Bigger data, Greater Lakes? Monitoring technology, data infrastructures, and the changing science-policy interface for water quality in lower Green Bay, Wisconsin

Abstract

This thesis examines how scientific knowledge, environmental monitoring practices, and data infrastructures have shaped water quality governance in the Lower Fox River and Green Bay region from 1972 to 2024. During this period, the region experienced major shifts in both ecological conditions and policy frameworks for managing water resources – from the Great Lakes Water Quality Agreement in 1972 and establishment of the Areas of Concern (AOC) program to the advent of large-scale restoration efforts under the Great Lakes Restoration Initiative (GLRI). Using a mixed-methods approach, the study integrates a systematic Web of Science literature search with bibliometric, thematic, and topic-modeling analyses, alongside semi-structured interviews with scientists, program managers, and technical experts who produce and use water quality information in the region. The results reveal several long-term trends: (1) growth and diversification in scientific research on nutrients, hypoxia, harmful algal blooms, and legacy contaminants; (2) persistent barriers between knowledge production and policy implementation; and (3) increasing reliance on digital infrastructures, automated monitoring, and data-intensive tools to guide management. Interviews highlight how institutional arrangements, financial and/or resource constraints, and political dynamics mediate the flow of information between researchers and decision-makers. In doing so, these factors shape the uptake and effectiveness of policy interventions like the RAP, TMDL, and watershed-based initiatives. The study findings demonstrate that while technological innovations offer substantial opportunities for adaptive, ecosystem-based governance, they also introduce new forms of “digital friction,” uneven capacities for adoption, and challenges with integration across monitoring programs. The thesis concludes that long-term restoration success depends not only on scientific advancement but on sustained institutional support, inclusive governance structures, and reflexive approaches to data use that recognize the social and political dimensions of environmental knowledge.