Editing Oxygen Optode Data from Field Test at Elora Research Station, Guelph, Ontario

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Section 1: Overview

Name of Research Project

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Purpose

The aim of this project is to build on existing research, which resulted in the development of a low-cost, lab-based fibre optic oxygen sensor for monitoring oxygen in soils and sediments. The field system was built in collaboration with an industrial partner, Hoskin Scientific, who developed the optical detection and electrical control units for the sensor system.

In the GWF program, the unit will be tested under field conditions, through deployment at the University of Guelph’s Elora Research Station, in Southern Ontario, in collaboration with the University of Guelph researchers. The optode data being collected will be used for evaluating the sensor performance under field conditions and for an improved understanding of soil oxygen dynamics given the seasonal variations in an agricultural field site.
	
Note that the initial sensor development was funded by the Canada Excellence Research Chair (CERC) program (CERC Ecohydrology), while the field sensor development was in partnership with Hoskin Scientific through an NSERC Engage Grant. The data set here will support the project titled "Sensors and Sensing Systems for Water Quality Monitoring", which is a Pillar 1 project under the Global Water Futures Program (GWF) funded by Canada First Research Excellence Fund.

Abstract

This data set includes a time series of the light intensity (a.u.) and oxygen concentration (specified in % saturation or mol/L) measured by 8 fibre opode sensors installed in 2 lysimeters (4 sensors in each lysimeter), one with sandy soil (L1), another with silty soil (L2), in an agricultural field site in Elora, Ontario. The sensor readings correspond to the following depths (relative to the soil surface): 5 cm, 10 cm, 30 cm, and 60 cm. One image is taken every three hours and captures values for all eight sensors simultaneously.

The data collected is in the form of digital images taken with a DSLR camera. The raw data includes the unprocessed images (.CR2 files). Each image is processed using freely available ImageJ software and analyzed for the average light intensity (a.u.) of each sensor spot in the image. In addition to the raw images, the processed values of average light intensity are included in an excel file. The light intensity must then be converted into an oxygen concentration, based on the Stern-Volmer equation and sensor calibration results.

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