TY - JOUR
T1 - A low‐cost water depth and electrical conductivity sensor for detecting inputs into urban stormwater networks
AU - Shi, Baiqian
AU - Catsamas, Stephen
AU - Kolotelo, Peter
AU - Wang, Miao
AU - Lintern, Anna
AU - Jovanovic, Dusan
AU - Bach, Peter M.
AU - Deletic, Ana
AU - McCarthy, David T.
N1 - Funding Information:
Funding: This research was funded by the Australian Research Council, Linkage Project Number LP160100241 titled “Advancing Water Pollution Emissions Modelling in Cities of the Future”, and by our industrial partners including Melbourne Water and South East Water.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/4/27
Y1 - 2021/4/27
N2 - 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.
AB - 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.
KW - Distributed sensing
KW - Electric conductivity
KW - Illegal discharge detection
KW - Low cost
KW - Low power
KW - Real‐time environmental monitoring
KW - Water IoT
KW - Water level measurement
UR - http://www.scopus.com/inward/record.url?scp=85104784978&partnerID=8YFLogxK
U2 - 10.3390/s21093056
DO - 10.3390/s21093056
M3 - Article
C2 - 33925612
AN - SCOPUS:85104784978
SN - 1424-8220
VL - 21
JO - Sensors
JF - Sensors
IS - 9
M1 - 3056
ER -