sustainability

Article Karst Aquifer Vulnerability Assessment (KAVA) Method—A Novel GIS-Based Method for Deep Karst Aquifers

Ranko Biondi´c*, Hrvoje Meaški, Božidar Biondi´cand Jelena Loborec

Faculty of Geotechnical Engineering, University of Zagreb, Varaždin 42000, Croatia; [email protected] (H.M.); [email protected] (B.B.); [email protected] (J.L.) * Correspondence: [email protected]

Abstract: Karst aquifers in the Dinaric karst are very rich with groundwater and are a very important resource for public water supply. The characteristics of the Dinaric karst are the lack, or very thin layer, of covering deposits, large amounts of precipitations, high groundwater velocities, very deep groundwater flow with a lot of faults and fault zones, pits to groundwater, concentrated sinking and large karst springs, making them extremely vulnerable to all anthropogenic influences, which are very quickly transmitted to the aquifer. Numerous multiparameter methods have been developed in the last 20 years to determine the level of vulnerability of aquifers. Each of them has its own specifics and is well adapted to the climate and region for which it was developed. The Karst Aquifer Vulnerability Assessment (KAVA) method was developed in accordance with all the characteristics of the deep karst aquifers of the Dinaric karst and tested on several basins in the area. It was developed as a part of the Global Environment Facility United Nations Environmental Programme



– the Mediterranean Action Plan Strategic Partnership for the Mediterranean Sea Large Marine
 Ecosystem (GEF UNEP/MAP MedPartnership Project). This paper presents the KAVA method and

Citation: Biondi´c,R.; Meaški, H.; its application to two characteristic karst basins of the Dinaric karst: the Novljanska Žrnovnica spring Biondi´c,B.; Loborec, J. Karst Aquifer catchment area and the Bakar Bay catchment area. Vulnerability Assessment (KAVA) Method—A Novel GIS-Based Method Keywords: groundwater vulnerability; karst aquifer; Dinaric karst; GIS for Deep Karst Aquifers. Sustainability 2021, 13, 3325. https:// doi.org/10.3390/su13063325 1. Introduction Academic Editor: Fernando António Groundwater from karst aquifers is considered an important resource and is exten- Leal Pacheco sively used for public water supply. In Europe, carbonate terrains occupy about 35% of the land surface, and in some countries karst groundwater contributes up to 50% to the total Received: 23 February 2021 drinking water supply. In many regions it is the only available freshwater resource [1]. In Accepted: 15 March 2021 Published: 17 March 2021 Croatia almost 50% of all public water supplies are from karst aquifers (Figure1;[2]). Karst aquifers are particularly vulnerable to contamination because of their thin

Publisher’s Note: MDPI stays neutral soils or absence of covering deposits, flow concentration within the epikarst zone and with regard to jurisdictional claims in concentrated recharge via swallow holes. As a result, contaminants may easily reach the published maps and institutional affil- groundwater and be rapidly transported in karst conduits over large distances [3]. For iations. these reasons, it is very important to determine the level of vulnerability of karst aquifers for their protection and remediation, but also for spatial planning. There are two main river basins in Croatia: the Danube River Basin and the Adriatic Sea River Basin. Each of them is further divided into several dozen grouped groundwater bodies, and river basin management plans are developed at that level in accordance with the Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Water Framework Directive [4]. Precisely because of this, these basins are a very important This article is an open access article for observation of and research on water resources, from the regional to local scales. The distributed under the terms and catchments shown in this paper are parts of grouped bodies of groundwater, i.e., they must conditions of the Creative Commons be subjected to a very detailed analysis on a local scale. Therefore, groundwater resources Attribution (CC BY) license (https:// need to be contextualized in multiscalar dimensions. This is an important characteristic of creativecommons.org/licenses/by/ groundwater resources, as well as the fact that they are invisible, and therefore pose an 4.0/). additional challenge to their management and governance [5].

Sustainability 2021, 13, 3325. https://doi.org/10.3390/su13063325 https://www.mdpi.com/journal/sustainability Sustainability 2021, 13, 3325 2 of 20

The first estimates of the intrinsic vulnerability of water resources in Europe, based on the differences in the lithological composition of rocks, were made in 1968 by Margat and in 1970 by Albinet and Margat for France [6,7]. Ten years later, Vierhuff and his associates made a similar estimate for West Germany [8]. During the 1990s, Europe’s first project related exclusively to the protection of karst aquifers was launched [1]. The project emphasized the importance of a multidisciplinary approach to research into karst areas, using geological, geomorphological, geophysical, hydrological, geochemical and other means of investigation in order to obtain information about the karst environment and dynamics of the groundwater flow. From about 1985 to recent times, researchers worldwide have developed numerous methods and, in the early 2000s, GIS technology started to be used in such analyses. Some of the methods were developed primarily to assess the intrinsic vulnerability of karst aquifers. They were used for the protection of karst aquifers or as one of the fundamental bases for the development of regional spatial plans. Some of these methods include DRASTIC [9], AVI [10], GOD [11,12], EPIK [13–15], the Irish Method [16], REKS [17], the Austrian Method [18], VULK [19], LEA [20], PI [21,22], COP [23], SINTACS [24], The Slovene Method [25] and CC-PESTO [26], as well as many other methods. The framework for vulnerability mapping was set up through the project COST 620 [27]. That methods were applied in several catchments worldwide and, because of the specific characteristics of some karst areas, some of the methods could be applied with- out modification of the parameters [28,29]; whilst others had to have some parameters modified [30–34]. For some areas, a comparative analysis of the use of several of the most common methods of intrinsic vulnerability mapping has been conducted [35,36]. The problem is that only a few of the developed methods can be used for vulnerability analysis of deep karst aquifers, like Dinaric karst aquifers, or in the wider Mediterranean region, but mostly with some limitations. Some of the methods can be used in karst aquifers but some of the parameters used in that multiparameter methods are not fully suitable for specific characteristics of karst aquifers like Dinaric karst aquifers (e.g., large amount of precipitation, depth to groundwater, groundwater dynamics, lack of covering deposits, direct input of surface waters into groundwater through swallow- holes, very large karst springs, etc.). There are several methods for determining the intrinsic vulnerability of karst aquifers that are frequently used in hydrogeological practice. The Karst Aquifer Vulnerability Assessment (KAVA) method was developed on the same pilot areas for which intrinsic vulnerability maps were made using the COP [23], SINTACS [24] and PI [21,22] methods. Those methods were tested with the conditions of Dinaric karst deep aquifers and some of them had some limitations, but there were also some very good parameters which were used and modified in the KAVA method. The PI method [21,22] seems at first sight to be simple, but its basic (P and I) parameters require extensive calculation of subparameters, and this creates considerable complexity. This complex method for assessment of the impact of covering soils is unsuited to this region, which mostly lacks covering deposits. Also, the range of values for factor P (recharge) is also unsuitable, because the cutoff point for the maximum precipitation class is only 400 mm/year. All of the Dinaric karst area in Croatia falls into this category, and in some areas the average yearly precipitation is more than 4000 mm. The same problem can also be expected in the other countries in the Dinaric karst region (Slovenia, Bosnia and Herzegovina, Montenegro, Albania), but also in the other karst aquifers in the European part of the Mediterranean area. The surface catchment area maps produced by the PI method are, however, very good and we used this idea in the KAVA method. The COP method [23] uses excessive zoning around the main sinkholes in its assess- ment of concentrated infiltration. The 11 categories, all utilizing a score range from 0 to 1, contrast awkwardly with the three categories used to define the influence of sinking watercourses, and this creates problems in the presentation of aquifer vulnerability. Sustainability 2021, 13, x FOR PEER REVIEW 3 of 20

