Scott Pruitt, EPA Administrator’s assertion that “global warming might be beneficial” may be reassuring to some, but others living close to the coast prefer the safety of an early warning when they might be flooded from rising sea levels.
Predicting floods from storm surges, rain, hurricanes and tides over miles of coastline is hard. How do your monitor water levels over such a broad area? How can floods be predicted with these data streams? How can thousands of people be alerted? The Virginia Institute of Marine Science (VIMS) is pioneering an innovative approach that combines IoT sensors, advanced mapping and Alexa.
Hampton Roads is a large coastal area between SouthEastern Virginia and NorthEastern Carolina that’s vulnerable to flooding. VIMS StormSense helps local coastal communities prepare for the disastrous impacts of sea level and coastal flooding. Derek Loftis, Assistant Research Scientist VIMS, and Sridhar Katragadda, System Analyst, City of Virginia Beach explained their award winning design.
The shoreline has changed in response to natural storm events and commercial activity as Norfolk has developed into one of the world’s largest and busiest commercial harbors. As the shoreline has been developed over the centuries to suit the needs of a growing population, the volume of water displaced by ‘new land’ must be accommodated elsewhere in the estuary. Citizen science with crowd-sourcing effort with the ‘Sea Level Rise’ mobile app have undertaken the task of collecting maximum flooding extent measurements of the flooding that routinely plagues Norfolk and the rest of Hampton Roads.
Many of the places the flood extents occupy can be linked to the former creek beds of previous centuries. Naturally, while a wall or bulkhead may be reinforced or elevated to act as a sea wall, when floodwaters are high enough during extra high tides, these lower elevation legacy creek beds will be the first areas to flood during even minor storm events. An interactive map of flood vulnerabilities demonstrates the anticipated inundation extents as a result of storm surge from a category 1 – 4 hurricane. These estimated extents are helpful in terms of planning and emergency preparedness. It’s important to research the combined effects of tide and rainfall, which commonly accompany significant storm surges. StormSense was used in 2015 to predict flooding up to 36 hours prior to flooding during the September ‘King Tide’ flooding events.
A network of bridge-mounted IoT water level sensors from VALARM are deployed in rivers, estuaries and non-tidal areas across Hampton Roads to monitor water levels. This map shows the sensor deployments. Time-stamped water level readings along with the sensor’s geo-coordinates are transmitted to the cloud via cellular broadband and LoRaWAN. This data is mapped by StormSense in real-time with ESRI ArcGIS Online.
Three types of sensors are being used:
- Senix ultrasonic sensors
- Flowline ultrasonic sensors
- Flowline radar sensors
Both ultrasonic and 26 GHz pulse radar “level” or distance sensors by Flowline and Senix are deployed in this project and send data to the Valarm Tools cloud servers over 3G/4G cellular networks.
Flood prediction models
Tide levels, storm surges and rainfall can all contribute to a flood. VIMS analyzes this datastream and water level data from the U.S. Geological Survey (USGS) using Microsoft Power BI to predict floods. Hydrodynamic models predict floods from storm surge and rainfall. The models have been used in the past with success in accurately predicting timing, depths and extent of flooding. Cities in the program pay about $20/month for both the sensor and data transmission for this advance warning system. A small price to pay for the reduction in property damage and injuries!
Automated flood alerts send threshold notifications when water levels reach critical thresholds for nuisance flooding of roadways, to certain thresholds of structures being affected by flooding. These alerts will shortly be offered to the general public as well. An Alexa skill named “storm sense” is used to respond to requests about water levels and flood warnings. The skill first has to be ‘enabled’ by the user on their Alexa or Reverb app in order to work. The skill interacts with the aggregated streaming data from the sensor networks that is stored in AWS DynamoDB and AWS Lambda – this supports the interaction between the data stream and Alexa.
A user can simply ask Alexa “ask storm sense water level at London bridge?”. “Water level” and “London bridge” are the variables extracted from this verbal query and used as parameters to query the data stream. A verbal response is generated from multiple parameters and spoken by Alexa. Chatbots are being considered for future alerts that could be delivered on Facebook, Skype and Slack.
VIMS’ StormSense uses a small investment in IoT sensors, ArcGIS mapping and Alexa skills to save millions in damages for thousands of Hampton Roads residents. “Global warming may be beneficial” as Scott Pruitt says, but most people would prefer to stay dry.
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