Geology topics

Aaron R. Mittelstet

Publications and source records attributed to Aaron R. Mittelstet.

2 recordsLinked to original sources

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

Landscape and flow metrics affecting the distribution of a federally-threatened fish: Improving management, model fit, and model transferability

Truncated distributions of pelagophilic fishes have been observed across the Great Plains of North America, with water use and landscape fragmentation implicated as contributing factors. Developing conservation strategies for these species is hindered by the existence of multiple competing flow regime hypotheses related to species persistence. Our primary study objective was to compare the predicted distributions of one pelagophil, the Arkansas River Shiner Notropis girardi , constructed using different flow regime metrics. Further, we investigated different approaches for improving temporal transferability of the species distribution model (SDM). We compared four hypotheses: mean annual flow (a baseline), the 75th percentile of daily flow, the number of zero-flow days, and the number of days above 55th percentile flows, to examine the relative importance of flows during the spawning period. Building on an earlier SDM, we added covariates that quantified wells in each catchment, point source discharges, and non-native species presence to a structured variable framework. We assessed the effects on model transferability and fit by reducing multicollinearity using Spearman’s rank correlations, variance inflation factors, and principal component analysis, as well as altering the regularization coefficient (β) within MaxEnt. The 75th percentile of daily flow was the most important flow metric related to structuring the species distribution. The number of wells and point source discharges were also highly ranked. At the default level of β, model transferability was improved using all methods to reduce collinearity; however, at higher levels of β, the correlation method performed best. Using β = 5 provided the best model transferability, while retaining the majority of variables that contributed 95% to the model. This study provides a workflow for improving model transferability and also presents water-management options that may be considered to improve the conservation status of pelagophils.

Great Plains of North America↗