The Suitability of Snow and Meteorological Conditions of South-Central Slovakia for Ski Slope Operation at Low Elevation—A Case Study of the Košútka Ski Centre

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Article The Suitability of Snow and Meteorological Conditions of South-Central Slovakia for Ski Slope Operation at Low Elevation—A Case Study of the Košútka Ski Centre

Michal Mikloš 1,*, Martin Janˇco 2, Katarína Korísteková 3, Jana Škvareninová 4 and Jaroslav Škvarenina 1

1 Department of Natural Environment, Technical University in Zvolen, 960 53 Zvolen, Slovakia; [email protected] 2 Department of Biology and General Ecology, Technical University in Zvolen, 960 53 Zvolen, Slovakia; [email protected] 3 Department of Fire Protection, Technical University in Zvolen, 960 53 Zvolen, Slovakia; [email protected] 4 Department of Applied Ecology, Technical University in Zvolen, 960 53 Zvolen, Slovakia; [email protected] * Correspondence: [email protected]; Tel.: +421-949-263-801

Received: 13 February 2018; Accepted: 5 July 2018; Published: 9 July 2018

Abstract: In this study, the snow conditions of South-Central Slovakia (Inner Western Carpathians; temperate zone) were analyzed to assess the suitability for ski slope operations without snow production under 1000 m a.s.l. For the study site of the Košútka Ski Centre, meteorological conditions for snowmaking, snowpack characteristics, and snow water equivalent (SWE) compared with seasonal precipitation were identiﬁed. To identify the months suitable for snowmaking, the number of potential snowmaking days (PSD) and the required number of snowmaking days (RNSD) were calculated for six winter seasons from 2010–2011 to 2015–2016. The results showed that the conditions of natural snow cover were not appropriate for ski slope operation because of a low natural snow depth. For the Košútka Ski Centre, it was concluded that the essential base layer snowmaking for ski slope operation is possible only for a few days in the winter season because of the increasing mean value of the mean average daily temperature and the consequently higher occurrence of liquid precipitation in the winter season. Essential high snow production results in the heterogeneous distribution of snow on the ski slope, and in high snow depth, density, and SWE of the ski slope snowpack, and in prolonged melting.

Keywords: precipitation; snow water equivalent; snowpack; snowmaking; ski resort; snow depth

1. Introduction Snowfall and snow cover have a signiﬁcant impact on different human activities and, therefore, on the entire society and environment. This impact is obvious mainly in mountainous regions of the world with an abundance of natural snow [1]. In Central Europe (above 500 m a.s.l., but mainly above 1000 m a.s.l.), such regions are, particularly, the Alpine and Carpathian regions. In these parts of Europe, the amount of snow and the duration of snow cover are of great social and economic importance. The amount of snow mainly affects winter tourism and water supplies for hydroelectric power stations [2]. Winter tourism is one of the most important economic sectors of mountainous regions in the world [3]. However, winter tourism depends on good snow conditions and is very

Water 2018, 10, 907; doi:10.3390/w10070907 www.mdpi.com/journal/water Water 2018, 10, 907 2 of 19 sensitive to the lack of snow [4]. The majority of climate change scenarios predict the shortening of the duration of seasonal snow cover [5]. Studies on precipitation variability show decreasing trends of precipitation totals in Central and Southern Europe [6–8]. In the context of climate change, areas with persistent snow cover shrink relatively quickly, and occasional snow cover with liquid precipitation in the middle of winter expands over the territory of Slovakia [9]. Vojtek et al. [10] and Škvarenina et al. [11] pointed out the general tendency of the decreasing duration of snow cover and solid precipitation occurrence at lower altitudes in Slovakia (Central Europe). Approximately, 55% of Slovakia has altitudes between 300 m a.s.l. and 1000 m a.s.l., but only 5.4% of its territory is higher than 1000 m a.s.l. [12]. Due to the low altitude of many Slovak ski areas, snow coverage is not always guaranteed [13]. The winter season at the study site (Košútka Ski Centre; 610 m a.s.l.; Inner Western Carpathians) usually lasts three months, from the end of December to the middle of March, because of heavy base layer snowmaking at the beginning of each season. Low-altitude valley runs in the Alps can also be reliably opened for three months only with the help of intensive snowmaking [14]. Winters with a lack of snow have caused significant, sometimes even existential, problems for ski resorts since the mid-1950s [15]. Systems for artificial snowmaking have become the main strategy to reduce the dependency on natural snow. A dynamic increase of artificial snowmaking was observed since the middle of the 1980s in parallel with more abrupt climate changes [16]. Snow production is coupled with some environmental doubts. These doubts mainly include the overconsumption of water and energy during snow production [17] and the negative impacts of snowmaking on vegetation, soil, and water balance [18,19]. The negative effects are primarily caused by the physical and chemical characteristics of the snowpack on the artificially covered ski slopes [20,21]. It was proved that covering high-altitude ski resorts (above 1000 m a.s.l.) with artificial snow results in a significant increase of snow water equivalent, snow depth, and density of snow [22]. The duration of the snowpack with added artificial snow is prolonged by more than two weeks in comparison with natural snow in the surrounding ski slope [19]. This discovery is of great importance because the duration and the distribution of snow cover affects the beginning and the duration of the growing season, and melted water from snow is the source of water and nutrients for plant growth [23]. Thus, it is crucial to know the characteristics of the snow cover at the end of the winter seasons to evaluate its impact on vegetation, water balance, and the calculation of water supplies in snow cover. Winter sports, mainly skiing, have a long tradition in high- as well as low-elevation regions of Central Slovakia. Nevertheless, under the present climate change, snow conditions in the Slovakian ski resorts have changed considerably, especially at low elevations. The first aim of the presented study was to analyze six seasons of data of four precipitation stations in South-Central Slovakia to assess the suitability of natural snow conditions (natural snow depth) for the ski slope operation under 1000 m a.s.l. The representative Košútka Ski Centre, located close to one of the four analyzed precipitation stations, was determined as a study site to achieve the following aims:

- to assess the suitability of meteorological and snow conditions for the ski slope operation without snow production; - to assess the suitability of meteorological conditions for snow production and for base layer snowmaking at the beginning of winter season; - to identify the seasonal variability of the ski slope snowpack characteristics (snow depth, as well as spatial variability, snow density, and snow water equivalent “SWE”) and to compare the ski slope snowpack SWE with seasonal precipitation.

2. Materials and Methods

2.1. Study Site The study was conducted at the Košútka Ski Centre (48.559◦ N, 19.535◦ E; Figure1a) in the Inner Western Carpathians (Slovenské Rudohorie Mts., Veporic Unit, Slovakia; Figure2). The study site belongs to the moderately warm climatic region with cool to cold winters [24], a mean annual Water 2018, 10, 907 3 of 19

◦ temperatureWater 2018, 10 of, x 5.5 FOR C[PEER25 REVIEW], a mean annual precipitation total of 850 mm [26,27], 90 days with3 of 19 snow cover,Water and 2018 a, mean10, x FOR snow PEER depthREVIEW of 36.7 cm [28] (data from 1961 to 1990). The length of the ski3 slopeof 19 is 950 mcover, with and an a altitudinal mean snow difference depth of 36.7 of 220 cm m[28] (500–720 (data from m a.s.l.),1961 to western 1990). The to northernlength of the aspect, ski slope and is slope fromcover,950 7◦ mto withand 25◦ aan(Figure mean altitudinal snow2). Since depth difference theof 36.7 establishment of cm220 [28]m (500–72 (data of from0 them a.s.l.), 1961 ski center towestern 1990). in toThe 2007, northern length the ofaspect, ski the slope ski and slope has slope beenis covered950from m by 7° with artiﬁcialto 25°an altitudinal(Figure snow 2). (Figure difference Since1 b).the Atofestablishment 220 the m end (500–72 ofthe of0 mthe winter a.s.l.), ski center season, western in a to2007, high northern the volume ski aspect, slope of snow andhas slope remainsbeen on thefromcovered slope 7° byto (Figure 25°artificial (Figure1a). snow Fixed 2). (FigureSince snow-making the 1b). establishment At the end lances, of theof which thewinter ski can season,center reach in a high a2007, distance volume the ski from of slope snow 5 tohas remains 30 been m and on the slope (Figure 1a). Fixed snow-making lances, which can reach a distance from 5 to 30 m and operatecovered at a by maximum artificial snow working (Figure temperature 1b). At the end of − of4 the◦C, winter have beenseason, used a high to producevolume of snow. snow remains The stream operate at a maximum working temperature of −4 °C, have been used to produce snow. The stream “Slanec”on the running slope (Figure at the 1a). foot Fixed of the snow-making ski slope is usedlances, as which the water can reach source. a distance from 5 to 30 m and operate“Slanec” at running a maximum at the wo footrking of the temperature ski slope is of used −4 °C, as thehave water been source. used to produce snow. The stream “Slanec” running at the foot of the ski slope is used as the water source.

Figure 1. (a) The studied ski slope of the Košútka Ski Centre after the snowmelt of natural snow in Figure 1. (a) The studied ski slope of the Košútka Ski Centre after the snowmelt of natural snow in Figurethe surroundings 1. (a) The studiedof the ski ski slope slope on of 18 the February Košútka 2016; Ski Cent (b) There after beginning the snowmelt of the season of natural started snow with in the surroundings of the ski slope on 18 February 2016; (b) The beginning of the season started with an thean surroundingsenormous production of the ski slopeof snow on 18(base February layer 2016; snowmaking; (b) The beginning 21 December of the season2016). startedShown with are enormous production of snow (base layer snowmaking; 21 December 2016). Shown are snowmaking ansnowmaking enormous lances production beside theof skisnow lift at(base the orographiclayer snowmaking; left side of 21the Decemberslope. 2016). Shown are lancessnowmaking beside the lances ski lift beside at the the orographic ski lift at the left orographic side of the left slope. side of the slope.

