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October 4, 2024

Q&A: New dataset provides a robust picture of Hurricane Helene’s destruction — and could help design more resilient communities

UW researchers collaborated with people at multiple institutions to collect pre-storm data and place sensors to measure storm surge levels and wave height during Hurricane Helene’s landfall. Shown here is UW undergraduate student Kandai Shimada checking a wave gauge in Cedar Key, Florida, the day before Hurricane Helene made landfall.RAPID Facility/University of Washington

Officials across multiple states in the Southeast are still determining just how wide a swath of destruction Hurricane Helene has left in its wake. Devastating hurricanes are increasing in frequency, and researchers are focused on how to help communities become more resilient.

One way to prepare is to have a full picture of what happens before, during and after a major hurricane. This information provides key details, such as wind speed and wave height during a landfall event, that can inform infrastructure design so it’s better able to withstand these types of storms.

Days before Hurricane Helene descended, University of Washington researchers in the RAPID Facility traveled to Cedar Key, Florida, and Horseshoe Beach, Florida, two small coastal communities near where the hurricane was predicted to make landfall. UW researchers collaborated with people at the University of Florida, the UF Center for Coastal Solutions and the Nearshore Extreme Events Reconnaissance Association to collect pre-storm data and place sensors to measure storm surge levels and wave height during the landfall event. Team members are headed back to Florida next week to collect post-storm data.

UW News asked Michael Grilliot, the RAPID Facility’s operations manager, about the trip and why this research is important.

What data did you collect before the storm arrived?

Michael GrilliotUniversity of Washington

Michael Grilliot: For this project, we collaborated with Nina Stark, an associate professor in the Engineering School for Sustainable Infrastructure and Environment at the University of Florida. To get before-storm data, we did lidar scans of beach fronts and nearby buildings and infrastructure systems. We also used a drone to collect aerial photos of Cedar Key. These images can be stitched together into a 3D model.

To collect data during the event, a team led by Brian Phillips, associate professor in the Engineering School for Sustainable Infrastructure and Environment at the University of Florida, deployed a 33-foot tall tower that measures wind speed, as well as other data.

UW RAPID staff also helped deploy 17 wave gauges and four pore pressure sensors to detect storm surge depth, timing and wave information during the storm. Kandai Shimada, a UW undergraduate student studying electrical and computer engineering who has worked for the RAPID Facility for several years, built 13 of the wave gauges that we deployed. Our wave gauges are almost as robust as commercially available models, but we built them for one-tenth of the cost. If we lose one in the storm, it’s not as much of a financial loss.

Shown here is Michael Grilliot collecting lidar data in Cedar Key, Florida, the day before Hurricane Helene made landfall.RAPID Facility/University of Washington

What do the wave gauges look like?

MG: They are 13 inches long in PVC pipe with a pressure sensor exposed on one end. Unfortunately they look kind of like a pipe bomb, so we put RAPID stickers all over them to try to make them more unassuming, especially when we fly with them. They say “RESEARCH” on them very clearly.

Shown here are some of the wave gauges built by UW undergraduate student Kandai Shimada.RAPID Facility/University of Washington

How do they work?

MG: Pressure increases with water depth, so as the storm surges we see a sharp increase in the recorded pressure. We do have to calibrate the instruments for ambient atmospheric pressure, which changes quite a bit during a hurricane, so there is some post-processing that we have to do before reporting actual water depths.

We attach the gauge to anything we think has a good chance of surviving the storm. This could be a light pole, dock pilings or street signs. We work a lot with private landowners to find locations with limited access to reduce the chance that someone might steal them. Once they are placed, we measure the sensor with a high-precision GPS to know the exact elevation of the pressure sensor.

After the storm and post-processing, we can report water levels as a depth above mean sea level, or, if the sensors are installed over land, simple flooding depth. It’s far easier for people to understand that they would be standing in 9 feet of water if they were standing where the wave gauge was installed instead of reporting something like “13 feet above mean sea level,” which sounds more abstract to people.

What data did you get from the wave gauges during the storm?

A wave gauge two days after Hurricane Helene made landfall. University of Florida researchers took this picture before recovering the gauge and downloading the data.Nina Stark/University of Florida

MG: Our partners at the University of Florida retrieved the wave gauges on Sunday and downloaded the data on Monday.

Peak surge occurs in a matter of hours once the water starts to rise. It almost looks like a heartbeat on an electrocardiogram. The water is much slower to recede, taking all night or all day to reach pre-storm levels. Superimposed on all of this are the smaller ups and downs of the waves. At first glance the data looks quite noisy, but we are able to filter out noise and capture what’s important.

The wave data shows the conditions during the peak surge, which will help modelers understand the energy and forces these waves exerted on buildings on the shore. It also shows us the flood level, which helps us know which level or floor of a building would be experiencing these waves.

Wave and storm surge levels during hurricanes are often predicted based on models, so this dataset can also help researchers validate and better calibrate their predictive models.

There are often a few wave gauges in place that catch storm surges. But this was unique in the fact that we were able to respond on such short notice to place so many sensors in conjunction with the pre-storm lidar and drone imagery. Also, some of the locations would have had no sensors and data available without our wave gauge deployment. That, combined with the wind data from the University of Florida’s tower makes a robust pre-storm and during-storm dataset that has not been captured before.

When you return to the area next week, what will you measure?

MG: We will be looking for a lot of coastal changes. We’ll be flying drone lidar as well as doing ground-based lidar, and collecting more imagery to capture changes to the beach, mangroves and structures. Understanding the changes in beach morphology is equally as important as understanding the damage to the structures. If we can learn what happens to the sediment and seabed, we can better predict what will happen above.

We are also taking the Z-boat this time. This remote-controlled boat will allow us to create a topographic map of underwater depth.

How will this research help communities prepare for future hurricanes?

MG: Ultimately, the hope is that we can build structures that can withstand the forces that we are measuring — both through the damage we see and in the data we captured during the storm. We hope that this will help people better predict storm surges and wave heights, and that people will be able to know how at risk they are, trust that information and act accordingly to save lives and property.

This research is part of a larger effort led by the Nearshore Extreme Events Reconnaissance (NEER) Association in collaboration with the Geotechnical Extreme Events Reconnaissance (GEER) Association, which are both funded by the National Science Foundation.

For more information, contact Grilliot at grilliot@uw.edu and Nina Stark, who is also the associate director of the UF Center for Coastal Solutions and the NEER team lead, at nina.stark@essie.ufl.edu.