An electrical conductivity low-cost sensor was used in a physical sandbox model that was built in LNEC’s modeling facilities under the MARSOL project. The artificial aquifer facility or physical sandbox model was built to conduct laboratory large scale infiltration and tracer tests, aiming to determine the soil infiltration rate and the contaminants retention and/or degradation capacity, namely to simulate Soil-Aquifer Treatment (SAT) in a Managed Aquifer Recharge (MAR) basin. Calibration and validation of the low-cost sensors were carried out before and after the experiments, by using as reference instrument a CDT diver multi-parameter groundwater datalogger. In this paper, we focused on sodium chloride tracer, to determine the concentration of electrical conductivity into the aquifer. Validation data of low-cost sensors presented an R2 correlation coefficient of 0.77 – 0.96 and Pearson’s r coefficient of 0.87 – 0.98, which confirmed the linear relationship between the two variables.
Statistical Analysis of Low-Cost Water Sensors for Measuring the Electrical Conductivity
Ana M. C. Ilie
;Carmela Vaccaro
2018
Abstract
An electrical conductivity low-cost sensor was used in a physical sandbox model that was built in LNEC’s modeling facilities under the MARSOL project. The artificial aquifer facility or physical sandbox model was built to conduct laboratory large scale infiltration and tracer tests, aiming to determine the soil infiltration rate and the contaminants retention and/or degradation capacity, namely to simulate Soil-Aquifer Treatment (SAT) in a Managed Aquifer Recharge (MAR) basin. Calibration and validation of the low-cost sensors were carried out before and after the experiments, by using as reference instrument a CDT diver multi-parameter groundwater datalogger. In this paper, we focused on sodium chloride tracer, to determine the concentration of electrical conductivity into the aquifer. Validation data of low-cost sensors presented an R2 correlation coefficient of 0.77 – 0.96 and Pearson’s r coefficient of 0.87 – 0.98, which confirmed the linear relationship between the two variables.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
