Neil Terry

Estimating belowground carbon stocks in peatlands of the Ecuadorian páramo using ground penetrating radar (GPR)

The paramo ecoregion of Ecuador contains extensive peatlands that are known to contain carbon (C) dense soils capable of long-term C storage. Although high-altitude mountain peatlands are typically small when compared to low altitude peatlands, they are abundant across the Andean landscape and are likely a key component in regional C cycling. Since efforts to quantify peatland distribution and C stocks across the tropical Andes have been limited due to the difficulty in sampling remote areas with very deep peat, there is a large knowledge gap in our quantification of the current C pools in the Andean mountains, which limits our ability to predict and monitor change from high rates of land use and climate change. In this paper we tested if ground penetrating radar (GPR), combined with manual coring and C analysis could be used for estimating C stocks in peatlands of the Ecuadorian paramo. Our results indicated that GPR was successful in quantifying peat depths and carbon stocks. Detection of volcanic horizons like tephra layers allowed further refinement of variability of C stocks within the peat column, while providing information on the lateral extent of tephras at high (cm scale) resolution that may prove very useful for the correlation of time-stratigraphic markers between sediments in alpine peatlands. In conclusion, this paper provides a methodological basis for quantifying C stocks in high altitude peatlands and to infer changes in the physical properties of soils that could be used as proxies for C content or paleoclimate reconstructions.

Scenario Evaluator for Electrical Resistivity Survey Pre-modeling Tool

Geophysical tools have much to offer users in environmental, water resource, and geotechnical fields; however, techniques such as electrical resistivity imaging (ERI) are often oversold and/or overinterpreted due to a lack of understanding of the limitations of the techniques, such as the appropriate depth intervals or resolution of the methods. The relationship between ERI data and resistivity is nonlinear; therefore, these limitations depend on site conditions and survey design and are best assessed through forward and inverse modeling exercises prior to field investigations. In this approach, proposed field surveys are first numerically simulated given the expected electrical properties of the site, and the resulting hypothetical data are then analyzed using inverse models. Performing ERI forward/inverse modeling, however, requires substantial expertise and can take many hours to implement. We present a new spreadsheet-based tool, the Scenario Evaluator for Electrical Resistivity (SEER), which features a graphical user interface that allows users to manipulate a resistivity model and instantly view how that model would likely be interpreted by an ERI survey. The SEER tool is intended for use by those who wish to determine the value of including ERI to achieve project goals, and is designed to have broad utility in industry, teaching, and research.

Gas bubble size estimation in peat soils from EM wave scattering observed with ground penetrating radar

The size of biogenic gas bubbles in peatlands is believed to regulate ebullition of carbon gases to the atmosphere. The measurement of electromagnetic (EM) wave travel times using ground penetrating radar (GPR) is a proven field-scale method for indirect estimation of volumetric gas content. However, there is also the possibility that information on the size of the gas bubbles can be determined from the analysis of the spectral content of GPR signals as scattering attenuation possesses a frequency dependence for bubbles smaller than the EM wavelength (Rayleigh-type scattering). Theoretical modeling shows that GPR data acquired with typical antenna frequencies are likely to be affected by bubble size in peat soils. Analysis of GPR data from two recent studies on peat monoliths where biogenic gas production was documented produced results consistent with the model predictions. Using the approach, zero offset cross-borehole GPR data in a northern peatland suggest that large bubble clusters (i.e., 0.05 m radius) occur in peat. These findings broaden the utility of GPR for providing information on biogenic gas dynamics in peatlands.

Free phase gas processes in a northern peatland inferred from autonomous field‐scale resistivity imaging

The mechanisms that control free phase gas (FPG) dynamics within peatlands, and therefore estimates of past, present, and future gas fluxes to the atmosphere remain unclear. Electrical resistivity imaging (ERI) is capable of autonomously collecting three-dimensional data on the centimeter to tens of meter scale and thus provides a unique opportunity to observe FPG dynamics in situ. We collected 127 3-D ERI data sets as well as water level, soil temperature, atmospheric pressure, and limited methane flux data at a site in a northern peatland over the period July–August 2013 to improve the understanding of mechanisms controlling gas releases at a hitherto uncaptured field scale. Our results show the ability of ERI to image the spatial distribution of gas accumulation and infer dynamics of gas migration through the peat column at high (i.e., hourly) temporal resolution. Furthermore, the method provides insights into the role of certain mechanisms previously associated with the triggering of FPG releases such as drops in atmospheric pressure. During these events, buoyancy-driven gas release primarily occurs in shallow peat as proposed by the “shallow peat model.” Releases from the deeper peat are impeded by confining layers, and we observed a large loss of FPG in deep peat that may likely represent a rupture event, where accumulated FPG escaped the confining layer as suggested by the “deep peat model.” Negative linear correlations between water table elevation and resistivity result from hydrostatic pressure regulating bubble volume, although these variations did not appear to trigger FPG transfer or release.

Scenario Evaluator for Electrical Resistivity (SEER) Survey Design Tool

The USGS Scenario Evaluator for Electrical Resistivity (SEER) is a quick and simple Excel-based decision support tool practitioners can use to assess the likely outcome of using two-dimensional (2D) electrical resistivity imaging for site characterization and remediation monitoring. SEER features a graphical user interface (GUI) that allows users to manipulate a resistivity model and instantly view how that model would likely be interpreted by an electrical resistivity imaging survey. The SEER tool is intended for use by practitioners who wish to determine the value of including electrical resistivity imaging to achieve project goals, and is designed to have broad utility in industry, teaching, and research. This is the initial release.