Simulation of Winter Wheat Phenology in Beijing Area with DSSAT-CERES Model
The Decision Support for Agrotechnology Transfer (DSSAT) model was a worldwide crop model, and crop accurate simulation of phenology was the premise to realize other functional simulations. The objective of this study was to attempt to calibrate the param
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Abstract. The Decision Support for Agrotechnology Transfer (DSSAT) model was a worldwide crop model, and crop accurate simulation of phenology was the premise to realize other functional simulations. The objective of this study was to attempt to calibrate the parameters of wheat phenology coefficients, including cultivar and ecotype coefficients, and develop the winter wheat phenology coefficients of Beijing area. To achieve this goal, field surveys of 7 years in wheat growing seasons in Beijing were carried out during 2005–2012. The trail-and-error method and GLUE method were used to calibrate the phenology parameters with 4 growing seasons of 05/06, 06/07, 07/08 and 08/09. Three growing seasons, 09/10, 10/11, and 11/12 were used for validation, and the results showed good agreements between observed date and predicted date. The RMSE of validation data for TS, BT, HD, AN, and MA were 1.63 d, 2.45 d, 3.16 d, 1.83 d, 3.56 d, respectively. Therefore, the calibrated parameters could be used to monitor winter wheat phenology, and could be used for other research as the basis phenology parameters of Beijing area. Keywords: Phenology wheat
DSSAT-CERES
Phenology coefficients
Winter
1 Introduction Knowledge of crop phenology is essential for plant physiological indexes, crop production and crop managements [1, 2]. Plant growth phase could represent partitioning of the assimilations into the plant organs [3]. Accurate prediction of crop production is closely related with some critical phenology stage, for example anthesis [4]. Besides, phenology is very important in the guidance of crop managements [3]. For most crops models, more than two phases can be used to describe their detail phenological sub-routines in terms of temperature and crop development [5]. Phenology is described by the dimensionless state variable development stage in ‘School of de Wit’ crop models, D. In these models, D is different numbers in different period, it is 0 during emergence, 1 at flowering, and change into 2 during maturity, and the development rate a function of photoperiod and environment temperature [6, 7]. The CERES © IFIP International Federation for Information Processing 2016 Published by Springer International Publishing AG 2016. All Rights Reserved D. Li and Z. Li (Eds.): CCTA 2015, Part II, IFIP AICT 479, pp. 259–268, 2016. DOI: 10.1007/978-3-319-48354-2_27
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model gives a detailed description of phenology simulation. The growth stages of wheat in the CERES model are divided into 9 stages, and vernalization affect is considered as well [8–10]. Water and nutrient can have influence on the development of rate, and STICS considered these affect in phenology simulation [5, 11]. During 49 growing seasons, performance of eight crop growth simulation models of winter wheat are compared by Reimund et al., and those models are widely used, easily accessible and well-documented and nine models for crop during 44 growing seasons of spring barley [12, 13]. The application of rigorous statistical techniques can be use
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