Assessment of the quality and possibility of groundwater use for irigation in the northern part of the Fruška Gora vineyard using the irrigation water quality indices

 

by Tanja Petrović Pantić ¹, Marina Magazinović ^1,*, Nataša Obradović ¹, Katarina Atanasković Samolov ¹, Milan Tomić ¹

¹  Geological Survey of Serbia

*  Corresponding author: marina.magazinovic@gzs,gov.rs

Abstract

Serbian viticulture has grown significantly over the past fifteen years. This study analyzes irrigation groundwater quality in the northern slopes of Fruška Gora. Twenty samples were collected from aquifers in Quaternary, Miocene and Pliocene sediments, along with springs in Paleozoic and Cretaceous formations and one well in Triassic sediments. Most waters were classified as HCO₃-Ca-Mg type. Irrigation suitability was evaluated using indices: SAR, Na%, PI, PS, MH, KI, IWQI. All 20 samples were excellent or suitable for irrigation based on SAR, Na%, and KI; most met PS and MH criteria, and PI rated all moderately suitable. IWQI classified samples as very good and good. GIS-based IDW maps visualized water quality, providing insight into groundwater suitability for northern Fruška Gora irrigation.  

Keywords

ground water, irrigation, water quality, viticulture, Serbia

Note:

Papers published in this special issue of the European Geologist journal have undergone a thorough peer-review process but have not been copy-edited. Authors bear full responsibility for the linguistic accuracy of their contributions.

This work is licensed under a Creative Commons Attribution 4.0 International License.

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1. Introduction

Water is essential for all life and human activity and access to freshwater in sufficient amounts and of suitable quality is a precondition to achieving sustainable development (Srebotnjak et al, 2012). In recent decades, groundwater quality has been significantly degraded and increasingly threatened due to various factors, including rapid population growth, industrial expansion, and the impacts of climate change. Good water quality is vital for sustainable agriculture, as pollution water can damage aquatic ecosystems and reduce agricultural productivity (Syafrudin et al, 2021). Globally, groundwater is most widely used for irrigation, followed by drinking water, and then industrial purposes. Groundwater suitability for irrigation purposes are estimated based on the geochemical aspects of the groundwater as every groundwater system has a distinct chemical composition, and its change depends on many factors like temperature, mineral dissolution, rock–water interaction, soil–water inter action, interaction time, and anthropogenic activities (Subba Rao, 2002). Irrigation water quality is often overlooked as a potential source of problems in plant growth, but it is actually crucial for successful cultivation. The properties of water quality can be divided into three categories: physical, biological, and chemical (Goldammer, 2018). Physical properties include suspended solids and temperature. These properties can lead to potential problems as they may cause clogging of irrigation nozzles and cause abrasion of irrigation equipment. Biological properties include the presence of bacteria, plant pathogens, or algae. The chemical properties of irrigation water are the most commonly tested properties because they can cause significant problems in production, and the information obtained from the test can be immediately used in crop management strategies. From the perspective of grape growers, the most critical chemical water quality properties are soluble salts, sodium and chloride concentration and pH. In some cases, elements such as iron, boron, and manganese are also considered critical parameters (Goldammer, 2018).

Over the past fifteen years, Serbian viticulture and winemaking have exhibited a significant growth trend, with an increasing focus on autochthonous grape varieties. Recognized as a strategic sector for national economic development, viticulture has been supported by the Wine Sector Development Strategy (2021–2030). According to the reionization of the viticultural geographical production areas of Serbia [5], the Fruška Gora vineyard belongs to the Srem region and stretches on the slopes of the Fruška Gora facing the Danube (northern part) and the Sava (southern part). This paper analyzes the potential use and quality of groundwater for irrigation purposes in viticultural area of the northern slopes of Fruška Gora. The analysis of chemical parameters and types of groundwater in the research area had the following main objectives: (1) to assess the suitability of groundwater for irrigation, (2) to generate maps using GIS in order to visualize water quality parameters across the research area, and (3) to calculate various irrigation water quality indices: Sodium Adsorption Ratio (SAR), Sodium Percentage (Na%), Permeability Index (PI), Potential Salinity (PS), Magnesium Hazard (MH), Kelly’s Index (KI), and Irrigation Water Quality Index (IWQI). Based on a review of the literature, none of these methods have been previously applied in this region or its surrounding areas. Based on a review of the literature, none of these methods have been previously applied in this region or its surrounding areas.

