TY - JOUR
T1 - Noninvasive 2D and 3D Mapping of Root Zone Soil Moisture Through the Detection of Coarse Roots With Ground-Penetrating Radar
AU - Liu, X.
AU - Chen, J.
AU - Butnor, J. R.
AU - Qin, G.
AU - Cui, X.
AU - Fan, B.
AU - Lin, H.
AU - Guo, L.
N1 - Funding Information:
The GPR raw data and the soil moisture data obtained by augering will be archived in ZENODO ( www.zenodo.org ). The authors are thankful for the assistance in field data collection from Qixin Liu, Zhenxian Quan, Qi Dong, Chishan Zhang, and Wenqing Wang. Financial support was provided by the National Natural Science Foundation of China (Grants 41571404 and 51879172). The source codes of GPR data processing, spatial interpolation, and data visualization are available from the authors upon request ( lug163@psu.edu or guolistory@gmail.com ). We are also thankful for the Editor (D. Scott Mackay), the Associate Editor (J.A. (Sander) Huisman), and three anonymous reviewers for their suggestions that have helped greatly improve the quality of this paper.
Publisher Copyright:
©2020. American Geophysical Union. All Rights Reserved.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Root zone soil moisture (RZSM) is important in sustaining terrestrial ecosystems and water cycling. However, noninvasive mapping of RZSM remains challenging in the field, especially its spatial variability at local scales. We propose a novel method of applying ground-penetrating radar (GPR) for noninvasive determination of RZSM. First, this method identified coarse root reflections in GPR images to obtain the reflected wave velocity and soil water storage at various locations. Then, the horizontal distributions of soil water storage to different depths were reconstructed using the inverse distance weighted interpolation. The difference in soil water storage between two depths was converted into 2D RZSM distribution for a specific depth interval. Finally, 2D RZSM distributions from a range of depths were combined to produce a 3D visualization of RZSM. The proposed method was validated in two field plots (30 m by 30 m) in shrublands. The comparisons with 2D RZSM distributions from soil cores sampled at 0.2-m depth intervals suggested a reasonable correspondence in both spatial patterns and absolute values, with the average root-mean-square error less than 0.017 m3·m−3 and correlation coefficients ranging from 0.502 to 0.798 in both plots. Furthermore, 3D visualizations of RZSM were generated based on GPR estimates to demonstrate the spatial variability of soil moisture at the study scale. The proposed method enhances noninvasive characterization of soil moisture down to the root zone, which contributes to a better understanding of the local-scale variability of soil moisture in the subsoil as well as the ecohydrological processes in the soil-plant-atmosphere continuum.
AB - Root zone soil moisture (RZSM) is important in sustaining terrestrial ecosystems and water cycling. However, noninvasive mapping of RZSM remains challenging in the field, especially its spatial variability at local scales. We propose a novel method of applying ground-penetrating radar (GPR) for noninvasive determination of RZSM. First, this method identified coarse root reflections in GPR images to obtain the reflected wave velocity and soil water storage at various locations. Then, the horizontal distributions of soil water storage to different depths were reconstructed using the inverse distance weighted interpolation. The difference in soil water storage between two depths was converted into 2D RZSM distribution for a specific depth interval. Finally, 2D RZSM distributions from a range of depths were combined to produce a 3D visualization of RZSM. The proposed method was validated in two field plots (30 m by 30 m) in shrublands. The comparisons with 2D RZSM distributions from soil cores sampled at 0.2-m depth intervals suggested a reasonable correspondence in both spatial patterns and absolute values, with the average root-mean-square error less than 0.017 m3·m−3 and correlation coefficients ranging from 0.502 to 0.798 in both plots. Furthermore, 3D visualizations of RZSM were generated based on GPR estimates to demonstrate the spatial variability of soil moisture at the study scale. The proposed method enhances noninvasive characterization of soil moisture down to the root zone, which contributes to a better understanding of the local-scale variability of soil moisture in the subsoil as well as the ecohydrological processes in the soil-plant-atmosphere continuum.
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U2 - 10.1029/2019WR026930
DO - 10.1029/2019WR026930
M3 - Article
AN - SCOPUS:85084582732
SN - 0043-1397
VL - 56
JO - Water Resources Research
JF - Water Resources Research
IS - 5
M1 - e2019WR026930
ER -