The COP method [23] uses excessive zoning around the main sinkholes in its assess- ment of concentrated infiltration. The 11 categories, all utilizing a score range from 0 to 1, contrast awkwardly with the three categories used to define the influence of sinking wa- tercourses, and this creates problems in the presentation of aquifer vulnerability. Although the SINTACS method [24] seems at first sight very complex, it mostly works well, because each parameter is strictly defined and described in detail, and there is no need to define subparameters. The main objection to the method after implementa- Sustainability 2021, 13, 3325 3 of 20 tion in the pilot areas in the Dinaric karst in Croatia was that it used too many geological parameters and with them explained all the other parameters, except the depth to the groundwaterAlthough the (S1) SINTACS and methodthe topo [24]graphic seems at firstslope sight (S2). very complex,This coul it mostlyd cause works the final map to be well,very because subjective, each parameter although is strictly the vulnerability defined and described map produced in detail, and for there the is nostudy need area was good. to defineThe subparameters. Karst Aquifer The Vulnerability main objection toAssessment the method after method implementation is derived in thefrom a combination ofpilot parameters areas in the Dinaric adjusted karst to in Croatiathe specific was that charac it usedteristics too many of geological the Dinaric parameters karst aquifers and is and with them explained all the other parameters, except the depth to the groundwater (S1)designed and the topographicprimarily slopefor assessment (S2). This could of cause the theintr finalinsic map vulnerability to be very subjective, of karst aquifers and sources,although the where vulnerability the final map spatial produced analysis for the study and area vulnerability was good. maps are made with multipa- rameterThe Karst GIS Aquifer technology. Vulnerability The Assessmentmethod was method developed is derived fromwithin a combination the GEF of UNEP/MAP Med- parameters adjusted to the specific characteristics of the Dinaric karst aquifers and is de- Partnershipsigned primarily Project, for assessment UNESCO-IHP of the intrinsic sub-component vulnerability of karst 1.1 aquifers “Management and sources, of coastal aquifers whereand groundwater”. the final spatial analysis The idea and vulnerability of the project maps was are made thatwith karstic multiparameter aquifers make GIS up a large pro- portiontechnology. of Thethe methodaquifers was in developed the Mediterranean within the GEF region, UNEP/MAP so developing MedPartnership a new method for their analysisProject, UNESCO-IHP would contribute sub-component greatly 1.1 “Managementto hydrogeolo of coastalgical practice aquifers and in ground-that area. This research water”. The idea of the project was that karstic aquifers make up a large proportion of endeavorthe aquifers inwas the prompted Mediterranean by region, the high so developing importance a new of method karst for aquifers their analysis in providing a water wouldsupply contribute to a large greatly concentration to hydrogeological of the practice regional in that population, area. This research and endeavorby the hope of increasing wastourism prompted in the by Mediterranean the high importance region. of karst In aquifers these inconditions, providing a waterit is necessary supply to a to harmonize and improvelarge concentration efficiency of the in regional the protection population, of and thes bye the valuable hope of increasingnatural resources tourism in in various coun- the Mediterranean region. In these conditions, it is necessary to harmonize and improve triesefficiency to safeguard in the protection the current of these and valuable future natural development resources in of various the region. countries to safeguardThe the novel current KAVA and future method development was tested of the region.on several different catchments in the Dinaric karstThe region novel KAVAin Croatia, method and was testedin this on paper several we different present catchments its application in the Dinaric in two neighboring karst region in Croatia, and in this paper we present its application in two neighboring catchment areas areas in the in northern the northern part of thepart Dinaric of the karst Dinaric area in Croatia:karst area the Novljanskain Croatia: the Novljanska Žrnovnica and and Bakar Bakar Bay catchment Bay catchment areas (Figure areas1). (Figure 1).

Figure 1. 1.Position Position of Novljanska of Novljanska Žrnovnica Žrnovnica and Bakar Bayand catchment Bakar Bay areas catchment in Croatia. areas in Croatia. Sustainability 2021, 13, x FOR PEER REVIEW 4 of 20

Sustainability 2021, 13, 3325 4 of 20 Although Novljanska Žrnovnica is a typical catchment area of the Dinaric karst in which is represented almost all the karst phenomena and forms involved in the develop- ment of the method, it was also necessary to apply the method to another catchment with Although Novljanska Žrnovnica is a typical catchment area of the Dinaric karst in slightly different characteristics. For this purpose, the Bakar Bay catchment was selected, which is represented almost all the karst phenomena and forms involved in the develop- a smaller karst catchment area situated adjacent to the Novljanska Žrnovnica catchment ment of the method, it was also necessary to apply the method to another catchment with slightlyarea. different characteristics. For this purpose, the Bakar Bay catchment was selected, a smaller karst catchment area situated adjacent to the Novljanska Žrnovnica catchment area. 2. Materials and Methods 2.2.1. Materials Description and of Methods the KAVA Method 2.1. DescriptionThe KAVA of themethod KAVAMethod is based on an origin–pathway–target conceptual model, which wasThe proposed KAVA within method the is project based onCOST an origin–pathway–target620 [27]. It is primarily designed conceptual for model, assessment which of wasintrinsic proposed vulnerability, within the with project the COSTfinal spatial 620 [27 analysis]. It is primarily and vulnerability designed formaps assessment being made of intrinsicwith multiparameter vulnerability, GIS with method the finalology. spatial Four analysis of the basic and vulnerability factors of the mapsKAVA being method made for withassessing multiparameter intrinsic vulnerability GIS methodology. are: overlay Four ofprotection the basic (O factors factor), of theprecipitation KAVA method influence for assessing(P factor), intrinsic infiltration vulnerability conditions are: (I overlayfactor) and protection aquifer (O conditions factor), precipitation (A factor) (Figures influence 2 and (P factor),3). infiltration conditions (I factor) and aquifer conditions (A factor) (Figures2 and3) .

FigureFigure 2. 2.Conceptual Conceptual modelmodel of the Karst Aquifer Aquifer Vu Vulnerabilitylnerability Assessment Assessment (KAVA) (KAVA) method. method. P— P— precipitation influence; Isv—infiltration condition subfactor slope and vegetation, Igwd—infiltra- precipitation influence; Isv—infiltration condition subfactor slope and vegetation, Igwd—infiltration tion condition subfactor groundwater depth; SCA 1–3—surface catchment areas; Os—overlay pro- condition subfactor groundwater depth; SCA 1–3—surface catchment areas; Os—overlay protection tection subfactor soils; Okf—overlay protection subfactor karst features; Ahg—aquifer conditions subfactorsubfactor soils; hydrogeological Okf—overlay description; protection subfactorAtt—aquifer karst conditions features; Ahg—aquifersubfactor tracing conditions tests. subfactor hydrogeological description; Att—aquifer conditions subfactor tracing tests. Unlike the European approach [27] and other existing methods for intrinsic vulnera- Unlike the European approach [27] and other existing methods for intrinsic vulnerabil- bility assessment, in the KAVA method the unsaturated and saturated parts of karst aq- ity assessment, in the KAVA method the unsaturated and saturated parts of karst aquifers uifers are treated together. There are several reasons for this, but the primary one is due are treated together. There are several reasons for this, but the primary one is due to the to the simplification of the overall model (the principle of Occam’s razor). Given that the simplification of the overall model (the principle of Occam’s razor). Given that the carbon- carbonate karst aquifer is a highly heterogeneous and anisotropic medium, without a suf- ate karst aquifer is a highly heterogeneous and anisotropic medium, without a sufficient ficient number of quite expensive and detailed exploration wells, which would provide number of quite expensive and detailed exploration wells, which would provide sufficient sufficient certainty for the determination of groundwater levels, the separation of the un- certainty for the determination of groundwater levels, the separation of the unsaturated andsaturated saturated and parts saturated of karst parts aquifers of karst is hardlyaquifers feasible. is hardly For feasible. these reasons, For these the reasons, boundary the betweenboundary unsaturated between unsaturated and saturated and zones saturated in karst zo aquifersnes in karst is often aquifers determined is often empiricallydetermined orempirically approximately, or approximately, and the use ofand unsaturated the use of unsaturated zone thickness zone is generallythickness is an generally unreliable an parameter,unreliable whichparameter, is the which lack of is all the models lack of that all models use it. that use it.

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Figure 3. The KAVAFigure methodology. 3. The KAVA methodology.

