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This report concerns Root water content (RWC) as a vital component in water flux in soil-plant-atmosphere continuum. Knowledge of RWC helps to better understand the root function and the soil-root interaction and improves water cycle modeling. However, due to the lack of appropriate methods, field monitoring of RWC is seriously constrained. In this study, we used ground-penetrating radar (GPR), a common geophysical technique, to characterize RWC of coarse roots noninvasively. An automatic GPR data processing framework was proposed to (1) identify hyperbolic root reflections and locate roots in GPR images and (2) extract waveform parameters from the reflected wave ofmore » identified roots. These waveform parameters were then used to establish an empirical model and a semiempirical model to determine RWC. We validated the developed models using GPR root data at three antenna center frequencies (500 MHz, 900 MHz, and 2 GHz) that were produced from simulation experiments (with RWC ranging from 70% to 150%) and field experiments in sandy soils (with RWC ranging from 66% to 144%). Our results show that both the empirical and the semiempirical models achieved a good performance in estimating RWC with similar accuracy, i.e., the prediction error [root-mean-square error (RMSE)] was less than 8% for the simulation data and 12% for the field data. For both models, the accuracy of RWC estimation was the highest when applied to 2-GHz data. This study renders a new opportunity to determine RWC under field conditions that enhances the application of GPR for root study and the understanding and modeling of ecohydrology in the rhizosphere.« less

Accurate quantification of coarse roots without disturbance represents a gap in our understanding of belowground ecology. Ground penetrating radar (GPR) has shown significant promise for coarse root detection and measurement, however root orientation relative to scanning transect direction, the difficulty identifying dead root mass, and the effects of root shadowing are all key factors affecting biomass estimation that require additional research. Specifically, many aspects of GPR applicability for coarse root measurement have not been tested with a full range of antenna frequencies. We tested the effects of multiple scanning directions, root crossover, and root versus soil moisture content in amore » sand-hill mixed oak community using a 1500 MHz antenna, which provides higher resolution than the oft used 900 MHz antenna. Combining four scanning directions produced a significant relationship between GPR signal reflectance and coarse root biomass (R2 = 0.75) (p < 0.01) and reduced variability encountered when fewer scanning directions were used. Additionally, significantly fewer roots were correctly identified when their moisture content was allowed to equalize with the surrounding soil (p < 0.01), providing evidence to support assertions that GPR cannot reliably identify dead root mass. The 1500 MHz antenna was able to identify roots in close proximity of each other as well as roots shadowed beneath shallower roots, providing higher precision than a 900 MHz antenna. As expected, using a 1500 MHz antenna eliminates some of the deficiency in precision observed in studies that utilized lower frequency antennas.« less

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less