Abstract Current crop models usually need a lot of input information to simulate crop leaf area index and have relatively large simulation errors under soil water stress, which need to be improved. In this study, based on experiments conducted in glass soil columns and field under rainout shelters in four years (2012-2016) in Yangling, Shaanxi Province in China, we attempted to establish a dynamic model for simulating leaf expansion and senescence of winter wheat under soil water stress. First, a temperature response function was established with four cardinal temperatures (base temperature, lower optimum temperature, higher optimum temperature, and maximum temperature). Then two soil water stress functions were established to quantify the effect of soil water stress on the processes of leaf expansion and leaf senescence of main stem per plant. The first order derivative of a logistic function was then modified with the temperature and soil water stress response function and was used to simulate the daily rate of leaf area expansion and senescence of main stem. The parameters of the new model were estimated using the Solver add-in in MS Excel and then validated based on the data of soil column experiments in 2014-2015 growing season. Then the new model was evaluated with another dataset of column experiments conducted in 2015-2016. Furthermore, the influence of soil water stress on wheat tillering was included in the new model based on open field experiments in 2012-2013 growing season. Then, the new leaf area index (LAI) simulation model was further verified with the data of open field experiments under rainout shelter (2013-2014) and rainfed condition (2004-2005, 2005-2006, and 2008-2009) in different sites. A comparison was conducted between new LAI model and the original LAI module of CERES-Wheat. The results showed that the leaf expansion rate was not affected when the relative soil water availability was greater than 0.7; water stress inhibited the leaf expansion when relative soil water availability was between 0.2 and 0.7; leaves withered and yellowed when relative soil water availability was less than 0.2. The overall average root mean square error (RMSE) and residual accumulation coefficient (CRM) were 9.78 cm2 plant−1, -0.03, and 6.51 cm2 plant−1; 0.05 for model calibration and validation, respectively. The RMSE of LAI decreased by an average of 47.89% compared with the original LAI module of CERES-Wheat. The results of this study can help to improve the current CERES-Wheat model for model applications in the arid and semi-arid regions of China.

中文翻译：

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土壤水分胁迫对冬小麦叶片膨胀和衰老影响的模拟

摘要 目前的作物模型在模拟作物叶面积指数时通常需要大量输入信息，在土壤水分胁迫下模拟误差较大，有待改进。本研究基于陕西省杨凌市四年（2012-2016）玻璃土柱和雨棚条件下的大田试验，尝试建立模拟冬小麦叶片膨胀和衰老的动力学模型。土壤水分胁迫。首先，建立了具有四个基本温度（基础温度、较低最适温度、较高最适温度和最高温度）的温度响应函数。然后建立两个土壤水分胁迫函数，量化土壤水分胁迫对单株主茎叶片扩张和叶片衰老过程的影响。然后用温度和土壤水分胁迫响应函数修改逻辑函数的一阶导数，并用于模拟主茎叶面积扩大和衰老的日速率。使用MS Excel中的Solver插件估计新模型的参数，然后根据2014-2015生长季节的土柱实验数据进行验证。然后使用 2015-2016 年进行的另一个柱实验数据集对新模型进行了评估。此外，基于2012-2013生长季的露地试验，新模型包含了土壤水分胁迫对小麦分蘖的影响。然后，利用雨棚（2013-2014）和雨养条件（2004-2005、2005-2006、和 2008-2009）在不同的站点。对新的 LAI 模型与 CERES-Wheat 的原始 LAI 模块进行了比较。结果表明，当土壤相对水分有效性大于0.7时，叶片膨胀率不受影响；当相对土壤水分有效性在0.2~0.7之间时，水分胁迫抑制叶片膨胀；当相对土壤水分利用率小于 0.2 时，叶片枯黄变黄。总体平均均方根误差 (RMSE) 和残留累积系数 (CRM) 分别为 9.78 cm2 植物-1、-0.03 和 6.51 cm2 植物-1；0.05 分别用于模型校准和验证。LAI 的 RMSE 与 CERES-Wheat 的原始 LAI 模块相比平均降低了 47.89%。