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Soil surface water content estimation by full-waveform GPR signal inversion in the presence of thin layers

机译:薄层存在下全波形GPR信号反演估算地表水含量

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摘要

We analyzed the effect of shallow thin layers on the estimation of soil surface water content using full-waveform inversion of off-ground ground penetrating radar (GPR) data. Strong dielectric contrasts are expected to occur under fast wetting or drying weather conditions, thereby leading to constructive and destructive interferences with respect to the surface reflection. First, synthetic GPR data were generated and subsequently inverted considering different thin-layer model configurations. The resulting inversion errors when neglecting the thin layer were quantified, and then, the possibility to reconstruct these layers was investigated. Second, laboratory experiments reproducing some of the numerical experiments configurations were conducted to assess the stability of the inverse solution with respect to actual measurement and modeling errors. Results showed that neglecting shallow thin layers may lead to significant errors on the estimation of soil surface water content ($\Delta\theta$ > 0.03 $m^3/m^3$), depending on the contrast. Accounting for these layers in the inversion process strongly improved the results, although some optimization issues were encountered. In the laboratory, the proposed full-waveform method permitted to reconstruct thin layers with a high resolution up to 2 cm and to retrieve the soil surface water content with an rmse less than 0.02 $m^3/m^3$, owing to the full-waveform inverse modeling. These results suggest that the proposed GPR approach is promising for field-scale mapping of soil surface water content of nondispersive soils with low electrical conductivity and for instances when soil layering is encountered.
机译:我们使用离地穿透雷达(GPR)数据的全波形反演分析了浅薄薄层对土壤表面含水量估计的影响。在快速湿润或干燥的天气条件下,预计会发生强介电对比,从而导致相对于表面反射的相长和相消干涉。首先,生成合成的GPR数据,然后考虑不同的薄层模型配置对其进行倒置。量化了忽略薄层时产生的反演误差,然后研究了重建这些层的可能性。其次,进行了复制某些数值实验配置的实验室实验,以评估反解相对于实际测量和建模误差的稳定性。结果表明,忽略浅薄层可能会导致土壤表面含水量估算的重大误差($ \ Delta \ theta $> 0.03 $ m ^ 3 / m ^ 3 $),具体取决于对比度。尽管遇到了一些优化问题,但在反演过程中考虑这些层会大大改善结果。在实验室中,所提出的全波形方法允许重建高达2 cm的高分辨率薄层,并以rmse小于0.02 $ m ^ 3 / m ^ 3 $的均方根值恢复土壤表面含水量。全波形逆建模。这些结果表明,所提出的GPR方法有望用于田间规模的低电导率非分散性土壤的土壤表层含水量测绘,例如在遇到土壤分层时。

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