Next Article in Journal
Risk Assessment of Oil Spills along the Coastline of Jiaozhou Bay Using GIS Techniques and the MEDSLIK-II Model
Previous Article in Journal
Multi-Objective Optimization Based on Simulation Integrated Pareto Analysis to Achieve Low-Carbon and Economical Operation of a Wastewater Treatment Plant
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 16
Issue 7
10.3390/w16070994
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Distribution and Characteristics of Springs in Two Neighboring Areas of Different Morphogenic Relief Type—Example of SW Medvednica Mountain (Central Croatia)

by
Ivan Martinić
and
Ivan Čanjevac
*
Department of Geography, Faculty of Science, University of Zagreb, Trg Marka Marulića 19/II, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Water 2024, 16(7), 994; https://doi.org/10.3390/w16070994
Submission received: 19 February 2024 / Revised: 19 March 2024 / Accepted: 26 March 2024 / Published: 29 March 2024
Browse Figures
Versions Notes

Abstract

:
Hydrogeological characteristics of certain areas are the most important factor in the distribution and hydrological characteristics of springs. Nevertheless, geomorphological, i.e., morphometrical characteristics can also play an important role in their distribution and/or can serve as spatial indicators of spring positions. This study compares the distribution of springs, their hydrological and morphometric characteristics in two neighboring areas of different morphogenic relief types in the Medvednica mountain (central Croatia), as well as their relationship with known faults. Results show that most of the springs in both areas researched have discharges between 0.01 L/s and 0.1 L/s. Nevertheless, in the fluviokarst area, there is a higher share of springs with discharges higher than 0.1 L/s. Morphometric characteristics of springs studied (altitude, slope, relative relief, curvature and Topographic Wetness Index (TWI)) have shown certain differences that are connected to the hydrogeological characteristics of the area. Results indicate that spring locations in the fluviodenudation relief area are more connected to the geomorphological processes caused by surface and shallow underground water runoff, while in the fluviokarst relief, that connection is less pronounced. Research has also shown that spring distribution in both areas is connected to faults, with somewhat higher concurrence in the fluviodenudation relief.

1. Introduction

Springs have always been of great importance to mankind, especially for the supply of drinking water. Apart from their importance to humans, springs are also of great ecological significance, as they are regarded as very important ecosystems [1,2]. Despite their importance, only recently has the research on springs intensified. The number of springs worldwide is estimated at up to 50 million [1]. However, springs are inadequately mapped almost everywhere. The first attempt to create a global spring database was made in 2023 by creating a book presenting the data of 75 countries [1]. Croatia was not among these countries, firstly because it does not have its own collective spring database. Spring research in Croatia usually focuses on the hydrology of the stronger karst springs [2]. Detailed mapping of springs is not so common, there are only a few such studies in Croatia [3,4,5]. The reasons for this are different. Previous research has shown that the occurrence of springs is the result of many spatial factors [2,6,7,8,9,10], which is why it is difficult to predict their exact locations. Despite technological progress and the use of remote sensing in spring research [11,12,13,14], it is still relatively difficult to determine the exact locations of springs without proper fieldwork, especially in the case of relatively small springs, considering their size and discharge. For this reason, studies of mountain springs often require extensive fieldwork, especially for their mapping [2,8]. By using field-collected data on springs, various analyses of the spatial distribution of springs and their correlation with other spatial phenomena and conditions can be carried out. The results of such analyses represent steps towards a better understanding of the occurrence of springs and towards an easier and more precise determination of their locations, either through fieldwork or remote sensing.
Since 2020, intensive field mapping and research of springs have been carried out in the Medvednica Nature Park in central Croatia. The primary goal of this project is to create a detailed spring database of the Medvednica mountain, as the existing spring data are very scarce. One of the most important spring characteristics included in the research is their hydrological and geomorphological properties. This paper deals with the analysis of the spatial distribution of springs in two neighboring areas in the southwestern part of Medvednica, for the first time showing their number and distribution. The two compared areas have different morphogenetic types of relief, and this study attempts to determine whether there are differences in the appearance and characteristics of their springs.
The objectives of the research are as follows:
  • To investigate differences in the spatial distribution of springs in the two studied areas;
  • To investigate hydrological differences (in a sense of discharge classes) of the springs between the researched areas;
  • To investigate the differences in the geomorphological (morphometric) characteristics of the springs;
  • To determine the relationship between the springs and the fault zones in the researched area.
The results of these objectives should provide new insights into the hydrology of springs, their location and their connections with other spatial factors and elements. All new findings are important for a better understanding of springs and their conservation, since their existence is endangered by climate change and various human impacts [15,16,17].

2. Materials and Methods

2.1. Study Area

The study area is located on the southwestern slopes of the Medvednica mountain, which rises north of the Croatian capital Zagreb (Figure 1). Medvednica mountain is an example of a so-called Pannonian scattered (island) mountain [18] with a very complex geological formation reflected in the high lithological heterogeneity. The study area includes the watersheds of two sinking streams—Jezeranec and Javorščak—as well as the watersheds of the Dubravica, Mačkovec, Družinec and Vrapčak streams. The general flow direction of these streams is from north to south. The Vrapčak stream, whose valley occupies the largest part of the research area (66%), is the richest in water. It is the only stream that has a hydrological station that is located immediately after the confluence of the Družinec stream. The average annual flow at this station is about 80 L/s in the last 5 years [19]. Other streams are significantly shorter and less abundant with water. It was estimated in the field that their mean flows are less than 15 L/s. The studied area is characterized by mountainous relief features. The lowest point is at an altitude of 180 m above sea level, and the highest is at 745 m. Two-thirds of the study area lies between 300 and 500 m above sea level. Slope inclinations from 12° to 32° (45% of the area) and relative relief between 100 and 300 m/km2 (96% of the area) prevail.
The entire study area consists of several stratigraphical and lithological units (Figure 2). Badenian deposits dominate in the southern and southwestern parts. They consist mainly of limestone deposits, more precisely Lithotamnium limestone and, to a lesser extent, sandstones and argillaceous marls [20,21,22]. These areas include the valleys of the Dubravica, Mačkovec and Družinec streams. The Badenian deposits lie directly on Triassic carbonates, mostly dolomites, which outcrop in the area of the Jezeranec and Javorščak streams. In their valleys and in the area of the Ponikve meadow, there are stream alluvial deposits from the Holocene age, deposited on the carbonate rocks. The valley of the Vrapčak stream consists mainly of Cretaceous deposits, which are overlain in the west on the Triassic carbonate deposits described above. This area is dominated by conglomerates of different compositions, flysch deposits and argillaceous marls [22]. In the southern part of the valley, in a smaller area, we can also find Devonian and Carboniferous parametamorphic deposits, mainly schists.
The climate of the area is a moderately warm, humid climate with hot summers, or Cfb according to the Köppen–Geiger classification [23,24]. The nearest meteorological stations are Puntijarka 7 km away to the northeast (991 m a.s.l.) and Zagreb Maksimir (123 m a.s.l.) 10 km away to the southeast. Based on the data from the two stations, it can be estimated that the average annual precipitation varies between 1000 and 1200 mm, depending on the altitude. Mean annual temperatures are between 7.5 °C and 11.9 °C, if we use the data from the mentioned stations [25].
The study area is divided into two parts according to the predominant morphogenetic relief type. The division was based on the available geological, hydrogeological and geomorphological data and on field observations. In the first area, the fluviokarst relief is dominant, with some clearly karstified zones. In the second, neighboring “non-karst” area, the fluviodenudation morphogenetic relief type, is dominant.
In the fluviokarst area, there are characteristical karst landforms such as dolines, ponors, blind valleys, karst springs, the Veternica cave and the Podcintarnica rock shelter (abri) [26]. In this area, however, the surface drainage network is relatively well-developed, which is reflected in the existence of permanent water flows listed above. For this reason, the area is geomorphologically characterized as fluviokarstic and not as karstic. The ponors of the Jezeranec and Javorščak streams are proven to be hydrologically connected to the Veternica cave system [26,27,28]. The water from ponors flows through a part of the cave system and then emerges at the Dubravica spring, the southernmost studied spring [27,28]. The watersheds of the Mačkovec and Družinec streams were also included in the fluviokarst part of the research area. In their valleys, the surface drainage network is somewhat more developed and there is a greater share of fluviodenudation processes, but there are also karst forms such as dolines, rock shelters and the occurrence of tufa. A smaller part of the Vrapčak stream watershed has been added to the fluviokarst area, namely in the southernmost part, where the karst type of relief is determined by dolines and Triassic carbonate deposits. The remaining part of the Vrapčak valley and watershed is the fluviodenudation part of the study area.
Fluviodenudation relief is created by the surface water flow in the part with the upper flow mechanism, mostly by the process of deep erosion. Along with the erosive work of the streams themselves, denudational slope processes on the valley sides also shape this type of relief [29]. A surface drainage network has been developed in it, which includes numerous ravines, gullies and stream valleys. The total size of the study area is 9.45 km2, of which the fluviokarst part covers 5.02 km2, and the fluviodenudation part 4.43 km2. The southern borders of the study area(s) were determined using the Medvednica Nature Park borders. That way, the urban areas and anthropogenic relief were left out of the analysis.
Water 16 00994 g001
Figure 1. Study area and its drainage network, smaller maps background by [30].
Figure 1. Study area and its drainage network, smaller maps background by [30].
Water 16 00994 g001
Water 16 00994 g002
Figure 2. Geological map of the study area (Holocene—stream alluvium; Miocene—Badenian lithothamnium limestone, sandstones and argillaceous marls; Cretaceous—conglomerates, flysch deposits and argillaceous marls; Upper Triassic—dolomitic limestones; Middle Triassic—dolomites; Devon, Carboniferous—schists), made after data from available geological maps [20,21].
Figure 2. Geological map of the study area (Holocene—stream alluvium; Miocene—Badenian lithothamnium limestone, sandstones and argillaceous marls; Cretaceous—conglomerates, flysch deposits and argillaceous marls; Upper Triassic—dolomitic limestones; Middle Triassic—dolomites; Devon, Carboniferous—schists), made after data from available geological maps [20,21].
Water 16 00994 g002

