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Study on Simulation of Rice Yield with WOFOST in Heilongjiang Province

机译:黑龙江省WOFOST水稻产量模拟研究

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WOFOST (world food study) model had been successfully used in daily business of agro meteorological monitoring and yield forecasting in European Union, and also been widely used in crop growth process simulation and yield estimation all over the world. In this study, with the help of the rice growth observed data, the meteorological data at the same time and the rice planting regional planning data in Heilongjiang Province, the crop parameters for WOFOST model were improved. Based on the localization and regionalization of the model, the rice yield in county and region scale in Heilongjiang Province was simulated. In province scale, the WOFOST simulated yield was good, and the relative error between estimated yield and statistical yield from 2006 to 2013 were respectively 2.71%, 8.47%, 6.41%, -15.96%, 3.95%, 0.02%, -7.06%, 0.88%, four of which beyond ±5%. But in county scale, the correlation between WOFOST simulated and statistical yield was poor, and not passing the test of significance. In order to improve the precision, the trend yield calculated by the statistical yield and the WOFOST simulated yield were both used to build a comprehensive rice yield simulation model by the multiple lineal' regression method year by year from 2006 to 201 3. Then the rice yield both in county and province scale in Heilongjiang Province was calculated by using the comprehensive model. In county scale, the comprehensive simulated yield and the statistical yield in county scale passed significant test of 0.01, and the correlation coefficients were respectively 0.715,0.728,0.829,0.810,0.888,0.919,0.868,0.798, the R2 were respectively 0.511, 0.529, 0.686, 0.656, 0.789, 0.844, 0.753, 0.636. In province scale, the relative error between the estimated yield and statistical yield during 2006-2013 were respectively-1.72%, 2.12%, 3.02%,-2.45%, 1.27%,-0.89%, -0.38%, 1.96%. The comprehensive model had a good effect on improving the defects of fluctuation in individual year with a relative hi
机译:WOFOST(世界粮食研究)模型已经在欧盟的农业气象监测和产量预测的日常业务获得成功应用,并在世界各地被广泛应用于农作物生长过程的模拟和产量估算。在这项研究中,与水稻生长的帮助下观察到的数据,在同一时间的气象数据和黑龙江省水稻种植区域规划数据,WOFOST模型作物参数进行了改进。基于本地化和模型的区域化,黑龙江省县和区域尺度水稻产量进行了模拟。在全省规模,WOFOST的模拟收益率还是不错的,和2006至2013年预计产量和统计产量的相对误差分别为2.71%,8.47%,6.41%,-15.96%,3.95%,0.02%,-7.06%,这超出了±5%4 0.88%。但在县城规模,WOFOST之间的相关性模拟和统计产量是穷人,而不是通过显着性检验。为了提高精度,趋势产量由统计产量和WOFOST模拟计算产量均被用来从2006年建立由一年多直系”回归法一年的综合性水稻产量仿真模型201 3.然后将大米黑龙江省县,全省规模以上产量都通过使用综合模型计算。在全县规模,综合模拟产量和规模县的统计产量传递的0.01显著测试,相关系数分别为0.715,0.728,0.829,0.810,0.888,0.919,0.868,0.798中,R2分别为0.511,0.529 ,0.686,0.656,0.789,0.844,0.753,0.636。在省规模,在2006-2013的估算产率和产量的统计之间的相对误差分别为-1.72%,2.12%,3.02%, - 2.45%,1.27%, - 0.89%,-0.38%,1.96%。综合模型对改善个别年份波动的缺陷与相对喜很好的效果

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