Ecological Modelling 222 (2011) 1614–1625 Contents lists available at ScienceDirect Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics C. Nendel ∗ , M. Berg, K.C. Kersebaum, W. Mirschel, X. Specka, M. Wegehenkel, K.O. Wenkel, R. Wieland Leibniz-Centre for Agricultural Landscape Research, Institute of Landscape System Analysis, Eberswalder Straße 84, 15374 Müncheberg, Germany article info Article history: Received 22 November 2010 Received in revised form 16 February 2011 Accepted 19 February 2011 Available online 21 March 2011 Keywords: Simulation model Climate change Validation Crop rotation Yield prediction 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 CO 2 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. © 2011 Elsevier B.V. All rights reserved. 1. Introduction The simulation model for nitrogen and carbon dynamics in agro- ecosystems (MONICA) was developed for the assessment of climate change impact on agricultural production and the environment. The dynamic, process-based model was especially designed to account for the coupled effect of climate variables that are expected to change significantly in future on crop growth and development, and soil processes in Central Europe. Temperature relations on photosynthesis, assimilation, evapotranspiration and other vital biochemical processes in the plant and soil moisture feedback to crop water requirements are well understood and implemented in all major simulation models of similar complexity. However, the effect of the atmospheric CO 2 concentration, referred to below as [CO 2 ], on crop photosynthesis and transpiration was included in many simulation models at a later stage (e.g. Mestre-Sanchis and Feijóo-Bello, 2009). A detailed overview of approaches imple- mented in crop models is given by Tubiello and Ewert (2002). The Braunschweig Free Air Carbon Enrichment (FACE) experiment (Weigel and Dämmgen, 2000) provided data for the first time on the growth and development of the most important crops (includ- ∗ Corresponding author. Tel.: +49 33432 82355; fax: +49 33432 82334. E-mail address: nendel@zalf.de (C. Nendel). ing sugar beet and winter barley) grown in Central Europe under the influence of a [CO 2 ] level of 550 ppm under field conditions. So far, these crops have received little attention in model-based climate change studies (Tubiello and Ewert, 2002). Different algo- rithms developed earlier to describe the effect of [CO 2 ] on crop photosynthesis and transpiration were tested against some of the Braunschweig data and evaluated with regard to their suitability for use in MONICA (Nendel et al., 2009). Equipped accordingly, MONICA now combines the simple, yet robust philosophy of its pro- genitor HERMES (Kersebaum, 1995; Kersebaum and Richter, 1991) with the functionality to explain the combined effect of temper- ature, radiation, water supply and [CO 2 ] on biomass growth and yield formation (Wall et al., 2006) for conditions in Central Europe. Since the consideration of this combined effect is a key functionality of understanding the impact of a changing climate on agricultural crop production, several models have been upgraded and tested before to this end. However, most of the previous modelling exer- cises concentrate on winter wheat as the world’s most important food crop (Tubiello and Ewert, 2002), while others focus on a larger scale and use very much simplified approaches (Ciais et al., 2010). A small number of simulation exercises have been presented, in which dynamic process models for crop growth were employed to predict future yields on larger than plot scales. These exercises were applied to single regions (Chavas et al., 2009; Stöckle et al., 2010; Thomson et al., 2006), countries (Alexandrov et al., 2002; 0304-3800/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolmodel.2011.02.018