2.2.2.2. Overlay Overlay Protection Protection (O (O Factor) Factor) TheThe OO factor defines defines the protective role of coveringcovering layers of karst catchments, the hydrogeologicalhydrogeological protective protective role of which can vary from place to place due to the different characteristicscharacteristics of of subsurface subsurface zones zones in in the the condition condition of of open open karst. karst. Therefore, Therefore, when when deter- deter- miningmining the the value value of of the the OO factor,factor, two basic data sets are used: the subfactor Os (soils) and subfactorsubfactor Okf Okf (karst (karst features). features). TheThe Subfactor OsOs (soils)(soils)is is evaluated evaluated to to present present the the protective protective role role of theof the covering covering soil. soil.It is aIt biologicallyis a biologically active active zone zone of the of aquifer the aquifer in relation in relation to the to ground the ground surface, surface, which which may mayresult result in detention in detention and/or and/or partial partial degradation degradation of potential of potential contaminants contaminants on the on surface the sur- or faceat the or surface. at the surface. For this For reason, this reason, when designing when designing a karst a intrinsic karst intrinsic vulnerability vulnerability project, pro- it is ject,always it is necessary always necessary to evaluate to the evaluate protective the roleprotective of soil coverrole of according soil cover to according the available to soilthe data. Some of the key parameters required to estimate the protective role of covering soils available soil data. Some of the key parameters required to estimate the protective role of are soil texture, particle size distribution and thickness of the covering soil. covering soils are soil texture, particle size distribution and thickness of the covering soil. The Subfactor Os was originally proposed as part of the COP method [23], in which The Subfactor Os was originally proposed as part of the COP method [23], in which overlying soil is divided into four basic groups according to its texture and grain size distri- overlying soil is divided into four basic groups according to its texture and grain size dis- bution. In the KAVA method, these soil categories are further simplified because the Dinaric tribution. In the KAVA method, these soil categories are further simplified because the karst catchments are mostly without cover deposits. The final assessment and scoring of Dinaric karst catchments are mostly without cover deposits. The final assessment and the O factor was adapted to additionally estimated characteristics of epikarst zones. Sustainability 2021, 13, 3325 6 of 20

The subfactor Okf (karst features) defines the impact of karstified and highly perme- able surface and subsurface zones of karst aquifers on the overall intrinsic vulnerability of karst catchments, i.e., the impacts of epikarst zones. The epikarst zone can vary in thickness from a few meters to tens of meters, and is individually assessed as, due to its creation and the processes that happen in it, it is structurally different from the rest of the karst aquifer. The problem with the analysis of epikarst zones is that they generally are not visible on the surface and their thickness and distribution can be determined only by detailed geophysical surveys and exploratory drilling. However, their existence is more often determined by the indirect method—by using spatial analysis of karst geomorphological features on the surface, which indicate its origin and development. The most commonly used analysis is the density of sinkholes on the surface. The basic assumption is that an epikarst zone exists even when it is not visible on the surface, as long as there are conditions that enable its development—pure limestone with visible severe open fracture systems, karst geomorphological indicators such as sinkholes, etc. [37]. The values of the O factor are obtained by subtracting the subfactor Okf from the subfactor Os as shown in Equation (1):

O score = Os − Ok f (1)

Possible O factor values ranges from 0.1 to 2 points. Very small values (0.1 to 0.5) correspond to the areas where the soil is very poorly developed or absent and where many dolines are present. Small to moderate values (0.5 to 1) correspond to the areas where the soil is developed to a depth of 1 m and many dolines are present, as well as areas where the soil is slightly shallower and fewer dolines are present per km2. Moderate to high values (1 to 1.5) correspond to areas where the soil is mainly developed to a depth of 2 m and fewer dolines are present. Very high values (over 1.5) generally correspond to areas where the soil is developed to a depth of 1 to 2 m and few dolines are present, as well as areas with very deep soils (>2 m) and no occurrence of dolines. In the preparation of the final intrinsic vulnerability map with the KAVA method, unclassified O factor values must be used.

2.3. Precipitation Influence (P Factor) The influence of precipitation (P factor) is an external stress applied to the whole vulnerability assessment used in the KAVA method. In assessing the P factor, an effective amount of rainfall must be taken into account. It is the part of the total rainfall that has a real chance of infiltrating from the surface and with percolation sinking into the deeper parts of the karst aquifer. The effective precipitation impact on the vulnerability is expressed in the form of the Pe subfactor (effective precipitation). In assessing the vulnerability of karst aquifers the most critical factors are considered in the Pe subfactor scoring, namely the high intensity and amount of rainfall that causes rapid infiltration and transport of water with potential contaminants into the deeper parts of the aquifer. Taking into account the fact that the distribution of total annual rainfall may also further affect the vulnerability of karst catchments, an additional Pi subfactor (precipitation intensity) is also used to determine the total P factor. This allows further modification, as needed, of the effective rainfall influence. The values of the subfactor Pe (effective precipitation) are determined from the val- ues of the mean effective rainfall in the catchment area. Values ranging from 1000 to 1500 mm/yr are taken as neutral, while all other values can modify the total intrinsic vulnerability of karst catchment (Figure3). Data on effective rainfall can be obtained from previous research, meteorological and precipitation maps, etc., as well as through the calcu- lation of many empirical formulas [38–40] that take into account the overall mean amount of precipitation, air temperature and other parameters relevant to effective precipitation evaluation. Sustainability 2021, 13, x FOR PEER REVIEW 7 of 20

Sustainability 2021, 13, 3325 7 of 20

of precipitation, air temperature and other parameters relevant to effective precipitation evaluation. Subfactor Pi (precipitation intensity) is determined from the values of the mean annual Subfactor Pi (precipitation intensity) is determined from the values of the mean an- rainfall and the total number of rainy days in the catchment area, using Equation (2): nual rainfall and the total number of rainy days in the catchment area, using Equation (2): P𝑃(mm 𝑚𝑚/𝑦𝑟/yr) Pi𝑃𝑖= = (2) Number𝑁𝑢𝑚𝑏𝑒𝑟 of rainy 𝑜𝑓 days 𝑟𝑎𝑖𝑛𝑦 𝑑𝑎𝑦𝑠 FewerFewer rainy rainy days days for the same total amount of rainfall causes higher precipitation intensities,intensities, which which results results in in the the increased increased intrinsic intrinsic vulnerability vulnerability of of karst karst aquifers. aquifers. In In addi- addi- tion,tion, more more intense intense precipitation precipitation favors favors the the conc concentratedentrated infiltration infiltration of water into the karst underground,underground, i.e., flushing flushing of the aquifer unsa unsaturatedturated zone. On the the other other hand, hand, more more rainy rainy daysdays causes causes lower precipitation intensity and more uniform distribution of total rainfall duringduring the the year. year. This This reduces reduces the the aquifer aquifer intrinsic intrinsic vulnerability vulnerability due due to to increased increased (slower) (slower) diffusiondiffusion infiltration infiltration of of water water into into the the karst karst underground. underground. To To assess assess the the overall overall impact impact of theof the Pi subfactor,Pi subfactor, three three categories categories of rainfall of rainfall intensity intensity are areused used (Figure (Figure 3), 3the), the principle principle se- lectionselection of ofwhich which is shown is shown in inFigure Figure 4 4for for three three values values of of the the total total mean mean annual annual rainfall. rainfall.

FigureFigure 4. 4. SelectionSelection of of basic basic Pi Pi (precipitation (precipitation intensity) categories.

TheThe P P factor was developed based on the guidelines proposed by the project COST 620620 [27] [27] with a certain simplification simplification of the whole procedure and keeping in mind that precipitationsprecipitations represent represent external external stress, stress, which which further further modifies modifies the the total total vulnerability vulnerability as- sessment;assessment; in inthe the case case of ofintense intense rainfall rainfall this this can can be be a apositive positive effect effect of of dilution dilution of of pollution. pollution. PP factorfactor values values are are obtained obtained by multiplying Pe and Pi subfactors (Equation (3)): P𝑃 score 𝑠𝑐𝑜𝑟𝑒= Pe·Pi =𝑃𝑒∙𝑃𝑖 (3)

PossiblePossible PP factorfactor values values range range from from 0.6 to 1.5. InIn the the preparation preparation of of the the final final intrinsic intrinsic vulnerability vulnerability map map with with the the KAVA KAVA method, method, unclassifiedunclassified P factorfactor values values should be used.

