Baldoncini Marica, Albéri Matteo, Bottardi Carlo, Chiarelli Enrico, Raptis Kassandra Giulia Cristina, Strati Virginia, Mantovani Fabio
INFN, Legnaro National Laboratories, Viale dell'Università 2, 35020, Legnaro, Padua, Italy; Department of Physics and Earth Sciences, University of Ferrara, Via Saragat 1, 44121, Ferrara, Italy.
INFN, Legnaro National Laboratories, Viale dell'Università 2, 35020, Legnaro, Padua, Italy; Department of Physics and Earth Sciences, University of Ferrara, Via Saragat 1, 44121, Ferrara, Italy.
J Environ Radioact. 2018 Dec;192:105-116. doi: 10.1016/j.jenvrad.2018.06.001. Epub 2018 Jun 15.
Proximal gamma-ray spectroscopy recently emerged as a promising technique for non-stop monitoring of soil water content with possible applications in the field of precision farming. The potentialities of the method are investigated by means of Monte Carlo simulations applied to the reconstruction of gamma-ray spectra collected by a NaI scintillation detector permanently installed at an agricultural experimental site. A two steps simulation strategy based on a geometrical translational invariance is developed. The strengths of this approach are the reduction of computational time with respect to a direct source-detector simulation, the reconstruction of K, Th and U fundamental spectra, the customization in relation to different experimental scenarios and the investigation of effects due to individual variables for sensitivity studies. The reliability of the simulation is effectively validated against an experimental measurement with known soil water content and radionuclides abundances. The relation between soil water content and gamma signal is theoretically derived and applied to a Monte Carlo synthetic calibration performed with the specific soil composition of the experimental site. Ready to use general formulae and simulated coefficients for the estimation of soil water content are also provided adopting standard soil compositions. Linear regressions between input and output soil water contents, inferred from simulated K and Tl gamma signals, provide excellent results demonstrating the capability of the proposed method in estimating soil water content with an average uncertainty <1%.
近地伽马射线光谱学最近成为一种很有前景的技术，可用于不间断监测土壤含水量，并可能在精准农业领域得到应用。通过蒙特卡罗模拟来研究该方法的潜力，这些模拟应用于重建由永久安装在一个农业试验场的碘化钠闪烁探测器收集的伽马射线光谱。开发了一种基于几何平移不变性的两步模拟策略。这种方法的优点是相对于直接的源 - 探测器模拟减少了计算时间，重建了钾、钍和铀的基本光谱，针对不同实验场景进行定制，以及研究各个变量对灵敏度研究的影响。通过与已知土壤含水量和放射性核素丰度的实验测量结果进行有效验证，证实了模拟的可靠性。从理论上推导了土壤含水量与伽马信号之间的关系，并将其应用于针对试验场特定土壤成分进行的蒙特卡罗合成校准。还采用标准土壤成分提供了用于估计土壤含水量的现成通用公式和模拟系数。从模拟的钾和铊伽马信号推断出的输入和输出土壤含水量之间的线性回归提供了出色的结果，证明了所提出方法在估计土壤含水量方面的能力，平均不确定性<1%。
