After every natural disaster, it is difficult to answer elementary questions on how to provide high quality water supplies and health services. There is no existing digital infrastructure to scientifically determine the hurricane impact on drinking water quality, the severity of a hazard to human health, or baseline data on the sophistication, connectivity, and operations of the distributed physical and related digital infrastructure systems. We test data publication mechanisms after Hurricane Maria in Puerto Rico to understand risks to human health by assessing the spatial and temporal presence of waterborne pathogens in multiple types of systems, demonstrating usability of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) HydroShare system as a clearinghouse for data related to Hurricanes Maria, Harvey, and Irma, and developing a prototype cyberinfrastructure to assess environmental and public health impacts. Our resulting archive and research software engineering practices provide a prototype cyberinfrastructure system for researchers to study natural disasters.

Recovery efforts from natural disasters can be more efficient with data-driven information on current needs and future risks. We advance open-source software infrastructure to support scientific investigation and data-driven decision making with a data sharing system using a water quality assessment developed to investigate post-Hurricane Maria drinking water contamination in Puerto Rico. One limitation to effective disaster response is easy and rapid access to diverse information about available resources and maps of community resource needs and risks. Research products are made Findable, Accessible, Interoperable, and Reproducible (FAIR) using HydroShare, a collaborative online sharing platform. Curating a central repository of assembled research data has the potential to greatly facilitate coordinated disaster responses of all types, with opportunities to improve planning, preparedness, and monitoring of the recovery process.

Almost Like Maria Team Members: Christina Bandaragoda, University of Washington Miguel Leon, University of Pennsylvania Jim Phuong, University of Washington Graciela Ramirez-Toro, Inter American University of Puerto Rico Kelsey Pieper, Virginia Tech William Rhoads, Virginia Tech Tim Ferguson-Sauder, Olin College Jeffery Horsburgh, Utah State University Jerad Bales, Consortium of Universities for the Advancement of Hydrological Science Sean Mooney, University of Washington Martin Seul, Consortium of Universities for the Advancement of Hydrological Science Kari Stephens, University of Washington Erkan Istanbulluoglu, University of Washington Julia Hart, University of Washington Marc Edwards, Virginia Tech Amy Pruden, Virginia Tech Virginia Riquelme, Virginia Tech Ishi Keenum, Virginia Tech Ben Davis, Virginia Tech Emily Lipscomb, Virginia Tech David Tarboton, Utah State University Amber Spackman Jones, Utah State University Eric Hutton, Cooperative Institute for Research in Environmental Sciences Gregory Tucker, University of Colorado Boulder Scott Peckham, University of Colorado Boulder Christopher Lenhardt, Renaissance Computing Institute William McDowell, University of New Hampshire David Arctur, University of Texas at Austin