Soil hydraulic material properties and layered architecture from time-lapse GPR
Soil hydraulic material properties and layered architecture from time-lapse GPR
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DOI：
10.5194/hess-22-2551-2018
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发表时间：
2018-04
影响因子：
6.3
通讯作者：
S. Jaumann;K. Roth
中科院分区：
文献类型：
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作者：
S. Jaumann;K. Roth
抽象。地下物质分布及其有效土壤水力物质特性的定量知识是预测土壤水分运动的必要条件。探地雷达（GPR）是一种非侵入、无损的地球物理测量方法，适用于监测水力过程。以往的研究表明，地下水位波动时的探地雷达信号对土壤水分特征和导水率函数敏感。在这项工作中，我们表明，来自地下建筑和地下水位波动的GPR信号是合适的，以估计层的位置内的地下建筑连同相关的有效土壤水力材料的性质与反演方法。为此，我们参数化的地下结构，解决理查兹方程，转换所得的水含量与复折射率模型（CRIM）的相对介电常数，并解决麦克斯韦方程数值。为了分析探地雷达信号，我们实现了一种新的启发式算法，检测雷达图（事件）中的相关信号，并提取相应的信号传播时间和幅度。该算法适用于模拟以及测量雷达图和检测到的事件自动关联。使用同相轴而不是全波使聚焦于相关测量信号的反演规则化。对于优化，我们使用一个全局-局部的方法与预处理。从拉丁超立方体算法绘制的初始参数集的合奏开始，我们依次耦合模拟退火算法与Levenberg-Marquardt算法。该方法适用于合成以及测量数据从ASSESS测试网站。我们表明，该方法产生合理的估计层的位置，以及土壤水力材料的性能，通过比较结果来自地面实况数据，以及从时域反射仪（TDR）的参考。
Abstract. Quantitative knowledge of the subsurface material distribution and its effective soil hydraulic material properties is essential to predict soil water movement. Ground-penetrating radar (GPR) is a noninvasive and nondestructive geophysical measurement method that is suitable to monitor hydraulic processes. Previous studies showed that the GPR signal from a fluctuating groundwater table is sensitive to the soil water characteristic and the hydraulic conductivity function. In this work, we show that the GPR signal originating from both the subsurface architecture and the fluctuating groundwater table is suitable to estimate the position of layers within the subsurface architecture together with the associated effective soil hydraulic material properties with inversion methods. To that end, we parameterize the subsurface architecture, solve the Richards equation, convert the resulting water content to relative permittivity with the complex refractive index model (CRIM), and solve Maxwell's equations numerically. In order to analyze the GPR signal, we implemented a new heuristic algorithm that detects relevant signals in the radargram (events) and extracts the corresponding signal travel time and amplitude. This algorithm is applied to simulated as well as measured radargrams and the detected events are associated automatically. Using events instead of the full wave regularizes the inversion focussing on the relevant measurement signal. For optimization, we use a global–local approach with preconditioning. Starting from an ensemble of initial parameter sets drawn with a Latin hypercube algorithm, we sequentially couple a simulated annealing algorithm with a Levenberg–Marquardt algorithm. The method is applied to synthetic as well as measured data from the ASSESS test site. We show that the method yields reasonable estimates for the position of the layers as well as for the soil hydraulic material properties by comparing the results to references derived from ground truth data as well as from time domain reflectometry (TDR).