Data optimization in nitrate water monitoring systems

Abstract

Anthropogenic activities, such as intensive fertilization, generate an increase in the concentration of nitrates in water systems that can cause contamination in waters for human consumption and eutrophication in surface waters. Discrete sample analysis reveals spatial differences in concentration, although continuous analysis provides more information about the origin, hydrological dynamics, transport, and nitrates bioprocessing. Nevertheless, the frequency, the period and the data quality must be optimized according to the research objective, since continuous monitoring implies high instrumental consumption and a large generation of data that may not provide relevant information for the objective. UV spectroscopy with continuous flow analysis is a technique that directly quantifies nitrate concentration and is well suited to high resolution monitoring. In this work, the design of a system that uses this type of analysis is proposed coupled to a conductivity sensor, as a trigger for the sampling frequency. Furthermore, the use of the Internet of Things (IoT) is implemented both to carry out configuration processes in data collection and for remote electromechanical actuation, which allows manual or automatic adjustment in obtaining data and, consequently, the information temporal and spatial required for the study of nitrates in the water resource.