Water quality in fresh water lakes across the United States is under threat due to intensive agricultural practices, climate change and urbanization. Management of these resources requires a comprehensive understanding of the tradeoffs between enhanced water quality and economic decisions along different margins. In this dissertation, I focus on recovering valuation estimates and latent preferences for water quality for three different groups of water quality beneficiaries: near lake homeowners, recreational fishermen and beach-goers. The theoretical framework and empirical analyses developed here are timely and relevant in informing both scientific and policy debates. This work not only helps policymakers better understand how people perceive and respond to water quality changes but also extends the non-market literature by providing a new method to value large, non-marginal changes in environmental quality. In Chapter 1 I provide a brief overview of the hedonic pricing model, one of the most common methods to value water quality changes, and the key insights that have emerged from this literature. Despite potentially large policy implications at regional, national, and global scales, very little is known about the damages caused by harmful algal blooms (HABs). This is particularly concerning as the impacts of urbanization and runoff are expected to amplify due to rising summer temperatures and more frequent, excessive rainfall events caused by global climate change. Subsequently, I fill this void within the literature by recovering a comprehensive set of HAB valuation estimates in Chapters 2 – 5. I begin by focusing on the impact HABs have on recreating behavior. Using a count data model and a recreational fishing license database, I find in Chapter 2 that fishing expenditures decrease by $2.25 to $5.58 million along the Lake Erie shoreline when algal conditions surpass the World Health Organization’s moderate health risk advisory threshold of 20,000 cyanobacteria cells/mL. I couple this estimate with beach-goer welfare losses in Chapter 3. My latent class model reveals significant preference heterogeneity exists between day-trippers who fish and/or boat and those who swim or wade in the water. In particular swimmers tend to be warier of E. coli, while fishermen and boaters are more averse to algae. In Chapters 4 and 5, I examine the impact that HAB concentrations have on surrounding housing markets. In Chapter 4 I find that property values drop between 11% and 22% when water conditions become so poor that a no-drinking advisory is issued. These losses are limited to houses within 500m – 600m of a lake and are not exacerbated by additional water quality degradation, suggesting that policies designed to eliminate, rather than constrain, algae will likely have greater benefits to surrounding residents. I build on these initial results in Chapter 5 and develop a methodology to recover a demand schedule for water quality using housing transactions from multiple markets and an instrumental variable developed from hydrological processes specific to the Lake Erie watershed. The recovery of a demand function provides additional policy insight by revealing willingness to pay measures across all possible water quality outcomes, allowing policymakers to measure the welfare implications of large-scale water quality changes. In Chapter 6 I expand my analysis outside of Ohio by recovering region and time-period specific water quality demand bound estimates using two nationwide databases and imperfect instruments rooted in Tiebout sorting behavior. I exploit this intertemporal and spatial heterogeneity to further our understanding of the tradeoffs homeowners are willing to make for improvements in water quality. My analysis reveals substantial differences in household well-being across three large regions within the United States due to climate-driven water quality change. This heterogeneity is not reflected within the pooled demand function estimate, however, potentially leading to a substantial undervaluation of environmental quality in some areas and an overvaluation in others. Finally, I conclude by discussing two possible research extensions, both of which involve merging concepts from the non-market valuation and dynamic resource management literature. In particular, I believe the water quality demand functions recovered in Chapters 5 and 6 can be embedded within a dynamic framework to: 1) analyze the cost-effectiveness of various land use management strategies aimed at curbing algal growth in the western basin of Lake Erie and 2) better understand the coupled relationship between land development patterns and the provision of water quality ecosystem services. Overall, my research provides key insights on the damages caused by the emergence and growth of HABs. I find HABs to have an adverse impact across multiple markets and across multiple stakeholder groups, resulting in hundreds of millions of dollars in losses each year. These damage estimates are essential for future policy development as they can be coupled with existing management costs to better understand the tradeoffs that exist across various strategies aimed at curbing HAB growth. In addition to providing water quality valuation estimates, I develop novel methods which allow policymakers to better understand where and to what extent we should be reacting to environmental quality changes. My research highlights the importance of recovering water quality demand functions; in particular, I find the slope of these functions to be insightful in determining how households react to water quality changes regardless of their starting environmental quality condition. This information is essential to policymakers as it allows for counterfactual policy analysis and improves our understanding of the losses (gains) attributed to large reductions (improvements) in water quality.