Accurate estimation of precipitation in mountain catchments is challenging due to its high spatial variability and lack of measured ground data. Weather radar can help to provide precipitation estimates in such conditions. This study investigates the differences between measured and radar-estimated daily precipitation in the mountain catchment of the Jalovecký Creek (area 22 km2, 6 rain gauges at altitudes 815–1900 m a.s.l.) in years 2017–2020. Despite good correlations between measured and radar-based precipitation at individual sites (correlation coefficients 0.68–0.90), the radar-estimated precipitation was mostly substantially smaller than measured precipitation. The underestimation was smaller at lower altitude (on average by –4% to –17% at 815 m a.s.l.) than at higher altitudes (–35% to –59% at 1400–1900 m a.s.l.). Unlike measured data, the radar-estimated precipitation did not show the differences in precipitation amounts at lower and higher altitudes (altitudinal differences). The differences between the measured and radar-estimated precipitation were not related to synoptic weather situations. The obtained results can be useful in preparation of more accurate precipitation estimates for the small mountain catchments.
Snow accumulation and melt are highly variable. Therefore, correct modeling of spatial variability of the snowmelt, timing and magnitude of catchment runoff still represents a challenge in mountain catchments for flood forecasting. The article presents the setup and results of detailed field measurements of snow related characteristics in a mountain microcatchment (area 59 000 m2 , mean altitude 1509 m a. s. l.) in the Western Tatra Mountains, Slovakia obtained in winter 2015. Snow water equivalent (SWE) measurements at 27 points documented a very large spatial variability through the entire winter. For instance, range of the SWE values exceeded 500 mm at the end of the accumulation period (March 2015). Simple snow lysimeters indicated that variability of snowmelt and discharge measured at the catchment outlet corresponded well with the rise of air temperature above 0°C. Temperature measurements at soil surface were used to identify the snow cover duration at particular points. Snow melt duration was related to spatial distribution of snow cover and spatial patterns of snow radiation. Obtained data together with standard climatic data (precipitation and air temperature) were used to calibrate and validate the spatially distributed hydrological model MIKE-SHE. The spatial redistribution of input precipitation seems to be important for modeling even on such a small scale. Acceptable simulation of snow water equivalents and snow duration does not guarantee correct simulation of peakflow at shorttime (hourly) scale required for example in flood forecasting. Temporal variability of the stream discharge during the snowmelt period was simulated correctly, but the simulated discharge was overestimated.
Large-scale forest dieback was reported in recent decades in many parts of the world. In Slovakia, the most endangered species is Norway spruce (Picea Abies). Spruce dieback affects also indigenous mountain forests. We analysed changes in snow cover characteristics in the disturbed spruce forest representing the tree line zone (1420 m a.s.l.) in the Western Tatra Mountains, Slovakia, in five winter seasons 2013–2017. Snow depth, density and water equivalent (SWE) were measured biweekly (10–12 times per winter) at four sites representing the living forest (Living), disturbed forest with dead trees (Dead), forest opening (Open) and large open area outside the forest (Meadow). The data confirmed statistically significant differences in snow depth between the living and disturbed forest. These differences increased since the third winter after forest dieback. The differences in snow density between the disturbed and living forest were in most cases not significant. Variability of snow density expressed by coefficient of variation was approximately half that of the snow depth. Forest dieback resulted in a significant increase (about 25%) of the water amount stored in the snow while the snowmelt characteristics (snowmelt beginning and time of snow disappearance) did not change much. Average SWE calculated for all measurements conducted during five winters increased in the sequence Living < Dead < Meadow < Open. SWE variability expressed by the coefficient of variation increased in the opposite order.