J. Mt. Sci. (2021) 18(4): 819-833 e-mail: jms@imde.ac.cn http://jms.imde.ac.cn https://doi.org/10.1007/s11629-020-6524-2 Spring recharge and groundwater flow patterns in flysch aquifer in the Połonina Wetlińska Massif in the Carpathian Mountains Karolina MOSTOWIK1* https://orcid.org/0000-0003-2945-5909; e-mail: karolina.mostowik@doctoral.uj.edu.pl Damian KRZYCZMAN1 https://orcid.org/0000-0001-6642-586X; e-mail: damian.krzyczman@gmail.com Eliza PŁACZKOWSKA2 https://orcid.org/0000-0001-7993-6706; e-mail: eliza.placzkowska@zg.pan.krakow.pl Bartłomiej RZONCA1 https://orcid.org/0000-0002-8938-1457;e-mail: b.rzonca@uj.edu.pl Janusz SIWEK1 https://orcid.org/0000-0003-1636-1524;e-mail: janusz.siwek@uj.edu.pl Patryk WACŁAWCZYK1 https://orcid.org/0000-0003-3142-9400; e-mail: patryk.waclawczyk@doctoral.uj.edu.pl *Corresponding author 1 Institute of Geography and Spatial Management, Jagiellonian University in Krakw, Gronostajowa St. 7, 30–387 Krakw, Poland 2 Institute of Geography and Spatial Organization, Polish Academy of Sciences, Św. Jana St. 22, 31–018 Krak, Poland Citation: Mostowik K, Krzyczman D, Płaczkowska E, et al. (2021) Spring recharge and groundwater flow patterns in flysch aquifer in the Polonina Wetlińska Massif in the Carpathian Mountains. Journal of Mountain Science 18(4). https://doi.org/10.1007/s11629-020-6524-2 © The Author(s) 2021. Abstract: Flysch-type aquifers in the Eastern Carpathians usually feed periodic and low-discharge springs. However, in some areas, such as in the upper part of the Połonina Wetlińska Massif, perennial springs with a relatively high discharge were identified. Therefore, the aim of this study was to identify recharge and groundwater flow patterns of three high-discharge springs based on the response of spring discharge to rainfall and on the relationship between specific electrical conductivity of water and spring discharge. The relation between spring discharge and rainfall was investigated by cross-correlation analyses. Generally, cumulative rainfall over a period from 10 days to 3 months is most strongly correlated with discharge; however, the response time of spring discharge varies throughout the year. Faster response to rainfall occurs in the spring after snowmelt, while in the summer and autumn months the response time increases. Two flow systems were identified: 1) a relatively deep, fissure-pore flow system with a long response time to precipitation and 2) a shallow, fissure-dominated system with a short response time, which is superimposed on the longer response. A small range of specific electrical conductivity combined with the varying discharge of two springs suggests that dilution of groundwater by rainwater does not play a significant role. The differences in the studied springs’ response to rainfall can be attributed to the recharge area, regolith features and local bedrock structures, i.e. occurrence of joints and faults, monoclinal dip of rock layers and gravitational slope deformations including ridge-top trenches, which, thus far, have been underestimated in determining groundwater storage capacity in the flysch part of the Carpathians. Keywords: Cross-correlation; Rainfall recharge; Spring response; Sedimentary rocks; Poland Introduction Determining the parameters of aquifers by interpreting spring discharge is one of the oldest methods used in hydrogeology, developed intensively since as early as the 19th century (Maillet 1905; Bonacci 1987). Springs recharged by groundwater penetrating within a shallow active zone are generally characterized by quick response time, even to single rainfall events. In turn, long spring response time is characteristic of springs draining deep aquifers and distant recharge areas. Inferring about groundwater storage capacity based on the dynamics of the groundwater depletion process, including the mechanism of recession of a spring recharged by studied aquifer, is indirect and is based on the simple assumption that the greater the groundwater storage capacity, the more slowly its resources are depleted, which manifests itself in a more stable and long-lasting recharge of springs (e.g. Maillet 1905; Kovács et al. 2005; Buczyński and Rzonca 2011; Płaczkowska et al. 2018). In addition to assessing the rate of depletion of aquifer resources during dry periods, the dynamics of spring discharge after periods of recharging the catchment with rainfall are also interpreted. This makes it possible to draw conclusions about the time of water residence in aquifers and the recharge pattern, in particular the rate of groundwater flow and pressure transfer (Bonacci 1987; Halihan and Wicks 1998; Lee and Lee 