Figure 2. Remaining snowpack on the investigated ski slope of the Košútka Ski Centre (22 March Figure2011). At 2. theRemaining 96 points snowpack of the snow on coursethe investigated (red dots), sk thei slope snow of depth the Košútka and density Ski Centreof the snow(22 March were Figure 2. Remaining snowpack on the investigated ski slope of the Košútka Ski Centre (22 March 2011). 2011).measured, At the while 96 points the occurrence of the snow of snow course was (red regularl dots),y therecorded snow depthon the and“observed density area”. of the The snow Košútka were At the 96 points of the snow course (red dots), the snow depth and density of the snow were measured, measured,Ski Centre iswhile situated the occurrence in South-Central of snow Slovakia was regularl (Centraly recorded Europe), on where the “observed 15 ski centers area”. (blue The dots) Košútka and while the occurrence of snow was regularly recorded on the “observed area”. The Košútka Ski Centre Skifour Centre investigated is situated precipitation in South-Central stations Slovakia (pink dots) (Central are located. Europe), where 15 ski centers (blue dots) and is situatedfour investigated in South-Central precipitation Slovakia stations (Central (pink dots) Europe), are located. where 15 ski centers (blue dots) and four investigatedThe Košútka precipitation Ski Centre stations is one (pinkof the dots)15 South-Cent are located.ral Slovakian ski centers in operation (Figure 2). OtherThe ski Košútka centers are Ski out Centre of service is one becauseof the 15 of South-Cent a lack of naturalral Slovakian snow orski because centers ofin economicoperation problems.(Figure 2). Other ski centers are out of service because of a lack of natural snow or because of economic problems.

Water 2018, 10, 907 4 of 19

The Košútka Ski Centre is one of the 15 South-Central Slovakian ski centers in operation (Figure2). Other ski centers are out of service because of a lack of natural snow or because of economic problems. The average length of the winter season at the 15 ski centers is 87 days (start: 20 December; end: 17 March; Table1), while the average ski slope elevation in all the ski centers is lower than 1000 m a.s.l., except for Skalka arena (1105 m a.s.l.). Ski slopes of the South-Central Slovakian ski centers are 68% artiﬁcially covered on average (Table1). At eight ski centers, ski slopes are fully artiﬁcially covered, while in three ski centers snowmaking is not used. The investigated precipitation stations of the Slovak Hydrometeorological Institute (SHMÚ) have comparable elevation (from 575 to 771 m a.s.l.) and location in the South-Central Slovakia to the 15 ski centers (Figure2). The macro climate conditions of the localities where the precipitation stations are situated are comparable to the characteristics of the Košútka Ski Centre study site (see above).

Table 1. Characteristics of the South-Central Slovakian ski centers. Probable start/end of the expected winter season 2018–2019, determined according to www.onthesnow.sk[ 29]. Artiﬁcially covered slopes = the percentage of the artiﬁcially covered ski slopes. Investigated ski center highlighted in bold.

Winter Season 2018–2019 Elevation (m a.s.l.) Artiﬁcially Covered Name of the Ski Center Start–End Length Min. Max. Average Slopes (%) Ski Cigel’ 26 December–17 March 81 630 825 728 100 DaˇcovLom—Lomník 2 January–17 March 74 425 530 478 100 Biele Vody—Hriˇnová 2 January–3 March 60 874 992 933 100 Košútka Ski Centre 25 December–10 March 75 500 720 610 100 Ski Krahule 7 December–24 March 107 900 1060 980 100 Ski Král’ová, Zvolen 2 January–10 March 67 650 800 725 0 Hotel Royal Látky 15 December–31 March 106 927 1025 976 33 Salamandra Resort 8 December–24 March 106 579 850 715 100 Skalka arena 8 December–7 April 120 958 1252 1105 72 Ski Blanc Ostrý Grúˇn 22 December–10 March 78 453 560 507 53 Ski TMG Remata 21 December–3 March 72 500 590 545 100 Ski centrum Drozdovo 8 December–31 March 113 690 810 750 56 Skicentrum Kokava—Línia 8 December–24 March 106 660 820 740 100 Tisovec–Bánovo 2 January–10 March 67 600 790 695 0 SKI Park Závada 2 January–10 March 67 555 700 628 0 Average 20 December–17 March 87 660 822 741 68

2.2. Meteorological, Snow, and Snowmaking Conditions Four precipitation stations (Figure2) situated below 1000 m a.s.l. were selected to identify the mean monthly snow depth in South-Central Slovakia. A depth of natural snow cover of at least 30 cm on grassland is considered sufficient for skiing [30]. In this study, a month was considered as suitable for ski slope operation when the mean monthly snow depth of natural snow cover was higher than 30 cm. Steiger [31] defined the minimum depth of the artificially covered ski slope snowpack as 20 cm, because of the higher snow density compared to natural snow cover. The artificially covered ski slope snowpack at the Ko´sútka Ski Centre was considered as suitable for operation when its depth was at least 20 cm. To analyze the meteorological and snow conditions, the mean monthly values were calculated from six seasons (from 2010–2011 to 2015–2016) and mean seasonal values were calculated from six months (XI–IV; the period with snow occurrence) or from four months (XII–III; the period when the South-Central Slovakian ski centers are in operation). To distinguish the seasonal values, the proper months are shown in brackets). The daily values of precipitation totals, the depth of new snow, and the depth of natural snow cover were measured by the Slovak Hydrometeorological Institute (SHMÚ) at the Snohy precipitation station (Figure2; 771 m a.s.l.; 48.628 ◦ N, 19.550◦ E), 7 km away from the ski center (air direct distance). The daily average temperature, wind speed, and wind direction was recorded by the meteorological station at the ski center. The analyzed data were from seasons 2010–2011 to 2015–2016, and, during each season, the months XI–IV were evaluated. Water 2018, 10, 907 5 of 19

The number of potential snowmaking days (PSD = days with optimal snowmaking conditions) and required number of snowmaking days (RNSD = number of days required for balancing snow melt by snow production) was identified for each month from XI to IV [15]. The number of PSD was calculated as a sum of days that reached the threshold of −2 ◦C daily average temperature [15]. The RNSD value was calculated according to a formula described in Steiger and Mayer [15]. A degree day factor of 3 mm was used in the formula because of the ski center’s low elevation. This factor describes the runoff (in mm) per degree day (the sum of all positive daily average temperatures). A month in which the PSD value is greater than the RNSD value is defined by Steiger and Mayer [15] as a month suitable for snowmaking. If a positive difference between PSD and RNSD was determined in several days greater or equal to five days in a month, the month was considered suitable for base layer snowmaking. This is because the average snowmaking systems can produce snow cover suitable for skiing (20 cm thick) in five days [31]. Base layer snowmaking is defined as ”the first area-wide snowmaking of a ski season, mostly started between mid-November and beginning of December” [32].

2.3. Characteristics of the Ski Slope Snowpack After the natural snow had melted away in the surroundings of ski slope (Figures1a and2) , the snow depth and density of the snow were measured on the artificially covered ski slope. The measurements were performed for only one day in each of the winter seasons from 2010−2011 to 2015−2016, except for 2013−2014 (when the ski center was out of service). The depth of the snow was always measured at 96 points, and the snow density was measured at least five points of the snow course (Figure2). The points of the snow course were localized by a GPS receiver and the SKPOS service (Slovak real-time positioning service). A model VS-43 snow sampling tube was used to obtain gravimetric samples of snow to measure the depth-averaged snow density. The method of the manual snow depth and density measurement is more thoroughly described in Hríbik et al. [33]. Ninety-six values of snow water equivalent were calculated from 96 values of snow depth multiplied by the mean value of the snow density. The ski slope snowpack was observed in the field and on ski center webcams to detect the date of its snowmelt. The duration of the examined snowpack melting, compared to off-piste sites with natural snow, represents the period between the date of our measurements and the date of its snowmelt. The snowpack was considered melted when less than 5% of the observed area (4.1 ha) was covered by snow (Figure2). To assess the distribution of snow over the groomed ski slope, the relationship between the snow depth and the closest distance from the fixed snow-making lances was tested using the set of 96 points of the snow course (Figure2). The distance of the points from the snow-making lances was generated in a GIS environment using the command “Near“. Only those lances which were in operation in a particular season were used in the analyses.

2.4. Statistical Analysis The relationship between the dependent variables (mean seasonal value of daily air temperature; mean seasonal depth of the ski slope snowpack; melting period of the ski slope snowpack; mean daily average temperature during the melting period) and the independent variables (six winter seasons; snowmelt day of natural snow cover) was tested in STATGRAPHICS using a simple linear regression. The output of the analyses included the Pearson correlation coefficient (r), which quantifies the strength of the linear statistical relationship. The significance of the relationship was examined by testing the variance of the values around the linear regression at the 95% significance level. If the “p” value was equal to or greater than 0.05, the relationship was not significant. In the chapter results, the mean values are presented with standard deviations (mean ± SD). To analyze the relationship between the snow depth and the closest distance from the fixed snow-making lances, the statistical tests of the logarithmic relationships (ANOVA) were used. The strength of each relationship was determined with the correlation coefficient (r). For the five-season multiple comparison of the ski slope, snowpack characteristics Water 2018, 10, 907 6 of 19

