Water Quality Monitoring

Monitoring of ambient conditions plays an essential role in environmental regulation and protection. Monitoring data are used to understand complex environmental systems, to detect trends, and to formulate and enforce regulations. Currently, most monitoring, and particularly water quality monitoring, occurs by infrequent (monthly to weekly) collection of grab samples or by in-situ measurements made with hand-held instruments. This approach provides information as snapshots in space and time and hence can miss potentially significant conditions that occur between measurements.

Technological advances have resulted in sensors that can provide continuous measurements that capture the critical dynamics of environmental systems, including infrequent but ecologically important conditions. These sensors portend many benefits, including more comprehensive data on the environment, standardization, and reduced labor, the transition to continuous sensor-based monitoring is complex. However, a transition to this new technology will require concurrent changes to institutions, norms, social practices, and understandings. The transition to continuous sensors may also affect the social dynamics and processes of the communities that use the data. In addition, the transition to sensor-based data may displace residents who help with monitoring programs and previously had roles in data collection, which in turn may decrease the public’s engagement with places and environmental quality.

The Continuous Oxygen Monitoring in Buzzards Bay (COMBB) Project

The University of Massachusetts Amherst, Buzzards Bay Coalition, Woodwell Climate Research Center, and Woods Hole Oceanographic Institution are jointly undertaking a project to examine the transition to the use of automated sensors for water quality monitoring.

Objectives: This project will contribute to integrated social and technical understandings of the transition to new technologies for water quality monitoring. It will determine how volunteer citizen scientists respond to use of in situ recording sensors rather than grab samples and will test the effects of different procedures for deploying and interacting with sensors on sustained volunteer engagement. The project will also test a new low-cost mobile platform for deploying continuous sensors in coastal waters that might be used and scaled up by groups that monitor water quality. In addition, this project will determine which combinations of and scales for sensor deployment produce data most likely to be used and acted upon by residents, town officials, and government regulators. It will also provide knowledge on how different communities interpret and make sense of more detailed water quality data derived from sensors compared with data from traditional grab samples

Activities: The project team will deploy a network of continuous dissolved oxygen sensors paired with an ongoing volunteer monitoring program led by Buzzards Bay Coalition (BBC) in four estuaries across Buzzards Bay, Massachusetts. Three communities – (1) local residents and environmental organizations; (2) town officials; and (3) state and federal agencies – will be engaged throughout the project to allow testing of how these different communities respond to varying monitoring program designs and data.

UMass Amherst is leading three social science components to this research that address

1. Integratation of new technologies with volunteer citizen-science water quality monitoring programs (Volunteer Water Monitoring Study).
2. Sense-making and communication of the high-temporal resolution data that is obtained from sensors.
3. Effective and efficient location of sensors to achieve the multiple concurrent monitoring and assessment goals of each of the three communities who use water quality monitoring data.

Questions, Suggestions, and Participation: For questions about this research or to volunteer to participate, please contact amilman ‘at’ eco.umass.edu.

This research is based upon work supported in part by the National Science Foundation under Grant No. 2317235 Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. For questions about this research please contact amilman ‘at’ eco.umass.edu.