Coastal communities face large challenges monitoring water quality in multiple places and frequently enough to identify water quality problems and to document improvements following investments in programs or infrastructure that improve water quality. Traditional water quality monitoring is conducted by periodic collection of physical water quality samples. However, conditions that lead to large water quality and biological impacts (such as periods of low oxygen during heat waves or following periods of high river discharge) occur infrequently and are not well captured by existing monitoring programs that sample only periodically. This makes it hard for citizens to document problems and for managers to identify appropriate water quality actions. New continuously-recording water quality sensors now have the potential be deployed across multiple locations to provide time-series and information to better identify water quality impacts and potential solutions. Dissolved oxygen is a key water quality parameter that can now be measured with reliable, low-cost sensors. However, the transition to continuous sensor-based monitoring is complex and will require concurrent changes to the institutions that conduct monitoring, their norms and social practices, and the way the public and regulatory agencies use this new form of water quality data.

This project will determine how volunteer citizen scientists respond to use of in situ recording sensors rather than grab samples, and test how volunteers respond to different procedures for deploying and interacting with sensors. The project will also test low-cost mobile platforms for deploying sensors in coastal waters. It will focus on three communities connected to water quality in the watershed of Buzzards Bay, Massachusetts: (1) local residents who live within coastal watersheds, including many who volunteer to collect water samples; (2) town officials responsible for water quality planning and regulation; and (3) state officials responsible for setting and enforcing water quality regulations. It will determine which combinations 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. Understanding this transition—both technologically and socially—will help advance the use of water and environmental sensors by the many organizations across the U.S. that conduct environmental monitoring and that might in the future deploy automated continuous environmental sensors.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.