Measuring the Soil Water Content Profile of a Sandy Soil with an Off-Ground Monostatic Ground Penetrating Radar

2004 ◽  
Vol 3 (4) ◽  
pp. 1063-1071 ◽  
Author(s):  
S. Lambot ◽  
J. Rhebergen ◽  
I. van den Bosch ◽  
E. C. Slob ◽  
M. Vanclooster
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Sandy Soil ◽  
Ground Penetrating Radar ◽  
Ground Penetrating

Measuring the Soil Water Content Profile of a Sandy Soil with an Off-Ground Monostatic Ground Penetrating Radar

2004 ◽  
Vol 3 (4) ◽  
pp. 1063-1071 ◽  
Author(s):  
S. Lambot ◽  
J. Rhebergen ◽  
I. van den Bosch ◽  
E. C. Slob ◽  
M. Vanclooster
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Sandy Soil ◽  
Ground Penetrating Radar ◽  
Ground Penetrating

Coupling of dielectric mixing models with full-wave ground-penetrating radar signal inversion for sandy-soil-moisture estimation

Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. H33-H44 ◽  
Author(s):  
Anh Phuong Tran ◽  
Mohammad Reza Mahmoudzadeh Ardekani ◽  
Sébastien Lambot
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Sandy Soil ◽  
Ground Penetrating Radar ◽  
Mixing Models ◽  
Apparent Conductivity ◽  
Full Wave ◽  
Ground Penetrating

We coupled dielectric mixing models with a full-wave ground-penetrating-radar (GPR) model to estimate the soil water content by inversion. Two mixing models were taken into account in this study, namely, a power law model and the Wang and Schmugge model. With this combination, we could account for the frequency dependence of the dielectric permittivity and apparent conductivity in the inverse algorithm and directly estimate the soil water content without using an empirical petrophysical formula or a priori knowledge on soil porosity. The approach was validated by a series of experiments with sandy soil in controlled laboratory conditions. The results showed that the performance of our approach is better than the common approach, which assumes a linear dependence of apparent conductivity on frequency and uses Topp’s equation to transform permittivity to water content. GPR data were perfectly reproduced in the time and frequency domains, leading to very accurate water-content estimates with an average absolute error of less than [Formula: see text]. However, the accuracy was reduced as the water content increased. Sensitivity analysis indicated that the Green’s function was most sensitive to the water content and sand-layer thickness but much less so with DC conductivity. The results also revealed that as the frequency increased, although the permittivity was nearly constant, the apparent electrical conductivity and the attenuation increased remarkably, especially for wet sands due to dielectric losses. The successful validation of the proposed approach opens a promising avenue of development to use dielectric mixing models for soil-moisture mapping from GPR measurements.

scholarly journals Soil water content estimation using ground penetrating radar data via group intelligence optimization algorithms: An application in the Northern Shaanxi Coal Mining Area

2020 ◽  
pp. 014459872097336
Author(s):  
Fan Cui ◽  
Jianyu Ni ◽  
Yunfei Du ◽  
Yuxuan Zhao ◽  
Yingqing Zhou
Keyword(s):  
Dielectric Constant ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Error Rate ◽  
Ground Penetrating Radar ◽  
Volumetric Water Content ◽  
Average Error ◽  
Average Error Rate ◽  
Ground Penetrating

The determination of quantitative relationship between soil dielectric constant and water content is an important basis for measuring soil water content based on ground penetrating radar (GPR) technology. The calculation of soil volumetric water content using GPR technology is usually based on the classic Topp formula. However, there are large errors between measured values and calculated values when using the formula, and it cannot be flexibly applied to different media. To solve these problems, first, a combination of GPR and shallow drilling is used to calibrate the wave velocity to obtain an accurate dielectric constant. Then, combined with experimental moisture content, the intelligent group algorithm is applied to accurately build mathematical models of the relative dielectric constant and volumetric water content, and the Topp formula is revised for sand and clay media. Compared with the classic Topp formula, the average error rate of sand is decreased by nearly 15.8%, the average error rate of clay is decreased by 31.75%. The calculation accuracy of the formula has been greatly improved. It proves that the revised model is accurate, and at the same time, it proves the rationality of the method of using GPR wave velocity calibration method to accurately calculate the volumetric water content.

scholarly journals Application of Ground-Penetrating Radar and a Combined Penetrometer–Moisture Probe for Evaluating Spatial Distribution of Soil Moisture and Soil Hardness in Coastal and Inland Windbreaks

Geosciences ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 238
Author(s):  
Kenta Iwasaki ◽  
Makoto Tamura ◽  
Hirokazu Sato ◽  
Kazuhiko Masaka ◽  
Daisuke Oka ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Ground Penetrating Radar ◽  
Soil Compaction ◽  
Soil Moisture Condition ◽  
Soil Hardness ◽  
Ground Penetrating

The development of a method to easily investigate the spatial distribution of soil moisture and soil hardness in tree windbreaks is necessary because these windbreaks often decline due to inappropriate soil moisture condition and soil compaction. This research examined the applicability of ground-penetrating radar (GPR) and a combined penetrometer–moisture probe (CPMP) for evaluating the spatial distribution of soil moisture and soil hardness in four windbreaks with different soil characteristics. A GPR-reflecting interface was observed at a less permeable layer in a coastal windbreak and at a depth affected by soil compaction in an inland windbreak with andosol. The spatial distribution of the groundwater table could also be evaluated by examining the attenuation of GPR reflection in a coastal windbreak. In contrast, GPR was not applicable in an inland windbreak with peat because of high soil water content near the soil surface. The CPMP could detect vertical distributions of soil hardness and soil water content regardless of soil type. The CPMP was useful for interpreting GPR profiles, and GPR was useful for interpolating the information about the horizontal distribution of soil moisture and soil hardness between survey points made with the CPMP. Thus, the combination of GPR and a CPMP is ideal for examining the two-dimensional spatial distribution of soil moisture and soil hardness at windbreaks with soils for which both methods are applicable.

Continuous and simultaneous measurement of reflector depth and average soil-water content with multichannel ground-penetrating radar

Geophysics ◽  
2008 ◽  
Vol 73 (4) ◽  
pp. J15-J23 ◽  
Author(s):  
Holger Gerhards ◽  
Ute Wollschläger ◽  
Qihao Yu ◽  
Philip Schiwek ◽  
Xicai Pan ◽  
...  
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Ground Penetrating Radar ◽  
Synthetic Data ◽  
Evaluation Procedure ◽  
Noninvasive Technique ◽  
Data Set ◽  
Large Variability ◽  
Ground Penetrating

Ground-penetrating radar is a fast noninvasive technique that can monitor subsurface structure and water-content distribution. To interpret traveltime information from single common-offset measurements, additional assumptions, such as constant permittivity, usually are required. We present a fast ground-penetrating-radar measurement technique using a multiple transmitter-and-receiver setup to measure simultaneously the reflector depth and average soil-water content. It can be considered a moving minicommon-midpoint measurement. For a simple analysis, we use a straightforward evaluation procedure that includes two traveltimes to the same reflector, obtained from different antenna separations. For a more accurate approach, an inverse evaluation procedure is added, using traveltimes obtained from all antenna separations at one position and its neighboring measurement locations. The evaluation of a synthetic data set with a lateral variability in reflector depth and an experimental example with a large variability in soil-water content are introduced to demonstrate the applicability for field-scale measurements. The crucial point for this application is the access to absolute traveltimes, which are difficult to determine accurately from common-offset measurements.

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