Measurement to (Im)prove Water Quality: Environmental Performance Measurement in Upper Mississippi River Basin Water and Agriculture Polic

Environmental data can play powerful roles in environmental governance. Monitoring and modeling allow managers to track conditions, trends, and potential futures, while social context shapes how actors use environmental data in policy implementation and assessment. Yet questions remain about how and why environmental information is negotiated and used in water quality policy. The primary goal of this research is to understand the social dimensions of environmental data in the governance of nonpoint source pollution at the land use-water quality nexus, and the ways in which scientific uncertainty informs policy. The dissertation also highlights options to improve the use of environmental data in water quality projects, and to increase the capacity of water governance to adapt to climate change. Focusing first on Soil and Water Conservation Districts (SWCDs) in the Upper Midwestern U.S., I conducted an online survey of SWCD employees (n=286) to examine the institutional, environmental and individual factors associated with staff use of water quality data. I also asked which of those factors increased the likelihood that an SWCD would implement adaptation measures in response to extreme storm events. Next, through a case study of a market-led water quality program in south central Wisconsin, I studied the effects of monitoring and modeling uncertainty on program development and stakeholder buy-in. I draw on these studies to inform the growing social science literature on how environmental measurement and prediction influence public program formation and implementation, and in turn, how policies influence data production.;I found evidence for a positive association between information use and employees' prosocial motivation, or the belief that they helped people and natural resources through their job, as well as the perceived trustworthiness of data, and staff discretion to prioritize programs locally. SWCD employees who were concerned about climate change and used precipitation projections were more likely to work in an office that implemented precipitation adaptation measures. Finally, water quality measurement uncertainty led to an iterative process of deciding how monitoring and modeling would be used to track and prove program progress in the local program case study.