Item: A SENSITIVITY ANALYSIS TO QUANTIFY HOW ERRORS IN FOREST DATA AFFECT AVALANCHE HAZARD MAPS IN NORWAY
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Title: A SENSITIVITY ANALYSIS TO QUANTIFY HOW ERRORS IN FOREST DATA AFFECT AVALANCHE HAZARD MAPS IN NORWAY
Proceedings: International Snow Science Workshop 2024, Tromsø, Norway
Authors:
- J. Paul McLean [ Norwegian Institute of Bioeconomy Research, Ås, Norway ]
- Dieter Issler [ Norwegian Geotechnical Institute, Oslo, Norway ]
- Kjersti G. Gisnås [ Norwegian Geotechnical Institute, Oslo, Norway ]
Date: 2024-09-23
Abstract: Forests play a major role in the mitigation of avalanche risk in Norway, but the regulations surrounding the management of “protection forests” are still being worked out. To promote protection forest management, avalanche hazard indication maps for Norway have been produced with the automated mapping tool NAKSIN in a way that makes it possible to quantity the effects of the current forests in a spatially explicit way. NAKSIN makes use of published relations for forest effects on snow properties and uses national models of forest characteristics to estimate the effects on release probability and runout given local climate and topography. The forest properties contain parameters that are directly measured (canopy cover), and properties that are predicted (tree diameter, number of trees) with approximately 70% precision according to ground truth data. NAKSIN uses these properties in long chains of models and the aim of this study was to quantify the propagation of error throughout those chains in a relevant case study region in Fjordic Western Norway. We examined hazard maps produced using 95% confidence level prediction errors for tree diameter and the number of trees per hectare to determine if these would dramatically affect the hazard zones. These hazard maps focused on runout properties as common release areas were implied for avalanches through a common forest canopy cover percentage applied across the two extreme scenarios. Across the entire region, the hazard zones were generally stable with respect to potential errors in the forest data, suggesting the approach is robust and the braking effect of forest is not overstated. There was one exception, where the prediction errors could reduce the forest braking function to negligible. This was easy to identify using the process and the process allows us to consider where more precise measurements of forests could be required in areas with high consequences. The implications of various approaches to estimate forest leaf area index, and how this might impact on release probability are illustrated to further consider this in the next steps of this research.
Object ID: ISSW2024_O4.3.pdf
Language of Article: English
Presenter(s): John Paul McLean
Keywords: Protection forest, uncertainty, avalanche, risk analysis
Page Number(s): 570 - 577
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