Groundwater contamination apportionment in Beida‑Bordj rural territory, northeast Algeria, using the nitrate pollution index (NPI) and groundwater pollution index (GPI)

Most of the time, too much use of artificial fertilizers in rural areas, especially nitrogen fertilizers used to make crops grow faster, causes nitrate levels in groundwater to rise. In the Beida-Bordj area in northeast Algeria, groundwater is the main source of water for agriculture and drinking. Because of this, the quality of groundwater is very important. Therefore, nitrogen pollution in groundwater, which is one of the most important environmental problems, needs to be looked into. Therefore, evaluating groundwater contamination to protect human health was the primary focus of this investigation. As a result, 111 samples were taken in May 2022 from wells in different parts of the study area for physical and chemical research. Therefore, the nitrogen pollution index (NPI) and the groundwater pollution index (GPI) have been used to measure how clean groundwater is. The results show that the groundwater in the area that was tested is alkaline. Based on their average values, the abundance of cations and anions is as follows: Ca 2+ > Na + > Mg 2+ > K + ; and SO 42− > Cl − > HCO 3− > NO 3− , in that order. The estimated NPIs ranged from – 1 to 4.5, with 0.92 being the average. Overall, the NPI data showed that only 25% of groundwater samples were clean, and the other 75% were dirty. The GPI readings ranged from 6.3 to 0.4, with an average of 1.2. This means that only 54% of the samples of groundwater from the study area were safe to drink. According to analyses of water quality parameters like SAR, SSP, RSC, PI, MH, and KR, the majority of groundwater samples from the research region are suitable for irrigation, because they fall into the "good" or "suitable" quality classes. This study's findings offer some intriguing suggestions for lowering pollution levels and bolstering groundwater management strategies for the future.


Introduction
To sustain human existence and advance the economy, water is essential (Ostad-Ali-Askari 2022a; Zhang et al. 2019;He et al. 2019;Khosravi et al. 2018;Yang et al. 2018;Huang et al. 2018;Gu et al. 2013). Because it is essential to life, this miraculous gift from God must be protected (Al-Hamdany et al. 2020). Therefore, there is a significant cause for alarm about groundwater quality in rural regions. There is an urgent need to address the worldwide issue of contaminated groundwater in these areas. It is crucially important because of the implications for people's well-being, progress, and the economy.
Sources agree that nitrogen (N) is crucial to the long-term success of farms (Ostad-Ali-Askari 2022b ;Delgado 2002;Shrestha and Ladah 2002). Extreme mobility and low sorption make nitrates a particularly troublesome form of nitrogen (Birkinshaw and Ewen 2000). Some of the human health and environmental consequences of groundwater nitrate contamination include esophageal, lymphatic, and stomach cancers; methemoglobinemia, or "blue baby" syndrome, in infants and pregnant women; and eutrophication across the hydrological system (Suthar et al. 2009;Panagopoulos et al. 2011;Stelzer and Scott 2018).
Agricultural activities are the primary cause of nitrate pollution. The long-term, unsustainable use of nitrogen 1 3 152 Page 2 of 15 fertilizers creates massive amounts of nitrate residues in soil, quickly seeping into groundwater. This is true whether chemical or organic fertilizers are used. Groundwater contamination by nitrates has thus become an important threat in agricultural planting regions (Jin et al. 2020). Anthropogenic causes of groundwater nitrate contamination are linked to industrial waste from food facilities, septic tanks, wastewater treatment plants, and livestock facilities (Hooda et al. 2002;Sahoo et al. 2016).
Groundwater is the primary source for agriculture and drinking in Algeria, which is a prominent climate change hotspot situated adjacent to the Mediterranean Sea. It is plagued by a shortage of water, excessive utilization of resources, coastal aquifer contamination due to elevated sea levels, and resource depletion, particularly in semi-arid regions. Furthermore, it is widely acknowledged that the pollution resulting from expanding agricultural activity poses a significant threat to groundwater quality.
The groundwater pollution index (GPI) and the nitrate pollution index (NPI) were created to help with this problem and make it easier to provide data (De Paula Filho et al. 2020;Zhang et al. 2020). Water pollution levels can be estimated using a single GP or NP index, which incorporates multiple water quality indicators. Therefore, one of the most pressing problems in numerous agricultural regions of Algeria is the need for this kind of study. Therefore, the rural sector of the Ain Lahdjar Plain in the Setif region was selected as the Beida-Bordj study area. By determining values for the groundwater pollution index (GPI) and the nitrate pollution index (NPI), this research aims to provide a rough assessment of the pollution level in the study area. In addition, NPI and GPI distribution maps were developed in this study to locate groundwater quality zones appropriate for specific applications. This approach can aid in managing semi-arid groundwater resources in developing nations with poor water monitoring infrastructure, such as the northeast of Algeria.

