Resumen
In this approach, a method utilizing data series from multivariate parameters to detect contaminant events is discussed and evaluated. Eight water quality sensors (pH, turbidity, conductivity, temperature, oxidation reduction potential, UV-254, nitrate and phosphate) are used in this study and the most commonly used herbicide, glyphosate, is selected as the test contaminant. Variations of all parameters are recorded in real time at different concentrations. The results from the experiment and analysis show that the proposed method with suitable optimization can detect a glyphosate contamination less than 5 min after the introduction of the contaminant using responses from online water quality sensors. The average true positive rate is 95.5%. The study also discusses the impact of the number of sensors on detection performance. The results show that if the number of sensors is reduced from 8 to 5, the true positive rate performance is still good. This indicates that the method is flexible and can be applied using a smaller number of sensors to reduce monitoring costs.