Cost-effective autonomous sensor for the long-term monitoring of water electrical conductivity of crop fields

Salinity is a key parameter determining water quality. In agriculture, irrigation water with high salinity levels impacts plant growth and yield negatively hence there is a need to monitor it and irrigate with fresh water whenever salinity surpasses the tolerance threshold of a cultivar. Electrical conductivity (EC) of water is usually measured periodically instead of salinity because of its practicality. This work describes a low-cost low-power (and yet inexpensive) autonomous sensor prototype that is able to compute continuously the EC of water from complex electrical impedance measurements based on synchronous sampling, a technique that lowers cost and power consumption. The sensor is easy to assemble and has been verified in the lab for an EC range from 0.35 dS m-1 to 6.18 dS m-1 , showing a maximal deviation of ± 0.03 dS m-1 from the readings of a commercial reference EC meter. The sensor has also been installed in a rice paddy and left unattended for a whole cultivation season (107 days). The maximum deviation observed during this field test is ± 0.14 dS m-1 , which is good enough to detect high salinity levels.Peer ReviewedPostprint (published version

Informe mensual d'articles publicats. Campus Baix Llobregat. Base de dades Scopus. Juny, juliol i agost 2019

Informe bibliomètric mensual Campus Baix Llobregat. Base de dades Scopus. Juny, juliol i agost 2019. EETAC i DEAB, ESAB.Postprint (published version

An integrated water quality sensing system : a review and analysis of critical parameters and an evaluation of contact and non-contact sensors : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University Albany, New Zealand

Figure 7 is re-used under a Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) license. Figure 8 is re-used under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. Figure 9 is re-used with the publisher's permission. Permission has been granted for the re-use of Figures copyrighted to IEEE (© IEEE).Several methodologies and standards exist for the measurement of water quality. The use of established water quality indices is embedded in these methodologies/standards and the measurement approach of these indices involves several different techniques and sensor technologies. Recent development in the field of water quality measurement has moved towards wireless sensor network systems to enable the monitoring of multiple bodies of water in any given geographical region, with most of the research focussing on the use of the Internet of Things (IoT) for the associated water quality sensing systems. There exists a small amount of research into combined sensor technologies that enable measurement simultaneously of multiple parameters. There is currently, however, no analysis available on the feasibility of developing a fully integrated system to measure all desirable water quality parameters simultaneously. Sensor solutions and analysis techniques for such a fully integrated system are therefore lacking. This research analyses common water quality measurement methods, comparing them particularly to non-contact alternatives to determine the viability of a cost effective and fully integrated water quality sensing system. In parallel it seeks to determine which types of sensors are best for effective analysis of water quality in distributed bodies of water. Literature analysis determined that a cost-effective, fully integrated water quality sensing system was feasible if the water quality parameters being measured were limited. As a result, an analysis of contact and non-contact sensors for the selected parameters was conducted. The results of this analysis were varied, and it was concluded that the types of sensor that should be used in an integrated water quality sensing system are dependent on the design of the critical parameter set being measured