Low-Cost IoT Water Sampler

Background and Problem

In Colorado and across the United States, agriculture is being identified as one source of nutrient pollution in State and Federal waters. Nutrients such as nitrogen and phosphorus run off farmlands and accumulate in surface waterways, causing water quality issues. Although agricultural nonpoint sources are not currently regulated in Colorado, initiatives are set up to encourage the adoption of Best Management Practices (BMPs) that protect surface water quality. Quantifying BMP impacts on water quality, requires robust, edge-of-field (EoF) monitoring systems that can accurately measure flow and collect water for nutrient and sediment analysis. NRCS EoF standards currently require equipment that is often too costly for pragmatic and scalable research.

Build One Yourself

To learn more about the low-cost IoT water sampler, visit this GitHub repository, where you can learn more and even try to build one yourself! For more detailed instructions, take a look at our journal article in HardwareX.

Our Solution

To address this need, the Colorado State University Agricultural Water Quality Program (AWQP) has developed a low-cost automated water sampler (LCS) with Internet of Things (IoT) technology for scalable, near-real-time water quality research. This work directly follows deliverables from an awarded NRCS Conservation Innovation Grant titled, “Next Generation Technology for Monitoring Edge-of-Field Water Quality in Organic Agriculture”. A preliminary comparison study performed by the AWQP indicates strong agreement between LCS depth measurements and commercial bubbler units, with a root mean squared error (RMSE) of 4.2 mm (n=1099). Additionally, measured analyte concentrations (total suspended solids, NO3, NO2, Total N, Orthophosphate, Total Phosphorous) were similar, but lacked enough sample points to accurately make a comparison.

Google Sites

Report abuse