Developing a Sensor-driven, Citizen Science Approach to Hazard Detection and Warning in Rural Communities

For many communities, landslides represent catastrophic and difficult-to-predict hazard. Predicting landslides is a significant challenge, as soil conditions, localized rainfall, patterns of human development, and many other factors converge to trigger slides in ways still not well understood by the geoscience community. Meanwhile, landslide warning and response is fraught with challenges. Citizens can become desensitized by too many "false alarms", or warnings not relevant to their locale. Also, different social groups have different levels of trust in governmental authorities, science, and each other. Risk management thus requires significantly improved understanding of how to communicate warning to diverse communities and how to prepare them to respond adequately to this information. Using Sitka, Alaska as our example, this planning grant will expand a national network of physical and social scientific collaborators and link them to our existing science and community connections in Sitka and elsewhere in Alaska. The planning effort will deepen the team?s shared understanding of the natural science of hazard prediction and the social science and information technology of warning and response systems.

In order to improve the necessary shared understanding of landslide prediction, warning, and response, the physical and social science domains must be coupled and co-evolve as effective warning systems depend on accurate predictive capabilities. This project will connect geoscientists, social scientists, and local stakeholders together to determine the critical research questions around effective, needs-based hazard prediction, warning, and response. Through this work, we will accomplish the following goals: (1) prepare to deploy a landslide monitoring system, (2) plan to leverage data from sensors to improve predictive power for landslides, (3) create a framework to improve understanding of risk perception and communication across social networks in remote and diverse communities, and (4) lay the groundwork for a project that would leverage improved landslide prediction capacity and increased understanding of risk perception and communication to implement a warning system. The project will use the following approaches to accomplish this work: (1) meetings and engagements with local and national geoscientists, (2) methodological and technological survey of citizen science and distributed sensors, (3) application of risk perception, social network, and cultural measurement methods from health research, and (4) collaborative grant-writing. We expect the following impact for the planning grant and follow-on work: (1) improved techniques for hazard-related citizen science; (2) better technical and social approaches to hazard warning systems in diverse communities; (3) improved understanding of risk perception and community resilience to natural hazards in rural and remote communities, including those with Native American populations; (4) improved understanding of landslide hazard prediction through connecting science with regional and national datasets.