Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchment
Modelling runoff generation in high-elevation Alpine catchments requires detailed knowledge on the spatio-temporal distribution of snow storage. With Sentinel-2 MultiSpectral Instrument (MSI), it is possible to map snow cover with a high temporal and spatial resolution. In contrast to the coarse MOD...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-05-01
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| Series: | Journal of Hydrology X |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589915522000050 |
| _version_ | 1828341482513235968 |
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| author | Florentin Hofmeister Leonardo F. Arias-Rodriguez Valentina Premier Carlo Marin Claudia Notarnicola Markus Disse Gabriele Chiogna |
| author_facet | Florentin Hofmeister Leonardo F. Arias-Rodriguez Valentina Premier Carlo Marin Claudia Notarnicola Markus Disse Gabriele Chiogna |
| author_sort | Florentin Hofmeister |
| collection | DOAJ |
| description | Modelling runoff generation in high-elevation Alpine catchments requires detailed knowledge on the spatio-temporal distribution of snow storage. With Sentinel-2 MultiSpectral Instrument (MSI), it is possible to map snow cover with a high temporal and spatial resolution. In contrast to the coarse MODIS data, Sentinel-2 MSI enables the investigation of small-scale differences in snow cover duration in complex terrains due to gravitational redistribution (slope), energy balance and wind-driven redistribution (aspect). In this study, we describe the generation of high-resolution spatial and temporal snow cover data sets from Sentinel-2 images for a high-elevation Alpine catchment and discuss how the data contribute to our understanding of the spatio-temporal snow cover distribution. The quality of snow and cloud detection is evaluated against in-situ snow observations and against other snow and cloud products. The main problem was in the false detection of snow in the presence of clouds and in topographically shaded areas. We then seek to explore the potential of the generated high-resolution snow cover maps in calibrating the gravitational snow redistribution module of a physically based snow model, especially for an area with a very data-scarce point snow observation network. Generally, the calibrated snow model is able to simulate both the mean snow cover duration with a high F1 accuracy score of > 0.9 and the fractional snow-covered area with a correlation coefficient of 0.98. The snow model is also able to reproduce spatio-temporal variability in snow cover duration due to surface energy balance dynamics, wind and gravitational redistribution. |
| first_indexed | 2024-04-13T23:13:43Z |
| format | Article |
| id | doaj.art-191ee01410ff4c0f90b3e0045a50a32e |
| institution | Directory Open Access Journal |
| issn | 2589-9155 |
| language | English |
| last_indexed | 2024-04-13T23:13:43Z |
| publishDate | 2022-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology X |
| spelling | doaj.art-191ee01410ff4c0f90b3e0045a50a32e2022-12-22T02:25:27ZengElsevierJournal of Hydrology X2589-91552022-05-0115100123Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchmentFlorentin Hofmeister0Leonardo F. Arias-Rodriguez1Valentina Premier2Carlo Marin3Claudia Notarnicola4Markus Disse5Gabriele Chiogna6TUM School of Engineering and Design, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany; Corresponding author.TUM School of Engineering and Design, Technical University of Munich, Arcisstrasse 21, 80333 Munich, GermanyInstitute for Earth Observation, Eurac Research, Viale Druso 1, 39100 Bolzano, ItalyInstitute for Earth Observation, Eurac Research, Viale Druso 1, 39100 Bolzano, ItalyInstitute for Earth Observation, Eurac Research, Viale Druso 1, 39100 Bolzano, ItalyTUM School of Engineering and Design, Technical University of Munich, Arcisstrasse 21, 80333 Munich, GermanyTUM School of Engineering and Design, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany; Institute of Geography, University of Innsbruck, Innrain 52, 6020 Innsbruck, AustriaModelling runoff generation in high-elevation Alpine catchments requires detailed knowledge on the spatio-temporal distribution of snow storage. With Sentinel-2 MultiSpectral Instrument (MSI), it is possible to map snow cover with a high temporal and spatial resolution. In contrast to the coarse MODIS data, Sentinel-2 MSI enables the investigation of small-scale differences in snow cover duration in complex terrains due to gravitational redistribution (slope), energy balance and wind-driven redistribution (aspect). In this study, we describe the generation of high-resolution spatial and temporal snow cover data sets from Sentinel-2 images for a high-elevation Alpine catchment and discuss how the data contribute to our understanding of the spatio-temporal snow cover distribution. The quality of snow and cloud detection is evaluated against in-situ snow observations and against other snow and cloud products. The main problem was in the false detection of snow in the presence of clouds and in topographically shaded areas. We then seek to explore the potential of the generated high-resolution snow cover maps in calibrating the gravitational snow redistribution module of a physically based snow model, especially for an area with a very data-scarce point snow observation network. Generally, the calibrated snow model is able to simulate both the mean snow cover duration with a high F1 accuracy score of > 0.9 and the fractional snow-covered area with a correlation coefficient of 0.98. The snow model is also able to reproduce spatio-temporal variability in snow cover duration due to surface energy balance dynamics, wind and gravitational redistribution.http://www.sciencedirect.com/science/article/pii/S2589915522000050Snow coverSnow redistributionHigh-elevation Alpine catchmentSentinel-2Physically based snow modelling |
| spellingShingle | Florentin Hofmeister Leonardo F. Arias-Rodriguez Valentina Premier Carlo Marin Claudia Notarnicola Markus Disse Gabriele Chiogna Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchment Journal of Hydrology X Snow cover Snow redistribution High-elevation Alpine catchment Sentinel-2 Physically based snow modelling |
| title | Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchment |
| title_full | Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchment |
| title_fullStr | Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchment |
| title_full_unstemmed | Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchment |
| title_short | Intercomparison of Sentinel-2 and modelled snow cover maps in a high-elevation Alpine catchment |
| title_sort | intercomparison of sentinel 2 and modelled snow cover maps in a high elevation alpine catchment |
| topic | Snow cover Snow redistribution High-elevation Alpine catchment Sentinel-2 Physically based snow modelling |
| url | http://www.sciencedirect.com/science/article/pii/S2589915522000050 |
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