2.4.2.4. Surface Surface Catchments Catchments Areas Areas TheThe surface surface catchment catchment area area (SCA) (SCA) parameter parameter is obtained is obtained by byspatial spatial analysis analysis of hydro- of hy- logicaldrological phenomena phenomena on the on surface the surface of certain of certain karst catchment karst catchment area. The area. basis The of the basis analysis of the isanalysis the separation is the separation of the main of thesurface main catchm surfaceent catchment areas for swallow-hole areas for swallow-hole zones and zones the sink- and ingthe streams sinking streamsthat gravitate that gravitate to them. to them. AfterAfter an an analysis, analysis, karst karst catchments catchments can can be be divided divided at at surface surface into into three three main main areas, areas, accordingaccording to Figure Figure 33.. In further spatial analysesanalyses dependentdependent onon thesethese areas,areas, thethe conditionsconditions ofof diffuse diffuse or or concentrated concentrated infiltration infiltration of of surface surface water water into into the the karst karst underground underground are arees- timatedestimated (SCA (SCA 2 and 2 and SCA SCA 3), and 3), andthe final the final intrinsic intrinsic vulnerability vulnerability map emphasizes map emphasizes the areas the ofareas greatest of greatest vulnerability vulnerability (SCA (SCA1), which 1), which include include sinkholes, sinkholes, sinkhole sinkhole zones zones and surface and surface wa- terwater bodies bodies that that affect affect them. them. Depending on the scale of the final intrinsic vulnerability map, the buffer zones around SCA 1s should be defined according to Figure3. Sustainability 2021, 13, 3325 8 of 20

2.5. Infiltration Conditions (I Factor) Assessment of the degree of surface water infiltration into the deeper parts of the karst aquifer depends on many parameters that control the processes of surface and subsurface water flow. The most important are: terrain slopes, properties of overlay deposits, the presence of vegetation and the presence of morphological forms that cause local infiltration anomalies (sinkholes, caves, dolines, etc.). Taking into account the fact that some of these parameters have been already used in the assessment of the O factor (properties of cover sediments and karst geomorphological forms), the I factor is developed in such a way that its impact on karst catchment vulnera- bility depends on two distinct yet mutually connected layers: the Isv subfactor (slope and vegetation) and the Igwd subfactor (depth to groundwater). The Isv subfactor (slope and vegetation) defines conditions at the ground surface that can affect the infiltration of surface water, and consequently conditions that affect the intrinsic vulnerability of the karst catchment, i.e., through this subfactor the influences of the terrain slope and vegetation cover on the infiltration are combined. The Vegetation parameter (v) is used for determination of the areas that are covered with dense or sparse vegetation (Figure3). Areas covered by dense vegetation include parts of the catchment area that are covered by forests, bushy forests and bushes, while the rest of the catchment area includes the areas covered by sparse vegetation, as well as those areas where there is no vegetation cover. This information can usually be obtained through spatial analysis of land-use maps or Corine Land Cover (CLC) maps. The slope parameter (s) can be obtained relatively easily from digital elevation models by using spatial analysis methods. After analysis has been conducted, obtained values can be further classified into one of four proposed categories of slopes (Figure3). Slope categories and vegetation classification were developed using only two cate- gories taken from the COP method [23] because this was the most appropriate method for the catchment areas in the Dinaric karst, with regard to estimation of surface water infiltration. Given the fact that the Isv subfactor is directly controlled by hydrological conditions on the catchment surface, prior to its overall impact assessment on catchment vulnerability it is necessary to align it with the SCA parameter. • When assessing the Isv in the SCA 2 area, the conditions of concentrated infiltration of water into the karst underground are assumed, because dominant surface runoffs related to concentration and flow of surface water to watercourses and their swallow holes are in this area. In such conditions, the combination of slopes and vegetation provides the Isv subfactor value, which suggests greater vulnerability in cases of major slopes and scarce vegetation (Figure3). In real conditions, this means shorter transport time and rapid water infiltration into the karst underground. • When assessing the Isv in the SCA3 area, conditions of diffuse infiltration of water into the karst underground are assumed, because longer retention of water on the catchment surface is dominant in this area. Therefore, the impact assessment of slopes and vegetation is determined in a reverse manner to the previous case. The Isv subfactor values are such that they indicate greater vulnerability in cases of small slopes and scarce vegetation (Figure3). The Igwd subfactor (groundwater depth), through the assessment of the depth to groundwater values, defines the impact (the importance) of the infiltrated surface water on the overall intrinsic vulnerability of a specific karst catchment area, where the values of the subfactor Igwd are not only related to the unsaturated zone, but to the whole aquifer. Although this subfactor is difficult to determine, it is not negligible. A deeper water table means that the impact of infiltrated surface water will be smaller, due to a longer and/or prolonged transport time of potentially contamination water toward the saturated part of the karst aquifer. For the best assessment of Igwd subfactor values, it is necessary to have a good piesometric boreholes network of the whole catchment area. With such data and with Sustainability 2021, 13, 3325 9 of 20

good spatial analysis, it is possible to determine the position of the water table in the karst aquifer and prepare a groundwater depth map (GWDM). Due to a lack of such data in karst areas, it is very difficult to make accurate ground- water depth maps. In this case, it is possible to estimate the Igwd subfactor based on good knowledge about hydrogeological relations in the karst catchment, particularly using knowledge of the absolute groundwater level in the aquifer. To obtain a final GWDM a map of the absolute level of groundwater is subtracted from the digital terrain model (elevation map). The final groundwater depth map obtained by spatial analyses of boreholes data or by estimation is the base for the scoring of the Igwd subfactor. Some of the vulnerability assessment methods for intrinsic vulnerability often divide the saturated and unsaturated zones of the aquifer, which is generally reasonable in the case of intergranular aquifers, but not in the case of karst aquifers. In the KAVA method, the exact depth to groundwater is not specified, but the range of values is, which means easier empirical evaluation of this parameter for researchers. This is actually a modified and further simplified version of the approach used in the SINTACS method [24], which also does not take into account exact values, but the ranges of depth to groundwater. The I factor values are obtained by summing the subfactors Igwd and Isv (which specifically define the SCA 2 and SCA 3 parts of the catchment area), because ultimately the influence of each of these two subfactors complements the other, as shown in Equation (4):

I score = Isv + Igwd (4)

Possible values are in the range of 1.5 to 2, implying that this factor impacts the overall intrinsic vulnerability of karst aquifers in a way that is always decreasing it—the only question is to what extent. In preparing the final intrinsic vulnerability map with the KAVA method, unclassified I factor values must be used.

2.6. Aquifer Conditions (A Factor) Conditions in the karst aquifer itself, important for the assessment of intrinsic vul- nerability, are defined as the A factor, the overall impact of which is estimated through two layers of data: static conditions in karst aquifers are estimated with the Ahg subfactor (hydrogeological description) and dynamic conditions in karst aquifers are estimated with the Att subfactor (tracing tests). In determining the Ahg subfactor values (hydrogeological description), static con- ditions in the karst aquifer are estimated based on available geological, lithological and hydrogeological data, while the basic criteria are the lithological composition of the rocks and the level of karstification. Other information that may also help in the assessment of this subfactor come from geomorphologic analysis, the results of speleological explo- ration, the results of well testing, spring hydrograph analysis, hydrochemical analysis and geophysical surveys. Scoring of the Ahg subfactor is adapted to the overall methodology and represents a relative and immeasurable value. These values only indicate the fact that one hydrogeolog- ical formation, relatively speaking, is more or less vulnerable than another (Figure3). In determining the Att subfactor values (tracing tests), dynamic conditions in the karst aquifer are estimated based on the results of tracing tests in the observed karst catchment area. Observed tracing tests have to be performed during the rain seasons when the groundwater flow velocities are the highest. Data can be obtained by analyzing the discrete apparent time values. It is possible to obtain these values for each tracing test by processing and analyzing all relevant tracing tests—apparent groundwater velocities and distance of tracer injection and tracer appearance sites. Using GIS spatial analysis with suitable interpolation methods, it is possible to obtain from discrete apparent time values a continuous spatial distribution of tracing values relevant for an investigated karst catchment area. Sustainability 2021, 13, 3325 10 of 20

It should be noted that the quality of spatial interpolation of tracing results will be more reliable the better the spatial distribution of the conducted tracing tests, which also results in more uniform values for tracing tests carried out in the same part of the catchment area. Smaller values of the Att subfactor suggest better “connectivity” of a certain part of the catchment with the karst source or source zone, which actually increases the overall vulnerability of that part of catchment area compared to the rest of the area (Figure3). When assessing the values of the Ahg and Att subfactors, it should be taken into account that, in relative time, these values are fixed, i.e., their potential variability cannot significantly effect the overall intrinsic vulnerability assessment of the karst system. This is important to note because karst aquifers can be very dynamic hydrogeological systems, as is the case of the karst area of the Dinarides in Croatia. In such conditions, some parts of the karst aquifers can change their hydrogeological function over time (e.g., permanent and temporary karst springs) and in space (e.g., fluctuations in the water table). However, due to the simplification of the model, these changes should be taken into account only when there are justifiable reasons or new knowledge (e.g., new hydrogeological studies, new tracing test results, etc.). In such cases, both subfactors should be re-evaluated and scored again and their impact on the overall intrinsic vulnerability of the karst system reassessed. The A factor values (A scores) are obtained by summing the Ahg and Att subfactors, as the effects of these two subfactors complement each other (Equation (5)):

A score = Ahg + Att (5)

Possible values are in the range of 0.2 to 3. Smaller values indicate the greater vulnera- bility of a karst system conditioned by greater karstification, potentially better permeability of layers and tracing test results that show better and faster connections with the karst spring. High values of the A factor indicate parts of the catchment area that are not directly related to karst springs, or parts of catchment areas for which the permeability is limited. These are very often areas made of non-carbonate rocks, in which shallow subsurface aquifers with limited spreading could be developed. In preparing the final intrinsic vulnerability map with the KAVA method, unclassified A factor values should be used.

