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首页> 外文期刊>Ecological Modelling >Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments
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Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments

机译：不同灌溉方式下动态农业生态系统模型的全局敏感性和不确定性分析

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Savings in consumptive use through limited or deficit irrigation in agriculture has become an increasingly viable source of additional water for places with high population growth such as the Colorado Front Range, USA. Crop models provide a mechanism to evaluate various management methods without performing costly and time-consuming experiments, e.g., field studies investigating irrigation scheduling and timing effects on crop growth. Few studies have focused on CERES-Maize crop model parameterization with respect to water-stressed conditions, and the model has previously been shown to overestimate evapotranspiration (ET) for limited irrigation treatments (stress during vegetative stage). It is therefore desirable to quantify the effects of CERES-Maize input parameters on model output responses typically used for calibration and/or important in limited irrigation management, including vegetative growth, crop yield, and ET. A sensitivity analysis (SA) utilizing the Morris one-at-a-time screening and Sobol' variance-based methods was performed on CERES-Maize v4.5 input parameters affecting water balance and crop growth including soil hydraulic properties, phenological growth properties, and radiation use efficiency. CERES-Maize output responses of interest for the SA included anthesis date, maturity date, leaf number per stem, maximum leaf area index, yield, and cumulative ET. The SA study utilized five years of multi-replicate field management data (both full and limited irrigation treatments) for each combination of random input parameters. Results comparing the Morris mean and the Sobol' total sensitivity index showed very high correlation between the two, indicating that in this study the computationally cheaper Morris method could have been used as an effective indicator of input parameter sensitivity. For the full irrigation treatment, CERES-Maize output responses were mostly sensitive to crop cultivar parameters. For the limited irrigation treatment, CERES-Maize leaf area index, yield, and ET output responses were highly influenced by soil lower limit and drained upper limit input parameters, which define water holding capacity. There was also a greater amount of interaction between input parameters for the limited irrigation treatment than for full irrigation. An uncertainty analysis was also conducted using model outputs from the Sobol' SA method. In some cases, cumulative ET had higher values for limited irrigation than for full irrigation, further indicating the need to evaluate model processes governing ET under water stress. A new methodology for systematic calibration of CERES-Maize, based on the Morris and Sobol' sensitivity indices for the two irrigation treatments, is proposed for future model evaluation as sensitivity differences between treatments indicates that existing CERES-Maize calibration procedures (typically based on non-stressed crops) may need to be reconsidered in cases of water stress.
机译：在农业人口有限或短缺的情况下，通过节水或节水灌溉来节约用水已成为增加人口增长的水源的可行途径，例如美国科罗拉多州前山区。作物模型提供了一种评估各种管理方法的机制，而无需执行昂贵且耗时的实验，例如，实地研究调查灌溉计划和时间安排对作物生长的影响。很少有研究着眼于水分胁迫条件下的CERES-玉米作物模型参数化，并且先前已证明该模型过高估计了有限灌溉处理（植物生长阶段的胁迫）的蒸散量（ET）。因此，需要量化CERES-玉米输入参数对模型输出响应的影响，该响应通常用于校准和/或在有限的灌溉管理中很重要，包括营养生长，作物产量和ET。在CERES-Maize v4.5输入参数上影响水平衡和作物生长的参数（包括土壤水力特性，物候生长特性，和辐射利用效率。 CERES-SA对玉米感兴趣的输出响应包括花期，成熟日期，每茎叶数，最大叶面积指数，产量和累积ET。 SA研究对随机输入参数的每种组合使用了五年的多次重复田间管理数据（完全和有限灌溉处理）。将莫里斯平均值和Sobol总灵敏度指数进行比较的结果表明，两者之间具有很高的相关性，这表明在这项研究中，计算上更便宜的莫里斯方法可以用作输入参数灵敏度的有效指标。对于完全灌溉处理，CERES-玉米的产量响应对作物品种参数最为敏感。在有限的灌溉条件下，土壤下限和排水上限输入参数极大地影响了CERES-玉米叶面积指数，产量和ET的产量响应，这些参数定义了持水量。与完全灌溉相比，有限灌溉处理的输入参数之间也存在更大的交互作用。还使用Sobol'SA方法的模型输出进行了不确定性分析。在某些情况下，有限灌溉下的累积ET值要高于完全灌溉下的值，这进一步表明需要评估在水分胁迫下控制ET的模型过程。提出了一种基于两种灌溉处理的莫里斯和索博尔敏感性指数的系统校准CERES-玉米的新方法，用于未来的模型评估，因为处理之间的敏感性差异表明现有的CERES-玉米校准程序（通常基于非干旱的情况下，可能需要重新考虑）。

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