2. Materials and Methods

Groundwater sampling was carried out during the implementation of hydrogeological investigations for the purpose of creating the basic hydrogeological maps at a scale of 1:100,000, sheet Novi Sad (Petrović Pantić and Kostić, 2021) and sheet Bačka Palanka (Petrović Pantić and Petrović, 2025) . Groundwater samples were taken during the summer and autumn. The chemical quality of groundwater was analyzed by processing 20 samples (16 springs, 3 dug wells, and 1 drilled well) (table 1).

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Table 1: Location, geological and hydrogeological information of sample points.

Sample point	Locality	X (o)	Y (o)	Z (m)	Type	Lithological information	Age	Q (l/s)	Depth (m)	Water level (m)
1	Stepin Do	19.6824191	45.207248	128	dug well	sandstones, sands, and marls	Pl12		4,53	2,94
2	Lug	19.5466053	45.1778462	199	dug well	loess	l		12,95	11,52
3	Sviloš	19.5875714	45.1712866	143	dug well	conglomerates, sandstones, limestones, clays, and tuffs	1M22		6,14	5,15
4	Klen	19.6841178	45.1992675	174	spring	paludine layers: clays, sands, and coal	Pl2,3	0,08
5	Kosarlija	19.5360834	45.1708728	168	spring	conglomerates, sandstones, limestones, clays, and tuffs	1M22	0,04
6	Duga Međa-Koruška	19.5699139	45.2053439	116	spring	Second river terrace	t2	0,32
7	Klenovačka česma	19.6014736	45.1890954	203	spring	paludine layers: clays, sands, and coal	Pl2,3	0,01
8	Stari Rakovac	19.7713905	45.1811422	189	spring	conglomerates, sandstones, limestones, clays, and tuffs	1M22	0,18
9	Sr.Kamenica	19.8406808	45.2216314	87	spring	alluvium: sands, silty clays, and gravels facies	alp	0,19
10	Čukale	19.819671	45.1858529	272	spring	conglomerates, sandstones, limestones, clays, and tuffs	1M22	0,01
11	Ladna	19.5992991	45.1557818	201	spring	serpentinite	Se	0,03
12	Plava česma	19.5435726	45.1860146	152	spring	paludine layers: clays, sands, and coal	Pl23	0,04
13	Zvečan	19.8076094	45.1717075	171	spring	flysch clays, sandstones, conglomerates, limestones, and marls	K23	0,28
14	Beočin	19.7232184	45.2072786	92	spring	proluvium: gravels, sands, and silty clays	pr	0,09
15	Rakovac	19.771391	45.181142	189	spring	conglomerates, sandstones, limestones, clays, and tuffs	1M22	0,18
16	Kišanj	19.7925546	45.1966477	143	spring	sands, clays, marls, gravels, conglomerates, and others	M31	0,07
17	Vizić, Dolina	19.4491426	45.1727229	201	spring	loess	l	0,05
18	Neštin, Belilo	19.448647	45.2247387	140	spring	sands, clays	a	0,76
19	Vizić	19.4516436	45.1663406	206	spring	loess /serpentinite	l/Se	0,066
20	Ledinci	19.8064181	45.2099226	94	well	peščari, konglomerati, glinci i glinoviti laporci	T1		80

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Groundwater sampling locations were measured in the field with the help of Global Positioning System (GPS). Coordinates (X, Y, Z) of each well location are recorded in the form of latitude, longitude, and altitude. Based on the GPS locations, all the monitoring points were marked in the georeferenced map. The Laboratory of the Geological Survey of Serbia carried out laboratory testing and determination of the physicochemical parameters of groundwater samples -. pH using a multimeter instrument (SensoDirect 150; LovibondR Tintometer Group, Amesbury, UK). Electroconductivity (EC) was measured by the conductometric method with a multi-parameter analyzer, while TDS was calculated based on all measured ionic components. The concentration of Na⁺, K⁺, Ca²⁺ and Mg²⁺ was measured by the atomic absorption spectrophotometry, flammable technique (PerkinElmer 4000 thermomechanical analysis system; PerkinElmer, Waltham, MA, USA). The concentrations of HCO₃^– and Cl^–, were measured by the volumetric method, and the concentrations of SO₄^2-, and NO₃^– were analyzed by spectrophotometry using a PerkinElmer UV/VIS Lambda 15 spectrometer. The concentrations of Fe²⁺ and B were determined by inductively coupled plasma-atomic emission spectrometry (ICP-AES) using SPECTROBLUE spectrometer (SPECTRO Analytical Instruments GmbH, Kleve, Germany). The results of these investigations were utilized as a basis for the preparation of this study

