An upcoming NSF-funded research project will show that small, cheap sensors can have a big impact: gathering information to allow more accurate flood modeling. Small sensors, that is, and the hard work of many dedicated researchers and community members.
The project is based in Puerto Rico’s capital of San Juan, an area that has historically been severely impacted by storms and flooding—causing millions of dollars of damage and loss of life.
This is in part due to a lack of accurate, real-time information about weather conditions and how they may impact flood conditions on the ground, as well as San Juan’s complex geography—with large mountains, vast river basins, and many communities living right up close to the rivers and the coast.
“Currently, in Puerto Rico, flood forecasts are essentially flying blind,” explained project lead, IRIS affiliate faculty member Felix Santiago-Collazo. “I met with several people there in April of last year at the National Weather Service office, and they were explaining that the only metric they have to predict flooding is through potential rainfall. They check the soil moisture on their monitors—which is also a rough forecast—and then they use their judgement to say, ‘Oh there might be a lot of rain that’s going to fall,’ and then to put up a flood warning.”
This is where the sensors come in. The sensor measures distance and detects obstacles between itself and the ground. It was developed by the FloodNet NYC project to collect real-time flood data across the city.
Santiago-Collazo hopes that these inexpensive sensors will give the National Weather Service office new, more accurate tools for predicting the weather and its threat to the community.
“In tandem with creating and testing our model, we’re going to distribute these sensors throughout the San Juan Bay estuary, including in places that have never had data collected on them before. In general, San Juan has never had this level of data on weather conditions before.”
However, the project doesn’t only want to improve rainfall forecast and its flood hazards: they also plan to tap into local knowledge to create flood models and solutions that are verified by real people on the ground, ensuring that, in conjunction with the new sensors, the models will be as accurate as possible, yielding community-centric flood mitigating solutions.
“We want to make flood models in collaboration with the community. They are the ones that know where and how much it floods during rainfall and hurricane events. They’re the ones living it, not us,” Santiago-Collazo said of the project.
With these models, the researchers will be able to develop what is called “impact-based forecasts,” which will be able to tell specific neighborhoods what to expect and how to handle it in order to remain safe.
“The United Nations’ goal is for everyone to have this type of early warning system. Right now it might say, “You’re going to have high winds, or you’re going to have six to ten inches of rainfall. But when you have a model that’s based on knowledge from locals, instead of saying to that community, “you’re going to have a high rainfall level,” now we’re able to tell you the street and even the addresses on the street that might be impacted, and from what times, and how you should handle it—e.g. take another route, or take shelter. Now we will be providing who’s going to get impacted for how long, and what you should do to stay safe.”
With a community-centered, multi-pronged approach to improving models and collecting data, the project is an innovative look at how grassroots research can help communities thrive. For example, even the sensors themselves will be built and installed by local college students and community residents.
“The sensors are going to be built at the site by college students from the local universities, University of Puerto Rico at Mayagüez and Polytechnic University of Puerto Rico. We’re going to have STEM workshops to show them the electrical and computer engineering they’ll need to build them, and then we’ll pay them for doing the work.”
While even just implementing more accurate flood models has the potential to save lives and livelihoods in San Juan, Santiago-Collazo and his colleagues don’t plan to stop there. Once they have created improved flood models, they’ll begin the third phase of their project: creating natural infrastructure designs to help lessen flooding in areas that need it.
They plan to have two University of Georgia capstone projects that focus on yielding real-life flood mitigation solutions. These solutions will be developed hand-in-hand with Polytechnic University of Puerto Rico students and members of the community.
While plans for this project have been long underway, the boots on the ground work will begin in August, when Santiago-Collazo and colleagues will visit San Juan to have their kickoff meeting and strengthen connections with local stakeholders.
Ultimately, Santiago Collazo hopes that this project paves the way for more like it:
“We want to do two things: Develop flood models and solutions using community knowledge, but also use what we learn from this project to create a guidebook that can tell others who want to do similar things how to do it.”
Good work comes from good teams.
This project has a long list of contributors we’d like to thank, in addition to Santiago-Collazo. Primary researchers on the project include Donald Nelson, UGA, Thomas Mote, UGA, In Kee Kim, UGA, Walter Silva-Araya, UPRM, Matthew Bilskie, UGA, and Ricardo Toledo-Crow, Next Generation Environmental Sensor Lab (CUNY).
Partners include the Caribbean Coastal Ocean Observing System Inc., Centro Caribeño de Aumento del Nivel del Mar: Fideicomiso para Ciencia, Tecnología e Investigación de Puerto Rico, Sea Grant Puerto Rico, Corredor del Yaguazo, Fideicomiso de la Tierra del Caño Martín Peña, Corporación del Proyecto ENLACE del Caño Martín Peña, Grupo de las Ocho Comunidades Caño Martín Peña (G-8), Programa del Estuario de la Bahía de San Juan, Negociado del Manejo de Emergencias y Administración de Desastres, National Weather Service- Southeast River Forecast Center, National Weather Service- Weather Forecast Office San Juan, Colegio de Ingenieros y Agrimensores de Puerto Rico, US Geological Survey- St. Petersburg Coastal and Marine Science Center, the Polytechnic University of Puerto Rico and Next Generation Environmental Sensor Lab (City University New York).