H13G-1191:
Water Quality Data at High Time and Space Resolution in the Field : Expanding Spectrophotometer Capabilities with Arduino Driven Autosamplers

Monday, 15 December 2014
François Birgand, Bryan Maxwell, Kyle Aveni-Deforge and Randall Etheridge, North Carolina State University at Raleigh, Raleigh, NC, United States
Abstract:
Availability of continuous hydrological data (e.g. flow rates, rainfall, etc.) for over a century has shaped our current understanding of the hydrological cycle. Until now, there has been no equivalence for water quality. Optics based systems now open the possibility to obtain data at a temporal resolution in par with that commonly used in quantitative hydrology (e.g. 15 min – 1 hr). We show that absorbance measured in the field using spectrophotometers can be statistically correlated with light- and none- absorbing constituents in the water. Water quality rating curves for 6-12 parameters can be derived as such using a single spectrophotometer, opening access to continuous water quality data for many parameters at a time. We then show that attaching such probe in the field with multiplexed pumping systems driven by Arduinos can expand the high temporal resolution capabilities to space as our systems can sample up to 12 different water sources located within 15 m of the water quality probe.