2.2. Data Collection

The data on the locations of the springs and their hydrological characteristics (average discharge) were collected through detailed field research. Based on the available maps and the digital relief model, the locations of known springs and potential locations of unmapped springs were determined. The coordinates of the locations were transferred to a mobile mapping application, which was used to verify them in the field. The field research was conducted throughout the year from 2021 to 2023, consequently in different hydrological conditions. Most springs were visited only once or twice. The coordinates of the springs were recorded in the field and their current discharge was measured using the volumetric method. A suitable container (bucket) and a stopwatch were used for the volumetric measurement. The spring water was diverted through a pipe to fill up the container of known volume. The time needed to fill was measured with the stopwatch. Discharge was calculated by dividing the measured volume by the measured time. The process was repeated three times and the average value was calculated from these measurements.
All data collected in the field were deposited into the GIS database. All analyses were then performed at the level of the entire study area, but also specifically for the fluviokarst part and the fluviodenudation part of the study area. The goal was to determine the spatial distribution and differences in the studied spring characteristics.

2.3. Data Analysis

Most of the analyses were carried out using the GIS software ArcMap 10.7. A spatial representation of the investigated springs was made and their average density was determined according to the defined areas. Average density is calculated simply by dividing the number of springs by the research area. The kernel density of the springs was also calculated and the randomness of their spatial distribution was analyzed using the nearest neighbor tool. In contrast to the average density, the kernel density method calculates the density of springs for each defined raster cell within the study area. In this way, different densities are applied to different parts of the study area. Each cell is associated with its search area defined by the search radius around each cell. The density value is highest at the location of the point (in this case spring) and diminishes with increasing distance from the point, reaching zero at the edges of the search area [31,32]. In this case, the search radius was 1 km2 and the raster cells were the size of 15 m × 15 m.
The nearest neighbor index is expressed as the ratio between the observed mean distance between the neighboring springs and the expected mean distance between the neighboring springs. The expected distance is the average distance between neighbors (in this case springs) in a hypothetical random distribution [33].
Based on the volumetric measurements and the assessment of hydrological conditions, the springs were classified into the discharge classes defined by Meinzer [34], and the distribution of the categories of the two research areas was analyzed. The hydrological conditions during the fieldwork days were assessed on the basis of the field observations (water levels of streams) and available hydrological and meteorological data from the nearest stations.
Using a digital relief model with the resolution of 5 m × 5 m (based on the data from the Croatian State Geodetic Administration), the morphometric characteristics of the relief, i.e., the areas in which the springs are located, were analyzed. The altitude of the springs, the inclination of the slopes on which they are located and the relative relief of spring areas were analysed. In addition, the curvature of the slopes on which the springs are located was also analyzed. Finally, the values of the Topographic Wetness Index (TWI) of the area studied and the locations of the springs were determined. TWI is used to quantify topographic controls on hydrological processes [35]. The topographic wetness index is defined as
TWI = ln a tan b
where a is the local upslope area draining through a certain point per unit contour length and tan b is the local slope in radians [36]. Low values of TWI indicate that the area is relatively dry, while higher values indicate wet areas.
In addition to the morphometric characteristics, the distances of the springs from known faults were also analyzed. Furthermore, the kernel density of the springs was compared with the kernel density of the faults using raster analysis. This method was used in an attempt to determine the dependence of the occurrence of springs on fault zones.

3. Results

3.1. Spatial Distribution of Springs

A total of 138 springs were mapped in the researched area. Among them, 66 springs are located in the fluviokarst area and 72 in the fluviodenudation research area. The analysis of the spatial distribution of springs using the average nearest neighbor method shows that there is a significant clustering of springs (Figure 3). The value of the nearest neighbor ratio for the fluviokarst area is 0.44, and for the fluviodenudation area 0.63. As the values are less than 1 in both cases, they indicate a grouping of the springs. The significance level (expressed as p-values) is less than 0.01 for both fluviokarst and fluviodenudation areas. The critical value (expressed as z-values) is less than −2.58 for both areas, specifically −5.9 for the fluviodenudation area and −8.7 for the fluviokarst area (Table 1). In both cases, the statistical values indicate that the probability that the spatial distribution of the springs is random is less than 1%.
The number of springs was divided by the area of the researched areas, and the results show that the average spring density in the fluviokarst relief area is 13.14 springs/km2 and 16.27 springs/km2 in the fluviodenudation relief part of the study area. The spring density was also calculated using the kernel method for the entire research area. In both areas, there are areas with a kernel density of 0 springs/km2. Although both the average density (16.27 springs/km2) and the average kernel density (14 springs/km2) are slightly higher in the fluviodenudation relief area than in the fluviokarst relief area (13.14 springs/km2, kernel: 12.72 springs/km2), the highest kernel density was measured in the fluviokarst area: 88.8 springs/km2 (Figure 4). This value was measured in the northern part of the fluviokarst area. The differences in spring density are smaller in the fluviodenudation relief area than in the fluviokarst area. The highest spring density in the fluviodenudation area is located in the south, near the border with the fluviokarst area, and amounts to 42.9 springs per km2, which is significantly less than in the fluviokarst area.