(snow depth,Water 2018 snow, 10, x FOR density, PEER REVIEW and snow water equivalent) used the multiple comparison procedure6 of 19 in STATGRAPHICS to determine which means were significantly different from each other. The output shows thedifferent estimated from differenceeach other. and The statisticallyoutput shows significant the estimated differences difference between and statistically each pair ofsignificant means. differences between each pair of means. 3. Results 3. Results 3.1. Meteorological and Snow Conditions 3.1. Meteorological and Snow Conditions 3.1.1. South-Central Slovakia 3.1.1. South-Central Slovakia The depth of natural snow cover on grassland is considered to be sufficient for skiing (ski slope The depth of natural snow cover on grassland is considered to be sufficient for skiing (ski slope operation) when it is at least 30 cm [30]. In the six-season average, the mean monthly depth of natural operation) when it is at least 30 cm [30]. In the six-season average, the mean monthly depth of natural snow cover in South-Central Slovakia was sufficient for ski slope operation for, maximally, two months snow cover in South-Central Slovakia was sufficient for ski slope operation for, maximally, two (January,months February; (January, Figure February;3b) in two Figure of six 3b) seasons in two (Tableof six seasons2). The probability(Table 2). The that, probability in the winter that, in season, the a monthwinter with sufficientseason, a month monthly with average sufficient snow monthly depth average will occur snow varied depth from will 17%occur to varied 33%. Highfrom 17% standard to deviations33%. displayed High standard in Figure deviations3a express displayed high in inter-seasonal Figure 3a express variability high inter-seasonal of the monthly variability average of snowthe depth, whichmonthly was average the highest snow atdepth, all precipitation which was stationsthe highes (“station”)t at all precipitation in February. stations The highest (“station”) variability in in FebruaryFebruary. was detectedThe highest at thevariability Bane station, in February where was the detected monthly at averagethe Bane snowstation, depth where in the February monthly 2012 was 66average cm and snow in February depth in 2014 February was 12012 cm. was Seasons 66 cm 2011–2012and in February and 2012–20132014 was 1 werecm. Seasons snow-rich 2011–2012 because the monthlyand 2012–2013 average were snow snow-rich depth in because all precipitation the monthly stations average wassnow higher depth in than all precipitation 30 cm for at stations least one was higher than 30 cm for at least one month (Table 2). Two month-long periods, when the monthly month (Table2). Two month-long periods, when the monthly average snow depth was higher than the average snow depth was higher than the threshold of 30 cm, were detected at the Bane station in the threshold of 30 cm, were detected at the Bane station in the 2011–2012 and 2012–2013 seasons and in 2011–2012 and 2012–2013 seasons and in the Snohy station in the 2011–2012 season. At all the Snohyprecipitation station in stations, the 2011–2012 the threshold season. of 30 At cm all (mean precipitation average snow stations, depth) the was threshold not reached of 30 in cm four (mean of averagesix snow seasons, depth) indicating was not that reached they were in foursnow of-poor six seasons,(seasons 2010–2011, indicating 2013–2014, that they 2014–2015, were snow-poor and (seasons2015–2016) 2010–2011, (see 2013–2014, Table 2). 2014–2015, and 2015–2016) (see Table2).

80 6 Štiavnica Hrochoť Bane Snohy Štiavnica Hrochoť Bane Snohy 5 60 Mean values (2010 − 2016) 4 40 3 2 20

Snow depth (cm) 1 Number of seasons Number of 0 0 a.) XI. XII. I. II. III. IV. b.) XI. XII. I. II. III. IV.

Figure 3. (a) Six-season mean values (mean ± SD) of monthly average snow depth at the four Figure 3. (a) Six-season mean values (mean ± SD) of monthly average snow depth at the four precipitationprecipitation stations, stations, which which are sorted are sorted in ascending in ascend ordering order according according to their to elevationtheir elevation (Štiavnica–lowest (Štiavnica– station).lowest The horizontal station). The dashed horizontal line dash indicatesed line the indicates depth the of snowdepth thatof snow is sufﬁcient that is sufficient for skiing for skiing on natural on snow (>30natural cm); snow (b) The(>30 numbercm); (b) The of seasonsnumber (fromof seasons the six(from analyzed the six analyzed seasons) seasons) in which in thewhich monthly the averagemonthly depth ofaverage natural depth snow of covernatural was snow sufﬁcient cover was for sufficient skiing. for skiing.

Table 2.TableMonthly 2. Monthly average average snow snow depth depth at theat the four four precipitation precipitationstations stations from the the 2010–2011 2010–2011 to tothe the 2015–20162015–2016 season. season. Values Values > 30 cm> 30 (sufﬁcientcm (sufficient natural natural snow snow depth depth for for skiing)skiing) are are highlighted highlighted in inyellow. yellow. Štiavnica 575 m a.s.l. Hrochoť 652 m a.s.l. IX. 2 Štiavnica0 5750 m a.s.l. 0 0 0 IX. 3 0 Hrochot’0 652 m0a.s.l. 0 0 IX. XII.2 12 0 2 09 01 01 0 0 IX. XII. 316 03 013 06 0 0 0 0 XII. I.12 3 218 928 10 1 4 0 4 XII. I. 164 323 1329 61 5 0 4 0 I. II.3 2 18 28 2847 00 424 4 1 I. II. 42 2337 2945 10 18 5 1 4 II. III.2 0 28 0 4713 00 240 1 0 II. III. 2 0 37 2 457 00 0 18 0 1 III. IV.0 0 00 131 00 02 0 0 III. IV. 00 20 71 00 3 0 0 0 IV. 0 0 1 Bane 758 0 m a.s.l. 2 0 IV. 0 0 Snohy 1 771 m 0a.s.l. 3 0 IX. 2 0Bane 758 m0 a.s.l.1 0 0 IX. 3 0 Snohy0 771 m a.s.l.0 0 0 IX. XII.2 16 0 7 015 111 01 0 0 IX. XII. 314 07 017 05 1 0 0 0 XII. I.16 4 752 1533 110 110 0 9 XII. I. 146 743 1728 5 2 6 1 5 0 I. II.4 252 66 3361 01 1025 9 7 I. II. 6 3 4338 2850 21 26 6 2 5 II. III.2 066 14 6126 10 25 1 7 1 II. III. 3 0 38 5 5016 10 0 26 0 2 III. IV.0 0 14 0 267 00 16 1 0 III. IV. 00 50 160 00 2 0 0 0 IV. 0 0 7 0 6 0 IV. 0 0 0 0 2 0 Season 2010–2011 2011–2012 2012–2013 2013–2014 2014–2015 2015–2016 Season 2010–2011 2011–2012 2012–2013 2013–2014 2014–2015 2015–2016 Water 2018, 10, x FOR PEER REVIEW 7 of 19

Water 2018, 102010–, 907 2011– 2012– 2013– 2014– 2015– 2010– 2011– 2012– 2013– 2014– 72015– of 19 Season Season 2011 2012 2013 2014 2015 2016 2011 2012 2013 2014 2015 2016

3.1.2.3.1.2. Koš Košútkaútka Ski Ski Centre Centre TheThe mean mean monthly monthly values values calculated calculated fromfrom six six seasons seasons (from (from 2010–2011 2010–2011 to to 2015–2016) 2015–2016) and and the the meanmean seasonal seasonal valuesvalues calculatedcalculated fromfrom sixsix monthsmonths (XI–IV)(XI–IV) forfor thethe Koš Košútkaútka SkiSki Centre Centre showed showed the the followingfollowing patterns patterns in in precipitation, precipitation, snow, snow, and and temperature. temperature. SolidSolid precipitationprecipitation (snow) in in the the study study site site occu occurredrred from from November November to April to April (Figure (Figure 4a,c).4 Snowa,c). Snowrepresented represented the highest the highest percentage percentage of the total of the mo totalnthly monthlyprecipitation precipitation in January in (61%), January December (61%), December(59%), and (59%), February and (39%) February (Figure (39%) 4c). (FigureMean monthl4c). Meany precipitation monthly precipitation totals (mean totals± SD) higher(mean than± SD) 55 higher± 13 mm than (value55 ± of13 XI–IV, mm (value average) of XI–IV,were determined average) were in February determined (69 ± in 60 February mm), November (69 ± 60 (65 mm), ± 44 Novembermm), and (65January± 44 mm),(62 ±and 27 Januarymm) (Figure (62 ± 4a),27 mm) while (Figure in December4a), while the in Decemberlowest mean the lowestmonthly meanprecipitation monthly total precipitation was identified total was (39 identified ± 3 mm). (39 A± high3 mm). inter-seasonal A high inter-seasonal variability variability of the monthly of the monthlyprecipitation precipitation totals was totals identified was identified in November, in November, January, January, February, February, and March and March(53 ± 36 (53 mm)± 36because mm) becauseof the high of the standard high standard deviation deviation of the mean of the monthly mean monthly precipitation precipitation totals (Figure totals (Figure 4a). 4a). TheThe highest highest seasonal seasonal precipitation precipitation totals totals were were found found in in the the 2012–2013, 2012–2013, 2015–2016, 2015–2016, and and 2010–2011 2010–2011 seasonsseasons (more(more thanthan 328328 mm–value of six-season six-season average; average; Figure Figure 4b).4b). In In the the 2012–2013 2012–2013 season, season, the thehighest highest volume volume of ofsolid solid precipitation precipitation was was identified identified (254 (254 mm). mm). Snow Snow in the 2011–20122011–2012 (52%)(52%) andand 2012–20132012–2013 (51%) (51%) seasons seasons represented represented more more than than 50% 50% of of the the seasonal seasonalprecipitation precipitationtotals totals(Figure (Figure4 d).4d). OnOn thethe contrary,contrary, solidsolid precipitationprecipitation duringduring thethe 2013–20142013–2014 (12%)(12%) andand 2015–20162015–2016 (13%)(13%) seasonsseasons representedrepresented the the lowest lowest percentage percentage of of the the seasonal seasonal total. total.

160 800 Rain Mean values Rain Mean values 120 (2010–2016) 600 (IX–IV) Snow Snow 80 400

40 200 Precipitation (mm) Precipitation Precipitation (mm) Precipitation 0 0 XI. XII. I. II. III. IV. 2010 2011 2012 2013 2014 2015 2011 2012 2013 2014 2015 2016 (a) (b)

100% 100% 80% 80% 60% 60% 40% 40%

Precipitation (%) Precipitation 20% 20% 0% 0% Precipitation totals (%) totals Precipitation XI. XII. I. II. III. IV. 2010 2011 2012 2013 2014 2015 (c) (d) 2011 2012 2013 2014 2015 2016

FigureFigure 4. 4.Mean Mean ( a(a)) monthly monthly and and ( b(b)) seasonal seasonal precipitation precipitation totals totals in in the the solid solid (snow) (snow) and and liquid liquid (rain) (rain) statesstates at at Koš Košútkaútka Ski Centre.Ski Centre. The standardThe standard error bars erro ofr thebars means of the were means calculated were from calculated the precipitation from the totals.precipitation The horizontal totals. The dotted horizontal lines indicatedotted lines the meanindicate of thethe displayedmean of the values. displayed The percentagevalues. The componentpercentage barcomponent charts show bar thecharts percentage show the from percentage the mean from (c) monthlythe mean or (c (d) )monthly seasonal or precipitation (d) seasonal totalsprecipitation (charts above). totals (charts above).

