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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.

SUBMITTER: Shi B

PROVIDER: S-EPMC8123848 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Recent transitions in the governance of urban stormwater, specifically developments that leverage the environmental and social benefits of green infrastructure (GI) including infiltration and neighborhood stabilization, often require capacities beyond those of any single municipal- or regional-scale organization. In many cities, transitions toward green stormwater infrastructure have been shepherded by networks of individuals spanning a diversity of organizations from governments to NGOs. These networks are often informal, that is, not established by legal mandate, governing authority, or formal agreement, and are often striking for their lack of formal hierarchy or formal leadership. Previous scholarship has revealed the importance of leadership in the development and efficacy of these multiorganizational, cross-sector environmental governance networks, but research has yet to empirically investigate and characterize informal network leaders within the context of GI for stormwater mitigation. To address this gap, we designed and administered a social network analysis (SNA) survey to individuals in a regional network of GI stormwater management professionals in and around Cleveland, Ohio USA. We collected network data on individual relationships, including collaboration and trust, and tested the impact of these relationships on peer-recognition of leaders in the GI network. Our findings suggest that network size, frequency of collaboration, and individual position within the network-specifically, betweenness centrality and openness-defined and likely supported leaders in the stormwater governance network. Leaders in this non-hierarchical, multi-institution context were more likely to be women and brokerage roles within the network benefitted women, not men, which contrasts with previous findings from research on single-organization and corporate networks. The implications of this research suggest that informal environmental governance networks, such as the GI network investigated, differ substantially from the generally more hierarchical networks of organizations. This finding is useful for municipalities and regional authorities grappling with complex environmental challenges, including transitions in strategies to manage excess stormwater for the protection of municipal drinking water sources and urban freshwater ecosystems.

Dataset Information

A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks.

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