University of Oulu

Leo-Juhani Meriö, Hannu Marttila, Pertti Ala-aho, Pekka Hänninen, Jarkko Okkonen, Raimo Sutinen, Bjørn Kløve, Snow profile temperature measurements in spatiotemporal analysis of snowmelt in a subarctic forest-mire hillslope, Cold Regions Science and Technology, Volume 151, 2018, Pages 119-132, ISSN 0165-232X, https://doi.org/10.1016/j.coldregions.2018.03.013

Snow profile temperature measurements in spatiotemporal analysis of snowmelt in a subarctic forest-mire hillslope

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Author: Meriö, Leo-Juhani1; Marttila, Hannu1; Ala-aho, Pertti1,2;
Organizations: 1Water Resources and Environmental Engineering, PO Box 4300, 90014, University of Oulu, Finland
2Geological Survey of Finland, PO Box 97, 67101 Kokkola, Finland
3Geological Survey of Finland, PO Box 77, 96101 Rovaniemi, Finland
Format: article
Version: accepted version
Access: embargoed
Persistent link: http://urn.fi/urn:nbn:fi-fe2018042418449
Language: English
Published: Elsevier, 2018
Publish Date: 2020-03-19
Description:

Abstract

Continuous data on spatial and temporal patterns of snowmelt rates are essential for hydrological studies, but are commonly not available, especially in the subarctic, mainly due to high monitoring costs. In this study, temperature loggers were used to measure local and microscale variations in snowpack temperature, in order to understand snowmelt processes and rates in subarctic northern Finland. The loggers were deployed on six test plots along a hillslope with varying topography (elevation and aspect) and vegetation (forest, transitional zone and mires, i.e. treeless peatlands) during two consecutive winters (2014 and 2015). At each test plot, the sensors were installed in five locations, at two heights in a snow profile. Algorithms were developed to analyse the snowmelt rates from high-resolution snowpack temperature data. The validity of the results was evaluated using snow depth and soil moisture data from adjacent reference sensors and the results were tested using an empirical degree-day snow model calibrated for each test plot. Snowmelt rates were relatively similar in mires (median 2.3 mm d−1 °C−1) and forests (median 2.6 mm d−1 °C−1) with apparent inter-annual variation. The observed melt rates were highest in the highest elevation plots, in transition zone in 2014 (median 4.6 mm d−1 °C−1) and southwest-facing forest line in 2015 (median 3.2 mm d−1 °C−1). The timing of the modelled meltwater outflow and snowpack ablation showed good agreement with the snowpack temperature-derived estimates and the soil moisture and snow depth measurements. The simple approach used represents a novel and cost-effective method to improve the spatial accuracy of in situ snow cover ablation measurements and melt rates and the precision of snowmelt models in the subarctic. An open-access R-based model is provided with this paper for analysis of high-frequency snow temperature data.

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Series: Cold regions science and technology
ISSN: 0165-232X
ISSN-E: 1872-7441
ISSN-L: 0165-232X
Volume: 151
Pages: 119 - 132
DOI: 10.1016/j.coldregions.2018.03.013
OADOI: https://oadoi.org/10.1016/j.coldregions.2018.03.013
Type of Publication: A1 Journal article – refereed
Field of Science: 1172 Environmental sciences
218 Environmental engineering
1171 Geosciences
117 Geography and environmental sciences
Subjects:
Funding: This study was funded by the Maa- ja vesitekniikan tuki ry.
Copyright information: © 2018 Elsevier B.V. All rights reserved.