Streambed Flux Measurement Informed by Distributed Temperature Sensing Leads to a Significantly Different Characterization of Groundwater Discharge

Authors

Troy E. Gilmore, University of Nebraska-LincolnFollow
Mason Johnson, University of Nebraska-LincolnFollow
Jesse T. Korus, University of Nebraska-LincolnFollow
Aaron R. Mittelstet, University of Nebraska-LincolnFollow
Marty A. Briggs, U.S. Geological SurveyFollow
Vitaly A. Zlotnik, University of Nebraska - LincolnFollow
Sydney Corcoran, University of Nebraska-LincolnFollow

ORCID IDs

https://orcid.org/0000-0001-9939-4780

https://orcid.org/0000-0003-3206-4132

https://orcid.org/0000-0002-9601-9464

Document Type

Article

Date of this Version

11-5-2019

Citation

2019 by the authors.

Comments

Water 2019, 11, 2312; doi:10.3390/w11112312 www.mdpi.com/journal/water

Abstract

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 dierent 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 day 1; n = 30) and informed (0.17 m day 1; n = 20) measurement locations. Mean values followed a similar pattern (0.12 versus 0.27 m day 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