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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

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Front Earth Sci    0, Vol. Issue () : 364-372    https://doi.org/10.1007/s11707-012-0332-0
RESEARCH ARTICLE
Estimating potential yield of wheat production in China based on cross-scale data-model fusion
Zhan TIAN1,2(), Honglin ZHONG1,2, Runhe SHI1, Laixiang SUN3, Günther FISCHER3, Zhuoran LIANG2
1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200062, China; 2. Shanghai Climate Center, Shanghai Meteorological Bureau, Shanghai 200030, China; 3. International Institute for Applied System Analysis, Laxenburg 2361, Austria
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Abstract

The response of the agro-ecological system to the environment includes the response of individual crop’s physiologic process and the adaption of the crop community to the environment. Observation and simulation at the single scale level cannot fully explain the above process. It is necessary to develop cross-scale agro-ecological models and study the interaction of agro-ecological processes across different scales. In this research, two typical agro-ecological models, the Decision Support System for Agro-technology Transfer (DSSAT) model and the Agro-ecological Zone (AEZ) model, are employed, and a framework for effective cross-scale data-model fusion is proposed and illustrated. The national observed data from 36 different agricultural observation stations and historical weather stations (1962-1999) are employed to estimate average crop productivity. Comparison of the two models’ estimations are consistent, which would indicate the possibility ofcross-scale crop model fusion.
Keywords DSSAT model      AEZ model      data-model fusion      agro-ecological system     
Corresponding Author(s): TIAN Zhan,Email:tianz@climate.sh.cn   
Issue Date: 05 December 2012
 Cite this article:   
Zhan TIAN,Honglin ZHONG,Günther FISCHER, et al. Estimating potential yield of wheat production in China based on cross-scale data-model fusion[J]. Front Earth Sci, 0, (): 364-372.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-012-0332-0
https://academic.hep.com.cn/fesci/EN/Y0/V/I/364
CodeDefinition
P1DPhotoperiod response
P1VDays, optimum vernalizing temperature, required for vernalization
P5Grain filling (excluding lag) phase duration
G1Kernel number per unit canopy weight at anthesis
G2Standard kernel size under optimum conditions
G3Kernel filling rate during the linear grain filling stage and under optimum conditions
PHINTPhylochron interval between successive leaf tip appearances
Tab.1  Genetic coefficients of wheat for the DSSAT model ()
Fig.1  Reclassified cropping zone map of China based on observation stations. (a) denotes the original cropping zones, (b) denotes the reclassified cropping zones, and the blue points stand for the observation stations
Fig.2  Comparison between the observed and the GLUE-simulated results (27 winter wheat stations; 9 spring wheat stations) nationwide ((a) and (c) refer to the anthesis day, whereas (b) and (d) denote the maturity day), DOY refers to day of the year.
Wheat typeAnthesis dayMaturity dayYieldUnit wt. Grain
Winter wheatSlope0.9510.9430.9310.842
(S.E.)(0.011)(0.013)(0.056)(0.039)
Spring wheatSlope0.7460.7480.8880.913
(S. E.)(0.035)(0.033)(0.042)(0.038)
Tab.2  Linear regression of simulated . observed results, slope coefficients and standard errors
Wheat typeStationAnthesis DayMaturity DayYield
MCMCGLUEMCMCGLUEMCMCGLUE
Winter wheatAHHF46.52.4414.216.7
SpringwheatFJLH10.411.63.75.128.433.6
Tab.3  RAE comparison of wheat simulations using GLUE and MCMC
Fig.3  Average yields (1962 to 1990) on irrigated land, AEZ (a) and up-scaled DSSAT (b)
Fig.4  Average yields (1962 to 1990) on rain-fed land, AEZ (a) and up-scaled DSSAT (b)
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