2000; Kovács et al. 2005; Fiorillo and Doglioni 2010; Diodato et al. 2014). The main difficulty in interpretation is the fact that the increased spring discharge following the rainfall does not necessarily result from the simple mechanism of inflow of fresh water, but usually from a general pressure increase in the aquifer and the release of “old” stored water pushed out by the “new” water infiltrated from the surface (Maloszewski et al. 2002). The mechanisms of groundwater flow and its gravity drainage from the aquifer are complicated (also in terms of mathematical description) and constitute various modifications and combinations of conceptual models, e.g.the piston flow model and exponential flow model, which are additionally modified by a number of physical phenomena such as mixing of waters of varying properties, molecular diffusion and preferential flow, and others observed in reservoirs of double or triple porosities (Maloszewski et al. 2002; 2004; Sukhija et al. 2003; Maloszewski 2004; Kovács and Perrochet 2008; Zuber et al. 2008). Springs in the Outer Carpathians, built of flysch rocks, drain shallow aquifers supplied with rain and snowmelt water. In recent years, this pattern has overlapped with pronounced climate warming, especially a gradual decrease in snow depth and snow-to-precipitation ratio in the winter, increased evapotranspiration in the summer, a decrease in the contribution of summer rainfall to the annual total, as well as longer periods without rain (Mostowik et al. 2019b; Pińskwar et al. 2019; Szwed 2019). In addition, owing to the complexity of snow cover forming and melting processes in mountain areas, their spatial variability, and the lack of monitoring these changes (such as snow water equivalent), the relationship between spring discharge and snow melting conditions is difficult to clearly identify and describe (Humnicki 2013). The generally complicated patterns of aquifer recharge and drainage cause the displacement and overlapping of water volumes from particular seasons and the inflow of water from recent infiltration, which affect spring discharge. Aquifers in the Flysch Carpathians pose particular difficulties to detailed hydrogeological characterization, especially in terms of identifying groundwater resources and recharge patterns. Aquifers are strongly heterogeneous and anisotropic because they are made of alternating layers of fractured sandstones, characterized by low porosity and permeability of a rock matrix, and clay- or mudstone ductile shale that constitutes aquitards. In addition, these rocks occur in the conditions of very strong tectonic overprint. It has always been emphasized that despite the presence of numerous springs in the Flysch Carpathians, most of them are characterized by low discharge (Chełmicki et al. 2011; Bartnik and Moniewski 2019) and recharged from thin, superficial permeable zone. Thus, deeper groundwater recharge has been marginalized; it has been believed not to play a significant role. Therefore, the identification of springs of discharge periodically exceeding 40 dm3·s-1 in the Połonina Wetlińska Massif (the High Bieszczady Mountains, Polish Flysch Carpathians) was a significant change. On the one hand, it shed completely new light on the mechanisms of groundwater flow patterns in flysch rocks (Mocior et al. 2015; Mostowik et al. 2016; Płaczkowska et al. 2018). On the other hand, it provided the opportunity to carry out more detailed research based on the interpretation of hydrographs of these springs, currently treated as valuable observation sites. The objective of this work is to identify the recharge and groundwater flow patterns in aquifers represented by flysch rocks, based on the response time of spring discharge to rainfall recharge and selected physical properties of water. Within this main objective, three issues will be addressed: (i) the relationship between rainfall and spring discharge; (ii) the relationship between spring discharge and the specific electrical conductivity of water (SEC); and (iii) factors determining observed differences in the response of springs to recharge impulses. 