To ensure the reliability and high quality of the analytical data, a strict QA/QC protocol was implemented. The accuracy of the major ion analyses was validated using the ionic charge balance error (CBE). For all water samples, the CBE was found to range from -0.72 to 1.61, or within the internationally accepted limit of ±5%, indicating that the analyses were chemically consistent and that no major ions were overlooked.

To assess water quality for agricultural use, various irrigation quality indices were calculated, including Sodium Adsorption Ratio (SAR), Sodium Percentage (Na%), Permeability Index (PI), Potential Salinity (PS), Magnesium Hazard (MH), and Kelly’s Index (KI). These indices were calculated using the equations provided in Table 2, according to recognized methods for assessing groundwater quality.

This study also evaluates groundwater quality through the Irrigation Water Quality Index (IWQI). The spatial variations of different irrigation water quality parameters were plotted using GIS.  The data was visualized using GIS zoning maps for each parameter.

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Table 2: Calculation methods for various groundwater quality indices for irrigation.

Indices	Equations	Reference
SAR	SAR=Na/√((Ca+Mg)/2)	Richards (1954)
Na %	Na(%)=Na/(Ca+Mg+Na+K)x100	Eaton (1950)
MH	MH(%)=Mg/(Ca+Mg)x100	Raghaunth (1989)
KI	KI=Na/(Ca+Mg)	Kelly (1963)
PS	PS=Cl+0,5xSO4	Doneen (1964)
PI	PI=(Na+√HCO3)/(Ca+Mg+Na)x100	Doneen (1964)

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3. Results

3.1. Study area

The research area is located in the northern part of Serbia, within the AP Vojvodina, in the Srem region. The Srem vineyard region lies on the slopes of Fruška Gora, facing the rivers Danube (to the north) and Sava (to the south), excluding the area of the National Park (figure 1).

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Viticulture and wine production in Srem and Fruška Gora are among the oldest in Europe. Due to its favorable geographic position, soil quality, proximity to the Danube, microclimate, and sunlight reflection from the Danube’s surface, grapes here ripen earlier and contain one to two percent more sugar compared to other viticultural regions in Vojvodina (Kalenjuk, 2013). The entire Srem region covers an area of 86,715.92 hectares, of which 2,140.96 hectares are under vineyards. The research area includes the northern parts of the Fruška Gora vineyard region and extends over 16,019 hectares

. Elevation gradually decreases from the slopes of Fruška Gora towards the edges of the region, ranging between 70 and 400 meters (figure 2a). This region is mainly characterized by moderately steep to gentle slopes (figure 2b), where the vineyards are located. The Fruška Gora area lies on the border of the temperate continental climate zone, and due to climatic changes along the elevation gradient and the influence of forest cover, the climate here has subcontinental characteristics. The average annual temperature is 11.2°C. As for the spatial distribution of annual precipitation the amount of precipitation increases proportionally with elevation. The difference in annual precipitation between the highest and lowest areas is 200 mm (Iriški Venac: 782 mm, Sremski Karlovci: 586 mm).

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3.2. Geology and hidrogeology

The geological structure of the terrain consists of diverse geological formations, varying both in age and lithological composition (Figure 3). The oldest rocks in the geological structure are represented by serpentinites (Se) and schists (Sazkt). The Triassic (T₂) is developed in the facies of sandstones, claystones, limestones, and dolomites. Upper Cretaceous sediments (K₂³) lie discordantly and are represented by breccias, conglomerates, sandstones, reef limestones, and marls. Latites (τα), probably of Oligo-Miocene age, are intruded into the Cretaceous sediments. Dacite-andesites (αq) occur on the southern side of Fruška Gora, cutting through serpentinites and Triassic sediments.