InIn the the six-season six-season average, average, the meanthe mean monthly monthly snow depthsnow ofdepth natural of snownatural cover snow was cover not sufﬁcient was not forsufficient skiing infor all skiing months in all with months snow with occurrence snow occurrence (XI–IV; Figure (XI–IV;5a). Figure The mean5a). The monthly mean monthly snow depth snow wasdepth lower was than lower the than sufﬁcient the sufficient snow depth snow fordepth ski fo sloper ski operationslope operation without without snow snow production production (30 cm). (30 Thecm). highest The highest mean mean monthly monthly snow snow depth depth (±SD) (±SD) was was determined determined in Februaryin February (20.0 (20.0± ±21.2 21.2 cm) cm) and and JanuaryJanuary (14.9 (14.9 ±± 16.816.8 cm). cm). The The winter winter season season at atthe the study study site site starts starts at the at theend end of December of December and andends endsin the in middle the middle of March of March(Table 1). (Table Therefore,1). Therefore, the mean the seasonal mean value seasonal of snow value depth of snow for natural depth snow for naturalcover was snow calculated cover was from calculated these four from months these four(XII–III). months The (XII–III).mean seasonal The mean depth seasonal of natural depth snow of

Water 2018, 10, 907 8 of 19 Water 2018, 10, x FOR PEER REVIEW 8 of 19 naturalcover (XII–III) snow cover was (XII–III) lower than was the lower sufficient than the snow sufficient depth snowfor ski depth slope for operatio ski slopen (30 operation cm) in all (30 the cm) six inanalyzed all the six winter analyzed seasons winter (Figure seasons 5c). The (Figure six-season5c). The average six-season mean averageseasonal meansnow seasonaldepth was snow 11.4 ± depth11.3 wascm (XII–III 11.4 ± 11.3mean cm ± (XII–IIISD from mean seasons± SD 2010 from–2016). seasons The 2010–2016). results showed The results high showedinter-seasonal high inter-seasonalvariability in variabilitythe mean seasonal in the mean depth seasonal of natural depth snow of (Figure natural 5c). snow The (Figure highest5c). mean The highestseasonal mean values seasonal(mean ± values SD) were(mean identified± SD) inwere seasons identified 2012–2013 in seasons (27.7 ± 2012–2013 16.0 cm) and (27.7 2011–2012± 16.0 cm) (23.3 and ± 20.1 2011–2012 cm). On (23.3the ±contrary,20.1 cm) the. On lowest the contrary, mean seasonal the lowest depths mean of natural seasonal snow depths were of identified natural snow in seasons were identified 2015–2016 in(1.7 seasons ± 2.2 2015–2016cm) and 2013–2014(1.7 ± 2.2 (1.9 cm) ±and 1.9 cm). 2013–2014 The values (1.9 ± of1.9 the cm). mean The seasonal values ofand the monthly mean seasonal snowfall andtotals monthly showed snowfall the same totals pattern showed (Figure the 5b,d). same The pattern highest (Figure mean5 monthlyb,d). The snow highestfall totals mean (mean monthly ± SD) snowfallwere determined totals (mean for ±theSD) following were determined months: January for the (47.5 following ± 32.2 months:cm), February January (29.5 (47.5 ± 29.1± 32.2 cm), cm), and FebruaryDecember(29.5 (26.5± ±29.1 20.0 cm), cm).and No December trend in the(26.5 season± 20.0al snow cm). depth No trend or snowfall in the seasonal totals was snow determined. depth or snowfallThe totals mean was seasonal determined. value (XII–III) of daily air temperature has shown an increasing tendency (y = 0.5979The meanx − 1.5342; seasonal Figure value 5c) since (XII–III) the of2010–2011 daily air season. temperature The relatively has shown strong an increasingPearson’s correlation tendency (ycoefficient= 0.5979x −(r 1.5342;= 0.711)Figure only 5confirmsc) since the this 2010–2011 result. Mean season. monthly The relatively daily average strong Pearson’stemperatures correlation (mean ± coefficientSD) under (r zero= 0.711) were only indicated confirms only this in result. December Mean (–0. monthly6 ± 2.5 daily°C), January average (–1.2 temperatures ± 1.3 °C),(mean and February± SD) ◦ ◦ under(–0.3 zero± 2.3 were °C) (Figure indicated 5c). only These in December relatively (–0.6high± mean2.5 C),winter January temperatures (–1.2 ± 1.3 couldC), andbe considered February ◦ (–0.3inappropriate± 2.3 C) conditions (Figure5c). for These snowmaking. relatively high mean winter temperatures could be considered inappropriateThe mean conditions seasonal for snow snowmaking. depth of natural snow cover in relation to the daily average temperaturesThe mean seasonal(Figure 5c) snow resulted depth in of the natural snowmelt snow covertiming in of relation the natural to the snow daily cover average (see temperatures chapter 3.3.). (FigureThe earliest5c) resulted snowmelt in the date snowmelt of the natural timing snow of the cover natural (18 snow February) cover was (see identified chapter 3.3). in the The 2015–2016 earliest snowmeltseason with date the of the highest natural mean snow seasonal cover (18 daily February) average was temperature identified in the(1.8 2015–2016 °C) and the season lowest with mean the ◦ highestseasonal mean snow seasonal depth (1.7 daily cm). average On the temperature contrary, the (1.8 latestC) andsnowmelt the lowest day of mean the natural seasonal snow snow cover depth (10 (1.7April) cm). was On theidentified contrary, in thethe latest2012–2013 snowmelt season, day wh ofen the the natural mean snow seasonal cover daily (10 April) average was temperature identified inreached the 2012–2013 the lowest season, value when (–1.3 the °C), mean and seasonalthe mean daily seasonal average snow temperature depth reached reached the highest the lowest value value (27.7 ◦ (–1.3cm). C), and the mean seasonal snow depth reached the highest value (27.7 cm).

50 sd Mean values 10 80 Mean values (2010 − 2016) (2010 − 2016) 40 T 8 60 30 6 40 20 4 10 2 20 Snow depth (cm)

0 0 Temperature (°C) 0 -10 XI. XII. I. II. III. IV. -2 Total snowfalls (cm) XI. XII. I. II. III. IV. (a) (b) 50 10 sd Mean values 300 Mean values 40 (XII. − III.) 8 (XII. − III.) T 30 6 200

20 4 100 10 2 Snow depth (cm)

0 0 Temperature (°C) 0 Total snowfalls (cm) -10 2010 2011 2012 2013 2014 2015 -2 2010 2011 2012 2013 2014 2015 2011 2012 2013 2014 2015 2016 (c) 2011 2012 2013 2014 2015 2016 (d) Figure 5. Mean (a,b) monthly and (c,d) seasonal values of the daily average snow depth (sd), daily Figure 5. Mean (a,b) monthly and (c,d) seasonal values of the daily average snow depth (sd), dailyaverage average temperature temperature (T), and (T), total and totalsnowfall snowfall (sum (sumof snowfalls). of snowfalls). The horizontal The horizontal dotted dottedlines indicate lines indicatethe mean the value mean from value the from displayed the displayed bar plot bar data. plot Bar data. plots Bar are plots shown are shownwith SD. with SD.

3.2. Snowmaking Conditions 3.2. Snowmaking Conditions The main meteorological conditions affecting snowmaking are (in order of importance): (i) The main meteorological conditions affecting snowmaking are (in order of importance): temperature; (ii) relative humidity; (iii) wind speed; and (iv) wind direction. (i) temperature; (ii) relative humidity; (iii) wind speed; and (iv) wind direction. According to Steiger and Mayer [15], the days with T lower than −2 °C daily average temperature According to Steiger and Mayer [15], the days with T lower than −2 ◦C daily average temperature are defined as potential snowmaking days with optimal snowmaking conditions. At the Košútka Ski are deﬁned as potential snowmaking days with optimal snowmaking conditions. At the Košútka Centre, potential snowmaking days occurred from November to March, with a peak in January Ski Centre, potential snowmaking days occurred from November to March, with a peak in January (Figure 6a). The optimal conditions for snowmaking (Table 3) were, therefore, mainly in January (13 days), December (10 days), and February (9 days).

Water 2018, 10, 907 9 of 19

(Figure6a). The optimal conditions for snowmaking (Table3) were, therefore, mainly in January (13Water days), 2018, 10 December, x FOR PEER (10 REVIEW days), and February (9 days). 9 of 19

Table 3.3.The The number number of of potential potential snowmaking snowmaking days days (PSD) (PSD) when when the daily theaverage daily average temperature temperature reached ◦ reachedthe threshold the threshold of −2 C, of the−2 °C, required the required number number of snowmaking of snowmaking days (RNSD), days (RNSD), and six-season and six-season mean meanmonthly monthly values values with standard with standard deviation deviation (Mean ±(MeanSD). Mean± SD). monthly Mean mont valueshly invalues bold identifyin bold identify a positive a positivedifference difference between between PSD and PSD RNSD. and RNSD.