2 Material and Methods 2.1Study area The Połonina Wetlińska Massif (49.17°N, 22.52°E) in the Bieszczady Mountains, which is the study area (Fig. 1), is built of flysch rocks belonging to the Silesian Unit (Malata et al. 2006). These mainly consist of thick-bedded Otryt sandstone interlayered with less resistant shale and thin-bedded sandstone – the total thickness of this member is up to 2000 m (Fig. 1). According to Chowaniec et al. (1983) and Machowski (2010), these rocks are characterized by low storage capacity, caused by quite low porosity (usually less that 6%) and low hydraulic conductivity (1.4×10-6 m·s-1 to a depth of 20 m and 2.4×10-7 m·s-1 in the depth range of 20–40 m), as well as by the shallowness of the permeable zone, up to a maximum of 100 metres. The water flow in aquifers occurs mainly via fissure- or fissure-pore systems. The steep slopes and low retention capacity of the bedrock combined with a dense drainage network limit recharge and groundwater storage as well as promote rapid surface runoff (Płaczkowska et al. 2015). These characteristics are reflected in the rate of groundwater component in the overall river flow, which is generally low in the Bieszczady Mountains and varies in different catchments from 25% to 45% (Łajczak 1996). Aquifers in the Flysch Carpathians are drained by numerous springs of small discharge, usually <0.5 dm3·s-1 (Chełmicki et al. 2011). On the other hand, fractures of tectonic origin occurring in the ridge zones strongly increase the permeability and depth of the active zone in specific localities, thus enlarging the bedrock retention capacity (Kleczkowski 1979; Machowski 2010; Mostowik et al. 2018). In addition, the subsurface water flow in the Połonina Wetlińska slopes is locally modified as a result of mass movements (e.g. lateral spreading, landslide, rock flow), solifluction, and mechanical weathering (Haczewski et al. 2007). The soil thickness is low and depends on the slope, from over 1 m on flat slopes (0°–6°), to 0.5–0.3 m on slopes >15°, and on the ridge (Kacprzak 2001). The regolith usually does not exceed 3 m (Kukulak 2001), however due to local mass movements it may increase several times. Aquifers are recharged by direct infiltration from the surface. The annual precipitation totals in the study area range from 900 mm in valleys to a probable maximum of 1,600-1,700 mm on hilltops (Laszczak et al. 2011; Mostowik et al. 2019b). Another factor also related to altitude is snow cover duration, which in valleys lasts 60–70 days in winter months (Szwed et al. 2017). This period increases with altitude, which means that in the highest parts of the mountains the first snow (not forming a permanent cover) can be expected in November and that the snow cover will have disappeared in April. The landscape of the Bieszczady Mountains is semi­natural. It is dominated by beech and fir forests up to an altitude of 1,150 m a.s.l. and subalpine and alpine meadows covering the highest ridges. The research area covers the ridge zone of the Połonina Wetlińska Massif. 2.2Characteristics of the studied springs The studied springs are located at altitudes ranging from 948 to 1,079 m a.s.l., on the northern slope of the Połonina Wetlińska, one of the mountain ranges in the Bieszczady Mountains rising to a maximum of 1,255 m a.s.l. (Fig. 1). The studied springs are hillslope springs, above which there are channel heads with well-developed niches (No. 3 and No. 7) or sections of dry V-shaped valleys – No. 5. Despite their location close to the ridge line and the small areas of topographic catchments (from 0.04 to 0.38 km2), the springs under investigation are characterized by relatively high discharge rates for springs draining a flysch bedrock and they flow almost continuously (Mocior et al. 2015; Mostowik et al. 2016; Płaczkowska et al. 2018). Average spring discharges ranged from 3.3 to 9.6 dm3·s-1 in the period 2013–2016, while averages in individual years showed significant differences (Fig. 2, Table 1), depending on Fig. 1 (A) The study area in the Carpathian Mountains; (B) the Polonina Wetlińska Massif with its geological and tectonic background (source: Malata et al. 2006; Haczewski et al. 2007), a – peaks, b – springs mapped in the zone above 900 m a.s.l. (after Mocior et al. 2015), c – numbered studied springs (numbering of springs according to Płaczkowska et al. 2018), d – strike and dip, e – streams, f – faults, g – line of cross section, h – sandstone-shale member, i – shale-sandstone member; (C) the weather stations’ location (black dots); (D) Geologic cross section through the Połonina Wetlińska, red rectangle shows the extent of conceptual models on Fig. 6. Fig. 2 (A) Daily mean air temperature, precipitation sum (Stuposiany weather station) and spring water temperature; (B) daily mean spring discharge during the study period. The cold half-year (not analyzed) is shaded. Table 1 Average annual (Nov–Oct) discharge of the studied springs in relation to precipitation totals Average annual discharge (dm3·s-1) Spring No. Monitored period Note: nd means lack of complete annual data. precipitation form, intensity and totals. Throughout the