A low‐cost water depth and electrical conductivity sensor for detecting inputs into urban stormwater networks
Abstract
High‐resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low‐cost sensor reliably measures the rate‐of‐change of water level without any re‐calibration by comparing with industry‐standard instruments such as HACH and HORIBA’s probes. To overcome the observed drift of level sensors, we developed an automated re‐calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher‐resolution sensing feasible from the budget control considerations, since the regular sensor re‐calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re‐calibration every two weeks is required to limit the sensor’s inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real‐time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high‐density monitoring that cannot be achieved before with high‐end loggers and sensors. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000482488Publication status
publishedExternal links
Journal / series
SensorsVolume
Pages / Article No.
Publisher
MDPISubject
water level measurement; electric conductivity; real-time environmental monitoring; illegal discharge detection; distributed sensing; low cost; low power; water IoTMore
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