SCC-CIVIC-PG Track B: Developing Low Power Wide Area Sensor Networks to Improve Cold Region Disaster Prediction and Management in the Fairbanks North Star Borough

The Arctic and subarctic are experiencing significant environmental shifts from rapid climate change induced warming. The goal of this project is to bring together local organizations engaged in land management and protection and disaster preparedness in the Fairbanks North Star Borough, Alaska, with researchers from the University of Alaska, Fairbanks to develop place-based, data-driven community resilience indicators and interventions that will better enable Alaskans to predict and respond to weather and climate driven events such as thaw-related flooding, subsidence of thawed soils, and wildfire.

These hazards are natural to the local ecosystem, but recent increases in the frequency, intensity, and duration of these events have challenged the resilience of mitigation or prevention strategies. Conventional sensor networks require high energy consumption and large antenna systems to achieve the range required for remote installations, which has resulted in sparse coverage, especially in low population areas.

Newer technologies like Low Power Wide Area (LPWA) networks provide a solution to overcome both cost and range issues, allowing for substantial improvements in observation networks. This project aims to determine the feasibility of using LPWA, support the collection of data types of greatest interest and utility to the community, and improve modeling, planning, and decision making.

Providing consistent, regular observations of crucial climate-related variables in areas of sparse coverage allows for the ability to better inform disaster management, policy, and decision-making mechanisms. Exploring LPWA networks of measurement sensors will expand scientific and technical knowledge crucial for practical applications in planning for climate-change-related threats in cold regions, such as extreme snowfall and flooding and infrastructure damage due to frozen ground thaw.

Students and community members will be trained during the course of the development of the network, and will learn to address climate challenges common to cold regions. Long-term outcomes will be used as materials for STEM education and shared with stakeholders who will directly benefit. The new LPWA networks are expected to serve as an alternative method for rural and suburban communities to collect data, leading to efficient resource consumption, disaster management, and better land use in world-wide cold regions.

Testing this application in the Fairbanks North Star Borough, where data validation is possible, will ultimately benefit many regions that are even more remote and underserved. This project is in response to the Civic Innovation Challenge program, Track B—Resilience to Natural Disasters—and is a collaboration between NSF and the Department of Homeland Security.

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.