year, the highest discharges of groundwater usually occur in spring (Fig. 2), which is related to the snowmelt recharge of aquifers and, additionally, to rainfall. In turn, the minimum discharge falls in the autumn and winter months. Spring discharge is highly variable, while the temperature of spring waters fluctuates only slightly. The average annual temperature of spring waters in the examined period (Fig. 2, Table 2) was 5.4°C (spring No. 5), 5.7°C (No. 3) and 6.0°C (No. 7). Based on the previous studies water temperature was almost constant in spring No. 5 (±0.1°C) throughout the year, while in others there were seasonal fluctuations by approx. ± 1.0°C; there was no significant relation between water temperature and spring discharge (Kisiel et al. 2015; Table 2 Spring water temperature in the studied period Water temperature (°C) Spring No. Note: nd means lack of data. Płaczkowska et al. 2018). The lowest water temperature occurred in winter in spring No. 3 and in March and April in spring No. 7 (Fig. 2), whereas the highest water temperature was noted from July to October in both springs. The average air temperature in the period 2013–2016 (Stuposiany station) was 6.8°C and varied from -3.0°C in January to 16.9°C in July. The average air temperature in the upper part of the Połonina Wetlińska Massif is expected to be about 2°C lower than in Stuposiany. 2.3 Methods This study is based on data covering the daily discharge of three springs located on the northern slope of the Połonina Wetlińska Massif (Fig. 1), recorded in the years 2012–2016 (Fig. 2, Table 1). The measurements were performed using the Keller DCX– 22AA water level (error 0.05% FS) and temperature logger. The springs’ discharge rates for the entire observation period were calculated on the basis of the logged water level data and the rating curves. Data recording took place using an hourly time step and then were averaged to daily discharge. In addition, the specific electrical conductivity (SEC) of spring water was measured periodically using the Elmetron CPC­401 conductivity meter. The coefficient of quartile deviation (cv) was calculated based on SEC measurements as follows: cv = (SEC75% – SEC25%)/(SEC75% + SEC25%) (1) Meteorological data included daily precipitation totals from the period of 2012–2016 recorded at the nearest stations in Kalnica (6 km west, 576 m a.s.l.) and Stuposiany (11 km east, 547 m a.s.l.), which are part of the national meteorological monitoring network (Table 1). Despite the fact, that stations are located at lower altitude than studied springs, they may be considered as quite well representing local weather conditions. Using data from both stations enabled to avoid random results based only on one rain gauge. Precipitation gradient in the Połonina Wetlińska is uncertain but precipitation totals in the ridge zone may be estimated up to 20%–30% higher than that in stations included in the study (Laszczak et al. 2011). To determine the relationship between rainfall recharge and spring discharge, the cross-correlation analysis was used (Padilla and Pulido-Bosch 1995; Leszkiewicz and Rżkowski 2000; Lee et al. 2006; Fiorillo et al. 2007; Jemcov 2007; Zhang et al. 2013; Diodato et al. 2014). According to the previous study (Płaczkowska et al. 2018), the springs may be identified as perennial with quite high groundwater storage capacity, which might result in a lack of an immediate increase in spring discharge after a rainfall event. Therefore, in addition to cross-correlations between daily discharge and daily rainfall, cumulative rainfall time series of different duration (1 to 100 days) with a time lag from 0 to 50 days were introduced to provide more detailed analysis of rainfall recharge influence on spring discharge and to comprehend a broader problem of groundwater flow patterns. The cross-correlation coefficient (rxy) was determined using the formula below: rxy(k) = Cxy(k)/(.x· .y) (2) where Cxy(k) is the covariance between time series x (cumulative rainfall) and time series y (daily spring discharge), computed at time lag k, .x and .y are the standard deviations of the time series. The level of significance assumed in all analyses in this study was p . 