2.7. Vulnerability Indices The overall results of the karst catchment analysis are two indices of vulnerability. The source vulnerability index (SV index) refers to the assessment of the intrinsic vulnerability of karst springs (Equation (6)), and the resource vulnerability index (RV index) refers to the assessment of the intrinsic vulnerability of karst aquifers (Equation (7)). In calculations of both indices, a critical parameter is the A factor. Specifically, when assessing the intrinsic vulnerability of karst springs (source vulnerability), values of the total A factor related to the observed spring are used, since in this case the A factor takes into account the static and dynamic conditions in the karst system. By separating the A factor into the two main subfactors (Ahg and Att) and taking into account only subfactor Ahg, an estimation of the intrinsic vulnerability of the karst aquifer (resource vulnerability) can be obtained, because in this case the A factor considers only the static conditions in the karst aquifer.

SVI score = (O score + I score + A score)·P score (6)

RVI score = (O score + I score + Ahg score)·P score (7) Calculation of both indices is made in such a way that the scores obtained by calcula- tion of each factor (O score, I score, A score) are summed altogether and multiplied by the score of the P factor (P score), which represents the external stress in the KAVA method. After that, the additional extraction of the most vulnerable parts in the catchment area (swallow holes, swallow hole zones and zones of sinking streams that gravitate to these Sustainability 2021, 13, 3325 11 of 20

swallow holes) should be undertaken in such a way that the SCA 1 parts of the catchment area automatically have a unique value of 0.1 points. Finally, the SV index values range between 0.25 and 10.5, and the RV index values range between 0.25 and 7.5. For the final intrinsic vulnerability map, the obtained values of these two indices are classified into six categories of vulnerability (Table1). The spatial distribution of the SV index is displayed in the form of a source vulnerability map and the spatial distribution of the RV index in the form of a resource vulnerability map.

Table 1. Resource and source vulnerability assessment scheme.

RVI Score RV Index Vulnerability Classes Colour SVI Score SV Index Vulnerability Classes Colour <2 1 Extreme red <2.7 1 Extreme red 2–2.5 2 Very high orange 2.7–3.2 2 Very high orange 2.5–3 3 High yellow 3.2–3.6 3 High yellow 3–3.5 4 Moderate light green 3.6–4 4 Moderate light green 3.5–4 5 Low green 4–5.8 5 Low green >4 6 Very low blue >5.8 6 Very low blue

3. Application of the KAVA Method 3.1. Description of the Novljanska Žrnovnica and the Bakar Bay Catchment Areas The Novljanska Žrnovnica catchment area occupies about 1000 km2, which makes it one of the largest karst catchments in the Adriatic basin in Croatia. The entire catchment is in Croatian territory; there are no cross-border characteristics. The catchment is oriented north-east–south-west, echoing the geological structures of the Dinarides. On the north side of the catchment boundary is the watershed between the Adriatic Sea and Danube River basins. Numerous complex hydrogeological studies have been carried out on this catchment area and these have shown the positions of the watersheds. The spring itself is in the central part of the catchment area. It is fed in part from the northwestern part of the catchment (Liˇcpolje), in part from the mountain areas in the hinterland, which stretch to the Gorski kotar area, and in part from the Lika area (the sinkhole zones around the rivers Sustainability 2021, 13, x FOR PEER REVIEWGacka and Lika) (Figure5). This pattern has been confirmed by numerous tracing12 tests of 20

and hydrogeochemical research.

FigureFigure 5. 5. CatchmentCatchment areas areas of of Novljanska Novljanska Žrnovnica and Bakar Bay.

The biggest spring in the catchment area is Novljanska Žrnovnica spring. The capac- ity of the spring varies during the year, from 0.5 m3/s during the summer drought period to almost 15 m3/s during the autumn rainy period. In addition to the Novljanska Žrnov- nica spring, there are several other permanent and temporary springs in the more than 100 km long discharge zone along the coast that forms a border of the catchment area. Some of them produce a significant amount of water, but only the water from Novljanska Žrnovnica is captured directly to contribute to the public water supply. The reasons are that the other springs dry up substantially or completely during the summer or have big problems with salinization [41]. In the geological composition of this catchment area most of the elements character- istic of the geological structure of the Dinarides can be found, from predominantly clastic rocks of the Palaeozoic Era in anticline forms to a complete sequence of Mesozoic Era rock formations, which means that the carbonate rocks are several thousand meters thick. The boundary conditions of the Novljanska Žrnovnica spring catchment area, the direction of groundwater flow and the occurrence of springs and sinks all directly reflect the geologi- cal and structural conditions. The most important water resources system in the Lika region, as well as in the Novljanska Žrnovnica catchment area, comprises the Lika and Gacka rivers, in which most of the surface water of the area is concentrated. Under natural conditions, the waters of these rivers sank entirely into swallow holes (ponor) in the Gacka and Lika poljes, and the groundwater in the area from Novi Vinodolski to the south drained into coastal springs. However, with the construction of HPP Senj (a hydroelectric power plant), the natural conditions have changed substantially, especially during dry periods, as during rainy periods the overflow of water still drains into the natural sinks. The Bakar Bay catchment area (Figure 5) spreads from the discharge zone on the north side of the Bakar Bay towards the mountain region of Gorski kotar. Also, ground- water that is temporarily discharged on the northeastern side of the Grobničko polje and sinks in the southern edge belongs to the same catchment area, as was confirmed by the tracing tests. The catchment covers the slopes of the mountain region of Gorski kotar from the southern part of Grobničko polje on the northwest to the Lič polje on the southeast side of the catchment area. The southwest boundaries of the catchment are impermeable flysch deposits of the Vinodol valley, which has been flooded by sea in the Bakar Bay area. The northeastern border is formed of impermeable clastic rocks with an anticline core in the Gorski kotar region. Occurrences of springs are related to the fault contact between the well-permeable carbonate rocks of the Gorski kotar anticline structure and the impermeable Eocene clastic Sustainability 2021, 13, 3325 12 of 20

The biggest spring in the catchment area is Novljanska Žrnovnica spring. The capacity of the spring varies during the year, from 0.5 m3/s during the summer drought period to almost 15 m3/s during the autumn rainy period. In addition to the Novljanska Žrnovnica spring, there are several other permanent and temporary springs in the more than 100 km long discharge zone along the coast that forms a border of the catchment area. Some of them produce a significant amount of water, but only the water from Novljanska Žrnovnica is captured directly to contribute to the public water supply. The reasons are that the other springs dry up substantially or completely during the summer or have big problems with salinization [41]. In the geological composition of this catchment area most of the elements characteristic of the geological structure of the Dinarides can be found, from predominantly clastic rocks of the Palaeozoic Era in anticline forms to a complete sequence of Mesozoic Era rock formations, which means that the carbonate rocks are several thousand meters thick. The boundary conditions of the Novljanska Žrnovnica spring catchment area, the direction of groundwater flow and the occurrence of springs and sinks all directly reflect the geological and structural conditions. The most important water resources system in the Lika region, as well as in the Novljanska Žrnovnica catchment area, comprises the Lika and Gacka rivers, in which most of the surface water of the area is concentrated. Under natural conditions, the waters of these rivers sank entirely into swallow holes (ponor) in the Gacka and Lika poljes, and the groundwater in the area from Novi Vinodolski to the south drained into coastal springs. However, with the construction of HPP Senj (a hydroelectric power plant), the natural conditions have changed substantially, especially during dry periods, as during rainy periods the overflow of water still drains into the natural sinks. The Bakar Bay catchment area (Figure5) spreads from the discharge zone on the north side of the Bakar Bay towards the mountain region of Gorski kotar. Also, groundwater that is temporarily discharged on the northeastern side of the Grobniˇckopolje and sinks in the southern edge belongs to the same catchment area, as was confirmed by the tracing tests. The catchment covers the slopes of the mountain region of Gorski kotar from the southern part of Grobniˇckopolje on the northwest to the Liˇcpolje on the southeast side of the catchment area. The southwest boundaries of the catchment are impermeable flysch deposits of the Vinodol valley, which has been flooded by sea in the Bakar Bay area. The northeastern border is formed of impermeable clastic rocks with an anticline core in the Gorski kotar region. Occurrences of springs are related to the fault contact between the well-permeable carbonate rocks of the Gorski kotar anticline structure and the impermeable Eocene clastic rocks on the northeast side of the submerged part of Vinodol valley in the Bakar Bay (Figure4). The mentioned faulted zone is very complex because of the appearance of laminate structures, with impaired identification of the hydrogeologically active parts of the aquifer. Part of the faulting zone is submerged, which creates problems in terms of the relations between fresh and salt water during summer dry periods. Several springs in the Bakar Bay catchment area are captured for the water supply but the biggest is Dobrica spring, with a minimum capacity of approximately 90 l/s. The problem with captured Dobrica spring water is the requirement for salinization during summer dry periods, sometimes for more than a month. The spring has problems with saltwater intrusion because of the submerged contact between carbonate rocks and flysch deposits, which has resulted in the openness of the structures to the intrusion of sea water and the direct influence on the coastal aquifer. On the other hand, deep karstification of carbonate rocks allows flows of specific weighted sea water in the deep parts of the aquifer and its conical raising towards the pumps at water captures when the pressure of fresh water from the basin gets low. Sustainability 2021, 13, 3325 13 of 20 Sustainability 2021, 13, x FOR PEER REVIEW 13 of 20

