A Comparison of Ground‐Penetrating Radar Early‐Time Signal Approaches for Mapping Changes in Shallow Soil Water Content. Issue 1 (7th September 2018)

• Record Type: Journal Article
• Authors: Algeo, Jonathan; Slater, Lee; Binley, Andrew; Van Dam, Remke L.; Watts, Chris
• Is Part Of: Vadose zone journal. Volume 17:Issue 1(2018)
• Page Start: 1
• Page End: 11
• Publication Date: 2018-09-07
• Subjects: Soil science -- Periodicals; Zone of aeration -- Periodicals; Groundwater flow -- Periodicals; Groundwater flow; Zone of aeration; Periodicals; Electronic journals; 631.4
• DOI: 10.2136/vzj2018.01.0001
• Languages: English
• ISSNs: 1539-1663

Abstract

Abstract : Core Ideas: Early‐time amplitude analysis requires understanding of site, system, and methodology. The AEA and CFA both have benefits and disadvantages. Time window selection is important when shallow reflectors may be present. Early time GPR results are highly frequency dependent. Improving irrigation efficiency requires accurate assessment of the soil moisture distribution in time and space, but obtaining accurate observational data is challenging. Early‐time signal (ETS) amplitude analysis of ground‐penetrating radar (GPR) data may permit such rapid noninvasive characterization. In this study we performed controlled irrigation experiments using a multifrequency GPR system to compare two statistics used to quantify the ETS: average envelope amplitude (AEA) and carrier frequency amplitude (CFA). Supporting data were provided by direct measurements, electrical resistivity imaging (ERI), and synthetic modeling. In our first experiment, both statistics successfully related the ETS for 250 and 400 MHz GPR data to increasing water content. However, the 400 MHz AEA lost sensitivity at later stages of the irrigation process, whereas the 400 MHz CFA remained sensitive to changes in water content. The 1000 MHz data did not show the expected relationships, possibly due to shallow reflectors, such as the wetting front, which the higher frequency antennae would have a greater chance of detecting, as supported by synthetic modeling. In our second experiment, we focused on the effect of the time window on calculating ETS statistics. We demonstrate that, when there is interference in the ETS, using a shorter time window instead of the more common first positive half cycle improves correlation with soil moisture content. Our work shows that the GPR ETS data respond to changes in soil water content in similar fashion to ERI data.