Tertiary formations also make up a significant part of the geological structure of Fruška Gora and its margins. These include the Lower, Middle, and Upper Miocene, as well as almost the entire Pliocene. The sediments of Lower Miocene (M₁²) are represented by breccias, conglomerates, sandstones, clays, claystones, and coal. The Middle Miocene is represented by conglomerates, sandstones, tuffs, and marls in the lower part (Lower Tortonian, ₁M₂²), and by limestones, sandstones, and marls in the upper part (Upper Tortonian, ₂M₂²). The Upper Miocene is represented by brackish Lower Sarmatian (M₃¹) in facies of sandstones, limestones, marls, clays, and by the caspibrackish Pannonian in facies of white marls and clays. Pannonian sediments – marls, marly clays, clayey marls, and sandstones (M₃²) – occur on the northern edge of Fruška Gora. The Upper Pontian (Pl₁²) is represented by shallow-water sediments with sandstones, gravels, sands, and clays containing lignite. Middle and Upper Pliocene are represented by freshwater “paludinian layers” (Pl_2,3). The Middle Pliocene or Lower Paludinian layers locally lie transgressively and discordantly over Sarmatian and Pannonian deposits, and where they lie over the Upper Pontian, the transition is gradual, making it difficult to clearly define the boundary between the strata.

Within the Quaternary formations, sediments of Pleistocene and Holocene age have been identified. In the Pleistocene, diluvial-proluvial sediments (dpr) are present, along with sediments of the Danube river terraces (t), and formations of continental loess (l). The Holocene includes sediments that form the wide alluvial plains (Čičulić-Trifunović and Rakić, 1977; Dimitrijević et al, 1985).

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The tectonics of the studied area are very complex and diverse. The entire Fruška Gora horst, along with all the formations that comprise it, was affected by both plicative (folding) and disjunctive (faulting) deformations. At the same time, there was intense magmatic and volcanic activity, during which masses of ultrabasic rocks, latites, and dacite-andesites were formed.

In the central parts of Fruška Gora, there are carbonate rocks of Triassic limestones with karst-type of aquifers, as well as serpentinites and other magmatic rocks (latites, dacites) with fracture aquifers. In the youngest Quaternary aquifer environments (pr, d, dpr, t, alp), an intergranular aquifer with an unconfined water table has formed. Proluvial, diluvial, and diluvio-proluvial sediments have low permeability and very low transmissivity, so they do not have significant hydrogeological importance. Terrace and alluvial deposits are characterized by moderate (older river terraces) to good (alluvial sediments and the youngest river terrace) hydrogeological properties. Within Tertiary-age deposits, complex and interconnected aquifers have formed, with both unconfined and confined water levels.

3.3. Groundwater quality

Table 3 presents the results of chemical analyses conducted on 20 groundwater samples. Based on the content of dominant anions and cations, the analyzed waters belong to the HCO₃-Ca-Mg type (figure 4).

The total dissolved solids (TDS) concentrations in the groundwater samples range from 427.1 to 953.7 mg/l. The effect of total salt content makes it more difficult for growing plants to take up water from the soil (Zhang, 2017). It is clear that collected groundwater samples were under the permissible limit. The pH values of the groundwater samples range from 6.87 to 7.83, indicating that the groundwater in this area is slightly acidic to slightly alkaline. The desired pH values for irrigation water range from 6.5 to 8.4. Values outside this normal range can affect nutrient availability, cause corrosion of irrigation equipment, and reduce the effectiveness of pesticides. Over time, the pH value of water can also influence soil pH (Schiavon and Moore, 2021). The EC values range from 600 to 900 μS/cm with average value of 707.5 μS/cm. Water with high EC values is toxic to plants and poses a salinity hazard. According to the guidelines for interpreting laboratory data on water suitability for grapes (Ayers and Westcot, 1986), for values below 1000 μS/cm, there is no restriction on use.

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Table 3: Water quality parameters for evaluating the suitability of groundwater for irrigation practices.