Defining the research site
Fifty-seven kilometers to the southeast of Setif lies the small community of Beida-Bordj. Batna bounds it to the east and south, Ain Azel to the west, and Ain Lahdjar and Tella to the north. The location can be identified by its geographical coordinates, specifically between latitudes 35° 45′ 37. 6′′ and 35° 56′ 14. 11′′ N and longitudes 5° 30′ 38. 6′′ and 5° 40′ 17. 2′′ E, as illustrated in Fig. 1.
The hypsometric curve for this area shows that the elevation varies from about 1.250 to about 900 m. The primary occupation of the majority of the populace, consisting of 35.276 individuals, is cereal cultivation, specifically of crops such as barley and maize. Beida-Bordj has a semi-arid climate (De-Martone index = 14.82), with an average annual temperature of 14.62 °C, an average yearly precipitation of 365 mm, and an average annual potential evapotranspiration of 795.95 mm. This year, there will be a severe deficit in the region's water balance of 467.68 mm.
An essential component of the complex geology of the Setif region is Beida-Bordj, which has undergone centuries of sedimentation and tectonic activity. According to several writers, sedimentary rocks from the Mesozoic and Cenozoic epochs predominate in the area (Kada 2022). Triassic salt deposits (gypsum, anhydrite, and halite) reflect the Mesozoic, while Jurassic rocks primarily comprise limestone, dolomite, and marl. According to Domzig (2007), the marl and limestone found in the Cretaceous (from the Barremian to the Cenomanian) alternate in layers. The Cenozoic Era spans the periods known as the Tertiary and Quaternary. Limestone, sandstone, and clays make up the Miocene formation. On the other hand, alluvial deposits of sand, clay, and gravel characterize the Quaternary. Hence, the geological terrains of Beida-Bordj are Triassic and Quaternary. Agricultural endeavors in Beida-Bordj that rely on groundwater resources for irrigation water supply have flourished, because alluvial formations dominate the region. The northeastern and southwestern parts of the study area have unique Triassic requirements. The majority of the material consists  Figure 1 summarizes the Eocene, Cretaceous, and Jurassic age formations that contain carbonate rocks (limestone and dolomites). Clays and conglomerates comprise the Miocene and Mio-Pliocene, whereas marl predominates in the Aptian.

Sampling
In May 2022, 111 water samples were taken from representative sites in the study area, ranging in depth from 150 to 200 m. The selected boreholes are put to use in farming and household activities. Figure 1 depicts the placement of sample bores. The groundwater sample procedure began after first pinpointing the precise latitude and longitude of each sampling spot using a Global Positioning System (GPS Garmin). The geographic coordinates have been transformed into UTM zone 31N coordinate space using the WGS 84 datum and the cylindrical projection coordinate system.

