Programmable automated low-cost IoT water sampler

Abstract

Water quality management is a critical environmental challenge for water resource managers in agriculture and other sectors due to pollution from contaminants like nitrogen and phosphorus. This pollution degrades ecosystems in waterways worldwide. Environmental pollutant mitigation methods rely heavily on the ability of managers to monitor water quality, often by collecting water samples (either by manual or automated methods) and sending them out for analyte characterization by a laboratory. Traditional automated samplers are often prohibitively expensive and/or complex, hindering effective water resource management across different contexts. Conversely, manual collection methods require more time and labor, but provide less data (i.e., a single point in time as opposed to a composite sample from multiple time points). Addressing this, the Colorado State University Agricultural Water Quality Program created a low-cost, automated water sampler (LCS) leveraging Internet of Things (IoT) technology that enables near-real-time, edge-of-field water monitoring. The LCS stands out for its affordability, simplicity, and real-time data provision, offering a practical tool for water resource managers seeking to monitor WQ. Furthermore, comparing LCS water quality and quantity data shows promising agreement, indicating that the device is a reasonable substitute for practical applications.