基于水动力规律的约束探地雷达数据反演无创土壤水电特性测定

S. Lambot, S. Guillaso, H. Vereecken, E. Slob
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引用次数: 0

摘要

我们利用水动力学建模对延时雷达数据进行全波反演,以同时识别浅层地下水力特性和连续垂直电剖面。雷达数据在频域使用矢量网络分析仪和离地单站天线进行采集。这样可以精确地过滤天线效应,并推导出格林函数,由此开始反演。为了证明雷达数据中包含了足够的信息,以确保估算的唯一性,我们对粗、中、细三种不同质地的土壤进行了水动力事件模拟。随后,对相应的时移雷达数据进行计算和反演,得到Mualem-van Genuchten模型中的关键土壤水力参数,即¿、n和Ks。对于所考虑的三种情况,三个水力参数被准确地检索出来,因此,相应的随时间变化的电气曲线也被检索出来。如果已知土壤含水量及其电性与水动力初始条件和边界条件之间的土壤特异性关系,则该方法有望在现场尺度上进行浅层地下水力特性的近距离测绘和水动力的监测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constraining GPR data inversion using hydrodynamic laws for noninvasive soil hydraulic and electric property determination
We constrain full-wave inversion of time-lapse radar data using hydrodynamic modeling to simultaneously identify the shallow subsurface hydraulic properties and continuous vertical electric profiles. Radar data are acquired in the frequency domain using a vector network analyzer combined with an off-ground monostatic antenna. This permits to accurately filter antenna effects and to derive Green functions from which the inversion is initiated. In order to demonstrate that enough information is contained in the radar data so as to ensure unique estimates, hydrodynamic events were simulated for three different textured soils, namely, coarse, medium, and fine. The corresponding time-lapse radar data were subsequently computed and inverted to find back key soil hydraulic parameters, i.e., ¿, n, and Ks in Mualem-van Genuchten's model. For the three scenarios considered, the three hydraulic parameters were exactly retrieved, and hence, the corresponding time-dependent electric profiles as well. Provided that the soil-specific relations between the soil water content and its electric properties and the hydrodynamic initial and boundary conditions are known, the proposed method appears to be promising for proximal mapping of the shallow subsurface hydraulic properties and monitoring of the water dynamics at the field scale.
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