The StormSense Project is an inundation forecasting research initiative funded by the National Institute of Standards and Technology (NIST). StormSense is funded through a Replicable Smart City Technologies grant awarded to the City of Newport News and Dr. Derek Loftis at VIMS, as announced by The White House in September 2016. The objective of StormSense is to enhance the capability of communities to prepare and respond to the disastrous impacts of sea level rise and coastal flooding in ways that are replicable, scalable, measurable, and make a comparable difference worldwide.
StormSense advances the field of emergency preparedness for flooding resulting from storm surge, rain, and tides, via a network of 'Internet of Things' (IoT)-enabled water level sensors in collaboration with the hydrodynamic flood modeling and forecasting capabilities of the Virginia Institute of Marine Science (VIMS) and their Tidewatch Network. Prior to the advent of StormSense, Hampton Roads, VA, had a total of 6 publicly-available water level sensors within its 527 mi² land area. These 6 sensors were installed and maintained by federal entities, and have been found to be tremendously valuable resources for determining inundation timing and depths and for verifying the accuracy of predictive models. The sensors verify VIMS’ hydrodynamic models using conventional statistical metrics of R2, Mean Absolute Error, and Root Mean Squared Error, between predicted and observed water levels.
Technological advances in computational efficiency, hydrodynamic modeling, improved digital elevation models enhanced with LiDAR, and cloud-based analytical platforms necessitated a denser network of sensors to better inform and validate VIMS’ predictive models. StormSenseVB began when Virginia Beach’s Public Works department funded a project to support the USGS to install 10 new water level sensors with weather stations to measure water level, air pressure, wind speed, and rainfall, to help key decision makers and citizens better understand flooding in the City. The sensors were installed in 2016 at an approximate cost of ~$38k/sensor. StormSense was funded by NIST in September 2016 to employ IoT solutions throughout Hampton Roads to purchase and install an additional 24 water level sensors at ~$3000 per sensor in Newport News, Norfolk, and Virginia Beach. As a result, StormSense throughout Hampton Roads, and StormSenseVB within Virginia Beach, have brought the total number of publicly-accessible water level sensors in the region from 6 to 40, resulting in a 5x increase from 2016 to 2017. Also, the IoT sensor approach is cost-effective and replicable, as StormSense’s IoT sensors are ~98% as accurate as the federal sensors, at <1/10th the cost.
Recurrent flood observation data maps
Citations for Source Content
Loftis, J.D., Wang, H., Forrest, D., Rhee, S., Nguyen, C. (2017). Emerging Flood Model Validation Frameworks for Street-Level Inundation Modeling with StormSense. SCOPE '17 Proceedings of the 2nd International Workshop on Science of Smart City Operations and Platforms Engineering, 2(1), 13-18. PDF
Loftis, J.D., Katragadda, S., Organski, T., Spencer, K., Nguyen, C., Rhee, S. (2018). StormSense: An Adaptive new IoT Sensor Network and data platform. (Submitted to Marine Technology Society Journal. PDF
Loftis, J.D., StormSense.com. (2017) StormSense Project: Forecasting Flooding from Storm Surge, Rain, and Tides