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首页> 外文期刊>Field Crops Research >Assessing crop management options with crop simulation models based on generated weather data.
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Assessing crop management options with crop simulation models based on generated weather data.

机译：根据生成的天气数据，使用作物模拟模型评估作物管理选项。

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The efficient use of crop simulation models is an effective complement to experimental research. Long-term weather data obtained at a specific site are normally required for the application of these crop simulation models to help determine alternate management practices and associated decisions. Stochastic weather generators sometimes are used to complement or substitute historical weather data. The objective of this study was to evaluate the suitability of weather data generated by the weather generators WGEN and SIMMETEO as input for crop simulation models in order to determine the best option(s) among a number of different crop management practices. Five locations across Iran representing different climates were selected. The wheat, maize, and soybean models of the Decision Support System for Agrotechnology Transfer (DSSAT) were applied in this study, using 30 years of observed weather data and 90 years of weather data generated by WGEN and SIMMETEO. Simulated grain yield using either observed weather data or weather data generated by WGEN and SIMMETEO in response to various 'experimental' factors, e.g., cultivar selection, planting date, planting density, irrigation threshold, and change in precipitation under irrigated and rainfed conditions were compared. The statistical evaluation was based on t, F, and Kolomogrov-Smirnov (K-S) tests. The average of the percentage rejected tests was 20% and the parameter estimation method had no impact on the number of rejected tests. Irrespective of some significant differences between simulated yield based on observed weather data and those based on weather data generated by WGEN and SIMMETEO, a similar conclusion could be drawn about the best cultivar, planting date, plant density and irrigation threshold and response to changes in the amount of precipitation. Based on the results of this study it can be concluded that for many crop model applications where only relative estimates or determination of the best management option(s) rather than absolute values are required, weather data generated by either WGEN and SIMMETEO are accurate and sufficient.
机译：作物模拟模型的有效利用是对实验研究的有效补充。这些作物模拟模型的应用通常需要在特定地点获得的长期天气数据，以帮助确定替代管理方法和相关决策。随机天气生成器有时用于补充或替代历史天气数据。这项研究的目的是评估由天气生成器WGEN和SIMMETEO生成的天气数据作为作物模拟模型的输入的适用性，以便确定许多不同作物管理实践中的最佳选择。选择了伊朗各地代表不同气候的五个地点。本研究应用了农业技术转移决策支持系统（DSSAT）的小麦，玉米和大豆模型，使用了30年的观测天气数据和WGEN和SIMMETEO生成的90年天气数据。使用观察到的天气数据或WGEN和SIMMETEO响应各种“实验”因素（例如品种选择，种植日期，种植密度，灌溉阈值以及灌溉和雨养条件下的降水变化）而模拟的粮食产量进行了比较。统计评估基于t，F和Kolomogrov-Smirnov（K-S）检验。拒绝测试的百分比平均值为20％，参数估计方法对拒绝测试的数量没有影响。不管基于观测天气数据的模拟产量与基于WGEN和SIMMETEO生成的天气数据的模拟产量之间存在显着差异，都可以得出类似的结论，即最佳品种，播种日期，植物密度和灌溉阈值以及对作物变化的响应降水量。根据这项研究的结果，可以得出结论，对于仅需要相对估计或确定最佳管理方案（而不是绝对值）的许多作物模型应用，WGEN和SIMMETEO生成的天气数据都是准确而充分的。

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