the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Operational regional slushflow early warning
Heidi A. Grønsten
Siv Å. Seljesæter
Abstract. Slushflows are observed worldwide in areas with seasonal snow cover. A regional early warning for slushflow hazard was established in Norway in 2013–14 as the first in the world of its kind and has been operational since. This paper presents a methodology using water supply – snow depth ratio by snow type, employing grid values and data from historical slushflows, to assess regional slushflow hazard. In Norway slushflows pose a significant natural hazard. Hazard prediction and early warning is therefore crucial to prevent casualties and damage to infrastructure. A benefit with this approach is that it can be implemented in other regions with slushflow hazard where the necessary input data are available.
Slushflows are rapid mass movements of water saturated snow. They release in low to moderate slopes (< 30°). Due to their high liquid water content, slushflows usually have long runouts, and they can transform into debris flows. A complex interaction between several factors is the key to slushflow initiation. Impeded infiltration of the ground is a prerequisite. Porous snow structures are most prone to destabilization. Rate and duration of water supply, due to rain on snow and/or intense snowmelt, is crucial.
The daily assessment of slushflow hazard is based on information on snow cover and hydro-meteorological conditions. Four main variables are central: ground conditions, snow properties, air temperature, and water supply to snow. A wide range of meteorological and hydrological parameters from multiple sources, together with real-time data from automatic stations and observations from the field, are assessed. The data is provided from the decision-making tool Varsom Xgeo, presenting outputs from model simulations as gridded maps (1x1 km). A first water supply-to-snow depth ratio for different types of snow has been developed using grid values and data from historical slushflows.
- Preprint
(2303 KB) - Metadata XML
- BibTeX
- EndNote
Monica Sund et al.
Status: open (extended)
-
RC1: 'Comment on nhess-2023-96', Harpa Grimsdottir, 21 Aug 2023
reply
The paper gives a good overview of the operational slushflow regional forecasting system in Norway, which is probably unique in the world. It gives some good background information on slushflows and what kind of situation may lead to slushflow danger in general, based on previous papers on slushflows. The paper is of importance to all who are dealing with this problem, forecasting for and warning against slushflow danger.
Here are a few questions and/or comments for the authors:
- According to our experience, slushflows can initiate in slopes that are quite steep in general, however the starting point might be in an area with inclination <30°. The starting point can be in a small „step“ in the slope, or at the lower part of a high and steep mountain where the slope starts to ease off. I feel that sometimes, the risk of slushflows may be underestimated in areas where the slope in general is considered to be too steep for slushflows but still includes areas where slushflows can initiate.
- It is mentioned that physical mitigation measures are expensive if possible, and in some areas difficult to implement. Therefore, EWS is important. It is also stated that the initiation of slushflows can be forecasted reasonably well. In my opinion it is important to consider physical mitigation especially in places where slushflows pose serious threat to settlement. There is great uncertainty associated with forecasting the time and location of a slushflow. In some slushflow paths the complication and cost is not as high as for typical dry snow avalanche mitigation measures, but in other areas it is more complicated.
- In Figure 2 (flowchart) the hazard level becomes automatically green (1) if the ground is not frozen, saturated or a bare rock. Earlier in the paper it is, however, stated that requirement of water saturation can also be met with unfrozen ground and when a thick ice layer is covered with snow. Perhaps slushflows occurrences in such conditions are so rare that they are not taken into account?
- In Table 2 it is a bit unclear to me what SD (cm) stands for. Is it the total snowdepth according to a model in Xgeo? Or does „Sum 1-3 Days“ apply to the snowdepth – is it the accumulated snow within the last 3 days? As I understand it, it is the total snowdepth, but then it is assumed that a total snowdepth of 0-25 cm can lead to danger levels 2, 3 and 4. However, in the flowchart in Figure 2, snowdepth less than 25 cm automatically leads to danger level 1. Does „Sum1-3 Days“ apply to the water supply (rain + snowmelt)?
- It would be interesting to include in the paper a bit more about how well the forecasting system has worked in practice. It is important to look at days both with and without slushflow events and check how often these weather, soil saturation and snow conditions occur, without any slushflows being recorded. I realise it is not easy due to the sparse slushflow data, however, some analyses of this has probably been done in Norway?
It would be interesting to try these methods in Iceland and other countries and continue to improve the system.
-
AC1: 'Reply on RC1', Monica Sund, 18 Sep 2023
reply
Please find our response in the attached pdf.
Monica Sund et al.
Monica Sund et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 246 | 53 | 10 | 309 | 7 | 6 |
- HTML: 246
- PDF: 53
- XML: 10
- Total: 309
- BibTeX: 7
- EndNote: 6
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1