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.
Current commercial sensors to monitor water flow velocities are expensive, bulky, and require significant effort to install. Low-cost sensors open the possibility of monitoring storm and waste water systems at a much greater spatial and temporal resolution without prohibitive costs and resource investment. To aid in this, this work developed a low-cost, low-power velocity sensor based on acoustic Doppler velocimetry. The sensor, costing less than 50 USD is open-source, open-hardware, compact, and easily interfaceable to a wide range of data-logging systems. A freely available sensor design at this price point does not currently exist, and its novelty is in enabling high-resolution real-time monitoring schemes. The design is capable of measuring water velocities up to 1200 mm/s. The sensor is characterised and then verified in an in-field long-term test. Finally, the data from this test are then used to evaluate the performance of the sensor in a real-world scenario. The analysis concludes that the sensor is capable of effectively measuring water velocity.
We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within ±6% and ±7 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered.
Illicit discharges in urban stormwater drains are a major environmental concern that deteriorate downstream waterway health. Conventional detection methods such as stormwater drain visual inspection and dye testing all have their fundamental drawbacks and limitations which might not easily locate and eliminate illegal discharges in a catchment. We deployed 22 novel low-cost level, temperature and conductivity sensors across an urban catchment in Melbourne for a year to monitor the distributed drainage network, thereby detecting likely illicit discharges ranging from a transitory flow with less than 10 minutes to persistent flows lasting longer than 20 hours. We discuss rapid deployment methods, real-time data collection and online processing. The ensemble analysis of all dry weather flow data across all sites indicates that: (i) large uncertainties are associated with discharge frequency, duration, and variation in water quality within industrial and residential land uses; (ii) most dry weather discharges are intermittent and transient flows which are hard to be detected and not simply due to cross-connections with the sewerage network; (iii) detectable diurnal discharge patterns can support mitigation efforts, including policies and regulatory measures (e.g., enforcement or education) to protect receiving waterways; and, (iv) that it is possible to cost effectively isolate sources of dry weather pollution using a distributed sensor network.
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