番茄田土壤水分模拟：近源gamma ray spectroscopy和土壤-作物系统模型
Modelling soil water conent in a tomato field: proximal gamma ray spectroscopy and soil-crop system models
摘要：
近端土壤传感器在理解精准农业中涉及的土壤水文地质过程中发挥着重要作用。在这方面，永久安装的伽马射线能谱台站是实地规模的最佳时空权衡方法之一。通过对番茄试验田地面γ辐射连续7个月的采集，验证了土壤含水量监测的可行性和可靠性。通过使用放置在2.25 m高度的1 L碘化钠检测器，我们研究了来自半径约25 m且深度约30 cm的区域的伽马信号。实验值，推断后的校准测量和校正的存在下的生物量，证实了在不同的土壤水分条件下获得的重量数据，给出了约2%的平均绝对差异。与AquaCrop，CRITeRIA和IRRINET土壤-作物系统模型模拟的数据进行了定量比较。不同的拟合优度在裸露的土壤条件下，在植被期突出显示，CRITeRIA显示最好的协议与实验数据在整个数据采集期间，而在番茄作物的存在下，IRRINET提供了最好的结果。
英文摘要：
Proximal soil sensors are taking hold in the understanding of soil hydrogeological processes involved in precision agriculture. In this context, permanently installed gamma ray spectroscopy stations represent one of the best space-time trade off methods at field scale. This study proved the feasibility and reliability of soil water content monitoring through a seven-month continuous acquisition of terrestrial gamma radiation in a tomato test field. By employing a 1 L sodium iodide detector placed at a height of 2.25 m, we investigated the gamma signal coming from an area having a ~25 m radius and from a depth of approximately 30 cm. Experimental values, inferred after a calibration measurement and corrected for the presence of biomass, were corroborated with gravimetric data acquired under different soil moisture conditions, giving an average absolute discrepancy of about 2%. A quantitative comparison was carried out with data simulated by AquaCrop, CRITeRIA, and IRRINET soil-crop system models. The different goodness of fit obtained in bare soil condition and during the vegetated period highlighted that CRITeRIA showed the best agreement with the experimental data over the entire data-taking period while, in presence of the tomato crop, IRRINET provided the best results.
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