Water resources in small flysch catchments in the Bieszczady Mountains Karolina Mostowik Jagiellonian University, Instute of Geography and Spaal Management, Gronostajowa St. 7, 30–387 Kraków, Poland [email protected] PL small catchments Lake Solina CZ UA cross section Introducon fault SK overthrust San main tectonic P O L A N D HU boundary The Carpathian Mountains are substantial source of water for surrounding lowland Silesian Unit B areas. Despite the fact that the mountains are characterized by high precipitation HR shale & sandstone San CS RO Otryt Sandstone Osława BA shale & sandstone supply, steep topography and low groundwater storage capacity of ysch bedrock Transition Beds Menilite Beds W determine fast surface runoff and poor groundwater resources in the Outer etlina Bieszczady National Park Dukla Unit Cisna Beds Carpathians. Hydrological studies in the Carpathians are frequently conducted in U K R A I N E Łupków Beds medium-sized catchments with little emphasis on variability among small (ca. 10 km2) sub-catchments. In fact, water resources in small, adjacent catchments may S L O V A K I A substantially differ, as was proved for zero-order catchments feeding springs in the 0 10 km upper part of the Połonina Wetlińska Massif (the Bieszczady Mountains, Eastern stream gauge (national monitoring) Carpathians, Płaczkowska et al. 2018, Mostowik et al. 2021). Therefore, this study Fig. 1. Map of the study area (red rectangle – the Połonina Wetlińska Massif with surroundings) focuses on further recognition of water resources in small catchments across the Połonina Wetlińska Massif (Fig. 1, Fig. 2). A Research Objecves 0 1 km ź photos: M. Kisiel S I L E S I A N U N I T to investigate hydrological conditions in small catchments with reference to SW NE m.n.p.m. Fore-Dukla Zone Połonina Wetlińska Suche Rzeki Magurka catchments’ characteristics Fig. 2. The Połonina Wetlińska Massif with its 1200 A syncline anticline syncline B ź to compare hydrological conditions in small catchments with medium-sized geological and tectonic background (based on the Detailed Geological Map of Poland 1:50000) 0 catchments of the San and Wetlina rivers (national monitoring network) 500 m Data & Methods The dataset used in this study covers hydrological years 2018–2019 and contains daily river ow from 7 own gauging sites in small catchments and from 2 gauging sites in medium-sized catchments supervised by the Institute of Meteorology and Water Management. The daily ow data was used to describe hydrological conditions in selected catchments, as well as to separate baseow with Eckhardt's digital lter based on parameters obtained as proposed by Collischonn and Fan (2013). Additionally, baseow in 19 small catchments across the Połonina Wetlińska Massif was measured during six campaigns in 2018 and 2019, when river ow was low and might have been identied as the effect of groundwater recharge only. Characteristics of 19 studied small catchments including their lithology, land use, slope, area, length, width, perimeter, mean, minimum and maximum elevation, elongation ratio and drainage density were dened in this study. In the next step the Spearman's rank correlation coefcient between baseow in the studied catchments and the catchment characteristics was calculated. Collishonn W., Fan F.M., 2013. Defining parameters for Eckhardt’s digital baseflow filter. Hydrol. Process. 27, 2614–2622 4. Surprisingly, almost none of the catchment 2 2 characteristics indicated evident correlation with 20 – Wetlina catchment (120 km ) 21 – San catchment (494 km ) Results Baseflow baseow during any studied period. Baseow 21 dm3s-1km-2 ≤ 3,0 1. Precipitation supply in the rst investigated hydrological year (2018) was was signicantly correlated only with maximum 3,1 – 6,0 worylczyk 6,1 – 9,0 approximately average and was characterized by wet winter season, whereas the catchment elevation (r =0.5 to r =0.7) and T 1 9,1 – 12,0 Aug18 Sep19 2 second year (2019) was clearly dry, especially in summer and autumn (Fig. 3). Fast with the ratio of the Transition Beds (r=-0.5 in Jul > 12,0 streamow response to rainfall events or snowmelt periods was typical for all