3.2. Discharge Categories of Springs

On the basis of field measurements of spring discharge using the volumetric method and on the basis of hydrological conditions during the measurement, the category of average spring discharge was estimated. The researched springs fit into four categories according to Meinzer’s discharge classes [34]. Springs with the lowest average discharge (<0.01 L/s) belong to category VIII; a total of 38 springs (27.5%) were sorted in this category. Most of the springs researched, namely 72 (52.2%), belong to category VII with an estimated mean discharge between 0.01 L/s and 0.1 L/s. In total, 25 springs (18.1%) belong to category VI with an estimated average discharge between 0.1 L/s and 1 L/s. Springs with the highest average discharge (1–10 L/s) belong to category V, and there are only three such springs, i.e., just over 2%. The spatial distribution of springs of different discharge categories is not uniform (Figure 5 and Figure 6). The fluviokarst relief, on average, has a higher discharge. In fluviokarst relief, category VII (0.01 L/s–0.1 L/s) has the largest number of springs (38), i.e., the largest share of springs (57.6%). The second most common category in the fluviokarst is category VI (0.1–1 L/s), with 27.3% of the springs. The category VIII, of smallest discharge (<0.01 L/s), includes seven springs (10.6%). All three springs in category V (1–10 L/s) are located in the fluviokarstic relief area. Accordingly, there are no category V springs in the fluviodenudation relief (Figure 5 and Figure 6). Category VI springs account for 9.7% of the springs in the fluviodenudation area, while category VII springs also dominate here with a share of 47.2%. Spring discharge category VIII has a significantly higher share in the fluviodenudation area with 43.1% of springs than in the fluviokarst area.

3.3. Morphometric Analysis

Morphometric analyses of the study area connected spring locations with altitudes (Figure 7; Appendix A). Only 1.1% of the fluviokarst relief area is below 200 m above sea level, while the fluviodenudation relief area is completely above that altitude. The areas between 200 m and 300 m above sea level account for about 12% of both fluviokarst and fluviodendation areas. A total of 28.4% of the fluviokarst area is located at altitudes between 300 and 400 m a.s.l. The largest part of the fluviodenudation area, namely 37.5%, is located at these altitudes. The largest part of the fluviokarst area (38.8%) is located at altitudes between 400 and 500 m a.s.l., while in the fluviodenudation area, they cover 33.7% of the terrain. Areas with altitudes between 500 and 600 m a.s.l. account for 19.8% of the fluviokarst area and 13.1% of the fluviodenudation area. In the fluviokarst area, only 1.7% of the terrain is above 600 m a.s.l., while in the fluviodenudation relief area, 3.7% of the terrain is above this altitude (Appendix A). The lowest spring is located at 198 m and the highest is at 657 m above sea level. Most springs are located at altitudes between 400 and 500 m above sea level (60 springs, i.e., 43.5%) and at altitudes between 300 and 400 m (51 springs, i.e., 37%). The fewest springs are located below 200 m (1 spring) and above 600 m (2 springs), but these areas together account for only slightly more than 2% of the study area and are not statistically significant. A comparison of the fluviokarst and fluviodenudation areas shows that most springs (36 or 54.6%) in the fluviokarst area are located at altitudes between 400 and 500 m above sea level. In the fluviodenudation area, most of the springs are found at altitudes between 300 and 400 m (35 springs or 48.6%). The number of springs was set in relation to the area of the altitude classes, thus calculating the density of springs per individual altitude class. In the fluviokarst part of the study area, the class with the most springs (400 to 500 m) has an above-average spring density (18.48 springs per km2), while in the fluviodenudation part, the class with the highest number of springs (300–400 m) also has an above-average density (21.12 springs per km2; Figure 7; Appendix A).
The studied area was also divided in terms of slope classes, following the IGU standard [37]. Relatively flat terrain with slopes less than 2° accounts for 6.9% of the fluviokarst relief area and 1.4% of the fluviodenudation relief area. Slightly steeper terrains, with slopes between 2° and 5° account for 20.9% of the fluviokarst area and 4.6% of the fluviodenudation area. Slopes between 5° and 12° account for 30.2% of the fluviokarst area, while they account for 20.6% of the fluviodenudation area. The majority of the terrain in both fluviokarst and fluviodenudation areas have slopes between 12° and 32°. They account for 32.5% of the fluviokarst area and 57.9% of the fluviodenudation area. Slopes steeper than 32° occupy the rest of the areas, namely 9.5% of the fluviokarst area and 15.47% of the fluviodenudation area. This shows that the fluviokarst relief area has a higher proportion of relatively flat terrain and that the fluviodenudation relief area is relatively steeper (Appendix A). The highest number and the highest density of springs are found on slopes of 12–32° (Figure 7; Appendix A). In the fluviokarst relief area, the density of springs in this class is the highest (30 springs/km2), while it also dominates in the fluviodenudation relief area, but to a somewhat lesser extent (21.8 springs/km2). Only three springs were found on leveled surfaces with slopes of less than 5°, all in the fluviokarst area (Figure 7; Appendix A). A relatively high spring density was found on steep slopes between 32° and 55° in the fluviodenudation area (14.6 springs/km2).
The relative relief of the studied area is quite uniform, and areas with relative relief values between 100 and 200 m/km2 and between 200 and 300 m/km2 dominate (Appendix A). In the fluviokarst area, there is a slightly higher proportion and density of springs in the areas with a relative relief class of 100–200 m/km2, while in the fluviodenudation relief part, as many as 95% of springs (69 of them) are located in the class of 200–300 m/km2 (Figure 7; Appendix A). It should be noted that this class of relative relief covers more than 86% of the fluviodenudation area (Appendix A).
As far as the curvature of the slopes is concerned, most of the springs appear on convergent slopes in the case of planform curvature, as well as on concave slopes in the case of profile curvature. However, it should be noted that some springs were also located on convex, divergent and flattened surfaces. In the case of planform curvature, the fluviodenudation area has a higher proportion of springs and their density on convergent slopes than in the case of the fluviokarst area. More specifically, 81% of springs and a density of 32.4 springs/km2 in the fluviodenudation area, compared to 69.7% of springs and a density of 21.6 springs/km2 in the fluviokarst area (Figure 8). In the case of the profile curvature, the density of springs on concave slopes is about the same in the fluviokarst and fluviodenudation area (27.2 springs/km2 and 27.9 springs/km2; Figure 8).
The Topographic Wetness Index (TWI) in the area of the investigated springs shows that the threshold value for the occurrence of springs is equal to 3. In areas with a TWI value between 3 and 6, 50% of the investigated springs were located (Figure 9). This proportion is slightly lower in the fluviokarst relief (45.5%) and slightly higher in the fluviodenudation relief (54.2%), but the majority of springs in both areas are located there. A total of 43.5% of the studied springs are in the TWI class with values from 6 to 9, and almost the same share of springs occurred when we analyzed the fluviokarst and fluviodenudation parts of the studied area separately (Figure 9). In areas with a TWI value between 9 and 12, there are a total of nine springs, eight of which are located in the fluviokarst relief. In areas with a TWI value greater than 12, there are none of the investigated springs. Areas with TWI values between 6 and 9 are characterized by a high density of springs, especially in the fluviodenudation relief area (77 springs/km2). In the fluviokarst relief, the areas with TWI index values of 6–9 and 9–12 have an equally high spring density (around 43 springs/km2).

