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StormSense: A Blueprint for Coastal Flood Forecast Information & Automated Alert Messaging Systems
Loftis, Jon Derek Katragadda, Sridhar Rhee, Sokwoo Nguyen, Cuong
Loftis, Jon Derek
Katragadda, Sridhar
Rhee, Sokwoo
Nguyen, Cuong
Abstract
Increased availability of low-cost water level sensors communicating through the Internet of Things (IoT) has expanded the horizons of publicly-ingestible data streams available to modern smart cities. StormSense is an IoT-enabled inundation forecasting research initiative and an active participant in the Global City Teams Challenge seeking to enhance flood preparedness in the smart cities of Hampton Roads, VA for flooding resulting from storm surge, rain, and tides. In this study, we present the a blueprint and series of applicable protocols through the use of the new StormSense water level sensors to help establish a regional resilience monitoring network. In furtherance of this effort, the Virginia Commonwealth Center for Recurrent Flooding Resiliency's Tidewatch tidal forecast system is being used as a starting point to integrate the extant (NOAA) and new (USGS and StormSense) water level sensors throughout the region, and demonstrate replicability of the solution across the cities of Newport News, Norfolk, and Virginia Beach within Hampton Roads, VA. StormSense's network employs a mix of ultrasonic sonar and radar remote sensing technologies to record water levels and develop autonomous alert messaging systems through the use of three separate cloud environments. One to manage the water level monitoring sensors and alert messaging, one to run the model and interface with the post-processed results, and one to geospatially present the flood results.
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2018-10-15
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925558.pdf
Adobe PDF, 925.63 KB
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Physical Sciences Peer-Reviewed Articles, Hydrodynamic Modeling, Internet of Things, Smart City, Global City Teams Challenge, Replicability, Citizen Science, Sea Level Rise
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Virginia Institute of Marine Science