Sample	Parameters	EC	TDS	pH	Ca	Mg	Na	K	HCO3	Cl	SO4	B	NO3	Fe	Mn
	Unit	µS/cm	mg/l	–	mg/l	mg/l	mg/l	mg/l	mg/l	mg/l	mg/l	mg/l	mg/l	mg/l	mg/l
1	SD-1	630	839,8	7,06	130,3	48,6	6,4	0	555	12,8	64,3	0	6,64	0,07	<0,02
2	Lu-1	660	682,7	7,13	108,6	35,2	9,8	0,4	463,6	17,5	20,3	0	7,27	0,14	<0,02
3	Sv-1	600	629,5	7,56	96,4	31,8	11,2	0,2	460,6	9,9	0	0,76	10,1	1,26	0,04
4	BB-1	600	836,4	7,05	135,9	45,6	5,7	0	518,4	7,1	107,5	0	5,07	<0,05	<0,02
5	Ko-1	720	752,1	7,08	119,8	39,8	5,6	1	500,2	14,8	39,2	0	10,4	0,06	<0,02
6	Sv-2	900	870,5	7,51	124,2	39,7	36	13,5	539,8	62	33	0	3,9	0,07	<0,02
7	Kč-1	600	590,4	7,83	93,6	30,1	5	0,2	393,4	17	20,8	0	6,92	/	0,1
8	Ra-1	760	834,1	7,12	105,4	58,6	16,7	3,8	533,8	57,4	32,8	0	0,58	0,07	<0,02
9	SKa-1	660	793,8	7,17	111,4	52,4	22,1	0,8	482	74,4	33,1	0	5,42	0,16	<0,02
10	Pop-1	610	581	6,92	85	33,8	6,1	0,3	427	10,6	3,8	0,2	0,64	0,09	<0,02
11	La-1	780	953,7	7,12	42,5	124	2,1	0,6	744,2	11,3	1	0,22	0,6	<0,05	0,01
12	Pč-2	780	642,4	6,95	96,8	38,6	9,2	0,2	439,2	29,8	5	2	8,74	<0,05	<0,02
13	Zv-2	600	472,1	6,99	62,2	29,8	10,2	2,8	335,5	9,6	8,7	0,33	0,23	<0,05	<0,02
14	Be-2	860	887,4	7,21	130,9	54,2	18,6	1,1	500,2	35,5	132	1,2	1,91	<0,05	<0,02
15	Ra-1	640	789,6	7,02	123,2	35,7	38,2	1,5	405,6	99,3	71	0	1,14	<0,05	<0,02
16	Ša-1	600	858,4	7,01	139,7	46,9	6,1	0,2	534,4	8,5	103,7	0	1,49	<0,05	<0,02
17	V-82	890	919,5	7,22	118	65,6	19,8	0,1	652,7	21,8	37,2	<0,26	1,66	<0,002	0,01
18	NsB-1	700	608,2	7,03	82,4	32,9	22,1	1,1	439,2	8,1	16,3	<0,26	3,08	<0,002	<0,001
19	VzC	720	657,7	7,53	45,7	57,2	33,2	0,1	500,2	4,2	9,9	<0,26	1,72	<0,002	<0,001
20	SVP	840	754	6,87	106,2	41,7	23,6	3,2	500,2	47,9	8,4	0,45	4,75	<0,05	<0,02
Min		600	472,1	6,87	42,5	29,8	2,1	0	335,5	4,2	0	0	0,23	0,06	0,01
Max		900	953,7	7,83	139,7	124	38,2	13,5	744,2	99,3	132	2	10,4	1,26	0,1
Av		707,5	747,6	7,17	102,9	47,1	15,4	1,5	496,3	27,9	37,4	0,3	4,11	0,24	0,04

