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作者	单位
郭其乐，李颖，田宏伟	（1.中国气象局\河南省农业气象保障与应用技术重点开放实验室，河南郑州 450003； 2.河南省气象科学研究所，河南郑州 450003； 3.中国农业科学院研究生院，北京 100081）

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中文摘要:

为分析WheatSM模型区域业务应用的适用性，采用EFAST全局敏感性分析方法，对WheatSM模型的小麦生长发育参数进行分析，筛选出了影响模型模拟效果的10个敏感参数，即冬小麦各发育阶段的基本发育系数（K1、K21、K22和K3）、出苗至越冬期的温度系数（P21）、越冬至拔节期的光周期系数（Q2）、抽穗后的光合产物向籽粒的转运效率（TR2）、比叶面积（SLA），以及拔节至抽穗期的穗干物质分配系数（PcEar34）和抽穗至成熟期的叶干物质分配系数（PcLeaf45）。然后，基于农业气象观测数据，利用SCE-UA全局优化算法，对敏感参数进行优化和率定。结果表明，模型对出苗期模拟具有很高的精度，RRMSE<0.5%，R>0.9，其对抽穗期、拔节期的模拟效果尚可，对越冬期的模拟效果最差；模型模拟的干物质和LAI与观测数据的相关性较高，但相对误差较大，精度为75.0%左右。

英文摘要:

To validate the application of WheatSM model,based on the global sensitivity analysis method (EFAST),wheat growth and development parameters of the WheatSM model were analyzed,and then ten key parameters were screened out to optimize,such as the basic development coefficients before heading (K1,K21,K22 and K3),the temperature coefficient from emergence to overwintering (P21),the genetic photoperiod coefficient from overwintering to jointing (Q2),the transfer rate of photosynthetic product to grain after heading (TR2) ,the specific leaf area (SLA),the partition coefficient of ear dry matter from jointing to heading (PcEar34),and the partition coefficient of leaf dry matter from heading to maturity (PcLeaf45). Based on these parameters,the global optimization algorithm (SCE-UA) was carried out,and observation data of many continuous years was used to constrain the cost function of optimization and validate the effect. The results showed that the WheatSM model has the highest accuracy for the simulation at emergence stage,with RRMSE<0.5%,and R>0.9; and it has a modest accuracy for the simulations at heading and jointing stages,but the worst accuracy for the simulation at overwintering stage. The simulation results of dry matter and LAI have high correlation to observed data,with R>0.9,but the accuracy is relatively lower (75.0%).

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