3.4. Spring Relationship with Faults

The locations of springs were also compared with the distance to the faults drawn on the Basic geological map [20]. Faults within the study area and faults within the buffer zone of 100 m around the study area were considered. The reason for including them in the analysis is that their location is relatively roughly drawn in relation to the size of the study area on a scale of 1:100,000, and their influence cannot be ignored. The results have shown that the number of springs tends to decrease with distance from the fault in both fluviokarst and fluviodenudation areas (Figure 10). Nevertheless, there are some springs that are located at a distance of more than 400 m from the drawn faults. Most springs, namely 49.3%, are located in the zone up to 100 m from the mapped faults, and 25.4% of them are located at a distance between 100 and 200 m from the mapped faults. In the fluviokarst, 57.6% of the faults are located at a distance of up to 100 m from the fault, while this proportion is slightly lower in the fluviodenudation area (41.7%). Analyzing the linear trends, the number of springs in the fluviokarst decreases more rapidly with distance from the fault than in the case of the fluviodenudation relief (Figure 10).
The fluviokarst relief area is dominated by faults that are oriented (north–)northeast–(south–)southwest (NNE–SSW and NE–SW), while the dominant faults in the fluviodenudation relief area are oriented north-northwest–south-southeast (NNW-SSE). Faults with north–south (N–S) and east–west (E–W) orientations are only represented to a very small extent (Figure 11). In order to compare the potential linear groupings (bands) of springs with the direction of faults, the study area was divided into 100 × 100 m grids [8]. The springs were counted within each grid. In the fluviodenudation area, no linear grouping of springs was established and grids with only one spring within them dominate. In the fluviokarst area, a linear connection of grids with more than two springs can be observed. The main extension is southeast–northwest, and the linear connection follows the extension of the Družinec stream valley, but can also continue in the direction of the Jezeranec stream valley. Parallel to this group of springs, there is also a series of dolines located about 500 m to the northeast (Figure 12). Such extension is actually perpendicular to the predominant extension of faults in the fluviokarst area, and at the same time, it coincides with the predominant extension of faults in the fluviodenudation area.
Kernel spring density and kernel fault density of the study area were compared to determine the degree of correspondence between fault density and spring density. The raster layers of the kernel densities of faults and springs were divided into eight classes using the Jenks natural breaks for class definition [38]. The cells with the highest density were assigned the value 8 and the cells with the lowest density were assigned the value 1. Then, using the Raster Calculator tool, the values of the fault density classes were subtracted from the values of the spring density classes. The value 0 was obtained in areas in which the spring and fault densities completely overlap. The more the value deviates from 0, the more the spring and fault densities do not match. Negative values represent a higher fault density than the spring density and positive values represent a higher spring density than the fault density. Theoretically, the resulting cell values can lie between −7 and +7. The values obtained through this analysis vary from −7 to +2 in the fluviodenudation relief area and between −6 and +4 in the fluviokarst relief area (Figure 13; Table 2). The proportion of cells with a very good density concurrence (from −1 to 1) accounts for 45.1% of the fluviodenudation area and 23.1% of the fluviokarst area. A partially good concurrence of fault and spring densities (cell values −2 to −3 and 2 to 3) covers 31.4% of the fluviodenudation area and 37.7% of the fluviokarst area. Poor concurrence of densities (values −4 to −5 and 4 to 5) accounts for 19.2% of the fluviodenudation relief area, while this proportion is 37.3% in the fluviokarst relief area. There is a complete discrepancy between the densities of faults and springs (values −6 and −7) in 4.4% of the fluviodenudation area and 1.8% of the fluviokarst (Figure 13; Table 2).