3.2. Vulnerability Maps of the Novljanska Žrnovnica and Bakar Bay Catchment Areas rocks on the northeast side of the submerged part of Vinodol valley in the Bakar Bay (Fig- The data needed to create the intrinsic vulnerability map were collected from numer- ure 4). The mentioned faulted zone is very complex because of the appearance of laminate ous studies made in the last fifty years. These studies were undertaken in the context of structures, with impaired identification of the hydrogeologically active parts of the aqui- groundwater protection, water research, determination of basins, groundwater tracing fer. Part of the faulting zone is submerged, which creates problems in terms of the rela- tests and detailed research in individual springs, sinkholes and sinking zones. In addition tions between fresh and salt water during summer dry periods. to the mentioned studies, data from thematic maps were used, such as data on covering depositsSeveral from springs the Hydropedological in the Bakar Bay catchment Map of the area Republic are captured of Croatia for the (S 1:300,000) water supply [42], butgeological the biggest data is from Dobrica the Basicspring, Geological with a minimum Map of capacity the Republic of approximately of Croatia (S 90 1:100,000), l/s. The problemdata on aquiferswith captured and hydrogeological Dobrica spring parameters water is the from requirement the Basic Hydrogeological for salinization during Map of summerthe Republic dry periods, of Croatia sometimes (S 1:100,000), for more hydrometeorological than a month. The data spring from thehas Climate problems Atlas with of saltwaterCroatia [ 43intrusion], digital because terrain of model the submerged from topographic contact between maps of carbonate the Republic rocks of and Croatia flysch (S deposits1:25,000),, which soil use has from resulted CORINE in the Land openness Cover of maps, the structures etc. to the intrusion of sea water and theFactor direct O valuesinfluence were on determinedthe coastal onaquifer. the basis On the of subfactors other hand, Os deep (soils) karstification and Okf (karst of carbonatefeatures). rocks Subfactor allows Os flows is defined of specific by two weighted criteria: sea the water soil texture in the (whichdeep parts differs of the in termsaquifer of andclay, its silty conical sand raising and loamy toward soil)s andthe thepumps thickness at water of the captures soil cover when (for the which pressure there of are fresh four waterclasses: from shallower the basin than gets 0.5 low. m, 0.5–1 m, 1–2 m and over 2 m). Descriptions of the texture and thickness of soils in the study area were taken from the hydropedological map (S 3.2.1:300,000) Vulnerability [31]. ThisMaps classification of the Novljanska produced Žrnovnica the requiredand Bakar polygonBay Catchment values. Areas Subfactor Okf concernsThe d theata impactneeded of to epikarst create the zones. intrinsic It was vulnerability estimated on map the were basis collected of a spatial from analysis numer- of ousthe densitystudies made of dolines, in the which last fifty was years. digitized These from studies topographic were undertaken maps (S 1:25,000). in the context Using theof groundwaterArcGIS/ArcInfo protection, Spatial Analyst water research, tool (ESRI) determination and the density of basins, analysis groundwater method, the discrete tracing testspoint and data detailed were converted research in to individual rasters. springs, sinkholes and sinking zones. In addition to theThe mentioned final values studies, of the data factor from O werethematic derived maps by were subtracting used, such the Okf as data score on from covering the Os depositsraster (Figure from 6the). These Hydropedological show the protective Map of role the of Republic covering of sediments Croatia in(S the1:300,000 Novljanska) [42], geologicalŽrnovnica data spring from and the the Basic Bakar Geological Bay catchment Map areas.of the Republic of Croatia (S 1:100,000), data onP factoraquifers values and werehydrogeological determined parameters on the basis from of thethe PeBasic(effective Hydrogeological precipitation) Map and of thePi (precipitationRepublic of Croatia intensity) (S 1:100,000 subfactors.), hydrometeorological Subfactor Pi was determined data from the from Climate mean Atlas annual of Croatiaprecipitation [43], digital and the terrain total numbermodel from of rainy topographic days. A maps map ofof meanthe Rep annualublic of precipitation Croatia (S 1:25,000for the) area, soil ofuse Croatia from CORINE is available Land as Cover a result maps, of earlieretc. monitoring and research [44]. In thisFactor study, O values only the were data determined related to on the the Novljanska basis of subfactors Žrnovnica Os spring(soils) and and Okf the (karst Bakar features).Bay catchment Subfactor areas Os were is defined used. Theby two total criteria: number the of soil rainy texture days (which was obtained differs in from terms the ofmap clay, of silty the meansand and annual loamy number soil) and of days the thickness with the amountof the soil of precipitationcover (for which≥ 1 there mm [are45]. fourDigitization classes: shallower of the precipitation than 0.5 m, data 0.5– provided1 m, 1–2 m the and required over 2 polygon m). Descriptions values, which of the were tex- turereclassified and thickness to the of default soils in values the study to produce area were the takenPi raster. from Subfactorthe hydropedologPe is determinedical map (fromS 1:300 the,000 values) [31]. of This mean classification effective precipitation produced the in required the catchment polygon area, values. using Subfactor the empirical Okf formula developed by Žugaj [40]; Equation (8)), which is often used to estimate the effective concerns the impact of epikarst zones. It was estimated on the basis of a spatial analysis amount of precipitation in the Dinaric karst in Croatia: of the density of dolines, which was digitized from topographic maps (S 1:25,000). Using the ArcGIS/ArcInfo Spatial Analyst tool (ESRI) and the density analysis method, the dis- crete point data were converted to rasters.Pe = 0.83 ·P − 250 (8)

(a) (b)

FigureFigure 6 6.. OverlayOverlay protection protection ( (O)O) map map—(—(aa)) Bakar Bakar Bay Bay catchment; catchment; ( (bb)) Novljanska Novljanska Ž Žrnovnicarnovnica catchment catchment.. Sustainability 2021, 13, x FOR PEER REVIEW 14 of 20

(a) (b) Figure 6. Overlay protection (O) map—(a) Bakar Bay catchment; (b) Novljanska Žrnovnica catchment.

P factor values were determined on the basis of the Pe (effective precipitation) and Pi (precipitation intensity) subfactors. Subfactor Pi was determined from mean annual pre- cipitation and the total number of rainy days. A map of mean annual precipitation for the area of Croatia is available as a result of earlier monitoring and research [44]. In this study, only the data related to the Novljanska Žrnovnica spring and the Bakar Bay catchment areas were used. The total number of rainy days was obtained from the map of the mean annual number of days with the amount of precipitation ≥ 1 mm [45]. Digitization of the precipitation data provided the required polygon values, which were reclassified to the default values to produce the Pi raster. Subfactor Pe is determined from the values of mean effective precipitation in the catchment area, using the empirical formula developed by

Sustainability 2021, 13, 3325 Žugaj ([40]; Equation (8)), which is often used to estimate the effective amount of precipi-14 of 20 tation in the Dinaric karst in Croatia: 𝑃𝑒 = 0.83 ∙ 𝑃 − 250 (8) The P scores were obtained by multiplying the Pe and Pi rasters to produce a grid with unclassified unclassified values for the spatial distributiondistribution of the P factor. These scores were then classifiedclassified to produce the P map (Figure 77),), whichwhich representsrepresents aaspatial spatial distributiondistribution ofof thethe precipitation impacts on natural vulnerabilityvulnerability in the Novljanska Žrnovnica spring and Bakar Bay catchment areas. From a spatial analysis of hydrological and hydrogeological relations, the catchment areas of the Novljanska Žrnovnica spring and Bakar Bay were divided into three main types of catchment area, using the definitions definitions for the SCA parameter. To do this, we used hydrogeological maps (S 1:100.000 1:100,000 and S 1:300.000), 1:300,000), previous hydrogeological studies and topographic maps (S 1:25.000). 1:25,000). The point and li linene data were converted into zonal polygon values using the ArcGIS/ArcInfo Spatial Spatial Anal Analystyst tool tool and the ring buffering method, and these were digitized to produce the SCA grid (Figure(Figure8 8).).