Laboratory analysis
After pumping for 10 min, we collected and stored groundwater samples in dry, clean, and sterilized 500 ml polyethylene bottles. The pieces were packaged, labeled, and shipped off to the lab. The samples were kept in an ice box at 4 °C until they were transported to the laboratory, where they were placed in a refrigerator until analysis the following day. Immediately following sampling, a hand-held instrument (HANNA HI 76/98195) was used to measure the temperature (T), electric conductivity (EC), and potential hydrogen (pH). Within 24 h of collection, lab technicians analyzed water samples using a flame spectrophotometer (Jenway Clinical PFP7) to identify chemical elements such as sodium and potassium. Volumetric titrations were used to analyze the concentrations of Ca 2+ , Mg 2+ , HCO 3 − , and Cl − ions; ion chromatography was used to probe for NO 3 − and SO 4 2− , and drying procedures were used to calculate for total dissolved solids (TDS) (Nollet 2007). Table 1 outlines the complete analysis process. Ion-balance error calculations were used to confirm the precision of the chemical analysis.
A cation-anion balancing computation was used to evaluate the precision of chemical analysis of groundwater samples, expecting that the sum of significant cations should equal the sum of major anions represented in meq/L. The term "ion balance errors" describes this phenomenon. Equation (1) can be used to determine the percentage error, commonly known as the IBE. According to Schwartz (1990), the ionic balance error (IBE) measured in the present investigation was found to be within the permissible range of 10%

Nitrate pollution index (NPI)
When it comes to groundwater quality, nitrate is one of the most important factors to consider .  Akakuru et al. (2023) highlight the importance of monitoring nitrate contamination and its impact on human health as a major global concern. In a study conducted by Muhib et al. (2023), modern agricultural practices, synthetic fertilizers, and more permeable soil were suggested as potential causes of an increase in nitrate concentration in groundwater.
Therefore, nitrate pollution in the examined wells was quantified using a single-parameter water quality index called the nitrate pollution index (NPI). Nitrate pollution in the groundwater, as measured by the NPI index, indicates human activity. To calculate the NPI (Eq. 2), the nitrate content in the sample, denoted by Cs, was used along with the anthropogenic source's threshold value, represented by HAV, and set at 20 mg/L (Obeida et al. 2012). The results of the NPI were used to divide the quality of the water supply into five groups (Table 3) (1) (2) NPI = Cs − HAV HAV . Groundwater pollution index (GPI) Subba Rao (2012) proposed the groundwater pollution index (GPI) method for evaluating the concentrations of many chemicals in water. Subba Rao's (2012) general method was utilized to calculate the GPI in this study. Based on its proportional influence on each chemical characteristic overall, each character is assigned a relative weight (RW) ranging from 1 to 5. The greatest RW "5" is allocated that naturally have the most impacts (NO 3 − , SO 4 2− , and Cl − ), while the lowest RW "1" is assigned to parameters that have the fewest effects (K + and HCO 3 -). Furthermore, RW "4" is allocated to pH, TDS, Na + , and TH, while RW "2" is assigned to Ca 2+ and Mg 2+ (Table 2).
(1) Each measurable chemical property is given a relative weight (RW) between 1 and 5 that reflects its relative importance in determining the overall characterization of the chemical. Parameters with the most negligible impact (K + and HCO 3 − ) are given the highest RW ("5"), while those with the most impact (NO 3 − , SO 4 2− , and Cl − ) are given the lowest RW ("1"). And finally, RW "4" is assigned to pH, TDS, Na + , and TH, while RW "2" is set to Ca 2+ and Mg 2+ (Table 2).
(2) Table 2 presents the weight parameter (WP), defined as the sum of all relative weights (RW) for all chemical water quality parameters. The WP is determined by the following equation using the formula: (3) The concentration status (SOC) can be determined with the use of the following formula: For each parameter in Table 1, C i n represents the concentration of the relevant chemical variable in the groundwater sample. DWQS represents the corresponding limit from the World Health Organization's drinking water quality standards for that parameter (WHO 2017).
(4) To determine the OQG of groundwater for human consumption, we apply Eq. (5) where WP represents the weight parameter and SOC represents the concentration status. (5) The OQG values are added together to derive the GPI (Eq. 6), which is then used to assess the impact of contaminants on groundwater quality Insignificant pollution (GPI 1.0), low pollution (GPI 1.5), moderate pollution (GPI 2.0), high pollution (GPI 2.5), and highly high pollution (GPI > 2.5) are the five categories Subba Rao (2012) uses to classify the GPI.