2010–2011 2011–2012 2012–2013 2013–2014 2014–2015 2015–2016 Mean ± SD 2010–2011 2011–2012 2012–2013 2013–2014 2014–2015 2015–2016 Mean ± SD PSD RNSD PSD RNSD PSD RNSD PSD RNSD PSD RNSD PSD RNSD PSD RNSD XI. PSD2 RNSD28 PSD6 RNSD23 PSD0 RNSD23 PSD2 RNSD23 PSD0 RNSD26 PSD2 RNSD26 PSD2.0 ± 0.9 RNSD22.4 ± 6.2 XII.XI. 202 282 6 4 23 1 019 231 2 8 23 5 0 6 2611 23 2612 2.0 ±10.00.9 ± 3.1 22.4 5.9± ± 6.24.5 XII.I. 1720 25 412 13 1918 13 8 8 5 9 6 8 11 6 314 12 4 10.0 12.8± 3.1 ± 1.8 5.9 4.9± ±4.5 2.2 II.I. 1517 54 1218 34 18 9 3 4 8 1 911 813 64 14 0 4 13 12.8 ±9.31.8 ± 3.0 4.9 6.6± ±2.2 4.3 III.II. 152 21 4 182 4 7 911 47 1 0 1132 130 418 00 13 20 9.3 ±2.53.0 ± 1.7 6.620.6± ±4.3 8.3 IV.III. 02 2146 20 742 110 742 00 3243 00 1836 00 2043 2.5 ± 1.7 0 20.641.9± ±8.3 3.4 IV. 0 46 0 42 0 42 0 43 0 36 0 43 0 41.9 ± 3.4 On average, the months of December, January, and February were identified as suitable for snowmaking.On average, In these the months months, of the December, number January,of potential and snowmaking February were days identified (PSD = asthe suitable days with for optimalsnowmaking. snowmaking In these conditions) months, the was number greater of potential than thesnowmaking required number days of (PSD snowmaking = the days withdays optimal(RNSD =snowmaking number of days conditions) required was for greater balancing than snow the required melt with number snow of production). snowmaking The days difference (RNSD = between number PSDof days and required RNSD foridentifies balancing the snownumber melt of with days snow suitable production). for base Thelayer difference snowmaking between (not PSD for andthe restorationRNSD identifies of melted the numbersnow). At of the days study suitable site, four for basesuch layerdays snowmakingwere identified (not in December, for the restoration eight days of inmelted January, snow). and At three the study days site,in February four such (six-s dayseason were average; identified Table in December, 3). The average eight days snowmaking in January, systemsand three can days produce in February sufficient (six-season snow cover average; for skiing Table (203). cm The thick) average in five snowmaking days [26]. systemsThus, at can the produceKošútka sufficientSki Centre, snow there cover were for skiingenough (20 snowma cm thick)king in fivedays days (for [ 26the]. Thus,20-cm-thick at the Košbaseútka layer Ski snowmaking)Centre, there wereonly enoughin January snowmaking (eight days; days Table (for 3) the on 20-cm-thickaverage. According base layer to snowmaking)the ski center onlyowner, in Januarybase layer (eight snowmaking days; Table is3) necessary on average. at Accordingthe beginn toing the (XII–I) ski center of each owner, season. base layerIn December, snowmaking it was is possiblenecessary during at the two beginning seasons (XII–I) and in of January each season. during In four December, seasons it (six-season was possible average; during Figure two seasons 6b). In twoand inseasons January (2013–2014 during four and seasons 2014–2015), (six-season less average;than a 20-cm-thick Figure6b). Insnow two seasonscover could (2013–2014 be created and (insufficient2014–2015), lessfor skiing). than a20-cm-thick Generally, at snow the beginning cover could of bethe created winter (insufficient season (XII–I) for there skiing). were Generally, 11 days withat the optimal beginning snowmaking of the winter conditions season (XII–I) (PSD), there but wereonly 11six days days with left optimalfor base snowmaking layer snowmaking conditions on (PSD),average. but The only remaining six days five left days for base were layer necessary snowmaking for the restoration on average. of The melted remaining snow. The five number days were of PSDnecessary and RNSD for the is restorationdependent on of the melted daily snow. average The temperature. number of PSDFigure and 6b RNSDclarifies is that, dependent in the months on the withdaily lower average mean temperature. daily average Figure temperatures,6b clarifies the that, number in the of months PSD increased with lower and meanthe number daily of average RNSD decreased.temperatures, Because the number of low ofmean PSD daily increased average and temp the numbereratures of in RNSD December decreased. and January Because in of two low of mean the sixdaily seasons average (seasons temperatures 2010–2011 in December and 2012–2013), and January a high in number two of theof PSD six seasonsin these (seasonsseasons 2010–2011was identified and (Figure2012–2013), 6b). a high number of PSD in these seasons was identified (Figure6b).

24 4 60 Mean values 8 (2010 - 2016) 18 3 45 6 12 2 30 4 6 1 0 0 15 2 -6 2010 2011 2012 2013 2014 2015 -1 -12 2011 2012 2013 2014 2015 2016 -2 Temperature (°C) 0 0 Temperature (°C) Snowmaking days Snowmaking days XI. XII. I. II. III. IV. -18 -3 -15 -2 XII. RNSD XII. PSD -24 I. RNSD I. PSD -4 RNSD PSD T (a)-30 -4 (b) T XII. T I.

Figure 6. ((a)) The The mean mean (±SD) (±SD) number number of of potential potential snowmaking snowmaking days days (PSD) (PSD) in in contrast contrast to to the the required required number of snowmaking days (RND) and the monthly course of mean daily average temperature temperature (T); (T); (b) Seasonal values of PSD PSD vs. vs. RNSD RNSD and and mean mean daily daily average average temperat temperaturesures in in December December and and January. January. The horizontal dotted dotted lines lines indicate indicate the the minimum minimum number number of offive ﬁve days days forfor base base layer layer snowmaking snowmaking (20 (20cm cmthick). thick).

Wind speed and wind direction are not crucial meteorological conditions for snowmaking. Nevertheless, wind significantly affects the accumulation of artificial snow during its production. In three-season averages, during the potential snowmaking days in December and January, wind with a maximum speed of 1 m/s occurred 73% of the time, while it blew 65% of the time from the SW–SE side (Figure 7a,b). The mean difference in the wind speed categories between December and January

Water 2018, 10, 907 10 of 19

Wind speed and wind direction are not crucial meteorological conditions for snowmaking. Nevertheless, wind signiﬁcantly affects the accumulation of artiﬁcial snow during its production. In three-season averages, during the potential snowmaking days in December and January, wind with a maximum speed of 1 m/s occurred 73% of the time, while it blew 65% of the time from the SW–SE side (FigureWaterWater 2018 20187a,b)., ,10 10, ,x x TheFOR FOR PEER PEER mean REVIEW REVIEW difference in the wind speed categories between December and1010 January of of 19 19 was 14 h (2% of occurrence; Figure7a). During the days with optimal snowmaking conditions (PSD) at waswas 1414 hh (2%(2% ofof occurrence;occurrence; FigureFigure 7a).7a). DuringDuring thethe daysdays withwith optioptimalmal snowmakingsnowmaking conditionsconditions (PSD)(PSD) the beginning of the winter season (XII–I), the wind speed was proper for the snow production most atat thethe beginningbeginning ofof thethe winterwinter seasonseason (XII–I),(XII–I), ththee windwind speedspeed waswas properproper forfor thethe snowsnow productionproduction of themost time.most ofof At thethe the time.time. beginning AtAt thethe beginningbeginning of the winter ofof thethe season, winterwinter at sese theason,ason, study atat thethe site, studystudy 94% site,site, of 94% the94% time ofof thethe the timetime wind thethe waswindwind calm or blewwaswas only calmcalm lightly oror blewblew with onlyonly a lightly maximumlightly withwith a speeda maximummaximum of 2 m/s speedspeed from ofof 22 m/s them/s fromSW–SEfrom thethe side SW–SESW–SE (Figure sideside (Figure8(Figure). 8).8).

100100 3030 Mean values XII.XII. I.I. Mean values XII.XII. I.I. MeanMean values values (2013 – 2016) 2525 (2013 – 2016) 7575 (2013 – 2016) (2013 – 2016) 2020 5050 1515 1010 2525 55 00 00 S E N S E N W 0 ≤ u < 1 1 ≤ u < 2 2 ≤ u < 3 3 ≤ u < 4 4 ≤ u < 5 SE W NE 0 ≤ u < 1 1 ≤ u < 2 2 ≤ u < 3 3 ≤ u < 4 4 ≤ u < 5 SE NE SW Percentage of occurrence (%) SSE ESE Percentage of occurrence (%) NW SW Percentage of occurrence (%) SSE ENE ESE Percentage of occurrence (%) NW NNE SSW ENE NNE SSW NNW WSW NNW WNW WSW (a)(a) WindWind speed speed (m/s) (m/s) (b)(b) WindWind direction direction WNW

FigureFigureFigure 7. Percentage 7.7. PercentagePercentage of (a) of windof ((aa)) wind speedwind speedspeed (u) and (u)(u) ( b andand) wind ((bb)) wind directionwind directiondirection occurrences occurrencesoccurrences in December inin DecemberDecember and Januaryandand duringJanuaryJanuary the potential duringduring the snowmakingthe potentialpotential snowmakingsnowmaking days (PSD). daysdays (PSD).(PSD).

N NN N MeanMean values values 125 125 NNWNNW125 NNENNE NNWNNW125 NNENNE (2013–2016)(2013–2016) NW NE NW NE NW 75 NE NW 7575 NE 75 WindWind speed speed WNW ENE WNWWNW ENEENE WNW 2525 ENE 2525 00 ≤ ≤ ws ws < < 1 1 WW -25-25 EE WW -25-25 EE 11 ≤ ≤ ws ws < < 2 2 WSW ESE WSWWSW ESEESE WSW ESE 22 ≤ ≤ ws ws < < 3 3 SWSW SESE SWSW SESE 33 ≤ ≤ ws ws < < 4 4 SSW SSE SSWSSW SSESSE SSW SSE 4 ≤ ws < 5 S SS 4 ≤ ws < 5 XII.XII. S I.I.

