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Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar

A Ground Penetrating Radar (GPR) system based on a ground-coupled, densely populated antenna array was used to collect data during an infiltration experiment conducted at a test site near the Tottori Sand Dune, Japan. The antenna array used in this study consists of 10 transmitting antennas (Tx) and...

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Autores principales: Saito, Hirotaka, Kuroda, Seiichiro, Iwasaki, Toshiki, Fujimaki, Haruyuki, Nagai, Nobuhito, Sala, Jacopo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MyJove Corporation 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101056/
https://www.ncbi.nlm.nih.gov/pubmed/29782019
http://dx.doi.org/10.3791/56847
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author Saito, Hirotaka
Kuroda, Seiichiro
Iwasaki, Toshiki
Fujimaki, Haruyuki
Nagai, Nobuhito
Sala, Jacopo
author_facet Saito, Hirotaka
Kuroda, Seiichiro
Iwasaki, Toshiki
Fujimaki, Haruyuki
Nagai, Nobuhito
Sala, Jacopo
author_sort Saito, Hirotaka
collection PubMed
description A Ground Penetrating Radar (GPR) system based on a ground-coupled, densely populated antenna array was used to collect data during an infiltration experiment conducted at a test site near the Tottori Sand Dune, Japan. The antenna array used in this study consists of 10 transmitting antennas (Tx) and 11 receiving antennas (Rx). For this experiment, the system was configured to use all possible Tx-Rx pairings, resulting in a Multi-Offset Gather (MOG) consisting of 110 Tx-Rx combinations. The array was left stationary at a position directly above the infiltration area and data were collected every 1.5 seconds using a time-based trigger. Common-Offset Gather (COG) and Common Mid-Point (CMP) data cubes were reconstructed from the MOG data during post-processing. There have been few studies that used time-lapse CMP data to estimate changes in velocity of propagation. In this study, electromagnetic (EM) wave velocity was estimated heuristically at 1-minute intervals from the reconstructed CMP data through curve fitting, using the hyperbola equation. We then proceeded to calculate the depth of the wetting front. The evolution of the wetting front over time obtain through this method is consistent with the observations from a soil moisture sensor which was placed at a depth below 20 cm. The results obtained in this study demonstrate the ability of such array GPR system to monitor a subsurface dynamic process like water infiltration accurately and quantitatively.
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spelling pubmed-61010562018-09-06 Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar Saito, Hirotaka Kuroda, Seiichiro Iwasaki, Toshiki Fujimaki, Haruyuki Nagai, Nobuhito Sala, Jacopo J Vis Exp Environmental Sciences A Ground Penetrating Radar (GPR) system based on a ground-coupled, densely populated antenna array was used to collect data during an infiltration experiment conducted at a test site near the Tottori Sand Dune, Japan. The antenna array used in this study consists of 10 transmitting antennas (Tx) and 11 receiving antennas (Rx). For this experiment, the system was configured to use all possible Tx-Rx pairings, resulting in a Multi-Offset Gather (MOG) consisting of 110 Tx-Rx combinations. The array was left stationary at a position directly above the infiltration area and data were collected every 1.5 seconds using a time-based trigger. Common-Offset Gather (COG) and Common Mid-Point (CMP) data cubes were reconstructed from the MOG data during post-processing. There have been few studies that used time-lapse CMP data to estimate changes in velocity of propagation. In this study, electromagnetic (EM) wave velocity was estimated heuristically at 1-minute intervals from the reconstructed CMP data through curve fitting, using the hyperbola equation. We then proceeded to calculate the depth of the wetting front. The evolution of the wetting front over time obtain through this method is consistent with the observations from a soil moisture sensor which was placed at a depth below 20 cm. The results obtained in this study demonstrate the ability of such array GPR system to monitor a subsurface dynamic process like water infiltration accurately and quantitatively. MyJove Corporation 2018-05-01 /pmc/articles/PMC6101056/ /pubmed/29782019 http://dx.doi.org/10.3791/56847 Text en Copyright © 2018, Journal of Visualized Experiments http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Environmental Sciences
Saito, Hirotaka
Kuroda, Seiichiro
Iwasaki, Toshiki
Fujimaki, Haruyuki
Nagai, Nobuhito
Sala, Jacopo
Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
title Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
title_full Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
title_fullStr Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
title_full_unstemmed Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
title_short Tracking Infiltration Front Depth Using Time-lapse Multi-offset Gathers Collected with Array Antenna Ground Penetrating Radar
title_sort tracking infiltration front depth using time-lapse multi-offset gathers collected with array antenna ground penetrating radar
topic Environmental Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101056/
https://www.ncbi.nlm.nih.gov/pubmed/29782019
http://dx.doi.org/10.3791/56847
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