GIS analysis
GIS, a computer system for handling spatial data, is one of the most used approaches for evaluating water geochemical changes. Data can be collected, logged, processed, transformed, illustrated, searched, analyzed, modeled, and produced, all while indicating its location regarding geographical coordinates (latitude and longitude). Simplifying complex data is a crucial feature of GIS (Pande and Moharir 2018). To handle groundwater quality management and environmental issues, it combines them in a way that is easily understood by decision-makers (Ameur et al. 2016). Additionally, different thematic layers were plotted using the spatial analysis tool in ArcGis (version 10.5). The provided maps were made by generating geographic variation plots of NPI and GPI indices using the inverse distance weighted (IDW) approach. When a cell's output is calculated using IDW, it can only take on values inside the interval of the interpolated values. Since IDW is a weighted distance average, its output is always between the maximum and minimum inputs. Therefore, it can only make a ridge or a valley if it has already sampled those ends of the spectrum.

Irrigation evaluation factors
Soluble sodium percentage, residual sodium carbonate, permeability index, magnesium hazard, and Kelly ratio are some indicators used to define irrigation water quality.
(5) OQG = WP + SOC, Based on Eq. 1, where all particle fixations are given in meq/L, the Sodium Absorption Ratio (SAR) of water is an important metric used to evaluate the viability of groundwater for agricultural activities (Richards 1954) • The hazardous effects of sodium can also be evaluated by looking at the soluble sodium percentage (SSP). When all ion concentrations are given in meq/L (Wilcox 1955), the %Na value of SSP can be computed using Eq. 2 • The harmful impact of carbonate and bicarbonate on irrigation water quality has been measured using residual sodium carbonate (RSC). After the consumption of Ca 2+ and Mg 2+ , the residual reducing power (RSC) is determined as an expression of the remaining CO 3 2− and HCO 3 − concentration. Equation 3 from Eaton (Eaton 1950) was used to determine the RSC All the ion concentrations are in meq/L.
• The toxicity of sodium and the appropriateness of water for agricultural use were both calculated using the Permeability Index (PI). Doneen (1962) proposed the following equation to determine PI. Meq/L is used for all ion concentrations • Szabolcs and Darab (1964) propose using the following formula to determine the magnesium hazard (MH) in irrigation water • The KR method relies on Kelley's (1940)  (8) SSP = 100 × Na + K Ca + Mg + Na + K .
for the observed variability in the chemical composition of groundwater.