Figure 8. Three-season (2013–2016) average wind speed and direction in (XII) December and (I) FigureFigure 8. Three-season 8. Three-season (2013–2016) (2013–2016) average average wind wind speedspeed and direction direction in in (XII) (XII) December December and and (I) (I) January.January. The The graph graph axis axis displays displays the the average average number number of of hours. hours. The The sum sum of of the the displayed displayed hours hours is is 676 676 January. The graph axis displays the average number of hours. The sum of the displayed hours is inin DecemberDecember andand 667667 inin January.January. WindWind rosesroses werewere createdcreated fromfrom thethe meanmean hourlyhourly windwind speedspeed andand 676 in December and 667 in January. Wind roses were created from the mean hourly wind speed and directiondirection data.data. direction data. 3.3.3.3. CharacteristicsCharacteristics ofof thethe SkiSki SlopeSlope SnowpackSnowpack 3.3. Characteristics of the Ski Slope Snowpack TheThe skiski slope slope snowpack snowpack meltsmelts severalseveral weeksweeks (melti(meltingng period period “mp”) “mp”) afterafter thethe naturalnatural snow snow covercover Theinin thethe ski surroundingssurroundings slope snowpack meltsmelts melts awayaway several (Figure(Figure weeks9b).9b). TheThe (melting memeltinglting periodperiod ofof “mp”) thethe skiski after slopeslope the snowpacksnowpack natural snowwaswas thethe cover in theshortestshortest surroundings inin thethe 2012–20132012–2013 melts away seasonseason (Figure (25(25 days)days)9b). and Theand thethe melting longestlongest period inin thethe 2015–2016of2015–2016 the ski season slopeseason snowpack (47(47 days).days). InIn was thethe the six-season average, the snowpack of the artificially covered ski slope persisted on the slope 29 days shortestsix-season in the 2012–2013 average, the season snowpack (25 days)of the andartificial thely longest covered in ski the slope 2015–2016 persisted season on the (47slope days). 29 days In the (median)(median) longerlonger comparedcompared toto off-pisteoff-piste sitessites withwith naturalnatural snow.snow. TheThe naturalnatural snowsnow covercover onon thethe off-off- six-season average, the snowpack of the artificially covered ski slope persisted on the slope 29 days pistepiste sitessites waswas meltedmelted awayaway eacheach seasonseason onon aa differdifferentent datedate (Figure(Figure 9a).9a). TheThe highesthighest differencedifference ofof 5151 (median)daysdays longer waswas identifiedidentified compared betweenbetween to off-piste thethe seasons sitesseasons with 2015–22015–2 natural016016 snow.(18(18 February)February) The natural andand snow2012–20132012–2013 cover (10(10 on April).April). the off-piste AA sites wassignificant,significant, melted linearlinear away relationshiprelationship each season waswas on provedproved a different betweenbetween date thethe (Figure datedate 9inina). thethe The seasonseason highest (independent(independent difference variable)variable) of 51 days was identifiedwhenwhen thethe betweennaturalnatural snowsnow the seasons covercover onon 2015–2016 thethe off-pisteoff-piste (18 sisi February)testes waswas meltedmelted and away 2012–2013away (date(date (10ofof snowmelt)snowmelt) April). A and significant,and thethe linearduration relationshipduration ofof thethe was skiski provedslopeslope snowpacksnowpack between meltingmelting the date periodperiod in the (dependent(dependent season (independent variablevariable 1)1) oror variable) thethe meanmean when dailydaily averageaverage the natural snowtemperature covertemperature on the duringduring off-piste thethe meltingmelting sites was periodperiod melted (dependent(dependent away (date vavariableriable of snowmelt)2)2) (Figure(Figure 9b).9b). and WithWith the anan duration earlierearlier datedate ofthe ofof ski slope snowpacksnowmelt,snowmelt, meltingthethe meltingmelting period periodperiod (dependent ofof thethe skiski variable slopeslope 1)snowpacksnowpack or the mean waswas dailylonger,longer, average andand thethe temperature dailydaily averageaverage during the meltingtemperaturetemperature period duringduring (dependent thisthis meltingmelting variable periodperiod 2) (Figure waswas lower.lower.9b). TheThe With remainingremaining an earlier skiski date slopeslope of snowpacksnowpack snowmelt, thatthat the waswas melting aa mixture of artificial snow and natural precipitation had the following characteristics (five-season periodmixture of the skiof artificial slope snowpack snow and was natural longer, precipitat and theion daily had the average following temperature characteristics during (five-season this melting meanmean valuesvalues ±± SD;SD; FigureFigure 9a,c,d):9a,c,d): snowsnow depth:depth: 44.544.5 ±± 9.59.5 cm,cm, density:density: 618.8618.8 ±± 63.163.1 kg/mkg/m33,, snowsnow waterwater period was lower. The remaining ski slope snowpack that was a mixture of artificial snow and natural equivalentequivalent (snow(snow waterwater equivalentequivalent (SWE):(SWE): 281.4281.4 ±± 46.246.2 mm.mm. AtAt thethe KošútkaKošútka SkiSki Centre,Centre, thethe depthdepth ofof thethe skiski slopslopee snowpacksnowpack atat thethe endend ofof thethe eacheach ofof thethe fivefive seasonsseasons waswas alwaysalways higherhigher thanthan thethe sufficientsufficient snsnowow depthdepth forfor skiingskiing (20(20 cm;cm; FigureFigure 9c).9c). TheThe meanmean

Water 2018, 10, 907 11 of 19 precipitation had the following characteristics (five-season mean values ± SD; Figure9a,c,d): snow depth: 44.5 ± 9.5 cm, density: 618.8 ± 63.1 kg/m3, snow water equivalent (snow water equivalent (SWE): 281.4 ± 46.2 mm. At the Košútka Ski Centre, the depth of the ski slope snowpack at the end of the each of the five seasons was always higher than the sufficient snow depth for skiing (20 cm; Figure9c). The mean depth ofWater the 2018 ski, 10 slope, x FOR snowpack PEER REVIEW measured at the end of the season showed a decreasing inter-seasonal11 of 19 trend (Figure9c; y = −5.181x + 60.051, r = 0.864) and significant differences (Table4). The highest differencedepth of of 22.9 the cm ski was slope identified snowpack between measured seasons at the 2011–2012end of the andseason 2015–2016. showed a The decreasing mean depth inter- of snow measuredseasonal trend on the(Figure artificially 9c; y = − covered5.181x + ski60.051, slope r = at0.864) the and end significant of the winter differences season (Table was 2.34). The times higherhighest (31.2 cm difference difference) of 22.9 than cm the was mean identified seasonal between depth (XII–III)seasons 2011–2012 of natural and snow 2015–2016. in the surroundings The mean depth of snow measured on the artificially covered ski slope at the end of the winter season was 2.3 (five-season average; Figure9c). The highest difference between these two values was determined in times higher (31.2 cm difference) than the mean seasonal depth (XII–III) of natural snow in the the seasons with a shortage of natural snow (seasons 2010–2011, 2011–2015 and 2015–2016). Because of surroundings (five-season average; Figure 9c). The highest difference between these two values was the highdetermined density ofin the seasons ski slope with snowpack, a shortage aof high natural amount snow (sea of watersons 2010–2011, was still 2011–2015 stored in and it after 2015– the natural2016). snow Because had melted of the away.high density In the of five-season the ski slope average, snowpack, the a mean high amount SWE value of water of the was remaining still stored ski slope snowpackin it after the (281.4 natural± 46.2 snow mm; had meanmelted± away.SD)represented In the five-season 120% average, of the seasonal the mean precipitation SWE value of totalsthe (XII–III;remaining234.1 ± 94.7 ski mm;slope Figuresnowpack9d), and(281.4 the ± water46.2 mm; input mean from ± theSD) melting represented ski slope 120% snowpack of the seasonal (=SWE; 281.4 ±precipitation46.2 mm; mean totals± (XII–III;SD) was 234. 1.31 ± times 94.7 highermm; Figure than 9d), the seasonaland the water (XI–IV) input solid from precipitation the melting totalsski (124.6 mm).slope snowpack A significantly (=SWE; different 281.4 ± 46.2 mean mm; SWE mean of ± SD) the skiwas slope 1.3 times snowpack, higher than measured the seasonal at the (XI–IV) end of these seasons,solid precipitation was identified totals between(124.6 mm). five A significantly seasons (Table different4). The mean highest SWE difference of the ski slope (126.5 snowpack, mm) was determinedmeasured between at the the end same of these seasons, seasons, as in thewas case identi offied the meanbetween snow five depth seasons (2011–2012 (Table 4). vs. The 2015–2016). highest difference (126.5 mm) was determined between the same seasons, as in the case of the mean snow At the end of the season, the mean snow density of the ski slope snowpack showed significant depth (2011–2012 vs. 2015–2016). At the end of the season, the mean snow density of the ski slope inter-seasonal differences (Table4). The five-season average showed above-average mean snow snowpack showed significant inter-seasonal differences (Table 4). The five-season average showed 3 ± 3 densityabove-average (higher than mean 618.8 snow kg/m density), identified (higher than in the 618.8 2014–2015 kg/m3), identified(737.4 in95.7 the kg/m2014–2015) and (737.4 2015–2016 ± 95.7 3 (663.7 ±kg/m95.03) kg/mand 2015–2016; Figure (663.79a) seasons. ± 95.0 kg/m3; Figure 9a) seasons.

