Using AI to detect and forecast snow avalanches

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Using AI to detect and forecast snow avalanches Alec van Herwijnen WSL Institute for Snow and Avalanche Research SLF WSL Institute for Snow and Avalanche Research SLF

Transcript of Using AI to detect and forecast snow avalanches

Page 1: Using AI to detect and forecast snow avalanches

Using AI to detect and forecast

snow avalanches

Alec van Herwijnen

WSL Institute for Snow and Avalanche Research SLF

WSL Institute for Snow and Avalanche Research SLF

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Snow avalanches

Photos: SLF / Alec van Herwijnen

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Snow avalanches

2018

1968

1999

1951

Photo SLFPhoto Alain Duclos

Photo AP BMFLVLaternser and Ammann, 2001

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Avalanche recipe

• Steep slope

• Snow

• Trigger

→ Any place that has mountains and snow

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Snow avalanches in Switzerland

• Destructive snow avalanches last 50 years

→ Avalanche forecasting:

when (and where) will

avalanches release?

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To warn the public about the avalanche danger

level requires data on:

• Weather

• Snow stratigraphy

• Avalanches

Avalanche forecasting

→ Very little

avalanche data

when it is most

needed

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Remote avalanche detection

• Seismic monitoring systems

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Remote avalanche detection

• Seismic monitoring systems

Heck et al., 2019

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Automatic avalanche detection

• Supervised machine learning to automatically find

signals generated by avalanches

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Automatic avalanche detection

• Supervised machine learning to automatically find

signals generated by avalanches

Heck et al., 2018

→ Accurate

avalanche data

potentially in

real-time

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Automatic weather stations

• Over 130 stations in the

Swiss Alps ( )

• Real-time data

• Snowpack modelling

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Tree 1 Tree 2 Tree n…

Level 2 Level 3 Level 2

Voting Σ

Input data

Level 2

Input data: Supervised machine learning: Output:

Danger scale

Regional

danger level

Random Forest

Automatic danger level prediction

1. Low

2. Moderate

3. Considerable

4. High

5. Very High

Weather data: air and

surface temperature,

wind speed,,…

SNOWPACK data:new

snow, wind drift index,

stability indiced…

→ Weather forecast data can be

used as input data

Pérez-Guillén et al., 2021

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SNOWPACK: Danger level prediction

All weather stations in Switzerland

Pérez-Guillén et al., 2021

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AI and avalanche forecasting

Machine learning will improve avalanche forecasting:

• Provide near real-time avalanche data

• Objective analysis of

large data volumes

• Improve the spatial and

temporal resolution of

forecasting products

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Challenges to implement AI in

operational avalanche forecasting

• Data availability and reliability (data sparse areas)

• Reliable training data

for avalanche detection

systems and avalanche

forecasting

• Extreme weather

events are becoming

more common

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References

Laternser, M., & Ammann, W. J., 2001. Der Lawinenwinter 1951. Schweizerische Zeitschrift

für Forstwesen, 152(1), 25-35. https://doi.org/10.3188/szf.2001.0025

Heck, M., van Herwijnen, A., Hammer, C., Hobiger, M., Schweizer, J., & Fäh, D. (2019).

Automatic detection of avalanches combining array classification and localization. Earth

Surface Dynamics, 7(2), 491-503. https://doi.org/10.5194/esurf-7-491-2019

Heck, M., Hammer, C., Van Herwijnen, A., Schweizer, J., & Fäh, D. (2018). Automatic

detection of snow avalanches in continuous seismic data using hidden Markov models.

Natural Hazards and Earth System Science, 18(1), 383-396. https://doi.org/10.5194/nhess-18-

383-2018

Pérez-Guillén, C., Hendrick, M., Techel, F., van Herwijnen, A., Volpi, M., Tasko, O., Pérez-

Cruz, F., Obozinski, G., and Schweizer, J., 2021. Data-driven automatic predictions of

avalanche danger in Switzerland, EGU General Assembly 2021, online, 19–30 Apr 2021,

EGU21-6154, https://doi.org/10.5194/egusphere-egu21-6154