Chemical data
Geology, lithology, solution dynamics, aquifer flow patterns, and human activities all shape groundwater's chemical makeup. The results of the 111 physicochemical analyses performed on the groundwater samples are presented in Table 1.
As a key indicator of water quality, pH provides crucial data on different geochemical equilibrium states (Hem 1985). The samples' pH readings have been recorded at values between 6.9 and 8.51, with a mean of 7.56. All of the collected samples have pH values that are within the safe range established by the World Health Organization in 2017. The results show that only two samples have pH levels that are too high (WHO 2017). Almost all groundwater samples (98%) were found to be alkaline. All biochemical reactions are sensitive to variation in pH despite the fact that pH has no direct effect on human health.
The World Health Organization has set a limit of 500 mg/L (Table 1) for TDS in drinking water. Therefore, high TDS groundwater is unfit for consumption or irrigation. Only 5% of groundwater samples fell within the acceptable limit (500 mg/L), and the TDS concentration ranged from 342 to 7380 mg/L (Table 1). According to Freeze and Cherry (1979), the TDS values classified 58% of groundwater samples as fresh and 42% as brackish.
Groundwater's electrical conductivity is determined by the ionic concentration, ionic type, and water temperature (Hem 1985). An increase in TDS content results in an automatic rise in conductivity. Table 1 shows that the electrical conductivity (EC) of the water in the study area varies from 500 to 5800 µS/cm, on average being 1683.78 µS/cm. Samples with a higher conductivity were found to contain more of the sulfite and chloride found in Chott Frein.
Ca 2+ and Mg 2+ ion concentrations are commonly referred to as hardness. Water hardness (TH) was proposed to be identified as follows by Todd and Mays (2004) of several diseases such as kidney stones, hypertension, stroke, osteoporosis, and colorectal cancer (WHO 2011). Table 1 shows that calcium concentrations in the study area vary widely, from 18 to 840 mg/L, on average 139.75 mg/L. 70% of the samples have calcium concentrations higher than the 75 mg/L threshold recommended by the World Health Organization (2017). Therefore, calcite and dolomite are likely to blame for the increased concentration of calcium ions in the groundwater in this area.
Approximately half (49 samples) of the samples have magnesium concentrations in excess of the WHO standard (WHO 2017), which is set at 50 mg/L. The magnesium concentration in the groundwater samples ranges from 14 to 226 mg/L, with a mean of 63.41mg/L (Table 1). Na + is the most important nutrient, and having enough of it is crucial to good health. Na + causes convulsions, hypertension, and vomiting in humans at high enough concentrations (Elton et al. 1963). Table 1 displays the range of sodium concentrations found in the groundwater samples collected throughout the study area, averaging 134.83 mg/L. Therefore, nearly 16% of the samples tested had sodium concentrations higher than the recommended maximum (200 mg/L; WHO 2017).
Chloride concentrations in this study ranged from 20 to 3520 mg/L, with an average value of 261.62 mg/L (Table 1). About 47% of the samples fall outside the acceptable range, according to WHO recommendations (WHO 2017). Clis a tracer for groundwater contamination and an indicator of water pollution (Loizidou and Kapitanios 1993).
Groundwater samples from the research area had an average HCO 3 − ion concentration of 253.62 mg/L, with a range of 68-665 mg/L. The bicarbonate level in the study area is greater than the recommended amount (300 mg/L; WHO 2017) in nearly all of the samples tested. There are no ill effects associated with HCO 3 − (WHO 2011). Sulfate concentrations (SO 4 2− ) average 302.79 mg/L across a wide range of values between 50 and 1380 mg/L. The results show that roughly 50% of samples show values higher than expected (WHO 2017). Groundwater in this region is rich in sulfate due to the weathering of sulfur-containing minerals like gypsum, anhydrite from Sebkha and Chott, and sulfide minerals from the mining context (Kada and Demdoum 2020).
Nitrates and potassium have the lowest concentrations of cations and anions, respectively. Rainwater, weathering of the potash silicate group of minerals, and the use of potash fertilizer are the primary contributors of K + to groundwater (Singh et al. 2015). Potassium is essential to human health, but too much of it can have adverse effects on the health of those who already suffer from kidney disease or who have another medical condition. The average concentration of potassium (K + ) is 5.44 mg/L, with a range of 1-74 mg/L. Seven samples, or about 9%, show that the potassium concentration in the study area is too high relative to the recommended value (WHO 2017).
Nitrates' (NO 3 − ) concentrations are highly variable, spanning from 0 to 110 mg/L on average. A total of 33 samples, or nearly 30%, show a nitrates' concentration over the WHO 2017 threshold value. Most people in the area of study rely on agricultural activities for their livelihood, and their use of various fertilizers to increase crop yields may be contributing to the area's high nitrate levels.

Assessment of groundwater quality using NPI
Nitrate contamination is a form of water pollution that can be quantified using the Nitrate Contamination Index (NPI). In the area we looked at, NPI values ranged from -4.5 to -0.92 on average. Groundwater samples are classified in Table 2 according to NPI. Sample sites were classified as moderately contaminated (33.33%; 37 samples), lightly contaminated (30.63%; 33 samples), unpolluted (25.25%; 28 samples), considerably polluted (6.30%; 7 samples), or very significantly polluted (4.5%) ( Table 3).
It was found that the groundwater system in the Beida-Bordj area (Fig. 2) was the most vulnerable to nitrate pollution. Surface contaminants can be loaded more easily into the aquifer system due to the shallow groundwater depth, substantial net recharge, moderate surface slope, and high permeability of this region. Therefore, extraordinary measures are needed, such as switching to organic farming practices and adjusting when fertilizer is applied.