1000 50 20 y = 0.1649x - 6691.3 mp T avg 800 40 r = 0.868 16 600 30 12 400 20 8 200 10 y = -0,3966x + 16140 4 r = 0.843 Temperature (°C) 0 0 0 Melting period Melting period (days) Snow density (kg/m³)

(a) (b)

120 Ski slope 800 SWE (Ski slope) 800 100 Surroundings Precipitation totals 600 600 80 60 400 400 40 200 200 20 SWE (mm) Snow depth (cm)

FigureFigure 9. (a) Mean9. (a) Mean density density of the of the residual residual snowpack snowpack on on the the artificially artificially coveredcovered ski slope slope after after the the disappearance of natural snow in the surroundings (five seasons); (b) Relationship between the date disappearance of natural snow in the surroundings (five seasons); (b) Relationship between the date in the season (five seasons displayed) when the natural snow cover on the off-piste sites was melted in the season (five seasons displayed) when the natural snow cover on the off-piste sites was melted away and the melting period (mp) or temperature (T avg). The melting period expresses the away and the melting period (mp) or temperature (T avg). The melting period expresses the prolonged prolonged duration of the melting of the snowpack on the artificially covered ski slope compared to durationoff-piste of the meltingsites. The of temperature the snowpack expresses on the the artificially mean daily covered average ski slopetemperat comparedure during to off-pistethe melting sites. The temperatureperiod; (c) Mean expresses depth the of meansnow on daily the averageartificially temperature covered ski slope during (at the the meltingend of winter period; season) (c) Mean in depth ofcomparison snow on theto the artificially mean seasonal covered depth ski (XII–III) slope (atof natural the end snow of winter in the surroundings; season) in comparison (d) Mean snow to the mean seasonalwater equivalent depth (XII–III) (SWE) of of the natural ski slope snow snowpack in the surroundings;(at the end of the (d winter) Mean se snowason) in water comparison equivalent to (SWE)the of theseasonal ski slope precipitation snowpack totals (at (XII–III). the end The of horizo the winterntal dashed season) lines in indicate comparison the mean to value the seasonal except precipitationfor subfigure totals (XII–III).“b”. Mean The values horizontal are displayed dashed with lines standard indicate deviation the mean bars. value except for subfigure “b”. Mean values are displayed with standard deviation bars. The distribution of snow on the ski slope was highly heterogeneous (Figure 10). The high variability of the snow depth data expressing the standard deviation of the mean snow depth is shown in Figure 9c. The observed snow depth minima at the end of each season were close to 0 cm, while the maxima reached values from 100 to 200 cm. The maxima always occurred at a distance below 30 m from the lances, which is the maximum distance of the used snowmaking technique. The

Water 2018, 10, 907 12 of 19

The distribution of snow on the ski slope was highly heterogeneous (Figure 10). The high variability of the snow depth data expressing the standard deviation of the mean snow depth is shown in Figure9c. The observed snow depth minima at the end of each season were close to 0 cm, while the maxima reached values from 100 to 200 cm. The maxima always occurred at a distanceWater 2018 below, 10, x FOR 30m PEER from REVIEW the lances, which is the maximum distance of the used snowmaking12 of 19 technique. The maximum snow depths were close to the snow-making lances. Significant logarithmic relationshipsmaximum snow were depths proved were between close the to snowthe snow-mak depth andingthe lances. distance Significant from the logarithmic fixed snow-making relationships lanceswere in proved all seasons between (ANOVA: the snowp < 0.05; depthFigure and 10 the). Thedistance snow from depth the decreased fixed snow-making as the distance lances from thein all lancesseasons increased. (ANOVA: The correlationp < 0.05; Figure was the 10). lowest The snow in the depth winters decreased of 2011–2012 as the and distance 2012–2013 from (Figure the lances10), whichincreased. were characterized The correlation by thewas highest the lowest mean in seasonal the winters snow of depth 2011–2012 of natural and snow2012–2013 cover (Figure in the ski 10), slopewhich surroundings were characterized (Figure5 a).by the In contrast, highest mean in the seasonal remaining snow three depth seasons of natural with low snow mean cover seasonal in the ski depthslope of surroundings natural snow (Figure cover, the 5a). need In contrast, to produce in the a high remaining volume three of snow seasons resulted with in low a more mean uneven seasonal distributiondepth of natural of snow snow on the cover, ski slope the need and, to therefore, produce a a higher high volume correlation of snow of the resulted analyzed in relationshipsa more uneven (higherdistribution correlation of snow coefficient; on the ski Figure slope 10 and,). therefore, a higher correlation of the analyzed relationships (higher correlation coefficient; Figure 10). Table 4. Multiple, inter-seasonal comparisons of mean snow depth, snow water equivalent (SWE), andTable snow 4. density Multiple, of the inter-seasonal ski slope snowpack, comparisons measured of mean at the snow end ofdepth, the five snow winter water seasons. equivalent Displayed (SWE), areand the snow estimated density differences of the ski between slope snowpack, each pair measured of means. at the end of the five winter seasons. Displayed are the estimated differences between each pair of means. Inter-Seasonal Comparison Snow Depth (cm) SWE (mm) Snow Density (kg/m3) Inter-Seasonal Comparison Snow Depth (cm) SWE (mm) Snow Density (kg/m3) 22 March 2011 vs. 15 March 2012 −7.0 −52.0 −17.2 22 March 2011 vs. 15 March 2012 –7.0 –52.0 –17.2 22 March 2011 vs. 10 April 2013 2.4 25.4 23.7 22 March22 March 2011 vs.2011 5 Marchvs. 10 April 2015 2013 13.1 *2.4 29.0 25.4 − 23.7136.1 * 22 March22 2011March vs. 2011 18 February vs. 5 March 2016 2015 15.9 13.1 * * 74.5 29.0 * –136.1−62.6 * * 15 March22 March 2012 2011 vs. vs. 10 April18 February 2013 2016 9.4 15.9 * 77.4 74.5 ** –62.6 40.9 * 15 March15 March 2012 vs.2012 5 Marchvs. 10 April 2015 2013 20.1 *9.4 81.0 77.4 ** − 40.9118.9 * 15 March15 2012March vs. 2012 18 February vs. 5 March 2016 2015 22.9 20.1 * * 126.5 81.0 * * –118.9−45.4 * 1015 April March 2013 2012 vs. 5vs. March 18 February 2015 2016 10.7 22.9 * 126.5 3.6 * − –45.4159.8 * 10 April10 2013 April vs. 2013 18 February vs. 5 March 2016 2015 13.5 10.7 * 49.1 3.6 –159.8−86.3 * * 5 March10 April 2015 vs.2013 18 vs. February 18 February 2016 2016 2.8 13.5 * 45.4 49.1 –86.3 73.5 * 5 March 2015* denotesvs. 18 February a statistically 2016 significant difference 2.8 at the 95.0% 45.4confidence level. 73.5 * denotes a statistically significant difference at the 95.0% confidence level.

250 22.03.2011; y = -46.51ln(x) + 198.38; r = 0.609

200 13.03.2012; y = -30.85ln(x) + 153.61; r = 0.455 10.04.2013; y = -21.96ln(x) + 116.75; r = 0.288 150 05.03.2015; y = -29.39ln(x) + 129.54; r = 0.648 18.02.2016; y = -32.71ln(x) + 140.96; r = 0.619 100

Snow depth (cm) 50

0 0 102030405060708090100 Distance (m)

Figure 10. Relationships between the snow depth on the artiﬁcially covered ski slope and the closestFigure distance 10. Relationships from the snow-making between the snow lances depth at the on end the ofartificially the 2010 covered−2011 to ski 2015 slope−2016 and seasons.the closest Thedistance correlation from coefﬁcient the snow-making “r” measures lances the at strengththe end ofof thethe logarithmic2010−2011 to relationship. 2015−2016 Theseasons points. The representcorrelation 96 measured coefficient values “r” measures of the snow the depth.strength of the logarithmic relationship. The points represent 96 measured values of the snow depth.

4. Discussion

4.1. Meteorological and Snow Conditions

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4. Discussion

4.1. Meteorological and Snow Conditions

4.1.1. South-Central Slovakia If the operability of the South-Central Slovakian ski centers was dependent only on natural snow, the ski slopes could have been opened only in two of the six analyzed winter seasons. The reason for this is the low monthly average snow depth, which was highly variable between the seasons. The high inter-seasonal variability of the monthly average snow depth confirms a study by Hríbik et al. [33] which was conducted in South-Central Slovakia (660 m a.s.l.). Hríbik et al. [33] identified three of six winter seasons (snow-poor seasons 2006–2009) in which the monthly average snow depth was lower than 30 cm (snow depth > than 30 cm is sufficient for skiing). In the presented study, a monthly average snow depth higher than 30 cm occurred only in January or February, but most often in February. Therefore, continual seasonal operability of the South-Central Slovakian ski slopes could not be achieved from December to March without the help of artificial snowmaking. Hríbik et al. [33] confirmed that the peak snow depth most often occurs in February. Nevertheless, in the snow-rich season 2004–2005, March was identified by Hríbik et al. [33] as the month with the highest monthly average snow depth.

4.1.2. Košútka Ski Centre A general high occurrence of liquid precipitation in the winter season was identified in the presented study, while this occurrence was highly variable between the individual seasons. A tendency of increasing mean seasonal value of the average daily temperature (seasonal = months XII–III) was discovered. These results are in good agreement with those of Pecho et al. [34], who have pointed out that winters after 1991 were not as cold as in the past, which resulted more often in the occurrence of mixed and liquid precipitation. From the six seasons (2010–2016) presented in this paper, the season 2012–2013 was identified as highly above average in precipitation totals (XI–IV) and in snowfall totals (XII–III). This season was described by Mikloš et al. [35] as snow-rich with high peak snow water equivalent in the mountainous watershed located only 10 km northwest of the Košútka Ski Centre. Pecho et al. [36] described this weather situation in more detail. According to Faško [37] and Falt’an et al. [38], precipitations occur currently with a higher intensity than in the past. This leads to the occurrence of months with extremely above normal and below normal levels of precipitation. The presented work confirms these conclusions because of the relatively high standard deviation of the mean monthly precipitation totals in November, January, February, and March. From a comparison of climate regions in Slovakia between the Landscape Atlas of the Slovak Republic published in 2002 [39] and the Climate Atlas of the Slovak Republic published in 2015 [40] there are obvious important changes in some regions and sub-regions [37]. In the areas located approximately 20 km south of the study site (Košútka Ski Centre), the warm, dry sub-region with cold winters (T3) changed to a warm, dry sub-region with mild winters (T2). The increasing seasonal values (XII–III) of the daily average temperature confirm these warming tendencies of South-Central Slovakia [13]. The meteorological and snow conditions of the study site are not suitable for the continuous operation of the ski slope from December to March without artificial snowmaking. The reason for this is the relatively high variability of the monthly average snow depth in the individual seasons. A deficit of natural snowfall due to the variability of meteorological and snow conditions was also identified by Durand et al. [41] in the European Alps. The vulnerability of the French ski resorts to the lack of natural snow was observed by Spandre et al. [42]. The altitude of the snow line with sufficient snow conditions for skiing has a rising trend in the European Alps [43,44]. If the ski slope operation in the investigated low-elevation ski center were dependent only on natural snow, then skiing would only be possible in some days or months during the season. Water 2018, 10, 907 14 of 19

