不同空间尺度下的ALMANAC模型验证

Validation of the ALMANAC model with different spatial scale

ALMANAC模型最早作为EPIC模型的一部分 ,用于模拟土壤侵蚀导致的土地生产力的下降 .它将试验数据的统计过程和作物生长的机理过程结合起来 ,是一种典型的基于过程模拟的应用型作物生长模型 .如能在不同的空间尺度上验证模型的适用性 ,无疑会大大扩展模型的应用范围 .从这一目的出发 ,利用美国得克萨斯州 1 9个试验田和 9个县的玉米和高粱产量资料及其相关的作物、土壤、田间管理等数据 ,模拟了 1 998年田间尺度 ,1 989～ 1 998年县级尺度的平均作物产量 .模拟结果表明 ,ALMANAC模型能够很好地模拟两种不同空间尺度的作物产量 ,其相对误差在田间尺度上分别为 8.9% (高粱 )和 9.4 % (玉米 ) ,在县级尺度上分别达到 2 .6 % (玉米 )和 - 0 .6 % (高粱 ) .该模型在进行产量预测、掌握作物生长动态 。

The ALMANAC model was validated in a drought stressed year and in a period from 1989 to 1998 at different sites of Texas to evaluate its ability in simulating maize and sorghum yields at different spatial scales and to extend its application range. There were 11 sites for maize and 8 sites for sorghum in plot size simulations, and 9 counties for maize and sorghum in county level simulations. The model showed similar accuracy in simulating both plot size and county level mean grain yields. It could also simulate single year yields under water limited climatic conditions for several sites and mean county yields of maize and sorghum, and had small CV values of mean yields for a long term prediction. The mean error was 8.9% for sorghum and 9.4% for maize in field scale simulations, and was only 2.6% for maize and 0.6% for sorghum in county level mean yield simulations.Crop models often require extensive input data sets to realistically simulate crop growth. The development of such input data sets is difficult for some model users. The soil, weather, and crop parameter data sets developed in this study could be used as the guidelines for model applications in similar climatic regions and on similar soils.