tested to predict crop growth, soil moisture and nitrogen dynamics for various experimental crop rotations across Germany, including major cereals, sugar beet and maize. The calibration procedure also included crops grown experimentally under elevated atmospheric CO2 concentration. The calibrated MONICA simulations yielded a median normalised mean absolute error (nMAE) of 0.20 across all observed target variables (n=42) and a median Willmott's Index of Agreement (d) of 0.91 (median modelling efficiency (ME): 0.75). Although the crop biomass, habitus and soil moisture variables were all within an acceptable range, the model often underperformed for variables related to nitrogen. Uncalibrated MONICA simulations yielded a median nMAE of 0.27 across all observed target variables (n=85) and a median d of 0.76 (median ME: 0.30), also showing predominantly acceptable results for the crop biomass, habitus and soil moisture variables. Based on the convincing performance of the model under uncalibrated conditions, MONICA can be regarded as a suitable simulation model for use in regional applications. Furthermore, its ability to reproduce the observed crop growth results in free-air carbon enrichment experiments makes it suited to predict agro-ecosystem behaviour under expected future climate conditions.

Suggested Citation

  • Nendel, C. & Berg, M. & Kersebaum, K.C. & Mirschel, W. & Specka, X. & Wegehenkel, M. & Wenkel, K.O. & Wieland, R., 2011. "The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics," Ecological Modelling, Elsevier, vol. 222(9), pages 1614-1625.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:9:p:1614-1625
    DOI: 10.1016/j.ecolmodel.2011.02.018
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    1. Marco Moriondo & Marco Bindi & Zbigniew Kundzewicz & M. Szwed & A. Chorynski & P. Matczak & M. Radziejewski & D. McEvoy & Anita Wreford, 2010. "Impact and adaptation opportunities for European agriculture in response to climatic change and variability," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(7), pages 657-679, October.
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    11. Carauta, M. & Guzman-Bustamante, I. & Meurer, K. & Hampf, A. & Troost, C. & Rodrigues, R. & Berger, T., 2018. "Assessing the full distribution of greenhouse gas emissions from crop, livestock and commercial forestry plantations in Brazil's Southern Amazon," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277118, International Association of Agricultural Economists.
    12. Carauta, Marcelo & Troost, Christian & Guzman-Bustamante, Ivan & Hampf, Anna & Libera, Affonso & Meurer, Katharina & Bönecke, Eric & Franko, Uwe & Ribeiro Rodrigues, Renato de Aragão & Berger, Thomas, 2021. "Climate-related land use policies in Brazil: How much has been achieved with economic incentives in agriculture?," Land Use Policy, Elsevier, vol. 109(C).
    13. Hampf, Anna C. & Stella, Tommaso & Berg-Mohnicke, Michael & Kawohl, Tobias & Kilian, Markus & Nendel, Claas, 2020. "Future yields of double-cropping systems in the Southern Amazon, Brazil, under climate change and technological development," Agricultural Systems, Elsevier, vol. 177(C).
    14. Carauta, Marcelo & Parussis, Julia & Hampf, Anna & Libera, Affonso & Berger, Thomas, 2021. "No more double cropping in Mato Grosso, Brazil? Evaluating the potential impact of climate change on the profitability of farm systems," Agricultural Systems, Elsevier, vol. 190(C).
    15. Xenia Specka & Claas Nendel & Ralf Wieland, 2019. "Temporal Sensitivity Analysis of the MONICA Model: Application of Two Global Approaches to Analyze the Dynamics of Parameter Sensitivity," Agriculture, MDPI, vol. 9(2), pages 1-29, February.

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