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The concentrations of sodium (Na⁺) in the collected groundwaters ranged between 2.1 and 38.2 mg/L. Sodium can become toxic to many plants when present in high concentrations. Sodium toxicity typically appears as leaf burn along the edges of older leaves. Another serious issue related to the presence of sodium in irrigation water is its dispersive effect on clay soils. In soils with significant clay content, sodium causes the separation of clay particles, which can lead to the deterioration of soil structure and reduced permeability. Sodicity hazard is measured by SAR or by sodium percentage. (Zhang, 2017). The concentrations of HCO₃⁻ in the collected groundwater samples ranged from 335.5 to 744.2 mg/l and Cl⁻ ranged from 7.1 to 99.3 mg/L. Bicarbonate (HCO₃) in water applied by overhead sprinklers may cause white deposits on fruit and leaves which reduces market acceptability, but is not toxic to the plant. Excess chloride may lead to leaf injury in grapevines and a resultant reduction in vine performance (Goldammer, 2018). Boron values for 20 samples are mostly below 1 mg/L, indicating no restrictions on water use. However, one sample with a boron concentration of 1.2 mg/L shows a slight to moderate degree of restriction on use for grape irrigation. Grapevines are also quite sensitive to boron. Boron injury is typically drying, yellowing and spotting along the tips and edges of older leaves (Goldammer, 2018). Sensitive plants, such as grapes experience toxic effects when the boron concentration in the soil reaches 1 ppm (Zhang, 2017). Iron may be present in a soluble (ferrous) form, which may create emitter clogging problems. Like iron, manganese in solution may precipitate out as a result of chemical or biological activity, forming sediment that clogs emitters and other system components (Goldammer, 2018). Based on the manganese content (<0.2 mg/l) and iron content (<5 mg/l) (Ayers and Wescot, 1985), all water samples are adequate for irrigation.

4. Discussion

Sodium Adsorption Ratio (SAR) : High sodium concentrations in irrigation water can reduce soil permeability and negatively affect soil structure. When the sodium level is high relative to calcium and magnesium, it disrupts soil aggregation, leading to decreased water infiltration and reduced permeability. The water samples were plotted on diagram, which illustrates the relationship between Electrical Conductivity (EC) and the Sodium Adsorption Ratio (SAR), and classifies water quality into various categories (Figure 5a). 13 water samples were classified as C2-S1 (medium salinity–low SAR), and 7 sample was classified as C3-S1 (high salinity-low SAR).

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To mitigate salinity hazard, especially for water classified in the C3-S1 category, the use of drip irrigation is recommended over sprinkler systems to prevent foliar salt damage and ensure efficient salt leaching. Even with low-sodium (S1) water, the cumulative effect of irrigation, especially in hard-rock terrains, can exacerbate osmotic stress on grapevines. Therefore, drip systems are preferred as they allow for precise water application, maintaining soil salinity below critical agronomic thresholds.

Percentage of sodium (Na%) : This indicator is crucial for assessing the potential impact of irrigation water on soil structure and permeability. High sodium concentrations can degrade soil structure, adversely affecting water infiltration and aeration (Maliki et al, 2024). The calculation of Na% of the groundwater samples in the study area shows values between 0.7 and 17.1% so the groundwater samples are excellent for irrigation compared to the percentage of Na. According to the Wilcox classification (1955) based on the values of Na% and electrical conductivity (EC) (Figure 5b), all samples fell into the good and excellent class.

Magnesium Hazard Ratio (MH) : As magnesium normally exchanges with sodium in the irrigated soil, magnesium hazard is the most important irrigation water index (Keesari et al, 2016). A high MAR can indicate water quality that might adversely affect soil structure and plant yields. In the study area the magnesium hazard values of 18 samples fall in the range of 32,3 to 47,8 %. In the study area, two samples showed MH ratio above 50 %. The elevated magnesium content in these two samples is expected, given the lithological environment (serpentinites) within which the groundwater is formed. The evaluation illustrates that >50% MH samples can cause adverse effect on the agricultural yield.

Kelly’s Index (KI) : Kelly’s index is another important parameter used to evaluate groundwater quality for irrigation purposes. When the concentration of sodium in groundwater is higher than that of calcium and magnesium, it can disrupt the ionic balance in the soil, leading to increased soil salinity. Rainfall and the leaching of Na⁺ from rock into water have caused the bulk of the groundwater samples to fall into a suitable category. Because of the dilution process, the average groundwater Kelly’s index value falls below an appropriate range (Tejashvini et al, 2024). Based on this index, all groundwater samples from are found suitable for the irrigation.