(a) (b) Sustainability 2021, 13, x FOR PEER REVIEW 15 of 20

Figure 7. Precipitation influence influence (P)(P) map—(a) Bakar Bay catchment; (b)) NovljanskaNovljanska ŽrnovnicaŽrnovnica catchment.catchment.

(a) (b)

Figure 8. SurfaceSurface catchment catchment area area ( (SCA)SCA) map—( a)) Bakar Bay catchment; ( b) Novljanska Žrnovnica catchment.

ValuesValues of of the the I Ifactor factor were were determined determined on onthe the basis basis of subfactors of subfactors Isv (slope Isv (slope and veg- and etation)vegetation) and Igwd and Igwd (infiltration (infiltration groundwater groundwater depth). depth). The map The of mapterrain of slopes terrain was slopes derived was fromderived the from digital the elevation digital elevation model (DEM), model(DEM), created created using terrain using terrain contours contours digitized digitized from topographicfrom topographic maps maps(S 1:25.000). (S 1:25,000). Figure Figure3 provides3 provides the classification the classification used to used produce to produce the Isv raster.the Isv raster. ToTo assess the impact of vegetation we used the CLC map and again classified classified the resultsresults using using Figure Figure 33 andand thethe definitionsdefinitions ofof vegetationvegetation covercover outlinedoutlined earlier.earlier. TheThe valuesvalues ofof s s and and v v were were harmonized harmonized with with the the SCA SCA para parametermeter to to produce produce a raster raster with with unclassified unclassified values for the spatial distribution of the Isv subfactor. Subfactor Igwd was determined based on the map of the depth to groundwater (groundwater map). Since, as was explained earlier, no accurate data were available, esti- mates were used. Final values of the I factor (I scores) were obtained by summing the Isv and Igwd rasters, which gave the raster with unclassified values for the spatial distribution of factor I. After reclassification of the raster, the I map was created (Figure 9), showing the impact of infiltration on the intrinsic vulnerability of the Novljanska Žrnovnica and Bakar Bay catchment areas.

(a) (b) Figure 9. Infiltration conditions (I) map—(a) Bakar Bay catchment; (b) Novljanska Žrnovnica catchment.

The values of the A factor were determined on the basis of subfactor Ahg (hydroge- ological description), which defines the static conditions in a karst aquifer (Figure 10), and subfactor Att (tracing tests), which defines the dynamic conditions in a karst aquifer (Fig- ure 11). For Ahg data on lithological units from the Basic Geological Map of Croatia were Sustainability 2021, 13, x FOR PEER REVIEW 15 of 20

(a) (b) Figure 8. Surface catchment area (SCA) map—(a) Bakar Bay catchment; (b) Novljanska Žrnovnica catchment.

Values of the I factor were determined on the basis of subfactors Isv (slope and veg- etation) and Igwd (infiltration groundwater depth). The map of terrain slopes was derived from the digital elevation model (DEM), created using terrain contours digitized from topographic maps (S 1:25.000). Figure 3 provides the classification used to produce the Isv raster. To assess the impact of vegetation we used the CLC map and again classified the Sustainability 2021, 13, 3325 results using Figure 3 and the definitions of vegetation cover outlined earlier. The values15 of 20 of s and v were harmonized with the SCA parameter to produce a raster with unclassified values for the spatial distribution of the Isv subfactor. Subfactor Igwd was determined based on the map of the depth to groundwatergroundwater (groundwater map). map). Since, Since, as as was was explained explained earl earlier,ier, no accurate no accurate data data were were available, available, esti- matesestimates were were used. used. Final values of the I factor (I scores) were obtainedobtained by summingsumming the Isv andand IgwdIgwd rasters, which gave the raster with unclassified unclassified values for the spatial distribution of factor I. After reclassification reclassification of the raster, the I map was created (Figure9 9),), showingshowing thethe impactimpact of infiltration infiltration on the intrinsic vulnerability of the Novljanska Žrnovnica and Bakar Bay catchment areas.

(a) (b)

Figure 9. InfiltrationInfiltration conditions (I) map—(a) Bakar Bay catchment; (b) Novljanska ŽrnovnicaŽrnovnica catchment.catchment.

The values values of of the the A A factor factor were were determined determined on on the the basis basis of ofsubfactor subfactor Ahg Ahg (hydroge- (hydro- Sustainability 2021, 13, x FOR PEER REVIEW 16 of 20 ologicalgeological description), description), which which defines defines the thestatic static conditions conditions in a inkarst a karst aquifer aquifer (Figure (Figure 10), and10), subfactorand subfactor Att (tracing Att (tracing tests), tests), which which defines defines the dynamic the dynamic conditions conditions in a karst in a karstaquifer aquifer (Fig- ure(Figure 11). 11For). Ahg For Ahgdata dataon lithological on lithological units units from fromthe Basic the BasicGeological Geological Map Mapof Croatia of Croatia were wereused, used,along alongwith hydrogeological with hydrogeological maps of maps the wider of the catchment wider catchment area and earlier area and studies earlier of studieshydrogeological of hydrogeological properties propertiesof carbonate of carbonaterocks in the rocks catchment. in the catchment. The values of subfactor Att (tracing tests) werewere obtained on the basis of the results ofof tracing tests performed inin thethe studystudy areaarea (Figure(Figure3 3).).

(a) (b) Figure 10. Aquifer conditions hydrogeological description (Ahg) raster—(a) Bakar Bay catchment; (b) Novljanska Žrnov- Figure 10. Aquifer conditions hydrogeological description (Ahg) raster—(a) Bakar Bay catchment; (b) Novljanska Žrnovnica nica catchment. catchment.

(a) (b) Figure 11. A map with the aquifer conditions tracing tests (Att) factor included—(a) Bakar Bay catchment; (b) Novljanska Žrnovnica catchment.

These procedures enabled us to produce the index value of the source (spring) intrin- sic vulnerability (SV index) and the resource intrinsic vulnerability of the aquifer as a whole (RV index). The values of the SV and RV indexes were derived from spatial analysis of all input maps defined by factors O, P, I and A using Equations (6) and (7). Figure 12 shows the SV map. In the Bakar Bay catchment area, the Dobrica spring was used as a reference spring in the analysis, it being the largest and most significant spring in the catchment area for the public water supply of the city of Rijeka. In the Novljanska Žrnovnica catchment area, the Novljanska Žrnovnica spring was used as a reference spring in the analysis, this also being the largest and most significant spring in the catchment area for the public water supply of the entire surrounding touristic riviera. Different parts of the catchment areas are marked to indicate their vulnerability, from very low vulnerability to extremely high vulnerability, highlighting where further detailed re- search would be needed to support any spatial interventions; the map can also be used as one of the bases for determining sanitary protection zones. The classified RV map (Figure 13) shows the intrinsic vulnerability of the karst aquifer in the catchment area. It is a good Sustainability 2021, 13, x FOR PEER REVIEW 16 of 20

used, along with hydrogeological maps of the wider catchment area and earlier studies of hydrogeological properties of carbonate rocks in the catchment. The values of subfactor Att (tracing tests) were obtained on the basis of the results of tracing tests performed in the study area (Figure 3).

Sustainability 2021(a, )13 , 3325 (b) 16 of 20 Figure 10. Aquifer conditions hydrogeological description (Ahg) raster—(a) Bakar Bay catchment; (b) Novljanska Žrnov- nica catchment.

(a) (b)

Figure 11. A map with the aquifer conditions tracing tests (Att) factor included—( a) Bakar Bay catchment; ( b) Novljanska Žrnovnica catchment.

