Štěpán KŘÍSTEK¹, Jaroslav HOLUŠA², Naděžda URBAŇCOVÁ¹, Jiří TROMBIK³ & Karel DRÁPELA^4
 1Forest Management Institute, Brandýs nad Labem, Frýdek-Místek Branch, Nádražní 2811, 738 01 Frýdek-Místek, Czech Republic, Email: kristek.stepan@uhul.cz
²Forestry and Game Management Research Institute, Frýdek-Místek Workplace, Nádražní 2811, 738 01 Frýdek-Místek, Czech Republic, Email: holusaj@seznam.cz
³University of Ostrava, Faculty of Science, 30. dubna 22, 701 03 Ostrava, Czech Republic, Email: jiri.trombik@gmail.com
⁴Mendel University in Brno, Faculty of Forestry and Wood Technology, Zemědělská 3, 613 00 Brno, Czech Republic, Email: drapela@mendelu.cz 

EXPEDITIONARY MEASUREMENTS OF SNOW IN EXTENSIVELY FORESTED CARPATHIAN MOUNTAINS: EVALUATING PARAMETERS VARIABILITY

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 Snow cover parameters are studied in the basin of the Šance water reservoir in the Moravian-Silesian Beskids (Czech Republic). The location is overlaid with a regular 2x2 km square grid along the axes of a coordinate system of a single trigonometric cadastral network. In each of the total of 52 squares at least one sample plot is established comprising of two types of subplots: open plots and plots under adjacent forest. The studied parameters include snowpack depth, snow density and snow water equivalent. Depth is measured directly on the plots and the two other characteristics are calculated additionally using the directly measured parameters (depth and weight of the snow samples taken).
Snowpack depth is measured 20 times on each plot with precision to 1 cm. For calculating snow density and snow water equivalent 2–5 samples of snow are taken and their corresponding values are determined on the basis of sample depth with precision to 1 cm, calibration volume of the sampling cylinder (precision to 0.05 l), and weight (to 0.01 kg). The purpose of this article is to evaluate the accuracy of the measuring of snow cover using jittering method on forest as well as unforested plots to get accurate data for evaluation of snow damage to forests.
The analysis demonstrated local variability of snowpack depth on the order of centimeters. Only exceptionally does the SD value exceed 10 cm. The coefficient of variation reaches high values only at the lowest values of snowpack depth, where the standard deviation is no more than a few centimeters. A procedure for eliminating maximum and minimum measured values reduces the variability significantly but has practically negligible influence on the mean snowpack depth. The estimated variability of water equivalent depends on the precision of determining the inputs for mean snow depth and density and usually ranges up to 10 mm. Nearly all indicators of snow depth variability correlate with the mean snowpack depth. While standard deviation increases only slightly with mean snowpack depth cover and may be characterized by linear regression, the coefficient of variation is inversely proportional to the mean snowpack depth.