RAPID: Almost Like Maria
On September 20, 2017, Hurricane Maria made landfall in Puerto Rico as a first Category 4 storm. With sustained winds of 155 miles per hour, just two miles per hour shy of a Category 5 classification, and three times the rainfall of Hurricane Harvey, Hurricane Maria decimated Puerto Rico’s infrastructure, denying 3.1 million people power or access to clean water.
While ongoing recovery efforts seek to restore electricity and access to clean water on the island, the National Science Foundation (NSF) has awarded over 50 new grants totaling nearly $5.3 million to help scientists understand how such disasters happen, how to best respond, and how to rebuild. In collaboration with Virginia Tech, University of Pennsylvania, Utah State University, University of Colorado-Boulder, and the Consortium of Universities for the Advancement of Hydrological Science Inc. (CUAHSI), FWI researchers at the University of Washington are the recipients of one such Rapid Response Research (RAPID) grant.
“Recovery efforts from natural disasters can be more efficient with data-driven information on current needs and future risks,” says project participant Dr. Christina Bandaragoda. The RAPID: 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 and analyzed for various microbial, chemical, and biological water quality parameters such as total coliform, E. coli, metal contamination, antibiotic resistant genes (ARGs), nitrogen speciation, pharmaceutical pollution, and a comprehensive panel of opportunistic pathogens frequently found in freshwater (e.g., Leptospira, Legionella, Giardia, etc.).
Following the collection of spatially- and temporally-resolved water quality data, the second objective of the project is to develop and demonstrate the usability of a centralized cyberinfrastructure 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 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 their website. You may 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.
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.
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.