These procedures enabledenabled usus toto produceproduce the the index index value value of of the the source source (spring) (spring) intrinsic intrin- sicvulnerability vulnerability (SV (SV index) index) and and the resourcethe resource intrinsic intrinsic vulnerability vulnerability of the of aquifer the aquifer as a whole as a whole(RV index). (RV index). The values The values of the of SV the and SV RV and indexes RV indexes were derivedwere derived from spatialfrom spatial analysis analysis of all ofinput all input maps maps defined defined by factors by factors O, P, IO, and P, AI and using A using Equations Equations (6) and (6) (7). and (7). Figure 12 showsshows thethe SV SV map. map. In In the the Bakar Baka Bayr Bay catchment catchment area, area, the Dobricathe Dobrica spring spring was wasused used as a referenceas a reference spring spring in the in analysis, the analysis, it being it thebeing largest the largest and most and significant most significant spring springin the catchmentin the catchment area for area the public for the water public supply water of supply the city of of the Rijeka. city In of the Rijeka. Novljanska In the NovljanskaŽrnovnica catchment Žrnovnica area, catchment the Novljanska area, the Žrnovnica Novljanska spring Žrnovnica was used spring as a reference was used spring as a referencein the analysis, spring this in alsothe analysis, being the this largest also andbeing most the significant largest and spring most insignificant the catchment spring area in thefor thecatchment public waterarea for supply the public of the water entire supply surrounding of the entire touristic surrounding riviera. Different touristic partsriviera. of Differentthe catchment parts areasof the are catchment marked areas to indicate are marked their vulnerability, to indicate their from vulnerability, very low vulnerability from very lowto extremely vulnerability high to vulnerability, extremely high highlighting vulnerability, where highlighting further detailed where further research detailed would re- be Sustainability 2021, 13, x FOR PEER REVIEW 17 of 20 searchneeded would to support be needed any spatial to support interventions; any spatial the interventions; map can also the be usedmap can as one also of be the used bases as onefor determiningof the bases for sanitary determining protection sanitary zones. prot Theection classified zones. RVThe map classified (Figure RV 13 map) shows (Figure the 13)intrinsic shows vulnerability the intrinsic of vulnerability the karst aquifer of the in kars the catchmentt aquifer in area. the catchment It is a good area. basis It for is a spatial good planning,basis for spatial as well planning, as for planning as well for as the for remediation planning for of potentialthe remediation and actual of potential pollutants and in theactual basin. pollutants in the basin.

(a) (b)

Figure 12.12. ClassifiedClassified source vulnerabilityvulnerability map—(map—(aa)) BakarBakar BayBay catchment;catchment; ((bb)) NovljanskaNovljanska ŽrnovnicaŽrnovnica catchment.catchment.

(a) (b) Figure 13. Classified resource vulnerability map—(a) Bakar Bay catchment; (b) Novljanska Žrnovnica catchment.

4. Conclusions The multiparameter KAVA methodology was developed as part of projects for the UNESCO-IHP in 2014 [41,44] and 2015 [45] examining the intrinsic vulnerability of the Novljanska Žrnovnica karstic spring catchment area and the Bakar Bay catchment area, located at the northern part of the Croatian seacoast. Although Novljanska Žrnovnica is a typical catchment area of the Dinaric karst in which almost all the karst phenomena and forms could be found with the development of the KAVA method, it was necessary to test the method in another catchment with slightly different characteristics. For this purpose, the Bakar Bay catchment was selected, a smaller karst catchment area situated adjacent to the Novljanska Žrnovnica catchment area. The verification of the KAVA methodology was carried out according to the existing KAVA methodology in the same way as the majority of the previous analyses on the Bakar Bay catchment area. In this way, initial vulnerability maps were obtained. By comparing the vulnerability maps and all subfactors and factors for both catchment areas, detailed multiparameter analysis of the obtained data was performed. Recommendations for the management of groundwater can be divided into four cat- egories: restrictions, active protection measures, remediation actions and dissemination. Restrictions can be developed according to the corresponding vulnerability classes, primarily for the locating of new (potentially polluting) human activities. In the case of karst aquifers, the protection criteria can be specified in accordance with the vulnerability Sustainability 2021, 13, x FOR PEER REVIEW 17 of 20

basis for spatial planning, as well as for planning for the remediation of potential and actual pollutants in the basin.

Sustainability 2021(a, 13) , 3325 (b) 17 of 20 Figure 12. Classified source vulnerability map—(a) Bakar Bay catchment; (b) Novljanska Žrnovnica catchment.

(a) (b)

Figure 13. ClassifiedClassified resource vulnerability map—(aa)) BakarBakar BayBay catchment;catchment; ((bb)) NovljanskaNovljanska ŽrnovnicaŽrnovnica catchment.catchment.

4. Conclusions 4. Conclusions The multiparameter KAVA methodology was developed as part of projects for the The multiparameter KAVA methodology was developed as part of projects for the UNESCO-IHP in 2014 [41,44] and 2015 [45] examining the intrinsic vulnerability of the UNESCO-IHP in 2014 [41,44] and 2015 [45] examining the intrinsic vulnerability of the Novljanska Žrnovnica karstic spring catchment area and the Bakar Bay catchment area, located at the northern partpart ofof thethe CroatianCroatian seacoast.seacoast. Although Novljanska ŽrnovnicaŽrnovnica isis aa typical catchment area of thethe DinaricDinaric karstkarst inin whichwhich almostalmost allall thethe karstkarst phenomenaphenomena andand forms could be found with the development of the KAVA method,method, itit waswas necessarynecessary toto testtest the method in another catchment with slightly different characteristics.characteristics. For this purpose, the Bakar Bay catchment was selected, a smaller karst catchment area situated adjacent toto the Novljanska Žrnovnica catchmentcatchment area.area. The verificationverification of the KAVA methodologymethodology waswas carriedcarried outout accordingaccording toto thethe existingexisting KAVA methodologymethodology in in thethe samesame wayway asas thethe majoritymajority ofof the previous analysesanalyses onon the Bakar Bay catchment area. In this way, initialinitial vulnerabilityvulnerability mapsmaps werewere obtained.obtained. ByBy comparingcomparing the vulnerability maps and allall subfactorssubfactors andand factorsfactors forfor bothboth catchmentcatchment areas,areas, detaileddetailed multiparameter analysis of the obtained datadata waswas performed.performed. Recommendations for for the the management management of of gr groundwateroundwater can can be bedivided divided into into four four cat- categories:egories: restrictions, restrictions, active active protection protection measures, measures, remediation remediation actions actions and and dissemination. dissemination. Restrictions can be developed according to the correspondingcorresponding vulnerability classes, primarily for the locatinglocating ofof newnew (potentially(potentially polluting)polluting) humanhuman activities.activities. In the casecase ofof karst aquifers, the protection criteria can be specifiedspecified in accordance with the vulnerability class determined by the RV index. In the case of karst springs or groundwater intakes, the protection criteria can be specified in accordance with the vulnerability class determined by the SV index. Active protection measures may include frequent water quality monitoring in the very high and extreme vulnerability karst areas, if it is possible with the morphology of the terrain. They may also include actions to improve the situation of water, such as construction of public water supply and wastewater disposal systems, introduction of clean production, ecological farming and installation of tanks for hazardous and polluting substances with additional multiple protection. Remediation actions primarily refer to existing human activities that may threaten the good condition of groundwater in a certain karst area. A necessary remediation action program may include a list of all pollutants in the karst area, a list of priority remediation procedures, etc. Dissemination activities refer to public participation, at a certain scale; this is always welcome and there are very good reasons why such activities should be organized, espe- cially at a local scale. Local public participation meetings could be held, organized either by the competent authority or by local water managers. Sustainability 2021, 13, 3325 18 of 20

The KAVA method was developed because only a very small number of the methods previously developed can be used without significant limitations in determining the intrin- sic vulnerability of karst aquifers, such as aquifers in the Dinaric karst. Due to the very similar characteristics of karst aquifers, this method can be used in the wider Mediterranean area as well as in Croatia, which was the intention of the UNESCO projects within which this method was developed. The results of the vulnerability mapping can be used as a tool—as additional information— in complex hydrogeological research work in a particular catchment area and in ground- water protection projects.

Author Contributions: Conceptualization, R.B., H.M. and B.B.; methodology, R.B. and H.M.; formal analysis, R.B., H.M. and J.L.; investigation, R.B., H.M., B.B. and J.L.; data curation, R.B.; writing— original draft preparation, R.B. and H.M.; writing—review and editing, R.B., H.M., B.B. and J.L.; visualization, R.B. and H.M. All authors have read and agreed to the published version of the manuscript. Funding: The work was funded by the UNESCO-IHP through the Global Environment Facility (GEF)—UN Environment Programme (UNEP)—Mediterranean Action Plan (MAP) Strategic Part- nership for the Mediterranean Sea Large Marine Ecosystem (MedPartnership Project)—UNESCO- International Hydrological Programme (IHP) sub-component 1.1 on “Management of coastal aquifers and groundwater”, and by the Primorsko-goranska County of the Republic of Croatia (co-financing of the research). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.

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