With the acceleration of climate change, floods are becoming more frequent and less predictable. In 2018, flooding accounted for 24% of all worldwide deaths related to natural disasters, second only to earthquakes. Flash floods, which involve the rapid flooding of low-lying areas, are particularly hazardous. Just 6 inches of fast-moving flood water can knock over an adult and 12 inches of rushing water can carry away most cars. The power of a flash flood increases linearly with water depth and with the cube of water velocity, both parameters that vary greatly by location. As a result, conventional techniques are inadequate for assessing flash flood threat and need to be supplemented with localized, real-time methods. The goal of the project is to prototype technologies that can assess flash flood threat at a specific location in real-time so that appropriate warnings can be generated for impacted people. This is done through robust measurements of water depth and water velocity. Water depth is measured acoustically, via an ultrasonic range-finding sensor and an Arduino. Water velocity is measured optically, via two implementations of large-scale particle image velocimetry (LSPIV): a smartphone application and a desktop software package. Early testing in a flume demonstrates both the viability of this approach and opportunities for improving measurement reliability. The technologies prototyped in this study, namely ultrasound depth sensing and LSPIV velocity measurement, can be incorporated into low-cost, weather-resistant devices that can be easily installed overlooking flood-prone locations for real-time assessment and communication of flash flood threat.

1. Real-Time Assessment of
Flash Flood Threat Using
Optical-Acoustic Technology
Anika Fuloria, The Harker School, San Jose, CA 95129
Dr. Marian Muste, IIHR - Hydroscience and Engineering, University of Iowa, Iowa City, IA 52242

2. Impact of Floods
● In 2018, floods caused
24% of deaths due to
natural disasters,
second only to
earthquakes
● Flood incidence
growing with climate
change

3. Flash Flood Threat
● Rapid flooding of low-lying areas
● Highly-localized, unpredictable impact
● Fast-moving water, extremely dangerous
via The Guardian

4. Power of a Moving Fluid
● P = power
● ⍴ = density of fluid (for water, this is constant)
● A = cross-sectional area of object in fluid
○ Depends on depth of water and width of object
○ For given object, cross-sectional area varies with water depth
● v = velocity of the water
Power of flash flood is function of both water depth and water velocity

5. Objective
To reduce the impact of flash floods through real-time and localized threat assessment,
derived from water depth and water velocity measurements

6. Water Depth Sensing
● Ultrasonic device points straight down and is calibrated to find the normal distance to
the ground (N)
● Device measures current distance to ground (H) and can find depth (D) of water

7. Ultrasonic Device (Top-Down View)

8. Ultrasonic Device (Side View)

9. Testing
98.4% accuracy of
ultrasonic device
Accuracy of ultrasonic
device is extremely high, so
depth of water can be
accurately calculated

10. Water Velocity Sensing
● Using a technique called Large Scale Particle Image Velocimetry (LSPIV)
● LSPIV finds the surface velocity of water the same way our eyes do
○ We look for patterns of particles on the surface of water estimate how fast they
are moving
○ Particles can be foam or any floating objects
○ LSPIV does the same through a computer by tracing particle patterns

11. LSPIV App
First, we tried the LSPIV smartphone application by Ryota Tsubaki, a Japanese researcher
Interrogation Area
Search Area
Computational Grid

12. Testing
93.5% “consistency” of ultrasonic device
“Consistency” = standard deviation of data over
the average
Data has a high degree of precision, but is not
accurate (off by orders of 10)
Scaling issue that needs to be fixed

13. Possible Error #1: Interrogation / Search Area Size
● Interrogation Area = small box where the pattern is defined in the first frame
● Search Area = larger box where the same pattern (from the Interrogation Area) is
searched for in a later frame
● If the interrogation area is too small, the space may not contain a full particle
● If the interrogation area is too big, correlations are hard to find as the pattern becomes
extremely complex
● If the search area is too small, the particle group may have moved out of the area
within the frame
● If the search area is too big, correlations are hard to find because there are many
clusters of particles that all look somewhat similar

14. Possible Error #2: Sparse Computational Grid
● Ideally, between 50 and 150 points on the image would have LSPIV performed to
maximize chances of getting a particle cluster in the interrogation an search areas
● LSPIV app only has 9 such spots, and sometimes has less based on the angle of the
camera

15. Possible Error #3: Correlation / Velocity Filters
● Correlation filters should be used to rule out outlying velocity values
● Hard maximum cut-offs should be used for extremely high, implausible velocities
● LSPIV app does not use either correlation filters or maximum velocity cutoffs

16. Next Steps
Fixing the LSPIV app
● Working with Ryota Tsubaki to fix
the LSPIV app scaling issue
● In process of fixing the scaling
issues
● Have made significant progress in
solving some of the apps internal
issues
Using other LSPIV software
● Using the FUDAA software for
LSPIV that was developed by
French researchers
● Software runs on computers and has
more options to customize how the
LSPIV should be run (i.e.
interrogation and search area sizes,
correlation filters)

17. FUDAA Software
Computational Grid
Velocity /
Correlation
Filters

18. Testing
96.1% “consistency” of ultrasonic device
Data has a high degree of precision, but is not
accurate (off by a small scaling factor)
Gray line = expected (actual = measured)
Blue line = naive settings on FUDAA
Orange line = more thought-through settings on
FUDAA

19. Results and Conclusions
Proof-of-concept was successful
● Ultrasonic device to find the water depth worked extremely well
● LSPIV app and FUDAA software prove the an LSPIV-approach to measuring water
velocity can be successful
● Together, water depth and water velocity robustly describe flash flood threat

20. Future Research
● Ultrasonic sensor, camera, and
single-board computer perform depth
and velocity sensing
● Single-board computer uses data points
to calculate the severity of a flash flood
● Cell modem sends out alerts if there is a
flash flood to nearby individuals

21. Acknowledgements
Special thanks to Dr. Marian Muste for his guidance on the project. Next, thanks to Libby
Casavant for her interest in my project and her additional testing.
Finally, thanks to Ryota Tsubaki and Alexandre Christophe Hauet for their help with the
LSPIV portion of the project.