Building Digital Infrastructure and Communities to Assess Risk of Drinking Water Hazards Caused by Hurricanes Maria and Florence

Hurricanes and floods are increasing in occurrence, duration, and magnitude; there is growing interest by communities to engage in research with outcomes usable to protect and educate themselves against water hazards. The recovery period is an important opportunity to engage the public in research to assess drinking water related health risks and better prepare for future water security for the most vulnerable populations. Our aim is to create a synthesized data and software system to advance our understanding of how digital and physical infrastructure and user-driven information can be integrated on a collaborative platform for ongoing research that reduces the impacts of natural disaster. Current data collection includes assessment of data and cyberinfrastructure needs as well as training for archiving new datasets for Hurricane Florence and Hurricane Maria. Datasets include hurricane observations, flood maps, storm track forecasts, National Water Model forecasts, drinking water quality sampling (de-identified), and other public data sources (non-profit,govt. open and crowd-sourced datasets). The hydrologic research community repository, HydroShare, will provide a point of access for research findings, with interoperability designed to link to data models and repositories used by Natural Hazards, Environmental Health, and Environmental Engineering communities in a consistent, documented format. This work will provide a network of water-domain data research expertise that can be leveraged to advance public education and disaster coordination. Synthesis of these datasets and educational tools are expected to generate analyses and visualization of hurricane impacts to address ongoing needs and prepare for the next hurricane season. Public data user engagement, research community support, and ongoing development are key to continuous development and usability of the analysis tools and datasets. Our study uses Hurricanes Florence and Maria datasets and case studies from North Carolina and Puerto Rico, to improve how we share knowledge and build capacity to support communities around the world who may use digital infrastructure to foster self-resiliency.