Application And Improvement Of WOFOST Model In North China

As the main food crops in China,maize and wheat account for 35.63%and 20.91%of China's total grain output,respectively.Summer maize and winter wheat are also important crops in North China.The accuracy and timeliness of growth monitoring and yield forecasting are the basis for ensuring food security.This paper takes winter wheat and summer maize from 2014 to 2017 in Daxing,Beijing as the research object.The field trials regularly observe indicators such as leaf area index,dry matter quality and yield.The sensitivity of each crop parameter in WOFOST model was evaluated by Simlab software.The parameters of winter wheat and summer maize in 2014-2017 were used to verify the adaptability of WOFOST model in North China.Finally,the spatial structure model of leaf was introduced.Improvements,current research progress,and realization of the model photosynthetic rate worthy of optimization.The main conclusions obtained are as follows:(1)The sensitive parameters of summer maize leaf area index LAI are the correction factor(TMNFTB12)with CO2 assimilation rate at 12 ?,the single-leaf initial quantum efficiency(EFFTB40)at 40 ?,and the dry matter quality TAGP.The sensitive parameters were the correction factor(TMNFTB12)with CO2 assimilation rate at 12 ? and the specific leaf area(SLATB0)at growth period of 0.The sensitive parameters for yield were the correction factor of CO2 assimilation rate at 12 ?.TMNFTB12),an aging correction factor(RFSETB2)at a growth period of 2,a single blade initial quantum efficiency(EFFTB40)at a temperature of 40 ?,and the like.(2)The sensitive parameters of leaf area index LAI of winter wheat are the correction factor(TMNFTB3)with CO2 assimilation rate at 3 ? and the single-leaf CO2 assimilation efficiency(AMAXTB000)with growth period of 0.The sensitive parameters for yield are Accumulated temperature between germination and flowering(TSUM1),evapotranspiration rate correction factor(CFET),and the like.(3)The parameters of 2014 summer maize and 2015 winter wheat were determined.It is concluded that the simulated consistency index d of the summer maize leaf area index LAI and dry matter quality TAGP is 0.938,0.984,respectively.The square root error nRMSE is 15.733%and 16.950%respectively;the simulated winter wheat leaf area index LAI has a simulated consistency index d of 0.893 and a standard root mean square error nRMSE of 23.775%.(4)Using the field data of 2015-2017 for parameter verification,it is concluded that the simulated consistency index d of the summer maize leaf area index LAI and dry matter quality TAGP in 2015 is 0.945,0.987,respectively,and the standard root mean square error nRMSE is 17.054%,14.068%;,the summer maize leaf area index LAI and dry matter quality TALP simulated consistency index d were 0.992,0.953,respectively,and the standard root mean square error nRMSE was 7.172%,29.037%;2016 winter wheat leaf The area consistency index LAI has a simulation consistency index d of 0.774 and a standard root mean square error nRMSE of 30.500%.The 2017 winter wheat leaf area index LAI has a simulated consistency index d of 0.789 and a standard root mean square error nRMSE of 10.771%.The results show that the adjusted parameters can accurately simulate the growth status of summer maize and winter wheat in North China.(5)To achieve the coupling between the WOFOST crop growth model and the photosynthetically active radiation model PAR model to ensure the accuracy of data and code transmission,this study used the 2012 photosynthetic rate measured values to verify the accuracy of the two types of computational models.And the degree of fitting with the measured data,the conclusions show that the fitting consistency coefficient d and the determination coefficient of the PAR model for the simulated and measured values of photosynthetic rate are higher than the WOFOST model,which lays a data foundation for the further optimization of the model.