Potential Salinity (PS): The PS uses the concentration of Cl and half of the SO₄ concentration to assess if groundwater is suitable for use in irrigation.  The suitability of water for irrigation is not dependent on soluble salts. Because, the low solubility salts precipitate in the soil and accumulate with successive irrigation, the concentration of highly soluble salts increases the soil salinity (Doneen, 1964). According to the PS, the study area’s 19 groundwater samples were all suitable for irrigation, except one sample (sample 15), which, with a value of 3.5, falls into the category unsuitable for irrigation.

Permeability Index (PI) : The Permeability Index is used to evaluate the impact of irrigation water on soil permeability (Doneen, 1964). It takes into account the concentrations of various ions—primarily sodium, calcium, magnesium, and bicarbonate—to estimate their long-term influence on the soil’s ability to transmit water. Elevated or imbalanced ion levels can lead to reduced permeability, ultimately affecting soil structure and irrigation efficiency. According to PI value, all water samples was found as moderate for irrigation.

Irrigation Water Quality Index (IWQI) : The assessment of groundwater for irrigation purposes using the Irrigation Water Quality Index (IWQI) involves the application of individual chemical indicators or a combination of multiple indices (Hamdy Eid et al, 2023). Irrigation Water Quality Index (IWQI) is calculated based on variables such as Electrical Conductivity (EC), Sodium Adsorption Ratio (SAR), Sodium (Na⁺), Chloride (Cl⁻), and Bicarbonate (HCO₃⁻), according to the following equation:  where Wi is the calculated weight of every variable (table 4, M’nassri et al, 2022), and Qi is the quality measurement value based on the permissible limits (Table 5, Batarseh  et al, 2021).

Q_i = Q_max –([(x_ij+x_inf)xQ_iamp]/x_amp)

where X_ij is each parameter’s observed value, X_inf is the value that correspond to the lower limit of the class, Q_imap is the class amplitude, and X_amp is the class amplitude to which the parameter belongs.  The resulting IWQI values varied from 61 to 73, and the IWQI available classification (Zahedi, 2017) revealed that a groundwater samples are very good and good for irrigation.

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Table 4: Weights for the IWQI parameters.

Parameters	EC	SAR	Na+	Cl–	HCO3–
Wi	0.211	0.189	0.204	0.194	0.202

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Table 5: Irrigation water quality parameters and their proposed limiting values.

Qi	EC	SAR	Na+	Cl–	HCO3–
85-100	200≤EC<750	SAR<3	2≤Na<3	Cl<4	1≤HCO3<1.5
60-85	750≤EC<1500	3≤SAR<6	3≤Na<6	4≤Cl<7	1.5≤HCO3<4.5
35-60	1500≤EC<3000	6≤SAR<12	6≤Na<9	7≤Cl<10	4.5≤HCO3<8.5
0-35	200>EC≥3000	SAR≥12	2>Na≥9	Cl≥10	1>HCO3 ≥8.5

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The results of all parametars with minimum and maximum values, with the classification of the collected groundwater samples according to irrigation parametars are presented in the table 6.

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Table 6: Classification of the collected groundwater samples.

Parameter	Min	Max	Suitability for Irrigation	Groundwater Samples Suitability
SAR	0.04	0.78	<10 Excellent 10-18 Good 18-26 Fair >26 Poor	100% Excellent
Na%	0.73	17.12	<20 Excellent 20-40 Good 40-60 Permissible 60-80 Doubtful >80 Unsuitable	100% Excellent
MH	32.33	82.79	<50 Suitable >50 Unsuitable	90% Suitable 10% Unsuitable
KI	0.01	0.21	<1 Suitable >1 Unsuitable	100% Suitable
PS	0.22	3.54	<3 Suitable >3 Unsuitable	95% Suitable 5% Unsuitable
PI	28.87	51.09	>75 Safe 25-75Moderate <25 Unsafe	100% Moderate
IWQI	61	73	>85 Excellent 70-85 Very good 55-70 Good 40-55Satisfactory <40 Unsuitable	70% Good 30% Very good

