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New Zealand Scientists Test Pollutant Monitoring Using EnviroDIY Hardware

Google Earth satellite image of Waihi Estuary, New Zealand
Google Earth Image including data from AirbusLandsat / CopernicusData SIO, NOAA, U.S. Navy, NGA, GEBCOData LDEO-Columbia, NSF, NOAA

Researchers in New Zealand discovered that high-frequency monitoring of rivers yielded a more accurate accounting of nitrogen, phosphorus, and sediment loads than monthly grab samples allowed for. While high-frequency monitoring was more expensive, “the added investment is minor when weighed against the risks of poorly informed land management actions or generic policies based on limited contaminant data.” The research was published in Scientific Reports.

James Dare and colleagues also tested whether a lower-cost, do-it-yourself monitoring approach was a feasible alternative to more expensive commercially-manufactured equipment. They deployed EnviroDIY Mayfly Data Loggers to record data from Meter Group conductivity, temperature, and depth sensors, as well as a Yosemitech nephelometer.

“The main advantage of this method remains its cost: equipment costs are up to ten times lower than OTS [off-the-shelf] systems, allowing wider spatial coverage across a catchment.” The authors report a total cost of $2,723 NZD per EnviroDIY Monitoring Station (including sensors), and an annual labor cost of $1,200 NZD for routine maintenance of 10 stations.

EnviroDIY Monitoring Station beside a stream showing an inset photo of the sensors on the stream bed and the Mayfly Data Logger in a weather-proof enclosure.
An EnviroDIY Monitoring Station similar to the ones used by Dare et al (2026). The left inset photo shows a Meter Group conductivity, temperature, and depth sensor secured to the creek bed. The right inset shows a Mayfly Data Logger, battery, and telemetry system housed in a tan weather-proof case (center photo).

The study also explored the use of artificial neural networks for predicting continuous nitrogen, phosphorus, and sediment concentration based on the surrogate parameters collected from sensors. This approach enabled inclusion of nitrogen, phosphorus, and sediment concentration changes during storm events, conditions not captured by routine monthly sampling. The higher temporal resolution data not only revealed higher nitrogen, phosphorus, and sediment export, it also revealed important differences in hydrologic behavior between rivers and their catchments.

Citation: Dare J.E., Özkundakci D. & McDowell R.W. A do-it-yourself water quality sensor network to elucidate contaminant signatures and improve land management advice. Sci Rep (2026). https://doi.org/10.1038/s41598-026-43915-9

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