4.2. Snowmaking This study clarifies that operability during every season of the South-Central Slovakian ski slopes is not possible without artificial snowmaking. Nevertheless, snowmaking is dependent on a low air temperature [3]. In South-Central Slovakia, creation of the base layer for skiing is essential at the beginning of the winter season (end of December–beginning of January) because of the high public demand (Christmas holidays). Thus, a high number of potential snowmaking days (PSD; days with optimal snowmaking conditions) is essential mainly in the seasons with a low depth of natural snow. In the Košútka Ski Centre, a low seasonal depth of natural snow cover was identified in four of six seasons (lower than 10 cm). Because of the low air temperature in December or January, the base layer snowmaking was possible in the snow-poor seasons of 2010–2011 and 2015–2016. In the relatively warm season of 2014–2015, the number of PSD was insufficient for base layer creation, but snowmaking was supplied by the above-average seasonal snowfall totals. In the 2013–2014 season, the ski slope of the Košútka Ski Centre was out of service because of warm winter temperatures in which base layer snowmaking was not possible and because of low seasonal snowfall totals. Additionally, Hopkins and Maclean [45] concluded that some regions in Scotland were not able to produce artificial snow due to inadequate meteorological conditions. Many authors claim that the use of artificial snow is a sufficient adaptation strategy against climate change [46,47], although low-altitude resorts remain negatively impacted by seasons with poor snow conditions [48–50]. Moreover, Vojtek et al. [10] and Škvarenina et al. [11] pointed out the general tendency of the decreasing duration of snow cover and solid precipitation occurrence at lower altitudes in Slovakia (Central Europe). In the current meteorological conditions of South-Central Slovakia, the operability of the investigated low-elevation ski slope is possible because of high snow production, which is possible only for a few days in the winter season. In the investigated low-elevation ski center, the wind speed and wind direction are probably not limiting factors for snowmaking. The reason for this is the low occurrence of wind with a speed higher than 2 m/s and a relatively constant wind direction during the days with optimal snowmaking conditions in December and January. Spandre et al. [51] also found ideal wind speed (low) and wind direction (constant) conditions for snowmaking, but in the higher elevated alpine ski resort “Les 2 Alpes” (1680 m a.s.l.). Suitable wind conditions for snowmaking in the investigated ski center could be explained by the results of Spandre et al. [52]. They concluded that the topography and vegetation have significant impacts on the efficiency of snow production. Ideal wind conditions during the potential snowmaking days increase the efficiency of the snowmaking because of low water losses. According to Olefs et al. [53], the water losses during snowmaking (evaporation, sublimation, wind erosion) varied between 5% and 15% for fan guns and from 15% to 40% for snowmaking lances. The mostly constant wind direction is, therefore, beneficial, especially for the use of snow-making lances that have fixed positions, as in the investigated Košútka Ski Centre.

4.3. Characteristics of Ski Slope Snowpack This study confirms that the snowpack of an artificially covered ski slope characterizes high snow depth and density of snow [22]. In contrast to previous surveys [22,33], the presented research was conducted in a low-elevation ski center under 1000 m a.s.l. Mossner et al. [54] reported that snow density on the ski slope ranging between 420 and 620 kg/m3 with a mean value of 556 kg/m3 (undefined ski slope in Switzerland). The results of our study show a high mean snow density of 619 kg/m3 at the end of the winter season (five-season mean value). A high density of the ski slope snowpack at the end of the winter season was also found by Keller et al. [55]. They stated that, in the middle of December, the snow density on slopes with artificial snow is around 500 kg/m3. Such snow becomes increasingly compact over time until it becomes a mixture of hard snow with clear ice with a maximum density around 700 kg/m3. In our case, the mean snow density was the highest at the end of the 2014−2015 season, with a value of 737 kg/m3. Such high mean density was not recorded by the other authors, probably because of the low elevation of the study site and late date of measuring. Water 2018, 10, 907 15 of 19

The high density could be the result of refreezing water or water saturation from the melting snow. The artificial snow significantly increases the depth of snow on the ski slopes [22]. Our results confirm these findings because, after the disappearance of natural snow on the off-piste sites, the depth of the snowpack with artificial snow was still 45 cm (five-season average). The mean depth of snow measured on the artificially covered ski slope at the end of the winter season was 2.3 times higher (70% difference) than at the off-piste sites with natural snow (five-season average). Stoeckli and Rixen [56] showed a 20% difference in the depth of the artificially covered ski slope snowpack compared to controlled plots with undisturbed natural snow (Swiss Alps; 1150–2515 m a.s.l.). The water input from the melting ski slope snowpack at the end of the season was 1.3 times higher than the seasonal (XI−IV) solid precipitation totals. Studies from the Alps confirmed that the water input from the melting ski slope snowpack usually reaches 0.7–2 times (up to five times) that from natural snow [56,57]. The depth of the ski slope snowpack at Košútka was significantly dependent on the distance from the snow-making lances. The maxima (over 2 m) were observed at a distance below 30 m from the lances. This is caused by the high snow production (base layer creation) at the beginning of the winter season. The influence of the wind during base layer snowmaking was probably not significant because of the low wind speed and constant wind direction. Spandre et al. [58] also showed that the highest snow depth occurred within 30 m from the snow gun while low wind speed conditions were determined. In the presented study, the ski slope snowpack (groomed) was examined at the end of the season, while Spandre et al. [58] described the characteristics of the artificial snow pile (undisturbed) from the beginning of the winter season. Therefore, for the managers of the Košútka ski slope, a more equal distribution of artificial snow would be beneficial. The changed characteristics of the ski slope snowpack result in prolonged melting. Keller et al. [55] and Rixen et al. [22] state that artificial snow in the Alps (above 1000 m a.s.l.) melts 28 days and 17 days longer than natural snow, respectively. We observed a prolongation of about 29 days (610 m a.s.l.). The cause is probably the high snow production and the earlier snowmelt of natural snow in the low-elevation study site. In the 2015–2016 season, the natural snow cover melted away at the earliest date (18 February) in the inter-seasonal comparison. This was because of the low seasonal snowfall totals and, consequently, low mean seasonal snow depth. The economic success during the winter season for ski centers is dependent on the income during specific periods (Christmas—end of December; spring academic holidays-February to the beginning of March) [59,60]. As deduced from the six-season average, the ski centers in South-Central Slovakia (under 1000 m a.s.l.) that do not use artificial snowmaking have no chance to expect that the mean monthly snow depth in December will be sufficient for skiing, but the probability that the mean monthly snow depth will be sufficient for skiing in February varied between 17% and 33%. Therefore, snowmaking is the only possible solution to increase the snow depth on South-Central Slovakian ski slopes. In the investigated Košútka Ski Centre, snowmaking has been effective, allowing the ski slope to be operational in five of six winter seasons.

5. Conclusions The results from this study showed that the snow depth of natural snow cover in South-Central Slovakia under 1000 m a.s.l. is not sufficient for continuous ski slope operation from December to March. The probability that, in the winter season, there will be a month with sufficient snow depth for ski slope operation varies from 17% to 33%. At the Košútka Ski Centre (the study site in South-Central Slovakia) the seasonal snowfalls and mean seasonal snow depth are highly variable. Every season, ski slope operability in this ski center is not possible without artificial snowmaking. A high percentage of the winter precipitation consists of liquid precipitation at the study site. Because of the low snow depth of the natural snow cover in the study site, the base layer creation at the beginning of each season is crucial for ski slope operability. A sufficient number of days for base layer snowmaking was identified only in four of six winter seasons. Essential, large production of artificial snow on the ski slope results in unequally distributed snow with high density, depth, and snow water equivalent Water 2018, 10, 907 16 of 19

(SWE). An inter-seasonal comparison of the ski slope snowpack characteristics, measured at the end of the season, showed significant differences in the mean snow depth, SWE, and snow density. The mean snow depth showed a decreasing trend. The distribution of snow on the artificially covered ski slope of Košútka Ski Centre is highly heterogenous. The snow depth decreases as the distance from the snowmaking lances increases. To improve the heterogeneous distribution of snow, it is necessary to move accumulated artificial snow under the snow-making lances further away to the opposite edge of the ski slope. The snowpack of the artificially covered ski slope persists on the slope longer than the natural snow on the off-piste sites. With an earlier snowmelt date of natural snow cover, the melting period of the ski slope snowpack from this date is longer, and the daily average temperature during this period is lower. Because of the high depth and density of the ski slope snowpack, a high amount of water is still stored in it after the natural snow has melted away from the off-piste sites. On average, this amount of water is higher than the seasonal precipitation (period XII–III). We can conclude that, in the current meteorological and snow conditions of South-Central Slovakia, the operability of the low-elevation ski slopes is possible only with high snow production. From the example of the Košútka Ski Centre, it was found that essential base layer snowmaking for ski slope operation is possible only for a few days at the beginning of the winter season. The increasing mean value of the daily average temperature and high occurrence of winter liquid precipitation can finally result in inadequate conditions for ski slope operation.

Author Contributions: M.M. did main part of the data collection, analyses and writing. M.J. wrote introduction and discussion; K.K. helped with data collection; J.Š. provided overall guidance; and J.Š. supervised the study. Funding: This research received no external funding. Acknowledgments: This work was accomplished as a part of VEGA projects No.: 1/0589/15, 1/0111/18. of the Ministry of Education, Science, Research and Sport of the Slovak Republic and the Slovak Academy of Science; and the projects of the Slovak Research and Development Agency No.: APVV-15-0425 and APVV-15-0497. The authors thank the agencies for the support. Authors would also like to show their gratitude to the Slovak Hydrometeorological Institute (SHMÚ) for data accessibility. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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