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The groundwater quality in the study area was visualized and evaluated for irrigation purposes using GIS-based zoning maps for the previously mentioned parameters (figure 7). ArcMap GIS software was applied to accomplish the hydrogeological work. Due to the limited sample size (n=20), Cross-Validation was performed to evaluate the reliability of the IDW interpolation and assess spatial uncertainty. IDW a suitable deterministic alternative for smaller sample sizes where complex statistical assumptions cannot be met (Burrough and McDonnell, 1998). In this way, statistical parameters are calculated that indicate the bias and accuracy of the model. Using this method, two key parameters are defined: ME (Mean Error) – the average difference between predicted and observed values, and RMSE (Root Mean Square Error) – which measures the average magnitude of prediction errors. Analysis of the cross-validation results led to the following conclusions: excellent models (ME close to zero, low RMSE): KI, SAR, and PS models are unbiased and precise, suitable for final interpolation and accurate spatial analyses and moderate models (ME close to zero, higher RMSE): IWQI, Na%, PI, and MH models are unbiased, but their predictions are not highly precise. Cross-validation analysis shows that the systematic error is minimal for all models (ME close to zero), indicating that bias is not a problem. The quality of the models is determined by the accuracy of predictions, i.e., the RMSE.

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5. Conclusions

Knowledge and assessment of irrigation water quality are key tools for effective water resource management. This study analyzed the irrigation water quality of the northern slopes of Fruška Gora based on 20 water samples from aquifers within Quaternary, Miocene, and Pliocene sediments, except two spring samples formed within the Paleozoic serpentine and Cretaceous flysch and one drilled well that captures the Triassic sediments. . Based on the content of dominant anions and cations, the analyzed waters belong to the HCO₃-Ca-Mg type. To assess water quality for agricultural use, various irrigation quality indices were calculated, including Sodium Adsorption Ratio (SAR), Sodium Percentage (Na%), Permeability Index (PI), Potential Salinity (PS), Magnesium Hazard (MH), and Kelly’s Index (KI). This study also evaluates groundwater quality through the Irrigation Water Quality Index (IWQI). Results showed that all 20 samples were classified as excellent or suitable for irrigation based on SAR, Na%, and KI values. Additionally, 95% of samples met PS suitability criteria, while 90% were acceptable based on MH. Aquifer formed in the serpentinized lithological units of Fruška Gora should not be considered a suitable source for irrigation, owing to the elevated magnesium concentrations in its groundwater, which are genetically inherent to this lithological environment.

According to PI, all samples were classified as moderately suitable. The Irrigation Water Quality Index (IWQI) determined that 30% of samples were very good and 70% good for irrigation purposes. Using Geographic Information System (GIS) tools and inverse distance weighting (IDW) spatial interpolation, maps were generated to visualize water quality parameters across the research area. The obtained results provide valuable insight into groundwater suitability for irrigation of the northern part of Fruška Gora.

Comprehensive hydrogeological investigations are imperative to quantify the aquifer’s characteristics and to delineate the available groundwater resources necessary to support such usage. Furthermore, beyond the assessment of groundwater quality for irrigation purposes, it is recommended to implement seasonal tracking of both Electrical Conductivity (EC) and soil salinity. This will allow managers to adjust irrigation volumes and fertilization programs dynamically, ensuring that the vineyard’s long-term productivity is not compromised by gradual salt accumulation.  

Author Contributions: Conceptualization, T.P.P. and M.M..; methodology, T.P.P. and M.M.; validation, K.A.S.and M.T..; formal analysis, N.O.; investigation, T.P.P. and M.T..; writing—original draft preparation, M.M..; writing—review and editing, T.P.P.; visualization, N.O., K.A.S. and M.T.; supervision, T.P.P., K.A.S, project administration, T.P.P. and M.M. All authors have read and agreed to the published version of the manuscript.

Funding: This paper is a result of the project “Basic hydrogeological map 1:100.000” supported by the Government of the Republic of Serbia, Ministry of Mining and Energy, and used for participation in GSEU Project funded from the European Union’s Horizon EU Program under Grant Agreement 101075609 – GSEU – HORIZON-CL5-2021-D3-02

Acknowledgments: The authors would like to thank to colleagues from Geological Survey of Serbia

Conflicts of Interest: The authors declare that there is no conflict of interest.

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This article has been published in European Geologist journal 60 – 5th IPGC Special Edition 1