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Coupling Aircraft and Unmanned Aerial Vehicle Remote Sensing with Simultaneous In Situ Coastal Measurements to Monitor the Dynamics of Submarine Groundwater Discharge
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|Title:||Coupling Aircraft and Unmanned Aerial Vehicle Remote Sensing with Simultaneous In Situ Coastal Measurements to Monitor the Dynamics of Submarine Groundwater Discharge|
|Issue Date:||Aug 2016|
|Publisher:||[Honolulu] : [University of Hawaii at Manoa], [August 2016]|
|Abstract:||Increased nutrient addition to the coastal zone via submarine groundwater discharge (SGD) has been suspected as the primary cause of the rapid decline of coral reefs and recurring macroalgal blooms on Maui. As a consequence, the island has been the focus of SGD research for close to 20 years. Very little, however, is known about the overall distribution of SGD around the island of Maui. To address this question, airplane-based thermal infrared (TIR) imaging was used to produce a spatially accurate regional scale map of coastal groundwater inputs around the western half of Maui. This data revealed over 70 areas of potential SGD locations over approximately 100km of coastline. Continuous radon monitoring was coupled with simultaneous time-series unmanned aerial vehicle (UAV or “drone”) TIR imagery to quantify and characterize the dynamic variability of SGD. In this endeavor, this research has demonstrated that incorporation of time-series TIR imagery from a UAV with continuous radon monitoring enables new and highly refined constraints on the variability of SGD. UAV-TIR imaging reveals the exact location and dispersal of the SGD flow in relation to time-series radon monitoring location(s), thus eliminating assumptions about the surface area over which groundwater is discharging into the coastal zone, and therefore allows for highly improved and exacting determinations of SGD rates and nutrient fluxes. Furthermore, the use of time-series UAV-TIR imaging provides imagery at unprecedented resolutions that can supply spatial and temporal information about SGD dynamics that can be used to uniquely constrain and differentiate variations in flow.|
|Description:||M.S. University of Hawaii at Manoa 2016.|
Includes bibliographical references.
|Appears in Collections:||M.S. - Geology and Geophysics|
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