4. Discussion

The spatial analysis has shown that there is a very significant clustering of springs, regardless of the morphogenetic relief type of the area studied. A slightly more pronounced clustering is present in the fluviokarst relief area, which is supported by the high values of spring kernel density found in that area (Figure 4).
The values of average spring density (total number of springs divided by total area) did not show significant differences: 13.14 springs/km2 in the fluviokarst and 16.27 springs/km2 in the fluviodenudation relief. In other studies, spring densities vary from 5 to 48 springs/km2 [39,40]. Density values depend on the definition (borders) of the study areas. Since there are differences in the methodology used, as well as in the areas of research, results from the mentioned studies are not directly comparable to the results of this paper.
The analysis of the spatial distribution of springs by discharge shows that there are more water-abundant springs in the fluviokarst relief than in the fluviodenudation relief. In both areas, springs with an average discharge between 0.01 and 0.1 L/s are the most common. Such results are very similar to those found in other research on mountain areas in Poland [10,39,40,41] and Croatia [3], as well as in Nepal [42] and the USA [43]. In all of the mentioned studies, springs with discharge lower than 1 L/s are dominant. However, some differences in discharge values between fluviokarst and fluviodenudation relief are visible in the results. In the fluviokarst, there is a much larger number of springs with an average discharge greater than 0.1 L/s and there are also springs with an average discharge greater than 1 L/s, which are absent in the fluviodenudation relief area. The reasons for this can be different. As the two areas compared are adjacent to each other, and at relatively the same altitudes, the cause of the differences cannot be due to different climatological characteristics. The general assumption is that most fluviokarst springs are connected to richer, larger and deeper aquifers This is not the case with springs in the fluviodenudation relief area of the Vrapčak stream valley. Most of the Vrapčak stream springs are most likely seepage springs with very shallow aquifers or even aquitards, where water flows just under the surface [44].
The above suggests that the fluviokarst area has more water-abundant springs that are somewhat more densely grouped than the fluviodenudation area. This is probably the result of more concentrated groundwater flows, i.e., groundwater reaching the surface in contact with rocks of lower permeability, which is characteristic of karst areas [45,46]. Fluviokarstic areas usually have tertiary (canal) porosity that supports concentrated underground flow. A good indicator of such hydrogeological properties in this area is the fluviokarstic system of the Veternica cave [26,44]. In fluviodenudation relief areas, secondary porosity with smaller and narrow underground channels as well as smaller aquifers (underground reservoirs) is more common [44]. Described differences are supported by field discoveries, more precisely by springs that are of cave/fissure type, where the water comes to the surface flowing predominantly through a channel or tube in the fluviokarst area. In the fluviodenudation area, such springs are not present. They are mostly helocrene types. In these types of springs, water emerges on the surface in small amounts from several small fissures that are usually covered by muddy surfaces [47,48,49].
The morphometric analyses of springs also show certain differences between the fluviokarst and fluviodenudation relief. The highest density and number of springs in the fluviodenudation relief area occur at altitudes of 300 to 400 m above sea level, i.e., at altitudes lower than the average altitude of the area, which is 407 m. In contrast, in the fluviokarst relief area, the highest density and number of springs occur at altitudes of 400 to 500 m above sea level, i.e., relatively high above the average altitude of the studied area (417 m). The differences in spring altitudes are likely the result of many factors. One of the factors could be the dip of the rock layers [8]. Unfortunately, there are no geological data available for this area with the accuracy required for such analysis. The curvature analysis tells us that most of the springs in the fluviodenudation area are mainly connected to channel heads, ravines and gullies [41,50], while in the fluviokarst, this connection is not so pronounced. The springs in the fluviodenudation relief area are mostly of the gravity and seepage type, and a certain saturation of the soil with water is required to form the spring. Taking into account the gravitational nature of seepage springs, they will occur at relatively low altitudes considering the surrounding area, depending also on pedological and lithological conditions. In the fluviokarst area, the largest number and density of springs are in the wider area of the Ponikve meadow, where springs occur along faults and contact zones of Triassic carbonate with less permeable Holocene stream alluvium.
There is a correspondence between the two areas in terms of slope gradients of springs. The highest number and density of springs in both areas are in the 12° to 32° slope range. Such results are similar to those in the other studies [8,42]. The rest of the results indicate that the springs in the fluviodenudation relief area occur on steeper slopes than those in the fluviokarst. In fluviokarst, a few springs also occur on flat surfaces. The steeper slopes in the fluviodenudation relief area indicate the previously described seepage type of springs, whose main driving force is gravity. In the fluviokarst area, springs on somewhat gentler slopes and even on flat areas indicate potential upward groundwater movement and overflow springs. These data indicate that the occurrence of springs on the fluviodenudation relief is more strongly related to the geomorphological conditions of the surface than in the case of the fluviokarst area. More precisely, springs of the fluviodenudation area are more related to the areas of high relief energy than is the case in the fluviokarst area. These hypotheses are also supported by the differences in the categories of relative relief and curvature. The results have shown that the majority of springs (97%) in the fluviodenudation area are located in areas with relative relief higher than 200 m/km2, while in the fluviokarst area, most springs (57%) are located in areas with relative relief values lower than 200 m/km2. As expected, the analysis of the curvature of the slopes shows that most springs in both areas are in the area of convergent or concave slopes. There are no significant differences between the areas in the occurrence of springs in the profile curvature, but the planform curvature shows a greater number and density of springs on convergent slopes in the fluviodenudation relief area compared to the fluviokarst. Convergent slopes are associated with gullies and stream valleys, which are the predominant ways of surface water runoff, and thus, also areas with pronounced geomorphological processes related to surface water runoff and shallow underground runoff. The incision of gullies also leads to the possibility of cutting lithological formations and the emergence of underground water to the surface [50].
(Hydro)geological conditions play a key role in the formation of springs, but geomorphological processes and forms can also be a factor or indicator of their location [8,50,51,52,53]. Results of this study suggest that in the fluviodenudation relief, the occurrence of springs is more related to the processes of shallow runoff in the soil and surface runoff (spring sapping, erosion), as they occur in areas where the effect of the mentioned processes is pronounced in the relief. In fluviokarst, springs are less related to the processes of surface runoff and shallow subsurface runoff, which is due to the (fluvio)karstic conditions in which subterranean runoff dominates.
The TWI analysis also supports this conclusion. A threshold value of 3 was determined, below which there were no springs. In other studies, TWI values of 2 are mentioned as threshold values [51]. The upper limit of the index was found to be 12, above which values refer to stream valleys in this case. For the fluviodenudation relief, according to the results, springs are to be expected in cells with values between 3 and 9. Those cells represent the transition from areas without surface runoff to areas of permanent surface runoff. In fluviokarst, the applicability of the TWI index is questionable, as it analyzes the topographic wetness of the area, which is quite unpredictable in karst areas. The method itself encounters problems due to karst forms such as ponors or dolines. Nevertheless, the limit values mentioned in this analysis also apply to the fluviokarst area of this study.
It is known that springs are very often associated with fault or contact zones [10,11,54,55]. Our results support this general rule showing that a large number of springs in the two areas studied are associated with mapped faults. This is particularly evident from the fact that the number of springs decreases with increasing distance from the fault. The analysis of the kernel density of faults and springs shows that in 76.5% of the fluviodenudation relief area, there is a good or very good match between the density of the faults and the density of the springs. In the fluviokarst area, the share of good and very good matching is somewhat lower—60.9%. In both areas, there are zones in which the fault density is higher than the spring density. This can be explained by the fact that the springs are not only defined by the occurrence of faults. However, it is important to point out that there are no areas or cells with values above 3 in the fluviodenudation relief and above 4 in the fluviokarst relief. This means that there are no areas with a high density of springs and a low density of faults.
The analysis of the linear grouping of the springs in relation to the directions of the faults shows that there is a single linear grouping of springs (that could have been distinguished), present in the fluviokarst area. Interestingly, it is perpendicular to the predominant direction of fault extension in this area and parallel to the extension of a series of dolines in the same area. The result somewhat differs from a similar analysis in the work of Mocior et al. [8] in which the direction of linear spring groups mostly coincided with the direction of faults. But, if we consider both areas as a whole, then the mentioned spring group does follow the dominant fault directions. One possible reason for this is the existence of an unmapped fault(s) in this area, but this does not necessarily have to be the case. These springs occur mainly in the valley of the Družinec stream, which is deeply cut into the relief. The deep incision has probably led to the cutting of relief below the groundwater level, which is why numerous springs occur at the edges of the valley. The question is whether the valley is predisposed by a fault. That could be the case since there are relatively lower discharges in the upper course, the force of which alone may not be sufficient to create such a deeply incised valley. Further research on this matter is necessary to answer these questions. It is also important to mention that the mentioned linear group of springs is perpendicular to the mountain ridge direction, which is also the case in the research of Mocior et al. [8].

5. Conclusions

This study analyzed differences in the spatial, hydrological and geomorphological characteristics of the 138 mapped springs in the SW of the Medvednica Nature Park (central Croatia). The main focus was on the difference between fluviokarst and fluviodenudation relief type areas. There is a very strong clustering of springs in both areas studied. The analysis of the spatial density of springs shows that there are larger groups of springs in the fluviokarst area, i.e., areas with significantly higher density than in the fluviodenudation area. This is probably the result of concentrated underground flows that occur in the permeable carbonate rocks and then reach the surface at certain points (usually in contact with less permeable rocks) through several cracks or through a single conduit in the form of a spring with greater discharge.
Category VII (0.01–0.1 L/s) springs according to Meinzer [34] dominate in both areas studied, although the fluviokarst area has more water-abundant springs than the fluviodenudation area. The reasons for these results are mainly to be found in the different hydrogeological characteristics of the areas, more precisely more of the fluviokarst springs being the result of concentrated underground flows.
Although there are certain similarities in the morphometric characteristics of the springs, the differences are also present. The springs in the fluviodenudation area are more strongly associated with fluviodenudation processes and landforms, such as channel heads, gullies and ravines, than is the case in the fluviokarst area. The morphometric analysis results also indicate that springs in the fluviodenudation area occur in the areas of higher relief energy (therefore, of more active denudation processes) than in the case of springs in the fluviokarst relief area.
The analysis of the Topographic Wetness Index (TWI) indicates that it could be applied to areas with fluviodenudation relief to predict potential spring locations more easily and accurately. Further investigation and application of the TWI index are required to confirm this. In (fluvio)karst areas, the applicability of the TWI index is questionable due to the prevalence of underground flow.
The analysis of the connection between spring densities and fault zones shows a certain concurrence. Together with the analysis of the distance of the springs from the faults, results support a connection between these two phenomena. The analysis of the linear groupings of the springs shows a perpendicularity of the distribution of the spring groups to the dominant direction of the fault distribution in the fluviokarst area. However, the results of this study should be interpreted with caution, due to relatively rough fault data. Moreover, only one linear grouping of springs was observed, which makes it difficult to speak of such a phenomenon as a rule.
The results of this study indicate that there are certain differences in the characteristics of the spring in relation to the different morphogenetic relief types of the observed area. Even though they do not play a key role in spring occurrence, geomorphological forms and conditions can be used for the prediction of spring locations, according to the morphogenetic relief type. This is because it is impossible to separate the processes of spring formation from geomorphological processes, especially in the fluviodenudation relief type area. Accordingly, the results of this and future similar studies could be applied for better determination of potential spring locations using remote sensing and available digital data as well as in various hydrological modeling (e.g., flooding risks), as well as for water resources estimations and use. Further research is very much needed, especially hydrological monitoring of springs in order to track the consequences of climate change [16,17].

