【摘要】 选取黄土高原东部地区的山西省灵丘县、介休县、隰县与盐湖县为研究区域,利用2005—2012年研究区域的田间观测数据,采用EFAST方法分析模型参数敏感性,采用试错法对玉米的生长发育参数进行调整;在此基础上融合MCD15A3H遥感数据,以叶面积指数为耦合变量,采用SUBPLEX算法将遥感叶面积指数(LAI)数据同化到校准的WOFOST模型中,并再次模拟各区域玉米的生长发育过程。结果表明,校准后的WOFOST模型对生育期和产量的模拟结果较好,生育期的模拟值与实测值的平均误差均小于3 d,产量的模拟值与实测值的相关系数(r)为0.80,均方根误差(RMSE)为956 kg/hm~2;将遥感数据与WOFOST模型同化后,产量的模拟值和实测值的r由0.80提高至0.91,RMSE从956 kg/hm~2降低到660 kg/hm~2。更多还原

【Abstract】 Lingqiu County,Jiexiu County,Xi County and Yanhu County of Shanxi Province in the eastern part of the Loess Plateau were selected as the study area. Field observation data from 2005 to 2012 were used to analyze the sensitivity of model parameters by using EFAST method,and the growth parameters of maize were adjusted by trial and error method. On this basis,MCD15A3H remote sensing data was fused,leaf area index(LAI)data,which was taken as the coupling variable was assimilated into the calibrated WOFOST model using SUBPLEX algorithm,and the growth and development process of maize in each region was simulated again. The results showed that the calibrated WOFOST model had better simulation results for growth period and yield. The average error between simulated value and measured value in the growth period was less than 3 days,the correlation coefficient(r)between simulated value and measured value of yield was 0.80,and the root mean square error(RMSE)was 956 kg/hm~2. After assimilating remote sensing data with WOFOST model,the r of simulated and measured yield increased from 0.80 to 0.91,and the RMSE decreased from 956 kg/hm~2 to 660 kg/hm~2.更多还原