0.05. Owing to the specific role played by snowmelt in groundwater recharge and the lack of sufficiently detailed data on snow cover duration, depth and water equivalent, data on winter spring discharge was excluded from the correlation analysis. This study only took into account daily discharge from the warm half-year period (May–Oct) and daily precipitation totals for the whole period. It has to be noticed that the data with longer lags (especially at the beginning of the warm half-year period) might have been influenced by March and April snowmelt and snowfall inputs which limits the inference about the relations between rainfall and spring discharge. Cross­ correlation analyses were performed for the entire period (May–Oct) separately for cumulative rainfall from Kalnica and Stuposiany stations. Additionally, using rainfall data from the nearest station in Kalnica, cross-correlation analyses were done for individual months (May, June, July, August, September, October) in order to more accurately characterize the response of springs to rainfall during the half-year. 3 Results 3.1 Warm half-year cross-correlations Correlograms were used to present the correlation coefficient between daily spring discharge and the cumulative rainfall, lasting for different periods as well as with different time lags. The cross-correlation analysis revealed that for both rainfall cumulative series (Kalnica and Stuposiany) similar correlation coefficients were obtained for each spring discharge, which confirmed substantial differences between springs’ responses (Fig. 3). Although the studied springs are situated within ca. 3 km, their responses to rainfall recharge were clearly different. The discharge of springs No. 3 and No. 5, displayed a weak correlation with the rainfall from several preceding days, whereas the discharge of spring No. 7 was highly correlated with shorter periods of cumulative rainfall. The discharge of Spring No. 3 during the warm half-year was most strongly correlated with the cumulative rainfall from a period of ca. 60 days immediately preceding this discharge (rKalnica=0.41, rStuposiany=0.36). However, r>0.3 was obtained for a wide interval of rainfall accumulation (20 to 100 days). The rate of decrease in the correlation coefficient with the increase in time lag for spring No. 3 was the smallest among the three analysed springs (Fig. 3). The highest values of the correlation coefficient (rKalnica=rStuposiany=0.59) occurred in spring No. 5, which has the highest discharge, and the cumulative rainfall from the 40 days immediately preceding the correlated discharge. A generally high correlation (r>0.50) was also found for the cumulative rainfall in a range of 20–60 days. Spring No. 7 clearly differed from the first two springs in terms of lower discharge and shorter periods of cumulative rainfall for which the correlation coefficients were high. The strongest correlation between rainfall and the discharge of spring No. 7 occurred for a rainfall cumulative period of about 10 days, and 1 day lag (rKalnica=rStuposiany=0.54). The rainfall totals from both shorter (<5 days) and longer (>20 days) periods were less strongly correlated with the discharge of spring No. 7. However, due to relatively similar correlation coefficients obtained for different cumulative rainfall periods, more detailed interpretation will be based on monthly cross-correlations. Fig. 3 Cross-correlation between cumulative rainfall (A – Kalnica, B – Stuposiany) and daily spring discharge for the warm half-year (May–Oct). 3.2Monthly cross-correlations More detailed information regarding the recharge pattern of springs was obtained from the cross-correlation analysis for individual months. Undoubtedly, the specific relationships between cumulative rainfall and spring discharge differed in the analysed months, with the highest correlation coefficients for short lags (Fig. 4). In May, the discharge of spring No. 3 was strongly correlated (r.0.6) with rainfall totals from 5 to 10 days with a slight lag. In the case of spring No. 5 the maximum correlation (r.0.6) occurred for the rainfall of varying duration (e.g. 10, 20, 100 days) preceding the discharge on a given day. The discharge of spring No. 7 had the highest correlation coefficients for Fig. 4 Cross-correlation between cumulative rainfall (Kalnica) and daily spring discharge analysed separately in months. cumulative rainfall from 3 (r=0.55) and 5 (r=0.58) days with a 1 day lag (Fig. 4). Furthermore, in May, the impact of rainfall from longer periods (20–40 days) with a lag of 1–2 months was clearly visible in springs No. 3 and 7. In June, individual characteristics in the recharge of each spring became apparent. In the case of spring No. 3, the strongest correlations (0.6340 days in September and October, the correlation coefficient maintained a similar value regardless of the length of the lag. This suggests that spring discharge in late summer and autumn is strongly dependent on rainfall conditions in the preceding few months. In spring No. 7, in October, the strongest correlation (0.59