Author Contributions

Conceptualization, I.M. and I.Č.; methodology, I.M. and I.Č.; software, I.M.; validation, I.M. and I.Č.; formal analysis, I.M.; investigation, I.M. and I.Č.; resources, I.M. and I.Č.; data curation, I.M.; writing—original draft preparation, I.M.; writing—review and editing, I.M. and I.Č.; visualization, I.M.; supervision, I.Č.; project administration, I.M. and I.Č.; funding acquisition, I.Č. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are available on demand. To acquire the data, please contact the authors.

Acknowledgments

We would like to thank Nenad Buzjak from the Department of Geography, Faculty of Science, University of Zagreb and Dominik Tomić for help in the fieldwork.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Spring numbers, shares and densities by morphometric parameters.
Table A1. Spring numbers, shares and densities by morphometric parameters.
Morphometric ParameterFluviokarst Relief AreaFluviodenudation Relief Area
Elevation (m a.s.l.)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)
100–20011.520.061.1117.8900.000.0000.000.00
200–300710.610.6011.9411.6856.940.53312.049.39
300–4001624.241.4228.3911.233548.611.65737.4521.12
400–5003654.551.9538.8118.482433.331.49133.7016.09
500–60069.090.9919.766.0568.330.57913.0810.37
>60000.000.001.680.0022.780.1653.7312.12
Total661005.0210013.15721004.4210016.27
Fluviokarst Relief AreaFluviodenudation Relief Area
Slope (°)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)
0–223.030.356.895.7800.000.061.400.0
2–511.521.0520.940.9500.000.204.600.0
5–121116.671.5230.237.2568.330.9120.566.6
12–324974.241.6332.4730.065677.782.5657.9721.8
32–5534.550.489.476.311013.890.6815.4714.6
Total661005.0210013.15721004.4210016.27
Fluviokarst Relief AreaFluviodenudation Relief Area
Relative Relief (m/km)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)
<10000.000.081.580.0000.000.000.000.00
100–2003857.582.4448.7015.5422.780.429.524.75
200–3002842.422.3647.0511.856995.833.8286.3918.05
>30000.000.132.670.0011.390.184.105.51
Total661005.0210013.15721004.4210016.27
Fluviokarst Relief AreaFluviodenudation Relief Area
Planform
Curvature		Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)
convergent (−)4669.702.1342.3921.615981.941.8241.1532.40
divergent (+)1624.242.2144.007.241013.892.0947.134.80
Flat
(−0.05–0.05)		46.060.6813.605.8634.170.5211.725.79
Total661005.0210013.15721004.4210016.27
Fluviokarst Relief AreaFluviodenudation Relief Area
Profile
Curvature		Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)
convex (−)1116.672.4148.034.561622.221.9243.508.31
concave (+)5278.791.9138.1127.185373.611.9042.8927.93
flat (−0.05–0.05)34.550.7013.864.3134.170.6013.614.98
Total661005.0210013.15721004.4210016.27
Fluviokarst Relief AreaFluviodenudation Relief Area
TWINumber of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)Number of SpringsShare (%)Area (km2)Share of Area (%)Density (spring/km2)
0–300.000.275.320.0000.000.429.460.00
3–63045.453.7574.658.003954.173.4878.5311.22
6–92842.420.6412.7343.803244.440.429.3977.00
9–12812.120.193.7642.4011.390.071.5614.48
>1200.000.183.540.0000.000.051.050.00
Total661005.0210013.15721004.4210016.27

