Spatial dimensions of water quality value in New England river networks

TitleSpatial dimensions of water quality value in New England river networks
Publication TypeJournal Article
Year of Publication2023
AuthorsJohnston RJ, Moeltner K, Peery S, Ndebele T, Yao Z, Crema S, Wollheim WM, Besedin E
JournalProceedings of the National Academy of Sciences
Volume120
Paginatione2120255119
Abstract

Households’ willingness to pay (WTP) for water quality improvements—representing their economic value—depends on where improvements occur. Households often hold higher values for improvements close to their homes or iconic areas. Are there other areas where improvements might hold high value to individual households, do effects on WTP vary by type of improvement, and can these areas be identified even if they are not anticipated by researchers? To answer these questions, we integrated a water quality model and map-based, interactive choice experiment to estimate households’ WTP for water quality improvements throughout a river network covering six New England states. The choice experiment was implemented using a push-to-web survey over a sample of New England households. Voting scenarios used to elicit WTP included interactive geographic information system (GIS) maps that illustrated three water quality measures at various zoom levels across the study domain. We captured data on how respondents maneuvered through these maps prior to answering the value-eliciting questions. Results show that WTP was influenced by regionwide quality improvements and improvements surrounding each respondent’s home, as anticipated, but also by improvements in individualized locations identifiable via each respondent’s map interactions. These spatial WTP variations only appear for low-quality rivers and are focused around particular areas of New England. The study shows that dynamic map interactions can convey salient information for WTP estimation and that predicting spatial WTP heterogeneity based primarily on home or iconic locations, as typically done, may overlook areas where water quality has high value.

URLhttps://www.pnas.org/doi/abs/10.1073/pnas.2120255119
DOI10.1073/pnas.2120255119
Citation Keyjohnston_spatial_2023