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Optimization and evaluation of the ANTHRO-BGC model for winter crops in Europe

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  • Ma, Shaoxiu
  • Churkina, Galina
  • Wieland, Ralf
  • Gessler, Arthur

Abstract

Climate change and agricultural development are interrelated processes, both of which take place on the global scale. An accurate representation of crop phenology and physiology in ecosystem models is important in order to investigate the interactive processes between atmosphere and biosphere. A new phenological model for crops has been recently incorporated into the ecosystem model BIOME-BGC. Fruit compartments as well as a module for harvest were added to the original model. Here we explore whether eddy flux measurements of agricultural ecosystems are helpful to identify the spatially generalized ecophysiological parameters of the ANTHRO-BGC model (updated BIOME-BGC model) for croplands. The maximum, minimum, and reference values of the ANTHRO-BGC parameters were derived from a literature review. The sensitive parameters of the model were detected by using global sensitivity analysis. The spatially generalized values of ecophysiological parameters for wheat, barley, and rape within a typical temperature and precipitation range in western and central Europe were identified with the help of optimization algorithms and eddy covariance measurements of carbon and water fluxes of agricultural ecosystems as observational constraints. Gross primary productivity (GPP) provided the best constraint on the model parameters for all the three crop types. The validity range of the parameter values defined by the literature review was proved to be reliable. The predictive ability of the optimized model has been improved for GPP and net ecosystem exchange (NEE), but not for evapotranspiration (ET). The performance of the ANTHRO-BGC model was comparable to the performances of other crop models such as DNDC, CERES-EGC, ORCHIDEE-STICS, and SPA model, tested on multiple sites. The optimized ANTHRO-BGC model was relatively stable in response to the variation of the parameters on multiple sites and years.

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  • Ma, Shaoxiu & Churkina, Galina & Wieland, Ralf & Gessler, Arthur, 2011. "Optimization and evaluation of the ANTHRO-BGC model for winter crops in Europe," Ecological Modelling, Elsevier, vol. 222(20), pages 3662-3679.
  • Handle: RePEc:eee:ecomod:v:222:y:2011:i:20:p:3662-3679
    DOI: 10.1016/j.ecolmodel.2011.08.025
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    References listed on IDEAS

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    1. Mo, Xingguo & Chen, Jing M. & Ju, Weimin & Black, T. Andrew, 2008. "Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter," Ecological Modelling, Elsevier, vol. 217(1), pages 157-173.
    2. Turley, Marianne C. & Ford, E. David, 2009. "Definition and calculation of uncertainty in ecological process models," Ecological Modelling, Elsevier, vol. 220(17), pages 1968-1983.
    3. Di Vittorio, Alan V. & Anderson, Ryan S. & White, Joseph D. & Miller, Norman L. & Running, Steven W., 2010. "Development and optimization of an Agro-BGC ecosystem model for C4 perennial grasses," Ecological Modelling, Elsevier, vol. 221(17), pages 2038-2053.
    4. Tubiello, Francesco N. & Rosenzweig, Cynthia & Volk, Tyler, 1995. "Interactions of CO2, temperature and management practices: Simulations with a modified version of CERES-Wheat," Agricultural Systems, Elsevier, vol. 49(2), pages 135-152.
    5. Neville Nicholls, 1997. "Increased Australian wheat yield due to recent climate trends," Nature, Nature, vol. 387(6632), pages 484-485, May.
    6. Chiesi, M. & Maselli, F. & Moriondo, M. & Fibbi, L. & Bindi, M. & Running, S.W., 2007. "Application of BIOME-BGC to simulate Mediterranean forest processes," Ecological Modelling, Elsevier, vol. 206(1), pages 179-190.
    7. Mitchell, Stephen & Beven, Keith & Freer, Jim, 2009. "Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange," Ecological Modelling, Elsevier, vol. 220(23), pages 3259-3270.
    8. Ana Iglesias & Luis Garrote & Sonia Quiroga & Marta Moneo, 2009. "Impacts of climate change in agriculture in Europe. PESETA-Agriculture study," JRC Research Reports JRC55386, Joint Research Centre.
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    Cited by:

    1. Hidy, D. & Barcza, Z. & Haszpra, L. & Churkina, G. & Pintér, K. & Nagy, Z., 2012. "Development of the Biome-BGC model for simulation of managed herbaceous ecosystems," Ecological Modelling, Elsevier, vol. 226(C), pages 99-119.
    2. 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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