By Julia Hart for Freshwater

Photo Courtesy of Mandalit Del Barco/NPR Richard Colón, better known by his stage name Crazy Legs at his home in Isabela, Puerto Rico, shows the before-and-after of the water filtration system he's helping deliver to people in remote areas. This photo originally appeared in https://www.npr.org/2017/10/01/554803408/richard-crazy-legs-col-n-returns-to-puerto-rico-with-a-clean-drinking-water-miss

Photo Courtesy of Mandalit Del Barco/NPR. Richard Colón, better known by his stage name Crazy Legs, at his home in Isabela, Puerto Rico, shows the before-and-after of the water filtration system he’s helping deliver to people in remote areas. This photo originally appeared in NPR.

On Sept. 20, 2017, Hurricane Maria made landfall in Puerto Rico as a Category 4 storm. With sustained winds of 155 miles per hour, just two miles per hour shy of a Category 5, Hurricane Maria decimated Puerto Rico’s infrastructure, denying 3.1 million people power or access to clean water.

Alongside efforts to restore electricity and access to clean water on the island, the National Science Foundation has awarded over 50 new grants totaling nearly $5.3 million to help scientists understand how such disasters happen, how to best respond to them, and how to rebuild afterwards. In collaboration with Virginia Tech, the University of Pennsylvania, Utah State University, the University of Colorado-Boulder, and the Consortium of Universities for the Advancement of Hydrological Science Inc., Freshwater researchers at the University of Washington have received one such Rapid Response Research (RAPID) grant for the Almost Like Maria Project.

The Almost Like Maria Project seeks to develop and advance open-source software infrastructure to support scientific investigation and data-driven decision-making following natural disasters like Hurricane Maria. Widespread disruption of water treatment processes following Hurricane Maria pose significant human health risks.

Therefore, the first objective of the project is to assess water samples for water-borne pathogens and chemical contaminants. Water samples from drinking, surface, and waste-water systems across Puerto Rico will be collected in collaboration with public water supply utilities. The samples will be screened for presence of various microbial, chemical, and biological water quality parameters such as total coliform, E. coli, metal contamination, antibiotic resistant genes, nitrogen speciation, pharmaceutical pollution, and a comprehensive panel of opportunistic pathogens frequently found in freshwater (e.g., Leptospira, Legionella, Giardia, etc.).

The second objective of the project is to develop and demonstrate the usability of a centralized clearing house to house selected datasets related to disaster response. Data collected following a natural disaster is often heterogeneous with many different data types: water quality, hydrologic data, population health assessments, disease outbreak maps, etc. Few projects have sought to archive and integrate disparate datasets of this nature into a single cyberinfrastructure workflow before.

Researchers at the various collaborating institutions will use an online, collaborative hydrologic information system called HydroShare to achieve this goal. HydroShare allows for the sharing of a wide variety of hydrologic data types, models, and code and seamlessly integrates time series with spatially-distributed environmental data.

HydroShare will serve as a prototype cyberinfrastructure for all data relevant to Hurricane Maria water quality and recovery efforts, providing data storage, curation, and analysis tools. For more information about the HydroShare platform, visit www.hydroshare.org where you can collaborate and join the new public group Puerto Rico Water Studies, where researchers will be archiving water data specific to Puerto Rico, or the CUAHSI 2017 Hurricane Data Community group for researchers interested in studies of Hurricanes Harvey, Irma, and Maria.

“Recovery efforts from natural disasters can be more efficient with data-driven information on current needs and future risks,” says the project’s principal investigator, Dr. Christina Bandaragoda, “we are researching how to improve the infrastructure that provides this information, with a focus on drinking water data”.

It is the researchers’ hope that the tools developed using this RAPID grant inform future software infrastructure needs when it comes to natural disaster response and recovery. The project thus serves to not only document post-disaster conditions, but also develop a process to track the recovery over time and contribute to community resilience in the future.

Project researchers:

Christina Bandaragoda, Civil & Environmental Engineering, University of Washington, eScience Institute affiliate

Erkan Istanbulluoglu, Civil & Environmental Engineering, University of Washington

Sean Mooney, Biomedical Informatics and Medical Education, University of Washington

Jimmy Phuong, Biomedical Informatics and Medical Education, University of Washington

Kari Stephens, UW Medicine, Psychiatry and Behavioral Sciences, University of Washington, eScience Institute Steering Commitee