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首页> 外文期刊>Vadose zone journal VZJ >Modeling Soil-Plant Dynamics: Assessing Simulation Accuracy by Comparison with Spatially Distributed Crop Yield Measurements
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Modeling Soil-Plant Dynamics: Assessing Simulation Accuracy by Comparison with Spatially Distributed Crop Yield Measurements

机译:对土壤植物动力学建模:通过与空间分布的农作物产量测量值进行比较来评估模拟精度

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摘要

Coupling hydrological models with plant physiology is crucial to capture the feedback mechanisms occurring within the soil-plant-atmosphere continuum. However, the ability of such models to describe the spatial variability of plant responses to different environmental factors remains to be proven, especially at large scales (field or watershed). We used an innovative three-dimensional soil-plant model to quantify temporal and spatial variability of crop productivity at the field scale, and we assessed simulation accuracy by comparison with spatially distributed crop yield measurements. A 25-ha field located in the Venice coastland, Italy, cultivated with a maize (Zea mays L.) crop and characterized by a highly heterogeneous soil subject to salt contamination, has been extensively studied by soil sampling, geophysical surveys, and hydrological monitoring. Based on these observations, field-scale simulations of soil moisture dynamics coupled with plant transpiration, photosynthesis, and growth were run and compared with crop yield maps of different growing seasons. The model captured the observed crop productivity (grain yield varying between 2 and 15 Mg ha(-1)), but the accuracy of the predicted spatial patterns was limited by the available information on soil heterogeneities. Further model uncertainties are related to the characterization of the rooting systems and their responses to environmental factors (soil characteristics, precipitation) that were shown to be crucial to describe the effect of drought conditions on growth processes. These results demonstrate that large-scale mechanistic simulations of soil-plant systems require a trade-off between site characterization, model processes, and computational efficiency, offering an open challenge for future ecohydrological research.
机译:水文模型与植物生理学的耦合对于捕获土壤-植物-大气连续体内发生的反馈机制至关重要。但是,这种模型描述植物对不同环境因素的空间变异性的能力仍有待证明,特别是在大规模(田间或流域)的情况下。我们使用了创新的三维土壤植物模型来量化田间尺度上作物生产力的时间和空间变异性,并且我们通过与空间分布的作物产量测量结果进行比较来评估模拟准确性。位于意大利威尼斯海岸的25公顷田地以玉米(Zea mays L.)作物种植,其特征是土壤高度异质易受盐污染,已通过土壤采样,地球物理调查和水文监测进行了广泛研究。基于这些观察结果,进行了土壤水分动力学以及植物蒸腾,光合作用和生长的田间规模模拟,并与不同生长季节的作物产量图进行了比较。该模型捕获了观察到的农作物生产力(粮食产量在2至15 Mg ha(-1)之间变化),但是预测的空间格局的准确性受到土壤异质性可用信息的限制。进一步的模型不确定性与生根系统的特征及其对环境因素(土壤特征,降水)的响应有关,这些因素对于描述干旱条件对生长过程的影响至关重要。这些结果表明,土壤-植物系统的大规模机械模拟需要在站点表征,模型过程和计算效率之间进行权衡,这为未来的生态水文学研究提供了开放的挑战。

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