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Assessment of snow water supplies for Istra station territory using Sentinel-2 imagery data
1 , * 1 , 2 , 3
1  All-Russian Research Institute for Silviculture and Mechanization of Forestry (VNIILM), Pushkino, Russia
2  Scientific Innovation Center for Monitoring the Natural Environment, Istra, Russia
3  Institute of Geography RAS, Moscow, Russia
Academic Editor: Tianxiang Yue

Abstract:

This article investigates the relationship between snow and its water supply accumulation and qualitative and spectral-reflective forest characteristics. This study aims to develop methods for determining snow water supplies using Sentinel-2 imagery data. Our research is based on experimental fieldwork and previous analyss of the features of water accumulation in the snow in various natural landscapes. Considering the previously obtained snow accumulation dependences on the species composition, age, and forest density, modern approaches in forest inventory interpretation were used to identify how snow accumulation and its water content correlate with territory features. The designed method determines snow water supplies according to optical satellite imagery or forest inventory materials based on a small number of field measurements. The method’s accuracy relies on the diversity of examined landscapes and ecosystems. The fieldwork was carried out on the territory belonging to the hydrological station of the Federal Budgetary Institution “All-Russian Research Institute of Silviculture and Forestry Mechanization” (FBU VNIILM), located in the Istra area, Moscow Region. Snow sampling and forest inventory were conducted along the routes that included various landscapes, from open spaces to high-density coniferous forests. This method estimates the water content in snow that we propose can be used to forecast moisture availability, surface runoff, and flooding and assesses the consequences of early spring droughts. The designed territory zoning of snow water accumulation is confirmed by plenty of previous studies conducted in similar conditions. The distinguishing feature of the method described in this article is the possibility of accurately assessing the snow water content while carrying out minimum experimental studies in vast areas, such as municipal districts or regions.

Keywords: Snow survey; snow water supply; snow cover; forest characteristics; forest inventory; remote sensing; Sentinel-2; optical imagery data

 
 
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