Ohkay Owingeh, NM
Low-Cost Efficient Wireless Intelligent Sensors (LEWIS) for Greater Preparedness and Resilience to Post-Wildfire Flooding in Native American Communities
Organization: University of New Mexico
Primary Investigator: Fernando Moreu
Research Track: Climate & Environmental Resilience
Native American Pueblo communities will design, build and implement their own Low-Cost Efficient Wireless Intelligent Sensors (LEWIS) that will inform communities of trends and thresholds that can assist in managing wildfires and providing early warning when fires and floods occur. This project will develop a Nationwide community of practice that shares ideas, designs, and applications for resilience in Tribal communities by co-developing capacity and decision-support tools.
Ohkay Owingeh, High Water Mark and UNM Create Sensors that Measure Rain and Flooding
newmexicoconsortium.org
NSF Abstract
The combined impacts of wildfires and subsequent post-wildfire floods have changed the lives and landscapes of New Mexico?s Native American Communities over the past 20 years. Native American communities, national and state agencies, university researchers, and others, have all stepped up to contribute to recovery efforts. Beyond recovery, researchers have also begun to initiate the process of fundamentally changing our approaches to building resilient communities and landscapes by learning from our tribal partners and civic partners. Specifically, tribal communities have indicated that they can benefit from building and designing their own sensor networks at a low cost, as opposed to using commercial off-the-shelf (COTS) sensors. This paradigm shift empowers the community as the sensor designer and builder: a new approach to enhancing community resilience. Community members of the Ohkay Owingeh Pueblo will co-design, co-build, and implement their own Low-Cost Efficient Wireless Intelligent Sensors (LEWIS) networks. This self-built, customized, and distributed sensor network will inform the community of trends and thresholds in landscapes that can help to prevent wildfires and provide critical information to early warning systems when floods occur. Our long-term vision is to develop scientific practice and evidence that will enhance the resilience of communities. The Ohkay Owingeh Pueblo in New Mexico will co-plan this project with researchers from four academic units of the University of New Mexico, consultants and evaluators, educators, national labs, the New Mexico Department of Transportation represented by the Tribal Liaison, and Native American Leaders in Native American Resilience in New Mexico.
This research in action project addresses a critical area of need in the American Southwest ? building resilience of tribal communities to the natural hazards of wildfires and post-wildfire floods. This community-based project will create a blueprint and framework for incorporating sensor data into decision support platforms. Participation from tribal youth will also increase the long-term sustainability of this project by building technical capacity within the community, which enables workforce development and training. The research will contribute to the following fields: (1) advancement of knowledge of the processes and outcomes for co-generation of knowledge between Native American communities and academic researchers; (2) incorporating place-based knowledge for co-developing resilience indices from LEWIS networks developed by the community, and decision support platforms; and (3) exploration of novel approaches to management, security, and selective sharing of data in ways that support the advancement of science, build community resilience to natural hazards, and respect concerns over data sovereignty. This project is part of the CIVIC Innovation Challenge which is a collaboration of NSF, the Department of Energy's Vehicle Technology Office, and the Department of Homeland Security's Science and Technology Directorate and Federal Emergency Management Agency.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.