Document Type

Article

Publication Date

2015

Keywords

Thermal infrared remote sensing, Submarine groundwater discharge, Fresh fraction, Radon, Radium

Abstract

Airborne thermal infrared (TIR) overflights were combined with shoreline radionuclide surveys to investigate submarine groundwater discharge (SGD) along the north shore of Long Island, NY between June 2013 and September 2014. Regression equations developed for three distinct geomorphological environments suggest a positive linear relationship between the rate of diffuse SGD and the spatial extent of the observed coastal TIR anomalies; such a relationship provides quantitative evidence of the ability to use TIR remote sensing as a tool to remotely identify and measure SGD. Landsat TIR scenes were unable to resolve any of the 18 TIR anomalies identified during the various airborne overflights. Two locations were studied in greater detail via 222Rn time series and manual seepage meters in order to understand why specific shoreline segments did not exhibit a TIR anomaly. SGD at the first site, located within a large, diffuse TIR anomaly, was composed of a mixture of fresh groundwater and circulated seawater with elevated levels of nitrate. In contrast, SGD at the second site, where no coastal TIR anomaly was observed, was composed of circulated seawater with negligible nitrate. Despite the compositional differences in seepage, both sites were similar in discharge magnitude, with average time series 222Rn derived SGD rates equal to 18 and 8 cm d−1 for the TIR site and non-TIR site, respectively. Results suggest that TIR remote sensing has the ability to identify locations of a mixture between diffuse fresh and circulated seawater SGD. If TIR anomalies can be demonstrated to represent a mixture between fresh and circulated seawater SGD, then the cumulative area of the TIR anomalies may be used to estimate the fresh fraction of SGD relative to the cumulative area of the seepage face, and thus allows for improved SGD derived nutrient flux calculations on a regional scale.

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