Assessment of groundwater using GPI
The GPI was developed to consolidate a wealth of physicochemical information into a single number that could be used to assess groundwater quality more comprehensively. Groundwater classification using GPI also aids in identifying the chemical suitability of drinking water. The average GPI was 1.2 out of a possible 7.0; the range was 0.42-6.3. These findings indicate that the groundwater in this study area can be classified into five different quality levels: very low, low, moderate, high, and very high pollution. 54.05% of groundwater samples were found to have "insignificant contamination," according to the GPI. Therefore, it has been determined that the groundwater in this area is suitable for human consumption. The percentage of groundwater samples with "low contamination" is approximately 25.22%, while the percentage with "moderate pollution" is approximately 11.71%. About 4.5% samples fall into the high and very high pollution ranges (Table 4). The groundwater in the examined area is only marginally drinkable, according to the GPI technique study. Groundwater  classifications evaluated using GPI methods are shown across the study area in Fig. 3.

Electrical conductivity (EC)
One of the most crucial characteristics for judging the quality of water intended for irrigation is its electrical conductivity (EC). The World Food and Agricultural Organisation (FAO) uses electrical conductivity values to categorize water into five classifications, ranging from "good" to "unsuitable" for irrigation (Ayers and Westcot 1985). Excellent water (250 µS/cm), good water (250-750 µS/cm), permissible water (750-2000 µS/cm), doubtful water (2000-3000 µS/cm), and unsuitable water (> 3000 µS/cm) are the five classifications. Table 5 shows that the water quality varies from "good" (71.6%) to "unsuitable" (11.1%) throughout the majority of the research region.

Sodium absorption ratio (SAR)
Since salt causes a decrease in soil permeability, it is essential to consider sodium concentration when assessing groundwater quality for irrigation. SAR is a valuable tool for highlighting the sodium risk of irrigation water, impacting its usefulness for agriculture (Al Obaidy et al. 2014). The SAR values for the groundwater samples in the research area vary from 1.13 to 21.95, with a mean of 5.82. According to research, water with an SAR value of less than 10 is ideal for irrigation purposes (Richard 1954). The results show that the quality of the water samples for irrigation ranges from "excellent" to "good" to "doubtful" (Table 5).

Soluble sodium percentage (SSP)
SSP was found to range from 7.32 to 51.35% among the groundwater samples in the research area, with a mean value of 22.18%. If the SSP is less than 20, the water is considered high quality for irrigation (Wilcox 1955). As a result, the quality of this groundwater for irrigation purposes is represented by all the samples (Table 5).

Residual sodium carbonate (RSC)
All groundwater samples have an RSC below zero, with computed values ranging from -0.18 to -24.47, on average -6.89. If the RSC value is less than 1.25, the water is considered suitable for irrigation (Eaton 1950). As seen in Table 5, all the water samples are of a high enough quality to be used for irrigation.

Permeability index (PI)
This study found a distribution of PI values from 12.76 to 53.37%, with a mean of 25.13%. According to the literature, water is unfit for irrigation if its PI value is less than 25% (Doneen1962). However, groundwater samples from the research area range from "good" to "unsuitable" for use in irrigation (Table 5).

Magnesium hazard (MH)
The levels of MH in the water samples taken from the research area ranged from 4.76 to 74.29%, on average coming in at 34.94%. According to reports, water is safe for irrigation if the MH value is less than 50 (Paliwal and Gandhi 1976). However, the groundwater samples collected during this study have a high suitability for irrigation (92.59%; Table 5).

Kelley ratio (KR)
The KR value should be less than one if the water is weak in Na + and can be used for irrigation (Kelley 1940). The KR for water samples taken in the research area is less than one in 99.76% of cases. The range was from 0.07 to 1.04, and the average was 0.29. In conclusion, groundwater samples from the study area can be used for irrigation (Table 5).

