Geology topics

Troy E. Gilmore

Publications and source records attributed to Troy E. Gilmore.

4 recordsLinked to original sources

USGS2021

Determination of vadose zone and saturated zone nitrate lag times using long-term groundwater monitoring data and statistical machine learning

In this study, we explored the use of statistical machine learning and long-term groundwater nitrate monitoring data to estimate vadose zone and saturated zone lag times in an irrigated alluvial agricultural setting. Unlike most previous statistical machine learning studies that sought to predict groundwater nitrate concentrations within aquifers, the focus of this study was to leverage available groundwater nitrate concentrations and other environmental variables to determine mean regional vertical velocities (transport rates) of water and solutes in the vadose zone and saturated zone (3.50 and 3.75 m yr −1 , respectively). The statistical machine learning results are consistent with two primary recharge processes in this western Nebraska aquifer, namely ( 1 ) diffuse recharge from irrigation and precipitation across the landscape and ( 2 ) focused recharge from leaking irrigation conveyance canals. The vadose zone mean velocity yielded a mean recharge rate (0.46 m yr −1 ) consistent with previous estimates from groundwater age dating in shallow wells (0.38 m yr −1 ). The saturated zone mean velocity yielded a recharge rate (1.31 m yr −1 ) that was more consistent with focused recharge from leaky irrigation canals, as indicated by previous results of groundwater age dating in intermediate-depth wells (1.22 m yr −1 ). Collectively, the statistical machine learning model results are consistent with previous observations of relatively high water fluxes and short transit times for water and nitrate in the primarily oxic aquifer. Partial dependence plots from the model indicate a sharp threshold in which high groundwater nitrate concentrations are mostly associated with total travel times of 7 years or less, possibly reflecting some combination of recent management practices and a tendency for nitrate concentrations to be higher in diffuse infiltration recharge than in canal leakage water. Limitations to the machine learning approach include the non-uniqueness of different transport rate combinations when comparing model performance and highlight the need to corroborate statistical model results with a robust conceptual model and complementary information such as groundwater age.

Nebraska↗

USGS2019

Streambed flux measurement informed by distributed temperature sensing leads to a significantly different characterization of groundwater discharge

Groundwater discharge though streambeds is often focused toward discrete zones, indicating that preliminary reconnaissance may be useful for capturing the full spectrum of groundwater discharge rates using point-scale quantitative methods. However, many direct-contact reconnaissance techniques can be time consuming, and remote sensing (e.g. thermal infrared) typically does not penetrate the water column to locate submerged seepages. In this study we tested whether dozens of groundwater discharge measurements made at "uninformed" (i.e., selected without knowledge on high-resolution temperature variations at the streambed) point locations along a reach would yield significantly different Darcy-based groundwater discharge rates when compared with “informed” measurements, focused at streambed thermal anomalies that were identified a-priori using fiber-optic distributed temperature sensing (FO-DTS). A non-parametric U-test showed a significant difference between median discharge rates for uninformed (0.05 m·d-1; n = 30) and informed (0.17 m·d-1; n = 20) measurement locations. Mean values followed a similar pattern (0.12 versus 0.27 m·d-1) and frequency distributions for uninformed and informed measurements were also significantly different based on a Kolmogorov-Smirnov test. Results suggest that even using a quick “snapshot-in-time” field analysis of FO-DTS data can be useful in streambeds with groundwater discharge rates <0.2 m·d-1, a lower threshold than proposed in a previous study. Collectively, study results highlight that FO-DTS is a powerful technique for identifying higher-discharge zones in streambeds, but the pros and cons of informed and uninformed sampling depend in part on groundwater/surface water exchange study goals. For example, studies focused on measuring representative groundwater and solute fluxes may be biased if high-discharge locations are preferentially sampled. However, identification of high-discharge locations may complement more randomized sampling plans and lead to improvements in interpolating streambed fluxes and upscaling point measurements to the stream reach scale.

Nebraska↗

USGS2016

A gas-tracer injection for evaluating the fate of methane in a coastal plain stream: Degassing versus in-stream oxidation

Methane emissions from streams and rivers have recently been recognized as an important component of global greenhouse budgets. Stream methane is lost as evasion to the atmosphere or in-stream methane oxidation. Previous studies have quantified evasion and oxidation with point-scale measurements. In this study, dissolved gases (methane, krypton) were injected into a coastal plain stream in North Carolina to quantify stream CH 4 losses at the watershed scale. Stream-reach modeling yielded gas transfer and oxidation rate constants of 3.2 ± 0.5 and 0.5 ± 1.5 d –1 , respectively, indicating a ratio of about 6:1. The resulting evasion and oxidation rates of 2.9 mmol m –2 d –1 and 1,140 nmol L –1 d –1 , respectively, lie within ranges of published values. Similarly, the gas transfer velocity ( K 600 ) of 2.1 m d –1 is consistent with other gas tracer studies. This study illustrates the utility of dissolved-gas tracers for evaluating stream methane fluxes. In contrast to point measurements, this approach provides a larger watershed-scale perspective. Further work is needed to quantify the magnitude of these fluxes under varying conditions (e.g., stream temperature, nutrient load, gradient, flow rate) at regional and global scales before reliable bottom-up estimates of methane evasion can be determined at global scales.

Environmental Science & Technology↗

USGS2015

A tube seepage meter for in situ measurement of seepage rate and groundwater sampling

We designed and evaluated a “tube seepage meter” for point measurements of vertical seepage rates ( q ), collecting groundwater samples, and estimating vertical hydraulic conductivity ( K ) in streambeds. Laboratory testing in artificial streambeds show that seepage rates from the tube seepage meter agreed well with expected values. Results of field testing of the tube seepage meter in a sandy-bottom stream with a mean seepage rate of about 0.5 m/day agreed well with Darcian estimates (vertical hydraulic conductivity times head gradient) when averaged over multiple measurements. The uncertainties in q and K were evaluated with a Monte Carlo method and are typically 20% and 60%, respectively, for field data, and depend on the magnitude of the hydraulic gradient and the uncertainty in head measurements. The primary advantages of the tube seepage meter are its small footprint, concurrent and colocated assessments of q and K , and that it can also be configured as a self-purging groundwater-sampling device.

Groundwater↗