References

  1. Stevens, L.E. Chapter 1: Springs of the World. In Springs of the World: Distribution, Ecology, and Conservation Status; Monograph 1; Stevens, L.E., Ed.; Spring Stewardship Institute: Flagstaff, AZ, USA, 2023; 198p. [Google Scholar]
  2. Martinić, I. An overview of classifications and modern research of springs in the world and in Croatia. Croat. Geogr. Bull. 2022, 84, 31–68. [Google Scholar] [CrossRef]
  3. Vujnović, T. Springs in the Žumberak–Samoborsko Gorje Nature Park. Nat. Croat. 2011, 20, 19–34. [Google Scholar]
  4. Miletić, S. GIS of Spring Water in the Area of Papuk Mountain. Master Thesis, University of Zagreb–Faculty of Geodesy, Zagreb, Croatia, 27 June 2014. (In Croatian). [Google Scholar]
  5. Martinić, I.; Čanjevac, I. Hydrological and hydrochemical research of springs on mt. Medvednica-Ponikve area. In Proceedings of the 8th Croatian Water Conference–Croatian Waters in Food and Energy Production: Proceedings, Poreč, Croatia, 23–25 November 2023; Biondić, D., Holjević, D., Vizner, M., Eds.; Croatian Waters: Zagreb, Croatia, 2023; pp. 363–371. (In Croatian). [Google Scholar]
  6. Bryan, K. Classification of Springs. J. Geol. 1919, 27, 522–561. [Google Scholar] [CrossRef]
  7. Borneuf, D. Springs of Alberta; ARC/AGS Earth Sciences Report 1982-3; Alberta Research Council: Edmonton, AB, Canada, 1983; 105p. [Google Scholar]
  8. Mocior, E.; Rzonca, B.; Siwek, J.; Plenzler, J.; Płaczkowska, E.; Dąbek, N.; Jaśkowiec, B.; Potoniec, P.; Roman, S.; Ździebko, D. Determinants of the distribution of springs in the upper part of a flysch ridge in the Bieszcady Mountains in southeatern Poland. Episodes 2015, 38, 21–30. [Google Scholar] [CrossRef]
  9. Mostowik, K.; Górnik, M.; Jaśkowiec, B.; Maciejczyk, K.; Murawska, M.; Płaczkowska, E.; Rzonca, B.; Siwek, J. High discharge springs in the Outer Flysch Carpathians on the example of the High Bieszczady Mountains (Poland). Carpathian J. Earth Environ. Sci. 2016, 11, 395–404. [Google Scholar]
  10. Buczyński, S.; Rzonca, B. Influence of geologic structure on the presence, discharge and physical and chemical properties of springs in the Muszynka catchment (Carpathian flysch). Episodes 2018, 48, 89–96. [Google Scholar] [CrossRef]
  11. Corsini, A.; Cervi, F.; Ronchetti, F. Weight evidence and artificial neural networks for potential groundwater spring mapping: An application to the Mt. Modino area (Northern Apennines, Italy). Geomorphology 2009, 111, 79–87. [Google Scholar] [CrossRef]
  12. Iván, V.; Stevenazzi, S.; Pollicino, L.C.; Masetti, M.; Mádl-Szőnyi, J. An Enhanced Approach to the Spatial and Statistical Analysis of Factors Influencing Spring Distribution on a Transboundary Karst Aquifer. Water 2020, 12, 2133. [Google Scholar] [CrossRef]
  13. Gebru, H.; Gebreyohannes, T.; Hagos, E. Identification of Groundwater Potential Zones Using Analytical Hierarchy Process (AHP) and GIS-Remote Sensing Integration, the Case of Golina River Basin, Northern Ethiopia. Int. J. Adv. Remote Sens. GIS 2020, 9, 3289–3311. [Google Scholar] [CrossRef]
  14. Niraula, R.R.; Sharma, S.; Pokharel, B.K.; Paudel, U. Spatial prediction of spring locations in data poor region of Central Himalayas. Hydrol. Res. 2021, 52, 492–505. [Google Scholar] [CrossRef]
  15. Cantonati, M.; Fensham, R.J.; Stevens, L.E.; Gerecke, R.; Glazier, D.S.; Goldscheider, N.; Knight, R.L.; Richardson, J.S.; Springer, A.E.; Töckner, K. An urgent plea for global spring protection. Conserv. Biol. 2020, 35, 378–382. [Google Scholar] [CrossRef]
  16. Gupta, A.; Kulkarni, H. Inventory and Revival of Springs in the Himalayas for Water Security; NITI Aayog: New Delhi, India, 2018; 52p.
  17. Poudel, D.; Duex, T.W. Vanishing springs in Nepalese Mountains: Assessment of water sources, farmers’ perceptions, and climate change adaptation. Mt. Res. Dev. 2017, 37, 35–46. [Google Scholar] [CrossRef]
  18. Bognar, A.; Faivre, S.; Buzjak, N.; Pahernik, M.; Bočić, N. Recent Landform Evolution in the Dinaric and Pannonian Regions of Croatia. In Recent Landform Evolution; Springer Geography; Lóczy, D., Stankoviansky, M., Kotarba, A., Eds.; Springer: Dordrecht, The Netherlands, 2012; pp. 313–344. [Google Scholar] [CrossRef]
  19. CMHS (Croatian Meteorological and Hydrological Service), 2023: Hydrological Data. Available online: https://hidro.dhz.hr/ (accessed on 11 January 2024).
  20. Šikić, K.; Basch, O.; Šimunić, A. Osnovna Geološka Karta (Basic Geological Map–in Croatian) SFRJ 1:100.000, List Zagreb L33–80; Institut za Geološka Istraživanja, Savezni Geološki Institut: Beograd, Serbia, 1978. [Google Scholar]
  21. Šikić, K.; Basch, O.; Šimunić, A. Osnovna Geološka Karta SFRJ 1:100.000, Tumač za list Zagreb L33–80. (Basic Geological Map: Interpretation–in Croatian); Institut za Geološka Istraživanja, Savezni Geološki Institut: Beograd, Serbia, 1979; p. 81. [Google Scholar]
  22. Šikić, K. Geološki Vodič Medvednice (Geological Guide of the Medvednica Mountain-in Croatian); Institut za Geološka Istraživanja: Zagreb, Croatia, 1995; pp. 7–30. [Google Scholar]
  23. Šegota, T.; Filipčić, A. Köppenova podjela klima i hrvatsko nazivlje (Köppen’s climate types and Croatian names–In Croatian). Geoadria 2003, 8, 17–37. [Google Scholar] [CrossRef]
  24. Kottek, K.; Grieser, J.; Beck, C.; Rudolf, B.; Rubel, F. World Map of the Köppen-Geiger climate classification updated. Meteorol. Z. 2006, 15, 259–263. [Google Scholar] [CrossRef]
  25. CMHS (Croatian Meteorological and Hydrological Service), 2023b: Meteorological Data. Available online: https://meteo.hr/klima_e.php?section=klima_pracenje&param=klel&Grad=puntijarka&Mjesec=01&Godina=2023 (accessed on 11 January 2024).
  26. Buzjak, N. Geotouristic potential of caves–example of Veternica Cave (Medvednica Nature Park, Croatia). In Proceedings of the 12th EuroSpeleo Forum, Ebensee, Austria, 23–26 August 2018; Mattes, J., Christian, E., Plan, L., Eds.; Verein für Höhlenkunde Ebensee: Neukirchen, Austria, 2018; pp. 38–41. [Google Scholar]
  27. Božičević, S. Hidrologija pećine Veternice kraj Zagreba na planini Medvednici (Hydrogeology of the Veternica Cave near Zagreb on the Medvednica Mt.–in Croatian). In Proceedings of the 8 Jugoslavenski Geološki Kongres (8th Yugoslavian Geological Congress–in Croatian), Ljubljana, Yugoslavia, 1–5 October 1974; Volume 4, pp. 5–12. [Google Scholar]
  28. Lacković, D.; Glumac, B.; Asmerom, Y.; Stroj, A. Evolution of the Veternica cave (Medvednica Mountain, Croatia) drainage system: Insights from the distribution and dating of cave deposits. Geol. Croat. 2011, 64, 213–221. [Google Scholar] [CrossRef]
  29. Bočić, N.; Pahernik, M.; Maradin, M. Temeljna geomorfološka obilježja Karlovačke županije (Basic geomorphological features of the Karlovac county–in Croatian). Prirodoslovlje 2016, 16, 153–172. [Google Scholar]
  30. National Geographic World Map-National Geographic, Esri, Garmin, HERE, UNEP-WCMC, USGS, NASA, ESA, METI, NRCAN, GEBCO, NOAA, increment P Corp. Available online: https://www.arcgis.com/home/item.html?id=b9b1b422198944fbbd5250b3241691b6 (accessed on 3 January 2024).
  31. Silverman, B.W. Density Estimation for Statistics and Data Analysis, 1st ed.; Chapman and Hall: New York, NY, USA, 1986; 186p. [Google Scholar]
  32. ArcGIS Pro: How Kernel Density Works. Available online: https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-analyst/how-kernel-density-works.htm (accessed on 12 March 2024).
  33. ArcGIS Pro–Average Nearest Neighbor (Spatial Statistics). Available online: https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/average-nearest-neighbor.htm#:~:text=The%20Nearest%20Neighbor%20Index%20is,in%20a%20hypothetical%20random%20distribution. (accessed on 10 January 2024).
  34. Meinzer, O.E. Outline of Ground-Water Hydrology; US Government Printing Office: Washington, DC, USA, 1923; 71p.
  35. Sørensen, R.; Zinko, U.; Seibert, J. On the calculation of the topographic wetness index: Evaluation of different methods based on field observations. Hydrol. Earth Syst. Sci. 2006, 10, 101–112. [Google Scholar] [CrossRef]
  36. Beven, K.J.; Kirkby, M.J. A physically based, variable contributing area model of basin hydrology. Hydrol. Sci. Bull. 1979, 24, 43–69. [Google Scholar] [CrossRef]
  37. Demek, J. Manual and Detailed Geomorphological Mapping; IGU–Comission on Geomorphological survey and mapping; Chechoslovak Academy of Science: Prague, Czech Republic, 1972. [Google Scholar]