analysed 2018, Aug 2019, and Sep 2019), where shale 3 Hulski catchments and daily ows among rivers were highly correlated. dominates over sandstone. However, this 4 Kindrat 19 5 Hylaty formation covers only 5% of the study area and 20 2. Streamow referred to a catchment area (specic runoff) has revealed high spatial P Berdo o ł 6 o cannot be considered as main factor affecting n variability, with the highest values noted for the catchment No. 7, located on the 18 i n 7 8 a 16 W Rzeka baseow in the whole region. Jałowy e t l 9 northern slope of the Połonina Wetlińska (Fig. 3, Fig. 4). Average specic runoff in 17 i ń 3 -1 -2 s k a Szumlaczy 5. Average baseow in the period 2018–2019 was small catchments varied from 24 to 54 dm ·s ·km in 2018, and from 17 to 33 Słowiański 14 3 -1 -2 3 -1 -2 15 13 12 dm ·s ·km in 2019, whereas in medium-sized catchments it was 34 and 25 the lowest in the San catchment (9.4 dm ·s ·km ), 10 3 -1 -2 3 -1 -2 3 -1 -2 11 Kostywski dm ·s ·km (Wetlina River), and 16 and 24 dm ·s ·km (San River), respectively (Fig. 4). whereas the highest equaled 36.1 dm ·s ·km in Klimakowski Pataraczakowski the catchment no. 7 (Fig. 6). The average 0 1 km baseow index ranged from 42% in the Fig. 5. Baseflow in small catchments across the Fig. 3. Specific runoff in selected catchments Fig. 4. Average specific runoff in the period 2018–2019 catchment no. 19 to 82% in the catchment no. 7 Połonina Wetlińska Massif during dry period, August 13-14, 2018 120.0 0 San River 2018 (Fig. 7). That conrms large differences in ] -2 100.0 50 San groundwater storage capacity across the km 24.3 -1 80 s 3 80.0 100 Połonina Wetlińska Massif reported in the median dm Wetlina River 70 25%–75% f [ f 5.0 analysis of baseow during selected dry periods. 60.0 150 10%–90% 2 ] 60 -2 km Table 1. Baseflow in selected catchments during six dry periods in -1 s 50 40.0 200 3 Precipitation [ mm] 30.3 2018 and 2019 (red – the lowest vaule, green – the highest value dm Specific runof 40 20.0 250 34.8 4 during a campaign) 30 3 -1 -2 Baseflow [dm ·s ·km ] Baseflow [ 0.0 300 21.6 5.4 No. River Nov Jan Mar May Jul Sep 57.6 Jul ‘18 Aug ‘18 Sep ‘18 Jul ‘19 Aug ‘19 Sep ‘19 20 120.0 0 6.6 19 4.1 21.3 1 Tworylczyk 14.8 7.2 4.0 6.0 3.0 1.7 10 2019 ] W 2 Lower Hulski 18.7 7.5 4.0 4.6 2.9 2.8 0 -2 100.0 50 etlina 5.0 7 2 4 7 9 12 16 19 San Wetlina km 16 27.9 -1 3 Lower Rzeka 22.5 6.6 6.4 8.9 4.9 3.2 s 27.2 23.0 3 80.0 100 9 4 Lower Hylaty 17.3 5.2 3.2 4.0 2.1 1.9 Fig. 6. Baseflow characteriscs in selected dm f [ f 35.1 catchments in the period 2018–2019 3.8 5 Upper Hulski 12.8 5.8 3.0 4.0 1.8 2.5 60.0 150 3.7 12 6 Berdo 23.3 13.3 4.3 11.8 5.1 3.5 40.0 200 7 Upper Rzeka 33.2 21.4 10.1 14.8 8.7 7.3 Precipitation [ mm] 9.0 100% Specific runof 8 Upper Hylaty 21.1 6.5 2.8 5.8 1.9 2.3 20.0 250 Specific runoff [dm3s-1km-2] 9 Szumlaczy 17.4 2.1 2.0 4.8 2.1 1.1 <25 median 80% 0.0 300 10 Tributary near quarry 14.8 2.9 2.2 3.8 0.5 0.5 25–30 25%–75% Nov Jan Mar May Jul Sep >30 10%–90% 11 Pataraczakowski 19.3 7.0 3.4 6.6 5.0 2.2 60% quickflow Precipitation 2 4 7 9 12 16 19 Wetlina San 12 Kostywski 34.3 9.4 6.7 13.8 5.7 3.7 13 Klimakowski 30.7 9.9 7.8 11.5 3.8 5.1 40% 3. Baseow during selected dry periods ranged from 0.2 to over 30 dm3·s-1·km-2 in the 14 Pański Zwór 12.8 4.2 4.8 4.6 1.8 1.7 15 Łomianykowski 8.8 2.8 3.4 1.4 0.3 0.2 20% studied catchments (Table 1), clearly showing unexpectedly large spatial differences 16 Słowiański 17.3 7.1 4.0 4.0 2.0 1.5 baseflow 0% in groundwater storage capacity. The highest baseow was identied in catchments 17 Tributary in Smerek 12.2 5.0 5.3 3.0 1.5 0.4 2 4 7 9 12 16 19 San Wetlina no. 7, 12, and 13, whereas the lowest was typical for catchments no. 10, 15, 17, and 18 Jałowy 13.6 4.0 4.4 2.0 0.6 0.2 18 (Fig. 5, Table 1). 19 Kindrat 15.1 7.3 4.2 5.0 1.9 1.7 Fig. 7. Baseflow and quickflow components of San 14.0 5.2 4.7 4.1 3.3 3.2 streamflow in the period 2018–2019 Wetlina 12.9 7.3 6.6 4.5 3.3 2.9 Conclusions In the ysch part of the Carpathians, similarities in small catchments’ lithology, climatic conditions, land use and morphometry do not imply similarities in groundwater resources, and, in consequences, in total catchment runoff.