Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions

• DOI: 10.5194/tc-17-4363-2023
• Publication Date: 2023-10-17T08:23:29Z
• Authors: Leo-Juhani Meriö; Anssi Rauhala; Pertti Ala-aho; Anton Kuzmin; Pasi Korpelainen; Timo Kumpula; Bjørn Kløve; Hannu Marttila
• Keywords: Snowmelt; Subarctic climate; Snow field; Tree canopy

Abstract. Detailed information on seasonal snow cover and depth is essential to the understanding of processes, operational forecasting, as input for hydrological models. Recent advances in uncrewed or unmanned aircraft systems (UASs) structure from motion (SfM) techniques have enabled low-cost monitoring spatial distribution resolutions up a few centimeters. Here, we study spatiotemporal variability interactions between vegetation different subarctic landscapes consisting mosaic conifer forest, mixed transitional woodland/shrub, peatland areas. To determine depth, used high-resolution (50 cm) maps generated repeated UAS–SfM surveys winter 2018/2019 snow-free bare-ground survey after snowmelt. Due poor subcanopy penetration with method, tree masks were utilized remove canopy areas area (36 immediately next before analysis. Snow compared situ course single-point continuous ultrasonic measurement. Based results, difference median measurement increased all land types during season, +5 cm at beginning accumulation −16 coniferous forests −32 melt period. This highlights representation point measurements selected locations even subcatchment scale. The agreed well measurement, but extent resolution substantially higher. range (5th–95th percentiles) within 17 42 peatlands 33 49 forest Both its found increase density; this was greatest area, followed by open peatlands. Using high-spatial-resolution data, systematic (2–20 then decline near increasing distance (from 1 2.5 m) peak value through season. applicability multiple snow–vegetation remote where field data are not available collected using classic courses.