Characterization and Classification of Groundwater from Wells Using an Electronic Tongue (Kairouan, Tunisia)

Abstract

A sensor array comprising 9 potentiometric chemical sensors and some pattern recognition tools for the data processing has been applied in order to characterize the groundwater in the plain of Kairouan Region (Tunisia). A total of 17 groundwater samples were collected from three different villages and analyzed for their chemical components. Nine chemical parameters were determined: Potassium, Sodium, Calcium, Ammonium, Cadmium, Chlorides, Nitrates, Fluoride and pH. Multi-sensor responses measured in each water sample were diagnosed by Principal Component Analysis (PCA) and Cluster Analysis (CA). PCA is a procedure for reducing data redundancy. CA is used to detect spatial similarity among sampling sites. This methodology is simple, rapid and the obtained results demonstrate that the electronic tongue technique based on the sensor array combined with pattern recognition method could be a useful tool for the characterization and the classification of wells water samples.