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Combining a weather generator and a standard sensitivity analysis method to quantify the relevance of weather variables on agrometeorological models outputs

机译:结合天气生成器和标准敏感性分析方法,以量化天气变量与农业气象模型输出的相关性

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摘要

Sensitivity analysis (SA) is increasingly used to explain models behaviour in response to inputs variation. Agrometeorologists are used to apply standard SA methods only on model parameters because of the difficulty of applying standard sampling techniques to derive series of weather data where each value cannot be sampled independently from those of the neighbouring days and from other variables in the same day. The impact of weather variability on a crop model was here analysed by coupling the Morris SA method to a weather generator. Spring barley in northern Italy was simulated and different outputs considered. Under the explored conditions, parameters involved with temperature generation resulted the most relevant in determining yield and maturity date. Radiation-related parameters were high-ranked for cumulated drainage and actual evapotranspiration. According to the author, this is the first time the sensitivity of a cropping system model to weather variables is quantified using standard SA techniques.
机译:灵敏度分析(SA)越来越多地用于解释模型响应输入变化的行为。农业气象学家只能将标准的SA方法应用于模型参数,因为难以应用标准的采样技术来导出一系列天气数据,在这些天气数据中,每个值都不能独立于相邻日期的数据和同一天的其他变量进行采样。通过将Morris SA方法与天气发生器耦合,分析了天气变化对作物模型的影响。模拟了意大利北部的春季大麦,并考虑了不同的产量。在探索的条件下,与温度产生有关的参数与确定产量和到期日期最相关。与辐射有关的参数在累积排水量和实际蒸散量方面排名较高。根据作者的说法,这是第一次使用标准的SA技术来量化种植系统模型对天气变量的敏感性。

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