Collaborative Research: Socio-economic Patterns, Public Perceptions, and ClimateVulnerabilities of Water Resources and Quality

Lead PI: Dr. William J. D'Andrea

Unit Affiliation: Biology and Paleo Environment, Lamont-Doherty Earth Observatory (LDEO)

December 2021 - November 2024
Project Type: Research

DESCRIPTION: Access to clean water is a fundamental requirement for a healthy society. Numerous water safety crises in the past decade have shown that access to safe drinking water is not a guarantee, however. Moreover, there is community- and individual-level heterogeneity in relative vulnerability to water problems. Individual characteristics are likely to affect perceptions of water, in turn affecting decisions surrounding water use and associated health outcomes. This project brings together an interdisciplinary team of scientists to examine social, behavioral, health, and climatic issues related to water resources. In addition to developing capacity at a minority-serving institution, the project advances undergraduate teaching and training through curricular development and hands-on research opportunities.

The project tests social science theories positing that ecological and social factors work together to affect water and climate vulnerability. Research objectives include examining the influence of social, economic, and political factors in water quality remediation efforts in a context with contemporary and historical variation in deployment of such efforts; and providing an analytical framework transferable to other environmental remediation projects. To do so, this project documents perceptions of water among diverse stakeholders, and how these perceptions interact with individual and community characteristics. The project also analyzes and provides data to document the full range of climate variability to layer results within broader historical climatic fluctuations. Importantly, this climate history will provide context for the lived experiences of people in the region over space and time and allow improved modeling to anticipate future changes in precipitation and water access.