Hydrogeochemical facies and mechanism of controlling groundwater chemistry
Groundwater host rocks in an aquifer are classified according to their chemical composition using the term "hydrochemical facies". Geology, lithology, solution dynamics, aquifer flow patterns, and human activities all influence the chemical makeup of groundwater. A Piper diagram was used to characterize the study area's water type and find the dominant hydrochemical facies. The diagram has three separate fields, two of which are triangular and one diamond-shaped. Cations are shown as a single point on the left triangle, while anions are shown on the right triangle (Piper 1944). The water samples from the study area contained Ca-Mg-HCO3 (53%), Na-Cl (14%), Na-SO 4 (10%), Ca-Mg-SO 4 (11%), Na-HCO 3 (7%), and Ca-Cl (5%). The research area's groundwater is depicted in Fig. 4 according to its various water types.
The majority of the samples fall under the Ca-Mg-HCO 3 category, as the data show. Carbonate rocks of the Cretaceous epoch (Barremian-to-Cenomanian) dissolve into the study area's groundwater, bringing high concentrations of HCO 3 − , Ca 2+ , and Mg 2+ (Kada and Demdoum 2020). The effects of rock-water interaction, evaporation, and precipitation on water chemistry can be understood and differentiated using Gibbs (1970) graphs. It is proposed that Total Dissolved Solids (TDS) be plotted against Na + /(Na + + Ca 2+ ) for cations and Cl − /(Cl − + HCO 3 − ) for anions to gain a more accurate understanding of the essential processes that regulate the groundwater. Sixty-seven percent of the samples in the research region fall into the rock weathering zone, as shown in Fig. 5; this suggests that the chemical weathering of rock-forming minerals is the primary factor determining the water chemistry for these samples. This would result from the decomposition of minerals like carbonates. The evaporation zone encompasses roughly 33% of the samples collected in the research area. This would be because of the weather and the landscape. Due to the semi-arid climate and lack of human disturbance in the research area, groundwater evaporation is a regular occurrence. As a result, evaporation raises salinity by adding more sodium and chloride ions to the water, increasing the total dissolved solids.

Suggestions for lowering nitrate exposure and other preventative measures
Farmers in the study area must be educated about the benefits of using organic slow-release nitrogen fertilizers instead of conventional nitrogen-based fertilizers. This is why government and non-government organizations should launch such campaigns. The city's management and public works staff will implement changes to improve trash management and ensure that sewage is properly routed.

Conclusion
The quality of our groundwater is a crucial indicator of our collective progress and standard of living. It is a significant supply of water for household and agricultural uses across the country of Algeria. The current study aimed to examine the correlation between groundwater quality and both natural and anthropogenic sources of pollution. To better understand the hydrochemistry of groundwater in arid and semiarid regions around the world, this study and its approach are invaluable.
Between 500 and 5800 µS/cm, the EC can be found. TDS concentrations are all over the study area, averaging 1150.35 mg/L. The groundwater had a total hardness (TH) of 69-1066 (mean 203.16) mg/L, where TH is the combined concentration of Ca 2+ and Mg 2+ dissolved in CaCO3.
The Ca-Mg-HCO 3 water type is typical of the groundwater in the research area, which points to the breakdown of carbonate rocks from the Cretaceous. The NPI and GPI classification tools were used in this study to assess groundwater quality for drinking purposes in a rural region of Beida-Bordj in Setif, northeastern Algeria. According to the NPI method, 25.25% of the groundwater samples obtained in the research area within the analyzed region were appropriate for drinking, while the remaining were of low or inferior quality. However, the GPI approach revealed that 45% of the samples from the research region were classified as having insignificant pollution, while the remaining samples were unsafe for drinking. Most samples' "EC, SAR, SSP, MH, RSC, PI, and KR" values indicate that they are of high enough quality for irrigation purposes.
Overall, the study aids those who engage in water resource management, policymakers, and other management bodies by providing an up-to-date state of groundwater in the study region. To improve groundwater quality in the study area, researchers suggested using fully covered septic tanks, switching to natural fertilizers rather than synthetic ones, and installing proper sewage drainage systems.