  38. Jenks, G.F. The Data Model Concept in Statistical Mappinng. Int. Yearb. Cartogr. 1967, 7, 186–190. [Google Scholar]
  39. Rzonca, B.; Kołodziej, A.; Laszczak, E.; Mocior, E.; Plenzler, J.; Płaczkowska, E.; Rozmus, M.; Siwek, J.; Ścisłowicz, B.; Wójcik, S.; et al. Zdródła w zlewni górnej Wołosatki w Bieszczadach Wysokich (Springs in the upper Wolosatka river catchment in the High Bieszczady Mountains in Polish). Przegląd Geol. 2008, 56, 772–779. [Google Scholar]
  40. Lasek, J.; Dąbek, N.; Jaśkowiec, B.; Mocior, E.; Peek, B.; Plenzler, J.; Płaczkowska, E.; Rzonca, B.; Siwek, J.; Wójcik, S. Źródła w Bieszczadach Wysokich (Springs in the High Bieszczady Mountains–in Polish). Rocz. Bieszczadzkie 2012, 20, 254–267. [Google Scholar]
  41. Płaczkowska, E.; Górnik, M.; Mocior, E.; Peek, B.; Potoniec, P.; Rzonca, B.; Siwek, J. Spatial distribution of channel heads in the Polish Flysch Carpathians. Catena 2015, 127, 240–249. [Google Scholar] [CrossRef]
  42. Pandit, S.; Shakya, N.; Shrestha, S. Distribution and classification of springs in Bansbari area of Melamchi Municipality, Sindhupalchowk, Nepal. J. Nepal Geol. Soc. 2019, 59, 49–58. [Google Scholar] [CrossRef]
  43. Flora, S.P. Hydrogeological Characterization and Discharge Variability of Springs in the Middle Verde River Watershed, Central Arizona. Master’s Thesis, Northern Arizona University, Flagstaff, AZ, USA, May 2004. [Google Scholar]
  44. Brkić, Ž.; Čakarun, A. Osnovna Hidrogeološka Karta Republike Hrvatske 1:100.000, Tumač za List Zagreb (Basic Hydrogeological Map of Croatia 1:100.000: Interpretation–in Croatian); Institut za Geološka Istraživanja: Zagreb, Croatia, 1998; 48p. [Google Scholar]
  45. Ford, D.C.; Williams, P. Karst Hydrogeology and Geomorphology; John Wiley & Sons: Hoboken, NJ, USA, 2007. [Google Scholar]
  46. Bakalowicz, M. Karst groundwater: A challenge for new resources. Hydrogeol. J. 2005, 13, 148–160. [Google Scholar] [CrossRef]
  47. Bornhauser, K. Die Tierwelt der Quellen in der Umgebung Basels; University of Michigan Library: Ann Arbor, MI, USA, 1912; pp. 1–90. [Google Scholar]
  48. Steinmann, P. Praktikum der Süßwasserbiologie. Tail 1: Die Organismen des fließenden Wassers; Borntraeger: Berlin, Germany, 1915; 184p. [Google Scholar]
  49. Thienemann, A. Hydrobiologische Untersuchungen an Quellen. Arch. Für Hydrobiol. 1924, 14, 151–190. [Google Scholar]
  50. Baker, V.R.; Kochel, R.C.; Laity, J.E.; Howard, A.D. Spring sapping and valley network development. In Groundwater Geomorphology, The Role of Subsurface Water in Earth-Surface Processes and Landforms; Higgins, C.G., Coates, D.R., Eds.; Geological Society of America: Boulder, CO, USA, 1990; Volume 252, pp. 235–265. [Google Scholar] [CrossRef]
  51. Ozdemir, A. GIS-based groundwater spring potential mapping in the Sultan Mountains (Konya, Turkey) using frequency ratio, weights of evidence and logistic regression methods and their comparison. J. Hydrol. 2011, 411, 290–308. [Google Scholar] [CrossRef]
  52. Dunne, T. Formation and controls of channel networks. Prog. Phys. Geogr. Earth Environ. 1980, 4, 211–239. [Google Scholar] [CrossRef]
  53. Mazurek, M. Geomorphological processes in channel heads initiated by groundwater outflows (The Parsęta catchment, north-western Poland). Quaest. Geogr. 2011, 30, 33–45. [Google Scholar] [CrossRef]
  54. Buczynski, S.; Rzonca, B. Effects of crystalline massif tectonics on groundwater origin and catchment size of a large spring area in Zieleniec, Sudety Mountains, southwestern Poland. Hydrogeol. J. 2011, 19, 1085–1101. [Google Scholar] [CrossRef]
  55. Bense, V.F.; Gleeson, T.; Loveless, S.E.; Bour, O.; Scibek, J. Fault zone hydrogeology. Earth Sci. Rev. 2013, 127, 171–192. [Google Scholar] [CrossRef]
Water 16 00994 g003
Figure 3. Clustering ratio of springs in the study area(s) calculated by average nearest neighbor method (image generated by ArcMap 10.7 software; the graph serves as a visualization of statistical values: the dashed blue line indicates the result of the calculation—springs being clustered).
Figure 3. Clustering ratio of springs in the study area(s) calculated by average nearest neighbor method (image generated by ArcMap 10.7 software; the graph serves as a visualization of statistical values: the dashed blue line indicates the result of the calculation—springs being clustered).
Water 16 00994 g003
Water 16 00994 g004
Figure 4. Mapped spring distribution within the study area (a) and kernel density of springs in the study area (b).
Figure 4. Mapped spring distribution within the study area (a) and kernel density of springs in the study area (b).
Water 16 00994 g004
Water 16 00994 g005
Figure 5. Distribution of springs by Meinzer’s discharge categories.
Figure 5. Distribution of springs by Meinzer’s discharge categories.
Water 16 00994 g005
Water 16 00994 g006
Figure 6. Number of springs within the discharge categories in the study areas.
Figure 6. Number of springs within the discharge categories in the study areas.
Water 16 00994 g006
Water 16 00994 g007
Figure 7. Number of springs and spring density by different morphometric parameters: elevation (a,b); slope (c,d); relative relief (e,f).
Figure 7. Number of springs and spring density by different morphometric parameters: elevation (a,b); slope (c,d); relative relief (e,f).
Water 16 00994 g007
Water 16 00994 g008
Figure 8. Share of springs and spring density by planform curvature (a,c) and profile curvature (b,d); planform curvature scheme (e) and profile curvature scheme (f).
Figure 8. Share of springs and spring density by planform curvature (a,c) and profile curvature (b,d); planform curvature scheme (e) and profile curvature scheme (f).
Water 16 00994 g008
Water 16 00994 g009
Figure 9. Share of springs (a) and spring density (b) by TWI categories.
Figure 9. Share of springs (a) and spring density (b) by TWI categories.
Water 16 00994 g009
Water 16 00994 g010
Figure 10. Share of springs by distance from faults.
Figure 10. Share of springs by distance from faults.
Water 16 00994 g010
Water 16 00994 g011
Figure 11. Fault directions and length share in the fluviokarst and fluviodenudation area.
Figure 11. Fault directions and length share in the fluviokarst and fluviodenudation area.
Water 16 00994 g011
Water 16 00994 g012
Figure 12. Analysis of linear spring distribution using 100 × 100 m squares.
Figure 12. Analysis of linear spring distribution using 100 × 100 m squares.
Water 16 00994 g012
Water 16 00994 g013
Figure 13. Results of fault and spring kernel densities overlap.
Figure 13. Results of fault and spring kernel densities overlap.
Water 16 00994 g013
Table 1. Results of the average nearest neighbor analysis.
Table 1. Results of the average nearest neighbor analysis.
Study AreaObserved Mean Distance between Neighboring SpringsExpected Mean
Distance between Neighboring Springs		Nearest Neighbor Ratioz-Scorep-Value
fluviokarst65.06 m147.89 m0.4399−8.704<0.001
fluviodenudation83.67 m131.59 m0.6358−5.912<0.001
Table 2. Areas of fault and spring density concurrence.
Table 2. Areas of fault and spring density concurrence.
Cell ValuesConcurrence LevelFluviokarst Area (%)Fluviodenudation Area (%)
from −6 to −7complete discrepancy1.834.35
from −4 to −5poor36.5319.18
from −3 to −2good30.6523.87
from −1 to 1very good23.1345.07
from 2 to 3good7.107.52
from 4 to 5poor0.770
from 6 to 7complete discrepancy00
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Martinić, I.; Čanjevac, I. Distribution and Characteristics of Springs in Two Neighboring Areas of Different Morphogenic Relief Type—Example of SW Medvednica Mountain (Central Croatia). Water 2024, 16, 994. https://doi.org/10.3390/w16070994

AMA Style

Martinić I, Čanjevac I. Distribution and Characteristics of Springs in Two Neighboring Areas of Different Morphogenic Relief Type—Example of SW Medvednica Mountain (Central Croatia). Water. 2024; 16(7):994. https://doi.org/10.3390/w16070994

Chicago/Turabian Style

Martinić, Ivan, and Ivan Čanjevac. 2024. "Distribution and Characteristics of Springs in Two Neighboring Areas of Different Morphogenic Relief Type—Example of SW Medvednica Mountain (Central Croatia)" Water 16, no. 7: 994. https://doi.org/10.3390/w16070994

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop