Water recreation is valuable to people and its value can be affected by changes in water quality. This paper presents the results of a primary data collection effort using a revealed preference survey to elicit coastal New England, USA residents’ values for water recreation and water quality. We combined the survey responses with a comprehensive dataset of coastal attributes, including in-water and remotely sensed water quality metrics for the coast of New England. The results provide an updated willingness-to-pay for a coastal recreation trip of $26-$28 (USD). Using a travel cost model framework, we found water clarity and the bacterial conditions of coastal waters to be practical water quality inputs to economic analysis, available at appropriate scales and meaningful to people and their behavior. Changes in clarity and bacterial conditions affected trip values, with a $4-$5 change for a meter in clarity and $0.13 for a one-unit change, respectively. We demonstrate their utility and the large potential value of improving water quality through welfare analysis scenarios for Narragansett Bay, Rhode Island, and Cape Cod, Massachusetts, USA. The paper discusses generalizable lessons for improving the policy relevance and applicability of water quality valuation studies in the U.S. and worldwide through improved water quality data collection and aggregation combined with application of scalable analysis tools for valuation.

Linking human behavior to environmental quality is critical for effective natural resource management. While it is commonly assumed that environmental conditions partially explain variation in visitation to coastal recreation areas across space and time, scarce and inconsistent visitation observations challenge our ability to reveal these variations. With the ubiquity of mobile phone usage, novel sources of digitally derived data are increasingly available at a massive scale. Applications of mobile phone locational data have been effective in research on urban-centric human mobility and transportation, but little work has been conducted on understanding behavioral patterns surrounding dynamic natural resources. We present an application of cell-phone locational data to estimate the effects of beach closures on visitation to coastal access points. Our results indicate that beach closures on Cape Cod, MA, USA have a significant negative correlation to visitation at those beaches with closures, while closures at a sample of coastal access points elsewhere in New England have no detected impact on visitation. Our findings represent geographic mobility patterns for over 7 million unique coastal visits and suggest that closures resulted in approximately 1,800 (0.026%) displaced visits for Cape Cod during the summer season of 2017. We demonstrate the potential for human-mobility data derived from mobile phones to reveal the scale of use and behavior in response to changes in dynamic natural resources. Future applications of passively collected geocoded data to human-environmental systems are vast.