GIS and field data-based modelling of snow water equivalent in shrub tundra
An approach for snow water equivalent (SWE) modelling in tundra environments has been developed for the test area on the Yamal peninsula. Detailed mapping of snow cover is very important for tundra areas under continuous permafrost conditions, because the snow cover affects the active layer thicknes...
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Geographical Society of Finland
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fttsvojs:oai:journal.fi:article/46363 2023-05-15T13:03:28+02:00 GIS and field data-based modelling of snow water equivalent in shrub tundra Dvornikov, Yury A. Khomutov, Artem V. Mullanurov, Damir R. Ermokhina, Ksenia A. Gubarkov, Anatoly A. Leibman, Marina O. 2015-05-04 application/pdf https://fennia.journal.fi/article/view/46363 eng eng Geographical Society of Finland https://fennia.journal.fi/article/view/46363/14638 https://fennia.journal.fi/article/view/46363 Fennia; Vol 193 Nro 1 (2015); 53-65 Fennia - International Journal of Geography; Vol 193 No 1 (2015); 53-65 1798-5617 Snow water equivalent GIS modelling topography snow survey info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Field study, GIS 2015 fttsvojs 2020-09-30T22:46:23Z An approach for snow water equivalent (SWE) modelling in tundra environments has been developed for the test area on the Yamal peninsula. Detailed mapping of snow cover is very important for tundra areas under continuous permafrost conditions, because the snow cover affects the active layer thickness (ALT) and the ground temperature, acting as a heat-insulating agent. The information concerning snow cover with specific regime of accumulation can support studies of ground temperature distribution and other permafrost related aspects. Special attention has been given to the presence of shrubs and microtopography, specifically ravines in a modelling approach. The methodology is based on statistical analysis of snow survey data and on GIS- (Geographical Information System) analysis of a range of parameters: topography, wind, and shrub vegetation. The topography significantly controls snow cover redistribution. This influence can be expressed as increase of snow depth on concave and decrease on convex surfaces. Specifically, snow depth was related to curvature in the study area with a correlation of R=0.83. An index is used to distinguish windward and leeward slopes in order to explain wind redistribution of snow. It is calculated from aspect data retrieved from a digital elevation model (obtained by field survey). It can be shown that shrub vegetation can serve as a ‘trap’ for wind-blown snow but is not a limiting factor for maximum snow depth, since the snow depth can be higher or lower than shrub height dependent on other factors. Article in Journal/Newspaper Active layer thickness permafrost Tundra Yamal Peninsula Federation of Finnish Learned Societies: Scientific Journals Online Yamal Peninsula ENVELOPE(69.873,69.873,70.816,70.816) |
institution |
Open Polar |
collection |
Federation of Finnish Learned Societies: Scientific Journals Online |
op_collection_id |
fttsvojs |
language |
English |
topic |
Snow water equivalent GIS modelling topography snow survey |
spellingShingle |
Snow water equivalent GIS modelling topography snow survey Dvornikov, Yury A. Khomutov, Artem V. Mullanurov, Damir R. Ermokhina, Ksenia A. Gubarkov, Anatoly A. Leibman, Marina O. GIS and field data-based modelling of snow water equivalent in shrub tundra |
topic_facet |
Snow water equivalent GIS modelling topography snow survey |
description |
An approach for snow water equivalent (SWE) modelling in tundra environments has been developed for the test area on the Yamal peninsula. Detailed mapping of snow cover is very important for tundra areas under continuous permafrost conditions, because the snow cover affects the active layer thickness (ALT) and the ground temperature, acting as a heat-insulating agent. The information concerning snow cover with specific regime of accumulation can support studies of ground temperature distribution and other permafrost related aspects. Special attention has been given to the presence of shrubs and microtopography, specifically ravines in a modelling approach. The methodology is based on statistical analysis of snow survey data and on GIS- (Geographical Information System) analysis of a range of parameters: topography, wind, and shrub vegetation. The topography significantly controls snow cover redistribution. This influence can be expressed as increase of snow depth on concave and decrease on convex surfaces. Specifically, snow depth was related to curvature in the study area with a correlation of R=0.83. An index is used to distinguish windward and leeward slopes in order to explain wind redistribution of snow. It is calculated from aspect data retrieved from a digital elevation model (obtained by field survey). It can be shown that shrub vegetation can serve as a ‘trap’ for wind-blown snow but is not a limiting factor for maximum snow depth, since the snow depth can be higher or lower than shrub height dependent on other factors. |
format |
Article in Journal/Newspaper |
author |
Dvornikov, Yury A. Khomutov, Artem V. Mullanurov, Damir R. Ermokhina, Ksenia A. Gubarkov, Anatoly A. Leibman, Marina O. |
author_facet |
Dvornikov, Yury A. Khomutov, Artem V. Mullanurov, Damir R. Ermokhina, Ksenia A. Gubarkov, Anatoly A. Leibman, Marina O. |
author_sort |
Dvornikov, Yury A. |
title |
GIS and field data-based modelling of snow water equivalent in shrub tundra |
title_short |
GIS and field data-based modelling of snow water equivalent in shrub tundra |
title_full |
GIS and field data-based modelling of snow water equivalent in shrub tundra |
title_fullStr |
GIS and field data-based modelling of snow water equivalent in shrub tundra |
title_full_unstemmed |
GIS and field data-based modelling of snow water equivalent in shrub tundra |
title_sort |
gis and field data-based modelling of snow water equivalent in shrub tundra |
publisher |
Geographical Society of Finland |
publishDate |
2015 |
url |
https://fennia.journal.fi/article/view/46363 |
long_lat |
ENVELOPE(69.873,69.873,70.816,70.816) |
geographic |
Yamal Peninsula |
geographic_facet |
Yamal Peninsula |
genre |
Active layer thickness permafrost Tundra Yamal Peninsula |
genre_facet |
Active layer thickness permafrost Tundra Yamal Peninsula |
op_source |
Fennia; Vol 193 Nro 1 (2015); 53-65 Fennia - International Journal of Geography; Vol 193 No 1 (2015); 53-65 1798-5617 |
op_relation |
https://fennia.journal.fi/article/view/46363/14638 https://fennia.journal.fi/article/view/46363 |
_version_ |
1766337515861573632 |