Preprints
https://doi.org/10.5194/nhess-2022-44
https://doi.org/10.5194/nhess-2022-44
 
22 Feb 2022
22 Feb 2022
Status: a revised version of this preprint was accepted for the journal NHESS and is expected to appear here in due course.

What weather variables are important for wet and slab avalanches under a changing climate in low altitude mountain range in Czechia?

Markéta Součková1,2, Roman Juras1, Kryštof Dytrt1, Vojtěch Moravec1,2, Johanna Ruth Blöcher1, and Martin Hanel1 Markéta Součková et al.
  • 1Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, Praha – Suchdol, 165 00, Czechia
  • 2T.G. Masaryk Water Research Institute, Department of Hydrology, Podbabská 2582/30, 160 00 Prague 6, Czechia

Abstract. Climate change impact on avalanches is ambiguous. Fewer, wetter, and smaller avalanches are expected in areas where snow cover is declining, while in higher altitude areas where snowfall prevails, snow avalanches are frequently and spontaneously triggered. In the present paper, we assess 39 years (winters of 1979–1999 to 2002–2020) of avalanche activity related to meteorological and snow drivers in the Krkonoše Mountains, Czechia, Central Europe. The analysis is based on an avalanche occurrence dataset for mostly south, south-easterly oriented 60 avalanche paths and related meteorological and snowpack data. Since 1979, 179/531 wet-snow/slab avalanches have been recorded. The aim is to analyze changes in avalanche activity: frequency and magnitude, and detect driving weather variables of wet and slab avalanches with quantification of variable importance. Especially, the number of wet avalanches in February and March has increased in the last three decades, while the number of slab avalanches has decreased with decadal variability. Medium, large, and very large slab avalanches seem to decline with decadal variability since 1961. The results indicate that wet avalanches are influenced by 3-day maximum and minimum air temperature, snow depth, wind speed, wind direction, and rainfall. Slab avalanche activity is determined by snow depth, rainfall, new snow, and wind speed. Air temperature-related variables for slab avalanches were less important than rain and snow-related variables based on the balanced random forest (RF) method. Surprisingly, the RF analysis revealed less significant relationship between new snow sum and slab avalanche activity. This could be because of the wind redistributing snow in storms in low altitude mountains. Our analysis allows the use of the identified wet and slab avalanche driving variables to be included in the avalanche danger levels alerts. Although it cannot replace operational forecasting, machine learning can allow for additional insights for the decision-making process to mitigate avalanche hazard.

Markéta Součková et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-44', Anonymous Referee #1, 28 Mar 2022
  • CC1: 'Comment on nhess-2022-44', Daniel Germain, 31 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-44', Anonymous Referee #1, 28 Mar 2022
  • CC1: 'Comment on nhess-2022-44', Daniel Germain, 31 Mar 2022

Markéta Součková et al.

Markéta Součková et al.

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Short summary
Avalanches are natural hazards threatening people and infrastructure. With climate change, avalanche activity is changing. We analyzed the change in frequency and size of avalanches in the Krkonoše Mountains, Czechia, and detected important variables with machine-learning tools from 1979–2020. Wet avalanches in February and March have increased, and slab avalanches have decreased, and become smaller. The identified variables and their thresholds levels may help in avalanche decision-making.
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