17:15 〜 19:15
[AGE34-P14] Non-Destructive and Non-Invasive Measurement of Infiltration Zones by Ground-Penetrating Radar
キーワード：地中レーダ、土中水分、浸潤、可視化
1. Introduction
Measuring soil water content and its distribution non-destructively and non-invasively is important for optimizing irrigation and/or disaster prevention, such as slope failure.
This study examines the effectiveness of surface ground-penetrating radar (GPR) for a non-destructive and non-invasive measurement of a wet volume during infiltration.
2. Material and Methods
2.1 Experimental areas
This study was conducted at Tokyo University of Agriculture and Technology and Arid Land Research Center, Tottori University with four different soil types: an indoor soil layer uniformly filled with river sand; an indoor soil layer uniformly filled with weathered decomposed granite soil; a field with Tottori dune sand; and an experimental field consists of Andosol.
2.2 Method
An infiltration test was conducted using a cylindrical tube as 1500 ml of water was injected for every experiment. During the infiltration test, the GPR was fixed around the cylinder, and time-lapse measurements were taken every second to monitor the movement of the infiltration front.
GPR was also used to perform grid measurements with a total of 54 cm×40cm transect at 2 cm intervals. This measurement was taken both before and after the infiltration test. After the GPR measurements, the infiltration zone was excavated at 5 cm depth intervals to collect data for validation.
2.3 GPR data processing
The average velocity of the reflected waves was estimated based on hyperbola fitting, where a strong reflection from the bottom of the infiltration zone was observed. This assumption was verified by comparing time-lapse data. The estimated velocity was applied to post-infiltration test GPR data to convert the time axis to the depth axis. For traces outside the infiltration zone and pre-test data, the velocity estimated from CMP measurements was used for depth conversion. Data were plotted in three-dimensional space, with the x and y coordinates representing horizontal positions and the z coordinate representing depth. A three-dimensional dataset of pre- and post-infiltration amplitudes was created. A threshold was chosen following Di Prima et al. (2020), based on the amplitude difference value corresponding to 1.5 times the standard deviation. Amplitude differences exceeding the threshold were binarized as 1, while the remaining values were set to 0.
3. Results
Similar results were obtained for river sand, decomposed granite soil and Tottori dune sand. The infiltration zone was visualized in expanding regions but not in narrowing regions.
However, in Andosol, the estimated infiltration zone did not match the actual infiltration zone at any depth.
4. Discussion
This study demonstrates that GPR can be used to visualize wet volumes during infiltration for three sandy soils. For Andosol, discrepancies between estimated and actual infiltration zones may be attributed to the higher initial moisture content compared to the other three soil types. This likely led to an ambiguous dielectric permittivity boundary, causing a mismatch between the sampled infiltration boundary and the boundary estimated from GPR data.
Measuring soil water content and its distribution non-destructively and non-invasively is important for optimizing irrigation and/or disaster prevention, such as slope failure.
This study examines the effectiveness of surface ground-penetrating radar (GPR) for a non-destructive and non-invasive measurement of a wet volume during infiltration.
2. Material and Methods
2.1 Experimental areas
This study was conducted at Tokyo University of Agriculture and Technology and Arid Land Research Center, Tottori University with four different soil types: an indoor soil layer uniformly filled with river sand; an indoor soil layer uniformly filled with weathered decomposed granite soil; a field with Tottori dune sand; and an experimental field consists of Andosol.
2.2 Method
An infiltration test was conducted using a cylindrical tube as 1500 ml of water was injected for every experiment. During the infiltration test, the GPR was fixed around the cylinder, and time-lapse measurements were taken every second to monitor the movement of the infiltration front.
GPR was also used to perform grid measurements with a total of 54 cm×40cm transect at 2 cm intervals. This measurement was taken both before and after the infiltration test. After the GPR measurements, the infiltration zone was excavated at 5 cm depth intervals to collect data for validation.
2.3 GPR data processing
The average velocity of the reflected waves was estimated based on hyperbola fitting, where a strong reflection from the bottom of the infiltration zone was observed. This assumption was verified by comparing time-lapse data. The estimated velocity was applied to post-infiltration test GPR data to convert the time axis to the depth axis. For traces outside the infiltration zone and pre-test data, the velocity estimated from CMP measurements was used for depth conversion. Data were plotted in three-dimensional space, with the x and y coordinates representing horizontal positions and the z coordinate representing depth. A three-dimensional dataset of pre- and post-infiltration amplitudes was created. A threshold was chosen following Di Prima et al. (2020), based on the amplitude difference value corresponding to 1.5 times the standard deviation. Amplitude differences exceeding the threshold were binarized as 1, while the remaining values were set to 0.
3. Results
Similar results were obtained for river sand, decomposed granite soil and Tottori dune sand. The infiltration zone was visualized in expanding regions but not in narrowing regions.
However, in Andosol, the estimated infiltration zone did not match the actual infiltration zone at any depth.
4. Discussion
This study demonstrates that GPR can be used to visualize wet volumes during infiltration for three sandy soils. For Andosol, discrepancies between estimated and actual infiltration zones may be attributed to the higher initial moisture content compared to the other three soil types. This likely led to an ambiguous dielectric permittivity boundary, causing a mismatch between the sampled infiltration boundary and the boundary estimated from GPR data.